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[ "While this issue may seem specific, it led to a silent problem in my workflow that took days to diagnose. If this feature is not intended to be supported, an error should be raised when encountering this configuration to prevent such issues.", "Thanks for reporting! This is a MRE:\r\n\r\n```python\r\nimport pyarrow as pa\r\nfrom datasets.table import cast_array_to_feature\r\nfrom datasets import Sequence, Value\r\ndata = [\r\n [[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]],\r\n [[7.0, 8.0, 9.0], [10.0, 11.0, 12.0]],\r\n]\r\narr = pa.array(data, pa.list_(pa.list_(pa.float32(), 3)))\r\ncast_array_to_feature(arr, Sequence(Sequence(Value(\"float32\"))))\r\n```\r\n\r\nI've opened a PR with a fix." ]

"2023-09-14T16:12:45Z"

"2023-09-14T16:15:53Z"

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[ "_The documentation is not available anymore as the PR was closed or merged._", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006753 / 0.011353 (-0.004600) | 0.004027 / 0.011008 (-0.006982) | 0.084200 / 0.038508 (0.045692) | 0.072233 / 0.023109 (0.049124) | 0.361535 / 0.275898 (0.085637) | 0.386196 / 0.323480 (0.062716) | 0.004047 / 0.007986 (-0.003939) | 0.003416 / 0.004328 (-0.000912) | 0.064724 / 0.004250 (0.060474) | 0.055740 / 0.037052 (0.018688) | 0.360422 / 0.258489 (0.101933) | 0.399230 / 0.293841 (0.105389) | 0.031537 / 0.128546 (-0.097009) | 0.008630 / 0.075646 (-0.067016) | 0.289652 / 0.419271 (-0.129620) | 0.052881 / 0.043533 (0.009348) | 0.359538 / 0.255139 (0.104399) | 0.379410 / 0.283200 (0.096211) | 0.024539 / 0.141683 (-0.117144) | 1.470891 / 1.452155 (0.018736) | 1.578879 / 1.492716 (0.086163) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.239200 / 0.018006 (0.221194) | 0.462100 / 0.000490 (0.461610) | 0.009055 / 0.000200 (0.008856) | 0.000406 / 0.000054 (0.000352) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.028736 / 0.037411 (-0.008675) | 0.088051 / 0.014526 (0.073525) | 0.098101 / 0.176557 (-0.078456) | 0.152399 / 0.737135 (-0.584737) | 0.098776 / 0.296338 (-0.197563) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.401761 / 0.215209 (0.186552) | 4.014143 / 2.077655 (1.936488) | 2.033255 / 1.504120 (0.529135) | 1.855347 / 1.541195 (0.314152) | 1.996144 / 1.468490 (0.527654) | 0.488545 / 4.584777 (-4.096232) | 3.712030 / 3.745712 (-0.033682) | 3.439725 / 5.269862 (-1.830137) | 2.119289 / 4.565676 (-2.446388) | 0.057523 / 0.424275 (-0.366752) | 0.007780 / 0.007607 (0.000173) | 0.479522 / 0.226044 (0.253477) | 4.798218 / 2.268929 (2.529290) | 2.543816 / 55.444624 (-52.900809) | 2.180392 / 6.876477 (-4.696085) | 2.427195 / 2.142072 (0.285122) | 0.602071 / 4.805227 (-4.203156) | 0.133450 / 6.500664 (-6.367214) | 0.061975 / 0.075469 (-0.013494) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.250040 / 1.841788 (-0.591748) | 19.532327 / 8.074308 (11.458019) | 14.200298 / 10.191392 (4.008906) | 0.165165 / 0.680424 (-0.515259) | 0.018326 / 0.534201 (-0.515875) | 0.389788 / 0.579283 (-0.189495) | 0.419301 / 0.434364 (-0.015063) | 0.452645 / 0.540337 (-0.087693) | 0.643409 / 1.386936 (-0.743527) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007040 / 0.011353 (-0.004313) | 0.004157 / 0.011008 (-0.006851) | 0.065439 / 0.038508 (0.026931) | 0.083210 / 0.023109 (0.060101) | 0.406707 / 0.275898 (0.130809) | 0.442759 / 0.323480 (0.119279) | 0.006321 / 0.007986 (-0.001665) | 0.003684 / 0.004328 (-0.000645) | 0.064517 / 0.004250 (0.060266) | 0.060676 / 0.037052 (0.023624) | 0.413395 / 0.258489 (0.154906) | 0.446776 / 0.293841 (0.152935) | 0.032542 / 0.128546 (-0.096004) | 0.008614 / 0.075646 (-0.067033) | 0.071760 / 0.419271 (-0.347511) | 0.049646 / 0.043533 (0.006113) | 0.402409 / 0.255139 (0.147270) | 0.422775 / 0.283200 (0.139575) | 0.024846 / 0.141683 (-0.116836) | 1.522915 / 1.452155 (0.070761) | 1.566518 / 1.492716 (0.073802) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.234478 / 0.018006 (0.216472) | 0.461318 / 0.000490 (0.460828) | 0.006304 / 0.000200 (0.006105) | 0.000105 / 0.000054 (0.000051) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.036904 / 0.037411 (-0.000508) | 0.102144 / 0.014526 (0.087619) | 0.108985 / 0.176557 (-0.067572) | 0.162609 / 0.737135 (-0.574526) | 0.110295 / 0.296338 (-0.186044) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.438735 / 0.215209 (0.223526) | 4.377602 / 2.077655 (2.299948) | 2.375305 / 1.504120 (0.871185) | 2.215877 / 1.541195 (0.674682) | 2.317468 / 1.468490 (0.848978) | 0.495137 / 4.584777 (-4.089640) | 3.726323 / 3.745712 (-0.019389) | 3.493785 / 5.269862 (-1.776077) | 2.177891 / 4.565676 (-2.387785) | 0.058975 / 0.424275 (-0.365300) | 0.007897 / 0.007607 (0.000290) | 0.514063 / 0.226044 (0.288019) | 5.132714 / 2.268929 (2.863786) | 2.914125 / 55.444624 (-52.530499) | 2.532912 / 6.876477 (-4.343564) | 2.776438 / 2.142072 (0.634365) | 0.624831 / 4.805227 (-4.180396) | 0.135023 / 6.500664 (-6.365641) | 0.062040 / 0.075469 (-0.013429) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.359970 / 1.841788 (-0.481818) | 20.816464 / 8.074308 (12.742156) | 16.103544 / 10.191392 (5.912152) | 0.149120 / 0.680424 (-0.531304) | 0.020279 / 0.534201 (-0.513922) | 0.408727 / 0.579283 (-0.170556) | 0.436191 / 0.434364 (0.001827) | 0.485056 / 0.540337 (-0.055281) | 0.737727 / 1.386936 (-0.649209) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#d15280f435b7e27c9350a0cc37a07dbc5e2ea9ca \"CML watermark\")\n", "CI failures are unrelated", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008102 / 0.011353 (-0.003251) | 0.004886 / 0.011008 (-0.006123) | 0.090482 / 0.038508 (0.051974) | 0.071594 / 0.023109 (0.048485) | 0.428678 / 0.275898 (0.152780) | 0.442179 / 0.323480 (0.118699) | 0.004329 / 0.007986 (-0.003657) | 0.003756 / 0.004328 (-0.000573) | 0.087125 / 0.004250 (0.082874) | 0.055159 / 0.037052 (0.018107) | 0.437646 / 0.258489 (0.179157) | 0.446665 / 0.293841 (0.152824) | 0.046402 / 0.128546 (-0.082145) | 0.014248 / 0.075646 (-0.061398) | 0.331401 / 0.419271 (-0.087871) | 0.062010 / 0.043533 (0.018478) | 0.434774 / 0.255139 (0.179635) | 0.441063 / 0.283200 (0.157863) | 0.037424 / 0.141683 (-0.104258) | 1.720276 / 1.452155 (0.268121) | 1.731491 / 1.492716 (0.238775) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.302935 / 0.018006 (0.284929) | 0.590556 / 0.000490 (0.590067) | 0.014473 / 0.000200 (0.014274) | 0.000712 / 0.000054 (0.000658) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.031289 / 0.037411 (-0.006122) | 0.091175 / 0.014526 (0.076649) | 0.112895 / 0.176557 (-0.063661) | 0.199558 / 0.737135 (-0.537577) | 0.113397 / 0.296338 (-0.182942) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.571586 / 0.215209 (0.356377) | 5.706894 / 2.077655 (3.629240) | 2.512701 / 1.504120 (1.008581) | 2.151705 / 1.541195 (0.610510) | 2.252738 / 1.468490 (0.784248) | 0.857524 / 4.584777 (-3.727253) | 5.189027 / 3.745712 (1.443315) | 4.464979 / 5.269862 (-0.804882) | 2.787486 / 4.565676 (-1.778190) | 0.090161 / 0.424275 (-0.334115) | 0.008649 / 0.007607 (0.001042) | 0.703367 / 0.226044 (0.477322) | 7.128971 / 2.268929 (4.860043) | 3.437475 / 55.444624 (-52.007149) | 2.562291 / 6.876477 (-4.314186) | 2.753419 / 2.142072 (0.611346) | 0.981964 / 4.805227 (-3.823263) | 0.194533 / 6.500664 (-6.306131) | 0.069659 / 0.075469 (-0.005810) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.510356 / 1.841788 (-0.331431) | 22.414117 / 8.074308 (14.339809) | 20.325418 / 10.191392 (10.134025) | 0.226823 / 0.680424 (-0.453601) | 0.029123 / 0.534201 (-0.505078) | 0.454656 / 0.579283 (-0.124627) | 0.559588 / 0.434364 (0.125224) | 0.547386 / 0.540337 (0.007048) | 0.770169 / 1.386936 (-0.616767) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.010167 / 0.011353 (-0.001186) | 0.005164 / 0.011008 (-0.005844) | 0.094897 / 0.038508 (0.056388) | 0.078027 / 0.023109 (0.054918) | 0.474442 / 0.275898 (0.198544) | 0.503362 / 0.323480 (0.179882) | 0.006988 / 0.007986 (-0.000998) | 0.005369 / 0.004328 (0.001041) | 0.079547 / 0.004250 (0.075297) | 0.059382 / 0.037052 (0.022329) | 0.468759 / 0.258489 (0.210270) | 0.566780 / 0.293841 (0.272939) | 0.050791 / 0.128546 (-0.077755) | 0.013191 / 0.075646 (-0.062455) | 0.086086 / 0.419271 (-0.333186) | 0.060399 / 0.043533 (0.016866) | 0.492985 / 0.255139 (0.237846) | 0.509139 / 0.283200 (0.225940) | 0.034537 / 0.141683 (-0.107146) | 1.699166 / 1.452155 (0.247011) | 1.789781 / 1.492716 (0.297065) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.278776 / 0.018006 (0.260769) | 0.615877 / 0.000490 (0.615387) | 0.009062 / 0.000200 (0.008862) | 0.000112 / 0.000054 (0.000057) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.032931 / 0.037411 (-0.004481) | 0.094796 / 0.014526 (0.080270) | 0.126697 / 0.176557 (-0.049859) | 0.168172 / 0.737135 (-0.568963) | 0.113906 / 0.296338 (-0.182433) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.602378 / 0.215209 (0.387169) | 5.987708 / 2.077655 (3.910054) | 2.800339 / 1.504120 (1.296219) | 2.474127 / 1.541195 (0.932932) | 2.502387 / 1.468490 (1.033897) | 0.808147 / 4.584777 (-3.776630) | 5.212691 / 3.745712 (1.466979) | 4.479452 / 5.269862 (-0.790409) | 2.831960 / 4.565676 (-1.733717) | 0.086777 / 0.424275 (-0.337498) | 0.009492 / 0.007607 (0.001885) | 0.716848 / 0.226044 (0.490803) | 7.099904 / 2.268929 (4.830975) | 3.794708 / 55.444624 (-51.649916) | 2.859826 / 6.876477 (-4.016650) | 3.109673 / 2.142072 (0.967600) | 0.936776 / 4.805227 (-3.868451) | 0.195152 / 6.500664 (-6.305512) | 0.074184 / 0.075469 (-0.001285) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.585419 / 1.841788 (-0.256369) | 22.420377 / 8.074308 (14.346068) | 20.761533 / 10.191392 (10.570141) | 0.228480 / 0.680424 (-0.451943) | 0.030944 / 0.534201 (-0.503257) | 0.444717 / 0.579283 (-0.134566) | 0.579632 / 0.434364 (0.145268) | 0.521669 / 0.540337 (-0.018669) | 0.748274 / 1.386936 (-0.638662) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#94e07965a400e6901f12e6f0f25c7090656c828c \"CML watermark\")\n" ]

"2023-09-14T12:06:32Z"

"2023-09-14T12:15:41Z"

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[ "What type of dataset are you using in this script? `torch.utils.data.Dataset` or `datasets.Dataset`? Please share the `datasets` package version if it's the latter. Otherwise, it's better to move this issue to the `accelerate` repo.", "Very sorry, I thought I had a repo in `accelerate!`\r\nI will close this issue and repo the issue in the appropriate place." ]

"2023-09-14T05:30:30Z"

"2023-09-14T23:54:42Z"

"2023-09-14T23:54:42Z"

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[ "I think this is the same issue as https://github.com/huggingface/datasets/issues/4776. Maybe installing `ffmpeg` can fix it:\r\n```python\r\nadd-apt-repository -y ppa:savoury1/ffmpeg4\r\napt-get -qq install -y ffmpeg\r\n```\r\n\r\nHowever, the best solution is to use a newer version of `datasets`. In the recent releases, we've replaced `torchaudio` with `soundfile`, which is easier to install and faster.", "@mariosasko \r\nThanks for your help" ]

"2023-09-13T22:30:01Z"

"2023-09-14T12:04:01Z"

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[ "`filter` treats the function's output as a (selection) mask - `True` keeps the sample, and `False` drops it. In your case, `bool(0)` evaluates to `False`, so dropping the first sample is the correct behavior.", "Oh gosh! 🤦 I totally misunderstood the API! My apologies!" ]

"2023-09-13T20:20:37Z"

"2023-09-14T11:59:16Z"

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[ "[This](https://huggingface.co/docs/datasets/nlp_process#map) is the most performant way to tokenize a dataset (`batched=True, num_proc=None, return_tensors=\"np\"`) \r\n\r\nIf`tokenizer.is_fast` returns `True`, `num_proc` must be `None/1` to benefit from the fast tokenizers' parallelism (the fast tokenizers are implemented in Rust, and Rust multi-threading doesn't work well with Python multi-processing)" ]

"2023-09-13T06:18:34Z"

"2023-09-13T18:04:47Z"

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[ "cc @Rocketknight1 ", "Hey! You can implement this yourself, just:\r\n\r\n1) Create the dataset with `to_tf_dataset()` with `shuffle=False`\r\n2) Add an `unbatch()` at the end (or use batch_size=1)\r\n3) Add a `shuffle()` to the resulting dataset with your desired buffer size\r\n4) Add a `batch()` at the end again to re-batch your dataset.\r\n\r\nNote that the way we construct datasets in `to_tf_dataset()`, we don't actually shuffle the entire dataset in-memory, using `tf.data.Dataset.shuffle()`! Instead, we shuffle an index array and then load from the dataset with that. This means that shuffling with `tf.data.Dataset.shuffle()` will probably be slower and use more memory than our approach - I don't think adding the option for smaller shuffle buffers will actually save you memory on this!", "Thanks for your reply! @Rocketknight1 \r\n\"We don't actually shuffle the entire dataset in-memory, using tf.data.Dataset.shuffle()! Instead, we shuffle an index array and then load from the dataset with that.\"\r\nIn such case, there will be random access to dataset data during shuffling. When the dataset is large, the performance can be X10 times slow. I have tried many ways with to_tf_dataset() trying to achieve comparable performance with tf.data.Dataset().shuffle(buffer_size).batch(). But the performance with to_tf_dataset() is still slow. \r\n" ]

"2023-09-13T03:19:44Z"

"2023-09-14T17:14:01Z"

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"2023-09-12T21:51:08Z"

"2023-09-12T21:51:08Z"

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[ "_The documentation is not available anymore as the PR was closed or merged._", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008370 / 0.011353 (-0.002983) | 0.004674 / 0.011008 (-0.006334) | 0.103912 / 0.038508 (0.065404) | 0.101668 / 0.023109 (0.078559) | 0.417945 / 0.275898 (0.142047) | 0.454805 / 0.323480 (0.131325) | 0.004763 / 0.007986 (-0.003223) | 0.003934 / 0.004328 (-0.000394) | 0.078446 / 0.004250 (0.074196) | 0.068383 / 0.037052 (0.031331) | 0.415100 / 0.258489 (0.156611) | 0.475272 / 0.293841 (0.181431) | 0.036884 / 0.128546 (-0.091662) | 0.010097 / 0.075646 (-0.065549) | 0.354962 / 0.419271 (-0.064309) | 0.062688 / 0.043533 (0.019155) | 0.420643 / 0.255139 (0.165504) | 0.446504 / 0.283200 (0.163304) | 0.029075 / 0.141683 (-0.112608) | 1.791517 / 1.452155 (0.339363) | 1.859820 / 1.492716 (0.367104) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.246929 / 0.018006 (0.228923) | 0.519593 / 0.000490 (0.519103) | 0.006848 / 0.000200 (0.006648) | 0.000168 / 0.000054 (0.000114) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.035179 / 0.037411 (-0.002232) | 0.115582 / 0.014526 (0.101057) | 0.128235 / 0.176557 (-0.048321) | 0.187123 / 0.737135 (-0.550012) | 0.120862 / 0.296338 (-0.175477) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.463406 / 0.215209 (0.248197) | 4.615517 / 2.077655 (2.537863) | 2.250513 / 1.504120 (0.746393) | 2.061226 / 1.541195 (0.520032) | 2.189938 / 1.468490 (0.721448) | 0.582984 / 4.584777 (-4.001793) | 4.299464 / 3.745712 (0.553751) | 4.037274 / 5.269862 (-1.232588) | 2.608967 / 4.565676 (-1.956710) | 0.068944 / 0.424275 (-0.355331) | 0.009501 / 0.007607 (0.001894) | 0.567436 / 0.226044 (0.341392) | 5.662738 / 2.268929 (3.393809) | 2.849094 / 55.444624 (-52.595530) | 2.461013 / 6.876477 (-4.415464) | 2.663245 / 2.142072 (0.521172) | 0.704528 / 4.805227 (-4.100699) | 0.163583 / 6.500664 (-6.337081) | 0.075719 / 0.075469 (0.000250) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.604743 / 1.841788 (-0.237044) | 24.512054 / 8.074308 (16.437746) | 17.870939 / 10.191392 (7.679547) | 0.199188 / 0.680424 (-0.481236) | 0.023820 / 0.534201 (-0.510381) | 0.487520 / 0.579283 (-0.091763) | 0.512543 / 0.434364 (0.078179) | 0.575138 / 0.540337 (0.034801) | 0.759863 / 1.386936 (-0.627073) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.010516 / 0.011353 (-0.000837) | 0.004779 / 0.011008 (-0.006229) | 0.078482 / 0.038508 (0.039974) | 0.108533 / 0.023109 (0.085424) | 0.498692 / 0.275898 (0.222794) | 0.534698 / 0.323480 (0.211218) | 0.007624 / 0.007986 (-0.000362) | 0.003938 / 0.004328 (-0.000391) | 0.077317 / 0.004250 (0.073067) | 0.078056 / 0.037052 (0.041004) | 0.493648 / 0.258489 (0.235159) | 0.540891 / 0.293841 (0.247050) | 0.040377 / 0.128546 (-0.088169) | 0.010155 / 0.075646 (-0.065491) | 0.084384 / 0.419271 (-0.334888) | 0.061419 / 0.043533 (0.017886) | 0.494474 / 0.255139 (0.239335) | 0.524656 / 0.283200 (0.241456) | 0.029052 / 0.141683 (-0.112631) | 1.794584 / 1.452155 (0.342429) | 1.939987 / 1.492716 (0.447270) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.377404 / 0.018006 (0.359398) | 0.516562 / 0.000490 (0.516072) | 0.109555 / 0.000200 (0.109356) | 0.001126 / 0.000054 (0.001071) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.039793 / 0.037411 (0.002382) | 0.123001 / 0.014526 (0.108475) | 0.127536 / 0.176557 (-0.049021) | 0.191681 / 0.737135 (-0.545455) | 0.128590 / 0.296338 (-0.167748) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.513689 / 0.215209 (0.298480) | 5.135114 / 2.077655 (3.057459) | 2.797885 / 1.504120 (1.293765) | 2.715332 / 1.541195 (1.174137) | 2.746437 / 1.468490 (1.277947) | 0.596480 / 4.584777 (-3.988297) | 4.382013 / 3.745712 (0.636301) | 3.965956 / 5.269862 (-1.303906) | 2.545206 / 4.565676 (-2.020471) | 0.069620 / 0.424275 (-0.354655) | 0.009321 / 0.007607 (0.001714) | 0.612424 / 0.226044 (0.386379) | 6.107037 / 2.268929 (3.838109) | 3.447246 / 55.444624 (-51.997379) | 3.073262 / 6.876477 (-3.803215) | 3.280185 / 2.142072 (1.138113) | 0.704776 / 4.805227 (-4.100451) | 0.160488 / 6.500664 (-6.340176) | 0.075730 / 0.075469 (0.000261) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.697035 / 1.841788 (-0.144753) | 24.766118 / 8.074308 (16.691809) | 18.476699 / 10.191392 (8.285307) | 0.176594 / 0.680424 (-0.503830) | 0.024249 / 0.534201 (-0.509952) | 0.478743 / 0.579283 (-0.100541) | 0.518774 / 0.434364 (0.084410) | 0.581498 / 0.540337 (0.041161) | 0.797784 / 1.386936 (-0.589152) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#722cea0f4929ff4ffcdbb7ca6b72cba229b9701a \"CML watermark\")\n" ]

"2023-09-12T06:53:06Z"

"2023-09-13T18:20:50Z"

"2023-09-13T18:10:04Z"

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[ "_The documentation is not available anymore as the PR was closed or merged._", "CI errors are unrelated", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006681 / 0.011353 (-0.004672) | 0.004132 / 0.011008 (-0.006876) | 0.085045 / 0.038508 (0.046536) | 0.077680 / 0.023109 (0.054571) | 0.382042 / 0.275898 (0.106144) | 0.412932 / 0.323480 (0.089452) | 0.005339 / 0.007986 (-0.002646) | 0.003408 / 0.004328 (-0.000921) | 0.065280 / 0.004250 (0.061030) | 0.055732 / 0.037052 (0.018680) | 0.400231 / 0.258489 (0.141742) | 0.432497 / 0.293841 (0.138656) | 0.031532 / 0.128546 (-0.097014) | 0.008721 / 0.075646 (-0.066925) | 0.289612 / 0.419271 (-0.129660) | 0.053089 / 0.043533 (0.009556) | 0.383300 / 0.255139 (0.128161) | 0.401204 / 0.283200 (0.118004) | 0.023582 / 0.141683 (-0.118100) | 1.493854 / 1.452155 (0.041699) | 1.583497 / 1.492716 (0.090781) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.239163 / 0.018006 (0.221157) | 0.469555 / 0.000490 (0.469065) | 0.008325 / 0.000200 (0.008125) | 0.000113 / 0.000054 (0.000059) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.028975 / 0.037411 (-0.008436) | 0.084195 / 0.014526 (0.069669) | 0.189394 / 0.176557 (0.012837) | 0.158010 / 0.737135 (-0.579125) | 0.097502 / 0.296338 (-0.198837) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.383085 / 0.215209 (0.167876) | 3.827030 / 2.077655 (1.749375) | 1.872279 / 1.504120 (0.368159) | 1.705808 / 1.541195 (0.164613) | 1.833706 / 1.468490 (0.365216) | 0.484744 / 4.584777 (-4.100033) | 3.658221 / 3.745712 (-0.087491) | 3.398462 / 5.269862 (-1.871399) | 2.064974 / 4.565676 (-2.500703) | 0.057740 / 0.424275 (-0.366535) | 0.007926 / 0.007607 (0.000319) | 0.465358 / 0.226044 (0.239314) | 4.652951 / 2.268929 (2.384022) | 2.328390 / 55.444624 (-53.116235) | 2.000606 / 6.876477 (-4.875870) | 2.268391 / 2.142072 (0.126318) | 0.586537 / 4.805227 (-4.218690) | 0.134749 / 6.500664 (-6.365915) | 0.061276 / 0.075469 (-0.014193) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.337913 / 1.841788 (-0.503875) | 20.232122 / 8.074308 (12.157814) | 14.478579 / 10.191392 (4.287187) | 0.167545 / 0.680424 (-0.512878) | 0.018745 / 0.534201 (-0.515456) | 0.401209 / 0.579283 (-0.178074) | 0.425748 / 0.434364 (-0.008616) | 0.462539 / 0.540337 (-0.077798) | 0.652446 / 1.386936 (-0.734490) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007159 / 0.011353 (-0.004194) | 0.004091 / 0.011008 (-0.006917) | 0.066202 / 0.038508 (0.027694) | 0.083096 / 0.023109 (0.059987) | 0.402160 / 0.275898 (0.126261) | 0.440565 / 0.323480 (0.117085) | 0.005757 / 0.007986 (-0.002228) | 0.003445 / 0.004328 (-0.000884) | 0.065498 / 0.004250 (0.061248) | 0.059787 / 0.037052 (0.022735) | 0.407017 / 0.258489 (0.148528) | 0.448270 / 0.293841 (0.154429) | 0.033606 / 0.128546 (-0.094941) | 0.008744 / 0.075646 (-0.066902) | 0.072902 / 0.419271 (-0.346369) | 0.050144 / 0.043533 (0.006611) | 0.401069 / 0.255139 (0.145930) | 0.426389 / 0.283200 (0.143189) | 0.023297 / 0.141683 (-0.118386) | 1.506152 / 1.452155 (0.053998) | 1.570211 / 1.492716 (0.077495) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.235759 / 0.018006 (0.217753) | 0.488410 / 0.000490 (0.487921) | 0.004587 / 0.000200 (0.004387) | 0.000115 / 0.000054 (0.000060) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.034123 / 0.037411 (-0.003289) | 0.102163 / 0.014526 (0.087638) | 0.110892 / 0.176557 (-0.065664) | 0.166000 / 0.737135 (-0.571135) | 0.110845 / 0.296338 (-0.185494) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.431397 / 0.215209 (0.216188) | 4.291540 / 2.077655 (2.213885) | 2.298248 / 1.504120 (0.794128) | 2.134752 / 1.541195 (0.593557) | 2.207913 / 1.468490 (0.739423) | 0.490607 / 4.584777 (-4.094170) | 3.683078 / 3.745712 (-0.062635) | 3.314266 / 5.269862 (-1.955596) | 2.059488 / 4.565676 (-2.506188) | 0.057876 / 0.424275 (-0.366399) | 0.007696 / 0.007607 (0.000089) | 0.512186 / 0.226044 (0.286142) | 5.124071 / 2.268929 (2.855142) | 2.803913 / 55.444624 (-52.640711) | 2.428558 / 6.876477 (-4.447919) | 2.655207 / 2.142072 (0.513135) | 0.584589 / 4.805227 (-4.220638) | 0.133518 / 6.500664 (-6.367146) | 0.060729 / 0.075469 (-0.014740) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.352916 / 1.841788 (-0.488872) | 20.249632 / 8.074308 (12.175323) | 15.283079 / 10.191392 (5.091686) | 0.157601 / 0.680424 (-0.522823) | 0.019650 / 0.534201 (-0.514551) | 0.396398 / 0.579283 (-0.182885) | 0.430111 / 0.434364 (-0.004252) | 0.480627 / 0.540337 (-0.059710) | 0.642165 / 1.386936 (-0.744771) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#9b21e181b642bd55b3ef68c1948bfbcd388136d6 \"CML watermark\")\n" ]

"2023-09-11T19:11:58Z"

"2023-09-13T22:17:39Z"

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6231). All of your documentation changes will be reflected on that endpoint." ]

"2023-09-11T16:27:09Z"

"2023-09-12T15:23:15Z"

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[ "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.005894 / 0.011353 (-0.005459) | 0.003621 / 0.011008 (-0.007387) | 0.080446 / 0.038508 (0.041938) | 0.056800 / 0.023109 (0.033691) | 0.326485 / 0.275898 (0.050587) | 0.376207 / 0.323480 (0.052727) | 0.004640 / 0.007986 (-0.003346) | 0.002795 / 0.004328 (-0.001533) | 0.062815 / 0.004250 (0.058565) | 0.045761 / 0.037052 (0.008709) | 0.341417 / 0.258489 (0.082928) | 0.373129 / 0.293841 (0.079288) | 0.027226 / 0.128546 (-0.101321) | 0.007873 / 0.075646 (-0.067774) | 0.261737 / 0.419271 (-0.157535) | 0.044648 / 0.043533 (0.001115) | 0.320195 / 0.255139 (0.065056) | 0.381892 / 0.283200 (0.098692) | 0.020431 / 0.141683 (-0.121252) | 1.405332 / 1.452155 (-0.046823) | 1.455592 / 1.492716 (-0.037125) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.191539 / 0.018006 (0.173533) | 0.423655 / 0.000490 (0.423165) | 0.002741 / 0.000200 (0.002541) | 0.000069 / 0.000054 (0.000014) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.023952 / 0.037411 (-0.013459) | 0.073387 / 0.014526 (0.058861) | 0.083746 / 0.176557 (-0.092810) | 0.144977 / 0.737135 (-0.592159) | 0.083808 / 0.296338 (-0.212530) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.436228 / 0.215209 (0.221019) | 4.370510 / 2.077655 (2.292855) | 2.340426 / 1.504120 (0.836306) | 2.202215 / 1.541195 (0.661021) | 2.258528 / 1.468490 (0.790037) | 0.503455 / 4.584777 (-4.081322) | 3.043695 / 3.745712 (-0.702017) | 2.784033 / 5.269862 (-2.485829) | 1.847956 / 4.565676 (-2.717721) | 0.057702 / 0.424275 (-0.366573) | 0.006703 / 0.007607 (-0.000904) | 0.510628 / 0.226044 (0.284583) | 5.101890 / 2.268929 (2.832961) | 2.816469 / 55.444624 (-52.628155) | 2.474220 / 6.876477 (-4.402257) | 2.617851 / 2.142072 (0.475779) | 0.593585 / 4.805227 (-4.211642) | 0.125895 / 6.500664 (-6.374769) | 0.062170 / 0.075469 (-0.013299) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.238792 / 1.841788 (-0.602996) | 18.096417 / 8.074308 (10.022108) | 13.548778 / 10.191392 (3.357386) | 0.144878 / 0.680424 (-0.535546) | 0.016644 / 0.534201 (-0.517557) | 0.334556 / 0.579283 (-0.244728) | 0.343680 / 0.434364 (-0.090684) | 0.383093 / 0.540337 (-0.157244) | 0.525075 / 1.386936 (-0.861861) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006125 / 0.011353 (-0.005228) | 0.003668 / 0.011008 (-0.007340) | 0.062650 / 0.038508 (0.024142) | 0.058882 / 0.023109 (0.035772) | 0.454643 / 0.275898 (0.178745) | 0.486659 / 0.323480 (0.163179) | 0.005558 / 0.007986 (-0.002427) | 0.002858 / 0.004328 (-0.001471) | 0.062603 / 0.004250 (0.058353) | 0.049701 / 0.037052 (0.012649) | 0.455903 / 0.258489 (0.197413) | 0.491544 / 0.293841 (0.197703) | 0.028581 / 0.128546 (-0.099965) | 0.008040 / 0.075646 (-0.067607) | 0.068314 / 0.419271 (-0.350957) | 0.040637 / 0.043533 (-0.002896) | 0.450288 / 0.255139 (0.195149) | 0.476330 / 0.283200 (0.193131) | 0.018989 / 0.141683 (-0.122693) | 1.455122 / 1.452155 (0.002967) | 1.496941 / 1.492716 (0.004225) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.227382 / 0.018006 (0.209376) | 0.432637 / 0.000490 (0.432147) | 0.002727 / 0.000200 (0.002527) | 0.000073 / 0.000054 (0.000019) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.026125 / 0.037411 (-0.011286) | 0.081342 / 0.014526 (0.066817) | 0.091227 / 0.176557 (-0.085329) | 0.145175 / 0.737135 (-0.591960) | 0.091988 / 0.296338 (-0.204351) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.454293 / 0.215209 (0.239083) | 4.537912 / 2.077655 (2.460257) | 2.489146 / 1.504120 (0.985026) | 2.307166 / 1.541195 (0.765971) | 2.380866 / 1.468490 (0.912376) | 0.509015 / 4.584777 (-4.075762) | 3.111069 / 3.745712 (-0.634644) | 2.839181 / 5.269862 (-2.430681) | 1.874630 / 4.565676 (-2.691047) | 0.058540 / 0.424275 (-0.365735) | 0.006693 / 0.007607 (-0.000914) | 0.528408 / 0.226044 (0.302363) | 5.285802 / 2.268929 (3.016874) | 2.952090 / 55.444624 (-52.492534) | 2.591496 / 6.876477 (-4.284980) | 2.741080 / 2.142072 (0.599007) | 0.595610 / 4.805227 (-4.209617) | 0.124387 / 6.500664 (-6.376277) | 0.061032 / 0.075469 (-0.014437) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.365816 / 1.841788 (-0.475972) | 18.684534 / 8.074308 (10.610226) | 14.540438 / 10.191392 (4.349046) | 0.146793 / 0.680424 (-0.533631) | 0.018165 / 0.534201 (-0.516036) | 0.333794 / 0.579283 (-0.245489) | 0.345533 / 0.434364 (-0.088830) | 0.384453 / 0.540337 (-0.155885) | 0.529104 / 1.386936 (-0.857832) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#6c884967dd5f4e8aa3d1f3c2e3a414ae53afe261 \"CML watermark\")\n", "_The documentation is not available anymore as the PR was closed or merged._", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006121 / 0.011353 (-0.005232) | 0.003683 / 0.011008 (-0.007325) | 0.083329 / 0.038508 (0.044821) | 0.063350 / 0.023109 (0.040241) | 0.329959 / 0.275898 (0.054061) | 0.396111 / 0.323480 (0.072631) | 0.003554 / 0.007986 (-0.004432) | 0.002907 / 0.004328 (-0.001421) | 0.064152 / 0.004250 (0.059902) | 0.049182 / 0.037052 (0.012130) | 0.343862 / 0.258489 (0.085373) | 0.414568 / 0.293841 (0.120727) | 0.027157 / 0.128546 (-0.101389) | 0.007957 / 0.075646 (-0.067689) | 0.261868 / 0.419271 (-0.157404) | 0.044938 / 0.043533 (0.001405) | 0.318470 / 0.255139 (0.063331) | 0.393319 / 0.283200 (0.110119) | 0.022848 / 0.141683 (-0.118835) | 1.419916 / 1.452155 (-0.032238) | 1.508783 / 1.492716 (0.016067) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.200530 / 0.018006 (0.182523) | 0.433586 / 0.000490 (0.433097) | 0.002063 / 0.000200 (0.001863) | 0.000070 / 0.000054 (0.000016) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.024803 / 0.037411 (-0.012609) | 0.075894 / 0.014526 (0.061368) | 0.086488 / 0.176557 (-0.090069) | 0.149058 / 0.737135 (-0.588077) | 0.087046 / 0.296338 (-0.209292) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.390771 / 0.215209 (0.175562) | 3.886178 / 2.077655 (1.808523) | 1.868626 / 1.504120 (0.364506) | 1.708532 / 1.541195 (0.167338) | 1.788491 / 1.468490 (0.320001) | 0.505706 / 4.584777 (-4.079071) | 3.062094 / 3.745712 (-0.683618) | 2.898559 / 5.269862 (-2.371302) | 1.901225 / 4.565676 (-2.664452) | 0.058366 / 0.424275 (-0.365909) | 0.006851 / 0.007607 (-0.000756) | 0.465382 / 0.226044 (0.239337) | 4.650187 / 2.268929 (2.381258) | 2.316152 / 55.444624 (-53.128472) | 1.989597 / 6.876477 (-4.886879) | 2.169266 / 2.142072 (0.027194) | 0.593257 / 4.805227 (-4.211970) | 0.126440 / 6.500664 (-6.374224) | 0.062227 / 0.075469 (-0.013242) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.283591 / 1.841788 (-0.558197) | 18.384667 / 8.074308 (10.310358) | 14.079611 / 10.191392 (3.888219) | 0.150453 / 0.680424 (-0.529971) | 0.017100 / 0.534201 (-0.517101) | 0.330503 / 0.579283 (-0.248780) | 0.348134 / 0.434364 (-0.086230) | 0.385726 / 0.540337 (-0.154612) | 0.529147 / 1.386936 (-0.857789) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006168 / 0.011353 (-0.005185) | 0.003801 / 0.011008 (-0.007208) | 0.063168 / 0.038508 (0.024660) | 0.062331 / 0.023109 (0.039221) | 0.448321 / 0.275898 (0.172423) | 0.484416 / 0.323480 (0.160937) | 0.004827 / 0.007986 (-0.003159) | 0.002848 / 0.004328 (-0.001480) | 0.062736 / 0.004250 (0.058486) | 0.049128 / 0.037052 (0.012075) | 0.449276 / 0.258489 (0.190787) | 0.499035 / 0.293841 (0.205194) | 0.028577 / 0.128546 (-0.099969) | 0.008114 / 0.075646 (-0.067532) | 0.068297 / 0.419271 (-0.350974) | 0.040835 / 0.043533 (-0.002698) | 0.453556 / 0.255139 (0.198417) | 0.475420 / 0.283200 (0.192220) | 0.020292 / 0.141683 (-0.121390) | 1.472226 / 1.452155 (0.020071) | 1.523809 / 1.492716 (0.031093) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.230662 / 0.018006 (0.212655) | 0.439697 / 0.000490 (0.439207) | 0.009899 / 0.000200 (0.009699) | 0.000087 / 0.000054 (0.000033) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.026418 / 0.037411 (-0.010993) | 0.082188 / 0.014526 (0.067662) | 0.091039 / 0.176557 (-0.085518) | 0.146646 / 0.737135 (-0.590489) | 0.091693 / 0.296338 (-0.204645) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.462086 / 0.215209 (0.246877) | 4.620925 / 2.077655 (2.543271) | 2.539234 / 1.504120 (1.035114) | 2.371178 / 1.541195 (0.829983) | 2.440538 / 1.468490 (0.972048) | 0.511047 / 4.584777 (-4.073730) | 3.082088 / 3.745712 (-0.663624) | 2.918162 / 5.269862 (-2.351700) | 1.899651 / 4.565676 (-2.666025) | 0.059003 / 0.424275 (-0.365272) | 0.006746 / 0.007607 (-0.000861) | 0.537863 / 0.226044 (0.311819) | 5.382355 / 2.268929 (3.113426) | 3.060091 / 55.444624 (-52.384534) | 2.754969 / 6.876477 (-4.121507) | 2.863156 / 2.142072 (0.721084) | 0.606888 / 4.805227 (-4.198339) | 0.127448 / 6.500664 (-6.373216) | 0.062975 / 0.075469 (-0.012494) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.336065 / 1.841788 (-0.505722) | 19.019902 / 8.074308 (10.945594) | 15.057979 / 10.191392 (4.866587) | 0.160646 / 0.680424 (-0.519778) | 0.018340 / 0.534201 (-0.515861) | 0.341664 / 0.579283 (-0.237619) | 0.356536 / 0.434364 (-0.077828) | 0.393974 / 0.540337 (-0.146363) | 0.546036 / 1.386936 (-0.840900) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#fd04e445bd36d7eb4af4d5a6b8519ab8e306ecf5 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007220 / 0.011353 (-0.004132) | 0.004537 / 0.011008 (-0.006471) | 0.087333 / 0.038508 (0.048825) | 0.095637 / 0.023109 (0.072528) | 0.323819 / 0.275898 (0.047921) | 0.358838 / 0.323480 (0.035358) | 0.005910 / 0.007986 (-0.002076) | 0.003781 / 0.004328 (-0.000548) | 0.064565 / 0.004250 (0.060315) | 0.062818 / 0.037052 (0.025766) | 0.322595 / 0.258489 (0.064106) | 0.371865 / 0.293841 (0.078024) | 0.031667 / 0.128546 (-0.096880) | 0.009068 / 0.075646 (-0.066579) | 0.290574 / 0.419271 (-0.128697) | 0.054618 / 0.043533 (0.011085) | 0.314708 / 0.255139 (0.059569) | 0.336647 / 0.283200 (0.053447) | 0.027070 / 0.141683 (-0.114613) | 1.500640 / 1.452155 (0.048485) | 1.586775 / 1.492716 (0.094059) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.294461 / 0.018006 (0.276455) | 0.580125 / 0.000490 (0.579635) | 0.008165 / 0.000200 (0.007965) | 0.000320 / 0.000054 (0.000266) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.032352 / 0.037411 (-0.005059) | 0.092187 / 0.014526 (0.077661) | 0.104993 / 0.176557 (-0.071564) | 0.162738 / 0.737135 (-0.574397) | 0.103242 / 0.296338 (-0.193096) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.396732 / 0.215209 (0.181523) | 3.955049 / 2.077655 (1.877394) | 1.876762 / 1.504120 (0.372642) | 1.698477 / 1.541195 (0.157282) | 1.847086 / 1.468490 (0.378596) | 0.488306 / 4.584777 (-4.096471) | 3.658922 / 3.745712 (-0.086790) | 3.559050 / 5.269862 (-1.710812) | 2.187363 / 4.565676 (-2.378313) | 0.059795 / 0.424275 (-0.364480) | 0.008966 / 0.007607 (0.001359) | 0.474212 / 0.226044 (0.248168) | 4.732540 / 2.268929 (2.463611) | 2.466370 / 55.444624 (-52.978254) | 2.112105 / 6.876477 (-4.764372) | 2.414624 / 2.142072 (0.272552) | 0.595447 / 4.805227 (-4.209780) | 0.136705 / 6.500664 (-6.363959) | 0.062267 / 0.075469 (-0.013202) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.266518 / 1.841788 (-0.575270) | 21.009975 / 8.074308 (12.935666) | 14.823960 / 10.191392 (4.632568) | 0.165630 / 0.680424 (-0.514793) | 0.018499 / 0.534201 (-0.515702) | 0.396720 / 0.579283 (-0.182563) | 0.424807 / 0.434364 (-0.009557) | 0.463326 / 0.540337 (-0.077011) | 0.653132 / 1.386936 (-0.733804) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007789 / 0.011353 (-0.003564) | 0.004720 / 0.011008 (-0.006288) | 0.066656 / 0.038508 (0.028148) | 0.094219 / 0.023109 (0.071109) | 0.414965 / 0.275898 (0.139067) | 0.454808 / 0.323480 (0.131328) | 0.006088 / 0.007986 (-0.001898) | 0.003980 / 0.004328 (-0.000349) | 0.066048 / 0.004250 (0.061797) | 0.065875 / 0.037052 (0.028823) | 0.419994 / 0.258489 (0.161505) | 0.462001 / 0.293841 (0.168160) | 0.033534 / 0.128546 (-0.095013) | 0.009010 / 0.075646 (-0.066636) | 0.072778 / 0.419271 (-0.346493) | 0.049834 / 0.043533 (0.006301) | 0.411003 / 0.255139 (0.155864) | 0.430918 / 0.283200 (0.147718) | 0.025664 / 0.141683 (-0.116019) | 1.526771 / 1.452155 (0.074616) | 1.634767 / 1.492716 (0.142051) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.271180 / 0.018006 (0.253174) | 0.576704 / 0.000490 (0.576214) | 0.004362 / 0.000200 (0.004162) | 0.000112 / 0.000054 (0.000058) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.035648 / 0.037411 (-0.001763) | 0.102407 / 0.014526 (0.087881) | 0.111613 / 0.176557 (-0.064944) | 0.166173 / 0.737135 (-0.570962) | 0.113371 / 0.296338 (-0.182967) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.436031 / 0.215209 (0.220822) | 4.347071 / 2.077655 (2.269416) | 2.366937 / 1.504120 (0.862817) | 2.216356 / 1.541195 (0.675161) | 2.335933 / 1.468490 (0.867443) | 0.490484 / 4.584777 (-4.094293) | 3.730656 / 3.745712 (-0.015056) | 3.497248 / 5.269862 (-1.772613) | 2.215729 / 4.565676 (-2.349947) | 0.057905 / 0.424275 (-0.366370) | 0.007983 / 0.007607 (0.000376) | 0.510413 / 0.226044 (0.284369) | 5.114502 / 2.268929 (2.845574) | 2.871599 / 55.444624 (-52.573026) | 2.537514 / 6.876477 (-4.338962) | 2.819135 / 2.142072 (0.677063) | 0.588397 / 4.805227 (-4.216830) | 0.134665 / 6.500664 (-6.365999) | 0.063349 / 0.075469 (-0.012120) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.352962 / 1.841788 (-0.488826) | 21.628664 / 8.074308 (13.554356) | 15.962105 / 10.191392 (5.770713) | 0.167781 / 0.680424 (-0.512643) | 0.020965 / 0.534201 (-0.513236) | 0.402809 / 0.579283 (-0.176474) | 0.435153 / 0.434364 (0.000789) | 0.481394 / 0.540337 (-0.058944) | 0.658068 / 1.386936 (-0.728868) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#12adf38b90fde8e2a4e46fcbb023ee23b5c4e98c \"CML watermark\")\n" ]

"2023-09-11T13:29:19Z"

"2023-09-13T18:21:28Z"

"2023-09-13T18:12:09Z"

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[ "From what I see, `MMSegInferencer` supports NumPy arrays, so replace the line `image_path = example['image']` with `image_path = np.array(example['image'])` to fix the issue (`example[\"image\"]` is a `PIL.Image` object). ", "> From what I see, `MMSegInferencer` supports NumPy arrays, so replace the line `image_path = example['image']` with `image_path = np.array(example['image'])` to fix the issue (`example[\"image\"]` is a `PIL.Image` object).\r\n\r\nThanks @mariosasko for your reply...\r\ni tried :\r\n```\r\n# Define a function to apply the code to each image in the dataset\r\ndef process_image(image_path):\r\n print(\"Processing image:\", image_path)\r\n result = inferencer(image_path)['predictions']\r\n mask = np.where(result == 12, 255, 0).astype('uint8')\r\n return Image.fromarray(mask)\r\n\r\n# Process and save masks for each image in the dataset\r\nfor idx, example in enumerate(dataset['train']):\r\n image_path = np.array(example['image'])\r\n mask_image = process_image(image_path)\r\n mask_image.save(f\"mask_{idx}.png\")\r\n```\r\nand got\r\n```\r\nProcessing image: [[[202 165 87]\r\n [203 166 88]\r\n [207 168 91]\r\n ...\r\n [243 205 122]\r\n [244 202 120]\r\n [242 200 118]]\r\n\r\n [[202 165 87]\r\n [203 166 88]\r\n [207 168 91]\r\n ...\r\n [244 206 123]\r\n [245 203 121]\r\n [243 201 119]]\r\n\r\n [[203 164 87]\r\n [204 165 88]\r\n [207 168 91]\r\n ...\r\n [245 207 126]\r\n [246 204 122]\r\n [245 203 121]]\r\n\r\n ...\r\n\r\n [[154 123 56]\r\n [155 124 57]\r\n [158 125 56]\r\n ...\r\n [ 3 3 1]\r\n [ 3 3 1]\r\n [ 3 3 1]]\r\n\r\n [[154 123 56]\r\n [154 123 56]\r\n [155 124 57]\r\n ...\r\n [ 2 2 0]\r\n [ 2 2 0]\r\n [ 2 2 0]]\r\n\r\n [[152 121 54]\r\n [152 121 54]\r\n [153 122 55]\r\n ...\r\n [ 2 2 0]\r\n [ 2 2 0]\r\n [ 2 2 0]]]\r\nInference ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ \r\nProcessing image: [[[ 39 44 40]\r\n [ 39 44 40]\r\n [ 39 43 44]\r\n ...\r\n [187 185 164]\r\n [208 204 175]\r\n [203 198 166]]\r\n\r\n [[ 42 47 43]\r\n [ 40 45 41]\r\n [ 40 44 45]\r\n ...\r\n [188 186 165]\r\n [202 198 169]\r\n [201 196 164]]\r\n\r\n [[ 41 46 42]\r\n [ 39 44 40]\r\n [ 40 44 45]\r\n ...\r\n [187 184 165]\r\n [197 193 166]\r\n [201 196 166]]\r\n\r\n ...\r\n\r\n [[ 29 27 30]\r\n [ 28 26 29]\r\n [ 25 23 26]\r\n ...\r\n [ 48 33 28]\r\n [ 44 31 25]\r\n [ 39 26 20]]\r\n\r\n [[ 34 29 33]\r\n [ 32 27 31]\r\n [ 29 24 28]\r\n ...\r\n [ 30 17 11]\r\n [ 36 23 15]\r\n [ 41 28 20]]\r\n\r\n [[ 35 30 34]\r\n [ 33 28 32]\r\n [ 28 23 27]\r\n ...\r\n [ 28 15 9]\r\n [ 41 28 20]\r\n [ 46 33 25]]]\r\nInference ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ \r\nProcessing image: [[[ 65 53 55]\r\n [ 65 53 55]\r\n [ 51 39 41]\r\n ...\r\n [133 127 111]\r\n [150 141 124]\r\n [133 124 107]]\r\n\r\n [[ 58 45 52]\r\n [ 61 48 55]\r\n [ 51 38 45]\r\n ...\r\n [148 141 123]\r\n [178 169 152]\r\n [144 135 118]]\r\n\r\n [[ 79 66 83]\r\n [ 73 60 77]\r\n [ 65 51 66]\r\n ...\r\n [140 131 114]\r\n [142 133 116]\r\n [147 136 118]]\r\n\r\n ...\r\n\r\n [[132 122 133]\r\n [ 95 85 94]\r\n [ 61 51 60]\r\n ...\r\n [ 39 28 42]\r\n [ 46 36 45]\r\n [ 25 16 21]]\r\n\r\n [[150 143 151]\r\n [114 107 115]\r\n [ 64 54 63]\r\n ...\r\n [ 47 35 47]\r\n [ 38 27 35]\r\n [140 129 133]]\r\n\r\n [[145 138 146]\r\n [115 108 116]\r\n [ 69 59 67]\r\n ...\r\n [ 31 19 31]\r\n [128 117 123]\r\n [196 185 189]]]\r\nInference ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ \r\nProcessing image: [[[159 151 140]\r\n [171 163 152]\r\n [161 148 142]\r\n ...\r\n [198 184 171]\r\n [189 175 162]\r\n [183 169 156]]\r\n\r\n [[128 118 106]\r\n [138 128 116]\r\n [138 125 116]\r\n ...\r\n [200 186 173]\r\n [190 176 163]\r\n [187 173 160]]\r\n\r\n [[165 153 137]\r\n [170 158 142]\r\n [174 162 148]\r\n ...\r\n [200 187 171]\r\n [188 175 159]\r\n [182 169 153]]\r\n```\r\nHowever , when trying to add to:\r\n```\r\nfrom datasets import load_dataset\r\ndataset = load_dataset('Andyrasika/cat_kingdom')\r\ndataset\r\n```\r\ni did \r\n```\r\nnew_column = [\"mask\"] * len(dataset[\"train\"])\r\nnew_column\r\ndataset = dataset.add_column(\"/workspace/data\", new_column)\r\n\r\nprint(dataset)\r\n```\r\ngot error:\r\n```\r\n---------------------------------------------------------------------------\r\nAttributeError Traceback (most recent call last)\r\nCell In[11], line 3\r\n 1 new_column = [\"mask\"] * len(dataset[\"train\"])\r\n 2 new_column\r\n----> 3 dataset = dataset.add_column(\"/workspace/data\", new_column)\r\n 5 print(dataset)\r\n\r\nAttributeError: 'DatasetDict' object has no attribute 'add_column'\r\n```", "https://github.com/huggingface/datasets/issues/6246 resolved the `add_column` error, so I'm closing this issue :) " ]

"2023-09-10T08:36:12Z"

"2023-09-13T06:05:20Z"

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[ "_The documentation is not available anymore as the PR was closed or merged._", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.009443 / 0.011353 (-0.001910) | 0.005274 / 0.011008 (-0.005734) | 0.105950 / 0.038508 (0.067441) | 0.079947 / 0.023109 (0.056837) | 0.414248 / 0.275898 (0.138350) | 0.440611 / 0.323480 (0.117131) | 0.006779 / 0.007986 (-0.001206) | 0.004301 / 0.004328 (-0.000028) | 0.080616 / 0.004250 (0.076366) | 0.061425 / 0.037052 (0.024372) | 0.418460 / 0.258489 (0.159971) | 0.468108 / 0.293841 (0.174267) | 0.051090 / 0.128546 (-0.077456) | 0.014133 / 0.075646 (-0.061513) | 0.376121 / 0.419271 (-0.043151) | 0.070715 / 0.043533 (0.027182) | 0.415435 / 0.255139 (0.160296) | 0.457925 / 0.283200 (0.174725) | 0.053653 / 0.141683 (-0.088030) | 1.872681 / 1.452155 (0.420527) | 1.961187 / 1.492716 (0.468470) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.255829 / 0.018006 (0.237823) | 0.574224 / 0.000490 (0.573735) | 0.007597 / 0.000200 (0.007397) | 0.000098 / 0.000054 (0.000044) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.032562 / 0.037411 (-0.004849) | 0.097528 / 0.014526 (0.083003) | 0.113487 / 0.176557 (-0.063070) | 0.185670 / 0.737135 (-0.551465) | 0.118909 / 0.296338 (-0.177430) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.611441 / 0.215209 (0.396232) | 5.908576 / 2.077655 (3.830921) | 2.586758 / 1.504120 (1.082638) | 2.310199 / 1.541195 (0.769004) | 2.333396 / 1.468490 (0.864906) | 0.900884 / 4.584777 (-3.683893) | 5.438304 / 3.745712 (1.692591) | 4.806611 / 5.269862 (-0.463250) | 2.970631 / 4.565676 (-1.595046) | 0.097861 / 0.424275 (-0.326414) | 0.009873 / 0.007607 (0.002266) | 0.739553 / 0.226044 (0.513509) | 7.104953 / 2.268929 (4.836024) | 3.150128 / 55.444624 (-52.294497) | 2.469552 / 6.876477 (-4.406924) | 2.709206 / 2.142072 (0.567133) | 0.983081 / 4.805227 (-3.822147) | 0.205150 / 6.500664 (-6.295514) | 0.075947 / 0.075469 (0.000478) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.631255 / 1.841788 (-0.210532) | 24.213679 / 8.074308 (16.139370) | 21.514481 / 10.191392 (11.323089) | 0.220360 / 0.680424 (-0.460063) | 0.031663 / 0.534201 (-0.502538) | 0.516029 / 0.579283 (-0.063254) | 0.591461 / 0.434364 (0.157097) | 0.612398 / 0.540337 (0.072061) | 0.807609 / 1.386936 (-0.579328) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.009443 / 0.011353 (-0.001910) | 0.005510 / 0.011008 (-0.005498) | 0.085722 / 0.038508 (0.047214) | 0.076256 / 0.023109 (0.053146) | 0.604248 / 0.275898 (0.328349) | 0.596222 / 0.323480 (0.272742) | 0.006786 / 0.007986 (-0.001200) | 0.004135 / 0.004328 (-0.000193) | 0.085934 / 0.004250 (0.081683) | 0.065890 / 0.037052 (0.028838) | 0.592080 / 0.258489 (0.333591) | 0.624560 / 0.293841 (0.330719) | 0.048200 / 0.128546 (-0.080346) | 0.015477 / 0.075646 (-0.060169) | 0.097042 / 0.419271 (-0.322230) | 0.060513 / 0.043533 (0.016981) | 0.557171 / 0.255139 (0.302032) | 0.582057 / 0.283200 (0.298858) | 0.035678 / 0.141683 (-0.106005) | 1.894947 / 1.452155 (0.442792) | 1.956652 / 1.492716 (0.463936) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.268927 / 0.018006 (0.250921) | 0.566086 / 0.000490 (0.565597) | 0.007190 / 0.000200 (0.006990) | 0.000101 / 0.000054 (0.000047) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.042090 / 0.037411 (0.004679) | 0.109618 / 0.014526 (0.095092) | 0.126588 / 0.176557 (-0.049968) | 0.200426 / 0.737135 (-0.536709) | 0.127032 / 0.296338 (-0.169306) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.669773 / 0.215209 (0.454564) | 6.453417 / 2.077655 (4.375763) | 3.119147 / 1.504120 (1.615027) | 2.818632 / 1.541195 (1.277437) | 2.930880 / 1.468490 (1.462390) | 0.922164 / 4.584777 (-3.662612) | 5.769564 / 3.745712 (2.023852) | 4.885108 / 5.269862 (-0.384754) | 3.041640 / 4.565676 (-1.524037) | 0.100186 / 0.424275 (-0.324090) | 0.009417 / 0.007607 (0.001810) | 0.783138 / 0.226044 (0.557094) | 8.113361 / 2.268929 (5.844432) | 4.018630 / 55.444624 (-51.425995) | 3.246772 / 6.876477 (-3.629704) | 3.520690 / 2.142072 (1.378618) | 1.063686 / 4.805227 (-3.741541) | 0.218667 / 6.500664 (-6.281997) | 0.084169 / 0.075469 (0.008700) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.791949 / 1.841788 (-0.049839) | 23.148341 / 8.074308 (15.074033) | 23.321125 / 10.191392 (13.129733) | 0.245391 / 0.680424 (-0.435032) | 0.031911 / 0.534201 (-0.502290) | 0.470707 / 0.579283 (-0.108576) | 0.608195 / 0.434364 (0.173832) | 0.559590 / 0.540337 (0.019253) | 0.786007 / 1.386936 (-0.600929) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#8e071f565cc0801f73f7f34fba92dc30a43946a9 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008428 / 0.011353 (-0.002925) | 0.004064 / 0.011008 (-0.006944) | 0.088421 / 0.038508 (0.049913) | 0.078042 / 0.023109 (0.054933) | 0.306356 / 0.275898 (0.030458) | 0.349766 / 0.323480 (0.026286) | 0.004086 / 0.007986 (-0.003900) | 0.003900 / 0.004328 (-0.000428) | 0.068379 / 0.004250 (0.064129) | 0.056214 / 0.037052 (0.019161) | 0.310211 / 0.258489 (0.051722) | 0.363692 / 0.293841 (0.069851) | 0.050421 / 0.128546 (-0.078125) | 0.011661 / 0.075646 (-0.063985) | 0.298400 / 0.419271 (-0.120871) | 0.063503 / 0.043533 (0.019970) | 0.339799 / 0.255139 (0.084660) | 0.359479 / 0.283200 (0.076279) | 0.039265 / 0.141683 (-0.102418) | 1.390578 / 1.452155 (-0.061576) | 1.573333 / 1.492716 (0.080617) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.260442 / 0.018006 (0.242436) | 0.560390 / 0.000490 (0.559900) | 0.003926 / 0.000200 (0.003726) | 0.000083 / 0.000054 (0.000029) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.025809 / 0.037411 (-0.011602) | 0.081902 / 0.014526 (0.067376) | 0.093655 / 0.176557 (-0.082901) | 0.149432 / 0.737135 (-0.587703) | 0.099059 / 0.296338 (-0.197279) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.505644 / 0.215209 (0.290435) | 5.108292 / 2.077655 (3.030638) | 2.121689 / 1.504120 (0.617569) | 1.846576 / 1.541195 (0.305381) | 1.836587 / 1.468490 (0.368097) | 0.708088 / 4.584777 (-3.876689) | 4.562630 / 3.745712 (0.816918) | 3.934747 / 5.269862 (-1.335115) | 2.453409 / 4.565676 (-2.112267) | 0.081908 / 0.424275 (-0.342367) | 0.012996 / 0.007607 (0.005389) | 0.636588 / 0.226044 (0.410544) | 6.361086 / 2.268929 (4.092157) | 2.911681 / 55.444624 (-52.532943) | 2.271809 / 6.876477 (-4.604667) | 2.670327 / 2.142072 (0.528254) | 0.943688 / 4.805227 (-3.861539) | 0.191677 / 6.500664 (-6.308988) | 0.066008 / 0.075469 (-0.009461) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.400139 / 1.841788 (-0.441648) | 21.896198 / 8.074308 (13.821890) | 17.853604 / 10.191392 (7.662212) | 0.226603 / 0.680424 (-0.453821) | 0.026682 / 0.534201 (-0.507518) | 0.460131 / 0.579283 (-0.119152) | 0.536790 / 0.434364 (0.102427) | 0.492913 / 0.540337 (-0.047424) | 0.724290 / 1.386936 (-0.662646) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007795 / 0.011353 (-0.003557) | 0.009045 / 0.011008 (-0.001963) | 0.085480 / 0.038508 (0.046972) | 0.071881 / 0.023109 (0.048772) | 0.514520 / 0.275898 (0.238622) | 0.569762 / 0.323480 (0.246282) | 0.006126 / 0.007986 (-0.001859) | 0.004153 / 0.004328 (-0.000175) | 0.072150 / 0.004250 (0.067900) | 0.056511 / 0.037052 (0.019458) | 0.484097 / 0.258489 (0.225607) | 0.532673 / 0.293841 (0.238832) | 0.040974 / 0.128546 (-0.087572) | 0.012071 / 0.075646 (-0.063575) | 0.102608 / 0.419271 (-0.316663) | 0.052893 / 0.043533 (0.009360) | 0.485832 / 0.255139 (0.230693) | 0.530479 / 0.283200 (0.247280) | 0.031556 / 0.141683 (-0.110127) | 1.737508 / 1.452155 (0.285354) | 1.834637 / 1.492716 (0.341921) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.423314 / 0.018006 (0.405308) | 0.614163 / 0.000490 (0.613673) | 0.052784 / 0.000200 (0.052584) | 0.000206 / 0.000054 (0.000151) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.031728 / 0.037411 (-0.005684) | 0.088048 / 0.014526 (0.073522) | 0.105759 / 0.176557 (-0.070798) | 0.181433 / 0.737135 (-0.555703) | 0.103133 / 0.296338 (-0.193205) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.659710 / 0.215209 (0.444501) | 5.876378 / 2.077655 (3.798723) | 2.899444 / 1.504120 (1.395324) | 2.871592 / 1.541195 (1.330397) | 2.861205 / 1.468490 (1.392715) | 0.879452 / 4.584777 (-3.705325) | 5.395988 / 3.745712 (1.650275) | 4.548359 / 5.269862 (-0.721502) | 2.946601 / 4.565676 (-1.619076) | 0.099832 / 0.424275 (-0.324443) | 0.008958 / 0.007607 (0.001351) | 0.778480 / 0.226044 (0.552435) | 7.672282 / 2.268929 (5.403354) | 3.963701 / 55.444624 (-51.480923) | 3.154950 / 6.876477 (-3.721527) | 3.351070 / 2.142072 (1.208997) | 1.059459 / 4.805227 (-3.745768) | 0.212035 / 6.500664 (-6.288629) | 0.076941 / 0.075469 (0.001472) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.639813 / 1.841788 (-0.201975) | 24.807517 / 8.074308 (16.733208) | 20.662500 / 10.191392 (10.471108) | 0.244486 / 0.680424 (-0.435937) | 0.032335 / 0.534201 (-0.501866) | 0.470896 / 0.579283 (-0.108387) | 0.581561 / 0.434364 (0.147197) | 0.495158 / 0.540337 (-0.045179) | 0.788350 / 1.386936 (-0.598586) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#99641ced2e08a28cb876f483babcdd43f7dd76d2 \"CML watermark\")\n" ]

"2023-09-08T16:09:13Z"

"2023-09-08T18:02:49Z"

"2023-09-08T17:52:16Z"

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[ "_The documentation is not available anymore as the PR was closed or merged._", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.005920 / 0.011353 (-0.005433) | 0.003623 / 0.011008 (-0.007385) | 0.079283 / 0.038508 (0.040775) | 0.058325 / 0.023109 (0.035216) | 0.313733 / 0.275898 (0.037835) | 0.360790 / 0.323480 (0.037310) | 0.004653 / 0.007986 (-0.003332) | 0.002876 / 0.004328 (-0.001452) | 0.062137 / 0.004250 (0.057886) | 0.045084 / 0.037052 (0.008031) | 0.328569 / 0.258489 (0.070079) | 0.368965 / 0.293841 (0.075124) | 0.027085 / 0.128546 (-0.101461) | 0.008051 / 0.075646 (-0.067595) | 0.260222 / 0.419271 (-0.159050) | 0.045477 / 0.043533 (0.001944) | 0.315344 / 0.255139 (0.060205) | 0.348215 / 0.283200 (0.065015) | 0.021352 / 0.141683 (-0.120331) | 1.432200 / 1.452155 (-0.019955) | 1.509217 / 1.492716 (0.016501) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.199843 / 0.018006 (0.181837) | 0.427925 / 0.000490 (0.427435) | 0.002903 / 0.000200 (0.002703) | 0.000067 / 0.000054 (0.000013) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.023121 / 0.037411 (-0.014291) | 0.072451 / 0.014526 (0.057925) | 0.083260 / 0.176557 (-0.093296) | 0.142879 / 0.737135 (-0.594257) | 0.084053 / 0.296338 (-0.212286) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.394922 / 0.215209 (0.179713) | 3.956111 / 2.077655 (1.878456) | 1.926411 / 1.504120 (0.422291) | 1.743840 / 1.541195 (0.202646) | 1.776957 / 1.468490 (0.308467) | 0.502134 / 4.584777 (-4.082643) | 3.001721 / 3.745712 (-0.743991) | 2.852496 / 5.269862 (-2.417365) | 1.862794 / 4.565676 (-2.702883) | 0.057544 / 0.424275 (-0.366731) | 0.006751 / 0.007607 (-0.000856) | 0.470619 / 0.226044 (0.244575) | 4.696674 / 2.268929 (2.427746) | 2.326545 / 55.444624 (-53.118080) | 1.980888 / 6.876477 (-4.895589) | 2.139172 / 2.142072 (-0.002901) | 0.590256 / 4.805227 (-4.214971) | 0.125815 / 6.500664 (-6.374849) | 0.061000 / 0.075469 (-0.014469) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.261948 / 1.841788 (-0.579839) | 18.317473 / 8.074308 (10.243165) | 13.810883 / 10.191392 (3.619491) | 0.146180 / 0.680424 (-0.534244) | 0.016701 / 0.534201 (-0.517500) | 0.330731 / 0.579283 (-0.248552) | 0.345103 / 0.434364 (-0.089261) | 0.374449 / 0.540337 (-0.165889) | 0.522463 / 1.386936 (-0.864473) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006217 / 0.011353 (-0.005136) | 0.003678 / 0.011008 (-0.007331) | 0.062321 / 0.038508 (0.023813) | 0.059256 / 0.023109 (0.036147) | 0.444501 / 0.275898 (0.168603) | 0.475881 / 0.323480 (0.152401) | 0.004863 / 0.007986 (-0.003123) | 0.002916 / 0.004328 (-0.001412) | 0.062197 / 0.004250 (0.057946) | 0.048449 / 0.037052 (0.011396) | 0.443680 / 0.258489 (0.185191) | 0.484570 / 0.293841 (0.190729) | 0.028694 / 0.128546 (-0.099852) | 0.008096 / 0.075646 (-0.067550) | 0.068347 / 0.419271 (-0.350924) | 0.041031 / 0.043533 (-0.002502) | 0.443907 / 0.255139 (0.188768) | 0.469888 / 0.283200 (0.186689) | 0.020237 / 0.141683 (-0.121445) | 1.438484 / 1.452155 (-0.013671) | 1.512652 / 1.492716 (0.019936) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.243118 / 0.018006 (0.225111) | 0.416797 / 0.000490 (0.416308) | 0.010421 / 0.000200 (0.010221) | 0.000082 / 0.000054 (0.000028) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.026191 / 0.037411 (-0.011220) | 0.080881 / 0.014526 (0.066355) | 0.093207 / 0.176557 (-0.083349) | 0.146708 / 0.737135 (-0.590428) | 0.091676 / 0.296338 (-0.204663) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.461475 / 0.215209 (0.246266) | 4.617351 / 2.077655 (2.539696) | 2.564369 / 1.504120 (1.060249) | 2.393263 / 1.541195 (0.852068) | 2.447343 / 1.468490 (0.978853) | 0.508764 / 4.584777 (-4.076013) | 3.075460 / 3.745712 (-0.670252) | 2.884683 / 5.269862 (-2.385179) | 1.866432 / 4.565676 (-2.699244) | 0.058759 / 0.424275 (-0.365516) | 0.006591 / 0.007607 (-0.001016) | 0.537718 / 0.226044 (0.311674) | 5.378709 / 2.268929 (3.109781) | 3.006751 / 55.444624 (-52.437873) | 2.666653 / 6.876477 (-4.209824) | 2.847559 / 2.142072 (0.705486) | 0.596878 / 4.805227 (-4.208350) | 0.125073 / 6.500664 (-6.375591) | 0.061345 / 0.075469 (-0.014124) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.349066 / 1.841788 (-0.492721) | 18.684735 / 8.074308 (10.610427) | 15.128142 / 10.191392 (4.936750) | 0.149254 / 0.680424 (-0.531170) | 0.017911 / 0.534201 (-0.516290) | 0.344057 / 0.579283 (-0.235226) | 0.363474 / 0.434364 (-0.070890) | 0.399425 / 0.540337 (-0.140912) | 0.549329 / 1.386936 (-0.837607) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#e675a2396efb5204a4553721001f3b46aa4cc334 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.005843 / 0.011353 (-0.005510) | 0.003549 / 0.011008 (-0.007460) | 0.082318 / 0.038508 (0.043810) | 0.056835 / 0.023109 (0.033726) | 0.312968 / 0.275898 (0.037070) | 0.345918 / 0.323480 (0.022438) | 0.003239 / 0.007986 (-0.004747) | 0.002762 / 0.004328 (-0.001567) | 0.062362 / 0.004250 (0.058111) | 0.045934 / 0.037052 (0.008882) | 0.317035 / 0.258489 (0.058546) | 0.358473 / 0.293841 (0.064632) | 0.027311 / 0.128546 (-0.101235) | 0.007994 / 0.075646 (-0.067652) | 0.261565 / 0.419271 (-0.157706) | 0.044942 / 0.043533 (0.001410) | 0.313092 / 0.255139 (0.057953) | 0.339021 / 0.283200 (0.055821) | 0.021555 / 0.141683 (-0.120127) | 1.421232 / 1.452155 (-0.030923) | 1.487597 / 1.492716 (-0.005119) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.206432 / 0.018006 (0.188425) | 0.421932 / 0.000490 (0.421442) | 0.002825 / 0.000200 (0.002625) | 0.000065 / 0.000054 (0.000011) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.022795 / 0.037411 (-0.014616) | 0.072666 / 0.014526 (0.058140) | 0.082779 / 0.176557 (-0.093778) | 0.142320 / 0.737135 (-0.594815) | 0.083343 / 0.296338 (-0.212995) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.394227 / 0.215209 (0.179018) | 3.931858 / 2.077655 (1.854203) | 1.909953 / 1.504120 (0.405833) | 1.711298 / 1.541195 (0.170104) | 1.745816 / 1.468490 (0.277326) | 0.503670 / 4.584777 (-4.081107) | 3.053677 / 3.745712 (-0.692035) | 2.802597 / 5.269862 (-2.467264) | 1.825315 / 4.565676 (-2.740362) | 0.057741 / 0.424275 (-0.366534) | 0.006581 / 0.007607 (-0.001027) | 0.463597 / 0.226044 (0.237552) | 4.638821 / 2.268929 (2.369893) | 2.301266 / 55.444624 (-53.143358) | 1.967111 / 6.876477 (-4.909365) | 2.097756 / 2.142072 (-0.044317) | 0.589840 / 4.805227 (-4.215387) | 0.125538 / 6.500664 (-6.375126) | 0.061203 / 0.075469 (-0.014266) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.291815 / 1.841788 (-0.549973) | 17.997040 / 8.074308 (9.922732) | 13.616252 / 10.191392 (3.424860) | 0.137349 / 0.680424 (-0.543075) | 0.016626 / 0.534201 (-0.517575) | 0.329611 / 0.579283 (-0.249672) | 0.346592 / 0.434364 (-0.087772) | 0.379521 / 0.540337 (-0.160817) | 0.528058 / 1.386936 (-0.858878) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006073 / 0.011353 (-0.005280) | 0.003594 / 0.011008 (-0.007414) | 0.062537 / 0.038508 (0.024029) | 0.057503 / 0.023109 (0.034394) | 0.449427 / 0.275898 (0.173529) | 0.482729 / 0.323480 (0.159249) | 0.004690 / 0.007986 (-0.003295) | 0.002901 / 0.004328 (-0.001428) | 0.062421 / 0.004250 (0.058171) | 0.046405 / 0.037052 (0.009353) | 0.456578 / 0.258489 (0.198089) | 0.492268 / 0.293841 (0.198427) | 0.028283 / 0.128546 (-0.100263) | 0.008028 / 0.075646 (-0.067618) | 0.067885 / 0.419271 (-0.351387) | 0.041273 / 0.043533 (-0.002260) | 0.449870 / 0.255139 (0.194731) | 0.472305 / 0.283200 (0.189106) | 0.018556 / 0.141683 (-0.123127) | 1.449016 / 1.452155 (-0.003138) | 1.490839 / 1.492716 (-0.001877) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.226569 / 0.018006 (0.208563) | 0.417106 / 0.000490 (0.416616) | 0.002784 / 0.000200 (0.002584) | 0.000072 / 0.000054 (0.000018) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.025803 / 0.037411 (-0.011608) | 0.081084 / 0.014526 (0.066559) | 0.091851 / 0.176557 (-0.084706) | 0.143982 / 0.737135 (-0.593153) | 0.090511 / 0.296338 (-0.205827) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.463664 / 0.215209 (0.248454) | 4.634528 / 2.077655 (2.556874) | 2.574739 / 1.504120 (1.070619) | 2.412857 / 1.541195 (0.871662) | 2.442858 / 1.468490 (0.974368) | 0.511990 / 4.584777 (-4.072787) | 3.070345 / 3.745712 (-0.675367) | 2.842290 / 5.269862 (-2.427571) | 1.846727 / 4.565676 (-2.718950) | 0.058852 / 0.424275 (-0.365424) | 0.006624 / 0.007607 (-0.000983) | 0.539616 / 0.226044 (0.313571) | 5.410784 / 2.268929 (3.141856) | 3.065593 / 55.444624 (-52.379031) | 2.677930 / 6.876477 (-4.198547) | 2.817548 / 2.142072 (0.675476) | 0.602672 / 4.805227 (-4.202555) | 0.125689 / 6.500664 (-6.374975) | 0.062007 / 0.075469 (-0.013462) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.335336 / 1.841788 (-0.506452) | 18.310099 / 8.074308 (10.235791) | 14.818452 / 10.191392 (4.627060) | 0.154001 / 0.680424 (-0.526423) | 0.017892 / 0.534201 (-0.516309) | 0.345989 / 0.579283 (-0.233294) | 0.352108 / 0.434364 (-0.082256) | 0.394333 / 0.540337 (-0.146004) | 0.547680 / 1.386936 (-0.839256) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#d058d6e9b849acb5bc61d7df597a94253b487eb6 \"CML watermark\")\n" ]

"2023-09-08T11:08:55Z"

"2023-09-08T12:29:21Z"

"2023-09-08T12:20:51Z"

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[]

[]

[ "Good catch!" ]

"2023-09-08T06:49:19Z"

"2023-09-08T17:52:18Z"

"2023-09-08T17:52:17Z"

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[ "_The documentation is not available anymore as the PR was closed or merged._", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.009450 / 0.011353 (-0.001903) | 0.007339 / 0.011008 (-0.003669) | 0.110150 / 0.038508 (0.071641) | 0.087794 / 0.023109 (0.064685) | 0.472099 / 0.275898 (0.196201) | 0.476622 / 0.323480 (0.153142) | 0.005057 / 0.007986 (-0.002929) | 0.005262 / 0.004328 (0.000933) | 0.103059 / 0.004250 (0.098808) | 0.069815 / 0.037052 (0.032763) | 0.489377 / 0.258489 (0.230888) | 0.547087 / 0.293841 (0.253247) | 0.048883 / 0.128546 (-0.079663) | 0.019192 / 0.075646 (-0.056454) | 0.410865 / 0.419271 (-0.008407) | 0.076215 / 0.043533 (0.032682) | 0.484825 / 0.255139 (0.229686) | 0.519035 / 0.283200 (0.235835) | 0.042030 / 0.141683 (-0.099653) | 1.909630 / 1.452155 (0.457475) | 2.120869 / 1.492716 (0.628153) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.267600 / 0.018006 (0.249594) | 0.619135 / 0.000490 (0.618645) | 0.005897 / 0.000200 (0.005697) | 0.000142 / 0.000054 (0.000087) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.033265 / 0.037411 (-0.004146) | 0.104476 / 0.014526 (0.089950) | 0.129199 / 0.176557 (-0.047358) | 0.196898 / 0.737135 (-0.540238) | 0.118852 / 0.296338 (-0.177487) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.598908 / 0.215209 (0.383699) | 6.263096 / 2.077655 (4.185441) | 2.672134 / 1.504120 (1.168014) | 2.428706 / 1.541195 (0.887511) | 2.431651 / 1.468490 (0.963161) | 0.918465 / 4.584777 (-3.666312) | 5.667857 / 3.745712 (1.922145) | 5.113696 / 5.269862 (-0.156166) | 3.276805 / 4.565676 (-1.288872) | 0.101829 / 0.424275 (-0.322446) | 0.010224 / 0.007607 (0.002617) | 0.741547 / 0.226044 (0.515502) | 7.517002 / 2.268929 (5.248073) | 3.546353 / 55.444624 (-51.898272) | 2.845956 / 6.876477 (-4.030521) | 3.172777 / 2.142072 (1.030705) | 1.153485 / 4.805227 (-3.651742) | 0.225758 / 6.500664 (-6.274906) | 0.084333 / 0.075469 (0.008864) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.704645 / 1.841788 (-0.137143) | 27.044110 / 8.074308 (18.969801) | 24.653837 / 10.191392 (14.462445) | 0.235452 / 0.680424 (-0.444971) | 0.029285 / 0.534201 (-0.504916) | 0.576122 / 0.579283 (-0.003161) | 0.626263 / 0.434364 (0.191899) | 0.600201 / 0.540337 (0.059864) | 0.838406 / 1.386936 (-0.548530) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.013754 / 0.011353 (0.002401) | 0.005954 / 0.011008 (-0.005054) | 0.089766 / 0.038508 (0.051258) | 0.096126 / 0.023109 (0.073017) | 0.556455 / 0.275898 (0.280557) | 0.579302 / 0.323480 (0.255822) | 0.009222 / 0.007986 (0.001236) | 0.006128 / 0.004328 (0.001800) | 0.099725 / 0.004250 (0.095475) | 0.075642 / 0.037052 (0.038589) | 0.556645 / 0.258489 (0.298156) | 0.615898 / 0.293841 (0.322057) | 0.057728 / 0.128546 (-0.070818) | 0.016746 / 0.075646 (-0.058900) | 0.098053 / 0.419271 (-0.321219) | 0.066676 / 0.043533 (0.023143) | 0.534156 / 0.255139 (0.279017) | 0.590020 / 0.283200 (0.306820) | 0.038782 / 0.141683 (-0.102901) | 1.952301 / 1.452155 (0.500146) | 2.104255 / 1.492716 (0.611539) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.305945 / 0.018006 (0.287939) | 0.643915 / 0.000490 (0.643426) | 0.006268 / 0.000200 (0.006068) | 0.000156 / 0.000054 (0.000102) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.039891 / 0.037411 (0.002479) | 0.117888 / 0.014526 (0.103363) | 0.134230 / 0.176557 (-0.042326) | 0.212544 / 0.737135 (-0.524591) | 0.128858 / 0.296338 (-0.167480) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.718165 / 0.215209 (0.502955) | 7.023867 / 2.077655 (4.946212) | 3.391344 / 1.504120 (1.887224) | 3.021248 / 1.541195 (1.480053) | 3.010217 / 1.468490 (1.541727) | 0.932608 / 4.584777 (-3.652169) | 5.787536 / 3.745712 (2.041824) | 5.221305 / 5.269862 (-0.048557) | 3.282552 / 4.565676 (-1.283125) | 0.105486 / 0.424275 (-0.318789) | 0.009800 / 0.007607 (0.002193) | 0.839358 / 0.226044 (0.613314) | 8.279712 / 2.268929 (6.010784) | 4.118466 / 55.444624 (-51.326158) | 3.407738 / 6.876477 (-3.468739) | 3.632538 / 2.142072 (1.490466) | 1.109673 / 4.805227 (-3.695555) | 0.216541 / 6.500664 (-6.284123) | 0.094031 / 0.075469 (0.018562) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.983979 / 1.841788 (0.142191) | 27.125882 / 8.074308 (19.051573) | 24.714002 / 10.191392 (14.522610) | 0.264417 / 0.680424 (-0.416007) | 0.034783 / 0.534201 (-0.499418) | 0.533304 / 0.579283 (-0.045979) | 0.647798 / 0.434364 (0.213434) | 0.588680 / 0.540337 (0.048343) | 0.854250 / 1.386936 (-0.532686) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#491604b46b1fd8d6fd1b7531f7917ccd657665a6 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006664 / 0.011353 (-0.004689) | 0.004164 / 0.011008 (-0.006844) | 0.085192 / 0.038508 (0.046684) | 0.073578 / 0.023109 (0.050469) | 0.356379 / 0.275898 (0.080481) | 0.389381 / 0.323480 (0.065902) | 0.005527 / 0.007986 (-0.002459) | 0.003488 / 0.004328 (-0.000840) | 0.065640 / 0.004250 (0.061390) | 0.055013 / 0.037052 (0.017960) | 0.358002 / 0.258489 (0.099513) | 0.400663 / 0.293841 (0.106822) | 0.030937 / 0.128546 (-0.097609) | 0.008838 / 0.075646 (-0.066808) | 0.287488 / 0.419271 (-0.131784) | 0.051503 / 0.043533 (0.007971) | 0.353945 / 0.255139 (0.098806) | 0.388778 / 0.283200 (0.105579) | 0.023346 / 0.141683 (-0.118337) | 1.479621 / 1.452155 (0.027466) | 1.559164 / 1.492716 (0.066448) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.245160 / 0.018006 (0.227154) | 0.561890 / 0.000490 (0.561400) | 0.004339 / 0.000200 (0.004139) | 0.000083 / 0.000054 (0.000028) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.028460 / 0.037411 (-0.008952) | 0.082046 / 0.014526 (0.067520) | 0.098005 / 0.176557 (-0.078552) | 0.154171 / 0.737135 (-0.582965) | 0.097632 / 0.296338 (-0.198707) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.389993 / 0.215209 (0.174784) | 3.893287 / 2.077655 (1.815632) | 1.885668 / 1.504120 (0.381549) | 1.715055 / 1.541195 (0.173860) | 1.778008 / 1.468490 (0.309518) | 0.482818 / 4.584777 (-4.101959) | 3.572153 / 3.745712 (-0.173559) | 3.267666 / 5.269862 (-2.002196) | 2.088394 / 4.565676 (-2.477282) | 0.056961 / 0.424275 (-0.367314) | 0.007784 / 0.007607 (0.000177) | 0.466586 / 0.226044 (0.240542) | 4.652505 / 2.268929 (2.383576) | 2.491392 / 55.444624 (-52.953233) | 2.127600 / 6.876477 (-4.748877) | 2.296778 / 2.142072 (0.154705) | 0.582332 / 4.805227 (-4.222895) | 0.134372 / 6.500664 (-6.366292) | 0.061737 / 0.075469 (-0.013732) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.253647 / 1.841788 (-0.588140) | 19.802353 / 8.074308 (11.728045) | 14.262815 / 10.191392 (4.071423) | 0.169489 / 0.680424 (-0.510935) | 0.018108 / 0.534201 (-0.516093) | 0.391711 / 0.579283 (-0.187572) | 0.406169 / 0.434364 (-0.028195) | 0.456728 / 0.540337 (-0.083609) | 0.633538 / 1.386936 (-0.753398) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006661 / 0.011353 (-0.004692) | 0.004181 / 0.011008 (-0.006827) | 0.064945 / 0.038508 (0.026437) | 0.073965 / 0.023109 (0.050856) | 0.406549 / 0.275898 (0.130651) | 0.441568 / 0.323480 (0.118089) | 0.005579 / 0.007986 (-0.002407) | 0.003523 / 0.004328 (-0.000805) | 0.065270 / 0.004250 (0.061019) | 0.055596 / 0.037052 (0.018544) | 0.407701 / 0.258489 (0.149212) | 0.444609 / 0.293841 (0.150768) | 0.031749 / 0.128546 (-0.096797) | 0.008680 / 0.075646 (-0.066966) | 0.071154 / 0.419271 (-0.348117) | 0.047376 / 0.043533 (0.003843) | 0.406409 / 0.255139 (0.151270) | 0.420477 / 0.283200 (0.137278) | 0.023707 / 0.141683 (-0.117976) | 1.484516 / 1.452155 (0.032361) | 1.568493 / 1.492716 (0.075777) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.266534 / 0.018006 (0.248528) | 0.573806 / 0.000490 (0.573316) | 0.006247 / 0.000200 (0.006048) | 0.000165 / 0.000054 (0.000110) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.033436 / 0.037411 (-0.003976) | 0.091947 / 0.014526 (0.077421) | 0.105556 / 0.176557 (-0.071000) | 0.162094 / 0.737135 (-0.575041) | 0.107879 / 0.296338 (-0.188459) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.429126 / 0.215209 (0.213917) | 4.281329 / 2.077655 (2.203675) | 2.295406 / 1.504120 (0.791286) | 2.123336 / 1.541195 (0.582141) | 2.190804 / 1.468490 (0.722314) | 0.492972 / 4.584777 (-4.091805) | 3.638485 / 3.745712 (-0.107227) | 3.304576 / 5.269862 (-1.965285) | 2.063694 / 4.565676 (-2.501983) | 0.058549 / 0.424275 (-0.365726) | 0.007591 / 0.007607 (-0.000016) | 0.504268 / 0.226044 (0.278223) | 5.031990 / 2.268929 (2.763061) | 2.773173 / 55.444624 (-52.671451) | 2.430789 / 6.876477 (-4.445688) | 2.699900 / 2.142072 (0.557828) | 0.593220 / 4.805227 (-4.212007) | 0.133710 / 6.500664 (-6.366954) | 0.059840 / 0.075469 (-0.015629) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.351158 / 1.841788 (-0.490629) | 20.176310 / 8.074308 (12.102002) | 14.933202 / 10.191392 (4.741810) | 0.169920 / 0.680424 (-0.510503) | 0.020156 / 0.534201 (-0.514045) | 0.397440 / 0.579283 (-0.181843) | 0.409395 / 0.434364 (-0.024969) | 0.471066 / 0.540337 (-0.069271) | 0.642670 / 1.386936 (-0.744266) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#cf90ca7fbfd9c4639cc3faf0a349eb26490e38fc \"CML watermark\")\n" ]

"2023-09-07T14:43:51Z"

"2023-09-07T15:46:10Z"

"2023-09-07T15:37:20Z"

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[ "_The documentation is not available anymore as the PR was closed or merged._", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006757 / 0.011353 (-0.004596) | 0.004233 / 0.011008 (-0.006775) | 0.084123 / 0.038508 (0.045614) | 0.077513 / 0.023109 (0.054404) | 0.357024 / 0.275898 (0.081126) | 0.392956 / 0.323480 (0.069476) | 0.005408 / 0.007986 (-0.002577) | 0.003363 / 0.004328 (-0.000966) | 0.064395 / 0.004250 (0.060145) | 0.054711 / 0.037052 (0.017659) | 0.367287 / 0.258489 (0.108798) | 0.402934 / 0.293841 (0.109093) | 0.031845 / 0.128546 (-0.096701) | 0.008646 / 0.075646 (-0.067000) | 0.288740 / 0.419271 (-0.130531) | 0.053171 / 0.043533 (0.009638) | 0.360711 / 0.255139 (0.105572) | 0.388707 / 0.283200 (0.105507) | 0.025321 / 0.141683 (-0.116361) | 1.500684 / 1.452155 (0.048529) | 1.585747 / 1.492716 (0.093030) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.207329 / 0.018006 (0.189323) | 0.465304 / 0.000490 (0.464814) | 0.003229 / 0.000200 (0.003029) | 0.000080 / 0.000054 (0.000025) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.028752 / 0.037411 (-0.008659) | 0.085327 / 0.014526 (0.070802) | 0.332210 / 0.176557 (0.155653) | 0.178779 / 0.737135 (-0.558356) | 0.097765 / 0.296338 (-0.198573) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.403710 / 0.215209 (0.188501) | 4.027069 / 2.077655 (1.949414) | 2.053451 / 1.504120 (0.549331) | 1.906647 / 1.541195 (0.365452) | 1.992507 / 1.468490 (0.524017) | 0.490203 / 4.584777 (-4.094574) | 3.696569 / 3.745712 (-0.049143) | 3.319919 / 5.269862 (-1.949943) | 2.072794 / 4.565676 (-2.492883) | 0.057893 / 0.424275 (-0.366383) | 0.007723 / 0.007607 (0.000116) | 0.485400 / 0.226044 (0.259355) | 4.842891 / 2.268929 (2.573963) | 2.578949 / 55.444624 (-52.865675) | 2.229217 / 6.876477 (-4.647259) | 2.468017 / 2.142072 (0.325945) | 0.595236 / 4.805227 (-4.209992) | 0.135641 / 6.500664 (-6.365023) | 0.061232 / 0.075469 (-0.014237) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.307059 / 1.841788 (-0.534729) | 20.108581 / 8.074308 (12.034273) | 14.438985 / 10.191392 (4.247593) | 0.168878 / 0.680424 (-0.511545) | 0.018208 / 0.534201 (-0.515993) | 0.395986 / 0.579283 (-0.183297) | 0.427440 / 0.434364 (-0.006924) | 0.459917 / 0.540337 (-0.080421) | 0.631379 / 1.386936 (-0.755557) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007002 / 0.011353 (-0.004351) | 0.004120 / 0.011008 (-0.006888) | 0.064817 / 0.038508 (0.026309) | 0.081297 / 0.023109 (0.058188) | 0.405598 / 0.275898 (0.129700) | 0.442360 / 0.323480 (0.118880) | 0.005475 / 0.007986 (-0.002511) | 0.003483 / 0.004328 (-0.000845) | 0.064750 / 0.004250 (0.060499) | 0.058111 / 0.037052 (0.021059) | 0.410154 / 0.258489 (0.151665) | 0.445137 / 0.293841 (0.151296) | 0.033314 / 0.128546 (-0.095232) | 0.008747 / 0.075646 (-0.066899) | 0.071595 / 0.419271 (-0.347676) | 0.048894 / 0.043533 (0.005361) | 0.409162 / 0.255139 (0.154023) | 0.428877 / 0.283200 (0.145677) | 0.024127 / 0.141683 (-0.117556) | 1.521369 / 1.452155 (0.069214) | 1.573505 / 1.492716 (0.080789) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.233199 / 0.018006 (0.215193) | 0.455619 / 0.000490 (0.455129) | 0.003688 / 0.000200 (0.003488) | 0.000081 / 0.000054 (0.000027) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.033186 / 0.037411 (-0.004225) | 0.100528 / 0.014526 (0.086003) | 0.105617 / 0.176557 (-0.070940) | 0.159437 / 0.737135 (-0.577698) | 0.108064 / 0.296338 (-0.188274) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.435509 / 0.215209 (0.220300) | 4.339920 / 2.077655 (2.262265) | 2.368983 / 1.504120 (0.864863) | 2.211761 / 1.541195 (0.670566) | 2.301701 / 1.468490 (0.833211) | 0.495144 / 4.584777 (-4.089633) | 3.768882 / 3.745712 (0.023170) | 3.348940 / 5.269862 (-1.920922) | 2.081142 / 4.565676 (-2.484534) | 0.058184 / 0.424275 (-0.366091) | 0.007597 / 0.007607 (-0.000010) | 0.508806 / 0.226044 (0.282762) | 5.089226 / 2.268929 (2.820297) | 2.851930 / 55.444624 (-52.592694) | 2.512144 / 6.876477 (-4.364332) | 2.724461 / 2.142072 (0.582388) | 0.593446 / 4.805227 (-4.211781) | 0.134908 / 6.500664 (-6.365756) | 0.060811 / 0.075469 (-0.014658) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.362279 / 1.841788 (-0.479508) | 20.548216 / 8.074308 (12.473908) | 15.179181 / 10.191392 (4.987789) | 0.170249 / 0.680424 (-0.510175) | 0.020772 / 0.534201 (-0.513429) | 0.398737 / 0.579283 (-0.180546) | 0.441487 / 0.434364 (0.007124) | 0.480096 / 0.540337 (-0.060242) | 0.645825 / 1.386936 (-0.741111) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#a6fb8b9a833afb25311da395c6e0d9bf770ca2c7 \"CML watermark\")\n" ]

"2023-09-07T11:33:20Z"

"2023-09-13T22:32:31Z"

"2023-09-13T22:23:42Z"

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[ "_The documentation is not available anymore as the PR was closed or merged._", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006655 / 0.011353 (-0.004698) | 0.004115 / 0.011008 (-0.006893) | 0.083895 / 0.038508 (0.045387) | 0.072770 / 0.023109 (0.049661) | 0.311401 / 0.275898 (0.035503) | 0.341079 / 0.323480 (0.017599) | 0.005488 / 0.007986 (-0.002497) | 0.003530 / 0.004328 (-0.000799) | 0.064691 / 0.004250 (0.060441) | 0.053096 / 0.037052 (0.016044) | 0.314969 / 0.258489 (0.056480) | 0.358245 / 0.293841 (0.064404) | 0.030789 / 0.128546 (-0.097757) | 0.008868 / 0.075646 (-0.066779) | 0.288022 / 0.419271 (-0.131249) | 0.052092 / 0.043533 (0.008559) | 0.310061 / 0.255139 (0.054922) | 0.345369 / 0.283200 (0.062170) | 0.024100 / 0.141683 (-0.117582) | 1.520573 / 1.452155 (0.068418) | 1.593750 / 1.492716 (0.101033) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.242520 / 0.018006 (0.224514) | 0.567963 / 0.000490 (0.567473) | 0.003183 / 0.000200 (0.002983) | 0.000074 / 0.000054 (0.000020) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.029473 / 0.037411 (-0.007939) | 0.083012 / 0.014526 (0.068486) | 0.262386 / 0.176557 (0.085830) | 0.155131 / 0.737135 (-0.582004) | 0.099880 / 0.296338 (-0.196458) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.382388 / 0.215209 (0.167179) | 3.816538 / 2.077655 (1.738884) | 1.863422 / 1.504120 (0.359302) | 1.694652 / 1.541195 (0.153457) | 1.738738 / 1.468490 (0.270248) | 0.477073 / 4.584777 (-4.107704) | 3.539244 / 3.745712 (-0.206468) | 3.238469 / 5.269862 (-2.031392) | 2.026154 / 4.565676 (-2.539523) | 0.056111 / 0.424275 (-0.368164) | 0.007615 / 0.007607 (0.000008) | 0.460620 / 0.226044 (0.234576) | 4.596383 / 2.268929 (2.327455) | 2.348645 / 55.444624 (-53.095979) | 1.977465 / 6.876477 (-4.899011) | 2.222828 / 2.142072 (0.080755) | 0.588065 / 4.805227 (-4.217162) | 0.132175 / 6.500664 (-6.368489) | 0.061322 / 0.075469 (-0.014147) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.260623 / 1.841788 (-0.581164) | 19.976475 / 8.074308 (11.902167) | 14.346488 / 10.191392 (4.155096) | 0.145614 / 0.680424 (-0.534810) | 0.018309 / 0.534201 (-0.515892) | 0.393644 / 0.579283 (-0.185639) | 0.405355 / 0.434364 (-0.029009) | 0.458355 / 0.540337 (-0.081982) | 0.630147 / 1.386936 (-0.756789) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006769 / 0.011353 (-0.004584) | 0.004172 / 0.011008 (-0.006836) | 0.064863 / 0.038508 (0.026355) | 0.076831 / 0.023109 (0.053722) | 0.419391 / 0.275898 (0.143493) | 0.439912 / 0.323480 (0.116432) | 0.006249 / 0.007986 (-0.001737) | 0.003571 / 0.004328 (-0.000757) | 0.064877 / 0.004250 (0.060626) | 0.056023 / 0.037052 (0.018971) | 0.419899 / 0.258489 (0.161410) | 0.459334 / 0.293841 (0.165493) | 0.032217 / 0.128546 (-0.096329) | 0.008628 / 0.075646 (-0.067019) | 0.071089 / 0.419271 (-0.348183) | 0.047463 / 0.043533 (0.003930) | 0.414961 / 0.255139 (0.159822) | 0.431408 / 0.283200 (0.148209) | 0.022406 / 0.141683 (-0.119277) | 1.511890 / 1.452155 (0.059735) | 1.580268 / 1.492716 (0.087551) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.280805 / 0.018006 (0.262799) | 0.553766 / 0.000490 (0.553276) | 0.006155 / 0.000200 (0.005955) | 0.000102 / 0.000054 (0.000047) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.032980 / 0.037411 (-0.004431) | 0.092981 / 0.014526 (0.078456) | 0.108820 / 0.176557 (-0.067737) | 0.161709 / 0.737135 (-0.575426) | 0.109772 / 0.296338 (-0.186566) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.433659 / 0.215209 (0.218450) | 4.328577 / 2.077655 (2.250923) | 2.316899 / 1.504120 (0.812779) | 2.142645 / 1.541195 (0.601451) | 2.245518 / 1.468490 (0.777028) | 0.489448 / 4.584777 (-4.095329) | 3.630074 / 3.745712 (-0.115638) | 3.322749 / 5.269862 (-1.947112) | 2.062307 / 4.565676 (-2.503370) | 0.058153 / 0.424275 (-0.366122) | 0.007453 / 0.007607 (-0.000154) | 0.507234 / 0.226044 (0.281190) | 5.071830 / 2.268929 (2.802902) | 2.839374 / 55.444624 (-52.605250) | 2.429583 / 6.876477 (-4.446893) | 2.671940 / 2.142072 (0.529868) | 0.588256 / 4.805227 (-4.216972) | 0.135135 / 6.500664 (-6.365530) | 0.060963 / 0.075469 (-0.014506) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.337462 / 1.841788 (-0.504326) | 20.292912 / 8.074308 (12.218604) | 14.871809 / 10.191392 (4.680417) | 0.169214 / 0.680424 (-0.511209) | 0.020450 / 0.534201 (-0.513751) | 0.397094 / 0.579283 (-0.182189) | 0.411623 / 0.434364 (-0.022741) | 0.471560 / 0.540337 (-0.068777) | 0.647293 / 1.386936 (-0.739643) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#0a068dbf3b446417ffd89d32857608394ec699e6 \"CML watermark\")\n" ]

"2023-09-06T23:17:24Z"

"2023-09-07T15:48:07Z"

"2023-09-07T15:39:09Z"

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[]

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[ "Not a fan of pickling this sort of stuff either.\r\nNote that users can also share the code in their dataset documentation." ]

"2023-09-06T16:03:32Z"

"2023-09-06T18:32:07Z"

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6220). All of your documentation changes will be reflected on that endpoint.", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.005950 / 0.011353 (-0.005403) | 0.003578 / 0.011008 (-0.007431) | 0.079327 / 0.038508 (0.040819) | 0.057862 / 0.023109 (0.034752) | 0.317288 / 0.275898 (0.041390) | 0.358210 / 0.323480 (0.034730) | 0.004685 / 0.007986 (-0.003301) | 0.002879 / 0.004328 (-0.001450) | 0.062355 / 0.004250 (0.058105) | 0.045093 / 0.037052 (0.008041) | 0.322520 / 0.258489 (0.064031) | 0.367114 / 0.293841 (0.073273) | 0.027233 / 0.128546 (-0.101313) | 0.007941 / 0.075646 (-0.067705) | 0.260511 / 0.419271 (-0.158761) | 0.044355 / 0.043533 (0.000822) | 0.332993 / 0.255139 (0.077854) | 0.351363 / 0.283200 (0.068163) | 0.020784 / 0.141683 (-0.120899) | 1.429044 / 1.452155 (-0.023111) | 1.489355 / 1.492716 (-0.003362) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.180903 / 0.018006 (0.162897) | 0.421566 / 0.000490 (0.421077) | 0.003259 / 0.000200 (0.003059) | 0.000068 / 0.000054 (0.000014) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.023765 / 0.037411 (-0.013646) | 0.072815 / 0.014526 (0.058289) | 0.084592 / 0.176557 (-0.091965) | 0.143556 / 0.737135 (-0.593579) | 0.083591 / 0.296338 (-0.212748) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.401896 / 0.215209 (0.186687) | 4.006344 / 2.077655 (1.928689) | 2.092280 / 1.504120 (0.588160) | 1.937828 / 1.541195 (0.396633) | 2.026901 / 1.468490 (0.558411) | 0.499999 / 4.584777 (-4.084778) | 3.008715 / 3.745712 (-0.736997) | 2.789735 / 5.269862 (-2.480127) | 1.827319 / 4.565676 (-2.738358) | 0.057413 / 0.424275 (-0.366862) | 0.006716 / 0.007607 (-0.000891) | 0.473061 / 0.226044 (0.247016) | 4.733256 / 2.268929 (2.464327) | 2.403922 / 55.444624 (-53.040702) | 2.017466 / 6.876477 (-4.859011) | 2.209710 / 2.142072 (0.067638) | 0.590813 / 4.805227 (-4.214414) | 0.124760 / 6.500664 (-6.375904) | 0.060976 / 0.075469 (-0.014494) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.229172 / 1.841788 (-0.612616) | 17.924644 / 8.074308 (9.850336) | 13.697347 / 10.191392 (3.505955) | 0.128258 / 0.680424 (-0.552166) | 0.016780 / 0.534201 (-0.517421) | 0.329301 / 0.579283 (-0.249982) | 0.344527 / 0.434364 (-0.089837) | 0.379482 / 0.540337 (-0.160855) | 0.513851 / 1.386936 (-0.873085) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.005962 / 0.011353 (-0.005391) | 0.003613 / 0.011008 (-0.007396) | 0.062428 / 0.038508 (0.023920) | 0.058151 / 0.023109 (0.035042) | 0.452926 / 0.275898 (0.177027) | 0.489740 / 0.323480 (0.166260) | 0.006137 / 0.007986 (-0.001848) | 0.002890 / 0.004328 (-0.001438) | 0.062880 / 0.004250 (0.058629) | 0.046175 / 0.037052 (0.009123) | 0.452416 / 0.258489 (0.193927) | 0.486047 / 0.293841 (0.192206) | 0.028517 / 0.128546 (-0.100029) | 0.008102 / 0.075646 (-0.067544) | 0.068251 / 0.419271 (-0.351020) | 0.040569 / 0.043533 (-0.002964) | 0.461306 / 0.255139 (0.206167) | 0.477675 / 0.283200 (0.194475) | 0.020944 / 0.141683 (-0.120739) | 1.414300 / 1.452155 (-0.037855) | 1.502108 / 1.492716 (0.009391) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.217786 / 0.018006 (0.199780) | 0.410757 / 0.000490 (0.410267) | 0.002981 / 0.000200 (0.002781) | 0.000081 / 0.000054 (0.000027) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.026846 / 0.037411 (-0.010565) | 0.080098 / 0.014526 (0.065572) | 0.090591 / 0.176557 (-0.085965) | 0.144674 / 0.737135 (-0.592461) | 0.091287 / 0.296338 (-0.205052) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.458224 / 0.215209 (0.243015) | 4.590541 / 2.077655 (2.512886) | 2.511251 / 1.504120 (1.007131) | 2.329165 / 1.541195 (0.787970) | 2.379187 / 1.468490 (0.910696) | 0.507485 / 4.584777 (-4.077292) | 3.135011 / 3.745712 (-0.610701) | 2.805913 / 5.269862 (-2.463948) | 1.851382 / 4.565676 (-2.714295) | 0.057981 / 0.424275 (-0.366294) | 0.006557 / 0.007607 (-0.001050) | 0.532496 / 0.226044 (0.306452) | 5.348802 / 2.268929 (3.079874) | 2.993379 / 55.444624 (-52.451245) | 2.636372 / 6.876477 (-4.240104) | 2.753219 / 2.142072 (0.611147) | 0.591989 / 4.805227 (-4.213238) | 0.126691 / 6.500664 (-6.373973) | 0.062359 / 0.075469 (-0.013110) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.345498 / 1.841788 (-0.496290) | 18.335767 / 8.074308 (10.261458) | 15.115449 / 10.191392 (4.924057) | 0.147382 / 0.680424 (-0.533041) | 0.017729 / 0.534201 (-0.516472) | 0.334337 / 0.579283 (-0.244946) | 0.359035 / 0.434364 (-0.075329) | 0.386319 / 0.540337 (-0.154019) | 0.536378 / 1.386936 (-0.850558) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#f2b028fd83d74e7701e7b8f2d87e740a989505a7 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.009136 / 0.011353 (-0.002216) | 0.005567 / 0.011008 (-0.005442) | 0.120320 / 0.038508 (0.081812) | 0.078082 / 0.023109 (0.054973) | 0.405579 / 0.275898 (0.129681) | 0.459714 / 0.323480 (0.136234) | 0.006327 / 0.007986 (-0.001659) | 0.007187 / 0.004328 (0.002859) | 0.084373 / 0.004250 (0.080122) | 0.059727 / 0.037052 (0.022675) | 0.418918 / 0.258489 (0.160429) | 0.486767 / 0.293841 (0.192927) | 0.047715 / 0.128546 (-0.080831) | 0.014417 / 0.075646 (-0.061229) | 0.379847 / 0.419271 (-0.039425) | 0.067472 / 0.043533 (0.023939) | 0.419304 / 0.255139 (0.164166) | 0.466260 / 0.283200 (0.183060) | 0.036872 / 0.141683 (-0.104811) | 1.876273 / 1.452155 (0.424119) | 2.043856 / 1.492716 (0.551140) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.296266 / 0.018006 (0.278260) | 0.601843 / 0.000490 (0.601354) | 0.005663 / 0.000200 (0.005463) | 0.000102 / 0.000054 (0.000048) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.033272 / 0.037411 (-0.004139) | 0.098839 / 0.014526 (0.084313) | 0.124658 / 0.176557 (-0.051899) | 0.190226 / 0.737135 (-0.546909) | 0.119288 / 0.296338 (-0.177051) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.600878 / 0.215209 (0.385668) | 6.011749 / 2.077655 (3.934095) | 2.611809 / 1.504120 (1.107689) | 2.314985 / 1.541195 (0.773790) | 2.398988 / 1.468490 (0.930498) | 0.835577 / 4.584777 (-3.749200) | 5.482848 / 3.745712 (1.737136) | 4.965393 / 5.269862 (-0.304469) | 3.082420 / 4.565676 (-1.483256) | 0.098048 / 0.424275 (-0.326227) | 0.009148 / 0.007607 (0.001541) | 0.725721 / 0.226044 (0.499676) | 7.297429 / 2.268929 (5.028501) | 3.558050 / 55.444624 (-51.886575) | 2.815884 / 6.876477 (-4.060593) | 3.094103 / 2.142072 (0.952031) | 1.023617 / 4.805227 (-3.781610) | 0.222453 / 6.500664 (-6.278211) | 0.081707 / 0.075469 (0.006238) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.788327 / 1.841788 (-0.053461) | 25.285829 / 8.074308 (17.211521) | 21.878811 / 10.191392 (11.687419) | 0.215494 / 0.680424 (-0.464930) | 0.032050 / 0.534201 (-0.502151) | 0.505210 / 0.579283 (-0.074073) | 0.623545 / 0.434364 (0.189181) | 0.583342 / 0.540337 (0.043005) | 0.826497 / 1.386936 (-0.560439) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.009640 / 0.011353 (-0.001713) | 0.005479 / 0.011008 (-0.005529) | 0.088940 / 0.038508 (0.050432) | 0.084186 / 0.023109 (0.061077) | 0.552290 / 0.275898 (0.276392) | 0.583296 / 0.323480 (0.259816) | 0.006999 / 0.007986 (-0.000987) | 0.004597 / 0.004328 (0.000269) | 0.089407 / 0.004250 (0.085157) | 0.067210 / 0.037052 (0.030157) | 0.554968 / 0.258489 (0.296479) | 0.595635 / 0.293841 (0.301794) | 0.052245 / 0.128546 (-0.076301) | 0.015914 / 0.075646 (-0.059733) | 0.097037 / 0.419271 (-0.322235) | 0.063954 / 0.043533 (0.020421) | 0.533752 / 0.255139 (0.278614) | 0.573789 / 0.283200 (0.290589) | 0.036526 / 0.141683 (-0.105157) | 1.867713 / 1.452155 (0.415558) | 1.996901 / 1.492716 (0.504185) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.414967 / 0.018006 (0.396961) | 0.632367 / 0.000490 (0.631877) | 0.064061 / 0.000200 (0.063861) | 0.000565 / 0.000054 (0.000510) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.035953 / 0.037411 (-0.001458) | 0.112603 / 0.014526 (0.098077) | 0.126227 / 0.176557 (-0.050330) | 0.196881 / 0.737135 (-0.540255) | 0.127635 / 0.296338 (-0.168704) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.674735 / 0.215209 (0.459526) | 6.614578 / 2.077655 (4.536923) | 3.208198 / 1.504120 (1.704078) | 2.870412 / 1.541195 (1.329217) | 2.979358 / 1.468490 (1.510868) | 0.872589 / 4.584777 (-3.712187) | 5.501771 / 3.745712 (1.756059) | 4.865191 / 5.269862 (-0.404671) | 3.075281 / 4.565676 (-1.490396) | 0.098048 / 0.424275 (-0.326227) | 0.009121 / 0.007607 (0.001514) | 0.801639 / 0.226044 (0.575595) | 8.062040 / 2.268929 (5.793111) | 3.996693 / 55.444624 (-51.447931) | 3.343770 / 6.876477 (-3.532706) | 3.555977 / 2.142072 (1.413904) | 1.035050 / 4.805227 (-3.770177) | 0.227552 / 6.500664 (-6.273112) | 0.097733 / 0.075469 (0.022264) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.897210 / 1.841788 (0.055422) | 25.762459 / 8.074308 (17.688151) | 22.771290 / 10.191392 (12.579898) | 0.252650 / 0.680424 (-0.427773) | 0.032534 / 0.534201 (-0.501667) | 0.521047 / 0.579283 (-0.058236) | 0.620850 / 0.434364 (0.186486) | 0.612750 / 0.540337 (0.072413) | 0.837486 / 1.386936 (-0.549451) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#1f522e5bdd73c45f7ba0a03f2ecd4e7de7351f2e \"CML watermark\")\n" ]

"2023-09-06T15:40:33Z"

"2023-09-06T15:52:33Z"

"2023-09-06T15:41:13Z"

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[]

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6219). All of your documentation changes will be reflected on that endpoint.", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.009523 / 0.011353 (-0.001830) | 0.005105 / 0.011008 (-0.005903) | 0.122664 / 0.038508 (0.084156) | 0.084688 / 0.023109 (0.061579) | 0.412057 / 0.275898 (0.136159) | 0.449690 / 0.323480 (0.126210) | 0.006627 / 0.007986 (-0.001358) | 0.004150 / 0.004328 (-0.000178) | 0.082079 / 0.004250 (0.077829) | 0.065289 / 0.037052 (0.028237) | 0.432934 / 0.258489 (0.174445) | 0.492068 / 0.293841 (0.198227) | 0.048317 / 0.128546 (-0.080229) | 0.015582 / 0.075646 (-0.060064) | 0.372050 / 0.419271 (-0.047222) | 0.070649 / 0.043533 (0.027116) | 0.431754 / 0.255139 (0.176615) | 0.473349 / 0.283200 (0.190149) | 0.037293 / 0.141683 (-0.104390) | 1.807537 / 1.452155 (0.355382) | 1.923073 / 1.492716 (0.430357) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.271214 / 0.018006 (0.253208) | 0.592961 / 0.000490 (0.592471) | 0.004062 / 0.000200 (0.003862) | 0.000089 / 0.000054 (0.000035) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.034766 / 0.037411 (-0.002645) | 0.093014 / 0.014526 (0.078488) | 0.131332 / 0.176557 (-0.045225) | 0.188110 / 0.737135 (-0.549025) | 0.117617 / 0.296338 (-0.178722) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.668223 / 0.215209 (0.453013) | 6.707031 / 2.077655 (4.629376) | 3.040178 / 1.504120 (1.536058) | 2.641776 / 1.541195 (1.100581) | 2.524057 / 1.468490 (1.055567) | 0.893592 / 4.584777 (-3.691185) | 5.535848 / 3.745712 (1.790136) | 4.867067 / 5.269862 (-0.402794) | 2.999933 / 4.565676 (-1.565743) | 0.103602 / 0.424275 (-0.320673) | 0.008887 / 0.007607 (0.001280) | 0.822214 / 0.226044 (0.596169) | 8.028476 / 2.268929 (5.759547) | 3.708895 / 55.444624 (-51.735730) | 2.858314 / 6.876477 (-4.018163) | 3.101727 / 2.142072 (0.959655) | 1.083136 / 4.805227 (-3.722091) | 0.219588 / 6.500664 (-6.281076) | 0.080151 / 0.075469 (0.004682) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.645819 / 1.841788 (-0.195969) | 24.407887 / 8.074308 (16.333579) | 22.371901 / 10.191392 (12.180509) | 0.219557 / 0.680424 (-0.460867) | 0.037867 / 0.534201 (-0.496334) | 0.484136 / 0.579283 (-0.095147) | 0.620546 / 0.434364 (0.186182) | 0.562272 / 0.540337 (0.021934) | 0.774256 / 1.386936 (-0.612680) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.009381 / 0.011353 (-0.001972) | 0.005565 / 0.011008 (-0.005444) | 0.091057 / 0.038508 (0.052549) | 0.078085 / 0.023109 (0.054975) | 0.538929 / 0.275898 (0.263031) | 0.555155 / 0.323480 (0.231675) | 0.007007 / 0.007986 (-0.000978) | 0.004268 / 0.004328 (-0.000060) | 0.086618 / 0.004250 (0.082368) | 0.064117 / 0.037052 (0.027065) | 0.523788 / 0.258489 (0.265299) | 0.586451 / 0.293841 (0.292610) | 0.050804 / 0.128546 (-0.077742) | 0.013964 / 0.075646 (-0.061682) | 0.096008 / 0.419271 (-0.323263) | 0.062242 / 0.043533 (0.018709) | 0.530398 / 0.255139 (0.275259) | 0.568527 / 0.283200 (0.285327) | 0.032456 / 0.141683 (-0.109227) | 1.894975 / 1.452155 (0.442820) | 2.084172 / 1.492716 (0.591455) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.295539 / 0.018006 (0.277533) | 0.588804 / 0.000490 (0.588314) | 0.006445 / 0.000200 (0.006245) | 0.000113 / 0.000054 (0.000059) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.033965 / 0.037411 (-0.003447) | 0.111743 / 0.014526 (0.097217) | 0.128805 / 0.176557 (-0.047752) | 0.185013 / 0.737135 (-0.552123) | 0.129400 / 0.296338 (-0.166938) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.749784 / 0.215209 (0.534575) | 7.091075 / 2.077655 (5.013420) | 3.424517 / 1.504120 (1.920397) | 3.069103 / 1.541195 (1.527908) | 3.122431 / 1.468490 (1.653941) | 0.949277 / 4.584777 (-3.635500) | 5.648731 / 3.745712 (1.903019) | 4.937684 / 5.269862 (-0.332178) | 3.198027 / 4.565676 (-1.367650) | 0.100289 / 0.424275 (-0.323987) | 0.009411 / 0.007607 (0.001803) | 0.862604 / 0.226044 (0.636559) | 8.615410 / 2.268929 (6.346482) | 4.306428 / 55.444624 (-51.138196) | 3.591404 / 6.876477 (-3.285073) | 3.823899 / 2.142072 (1.681827) | 1.108006 / 4.805227 (-3.697221) | 0.215330 / 6.500664 (-6.285334) | 0.080755 / 0.075469 (0.005286) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.774914 / 1.841788 (-0.066873) | 25.360983 / 8.074308 (17.286675) | 23.624044 / 10.191392 (13.432652) | 0.226887 / 0.680424 (-0.453537) | 0.032625 / 0.534201 (-0.501576) | 0.499730 / 0.579283 (-0.079553) | 0.647819 / 0.434364 (0.213455) | 0.592239 / 0.540337 (0.051901) | 0.805751 / 1.386936 (-0.581185) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#0daa82428a0529478801574bcc68e1ed32051f3a \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008656 / 0.011353 (-0.002697) | 0.005545 / 0.011008 (-0.005463) | 0.107936 / 0.038508 (0.069428) | 0.077436 / 0.023109 (0.054327) | 0.391412 / 0.275898 (0.115514) | 0.452811 / 0.323480 (0.129331) | 0.004883 / 0.007986 (-0.003103) | 0.005125 / 0.004328 (0.000796) | 0.080006 / 0.004250 (0.075755) | 0.054425 / 0.037052 (0.017373) | 0.399667 / 0.258489 (0.141178) | 0.458099 / 0.293841 (0.164258) | 0.047302 / 0.128546 (-0.081244) | 0.014153 / 0.075646 (-0.061493) | 0.337281 / 0.419271 (-0.081991) | 0.062153 / 0.043533 (0.018620) | 0.399927 / 0.255139 (0.144788) | 0.407186 / 0.283200 (0.123987) | 0.036759 / 0.141683 (-0.104924) | 1.825935 / 1.452155 (0.373780) | 1.852238 / 1.492716 (0.359522) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.274163 / 0.018006 (0.256157) | 0.615624 / 0.000490 (0.615134) | 0.003782 / 0.000200 (0.003582) | 0.000115 / 0.000054 (0.000060) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.026386 / 0.037411 (-0.011026) | 0.101151 / 0.014526 (0.086625) | 0.106115 / 0.176557 (-0.070442) | 0.161253 / 0.737135 (-0.575882) | 0.108861 / 0.296338 (-0.187478) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.587079 / 0.215209 (0.371870) | 6.141743 / 2.077655 (4.064089) | 2.727199 / 1.504120 (1.223079) | 2.526827 / 1.541195 (0.985632) | 2.598321 / 1.468490 (1.129831) | 0.904706 / 4.584777 (-3.680071) | 5.227742 / 3.745712 (1.482030) | 4.621627 / 5.269862 (-0.648234) | 2.931792 / 4.565676 (-1.633885) | 0.089538 / 0.424275 (-0.334737) | 0.008281 / 0.007607 (0.000674) | 0.675773 / 0.226044 (0.449729) | 7.212869 / 2.268929 (4.943941) | 3.541569 / 55.444624 (-51.903056) | 2.804034 / 6.876477 (-4.072443) | 3.080192 / 2.142072 (0.938120) | 1.034577 / 4.805227 (-3.770650) | 0.218727 / 6.500664 (-6.281937) | 0.084548 / 0.075469 (0.009079) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.528974 / 1.841788 (-0.312814) | 21.754329 / 8.074308 (13.680021) | 20.359808 / 10.191392 (10.168416) | 0.234719 / 0.680424 (-0.445705) | 0.026182 / 0.534201 (-0.508019) | 0.448956 / 0.579283 (-0.130327) | 0.577015 / 0.434364 (0.142651) | 0.513675 / 0.540337 (-0.026662) | 0.729780 / 1.386936 (-0.657156) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.010427 / 0.011353 (-0.000926) | 0.005126 / 0.011008 (-0.005882) | 0.082759 / 0.038508 (0.044251) | 0.084892 / 0.023109 (0.061783) | 0.543826 / 0.275898 (0.267927) | 0.603050 / 0.323480 (0.279570) | 0.006667 / 0.007986 (-0.001319) | 0.004036 / 0.004328 (-0.000292) | 0.079534 / 0.004250 (0.075283) | 0.067523 / 0.037052 (0.030471) | 0.544845 / 0.258489 (0.286356) | 0.578823 / 0.293841 (0.284982) | 0.054786 / 0.128546 (-0.073760) | 0.014888 / 0.075646 (-0.060759) | 0.095696 / 0.419271 (-0.323576) | 0.064908 / 0.043533 (0.021375) | 0.558087 / 0.255139 (0.302948) | 0.593919 / 0.283200 (0.310719) | 0.039190 / 0.141683 (-0.102493) | 1.828680 / 1.452155 (0.376526) | 1.908891 / 1.492716 (0.416174) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.298926 / 0.018006 (0.280920) | 0.589467 / 0.000490 (0.588977) | 0.005276 / 0.000200 (0.005076) | 0.000112 / 0.000054 (0.000057) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.034300 / 0.037411 (-0.003111) | 0.096990 / 0.014526 (0.082464) | 0.109347 / 0.176557 (-0.067209) | 0.171312 / 0.737135 (-0.565823) | 0.121736 / 0.296338 (-0.174603) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.641619 / 0.215209 (0.426410) | 6.365556 / 2.077655 (4.287901) | 2.947989 / 1.504120 (1.443869) | 2.631680 / 1.541195 (1.090485) | 2.602762 / 1.468490 (1.134272) | 0.812767 / 4.584777 (-3.772010) | 5.185753 / 3.745712 (1.440041) | 4.589897 / 5.269862 (-0.679964) | 2.833020 / 4.565676 (-1.732656) | 0.097782 / 0.424275 (-0.326493) | 0.008625 / 0.007607 (0.001018) | 0.741613 / 0.226044 (0.515568) | 7.662905 / 2.268929 (5.393976) | 3.533753 / 55.444624 (-51.910871) | 2.898929 / 6.876477 (-3.977547) | 3.042616 / 2.142072 (0.900544) | 0.933932 / 4.805227 (-3.871296) | 0.195710 / 6.500664 (-6.304954) | 0.066954 / 0.075469 (-0.008515) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.745353 / 1.841788 (-0.096434) | 23.820840 / 8.074308 (15.746532) | 20.892645 / 10.191392 (10.701253) | 0.234853 / 0.680424 (-0.445571) | 0.029149 / 0.534201 (-0.505051) | 0.458953 / 0.579283 (-0.120330) | 0.594278 / 0.434364 (0.159914) | 0.522929 / 0.540337 (-0.017409) | 0.753731 / 1.386936 (-0.633205) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#de6391d732ea0471ee5bdfb91b8cecc4503da96b \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.005976 / 0.011353 (-0.005377) | 0.003636 / 0.011008 (-0.007372) | 0.079946 / 0.038508 (0.041437) | 0.060143 / 0.023109 (0.037034) | 0.314752 / 0.275898 (0.038854) | 0.353714 / 0.323480 (0.030234) | 0.004706 / 0.007986 (-0.003280) | 0.002862 / 0.004328 (-0.001466) | 0.061988 / 0.004250 (0.057737) | 0.045907 / 0.037052 (0.008855) | 0.316118 / 0.258489 (0.057629) | 0.358488 / 0.293841 (0.064647) | 0.027377 / 0.128546 (-0.101170) | 0.007970 / 0.075646 (-0.067677) | 0.261677 / 0.419271 (-0.157594) | 0.045289 / 0.043533 (0.001757) | 0.307931 / 0.255139 (0.052792) | 0.341364 / 0.283200 (0.058165) | 0.021021 / 0.141683 (-0.120662) | 1.440002 / 1.452155 (-0.012153) | 1.502904 / 1.492716 (0.010187) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.201746 / 0.018006 (0.183740) | 0.451114 / 0.000490 (0.450624) | 0.003351 / 0.000200 (0.003151) | 0.000067 / 0.000054 (0.000013) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.024233 / 0.037411 (-0.013178) | 0.075042 / 0.014526 (0.060516) | 0.085636 / 0.176557 (-0.090920) | 0.144699 / 0.737135 (-0.592436) | 0.085222 / 0.296338 (-0.211117) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.389464 / 0.215209 (0.174255) | 3.889072 / 2.077655 (1.811417) | 1.908307 / 1.504120 (0.404187) | 1.738914 / 1.541195 (0.197719) | 1.866869 / 1.468490 (0.398379) | 0.500536 / 4.584777 (-4.084240) | 3.050155 / 3.745712 (-0.695557) | 2.832259 / 5.269862 (-2.437602) | 1.886657 / 4.565676 (-2.679020) | 0.059214 / 0.424275 (-0.365062) | 0.006711 / 0.007607 (-0.000896) | 0.467753 / 0.226044 (0.241709) | 4.666939 / 2.268929 (2.398011) | 2.471168 / 55.444624 (-52.973456) | 2.223508 / 6.876477 (-4.652968) | 2.176543 / 2.142072 (0.034470) | 0.593461 / 4.805227 (-4.211766) | 0.126216 / 6.500664 (-6.374448) | 0.061495 / 0.075469 (-0.013974) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.301279 / 1.841788 (-0.540509) | 18.317461 / 8.074308 (10.243153) | 13.877813 / 10.191392 (3.686421) | 0.143510 / 0.680424 (-0.536914) | 0.016826 / 0.534201 (-0.517375) | 0.328735 / 0.579283 (-0.250548) | 0.342272 / 0.434364 (-0.092092) | 0.375768 / 0.540337 (-0.164570) | 0.517600 / 1.386936 (-0.869336) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006215 / 0.011353 (-0.005138) | 0.003587 / 0.011008 (-0.007422) | 0.062248 / 0.038508 (0.023740) | 0.059830 / 0.023109 (0.036721) | 0.443278 / 0.275898 (0.167380) | 0.481279 / 0.323480 (0.157799) | 0.004773 / 0.007986 (-0.003213) | 0.002870 / 0.004328 (-0.001459) | 0.062730 / 0.004250 (0.058480) | 0.049422 / 0.037052 (0.012369) | 0.444196 / 0.258489 (0.185707) | 0.498614 / 0.293841 (0.204773) | 0.028477 / 0.128546 (-0.100069) | 0.008009 / 0.075646 (-0.067638) | 0.067919 / 0.419271 (-0.351352) | 0.040416 / 0.043533 (-0.003117) | 0.439460 / 0.255139 (0.184321) | 0.470529 / 0.283200 (0.187329) | 0.020767 / 0.141683 (-0.120916) | 1.478223 / 1.452155 (0.026068) | 1.538580 / 1.492716 (0.045863) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.271321 / 0.018006 (0.253315) | 0.456436 / 0.000490 (0.455946) | 0.011817 / 0.000200 (0.011617) | 0.000115 / 0.000054 (0.000061) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.026355 / 0.037411 (-0.011056) | 0.081681 / 0.014526 (0.067155) | 0.091699 / 0.176557 (-0.084858) | 0.146115 / 0.737135 (-0.591021) | 0.094376 / 0.296338 (-0.201963) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.471677 / 0.215209 (0.256468) | 4.702909 / 2.077655 (2.625254) | 2.664882 / 1.504120 (1.160762) | 2.504106 / 1.541195 (0.962911) | 2.573226 / 1.468490 (1.104736) | 0.509679 / 4.584777 (-4.075097) | 3.034970 / 3.745712 (-0.710742) | 2.894704 / 5.269862 (-2.375157) | 1.915148 / 4.565676 (-2.650528) | 0.058312 / 0.424275 (-0.365963) | 0.006615 / 0.007607 (-0.000993) | 0.545339 / 0.226044 (0.319295) | 5.462261 / 2.268929 (3.193332) | 3.101482 / 55.444624 (-52.343143) | 2.755417 / 6.876477 (-4.121060) | 2.931440 / 2.142072 (0.789368) | 0.597521 / 4.805227 (-4.207707) | 0.125676 / 6.500664 (-6.374988) | 0.061798 / 0.075469 (-0.013671) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.356208 / 1.841788 (-0.485579) | 18.912492 / 8.074308 (10.838184) | 14.830128 / 10.191392 (4.638736) | 0.145992 / 0.680424 (-0.534432) | 0.019121 / 0.534201 (-0.515080) | 0.331534 / 0.579283 (-0.247749) | 0.361712 / 0.434364 (-0.072652) | 0.387532 / 0.540337 (-0.152805) | 0.536075 / 1.386936 (-0.850861) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#de6391d732ea0471ee5bdfb91b8cecc4503da96b \"CML watermark\")\n" ]

"2023-09-06T15:17:10Z"

"2023-09-06T15:46:20Z"

"2023-09-06T15:18:51Z"

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[ "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006529 / 0.011353 (-0.004823) | 0.004010 / 0.011008 (-0.006998) | 0.086258 / 0.038508 (0.047750) | 0.073775 / 0.023109 (0.050666) | 0.307573 / 0.275898 (0.031675) | 0.337091 / 0.323480 (0.013611) | 0.004251 / 0.007986 (-0.003735) | 0.003886 / 0.004328 (-0.000443) | 0.068238 / 0.004250 (0.063987) | 0.057000 / 0.037052 (0.019948) | 0.321751 / 0.258489 (0.063262) | 0.359227 / 0.293841 (0.065386) | 0.030841 / 0.128546 (-0.097705) | 0.008569 / 0.075646 (-0.067078) | 0.299523 / 0.419271 (-0.119748) | 0.052563 / 0.043533 (0.009030) | 0.312806 / 0.255139 (0.057667) | 0.342273 / 0.283200 (0.059074) | 0.025725 / 0.141683 (-0.115958) | 1.479263 / 1.452155 (0.027108) | 1.554975 / 1.492716 (0.062259) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.316328 / 0.018006 (0.298322) | 0.598993 / 0.000490 (0.598503) | 0.004548 / 0.000200 (0.004348) | 0.000080 / 0.000054 (0.000026) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.027399 / 0.037411 (-0.010013) | 0.081683 / 0.014526 (0.067157) | 0.096968 / 0.176557 (-0.079589) | 0.151559 / 0.737135 (-0.585576) | 0.096558 / 0.296338 (-0.199781) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.383117 / 0.215209 (0.167908) | 3.818634 / 2.077655 (1.740979) | 1.878112 / 1.504120 (0.373992) | 1.729031 / 1.541195 (0.187836) | 1.770259 / 1.468490 (0.301769) | 0.484061 / 4.584777 (-4.100716) | 3.596998 / 3.745712 (-0.148715) | 3.246846 / 5.269862 (-2.023016) | 2.019481 / 4.565676 (-2.546195) | 0.057279 / 0.424275 (-0.366996) | 0.007455 / 0.007607 (-0.000152) | 0.465002 / 0.226044 (0.238958) | 4.644669 / 2.268929 (2.375741) | 2.346415 / 55.444624 (-53.098209) | 2.039686 / 6.876477 (-4.836791) | 2.172822 / 2.142072 (0.030750) | 0.582925 / 4.805227 (-4.222302) | 0.134246 / 6.500664 (-6.366418) | 0.060093 / 0.075469 (-0.015376) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.249033 / 1.841788 (-0.592755) | 19.585949 / 8.074308 (11.511641) | 14.100681 / 10.191392 (3.909289) | 0.147138 / 0.680424 (-0.533286) | 0.018307 / 0.534201 (-0.515894) | 0.397939 / 0.579283 (-0.181344) | 0.413916 / 0.434364 (-0.020448) | 0.465688 / 0.540337 (-0.074650) | 0.642140 / 1.386936 (-0.744797) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006627 / 0.011353 (-0.004726) | 0.004173 / 0.011008 (-0.006835) | 0.063850 / 0.038508 (0.025342) | 0.074733 / 0.023109 (0.051623) | 0.398111 / 0.275898 (0.122213) | 0.426344 / 0.323480 (0.102864) | 0.006261 / 0.007986 (-0.001725) | 0.003507 / 0.004328 (-0.000822) | 0.064511 / 0.004250 (0.060260) | 0.056508 / 0.037052 (0.019456) | 0.401750 / 0.258489 (0.143261) | 0.437081 / 0.293841 (0.143240) | 0.031815 / 0.128546 (-0.096732) | 0.008703 / 0.075646 (-0.066943) | 0.071411 / 0.419271 (-0.347861) | 0.048153 / 0.043533 (0.004620) | 0.399221 / 0.255139 (0.144082) | 0.429312 / 0.283200 (0.146112) | 0.022157 / 0.141683 (-0.119526) | 1.485656 / 1.452155 (0.033502) | 1.550967 / 1.492716 (0.058250) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.330575 / 0.018006 (0.312569) | 0.525553 / 0.000490 (0.525064) | 0.004574 / 0.000200 (0.004374) | 0.000093 / 0.000054 (0.000038) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.031871 / 0.037411 (-0.005541) | 0.091819 / 0.014526 (0.077293) | 0.105542 / 0.176557 (-0.071015) | 0.158210 / 0.737135 (-0.578926) | 0.107167 / 0.296338 (-0.189172) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.430226 / 0.215209 (0.215017) | 4.293456 / 2.077655 (2.215801) | 2.289538 / 1.504120 (0.785418) | 2.122255 / 1.541195 (0.581060) | 2.181840 / 1.468490 (0.713350) | 0.498529 / 4.584777 (-4.086248) | 3.686636 / 3.745712 (-0.059077) | 3.287279 / 5.269862 (-1.982582) | 2.068397 / 4.565676 (-2.497280) | 0.058775 / 0.424275 (-0.365500) | 0.007583 / 0.007607 (-0.000024) | 0.507165 / 0.226044 (0.281121) | 5.072330 / 2.268929 (2.803401) | 2.796396 / 55.444624 (-52.648228) | 2.409946 / 6.876477 (-4.466531) | 2.657322 / 2.142072 (0.515250) | 0.597744 / 4.805227 (-4.207483) | 0.133803 / 6.500664 (-6.366861) | 0.060231 / 0.075469 (-0.015238) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.333130 / 1.841788 (-0.508658) | 20.545936 / 8.074308 (12.471627) | 14.875020 / 10.191392 (4.683628) | 0.168873 / 0.680424 (-0.511551) | 0.020316 / 0.534201 (-0.513885) | 0.397203 / 0.579283 (-0.182080) | 0.412412 / 0.434364 (-0.021952) | 0.479952 / 0.540337 (-0.060385) | 0.657155 / 1.386936 (-0.729781) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#13fbee4ca8742460e9baab86a89d9100a294df3e \"CML watermark\")\n", "_The documentation is not available anymore as the PR was closed or merged._", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007885 / 0.011353 (-0.003468) | 0.005221 / 0.011008 (-0.005787) | 0.099457 / 0.038508 (0.060949) | 0.085867 / 0.023109 (0.062758) | 0.359922 / 0.275898 (0.084024) | 0.406479 / 0.323480 (0.082999) | 0.005001 / 0.007986 (-0.002985) | 0.003678 / 0.004328 (-0.000650) | 0.075647 / 0.004250 (0.071396) | 0.064318 / 0.037052 (0.027265) | 0.372180 / 0.258489 (0.113691) | 0.419206 / 0.293841 (0.125365) | 0.040438 / 0.128546 (-0.088108) | 0.010008 / 0.075646 (-0.065638) | 0.340911 / 0.419271 (-0.078360) | 0.063326 / 0.043533 (0.019793) | 0.359015 / 0.255139 (0.103876) | 0.408601 / 0.283200 (0.125402) | 0.029828 / 0.141683 (-0.111855) | 1.767822 / 1.452155 (0.315667) | 1.829079 / 1.492716 (0.336363) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.234455 / 0.018006 (0.216449) | 0.507786 / 0.000490 (0.507297) | 0.004009 / 0.000200 (0.003809) | 0.000101 / 0.000054 (0.000046) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.033374 / 0.037411 (-0.004038) | 0.100817 / 0.014526 (0.086291) | 0.113415 / 0.176557 (-0.063141) | 0.180368 / 0.737135 (-0.556768) | 0.115446 / 0.296338 (-0.180893) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.488976 / 0.215209 (0.273767) | 4.911354 / 2.077655 (2.833699) | 2.623525 / 1.504120 (1.119405) | 2.424400 / 1.541195 (0.883206) | 2.497580 / 1.468490 (1.029089) | 0.561106 / 4.584777 (-4.023671) | 4.265649 / 3.745712 (0.519937) | 3.830267 / 5.269862 (-1.439595) | 2.404727 / 4.565676 (-2.160949) | 0.067303 / 0.424275 (-0.356972) | 0.009177 / 0.007607 (0.001570) | 0.588433 / 0.226044 (0.362388) | 5.871573 / 2.268929 (3.602645) | 3.087845 / 55.444624 (-52.356779) | 2.765381 / 6.876477 (-4.111096) | 3.007863 / 2.142072 (0.865791) | 0.687327 / 4.805227 (-4.117901) | 0.157687 / 6.500664 (-6.342977) | 0.071291 / 0.075469 (-0.004178) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.510931 / 1.841788 (-0.330857) | 22.129590 / 8.074308 (14.055282) | 16.780479 / 10.191392 (6.589087) | 0.168297 / 0.680424 (-0.512127) | 0.021294 / 0.534201 (-0.512907) | 0.464535 / 0.579283 (-0.114748) | 0.480041 / 0.434364 (0.045677) | 0.549185 / 0.540337 (0.008848) | 0.739438 / 1.386936 (-0.647498) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007834 / 0.011353 (-0.003518) | 0.004576 / 0.011008 (-0.006432) | 0.073331 / 0.038508 (0.034823) | 0.084688 / 0.023109 (0.061579) | 0.486367 / 0.275898 (0.210469) | 0.523127 / 0.323480 (0.199647) | 0.006278 / 0.007986 (-0.001708) | 0.003792 / 0.004328 (-0.000537) | 0.075416 / 0.004250 (0.071166) | 0.064053 / 0.037052 (0.027001) | 0.491908 / 0.258489 (0.233419) | 0.529177 / 0.293841 (0.235336) | 0.038483 / 0.128546 (-0.090063) | 0.009560 / 0.075646 (-0.066087) | 0.083431 / 0.419271 (-0.335841) | 0.057114 / 0.043533 (0.013581) | 0.486316 / 0.255139 (0.231177) | 0.512384 / 0.283200 (0.229185) | 0.028452 / 0.141683 (-0.113231) | 1.788886 / 1.452155 (0.336731) | 1.893834 / 1.492716 (0.401118) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.343018 / 0.018006 (0.325011) | 0.513673 / 0.000490 (0.513183) | 0.056778 / 0.000200 (0.056578) | 0.001799 / 0.000054 (0.001745) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.038530 / 0.037411 (0.001119) | 0.109286 / 0.014526 (0.094760) | 0.122812 / 0.176557 (-0.053745) | 0.187780 / 0.737135 (-0.549355) | 0.124083 / 0.296338 (-0.172255) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.509839 / 0.215209 (0.294630) | 5.085840 / 2.077655 (3.008186) | 2.746695 / 1.504120 (1.242575) | 2.542283 / 1.541195 (1.001088) | 2.650243 / 1.468490 (1.181753) | 0.592801 / 4.584777 (-3.991976) | 4.316721 / 3.745712 (0.571009) | 3.811672 / 5.269862 (-1.458189) | 2.433982 / 4.565676 (-2.131695) | 0.066861 / 0.424275 (-0.357414) | 0.008633 / 0.007607 (0.001026) | 0.590482 / 0.226044 (0.364437) | 5.923484 / 2.268929 (3.654556) | 3.282293 / 55.444624 (-52.162332) | 2.882716 / 6.876477 (-3.993761) | 3.139581 / 2.142072 (0.997509) | 0.690702 / 4.805227 (-4.114525) | 0.156781 / 6.500664 (-6.343883) | 0.071487 / 0.075469 (-0.003982) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.604557 / 1.841788 (-0.237231) | 24.000026 / 8.074308 (15.925718) | 17.548685 / 10.191392 (7.357293) | 0.174883 / 0.680424 (-0.505541) | 0.023812 / 0.534201 (-0.510389) | 0.473522 / 0.579283 (-0.105761) | 0.494683 / 0.434364 (0.060319) | 0.593352 / 0.540337 (0.053015) | 0.771852 / 1.386936 (-0.615084) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#b61c96a806fa97800bc8a66607fb0c78a5d04146 \"CML watermark\")\n", "thanks! i wonder if we should also fix (change config name) all the old `dataset_infos.json` on the Hub?", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006388 / 0.011353 (-0.004965) | 0.003876 / 0.011008 (-0.007132) | 0.083960 / 0.038508 (0.045452) | 0.068328 / 0.023109 (0.045219) | 0.337958 / 0.275898 (0.062060) | 0.370783 / 0.323480 (0.047303) | 0.003925 / 0.007986 (-0.004060) | 0.004221 / 0.004328 (-0.000107) | 0.064198 / 0.004250 (0.059947) | 0.052681 / 0.037052 (0.015629) | 0.348890 / 0.258489 (0.090401) | 0.389038 / 0.293841 (0.095197) | 0.031133 / 0.128546 (-0.097413) | 0.008566 / 0.075646 (-0.067080) | 0.288169 / 0.419271 (-0.131102) | 0.053290 / 0.043533 (0.009757) | 0.344654 / 0.255139 (0.089515) | 0.381287 / 0.283200 (0.098087) | 0.022350 / 0.141683 (-0.119333) | 1.459933 / 1.452155 (0.007778) | 1.543097 / 1.492716 (0.050380) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.212592 / 0.018006 (0.194586) | 0.461863 / 0.000490 (0.461373) | 0.003468 / 0.000200 (0.003268) | 0.000084 / 0.000054 (0.000029) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.026849 / 0.037411 (-0.010563) | 0.081059 / 0.014526 (0.066533) | 0.093986 / 0.176557 (-0.082571) | 0.150328 / 0.737135 (-0.586807) | 0.094253 / 0.296338 (-0.202085) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.382198 / 0.215209 (0.166989) | 3.813878 / 2.077655 (1.736224) | 1.855686 / 1.504120 (0.351566) | 1.672995 / 1.541195 (0.131800) | 1.697705 / 1.468490 (0.229215) | 0.479920 / 4.584777 (-4.104857) | 3.608305 / 3.745712 (-0.137407) | 3.216712 / 5.269862 (-2.053149) | 1.984781 / 4.565676 (-2.580896) | 0.056801 / 0.424275 (-0.367475) | 0.007499 / 0.007607 (-0.000108) | 0.454155 / 0.226044 (0.228110) | 4.531147 / 2.268929 (2.262218) | 2.296149 / 55.444624 (-53.148475) | 1.968701 / 6.876477 (-4.907775) | 2.144286 / 2.142072 (0.002213) | 0.599254 / 4.805227 (-4.205973) | 0.138150 / 6.500664 (-6.362514) | 0.060118 / 0.075469 (-0.015351) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.282486 / 1.841788 (-0.559301) | 19.127792 / 8.074308 (11.053483) | 14.116521 / 10.191392 (3.925129) | 0.163792 / 0.680424 (-0.516632) | 0.018116 / 0.534201 (-0.516085) | 0.390789 / 0.579283 (-0.188494) | 0.409241 / 0.434364 (-0.025123) | 0.457824 / 0.540337 (-0.082513) | 0.624390 / 1.386936 (-0.762546) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006637 / 0.011353 (-0.004716) | 0.003932 / 0.011008 (-0.007076) | 0.063456 / 0.038508 (0.024948) | 0.070062 / 0.023109 (0.046953) | 0.410570 / 0.275898 (0.134672) | 0.436700 / 0.323480 (0.113220) | 0.005324 / 0.007986 (-0.002662) | 0.003263 / 0.004328 (-0.001065) | 0.063590 / 0.004250 (0.059340) | 0.054823 / 0.037052 (0.017770) | 0.408720 / 0.258489 (0.150231) | 0.441493 / 0.293841 (0.147652) | 0.031655 / 0.128546 (-0.096891) | 0.008421 / 0.075646 (-0.067225) | 0.070657 / 0.419271 (-0.348614) | 0.047370 / 0.043533 (0.003837) | 0.408217 / 0.255139 (0.153078) | 0.422178 / 0.283200 (0.138978) | 0.022282 / 0.141683 (-0.119401) | 1.511417 / 1.452155 (0.059262) | 1.570337 / 1.492716 (0.077620) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.224334 / 0.018006 (0.206327) | 0.447589 / 0.000490 (0.447099) | 0.004227 / 0.000200 (0.004027) | 0.000099 / 0.000054 (0.000045) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.030797 / 0.037411 (-0.006615) | 0.091276 / 0.014526 (0.076750) | 0.102665 / 0.176557 (-0.073892) | 0.155423 / 0.737135 (-0.581712) | 0.103779 / 0.296338 (-0.192560) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.434509 / 0.215209 (0.219300) | 4.328910 / 2.077655 (2.251255) | 2.311424 / 1.504120 (0.807304) | 2.138380 / 1.541195 (0.597185) | 2.196293 / 1.468490 (0.727803) | 0.482123 / 4.584777 (-4.102654) | 3.597870 / 3.745712 (-0.147842) | 3.222426 / 5.269862 (-2.047435) | 1.994467 / 4.565676 (-2.571210) | 0.057517 / 0.424275 (-0.366758) | 0.007336 / 0.007607 (-0.000271) | 0.504968 / 0.226044 (0.278923) | 5.047940 / 2.268929 (2.779012) | 2.824014 / 55.444624 (-52.620610) | 2.457762 / 6.876477 (-4.418714) | 2.606970 / 2.142072 (0.464897) | 0.580758 / 4.805227 (-4.224469) | 0.132584 / 6.500664 (-6.368080) | 0.059258 / 0.075469 (-0.016211) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.354386 / 1.841788 (-0.487402) | 19.738147 / 8.074308 (11.663839) | 14.858001 / 10.191392 (4.666609) | 0.166074 / 0.680424 (-0.514350) | 0.020181 / 0.534201 (-0.514020) | 0.398333 / 0.579283 (-0.180950) | 0.406969 / 0.434364 (-0.027395) | 0.474515 / 0.540337 (-0.065822) | 0.649571 / 1.386936 (-0.737365) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#b3ac3b3a9c5f40a29fae71504574cfdeebefe349 \"CML watermark\")\n", "I would say we should delete all `dataset_infos.json` on the Hub...", "@albertvillanova @lhoestq @mariosasko should we really stop supporting it and delete from everywhere?\r\n(bc if not, I've found a bug in updating `dataset_infos.json` with `.push_to_hub` and I'd open a PR to fix it)", "We can only delete them for the datasets without namespace and open PRs for the others, so we need to keep supporting them for now" ]

"2023-09-06T10:40:05Z"

"2023-09-07T08:31:29Z"

"2023-09-06T11:23:56Z"

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[]

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[ "We need to implement the `Image` type as a PyArrow extension type (to allow us to override the Python conversion) for this to work as expected. For now, it's best to use your approach indeed." ]

"2023-09-06T09:26:16Z"

"2023-09-08T17:08:52Z"

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[ "_The documentation is not available anymore as the PR was closed or merged._", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007801 / 0.011353 (-0.003552) | 0.004831 / 0.011008 (-0.006177) | 0.123101 / 0.038508 (0.084593) | 0.053246 / 0.023109 (0.030137) | 0.381787 / 0.275898 (0.105889) | 0.461822 / 0.323480 (0.138342) | 0.004655 / 0.007986 (-0.003331) | 0.004818 / 0.004328 (0.000490) | 0.090865 / 0.004250 (0.086614) | 0.070626 / 0.037052 (0.033574) | 0.409122 / 0.258489 (0.150633) | 0.449627 / 0.293841 (0.155787) | 0.037477 / 0.128546 (-0.091069) | 0.010677 / 0.075646 (-0.064970) | 0.419970 / 0.419271 (0.000699) | 0.064626 / 0.043533 (0.021093) | 0.379536 / 0.255139 (0.124397) | 0.405790 / 0.283200 (0.122590) | 0.027290 / 0.141683 (-0.114393) | 1.884973 / 1.452155 (0.432819) | 1.960547 / 1.492716 (0.467831) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.259393 / 0.018006 (0.241386) | 0.502130 / 0.000490 (0.501640) | 0.013053 / 0.000200 (0.012853) | 0.000336 / 0.000054 (0.000281) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.033459 / 0.037411 (-0.003953) | 0.135888 / 0.014526 (0.121362) | 0.145354 / 0.176557 (-0.031203) | 0.213289 / 0.737135 (-0.523847) | 0.151239 / 0.296338 (-0.145100) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.510817 / 0.215209 (0.295608) | 5.077888 / 2.077655 (3.000234) | 2.502991 / 1.504120 (0.998871) | 2.275566 / 1.541195 (0.734371) | 2.353025 / 1.468490 (0.884535) | 0.659062 / 4.584777 (-3.925715) | 4.411399 / 3.745712 (0.665686) | 2.227395 / 5.269862 (-3.042467) | 1.306771 / 4.565676 (-3.258905) | 0.081121 / 0.424275 (-0.343154) | 0.014252 / 0.007607 (0.006645) | 0.635040 / 0.226044 (0.408996) | 6.357500 / 2.268929 (4.088572) | 3.056647 / 55.444624 (-52.387977) | 2.671997 / 6.876477 (-4.204480) | 2.847955 / 2.142072 (0.705883) | 0.808163 / 4.805227 (-3.997064) | 0.177176 / 6.500664 (-6.323488) | 0.079984 / 0.075469 (0.004515) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.490471 / 1.841788 (-0.351317) | 17.927433 / 8.074308 (9.853124) | 17.744967 / 10.191392 (7.553575) | 0.171034 / 0.680424 (-0.509390) | 0.021432 / 0.534201 (-0.512769) | 0.515745 / 0.579283 (-0.063538) | 0.504746 / 0.434364 (0.070382) | 0.630862 / 0.540337 (0.090524) | 0.755275 / 1.386936 (-0.631662) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008227 / 0.011353 (-0.003126) | 0.004864 / 0.011008 (-0.006144) | 0.092801 / 0.038508 (0.054293) | 0.054996 / 0.023109 (0.031887) | 0.500348 / 0.275898 (0.224450) | 0.565028 / 0.323480 (0.241548) | 0.004792 / 0.007986 (-0.003194) | 0.005052 / 0.004328 (0.000723) | 0.090640 / 0.004250 (0.086390) | 0.074427 / 0.037052 (0.037374) | 0.499908 / 0.258489 (0.241419) | 0.566260 / 0.293841 (0.272419) | 0.040011 / 0.128546 (-0.088536) | 0.010438 / 0.075646 (-0.065208) | 0.099385 / 0.419271 (-0.319887) | 0.060485 / 0.043533 (0.016952) | 0.480603 / 0.255139 (0.225464) | 0.508807 / 0.283200 (0.225607) | 0.025976 / 0.141683 (-0.115707) | 1.870860 / 1.452155 (0.418705) | 1.943460 / 1.492716 (0.450744) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.227753 / 0.018006 (0.209747) | 0.501859 / 0.000490 (0.501369) | 0.008211 / 0.000200 (0.008011) | 0.000127 / 0.000054 (0.000073) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.038329 / 0.037411 (0.000918) | 0.148214 / 0.014526 (0.133688) | 0.162704 / 0.176557 (-0.013852) | 0.218543 / 0.737135 (-0.518592) | 0.162992 / 0.296338 (-0.133347) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.553195 / 0.215209 (0.337986) | 5.568080 / 2.077655 (3.490425) | 2.936616 / 1.504120 (1.432496) | 2.712624 / 1.541195 (1.171429) | 2.713245 / 1.468490 (1.244755) | 0.648593 / 4.584777 (-3.936184) | 4.641361 / 3.745712 (0.895648) | 2.207064 / 5.269862 (-3.062798) | 1.315325 / 4.565676 (-3.250351) | 0.080285 / 0.424275 (-0.343990) | 0.014143 / 0.007607 (0.006536) | 0.672467 / 0.226044 (0.446423) | 6.730262 / 2.268929 (4.461333) | 3.344468 / 55.444624 (-52.100157) | 2.927837 / 6.876477 (-3.948640) | 3.124735 / 2.142072 (0.982662) | 0.795894 / 4.805227 (-4.009333) | 0.170985 / 6.500664 (-6.329679) | 0.077406 / 0.075469 (0.001937) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.598059 / 1.841788 (-0.243729) | 18.531854 / 8.074308 (10.457546) | 18.394895 / 10.191392 (8.203503) | 0.195702 / 0.680424 (-0.484722) | 0.023633 / 0.534201 (-0.510568) | 0.518110 / 0.579283 (-0.061173) | 0.517773 / 0.434364 (0.083409) | 0.617902 / 0.540337 (0.077565) | 0.736459 / 1.386936 (-0.650477) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#5d4bb03237b74c0009043d50c5b4e4339cb98b2b \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006943 / 0.011353 (-0.004410) | 0.004524 / 0.011008 (-0.006485) | 0.121603 / 0.038508 (0.083095) | 0.047462 / 0.023109 (0.024353) | 0.362393 / 0.275898 (0.086495) | 0.440577 / 0.323480 (0.117098) | 0.004153 / 0.007986 (-0.003832) | 0.003778 / 0.004328 (-0.000550) | 0.090402 / 0.004250 (0.086152) | 0.066268 / 0.037052 (0.029216) | 0.380721 / 0.258489 (0.122232) | 0.442959 / 0.293841 (0.149118) | 0.035228 / 0.128546 (-0.093318) | 0.010217 / 0.075646 (-0.065429) | 0.408587 / 0.419271 (-0.010684) | 0.062609 / 0.043533 (0.019076) | 0.372682 / 0.255139 (0.117543) | 0.389270 / 0.283200 (0.106070) | 0.026699 / 0.141683 (-0.114984) | 1.760476 / 1.452155 (0.308321) | 1.795081 / 1.492716 (0.302365) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.229912 / 0.018006 (0.211906) | 0.476837 / 0.000490 (0.476348) | 0.008178 / 0.000200 (0.007978) | 0.000100 / 0.000054 (0.000045) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.031116 / 0.037411 (-0.006296) | 0.126767 / 0.014526 (0.112241) | 0.134242 / 0.176557 (-0.042315) | 0.202120 / 0.737135 (-0.535016) | 0.142777 / 0.296338 (-0.153561) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.470690 / 0.215209 (0.255481) | 4.723198 / 2.077655 (2.645543) | 2.163870 / 1.504120 (0.659750) | 1.914177 / 1.541195 (0.372982) | 2.034529 / 1.468490 (0.566038) | 0.620472 / 4.584777 (-3.964305) | 4.391008 / 3.745712 (0.645296) | 2.100966 / 5.269862 (-3.168896) | 1.225945 / 4.565676 (-3.339732) | 0.076279 / 0.424275 (-0.347996) | 0.013551 / 0.007607 (0.005944) | 0.600989 / 0.226044 (0.374945) | 5.946715 / 2.268929 (3.677787) | 2.665117 / 55.444624 (-52.779508) | 2.320004 / 6.876477 (-4.556473) | 2.413131 / 2.142072 (0.271059) | 0.771908 / 4.805227 (-4.033320) | 0.165438 / 6.500664 (-6.335226) | 0.074512 / 0.075469 (-0.000957) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.432728 / 1.841788 (-0.409060) | 17.398133 / 8.074308 (9.323824) | 16.819152 / 10.191392 (6.627760) | 0.191849 / 0.680424 (-0.488575) | 0.021557 / 0.534201 (-0.512644) | 0.514380 / 0.579283 (-0.064903) | 0.501453 / 0.434364 (0.067089) | 0.634091 / 0.540337 (0.093753) | 0.756786 / 1.386936 (-0.630150) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007946 / 0.011353 (-0.003407) | 0.004751 / 0.011008 (-0.006257) | 0.090190 / 0.038508 (0.051682) | 0.052841 / 0.023109 (0.029732) | 0.480150 / 0.275898 (0.204252) | 0.537509 / 0.323480 (0.214029) | 0.004833 / 0.007986 (-0.003153) | 0.004796 / 0.004328 (0.000467) | 0.090616 / 0.004250 (0.086366) | 0.074325 / 0.037052 (0.037273) | 0.483776 / 0.258489 (0.225287) | 0.552094 / 0.293841 (0.258254) | 0.039240 / 0.128546 (-0.089307) | 0.010416 / 0.075646 (-0.065230) | 0.100275 / 0.419271 (-0.318996) | 0.058086 / 0.043533 (0.014553) | 0.468989 / 0.255139 (0.213850) | 0.485502 / 0.283200 (0.202302) | 0.027514 / 0.141683 (-0.114169) | 1.849625 / 1.452155 (0.397470) | 1.919515 / 1.492716 (0.426798) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.248061 / 0.018006 (0.230055) | 0.475630 / 0.000490 (0.475141) | 0.006248 / 0.000200 (0.006048) | 0.000105 / 0.000054 (0.000050) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.037746 / 0.037411 (0.000335) | 0.141638 / 0.014526 (0.127112) | 0.149530 / 0.176557 (-0.027026) | 0.209255 / 0.737135 (-0.527880) | 0.156447 / 0.296338 (-0.139892) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.544640 / 0.215209 (0.329431) | 5.493152 / 2.077655 (3.415497) | 2.869733 / 1.504120 (1.365613) | 2.624216 / 1.541195 (1.083022) | 2.710818 / 1.468490 (1.242328) | 0.640626 / 4.584777 (-3.944151) | 4.516130 / 3.745712 (0.770418) | 2.128097 / 5.269862 (-3.141765) | 1.278990 / 4.565676 (-3.286686) | 0.077114 / 0.424275 (-0.347161) | 0.013280 / 0.007607 (0.005673) | 0.655552 / 0.226044 (0.429507) | 6.526875 / 2.268929 (4.257947) | 3.347072 / 55.444624 (-52.097553) | 2.992435 / 6.876477 (-3.884041) | 3.124351 / 2.142072 (0.982278) | 0.778523 / 4.805227 (-4.026704) | 0.161873 / 6.500664 (-6.338791) | 0.072897 / 0.075469 (-0.002572) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.587058 / 1.841788 (-0.254730) | 18.170612 / 8.074308 (10.096304) | 17.220483 / 10.191392 (7.029091) | 0.207863 / 0.680424 (-0.472561) | 0.023746 / 0.534201 (-0.510455) | 0.512607 / 0.579283 (-0.066676) | 0.513258 / 0.434364 (0.078894) | 0.597880 / 0.540337 (0.057543) | 0.714974 / 1.386936 (-0.671962) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#98b1bdd492df953ca7139bb8c9a1771d5c603797 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006224 / 0.011353 (-0.005128) | 0.003857 / 0.011008 (-0.007151) | 0.099786 / 0.038508 (0.061278) | 0.037919 / 0.023109 (0.014810) | 0.315294 / 0.275898 (0.039396) | 0.390178 / 0.323480 (0.066698) | 0.005358 / 0.007986 (-0.002628) | 0.002989 / 0.004328 (-0.001340) | 0.077834 / 0.004250 (0.073583) | 0.053315 / 0.037052 (0.016263) | 0.325155 / 0.258489 (0.066666) | 0.374712 / 0.293841 (0.080871) | 0.029176 / 0.128546 (-0.099370) | 0.008658 / 0.075646 (-0.066988) | 0.314245 / 0.419271 (-0.105027) | 0.046684 / 0.043533 (0.003151) | 0.316473 / 0.255139 (0.061334) | 0.346119 / 0.283200 (0.062919) | 0.022452 / 0.141683 (-0.119230) | 1.540497 / 1.452155 (0.088343) | 1.594888 / 1.492716 (0.102172) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.204349 / 0.018006 (0.186343) | 0.426842 / 0.000490 (0.426353) | 0.003060 / 0.000200 (0.002860) | 0.000073 / 0.000054 (0.000019) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.023611 / 0.037411 (-0.013801) | 0.100247 / 0.014526 (0.085721) | 0.107824 / 0.176557 (-0.068733) | 0.166845 / 0.737135 (-0.570291) | 0.112782 / 0.296338 (-0.183556) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.423053 / 0.215209 (0.207844) | 4.235553 / 2.077655 (2.157899) | 1.936589 / 1.504120 (0.432469) | 1.738519 / 1.541195 (0.197325) | 1.787905 / 1.468490 (0.319415) | 0.573362 / 4.584777 (-4.011414) | 3.395272 / 3.745712 (-0.350440) | 1.765977 / 5.269862 (-3.503884) | 1.049596 / 4.565676 (-3.516081) | 0.068868 / 0.424275 (-0.355407) | 0.011028 / 0.007607 (0.003421) | 0.532835 / 0.226044 (0.306791) | 5.314890 / 2.268929 (3.045962) | 2.368733 / 55.444624 (-53.075891) | 2.033959 / 6.876477 (-4.842518) | 2.130481 / 2.142072 (-0.011591) | 0.689360 / 4.805227 (-4.115867) | 0.140271 / 6.500664 (-6.360393) | 0.068198 / 0.075469 (-0.007271) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.237212 / 1.841788 (-0.604576) | 14.182215 / 8.074308 (6.107907) | 14.972608 / 10.191392 (4.781216) | 0.133977 / 0.680424 (-0.546447) | 0.016759 / 0.534201 (-0.517442) | 0.361552 / 0.579283 (-0.217731) | 0.394932 / 0.434364 (-0.039432) | 0.442601 / 0.540337 (-0.097736) | 0.535709 / 1.386936 (-0.851227) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006327 / 0.011353 (-0.005026) | 0.003780 / 0.011008 (-0.007228) | 0.078358 / 0.038508 (0.039850) | 0.037271 / 0.023109 (0.014162) | 0.456766 / 0.275898 (0.180868) | 0.515721 / 0.323480 (0.192241) | 0.004770 / 0.007986 (-0.003216) | 0.002942 / 0.004328 (-0.001387) | 0.077383 / 0.004250 (0.073132) | 0.051773 / 0.037052 (0.014721) | 0.460722 / 0.258489 (0.202233) | 0.519997 / 0.293841 (0.226157) | 0.030461 / 0.128546 (-0.098085) | 0.008622 / 0.075646 (-0.067024) | 0.083271 / 0.419271 (-0.336000) | 0.042242 / 0.043533 (-0.001291) | 0.447691 / 0.255139 (0.192552) | 0.481965 / 0.283200 (0.198765) | 0.019510 / 0.141683 (-0.122173) | 1.536718 / 1.452155 (0.084563) | 1.588433 / 1.492716 (0.095717) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.215880 / 0.018006 (0.197874) | 0.426102 / 0.000490 (0.425612) | 0.003976 / 0.000200 (0.003776) | 0.000079 / 0.000054 (0.000025) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.026168 / 0.037411 (-0.011243) | 0.105786 / 0.014526 (0.091260) | 0.113772 / 0.176557 (-0.062785) | 0.166576 / 0.737135 (-0.570559) | 0.117560 / 0.296338 (-0.178779) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.490485 / 0.215209 (0.275276) | 4.890105 / 2.077655 (2.812450) | 2.515099 / 1.504120 (1.010979) | 2.306591 / 1.541195 (0.765396) | 2.383634 / 1.468490 (0.915144) | 0.573780 / 4.584777 (-4.010997) | 3.474394 / 3.745712 (-0.271318) | 1.746795 / 5.269862 (-3.523067) | 1.044678 / 4.565676 (-3.520998) | 0.069176 / 0.424275 (-0.355099) | 0.011045 / 0.007607 (0.003438) | 0.597234 / 0.226044 (0.371189) | 5.979614 / 2.268929 (3.710685) | 3.024203 / 55.444624 (-52.420422) | 2.687502 / 6.876477 (-4.188975) | 2.781637 / 2.142072 (0.639565) | 0.690482 / 4.805227 (-4.114745) | 0.150138 / 6.500664 (-6.350526) | 0.077076 / 0.075469 (0.001607) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.307501 / 1.841788 (-0.534287) | 14.366780 / 8.074308 (6.292471) | 14.966981 / 10.191392 (4.775589) | 0.153829 / 0.680424 (-0.526594) | 0.018047 / 0.534201 (-0.516154) | 0.361391 / 0.579283 (-0.217892) | 0.398345 / 0.434364 (-0.036019) | 0.424574 / 0.540337 (-0.115764) | 0.517165 / 1.386936 (-0.869771) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#98b1bdd492df953ca7139bb8c9a1771d5c603797 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006944 / 0.011353 (-0.004409) | 0.004504 / 0.011008 (-0.006504) | 0.105224 / 0.038508 (0.066716) | 0.047830 / 0.023109 (0.024721) | 0.339723 / 0.275898 (0.063825) | 0.419249 / 0.323480 (0.095769) | 0.005510 / 0.007986 (-0.002476) | 0.003574 / 0.004328 (-0.000754) | 0.079879 / 0.004250 (0.075628) | 0.066610 / 0.037052 (0.029557) | 0.353818 / 0.258489 (0.095329) | 0.397992 / 0.293841 (0.104151) | 0.031551 / 0.128546 (-0.096995) | 0.009037 / 0.075646 (-0.066610) | 0.355310 / 0.419271 (-0.063961) | 0.054931 / 0.043533 (0.011398) | 0.335153 / 0.255139 (0.080014) | 0.357460 / 0.283200 (0.074260) | 0.026031 / 0.141683 (-0.115652) | 1.546705 / 1.452155 (0.094550) | 1.627324 / 1.492716 (0.134608) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.276708 / 0.018006 (0.258701) | 0.589402 / 0.000490 (0.588912) | 0.009560 / 0.000200 (0.009360) | 0.000095 / 0.000054 (0.000041) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.031041 / 0.037411 (-0.006370) | 0.117219 / 0.014526 (0.102693) | 0.125200 / 0.176557 (-0.051356) | 0.181528 / 0.737135 (-0.555607) | 0.131898 / 0.296338 (-0.164440) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.409965 / 0.215209 (0.194756) | 4.102700 / 2.077655 (2.025045) | 1.887578 / 1.504120 (0.383458) | 1.696490 / 1.541195 (0.155295) | 1.821352 / 1.468490 (0.352862) | 0.545422 / 4.584777 (-4.039355) | 3.933784 / 3.745712 (0.188071) | 1.934254 / 5.269862 (-3.335607) | 1.114935 / 4.565676 (-3.450742) | 0.067615 / 0.424275 (-0.356660) | 0.012004 / 0.007607 (0.004397) | 0.522048 / 0.226044 (0.296004) | 5.209224 / 2.268929 (2.940296) | 2.369911 / 55.444624 (-53.074714) | 2.032960 / 6.876477 (-4.843517) | 2.228874 / 2.142072 (0.086802) | 0.673172 / 4.805227 (-4.132055) | 0.147017 / 6.500664 (-6.353647) | 0.067020 / 0.075469 (-0.008449) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.281490 / 1.841788 (-0.560298) | 16.129701 / 8.074308 (8.055393) | 15.474730 / 10.191392 (5.283338) | 0.143934 / 0.680424 (-0.536490) | 0.018311 / 0.534201 (-0.515890) | 0.435940 / 0.579283 (-0.143343) | 0.446846 / 0.434364 (0.012482) | 0.543943 / 0.540337 (0.003605) | 0.648041 / 1.386936 (-0.738895) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007380 / 0.011353 (-0.003973) | 0.004510 / 0.011008 (-0.006499) | 0.080741 / 0.038508 (0.042233) | 0.050907 / 0.023109 (0.027797) | 0.425548 / 0.275898 (0.149650) | 0.487959 / 0.323480 (0.164479) | 0.005887 / 0.007986 (-0.002099) | 0.003689 / 0.004328 (-0.000639) | 0.079588 / 0.004250 (0.075338) | 0.071841 / 0.037052 (0.034788) | 0.425172 / 0.258489 (0.166683) | 0.471185 / 0.293841 (0.177344) | 0.035768 / 0.128546 (-0.092779) | 0.009229 / 0.075646 (-0.066418) | 0.086021 / 0.419271 (-0.333250) | 0.052424 / 0.043533 (0.008891) | 0.413634 / 0.255139 (0.158495) | 0.422310 / 0.283200 (0.139111) | 0.026019 / 0.141683 (-0.115664) | 1.616861 / 1.452155 (0.164707) | 1.653660 / 1.492716 (0.160943) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.280096 / 0.018006 (0.262090) | 0.587853 / 0.000490 (0.587363) | 0.006560 / 0.000200 (0.006360) | 0.000181 / 0.000054 (0.000127) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.033747 / 0.037411 (-0.003665) | 0.125089 / 0.014526 (0.110564) | 0.137995 / 0.176557 (-0.038561) | 0.188192 / 0.737135 (-0.548943) | 0.141438 / 0.296338 (-0.154900) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.471524 / 0.215209 (0.256315) | 4.713988 / 2.077655 (2.636334) | 2.414785 / 1.504120 (0.910665) | 2.226815 / 1.541195 (0.685620) | 2.259222 / 1.468490 (0.790732) | 0.551663 / 4.584777 (-4.033114) | 4.031399 / 3.745712 (0.285686) | 1.966917 / 5.269862 (-3.302945) | 1.154487 / 4.565676 (-3.411190) | 0.068500 / 0.424275 (-0.355775) | 0.012127 / 0.007607 (0.004520) | 0.579342 / 0.226044 (0.353298) | 5.757415 / 2.268929 (3.488486) | 2.820012 / 55.444624 (-52.624613) | 2.521783 / 6.876477 (-4.354694) | 2.699994 / 2.142072 (0.557921) | 0.686152 / 4.805227 (-4.119075) | 0.148521 / 6.500664 (-6.352143) | 0.068478 / 0.075469 (-0.006991) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.336260 / 1.841788 (-0.505528) | 17.016935 / 8.074308 (8.942627) | 16.406951 / 10.191392 (6.215559) | 0.166907 / 0.680424 (-0.513517) | 0.020166 / 0.534201 (-0.514035) | 0.437690 / 0.579283 (-0.141593) | 0.480337 / 0.434364 (0.045973) | 0.518065 / 0.540337 (-0.022272) | 0.625904 / 1.386936 (-0.761032) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#98b1bdd492df953ca7139bb8c9a1771d5c603797 \"CML watermark\")\n" ]

"2023-09-06T08:15:32Z"

"2023-09-06T08:52:18Z"

"2023-09-06T08:22:43Z"

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[]

[ "_The documentation is not available anymore as the PR was closed or merged._", "oh wow good catch", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006681 / 0.011353 (-0.004672) | 0.003967 / 0.011008 (-0.007041) | 0.085590 / 0.038508 (0.047082) | 0.079285 / 0.023109 (0.056176) | 0.311583 / 0.275898 (0.035685) | 0.345578 / 0.323480 (0.022098) | 0.004115 / 0.007986 (-0.003871) | 0.004286 / 0.004328 (-0.000043) | 0.064405 / 0.004250 (0.060155) | 0.055084 / 0.037052 (0.018032) | 0.316117 / 0.258489 (0.057628) | 0.354737 / 0.293841 (0.060896) | 0.031280 / 0.128546 (-0.097266) | 0.008395 / 0.075646 (-0.067251) | 0.288910 / 0.419271 (-0.130362) | 0.051291 / 0.043533 (0.007759) | 0.309125 / 0.255139 (0.053986) | 0.349673 / 0.283200 (0.066473) | 0.025016 / 0.141683 (-0.116667) | 1.475577 / 1.452155 (0.023422) | 1.558967 / 1.492716 (0.066251) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.208504 / 0.018006 (0.190498) | 0.462270 / 0.000490 (0.461780) | 0.003476 / 0.000200 (0.003276) | 0.000073 / 0.000054 (0.000018) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.030371 / 0.037411 (-0.007041) | 0.086157 / 0.014526 (0.071631) | 0.098162 / 0.176557 (-0.078395) | 0.154649 / 0.737135 (-0.582486) | 0.098697 / 0.296338 (-0.197642) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.405883 / 0.215209 (0.190674) | 4.049614 / 2.077655 (1.971959) | 2.075047 / 1.504120 (0.570927) | 1.917782 / 1.541195 (0.376587) | 2.030268 / 1.468490 (0.561778) | 0.483974 / 4.584777 (-4.100803) | 3.542147 / 3.745712 (-0.203566) | 3.305999 / 5.269862 (-1.963863) | 2.052287 / 4.565676 (-2.513390) | 0.057246 / 0.424275 (-0.367029) | 0.007631 / 0.007607 (0.000024) | 0.488189 / 0.226044 (0.262144) | 4.884784 / 2.268929 (2.615856) | 2.576304 / 55.444624 (-52.868320) | 2.241249 / 6.876477 (-4.635228) | 2.490512 / 2.142072 (0.348440) | 0.584495 / 4.805227 (-4.220733) | 0.134741 / 6.500664 (-6.365923) | 0.061639 / 0.075469 (-0.013830) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.317717 / 1.841788 (-0.524071) | 20.098594 / 8.074308 (12.024286) | 14.641051 / 10.191392 (4.449659) | 0.165291 / 0.680424 (-0.515133) | 0.019179 / 0.534201 (-0.515022) | 0.399506 / 0.579283 (-0.179777) | 0.407662 / 0.434364 (-0.026701) | 0.457965 / 0.540337 (-0.082372) | 0.626401 / 1.386936 (-0.760536) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007076 / 0.011353 (-0.004277) | 0.004125 / 0.011008 (-0.006884) | 0.064861 / 0.038508 (0.026353) | 0.082390 / 0.023109 (0.059281) | 0.423227 / 0.275898 (0.147329) | 0.452229 / 0.323480 (0.128750) | 0.005594 / 0.007986 (-0.002392) | 0.003465 / 0.004328 (-0.000863) | 0.064661 / 0.004250 (0.060411) | 0.057945 / 0.037052 (0.020892) | 0.424572 / 0.258489 (0.166083) | 0.465349 / 0.293841 (0.171509) | 0.032687 / 0.128546 (-0.095859) | 0.008573 / 0.075646 (-0.067074) | 0.073020 / 0.419271 (-0.346251) | 0.048423 / 0.043533 (0.004891) | 0.413425 / 0.255139 (0.158286) | 0.433778 / 0.283200 (0.150578) | 0.023942 / 0.141683 (-0.117741) | 1.495190 / 1.452155 (0.043036) | 1.586526 / 1.492716 (0.093810) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.271805 / 0.018006 (0.253799) | 0.454922 / 0.000490 (0.454432) | 0.015386 / 0.000200 (0.015186) | 0.000129 / 0.000054 (0.000074) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.033804 / 0.037411 (-0.003607) | 0.099317 / 0.014526 (0.084791) | 0.107207 / 0.176557 (-0.069349) | 0.160926 / 0.737135 (-0.576210) | 0.108669 / 0.296338 (-0.187670) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.430776 / 0.215209 (0.215567) | 4.297622 / 2.077655 (2.219967) | 2.285918 / 1.504120 (0.781798) | 2.109608 / 1.541195 (0.568413) | 2.208326 / 1.468490 (0.739836) | 0.490016 / 4.584777 (-4.094761) | 3.570609 / 3.745712 (-0.175103) | 3.406335 / 5.269862 (-1.863526) | 2.070664 / 4.565676 (-2.495012) | 0.058089 / 0.424275 (-0.366186) | 0.007425 / 0.007607 (-0.000182) | 0.506972 / 0.226044 (0.280927) | 5.078643 / 2.268929 (2.809714) | 2.858973 / 55.444624 (-52.585651) | 2.457344 / 6.876477 (-4.419132) | 2.687727 / 2.142072 (0.545654) | 0.592134 / 4.805227 (-4.213093) | 0.133966 / 6.500664 (-6.366698) | 0.061800 / 0.075469 (-0.013669) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.337167 / 1.841788 (-0.504620) | 20.743951 / 8.074308 (12.669643) | 15.402686 / 10.191392 (5.211294) | 0.164548 / 0.680424 (-0.515876) | 0.020244 / 0.534201 (-0.513957) | 0.399044 / 0.579283 (-0.180239) | 0.414036 / 0.434364 (-0.020328) | 0.474141 / 0.540337 (-0.066197) | 0.654455 / 1.386936 (-0.732482) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#4de930c45a81a6dff1805bf45f59170e9f953eeb \"CML watermark\")\n" ]

"2023-09-05T15:10:47Z"

"2023-09-06T10:34:00Z"

"2023-09-06T10:25:00Z"

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[]

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"2023-09-05T11:02:58Z"

"2023-09-05T11:26:03Z"

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[ "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008451 / 0.011353 (-0.002902) | 0.005056 / 0.011008 (-0.005952) | 0.086367 / 0.038508 (0.047859) | 0.068030 / 0.023109 (0.044920) | 0.358812 / 0.275898 (0.082914) | 0.385790 / 0.323480 (0.062310) | 0.005608 / 0.007986 (-0.002378) | 0.004262 / 0.004328 (-0.000067) | 0.066618 / 0.004250 (0.062368) | 0.053901 / 0.037052 (0.016849) | 0.398456 / 0.258489 (0.139967) | 0.391681 / 0.293841 (0.097840) | 0.046743 / 0.128546 (-0.081804) | 0.014118 / 0.075646 (-0.061528) | 0.308479 / 0.419271 (-0.110793) | 0.064214 / 0.043533 (0.020681) | 0.367940 / 0.255139 (0.112801) | 0.387204 / 0.283200 (0.104004) | 0.036093 / 0.141683 (-0.105590) | 1.534182 / 1.452155 (0.082027) | 1.598357 / 1.492716 (0.105641) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.265910 / 0.018006 (0.247904) | 0.589453 / 0.000490 (0.588963) | 0.004881 / 0.000200 (0.004681) | 0.000090 / 0.000054 (0.000036) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.032540 / 0.037411 (-0.004872) | 0.083153 / 0.014526 (0.068627) | 0.098960 / 0.176557 (-0.077597) | 0.162044 / 0.737135 (-0.575091) | 0.093602 / 0.296338 (-0.202736) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.517056 / 0.215209 (0.301847) | 5.167908 / 2.077655 (3.090253) | 2.359856 / 1.504120 (0.855736) | 2.092448 / 1.541195 (0.551253) | 2.100270 / 1.468490 (0.631780) | 0.742321 / 4.584777 (-3.842456) | 4.845010 / 3.745712 (1.099298) | 4.361808 / 5.269862 (-0.908054) | 2.621941 / 4.565676 (-1.943736) | 0.094907 / 0.424275 (-0.329369) | 0.009357 / 0.007607 (0.001750) | 0.719859 / 0.226044 (0.493814) | 6.929731 / 2.268929 (4.660802) | 3.240862 / 55.444624 (-52.203763) | 2.700817 / 6.876477 (-4.175659) | 2.904600 / 2.142072 (0.762527) | 0.924930 / 4.805227 (-3.880298) | 0.194390 / 6.500664 (-6.306274) | 0.078331 / 0.075469 (0.002862) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.539347 / 1.841788 (-0.302441) | 22.696358 / 8.074308 (14.622050) | 18.791692 / 10.191392 (8.600300) | 0.221376 / 0.680424 (-0.459048) | 0.029824 / 0.534201 (-0.504377) | 0.455604 / 0.579283 (-0.123679) | 0.573169 / 0.434364 (0.138805) | 0.507109 / 0.540337 (-0.033228) | 0.730986 / 1.386936 (-0.655950) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.009308 / 0.011353 (-0.002045) | 0.005027 / 0.011008 (-0.005982) | 0.074094 / 0.038508 (0.035586) | 0.068277 / 0.023109 (0.045168) | 0.412716 / 0.275898 (0.136818) | 0.446883 / 0.323480 (0.123403) | 0.005864 / 0.007986 (-0.002122) | 0.003753 / 0.004328 (-0.000575) | 0.072575 / 0.004250 (0.068325) | 0.064434 / 0.037052 (0.027382) | 0.445395 / 0.258489 (0.186906) | 0.464520 / 0.293841 (0.170679) | 0.045303 / 0.128546 (-0.083243) | 0.013120 / 0.075646 (-0.062527) | 0.077830 / 0.419271 (-0.341441) | 0.057303 / 0.043533 (0.013770) | 0.420845 / 0.255139 (0.165706) | 0.431308 / 0.283200 (0.148109) | 0.033908 / 0.141683 (-0.107775) | 1.577667 / 1.452155 (0.125512) | 1.677321 / 1.492716 (0.184604) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.305855 / 0.018006 (0.287849) | 0.601442 / 0.000490 (0.600953) | 0.010722 / 0.000200 (0.010522) | 0.000158 / 0.000054 (0.000104) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.029202 / 0.037411 (-0.008209) | 0.094576 / 0.014526 (0.080050) | 0.106734 / 0.176557 (-0.069822) | 0.168114 / 0.737135 (-0.569021) | 0.107241 / 0.296338 (-0.189098) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.643634 / 0.215209 (0.428425) | 6.391757 / 2.077655 (4.314103) | 3.011679 / 1.504120 (1.507559) | 2.379711 / 1.541195 (0.838517) | 2.387444 / 1.468490 (0.918954) | 0.823460 / 4.584777 (-3.761317) | 4.882240 / 3.745712 (1.136528) | 4.091170 / 5.269862 (-1.178691) | 2.688761 / 4.565676 (-1.876915) | 0.094555 / 0.424275 (-0.329720) | 0.008464 / 0.007607 (0.000857) | 0.665949 / 0.226044 (0.439905) | 6.948237 / 2.268929 (4.679309) | 3.384894 / 55.444624 (-52.059730) | 2.675570 / 6.876477 (-4.200907) | 3.073045 / 2.142072 (0.930973) | 0.969780 / 4.805227 (-3.835447) | 0.205859 / 6.500664 (-6.294805) | 0.072548 / 0.075469 (-0.002922) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.563869 / 1.841788 (-0.277919) | 22.431392 / 8.074308 (14.357084) | 19.434811 / 10.191392 (9.243419) | 0.255135 / 0.680424 (-0.425289) | 0.027799 / 0.534201 (-0.506402) | 0.427713 / 0.579283 (-0.151570) | 0.527030 / 0.434364 (0.092666) | 0.503660 / 0.540337 (-0.036678) | 0.730996 / 1.386936 (-0.655940) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#06c1940953807dbde4bc18af64bd3d87234edf00 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007597 / 0.011353 (-0.003756) | 0.004492 / 0.011008 (-0.006516) | 0.103779 / 0.038508 (0.065271) | 0.079287 / 0.023109 (0.056178) | 0.389651 / 0.275898 (0.113753) | 0.421955 / 0.323480 (0.098475) | 0.006023 / 0.007986 (-0.001963) | 0.003727 / 0.004328 (-0.000602) | 0.078604 / 0.004250 (0.074354) | 0.060810 / 0.037052 (0.023758) | 0.412170 / 0.258489 (0.153681) | 0.436218 / 0.293841 (0.142377) | 0.037282 / 0.128546 (-0.091264) | 0.010341 / 0.075646 (-0.065305) | 0.357652 / 0.419271 (-0.061620) | 0.063320 / 0.043533 (0.019788) | 0.389454 / 0.255139 (0.134315) | 0.433073 / 0.283200 (0.149874) | 0.028449 / 0.141683 (-0.113234) | 1.894107 / 1.452155 (0.441952) | 1.954190 / 1.492716 (0.461474) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.224477 / 0.018006 (0.206471) | 0.510878 / 0.000490 (0.510388) | 0.005013 / 0.000200 (0.004813) | 0.000092 / 0.000054 (0.000037) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.032976 / 0.037411 (-0.004436) | 0.101073 / 0.014526 (0.086547) | 0.113990 / 0.176557 (-0.062566) | 0.183499 / 0.737135 (-0.553636) | 0.114283 / 0.296338 (-0.182056) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.473242 / 0.215209 (0.258033) | 4.719800 / 2.077655 (2.642146) | 2.318732 / 1.504120 (0.814612) | 2.102336 / 1.541195 (0.561141) | 2.143618 / 1.468490 (0.675128) | 0.594122 / 4.584777 (-3.990654) | 4.265961 / 3.745712 (0.520249) | 3.794635 / 5.269862 (-1.475226) | 2.394506 / 4.565676 (-2.171170) | 0.070091 / 0.424275 (-0.354184) | 0.009222 / 0.007607 (0.001614) | 0.564496 / 0.226044 (0.338452) | 5.644348 / 2.268929 (3.375419) | 2.934395 / 55.444624 (-52.510229) | 2.429076 / 6.876477 (-4.447401) | 2.592010 / 2.142072 (0.449937) | 0.713371 / 4.805227 (-4.091856) | 0.165019 / 6.500664 (-6.335646) | 0.075913 / 0.075469 (0.000444) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.570836 / 1.841788 (-0.270951) | 22.569763 / 8.074308 (14.495455) | 17.159658 / 10.191392 (6.968266) | 0.185716 / 0.680424 (-0.494708) | 0.021938 / 0.534201 (-0.512263) | 0.487204 / 0.579283 (-0.092079) | 0.472776 / 0.434364 (0.038412) | 0.565052 / 0.540337 (0.024714) | 0.763322 / 1.386936 (-0.623614) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007810 / 0.011353 (-0.003543) | 0.005140 / 0.011008 (-0.005869) | 0.079018 / 0.038508 (0.040510) | 0.080899 / 0.023109 (0.057790) | 0.489213 / 0.275898 (0.213315) | 0.525334 / 0.323480 (0.201854) | 0.006992 / 0.007986 (-0.000994) | 0.003729 / 0.004328 (-0.000599) | 0.079277 / 0.004250 (0.075026) | 0.064883 / 0.037052 (0.027831) | 0.496718 / 0.258489 (0.238229) | 0.534976 / 0.293841 (0.241135) | 0.038790 / 0.128546 (-0.089756) | 0.010122 / 0.075646 (-0.065524) | 0.087669 / 0.419271 (-0.331603) | 0.057959 / 0.043533 (0.014426) | 0.490611 / 0.255139 (0.235472) | 0.518376 / 0.283200 (0.235176) | 0.026561 / 0.141683 (-0.115122) | 1.843241 / 1.452155 (0.391086) | 1.952367 / 1.492716 (0.459651) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.289799 / 0.018006 (0.271792) | 0.486999 / 0.000490 (0.486509) | 0.017481 / 0.000200 (0.017281) | 0.000122 / 0.000054 (0.000068) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.037662 / 0.037411 (0.000250) | 0.113238 / 0.014526 (0.098712) | 0.123918 / 0.176557 (-0.052638) | 0.190484 / 0.737135 (-0.546652) | 0.126473 / 0.296338 (-0.169865) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.530622 / 0.215209 (0.315413) | 5.292093 / 2.077655 (3.214438) | 2.819354 / 1.504120 (1.315234) | 2.609821 / 1.541195 (1.068626) | 2.680090 / 1.468490 (1.211600) | 0.603490 / 4.584777 (-3.981287) | 4.344541 / 3.745712 (0.598828) | 3.874001 / 5.269862 (-1.395861) | 2.445302 / 4.565676 (-2.120375) | 0.071173 / 0.424275 (-0.353102) | 0.009131 / 0.007607 (0.001524) | 0.627273 / 0.226044 (0.401229) | 6.278637 / 2.268929 (4.009709) | 3.433762 / 55.444624 (-52.010862) | 2.973400 / 6.876477 (-3.903077) | 3.188165 / 2.142072 (1.046093) | 0.722824 / 4.805227 (-4.082404) | 0.165154 / 6.500664 (-6.335510) | 0.075268 / 0.075469 (-0.000202) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.652994 / 1.841788 (-0.188794) | 23.309030 / 8.074308 (15.234722) | 18.135649 / 10.191392 (7.944257) | 0.177543 / 0.680424 (-0.502881) | 0.024784 / 0.534201 (-0.509417) | 0.489952 / 0.579283 (-0.089331) | 0.485368 / 0.434364 (0.051004) | 0.580583 / 0.540337 (0.040246) | 0.787843 / 1.386936 (-0.599093) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#5982039f7814a204fe532240ca6aabe72430d834 \"CML watermark\")\n", "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6213). All of your documentation changes will be reflected on that endpoint.", "A bug in `FixedSizeArray.flatten` in `PyArrow<10.0.0` makes CI fail. Colab installs 9.0.0 by default, so we should be able to set the minimal version to `10.0.0` soon. Keeping this PR as a draft in the meantime." ]

"2023-09-04T16:21:23Z"

"2023-09-04T17:53:17Z"

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[ "Hi @exs-avianello, is it really needed? Note you can alternatively use `pathlib.Path` among others as it follows:\r\n\r\n```python\r\nimport datasets\r\nfrom pathlib import Path\r\n\r\n# save a parquet file at ~/path/to/data.parquet\r\n\r\ndata_files = Path.home() / \"path/to/data.parquet\"\r\ndataset = datasets.load_dataset(\"parquet\", data_files=data_files)\r\n```", "Hi @alvarobartt ! \r\n\r\nThis is definitely just a \"nice to have\" and I am personally more than happy to just use absolute paths client-side. I just wanted to flag it up in case it can help improve the package even more 🙌 It might not be immediately obvious from the stack trace that the error is triggered by the `~` in the path" ]

"2023-09-04T14:23:49Z"

"2023-09-05T08:28:39Z"

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[ "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007756 / 0.011353 (-0.003597) | 0.004733 / 0.011008 (-0.006275) | 0.095874 / 0.038508 (0.057366) | 0.081957 / 0.023109 (0.058848) | 0.426430 / 0.275898 (0.150532) | 0.457670 / 0.323480 (0.134190) | 0.004448 / 0.007986 (-0.003537) | 0.004956 / 0.004328 (0.000627) | 0.074195 / 0.004250 (0.069945) | 0.061101 / 0.037052 (0.024048) | 0.435134 / 0.258489 (0.176645) | 0.457245 / 0.293841 (0.163404) | 0.034945 / 0.128546 (-0.093601) | 0.010028 / 0.075646 (-0.065618) | 0.350724 / 0.419271 (-0.068548) | 0.064433 / 0.043533 (0.020901) | 0.417882 / 0.255139 (0.162743) | 0.445087 / 0.283200 (0.161887) | 0.027576 / 0.141683 (-0.114107) | 1.824066 / 1.452155 (0.371912) | 1.957568 / 1.492716 (0.464852) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.238568 / 0.018006 (0.220562) | 0.505289 / 0.000490 (0.504799) | 0.003527 / 0.000200 (0.003327) | 0.000120 / 0.000054 (0.000065) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.032839 / 0.037411 (-0.004572) | 0.096708 / 0.014526 (0.082182) | 0.112100 / 0.176557 (-0.064456) | 0.177215 / 0.737135 (-0.559920) | 0.111273 / 0.296338 (-0.185066) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.475200 / 0.215209 (0.259991) | 4.725737 / 2.077655 (2.648082) | 2.414672 / 1.504120 (0.910552) | 2.196357 / 1.541195 (0.655162) | 2.329298 / 1.468490 (0.860808) | 0.575258 / 4.584777 (-4.009519) | 4.343630 / 3.745712 (0.597918) | 3.837665 / 5.269862 (-1.432196) | 2.497970 / 4.565676 (-2.067706) | 0.066467 / 0.424275 (-0.357808) | 0.008680 / 0.007607 (0.001073) | 0.569923 / 0.226044 (0.343878) | 5.634230 / 2.268929 (3.365302) | 2.959222 / 55.444624 (-52.485402) | 2.535954 / 6.876477 (-4.340523) | 2.804844 / 2.142072 (0.662771) | 0.682000 / 4.805227 (-4.123227) | 0.158193 / 6.500664 (-6.342471) | 0.072315 / 0.075469 (-0.003154) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.578148 / 1.841788 (-0.263639) | 22.993419 / 8.074308 (14.919110) | 16.524477 / 10.191392 (6.333085) | 0.169415 / 0.680424 (-0.511009) | 0.021520 / 0.534201 (-0.512681) | 0.455970 / 0.579283 (-0.123313) | 0.489022 / 0.434364 (0.054658) | 0.535656 / 0.540337 (-0.004682) | 0.802341 / 1.386936 (-0.584595) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008002 / 0.011353 (-0.003351) | 0.005577 / 0.011008 (-0.005431) | 0.087803 / 0.038508 (0.049295) | 0.091285 / 0.023109 (0.068176) | 0.500514 / 0.275898 (0.224616) | 0.549770 / 0.323480 (0.226290) | 0.006125 / 0.007986 (-0.001861) | 0.004031 / 0.004328 (-0.000297) | 0.077941 / 0.004250 (0.073691) | 0.071419 / 0.037052 (0.034367) | 0.497570 / 0.258489 (0.239081) | 0.542454 / 0.293841 (0.248613) | 0.040827 / 0.128546 (-0.087719) | 0.011029 / 0.075646 (-0.064617) | 0.088788 / 0.419271 (-0.330484) | 0.056970 / 0.043533 (0.013438) | 0.523934 / 0.255139 (0.268795) | 0.552507 / 0.283200 (0.269308) | 0.029794 / 0.141683 (-0.111889) | 1.817778 / 1.452155 (0.365623) | 1.955843 / 1.492716 (0.463126) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.246992 / 0.018006 (0.228986) | 0.467879 / 0.000490 (0.467390) | 0.005439 / 0.000200 (0.005239) | 0.000110 / 0.000054 (0.000056) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.037774 / 0.037411 (0.000363) | 0.109332 / 0.014526 (0.094806) | 0.120103 / 0.176557 (-0.056454) | 0.185259 / 0.737135 (-0.551876) | 0.126189 / 0.296338 (-0.170149) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.492856 / 0.215209 (0.277646) | 5.033209 / 2.077655 (2.955554) | 2.885551 / 1.504120 (1.381431) | 2.480304 / 1.541195 (0.939109) | 2.579092 / 1.468490 (1.110602) | 0.557671 / 4.584777 (-4.027106) | 4.352765 / 3.745712 (0.607053) | 4.039124 / 5.269862 (-1.230738) | 2.534342 / 4.565676 (-2.031335) | 0.067267 / 0.424275 (-0.357008) | 0.008891 / 0.007607 (0.001284) | 0.591592 / 0.226044 (0.365547) | 5.939982 / 2.268929 (3.671053) | 3.258389 / 55.444624 (-52.186235) | 2.843899 / 6.876477 (-4.032578) | 3.074217 / 2.142072 (0.932144) | 0.695065 / 4.805227 (-4.110162) | 0.156917 / 6.500664 (-6.343747) | 0.070185 / 0.075469 (-0.005284) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.586716 / 1.841788 (-0.255072) | 23.405837 / 8.074308 (15.331529) | 17.200851 / 10.191392 (7.009459) | 0.170073 / 0.680424 (-0.510351) | 0.023345 / 0.534201 (-0.510856) | 0.459192 / 0.579283 (-0.120091) | 0.477419 / 0.434364 (0.043055) | 0.558581 / 0.540337 (0.018244) | 0.814373 / 1.386936 (-0.572563) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#28bbe5667e6eaa1bb21685791fcf1a4ed1ef1777 \"CML watermark\")\n", "_The documentation is not available anymore as the PR was closed or merged._", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006050 / 0.011353 (-0.005303) | 0.003661 / 0.011008 (-0.007348) | 0.081753 / 0.038508 (0.043245) | 0.061275 / 0.023109 (0.038166) | 0.316278 / 0.275898 (0.040380) | 0.350783 / 0.323480 (0.027303) | 0.004694 / 0.007986 (-0.003291) | 0.003003 / 0.004328 (-0.001326) | 0.062877 / 0.004250 (0.058627) | 0.046985 / 0.037052 (0.009933) | 0.315698 / 0.258489 (0.057208) | 0.364607 / 0.293841 (0.070766) | 0.027365 / 0.128546 (-0.101181) | 0.008016 / 0.075646 (-0.067631) | 0.261379 / 0.419271 (-0.157893) | 0.045173 / 0.043533 (0.001640) | 0.313499 / 0.255139 (0.058360) | 0.339383 / 0.283200 (0.056184) | 0.020855 / 0.141683 (-0.120828) | 1.429851 / 1.452155 (-0.022303) | 1.506112 / 1.492716 (0.013396) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.194872 / 0.018006 (0.176866) | 0.451951 / 0.000490 (0.451462) | 0.002790 / 0.000200 (0.002590) | 0.000070 / 0.000054 (0.000015) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.024331 / 0.037411 (-0.013081) | 0.073156 / 0.014526 (0.058630) | 0.084054 / 0.176557 (-0.092502) | 0.145656 / 0.737135 (-0.591480) | 0.084998 / 0.296338 (-0.211340) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.391324 / 0.215209 (0.176115) | 3.898406 / 2.077655 (1.820751) | 1.891175 / 1.504120 (0.387055) | 1.698738 / 1.541195 (0.157543) | 1.774324 / 1.468490 (0.305834) | 0.495129 / 4.584777 (-4.089648) | 3.027027 / 3.745712 (-0.718685) | 2.821423 / 5.269862 (-2.448439) | 1.870761 / 4.565676 (-2.694915) | 0.057029 / 0.424275 (-0.367246) | 0.006715 / 0.007607 (-0.000892) | 0.465801 / 0.226044 (0.239757) | 4.650891 / 2.268929 (2.381962) | 2.425097 / 55.444624 (-53.019527) | 2.134731 / 6.876477 (-4.741745) | 2.312854 / 2.142072 (0.170781) | 0.589668 / 4.805227 (-4.215559) | 0.124673 / 6.500664 (-6.375991) | 0.060887 / 0.075469 (-0.014582) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.243622 / 1.841788 (-0.598166) | 18.501640 / 8.074308 (10.427332) | 13.853099 / 10.191392 (3.661707) | 0.130255 / 0.680424 (-0.550168) | 0.016824 / 0.534201 (-0.517377) | 0.332297 / 0.579283 (-0.246986) | 0.360346 / 0.434364 (-0.074018) | 0.388598 / 0.540337 (-0.151739) | 0.527551 / 1.386936 (-0.859385) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006181 / 0.011353 (-0.005172) | 0.003688 / 0.011008 (-0.007320) | 0.063395 / 0.038508 (0.024887) | 0.062531 / 0.023109 (0.039422) | 0.446565 / 0.275898 (0.170667) | 0.485224 / 0.323480 (0.161744) | 0.004982 / 0.007986 (-0.003004) | 0.002961 / 0.004328 (-0.001367) | 0.063124 / 0.004250 (0.058874) | 0.050234 / 0.037052 (0.013182) | 0.449731 / 0.258489 (0.191242) | 0.487293 / 0.293841 (0.193452) | 0.028528 / 0.128546 (-0.100018) | 0.008210 / 0.075646 (-0.067436) | 0.069520 / 0.419271 (-0.349751) | 0.041026 / 0.043533 (-0.002507) | 0.451370 / 0.255139 (0.196231) | 0.469151 / 0.283200 (0.185951) | 0.021076 / 0.141683 (-0.120607) | 1.439185 / 1.452155 (-0.012970) | 1.492634 / 1.492716 (-0.000082) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.235932 / 0.018006 (0.217926) | 0.430070 / 0.000490 (0.429581) | 0.007347 / 0.000200 (0.007147) | 0.000084 / 0.000054 (0.000029) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.026102 / 0.037411 (-0.011309) | 0.081333 / 0.014526 (0.066807) | 0.090111 / 0.176557 (-0.086446) | 0.144578 / 0.737135 (-0.592557) | 0.091961 / 0.296338 (-0.204378) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.455761 / 0.215209 (0.240552) | 4.536345 / 2.077655 (2.458690) | 2.496833 / 1.504120 (0.992713) | 2.323325 / 1.541195 (0.782130) | 2.388364 / 1.468490 (0.919873) | 0.512010 / 4.584777 (-4.072767) | 3.106268 / 3.745712 (-0.639444) | 2.879224 / 5.269862 (-2.390637) | 1.893859 / 4.565676 (-2.671818) | 0.059131 / 0.424275 (-0.365144) | 0.006763 / 0.007607 (-0.000844) | 0.528205 / 0.226044 (0.302161) | 5.296649 / 2.268929 (3.027720) | 2.933787 / 55.444624 (-52.510838) | 2.598258 / 6.876477 (-4.278218) | 2.768195 / 2.142072 (0.626123) | 0.597430 / 4.805227 (-4.207797) | 0.125865 / 6.500664 (-6.374799) | 0.061684 / 0.075469 (-0.013785) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.341194 / 1.841788 (-0.500594) | 18.948225 / 8.074308 (10.873917) | 14.912340 / 10.191392 (4.720948) | 0.146905 / 0.680424 (-0.533519) | 0.017952 / 0.534201 (-0.516249) | 0.332299 / 0.579283 (-0.246984) | 0.362733 / 0.434364 (-0.071631) | 0.388278 / 0.540337 (-0.152060) | 0.546436 / 1.386936 (-0.840500) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#cb4f8357de001df656f2ea7af27625e189c3995b \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008314 / 0.011353 (-0.003038) | 0.004904 / 0.011008 (-0.006105) | 0.097486 / 0.038508 (0.058978) | 0.074627 / 0.023109 (0.051518) | 0.396395 / 0.275898 (0.120497) | 0.440519 / 0.323480 (0.117039) | 0.005964 / 0.007986 (-0.002022) | 0.004203 / 0.004328 (-0.000126) | 0.079998 / 0.004250 (0.075747) | 0.055158 / 0.037052 (0.018106) | 0.415439 / 0.258489 (0.156950) | 0.476101 / 0.293841 (0.182260) | 0.044761 / 0.128546 (-0.083785) | 0.013966 / 0.075646 (-0.061680) | 0.351279 / 0.419271 (-0.067993) | 0.067250 / 0.043533 (0.023717) | 0.414310 / 0.255139 (0.159171) | 0.458104 / 0.283200 (0.174904) | 0.033678 / 0.141683 (-0.108005) | 1.730539 / 1.452155 (0.278385) | 1.840013 / 1.492716 (0.347297) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.272708 / 0.018006 (0.254702) | 0.593563 / 0.000490 (0.593074) | 0.005153 / 0.000200 (0.004953) | 0.000179 / 0.000054 (0.000125) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.029595 / 0.037411 (-0.007816) | 0.087994 / 0.014526 (0.073469) | 0.106066 / 0.176557 (-0.070491) | 0.180491 / 0.737135 (-0.556644) | 0.103707 / 0.296338 (-0.192631) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.566711 / 0.215209 (0.351502) | 5.589034 / 2.077655 (3.511380) | 2.364034 / 1.504120 (0.859914) | 2.119050 / 1.541195 (0.577855) | 2.103823 / 1.468490 (0.635333) | 0.819906 / 4.584777 (-3.764871) | 5.178464 / 3.745712 (1.432752) | 4.433986 / 5.269862 (-0.835875) | 2.825470 / 4.565676 (-1.740207) | 0.096907 / 0.424275 (-0.327368) | 0.008573 / 0.007607 (0.000966) | 0.677607 / 0.226044 (0.451563) | 6.811090 / 2.268929 (4.542162) | 3.140923 / 55.444624 (-52.303701) | 2.492251 / 6.876477 (-4.384225) | 2.660231 / 2.142072 (0.518158) | 0.980573 / 4.805227 (-3.824655) | 0.209028 / 6.500664 (-6.291636) | 0.079413 / 0.075469 (0.003944) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.578861 / 1.841788 (-0.262926) | 22.518269 / 8.074308 (14.443961) | 21.335916 / 10.191392 (11.144524) | 0.211311 / 0.680424 (-0.469113) | 0.033216 / 0.534201 (-0.500985) | 0.473266 / 0.579283 (-0.106017) | 0.581650 / 0.434364 (0.147286) | 0.522442 / 0.540337 (-0.017895) | 0.729039 / 1.386936 (-0.657897) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008349 / 0.011353 (-0.003003) | 0.005856 / 0.011008 (-0.005152) | 0.077855 / 0.038508 (0.039347) | 0.080608 / 0.023109 (0.057499) | 0.512533 / 0.275898 (0.236635) | 0.551862 / 0.323480 (0.228382) | 0.007004 / 0.007986 (-0.000982) | 0.004147 / 0.004328 (-0.000181) | 0.086625 / 0.004250 (0.082374) | 0.065962 / 0.037052 (0.028910) | 0.545590 / 0.258489 (0.287101) | 0.586313 / 0.293841 (0.292472) | 0.048719 / 0.128546 (-0.079827) | 0.014997 / 0.075646 (-0.060649) | 0.089510 / 0.419271 (-0.329761) | 0.060936 / 0.043533 (0.017404) | 0.498455 / 0.255139 (0.243316) | 0.535460 / 0.283200 (0.252260) | 0.034624 / 0.141683 (-0.107059) | 1.717401 / 1.452155 (0.265246) | 1.808772 / 1.492716 (0.316056) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.379504 / 0.018006 (0.361497) | 0.601756 / 0.000490 (0.601266) | 0.061740 / 0.000200 (0.061540) | 0.000497 / 0.000054 (0.000442) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.031215 / 0.037411 (-0.006196) | 0.097501 / 0.014526 (0.082975) | 0.117434 / 0.176557 (-0.059122) | 0.166014 / 0.737135 (-0.571121) | 0.116466 / 0.296338 (-0.179873) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.699444 / 0.215209 (0.484235) | 6.329332 / 2.077655 (4.251678) | 3.072812 / 1.504120 (1.568693) | 2.729878 / 1.541195 (1.188683) | 2.933785 / 1.468490 (1.465295) | 0.935858 / 4.584777 (-3.648919) | 5.532532 / 3.745712 (1.786820) | 4.677139 / 5.269862 (-0.592722) | 2.963527 / 4.565676 (-1.602149) | 0.099661 / 0.424275 (-0.324614) | 0.009095 / 0.007607 (0.001488) | 0.751158 / 0.226044 (0.525114) | 7.652588 / 2.268929 (5.383660) | 3.802005 / 55.444624 (-51.642619) | 3.163126 / 6.876477 (-3.713351) | 3.401125 / 2.142072 (1.259052) | 0.998627 / 4.805227 (-3.806600) | 0.203310 / 6.500664 (-6.297354) | 0.073827 / 0.075469 (-0.001642) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.662989 / 1.841788 (-0.178799) | 23.777818 / 8.074308 (15.703510) | 20.855378 / 10.191392 (10.663986) | 0.279892 / 0.680424 (-0.400532) | 0.029303 / 0.534201 (-0.504898) | 0.473681 / 0.579283 (-0.105602) | 0.579148 / 0.434364 (0.144784) | 0.546931 / 0.540337 (0.006593) | 0.769740 / 1.386936 (-0.617196) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#63114e9cb78fe02dc145f923dec13d545a8d0327 \"CML watermark\")\n" ]

"2023-09-04T13:13:53Z"

"2023-09-04T14:58:34Z"

"2023-09-04T14:47:17Z"

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[ "_The documentation is not available anymore as the PR was closed or merged._", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006494 / 0.011353 (-0.004859) | 0.003896 / 0.011008 (-0.007112) | 0.083940 / 0.038508 (0.045432) | 0.068335 / 0.023109 (0.045225) | 0.365770 / 0.275898 (0.089872) | 0.403702 / 0.323480 (0.080222) | 0.004005 / 0.007986 (-0.003981) | 0.003276 / 0.004328 (-0.001052) | 0.064877 / 0.004250 (0.060626) | 0.053524 / 0.037052 (0.016472) | 0.372951 / 0.258489 (0.114462) | 0.420935 / 0.293841 (0.127094) | 0.030656 / 0.128546 (-0.097890) | 0.009048 / 0.075646 (-0.066599) | 0.287607 / 0.419271 (-0.131665) | 0.052042 / 0.043533 (0.008509) | 0.371446 / 0.255139 (0.116307) | 0.408781 / 0.283200 (0.125581) | 0.024228 / 0.141683 (-0.117455) | 1.483325 / 1.452155 (0.031170) | 1.544321 / 1.492716 (0.051605) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.212355 / 0.018006 (0.194349) | 0.463298 / 0.000490 (0.462808) | 0.005170 / 0.000200 (0.004970) | 0.000087 / 0.000054 (0.000032) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.027824 / 0.037411 (-0.009587) | 0.081880 / 0.014526 (0.067354) | 0.094886 / 0.176557 (-0.081670) | 0.150024 / 0.737135 (-0.587111) | 0.096643 / 0.296338 (-0.199696) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.388521 / 0.215209 (0.173312) | 3.877251 / 2.077655 (1.799596) | 1.931085 / 1.504120 (0.426965) | 1.766525 / 1.541195 (0.225330) | 1.814802 / 1.468490 (0.346312) | 0.489478 / 4.584777 (-4.095299) | 3.570973 / 3.745712 (-0.174739) | 3.190211 / 5.269862 (-2.079651) | 2.015670 / 4.565676 (-2.550006) | 0.057773 / 0.424275 (-0.366503) | 0.007611 / 0.007607 (0.000004) | 0.462162 / 0.226044 (0.236117) | 4.616173 / 2.268929 (2.347244) | 2.360531 / 55.444624 (-53.084094) | 2.053680 / 6.876477 (-4.822797) | 2.228057 / 2.142072 (0.085985) | 0.584921 / 4.805227 (-4.220306) | 0.132470 / 6.500664 (-6.368194) | 0.060482 / 0.075469 (-0.014987) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.263393 / 1.841788 (-0.578394) | 19.416841 / 8.074308 (11.342532) | 14.049032 / 10.191392 (3.857640) | 0.162822 / 0.680424 (-0.517602) | 0.018189 / 0.534201 (-0.516012) | 0.391142 / 0.579283 (-0.188141) | 0.409367 / 0.434364 (-0.024997) | 0.454589 / 0.540337 (-0.085748) | 0.632946 / 1.386936 (-0.753990) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006568 / 0.011353 (-0.004785) | 0.004026 / 0.011008 (-0.006982) | 0.064522 / 0.038508 (0.026014) | 0.071738 / 0.023109 (0.048629) | 0.395771 / 0.275898 (0.119873) | 0.421553 / 0.323480 (0.098073) | 0.005291 / 0.007986 (-0.002694) | 0.003266 / 0.004328 (-0.001063) | 0.064464 / 0.004250 (0.060214) | 0.054622 / 0.037052 (0.017569) | 0.395010 / 0.258489 (0.136521) | 0.433895 / 0.293841 (0.140054) | 0.031670 / 0.128546 (-0.096876) | 0.008536 / 0.075646 (-0.067111) | 0.071059 / 0.419271 (-0.348212) | 0.047117 / 0.043533 (0.003584) | 0.391210 / 0.255139 (0.136071) | 0.411685 / 0.283200 (0.128486) | 0.022779 / 0.141683 (-0.118904) | 1.479900 / 1.452155 (0.027746) | 1.551853 / 1.492716 (0.059137) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.332814 / 0.018006 (0.314807) | 0.460654 / 0.000490 (0.460164) | 0.062257 / 0.000200 (0.062057) | 0.000374 / 0.000054 (0.000319) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.031801 / 0.037411 (-0.005610) | 0.090730 / 0.014526 (0.076204) | 0.102955 / 0.176557 (-0.073602) | 0.155928 / 0.737135 (-0.581207) | 0.103028 / 0.296338 (-0.193310) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.434460 / 0.215209 (0.219251) | 4.331550 / 2.077655 (2.253895) | 2.335990 / 1.504120 (0.831870) | 2.183985 / 1.541195 (0.642790) | 2.233086 / 1.468490 (0.764595) | 0.488484 / 4.584777 (-4.096293) | 3.603856 / 3.745712 (-0.141856) | 3.229833 / 5.269862 (-2.040029) | 2.007366 / 4.565676 (-2.558311) | 0.057658 / 0.424275 (-0.366617) | 0.007339 / 0.007607 (-0.000268) | 0.512812 / 0.226044 (0.286768) | 5.141497 / 2.268929 (2.872569) | 2.847383 / 55.444624 (-52.597241) | 2.467010 / 6.876477 (-4.409467) | 2.644995 / 2.142072 (0.502923) | 0.581385 / 4.805227 (-4.223842) | 0.130755 / 6.500664 (-6.369909) | 0.058834 / 0.075469 (-0.016635) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.350162 / 1.841788 (-0.491626) | 19.768412 / 8.074308 (11.694104) | 15.079196 / 10.191392 (4.887804) | 0.167083 / 0.680424 (-0.513341) | 0.020372 / 0.534201 (-0.513829) | 0.402685 / 0.579283 (-0.176598) | 0.408338 / 0.434364 (-0.026026) | 0.476788 / 0.540337 (-0.063550) | 0.654765 / 1.386936 (-0.732171) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#ff803c7e9f256c5a137c25c090e18d844f9fc6e4 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008047 / 0.011353 (-0.003305) | 0.004662 / 0.011008 (-0.006346) | 0.102487 / 0.038508 (0.063978) | 0.096832 / 0.023109 (0.073723) | 0.375298 / 0.275898 (0.099400) | 0.420604 / 0.323480 (0.097124) | 0.004655 / 0.007986 (-0.003330) | 0.005699 / 0.004328 (0.001370) | 0.077681 / 0.004250 (0.073430) | 0.065987 / 0.037052 (0.028935) | 0.393146 / 0.258489 (0.134657) | 0.436324 / 0.293841 (0.142483) | 0.036168 / 0.128546 (-0.092378) | 0.010398 / 0.075646 (-0.065248) | 0.347579 / 0.419271 (-0.071693) | 0.061723 / 0.043533 (0.018190) | 0.377439 / 0.255139 (0.122300) | 0.416666 / 0.283200 (0.133467) | 0.031874 / 0.141683 (-0.109809) | 1.818885 / 1.452155 (0.366730) | 1.904749 / 1.492716 (0.412032) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.240497 / 0.018006 (0.222491) | 0.507907 / 0.000490 (0.507417) | 0.004574 / 0.000200 (0.004374) | 0.000098 / 0.000054 (0.000044) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.033504 / 0.037411 (-0.003907) | 0.102919 / 0.014526 (0.088393) | 0.113014 / 0.176557 (-0.063543) | 0.181111 / 0.737135 (-0.556024) | 0.115047 / 0.296338 (-0.181291) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.453640 / 0.215209 (0.238431) | 4.514604 / 2.077655 (2.436949) | 2.219758 / 1.504120 (0.715638) | 2.004735 / 1.541195 (0.463541) | 2.112817 / 1.468490 (0.644327) | 0.579534 / 4.584777 (-4.005243) | 4.095994 / 3.745712 (0.350282) | 3.887204 / 5.269862 (-1.382658) | 2.461755 / 4.565676 (-2.103921) | 0.068930 / 0.424275 (-0.355345) | 0.009102 / 0.007607 (0.001495) | 0.540031 / 0.226044 (0.313987) | 5.394324 / 2.268929 (3.125396) | 2.738906 / 55.444624 (-52.705719) | 2.332041 / 6.876477 (-4.544436) | 2.600764 / 2.142072 (0.458692) | 0.697859 / 4.805227 (-4.107368) | 0.159247 / 6.500664 (-6.341417) | 0.073339 / 0.075469 (-0.002130) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.561082 / 1.841788 (-0.280706) | 23.581031 / 8.074308 (15.506723) | 17.011085 / 10.191392 (6.819693) | 0.196115 / 0.680424 (-0.484308) | 0.022050 / 0.534201 (-0.512151) | 0.470865 / 0.579283 (-0.108418) | 0.480539 / 0.434364 (0.046175) | 0.546458 / 0.540337 (0.006120) | 0.744353 / 1.386936 (-0.642583) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007884 / 0.011353 (-0.003468) | 0.004723 / 0.011008 (-0.006286) | 0.076431 / 0.038508 (0.037923) | 0.087016 / 0.023109 (0.063907) | 0.501880 / 0.275898 (0.225982) | 0.546286 / 0.323480 (0.222806) | 0.006224 / 0.007986 (-0.001762) | 0.003858 / 0.004328 (-0.000471) | 0.076485 / 0.004250 (0.072234) | 0.066758 / 0.037052 (0.029706) | 0.510090 / 0.258489 (0.251601) | 0.553935 / 0.293841 (0.260094) | 0.037785 / 0.128546 (-0.090761) | 0.009946 / 0.075646 (-0.065700) | 0.084001 / 0.419271 (-0.335270) | 0.056732 / 0.043533 (0.013199) | 0.490724 / 0.255139 (0.235585) | 0.528367 / 0.283200 (0.245168) | 0.026082 / 0.141683 (-0.115601) | 1.769200 / 1.452155 (0.317045) | 1.847559 / 1.492716 (0.354843) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.306752 / 0.018006 (0.288745) | 0.481215 / 0.000490 (0.480725) | 0.048231 / 0.000200 (0.048031) | 0.000249 / 0.000054 (0.000194) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.039517 / 0.037411 (0.002106) | 0.112884 / 0.014526 (0.098359) | 0.123858 / 0.176557 (-0.052698) | 0.188260 / 0.737135 (-0.548875) | 0.125819 / 0.296338 (-0.170520) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.515260 / 0.215209 (0.300051) | 5.125038 / 2.077655 (3.047383) | 2.785122 / 1.504120 (1.281003) | 2.590753 / 1.541195 (1.049558) | 2.682084 / 1.468490 (1.213594) | 0.581162 / 4.584777 (-4.003615) | 4.241776 / 3.745712 (0.496063) | 3.860979 / 5.269862 (-1.408883) | 2.434203 / 4.565676 (-2.131473) | 0.068580 / 0.424275 (-0.355695) | 0.008700 / 0.007607 (0.001093) | 0.604712 / 0.226044 (0.378667) | 6.044240 / 2.268929 (3.775311) | 3.379734 / 55.444624 (-52.064890) | 2.968906 / 6.876477 (-3.907571) | 3.195775 / 2.142072 (1.053703) | 0.702431 / 4.805227 (-4.102796) | 0.158752 / 6.500664 (-6.341912) | 0.072795 / 0.075469 (-0.002674) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.616354 / 1.841788 (-0.225434) | 24.258731 / 8.074308 (16.184423) | 17.505483 / 10.191392 (7.314091) | 0.173445 / 0.680424 (-0.506979) | 0.023215 / 0.534201 (-0.510986) | 0.472975 / 0.579283 (-0.106308) | 0.478425 / 0.434364 (0.044061) | 0.566950 / 0.540337 (0.026612) | 0.767648 / 1.386936 (-0.619288) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#a1d520a5226268f2c6f0303de3e8bfd72198b082 \"CML watermark\")\n" ]

"2023-09-04T07:07:07Z"

"2023-09-04T07:40:23Z"

"2023-09-04T07:30:00Z"

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"2023-09-04T06:47:05Z"

"2023-09-04T07:30:01Z"

"2023-09-04T07:30:01Z"

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[ "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006797 / 0.011353 (-0.004556) | 0.003966 / 0.011008 (-0.007042) | 0.085296 / 0.038508 (0.046788) | 0.076873 / 0.023109 (0.053764) | 0.355795 / 0.275898 (0.079897) | 0.397132 / 0.323480 (0.073652) | 0.005325 / 0.007986 (-0.002660) | 0.003343 / 0.004328 (-0.000986) | 0.064966 / 0.004250 (0.060716) | 0.054519 / 0.037052 (0.017467) | 0.357864 / 0.258489 (0.099374) | 0.409238 / 0.293841 (0.115397) | 0.031620 / 0.128546 (-0.096926) | 0.008529 / 0.075646 (-0.067117) | 0.288502 / 0.419271 (-0.130769) | 0.053260 / 0.043533 (0.009728) | 0.355245 / 0.255139 (0.100106) | 0.384139 / 0.283200 (0.100939) | 0.024507 / 0.141683 (-0.117176) | 1.494696 / 1.452155 (0.042541) | 1.579847 / 1.492716 (0.087130) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.204011 / 0.018006 (0.186005) | 0.451729 / 0.000490 (0.451239) | 0.004628 / 0.000200 (0.004428) | 0.000081 / 0.000054 (0.000026) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.028342 / 0.037411 (-0.009069) | 0.084647 / 0.014526 (0.070121) | 0.096174 / 0.176557 (-0.080383) | 0.151753 / 0.737135 (-0.585382) | 0.096347 / 0.296338 (-0.199991) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.387179 / 0.215209 (0.171970) | 3.861552 / 2.077655 (1.783898) | 1.844033 / 1.504120 (0.339913) | 1.678811 / 1.541195 (0.137616) | 1.793207 / 1.468490 (0.324717) | 0.485836 / 4.584777 (-4.098941) | 3.566274 / 3.745712 (-0.179438) | 3.269888 / 5.269862 (-1.999974) | 2.042850 / 4.565676 (-2.522827) | 0.057088 / 0.424275 (-0.367187) | 0.007627 / 0.007607 (0.000019) | 0.460510 / 0.226044 (0.234465) | 4.602019 / 2.268929 (2.333090) | 2.390984 / 55.444624 (-53.053641) | 1.976150 / 6.876477 (-4.900327) | 2.193394 / 2.142072 (0.051322) | 0.582775 / 4.805227 (-4.222453) | 0.133408 / 6.500664 (-6.367256) | 0.060577 / 0.075469 (-0.014893) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.248505 / 1.841788 (-0.593283) | 19.771301 / 8.074308 (11.696993) | 14.327871 / 10.191392 (4.136479) | 0.155288 / 0.680424 (-0.525136) | 0.018310 / 0.534201 (-0.515891) | 0.393664 / 0.579283 (-0.185619) | 0.410578 / 0.434364 (-0.023786) | 0.459301 / 0.540337 (-0.081037) | 0.631921 / 1.386936 (-0.755015) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006827 / 0.011353 (-0.004526) | 0.004094 / 0.011008 (-0.006915) | 0.065299 / 0.038508 (0.026791) | 0.079496 / 0.023109 (0.056387) | 0.403661 / 0.275898 (0.127763) | 0.434449 / 0.323480 (0.110969) | 0.005398 / 0.007986 (-0.002588) | 0.003410 / 0.004328 (-0.000919) | 0.064832 / 0.004250 (0.060582) | 0.056303 / 0.037052 (0.019250) | 0.397848 / 0.258489 (0.139359) | 0.438244 / 0.293841 (0.144403) | 0.032637 / 0.128546 (-0.095909) | 0.008584 / 0.075646 (-0.067063) | 0.071406 / 0.419271 (-0.347866) | 0.048265 / 0.043533 (0.004732) | 0.397814 / 0.255139 (0.142675) | 0.421601 / 0.283200 (0.138402) | 0.023815 / 0.141683 (-0.117868) | 1.504814 / 1.452155 (0.052659) | 1.577185 / 1.492716 (0.084469) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.231775 / 0.018006 (0.213769) | 0.445437 / 0.000490 (0.444948) | 0.005252 / 0.000200 (0.005052) | 0.000093 / 0.000054 (0.000039) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.032777 / 0.037411 (-0.004634) | 0.095054 / 0.014526 (0.080528) | 0.106429 / 0.176557 (-0.070127) | 0.160111 / 0.737135 (-0.577024) | 0.108075 / 0.296338 (-0.188263) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.426034 / 0.215209 (0.210825) | 4.244668 / 2.077655 (2.167013) | 2.257938 / 1.504120 (0.753818) | 2.087993 / 1.541195 (0.546798) | 2.170878 / 1.468490 (0.702387) | 0.485228 / 4.584777 (-4.099549) | 3.725912 / 3.745712 (-0.019800) | 3.286925 / 5.269862 (-1.982937) | 2.059929 / 4.565676 (-2.505748) | 0.057813 / 0.424275 (-0.366462) | 0.007518 / 0.007607 (-0.000089) | 0.506632 / 0.226044 (0.280588) | 5.048340 / 2.268929 (2.779411) | 2.744756 / 55.444624 (-52.699869) | 2.406636 / 6.876477 (-4.469841) | 2.617552 / 2.142072 (0.475480) | 0.588476 / 4.805227 (-4.216751) | 0.133518 / 6.500664 (-6.367146) | 0.060778 / 0.075469 (-0.014691) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.356416 / 1.841788 (-0.485372) | 20.467516 / 8.074308 (12.393208) | 15.265443 / 10.191392 (5.074051) | 0.169201 / 0.680424 (-0.511223) | 0.020087 / 0.534201 (-0.514114) | 0.402332 / 0.579283 (-0.176951) | 0.414848 / 0.434364 (-0.019516) | 0.470422 / 0.540337 (-0.069916) | 0.647266 / 1.386936 (-0.739670) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#eb001b4cee7f1d71e393c3ad489a8a5cd8119df5 \"CML watermark\")\n", "_The documentation is not available anymore as the PR was closed or merged._", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.005804 / 0.011353 (-0.005549) | 0.003519 / 0.011008 (-0.007489) | 0.080003 / 0.038508 (0.041495) | 0.055419 / 0.023109 (0.032309) | 0.395254 / 0.275898 (0.119356) | 0.432714 / 0.323480 (0.109234) | 0.004438 / 0.007986 (-0.003548) | 0.002832 / 0.004328 (-0.001496) | 0.062026 / 0.004250 (0.057775) | 0.044334 / 0.037052 (0.007282) | 0.401278 / 0.258489 (0.142789) | 0.451516 / 0.293841 (0.157675) | 0.026791 / 0.128546 (-0.101755) | 0.007946 / 0.075646 (-0.067700) | 0.265166 / 0.419271 (-0.154106) | 0.044119 / 0.043533 (0.000586) | 0.399621 / 0.255139 (0.144482) | 0.422808 / 0.283200 (0.139609) | 0.019998 / 0.141683 (-0.121685) | 1.433559 / 1.452155 (-0.018596) | 1.596902 / 1.492716 (0.104186) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.195662 / 0.018006 (0.177656) | 0.423167 / 0.000490 (0.422677) | 0.003426 / 0.000200 (0.003227) | 0.000066 / 0.000054 (0.000012) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.023318 / 0.037411 (-0.014094) | 0.072532 / 0.014526 (0.058006) | 0.082181 / 0.176557 (-0.094375) | 0.142214 / 0.737135 (-0.594921) | 0.083423 / 0.296338 (-0.212915) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.402270 / 0.215209 (0.187061) | 4.027607 / 2.077655 (1.949953) | 2.059803 / 1.504120 (0.555684) | 1.865115 / 1.541195 (0.323920) | 1.934976 / 1.468490 (0.466485) | 0.502145 / 4.584777 (-4.082632) | 2.970865 / 3.745712 (-0.774847) | 2.784155 / 5.269862 (-2.485707) | 1.822003 / 4.565676 (-2.743673) | 0.057699 / 0.424275 (-0.366576) | 0.006668 / 0.007607 (-0.000939) | 0.471164 / 0.226044 (0.245120) | 4.733079 / 2.268929 (2.464150) | 2.445119 / 55.444624 (-52.999505) | 2.132956 / 6.876477 (-4.743521) | 2.335998 / 2.142072 (0.193926) | 0.594881 / 4.805227 (-4.210347) | 0.125801 / 6.500664 (-6.374863) | 0.060780 / 0.075469 (-0.014689) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.233170 / 1.841788 (-0.608618) | 17.942205 / 8.074308 (9.867897) | 13.587020 / 10.191392 (3.395628) | 0.142110 / 0.680424 (-0.538314) | 0.016600 / 0.534201 (-0.517601) | 0.328659 / 0.579283 (-0.250624) | 0.347759 / 0.434364 (-0.086605) | 0.378651 / 0.540337 (-0.161687) | 0.523474 / 1.386936 (-0.863462) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006028 / 0.011353 (-0.005325) | 0.003552 / 0.011008 (-0.007456) | 0.062175 / 0.038508 (0.023667) | 0.057602 / 0.023109 (0.034493) | 0.444585 / 0.275898 (0.168687) | 0.471238 / 0.323480 (0.147758) | 0.004562 / 0.007986 (-0.003423) | 0.002871 / 0.004328 (-0.001457) | 0.063101 / 0.004250 (0.058851) | 0.046072 / 0.037052 (0.009020) | 0.448253 / 0.258489 (0.189764) | 0.478734 / 0.293841 (0.184893) | 0.028463 / 0.128546 (-0.100084) | 0.008090 / 0.075646 (-0.067557) | 0.068142 / 0.419271 (-0.351130) | 0.040517 / 0.043533 (-0.003016) | 0.447145 / 0.255139 (0.192006) | 0.469472 / 0.283200 (0.186273) | 0.019391 / 0.141683 (-0.122291) | 1.471195 / 1.452155 (0.019040) | 1.532966 / 1.492716 (0.040249) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.259894 / 0.018006 (0.241888) | 0.412987 / 0.000490 (0.412497) | 0.020780 / 0.000200 (0.020580) | 0.000084 / 0.000054 (0.000030) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.026352 / 0.037411 (-0.011060) | 0.080024 / 0.014526 (0.065498) | 0.088041 / 0.176557 (-0.088516) | 0.142987 / 0.737135 (-0.594148) | 0.090108 / 0.296338 (-0.206231) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.458874 / 0.215209 (0.243665) | 4.573005 / 2.077655 (2.495351) | 2.507885 / 1.504120 (1.003765) | 2.335432 / 1.541195 (0.794238) | 2.379617 / 1.468490 (0.911126) | 0.503331 / 4.584777 (-4.081446) | 3.078284 / 3.745712 (-0.667428) | 2.750580 / 5.269862 (-2.519282) | 1.828100 / 4.565676 (-2.737577) | 0.057572 / 0.424275 (-0.366703) | 0.006553 / 0.007607 (-0.001054) | 0.532283 / 0.226044 (0.306239) | 5.310584 / 2.268929 (3.041656) | 2.943559 / 55.444624 (-52.501065) | 2.587544 / 6.876477 (-4.288932) | 2.718261 / 2.142072 (0.576188) | 0.590267 / 4.805227 (-4.214961) | 0.123229 / 6.500664 (-6.377435) | 0.060219 / 0.075469 (-0.015250) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.340773 / 1.841788 (-0.501014) | 18.420766 / 8.074308 (10.346458) | 14.630550 / 10.191392 (4.439158) | 0.146666 / 0.680424 (-0.533758) | 0.017905 / 0.534201 (-0.516296) | 0.332483 / 0.579283 (-0.246801) | 0.355490 / 0.434364 (-0.078874) | 0.382618 / 0.540337 (-0.157720) | 0.531336 / 1.386936 (-0.855600) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#d438617fc577bc0222527714edafea0c52ebf239 \"CML watermark\")\n", "There were CI errors unrelated to this PR.", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008702 / 0.011353 (-0.002651) | 0.005060 / 0.011008 (-0.005948) | 0.097017 / 0.038508 (0.058509) | 0.073740 / 0.023109 (0.050631) | 0.435138 / 0.275898 (0.159240) | 0.512776 / 0.323480 (0.189296) | 0.006186 / 0.007986 (-0.001800) | 0.003970 / 0.004328 (-0.000358) | 0.089523 / 0.004250 (0.085273) | 0.054441 / 0.037052 (0.017389) | 0.447415 / 0.258489 (0.188926) | 0.464851 / 0.293841 (0.171010) | 0.050264 / 0.128546 (-0.078283) | 0.016643 / 0.075646 (-0.059004) | 0.350565 / 0.419271 (-0.068707) | 0.071220 / 0.043533 (0.027687) | 0.432531 / 0.255139 (0.177392) | 0.472994 / 0.283200 (0.189795) | 0.040229 / 0.141683 (-0.101454) | 1.743431 / 1.452155 (0.291276) | 1.778653 / 1.492716 (0.285936) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.261992 / 0.018006 (0.243986) | 0.571979 / 0.000490 (0.571489) | 0.006270 / 0.000200 (0.006071) | 0.000109 / 0.000054 (0.000054) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.027821 / 0.037411 (-0.009590) | 0.081874 / 0.014526 (0.067348) | 0.103725 / 0.176557 (-0.072831) | 0.170593 / 0.737135 (-0.566542) | 0.108749 / 0.296338 (-0.187590) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.690774 / 0.215209 (0.475565) | 6.770902 / 2.077655 (4.693247) | 2.887218 / 1.504120 (1.383098) | 2.456226 / 1.541195 (0.915032) | 2.509422 / 1.468490 (1.040932) | 0.768451 / 4.584777 (-3.816326) | 4.988933 / 3.745712 (1.243221) | 4.151460 / 5.269862 (-1.118402) | 2.640472 / 4.565676 (-1.925205) | 0.093522 / 0.424275 (-0.330753) | 0.008614 / 0.007607 (0.001007) | 0.696281 / 0.226044 (0.470237) | 6.721077 / 2.268929 (4.452149) | 3.229760 / 55.444624 (-52.214864) | 2.668521 / 6.876477 (-4.207956) | 2.866420 / 2.142072 (0.724347) | 0.945328 / 4.805227 (-3.859899) | 0.197645 / 6.500664 (-6.303019) | 0.074442 / 0.075469 (-0.001027) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.630468 / 1.841788 (-0.211320) | 22.991661 / 8.074308 (14.917353) | 19.816919 / 10.191392 (9.625527) | 0.257410 / 0.680424 (-0.423014) | 0.027228 / 0.534201 (-0.506973) | 0.444515 / 0.579283 (-0.134768) | 0.597067 / 0.434364 (0.162703) | 0.528151 / 0.540337 (-0.012186) | 0.771276 / 1.386936 (-0.615660) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.009154 / 0.011353 (-0.002199) | 0.004648 / 0.011008 (-0.006360) | 0.073054 / 0.038508 (0.034546) | 0.077146 / 0.023109 (0.054037) | 0.481659 / 0.275898 (0.205761) | 0.516985 / 0.323480 (0.193505) | 0.007447 / 0.007986 (-0.000538) | 0.003890 / 0.004328 (-0.000438) | 0.078701 / 0.004250 (0.074450) | 0.059183 / 0.037052 (0.022131) | 0.475350 / 0.258489 (0.216861) | 0.547834 / 0.293841 (0.253993) | 0.058440 / 0.128546 (-0.070106) | 0.013563 / 0.075646 (-0.062083) | 0.084320 / 0.419271 (-0.334951) | 0.065965 / 0.043533 (0.022433) | 0.483541 / 0.255139 (0.228402) | 0.513940 / 0.283200 (0.230740) | 0.042889 / 0.141683 (-0.098794) | 1.676050 / 1.452155 (0.223895) | 1.759206 / 1.492716 (0.266489) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.274848 / 0.018006 (0.256841) | 0.588965 / 0.000490 (0.588475) | 0.006312 / 0.000200 (0.006112) | 0.000120 / 0.000054 (0.000065) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.033871 / 0.037411 (-0.003540) | 0.104013 / 0.014526 (0.089487) | 0.118457 / 0.176557 (-0.058099) | 0.178268 / 0.737135 (-0.558868) | 0.116972 / 0.296338 (-0.179366) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.609952 / 0.215209 (0.394743) | 5.788754 / 2.077655 (3.711100) | 2.812166 / 1.504120 (1.308046) | 2.362861 / 1.541195 (0.821666) | 2.641295 / 1.468490 (1.172804) | 0.767601 / 4.584777 (-3.817176) | 5.027439 / 3.745712 (1.281727) | 4.612511 / 5.269862 (-0.657351) | 2.654364 / 4.565676 (-1.911312) | 0.103100 / 0.424275 (-0.321175) | 0.012233 / 0.007607 (0.004626) | 0.749283 / 0.226044 (0.523238) | 7.511093 / 2.268929 (5.242165) | 3.585867 / 55.444624 (-51.858757) | 3.255110 / 6.876477 (-3.621366) | 3.260174 / 2.142072 (1.118102) | 0.958422 / 4.805227 (-3.846806) | 0.209096 / 6.500664 (-6.291568) | 0.075014 / 0.075469 (-0.000455) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.728283 / 1.841788 (-0.113504) | 25.411147 / 8.074308 (17.336839) | 21.335202 / 10.191392 (11.143810) | 0.199090 / 0.680424 (-0.481334) | 0.031288 / 0.534201 (-0.502913) | 0.449226 / 0.579283 (-0.130057) | 0.555570 / 0.434364 (0.121206) | 0.570297 / 0.540337 (0.029960) | 0.758673 / 1.386936 (-0.628263) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#fa696b4b4f0d11c5b8592eb31cb1d54a707e3d33 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006862 / 0.011353 (-0.004491) | 0.003959 / 0.011008 (-0.007049) | 0.087219 / 0.038508 (0.048711) | 0.078335 / 0.023109 (0.055226) | 0.319019 / 0.275898 (0.043121) | 0.342871 / 0.323480 (0.019391) | 0.004065 / 0.007986 (-0.003921) | 0.004346 / 0.004328 (0.000017) | 0.065243 / 0.004250 (0.060993) | 0.056698 / 0.037052 (0.019646) | 0.326906 / 0.258489 (0.068417) | 0.354323 / 0.293841 (0.060482) | 0.031252 / 0.128546 (-0.097295) | 0.008587 / 0.075646 (-0.067060) | 0.300323 / 0.419271 (-0.118948) | 0.052810 / 0.043533 (0.009277) | 0.323866 / 0.255139 (0.068727) | 0.346011 / 0.283200 (0.062811) | 0.025584 / 0.141683 (-0.116099) | 1.464475 / 1.452155 (0.012320) | 1.530868 / 1.492716 (0.038152) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.208927 / 0.018006 (0.190921) | 0.454147 / 0.000490 (0.453657) | 0.003945 / 0.000200 (0.003746) | 0.000081 / 0.000054 (0.000026) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.029901 / 0.037411 (-0.007511) | 0.088889 / 0.014526 (0.074363) | 0.098181 / 0.176557 (-0.078375) | 0.156787 / 0.737135 (-0.580349) | 0.099015 / 0.296338 (-0.197324) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.384981 / 0.215209 (0.169772) | 3.831040 / 2.077655 (1.753386) | 1.858312 / 1.504120 (0.354192) | 1.686846 / 1.541195 (0.145651) | 1.771509 / 1.468490 (0.303019) | 0.485618 / 4.584777 (-4.099159) | 3.430961 / 3.745712 (-0.314751) | 3.264489 / 5.269862 (-2.005372) | 2.040125 / 4.565676 (-2.525551) | 0.057218 / 0.424275 (-0.367057) | 0.007640 / 0.007607 (0.000033) | 0.468072 / 0.226044 (0.242027) | 4.677214 / 2.268929 (2.408286) | 2.348425 / 55.444624 (-53.096199) | 1.994352 / 6.876477 (-4.882125) | 2.217020 / 2.142072 (0.074948) | 0.587467 / 4.805227 (-4.217760) | 0.133550 / 6.500664 (-6.367114) | 0.060571 / 0.075469 (-0.014898) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.271003 / 1.841788 (-0.570785) | 19.986365 / 8.074308 (11.912057) | 14.574046 / 10.191392 (4.382654) | 0.146212 / 0.680424 (-0.534212) | 0.018320 / 0.534201 (-0.515881) | 0.394524 / 0.579283 (-0.184759) | 0.399707 / 0.434364 (-0.034657) | 0.458965 / 0.540337 (-0.081372) | 0.619940 / 1.386936 (-0.766996) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006982 / 0.011353 (-0.004371) | 0.004061 / 0.011008 (-0.006947) | 0.064520 / 0.038508 (0.026012) | 0.076828 / 0.023109 (0.053719) | 0.402989 / 0.275898 (0.127090) | 0.439697 / 0.323480 (0.116217) | 0.005511 / 0.007986 (-0.002475) | 0.003378 / 0.004328 (-0.000950) | 0.064727 / 0.004250 (0.060477) | 0.058114 / 0.037052 (0.021062) | 0.402054 / 0.258489 (0.143565) | 0.442377 / 0.293841 (0.148536) | 0.032808 / 0.128546 (-0.095738) | 0.008604 / 0.075646 (-0.067043) | 0.070994 / 0.419271 (-0.348278) | 0.048738 / 0.043533 (0.005205) | 0.399786 / 0.255139 (0.144647) | 0.423537 / 0.283200 (0.140338) | 0.022397 / 0.141683 (-0.119286) | 1.504613 / 1.452155 (0.052458) | 1.571064 / 1.492716 (0.078348) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.226876 / 0.018006 (0.208870) | 0.451477 / 0.000490 (0.450987) | 0.004511 / 0.000200 (0.004311) | 0.000095 / 0.000054 (0.000041) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.032998 / 0.037411 (-0.004413) | 0.095843 / 0.014526 (0.081317) | 0.105684 / 0.176557 (-0.070873) | 0.158175 / 0.737135 (-0.578960) | 0.107297 / 0.296338 (-0.189041) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.434912 / 0.215209 (0.219703) | 4.326394 / 2.077655 (2.248740) | 2.287310 / 1.504120 (0.783190) | 2.127987 / 1.541195 (0.586793) | 2.202485 / 1.468490 (0.733995) | 0.494305 / 4.584777 (-4.090472) | 3.575176 / 3.745712 (-0.170536) | 3.354358 / 5.269862 (-1.915504) | 2.074293 / 4.565676 (-2.491383) | 0.058967 / 0.424275 (-0.365308) | 0.007712 / 0.007607 (0.000105) | 0.513734 / 0.226044 (0.287690) | 5.107538 / 2.268929 (2.838610) | 2.776190 / 55.444624 (-52.668434) | 2.425051 / 6.876477 (-4.451426) | 2.666715 / 2.142072 (0.524643) | 0.598844 / 4.805227 (-4.206383) | 0.134186 / 6.500664 (-6.366478) | 0.062403 / 0.075469 (-0.013066) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.346730 / 1.841788 (-0.495058) | 20.533190 / 8.074308 (12.458882) | 15.174443 / 10.191392 (4.983051) | 0.167204 / 0.680424 (-0.513219) | 0.020619 / 0.534201 (-0.513582) | 0.399033 / 0.579283 (-0.180250) | 0.394428 / 0.434364 (-0.039936) | 0.468792 / 0.540337 (-0.071545) | 0.640122 / 1.386936 (-0.746814) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#2c4c2b529e2a262a5006e4caa55fbc003378006a \"CML watermark\")\n" ]

"2023-09-04T06:07:12Z"

"2023-09-04T09:22:19Z"

"2023-09-04T09:13:32Z"

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"2023-09-04T05:50:27Z"

"2023-09-04T09:13:33Z"

"2023-09-04T09:13:33Z"

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[ "I solved the problem by modifying the \"self DEFAULT_WRITER_BATCH_SIZE\" in \"class MyDataset (datasets. GeneratorBasedBuilder) : __init__\"" ]

"2023-09-04T04:14:00Z"

"2023-09-04T06:05:50Z"

"2023-09-04T06:05:49Z"

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[ "(cross-posting from the linked DVC issue)\r\n\r\nI think this should already work out of the box with the current `datasets` and `dvc.api` releases by passing the correct `storage_options` into the datasets calls. `storage_options` is essentially just the kwargs dict that gets passed to the fsspec fs constructor.\r\n\r\nThe main thing to note here is that the fsspec DVCFileSystem URL should be `dvc://folder/file.json` (i.e. this should be the DVCFileSystem path that is relative to the DVC repo root). You cannot use a URL like `https://gitlab.com/user/repo/folder/file.json`.\r\n\r\nI think something like this should work for you (in a venv where both DVC and datasets are installed):\r\n```python\r\nimport datasets\r\n\r\n# load a dataset from Git/DVC repository where Git repo is located at https://gitlab.com/user/repo.git\r\n# and path to dataset (relative to git/dvc repo root) is 'folder/file.json'\r\ndatasets.load_from_disk(\r\n \"dvc://folder/file.json\",\r\n storage_options={\"url\": \"https://gitlab.com/user/repo.git\"},\r\n)\r\n```\r\n\r\nbasically the `dvc://` is what tells fsspec to create a `DVCFileSystem` and it will construct it like\r\n```python\r\nfs = DVCFileSystem(**storage_options)\r\n```\r\n\r\nThen the subsequent calls use the rest of the `dvc://...` URL like \r\n```python\r\nfs.exists(\"folder/file.json\")\r\n```", "Hi @pmrowla Thank you for your help, that's very helpful, I was indeed using `fsspec` incorrectly here. There is still an issue with `datasets`:\r\n\r\n```python\r\nimport datasets\r\ndataset = datasets.load_dataset(\"json\", data_files=\"dvc://folder/file.jsonl\", storage_options={\"url\": \"https://gitlab.com/repo/folder/\"})\r\n```\r\n\r\nresults in the following exception:\r\n\r\n```\r\nTraceback (most recent call last): \r\n File \"/Users/bilelomrani/Documents/ILLUIN.nosync/instructions-finetuning/.venv/lib/python3.11/site-packages/scmrepo/fs.py\", line 217, in info\r\n ret = self.trie.info(key)\r\n ^^^^^^^^^^^^^^^^^^^\r\n File \"/Users/bilelomrani/Documents/ILLUIN.nosync/instructions-finetuning/.venv/lib/python3.11/site-packages/scmrepo/git/objects.py\", line 141, in info\r\n obj = self.trie[key]\r\n ~~~~~~~~~^^^^^\r\n File \"/Users/bilelomrani/Documents/ILLUIN.nosync/instructions-finetuning/.venv/lib/python3.11/site-packages/pygtrie.py\", line 937, in __getitem__\r\n node, _ = self._get_node(key_or_slice)\r\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^\r\n File \"/Users/bilelomrani/Documents/ILLUIN.nosync/instructions-finetuning/.venv/lib/python3.11/site-packages/pygtrie.py\", line 630, in _get_node\r\n raise KeyError(key)\r\nKeyError: ('dvc:', 'datasets', 'spider', 'train.jsonl')\r\n\r\nDuring handling of the above exception, another exception occurred:\r\n\r\nTraceback (most recent call last):\r\n File \"<stdin>\", line 1, in <module>\r\n File \"/Users/bilelomrani/Documents/ILLUIN.nosync/instructions-finetuning/.venv/lib/python3.11/site-packages/datasets/load.py\", line 2129, in load_dataset\r\n builder_instance = load_dataset_builder(\r\n ^^^^^^^^^^^^^^^^^^^^^\r\n File \"/Users/bilelomrani/Documents/ILLUIN.nosync/instructions-finetuning/.venv/lib/python3.11/site-packages/datasets/load.py\", line 1815, in load_dataset_builder\r\n dataset_module = dataset_module_factory(\r\n ^^^^^^^^^^^^^^^^^^^^^^^\r\n File \"/Users/bilelomrani/Documents/ILLUIN.nosync/instructions-finetuning/.venv/lib/python3.11/site-packages/datasets/load.py\", line 1430, in dataset_module_factory\r\n ).get_module()\r\n ^^^^^^^^^^^^\r\n File \"/Users/bilelomrani/Documents/ILLUIN.nosync/instructions-finetuning/.venv/lib/python3.11/site-packages/datasets/load.py\", line 958, in get_module\r\n data_files = DataFilesDict.from_patterns(\r\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^\r\n File \"/Users/bilelomrani/Documents/ILLUIN.nosync/instructions-finetuning/.venv/lib/python3.11/site-packages/datasets/data_files.py\", line 674, in from_patterns\r\n DataFilesList.from_patterns(\r\n File \"/Users/bilelomrani/Documents/ILLUIN.nosync/instructions-finetuning/.venv/lib/python3.11/site-packages/datasets/data_files.py\", line 589, in from_patterns\r\n origin_metadata = _get_origin_metadata(data_files, download_config=download_config)\r\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\r\n File \"/Users/bilelomrani/Documents/ILLUIN.nosync/instructions-finetuning/.venv/lib/python3.11/site-packages/datasets/data_files.py\", line 504, in _get_origin_metadata\r\n return thread_map(\r\n ^^^^^^^^^^^\r\n File \"/Users/bilelomrani/Documents/ILLUIN.nosync/instructions-finetuning/.venv/lib/python3.11/site-packages/tqdm/contrib/concurrent.py\", line 69, in thread_map\r\n return _executor_map(ThreadPoolExecutor, fn, *iterables, **tqdm_kwargs)\r\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\r\n File \"/Users/bilelomrani/Documents/ILLUIN.nosync/instructions-finetuning/.venv/lib/python3.11/site-packages/tqdm/contrib/concurrent.py\", line 51, in _executor_map\r\n return list(tqdm_class(ex.map(fn, *iterables, chunksize=chunksize), **kwargs))\r\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\r\n File \"/Users/bilelomrani/.pyenv/versions/3.11.4/lib/python3.11/concurrent/futures/_base.py\", line 619, in result_iterator\r\n yield _result_or_cancel(fs.pop())\r\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^\r\n File \"/Users/bilelomrani/.pyenv/versions/3.11.4/lib/python3.11/concurrent/futures/_base.py\", line 317, in _result_or_cancel\r\n return fut.result(timeout)\r\n ^^^^^^^^^^^^^^^^^^^\r\n File \"/Users/bilelomrani/.pyenv/versions/3.11.4/lib/python3.11/concurrent/futures/_base.py\", line 456, in result\r\n return self.__get_result()\r\n ^^^^^^^^^^^^^^^^^^^\r\n File \"/Users/bilelomrani/.pyenv/versions/3.11.4/lib/python3.11/concurrent/futures/_base.py\", line 401, in __get_result\r\n raise self._exception\r\n File \"/Users/bilelomrani/.pyenv/versions/3.11.4/lib/python3.11/concurrent/futures/thread.py\", line 58, in run\r\n result = self.fn(*self.args, **self.kwargs)\r\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\r\n File \"/Users/bilelomrani/Documents/ILLUIN.nosync/instructions-finetuning/.venv/lib/python3.11/site-packages/datasets/data_files.py\", line 491, in _get_single_origin_metadata\r\n info = fs.info(data_file)\r\n ^^^^^^^^^^^^^^^^^^\r\n File \"/Users/bilelomrani/Documents/ILLUIN.nosync/instructions-finetuning/.venv/lib/python3.11/site-packages/dvc/fs/dvc.py\", line 357, in info\r\n return self._info(key, path, ignore_subrepos=ignore_subrepos)\r\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\r\n File \"/Users/bilelomrani/Documents/ILLUIN.nosync/instructions-finetuning/.venv/lib/python3.11/site-packages/dvc/fs/dvc.py\", line 377, in _info\r\n fs_info = fs.info(fs_path)\r\n ^^^^^^^^^^^^^^^^\r\n File \"/Users/bilelomrani/Documents/ILLUIN.nosync/instructions-finetuning/.venv/lib/python3.11/site-packages/dvc_objects/fs/base.py\", line 501, in info\r\n return self.fs.info(path, **kwargs)\r\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^\r\n File \"/Users/bilelomrani/Documents/ILLUIN.nosync/instructions-finetuning/.venv/lib/python3.11/site-packages/scmrepo/fs.py\", line 221, in info\r\n raise FileNotFoundError(errno.ENOENT, os.strerror(errno.ENOENT), path)\r\nFileNotFoundError: [Errno 2] No such file or directory: '/dvc:/folder/file.jsonl'\r\n```\r\n\r\nSomehow the URL gets turned into `/dvc:/folder/file.jsonl` inside `datasets`. Otherwise I can confirm that using `fsspec` properly with DVC works as expected.\r\n", "For the record, there was a `dvc.api.DVCFileSystem` bug which is fixed in DVC `main` and will be available in the next DVC release.\r\n\r\nTo use DVC with `datasets` you just need to pass the Git/DVC repo `url` in `storage_options` as discussed above.\r\n\r\n(note that this requires having both `datasets` and `dvc` installed in your python environment)\r\n```python\r\n>>> from datasets import load_dataset\r\n>>> load_dataset(\r\n... \"json\",\r\n... data_files=\"dvc://eval/metrics.json\",\r\n... storage_options={\"url\": \"https://github.com/iterative/example-get-started.git\"},\r\n... )\r\nDatasetDict({\r\n train: Dataset({\r\n features: ['avg_prec', 'roc_auc'],\r\n num_rows: 1\r\n })\r\n})\r\n```\r\n\r\nAny additional `DVCFileSystem` args can be passed in the same way, so to get a specific branch/tag/commit from the DVC repo you just need to specify the `rev` in `storage_options` like\r\n```\r\nstorage_options={\"url\": \"https://github.com/iterative/example-get-started.git\", \"rev\": \"main\"}\r\n```\r\n\r\nI think this issue can probably be closed now.", "Thank you for your help, closing." ]

"2023-09-01T14:04:52Z"

"2023-09-15T06:09:00Z"

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"2023-09-01T02:57:57Z"

"2023-09-01T02:58:53Z"

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[ "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006852 / 0.011353 (-0.004501) | 0.004195 / 0.011008 (-0.006813) | 0.095008 / 0.038508 (0.056500) | 0.073469 / 0.023109 (0.050360) | 0.350170 / 0.275898 (0.074272) | 0.394309 / 0.323480 (0.070829) | 0.004391 / 0.007986 (-0.003595) | 0.003432 / 0.004328 (-0.000896) | 0.072849 / 0.004250 (0.068599) | 0.058595 / 0.037052 (0.021543) | 0.372335 / 0.258489 (0.113846) | 0.410616 / 0.293841 (0.116775) | 0.034477 / 0.128546 (-0.094069) | 0.009426 / 0.075646 (-0.066220) | 0.329262 / 0.419271 (-0.090009) | 0.057941 / 0.043533 (0.014408) | 0.358624 / 0.255139 (0.103485) | 0.413803 / 0.283200 (0.130604) | 0.025845 / 0.141683 (-0.115837) | 1.684289 / 1.452155 (0.232134) | 1.791567 / 1.492716 (0.298850) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.222731 / 0.018006 (0.204724) | 0.511615 / 0.000490 (0.511126) | 0.004163 / 0.000200 (0.003963) | 0.000088 / 0.000054 (0.000033) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.033260 / 0.037411 (-0.004152) | 0.091685 / 0.014526 (0.077159) | 0.105655 / 0.176557 (-0.070901) | 0.167973 / 0.737135 (-0.569163) | 0.105458 / 0.296338 (-0.190880) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.441789 / 0.215209 (0.226580) | 4.404803 / 2.077655 (2.327148) | 2.163739 / 1.504120 (0.659620) | 1.956828 / 1.541195 (0.415633) | 2.042183 / 1.468490 (0.573693) | 0.552221 / 4.584777 (-4.032556) | 3.951769 / 3.745712 (0.206057) | 3.591983 / 5.269862 (-1.677878) | 2.225058 / 4.565676 (-2.340619) | 0.064528 / 0.424275 (-0.359747) | 0.008403 / 0.007607 (0.000796) | 0.528830 / 0.226044 (0.302786) | 5.233686 / 2.268929 (2.964757) | 2.681156 / 55.444624 (-52.763468) | 2.261188 / 6.876477 (-4.615289) | 2.470037 / 2.142072 (0.327964) | 0.661793 / 4.805227 (-4.143434) | 0.150138 / 6.500664 (-6.350527) | 0.068663 / 0.075469 (-0.006807) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.463086 / 1.841788 (-0.378701) | 21.408232 / 8.074308 (13.333924) | 15.521718 / 10.191392 (5.330326) | 0.164587 / 0.680424 (-0.515837) | 0.021035 / 0.534201 (-0.513166) | 0.445466 / 0.579283 (-0.133817) | 0.462489 / 0.434364 (0.028125) | 0.517733 / 0.540337 (-0.022604) | 0.724242 / 1.386936 (-0.662694) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007117 / 0.011353 (-0.004236) | 0.004230 / 0.011008 (-0.006778) | 0.072186 / 0.038508 (0.033678) | 0.076758 / 0.023109 (0.053648) | 0.452606 / 0.275898 (0.176708) | 0.491872 / 0.323480 (0.168392) | 0.005989 / 0.007986 (-0.001996) | 0.003611 / 0.004328 (-0.000717) | 0.072642 / 0.004250 (0.068392) | 0.058985 / 0.037052 (0.021933) | 0.463414 / 0.258489 (0.204925) | 0.497538 / 0.293841 (0.203697) | 0.036325 / 0.128546 (-0.092221) | 0.009814 / 0.075646 (-0.065832) | 0.078745 / 0.419271 (-0.340527) | 0.054308 / 0.043533 (0.010775) | 0.468210 / 0.255139 (0.213071) | 0.476434 / 0.283200 (0.193234) | 0.023683 / 0.141683 (-0.118000) | 1.706457 / 1.452155 (0.254302) | 1.775855 / 1.492716 (0.283139) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.241599 / 0.018006 (0.223592) | 0.483859 / 0.000490 (0.483370) | 0.006432 / 0.000200 (0.006233) | 0.000177 / 0.000054 (0.000123) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.034723 / 0.037411 (-0.002688) | 0.104420 / 0.014526 (0.089894) | 0.121071 / 0.176557 (-0.055486) | 0.174899 / 0.737135 (-0.562237) | 0.119587 / 0.296338 (-0.176751) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.492731 / 0.215209 (0.277522) | 4.898621 / 2.077655 (2.820967) | 2.710931 / 1.504120 (1.206811) | 2.513889 / 1.541195 (0.972694) | 2.578073 / 1.468490 (1.109583) | 0.548318 / 4.584777 (-4.036459) | 4.048603 / 3.745712 (0.302891) | 3.637654 / 5.269862 (-1.632208) | 2.263682 / 4.565676 (-2.301994) | 0.065786 / 0.424275 (-0.358489) | 0.008119 / 0.007607 (0.000512) | 0.578693 / 0.226044 (0.352649) | 5.780619 / 2.268929 (3.511691) | 3.224625 / 55.444624 (-52.220000) | 2.838750 / 6.876477 (-4.037726) | 2.970276 / 2.142072 (0.828204) | 0.654423 / 4.805227 (-4.150805) | 0.148696 / 6.500664 (-6.351969) | 0.066469 / 0.075469 (-0.009000) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.574772 / 1.841788 (-0.267015) | 21.822356 / 8.074308 (13.748048) | 16.504127 / 10.191392 (6.312735) | 0.183357 / 0.680424 (-0.497067) | 0.022759 / 0.534201 (-0.511442) | 0.453746 / 0.579283 (-0.125537) | 0.447037 / 0.434364 (0.012673) | 0.536562 / 0.540337 (-0.003775) | 0.731063 / 1.386936 (-0.655873) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#a9027eb4d9c5b3fa60a18daa7aef121428964d90 \"CML watermark\")\n", "_The documentation is not available anymore as the PR was closed or merged._", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008542 / 0.011353 (-0.002811) | 0.005481 / 0.011008 (-0.005527) | 0.100122 / 0.038508 (0.061614) | 0.078968 / 0.023109 (0.055858) | 0.403751 / 0.275898 (0.127853) | 0.457559 / 0.323480 (0.134079) | 0.006152 / 0.007986 (-0.001834) | 0.003805 / 0.004328 (-0.000523) | 0.072787 / 0.004250 (0.068536) | 0.054794 / 0.037052 (0.017741) | 0.419815 / 0.258489 (0.161326) | 0.437453 / 0.293841 (0.143612) | 0.044641 / 0.128546 (-0.083905) | 0.013755 / 0.075646 (-0.061892) | 0.374683 / 0.419271 (-0.044589) | 0.071442 / 0.043533 (0.027909) | 0.395814 / 0.255139 (0.140675) | 0.439042 / 0.283200 (0.155842) | 0.034596 / 0.141683 (-0.107087) | 1.655056 / 1.452155 (0.202902) | 1.826410 / 1.492716 (0.333694) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.278667 / 0.018006 (0.260661) | 0.617354 / 0.000490 (0.616864) | 0.004111 / 0.000200 (0.003911) | 0.000138 / 0.000054 (0.000083) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.025905 / 0.037411 (-0.011506) | 0.084721 / 0.014526 (0.070195) | 0.099737 / 0.176557 (-0.076819) | 0.163016 / 0.737135 (-0.574119) | 0.095104 / 0.296338 (-0.201234) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.531589 / 0.215209 (0.316380) | 5.455303 / 2.077655 (3.377649) | 2.495112 / 1.504120 (0.990992) | 2.234139 / 1.541195 (0.692944) | 2.295090 / 1.468490 (0.826599) | 0.777627 / 4.584777 (-3.807150) | 5.053069 / 3.745712 (1.307357) | 4.488715 / 5.269862 (-0.781147) | 2.775991 / 4.565676 (-1.789686) | 0.094175 / 0.424275 (-0.330100) | 0.008681 / 0.007607 (0.001074) | 0.668174 / 0.226044 (0.442130) | 6.631876 / 2.268929 (4.362948) | 3.118055 / 55.444624 (-52.326569) | 2.480355 / 6.876477 (-4.396122) | 2.706643 / 2.142072 (0.564571) | 0.927173 / 4.805227 (-3.878054) | 0.217385 / 6.500664 (-6.283279) | 0.067110 / 0.075469 (-0.008359) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.517926 / 1.841788 (-0.323861) | 21.420546 / 8.074308 (13.346238) | 21.108266 / 10.191392 (10.916874) | 0.222449 / 0.680424 (-0.457975) | 0.027969 / 0.534201 (-0.506232) | 0.459484 / 0.579283 (-0.119799) | 0.582629 / 0.434364 (0.148265) | 0.520971 / 0.540337 (-0.019366) | 0.694270 / 1.386936 (-0.692666) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008257 / 0.011353 (-0.003096) | 0.004511 / 0.011008 (-0.006497) | 0.075031 / 0.038508 (0.036523) | 0.070526 / 0.023109 (0.047416) | 0.445595 / 0.275898 (0.169697) | 0.512312 / 0.323480 (0.188832) | 0.005933 / 0.007986 (-0.002052) | 0.003814 / 0.004328 (-0.000515) | 0.073553 / 0.004250 (0.069302) | 0.058174 / 0.037052 (0.021121) | 0.472307 / 0.258489 (0.213818) | 0.519679 / 0.293841 (0.225838) | 0.046027 / 0.128546 (-0.082520) | 0.011757 / 0.075646 (-0.063889) | 0.084883 / 0.419271 (-0.334388) | 0.056476 / 0.043533 (0.012943) | 0.475608 / 0.255139 (0.220469) | 0.507588 / 0.283200 (0.224388) | 0.031661 / 0.141683 (-0.110022) | 1.673183 / 1.452155 (0.221028) | 1.736836 / 1.492716 (0.244120) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.350887 / 0.018006 (0.332881) | 0.589796 / 0.000490 (0.589306) | 0.023066 / 0.000200 (0.022867) | 0.000106 / 0.000054 (0.000052) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.030764 / 0.037411 (-0.006647) | 0.116967 / 0.014526 (0.102441) | 0.102760 / 0.176557 (-0.073796) | 0.167690 / 0.737135 (-0.569445) | 0.111350 / 0.296338 (-0.184988) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.584565 / 0.215209 (0.369356) | 5.898081 / 2.077655 (3.820426) | 2.770374 / 1.504120 (1.266254) | 2.467519 / 1.541195 (0.926324) | 2.463319 / 1.468490 (0.994829) | 0.794294 / 4.584777 (-3.790483) | 5.272285 / 3.745712 (1.526573) | 4.514830 / 5.269862 (-0.755032) | 2.937259 / 4.565676 (-1.628417) | 0.093702 / 0.424275 (-0.330574) | 0.008012 / 0.007607 (0.000405) | 0.772371 / 0.226044 (0.546327) | 7.574941 / 2.268929 (5.306013) | 3.710965 / 55.444624 (-51.733659) | 2.927964 / 6.876477 (-3.948513) | 3.256036 / 2.142072 (1.113964) | 1.051649 / 4.805227 (-3.753578) | 0.203055 / 6.500664 (-6.297609) | 0.081072 / 0.075469 (0.005603) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.574251 / 1.841788 (-0.267537) | 22.340801 / 8.074308 (14.266493) | 20.497769 / 10.191392 (10.306377) | 0.228725 / 0.680424 (-0.451699) | 0.029095 / 0.534201 (-0.505106) | 0.452460 / 0.579283 (-0.126823) | 0.586419 / 0.434364 (0.152055) | 0.571237 / 0.540337 (0.030900) | 0.745069 / 1.386936 (-0.641867) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#61b23b028dfc72c297391c5f670342732b9bd9fe \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006529 / 0.011353 (-0.004824) | 0.004062 / 0.011008 (-0.006946) | 0.083712 / 0.038508 (0.045204) | 0.072378 / 0.023109 (0.049269) | 0.358779 / 0.275898 (0.082881) | 0.387216 / 0.323480 (0.063736) | 0.004038 / 0.007986 (-0.003948) | 0.003316 / 0.004328 (-0.001013) | 0.065207 / 0.004250 (0.060956) | 0.054439 / 0.037052 (0.017386) | 0.370689 / 0.258489 (0.112200) | 0.411008 / 0.293841 (0.117167) | 0.031133 / 0.128546 (-0.097413) | 0.008600 / 0.075646 (-0.067047) | 0.287753 / 0.419271 (-0.131518) | 0.051845 / 0.043533 (0.008312) | 0.360327 / 0.255139 (0.105188) | 0.394791 / 0.283200 (0.111591) | 0.025139 / 0.141683 (-0.116544) | 1.488151 / 1.452155 (0.035996) | 1.556776 / 1.492716 (0.064059) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.209462 / 0.018006 (0.191456) | 0.459168 / 0.000490 (0.458678) | 0.006037 / 0.000200 (0.005837) | 0.000079 / 0.000054 (0.000025) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.028444 / 0.037411 (-0.008967) | 0.082974 / 0.014526 (0.068448) | 0.094919 / 0.176557 (-0.081638) | 0.151875 / 0.737135 (-0.585260) | 0.096143 / 0.296338 (-0.200195) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.402675 / 0.215209 (0.187466) | 4.014787 / 2.077655 (1.937133) | 2.015793 / 1.504120 (0.511673) | 1.838976 / 1.541195 (0.297782) | 1.931733 / 1.468490 (0.463243) | 0.489435 / 4.584777 (-4.095342) | 3.581662 / 3.745712 (-0.164050) | 3.315392 / 5.269862 (-1.954469) | 2.053369 / 4.565676 (-2.512307) | 0.057749 / 0.424275 (-0.366526) | 0.007720 / 0.007607 (0.000113) | 0.483388 / 0.226044 (0.257343) | 4.820798 / 2.268929 (2.551870) | 2.544264 / 55.444624 (-52.900361) | 2.170513 / 6.876477 (-4.705963) | 2.416976 / 2.142072 (0.274903) | 0.588351 / 4.805227 (-4.216876) | 0.136988 / 6.500664 (-6.363676) | 0.062294 / 0.075469 (-0.013175) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.263807 / 1.841788 (-0.577980) | 19.888202 / 8.074308 (11.813894) | 14.352977 / 10.191392 (4.161585) | 0.167200 / 0.680424 (-0.513224) | 0.018449 / 0.534201 (-0.515752) | 0.393262 / 0.579283 (-0.186021) | 0.407854 / 0.434364 (-0.026510) | 0.455852 / 0.540337 (-0.084485) | 0.629024 / 1.386936 (-0.757912) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006642 / 0.011353 (-0.004710) | 0.004041 / 0.011008 (-0.006967) | 0.065823 / 0.038508 (0.027315) | 0.076810 / 0.023109 (0.053701) | 0.397680 / 0.275898 (0.121782) | 0.430104 / 0.323480 (0.106624) | 0.006035 / 0.007986 (-0.001951) | 0.003389 / 0.004328 (-0.000939) | 0.066056 / 0.004250 (0.061806) | 0.054222 / 0.037052 (0.017170) | 0.397964 / 0.258489 (0.139475) | 0.439277 / 0.293841 (0.145436) | 0.032394 / 0.128546 (-0.096152) | 0.008586 / 0.075646 (-0.067060) | 0.072538 / 0.419271 (-0.346734) | 0.048346 / 0.043533 (0.004813) | 0.399631 / 0.255139 (0.144492) | 0.418684 / 0.283200 (0.135484) | 0.022570 / 0.141683 (-0.119113) | 1.519788 / 1.452155 (0.067633) | 1.581457 / 1.492716 (0.088740) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.243443 / 0.018006 (0.225436) | 0.453095 / 0.000490 (0.452606) | 0.009940 / 0.000200 (0.009740) | 0.000121 / 0.000054 (0.000066) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.032293 / 0.037411 (-0.005118) | 0.091681 / 0.014526 (0.077155) | 0.103729 / 0.176557 (-0.072827) | 0.156361 / 0.737135 (-0.580775) | 0.105034 / 0.296338 (-0.191305) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.427761 / 0.215209 (0.212551) | 4.266044 / 2.077655 (2.188390) | 2.285161 / 1.504120 (0.781041) | 2.118652 / 1.541195 (0.577457) | 2.203469 / 1.468490 (0.734979) | 0.494587 / 4.584777 (-4.090190) | 3.676706 / 3.745712 (-0.069006) | 3.252478 / 5.269862 (-2.017383) | 2.027432 / 4.565676 (-2.538245) | 0.057856 / 0.424275 (-0.366419) | 0.007279 / 0.007607 (-0.000328) | 0.502767 / 0.226044 (0.276723) | 5.031409 / 2.268929 (2.762480) | 2.741767 / 55.444624 (-52.702858) | 2.408480 / 6.876477 (-4.467997) | 2.607193 / 2.142072 (0.465121) | 0.590787 / 4.805227 (-4.214440) | 0.133633 / 6.500664 (-6.367031) | 0.061195 / 0.075469 (-0.014274) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.342824 / 1.841788 (-0.498964) | 20.137195 / 8.074308 (12.062887) | 14.986743 / 10.191392 (4.795351) | 0.168218 / 0.680424 (-0.512206) | 0.020209 / 0.534201 (-0.513992) | 0.397446 / 0.579283 (-0.181837) | 0.427496 / 0.434364 (-0.006868) | 0.475058 / 0.540337 (-0.065279) | 0.648439 / 1.386936 (-0.738497) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#0b54cbd6c01f52139dedbcf209ff41f0c88b9aa5 \"CML watermark\")\n" ]

"2023-08-31T10:38:08Z"

"2023-09-05T11:07:07Z"

"2023-09-05T10:58:21Z"

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[ "_The documentation is not available anymore as the PR was closed or merged._", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008978 / 0.011353 (-0.002375) | 0.005143 / 0.011008 (-0.005865) | 0.104787 / 0.038508 (0.066279) | 0.077069 / 0.023109 (0.053960) | 0.427703 / 0.275898 (0.151805) | 0.469865 / 0.323480 (0.146386) | 0.004618 / 0.007986 (-0.003368) | 0.004074 / 0.004328 (-0.000255) | 0.088656 / 0.004250 (0.084405) | 0.059798 / 0.037052 (0.022746) | 0.465906 / 0.258489 (0.207417) | 0.510281 / 0.293841 (0.216440) | 0.051192 / 0.128546 (-0.077354) | 0.013623 / 0.075646 (-0.062024) | 0.379339 / 0.419271 (-0.039932) | 0.077393 / 0.043533 (0.033860) | 0.445165 / 0.255139 (0.190026) | 0.473577 / 0.283200 (0.190378) | 0.038125 / 0.141683 (-0.103558) | 1.858635 / 1.452155 (0.406480) | 1.869033 / 1.492716 (0.376316) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.209011 / 0.018006 (0.191004) | 0.550978 / 0.000490 (0.550488) | 0.004904 / 0.000200 (0.004704) | 0.000106 / 0.000054 (0.000051) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.031418 / 0.037411 (-0.005993) | 0.089623 / 0.014526 (0.075098) | 0.103491 / 0.176557 (-0.073066) | 0.178158 / 0.737135 (-0.558978) | 0.108515 / 0.296338 (-0.187824) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.648293 / 0.215209 (0.433084) | 6.332361 / 2.077655 (4.254707) | 2.469076 / 1.504120 (0.964956) | 2.286228 / 1.541195 (0.745033) | 2.257408 / 1.468490 (0.788918) | 0.918027 / 4.584777 (-3.666750) | 5.229539 / 3.745712 (1.483827) | 4.676150 / 5.269862 (-0.593712) | 3.220411 / 4.565676 (-1.345266) | 0.095863 / 0.424275 (-0.328413) | 0.008696 / 0.007607 (0.001089) | 0.722356 / 0.226044 (0.496312) | 7.796690 / 2.268929 (5.527762) | 3.715044 / 55.444624 (-51.729581) | 2.852696 / 6.876477 (-4.023780) | 2.891838 / 2.142072 (0.749766) | 1.195536 / 4.805227 (-3.609691) | 0.246908 / 6.500664 (-6.253756) | 0.079454 / 0.075469 (0.003984) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.652740 / 1.841788 (-0.189047) | 23.791791 / 8.074308 (15.717482) | 22.778999 / 10.191392 (12.587607) | 0.253878 / 0.680424 (-0.426546) | 0.031367 / 0.534201 (-0.502834) | 0.509460 / 0.579283 (-0.069823) | 0.603085 / 0.434364 (0.168721) | 0.603890 / 0.540337 (0.063553) | 0.826606 / 1.386936 (-0.560330) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.010407 / 0.011353 (-0.000946) | 0.004751 / 0.011008 (-0.006257) | 0.086761 / 0.038508 (0.048253) | 0.087281 / 0.023109 (0.064172) | 0.498409 / 0.275898 (0.222511) | 0.560727 / 0.323480 (0.237247) | 0.006563 / 0.007986 (-0.001423) | 0.004078 / 0.004328 (-0.000251) | 0.086383 / 0.004250 (0.082133) | 0.065915 / 0.037052 (0.028862) | 0.521871 / 0.258489 (0.263382) | 0.582281 / 0.293841 (0.288440) | 0.057189 / 0.128546 (-0.071357) | 0.015514 / 0.075646 (-0.060133) | 0.102574 / 0.419271 (-0.316697) | 0.069155 / 0.043533 (0.025622) | 0.525000 / 0.255139 (0.269861) | 0.557968 / 0.283200 (0.274769) | 0.036934 / 0.141683 (-0.104749) | 1.919335 / 1.452155 (0.467181) | 1.870948 / 1.492716 (0.378231) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.241932 / 0.018006 (0.223926) | 0.560136 / 0.000490 (0.559646) | 0.006438 / 0.000200 (0.006238) | 0.000108 / 0.000054 (0.000053) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.036192 / 0.037411 (-0.001220) | 0.106829 / 0.014526 (0.092303) | 0.128667 / 0.176557 (-0.047890) | 0.200514 / 0.737135 (-0.536621) | 0.127542 / 0.296338 (-0.168797) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.754556 / 0.215209 (0.539347) | 7.237324 / 2.077655 (5.159670) | 3.267424 / 1.504120 (1.763304) | 2.789601 / 1.541195 (1.248407) | 2.875728 / 1.468490 (1.407238) | 0.894274 / 4.584777 (-3.690503) | 5.394556 / 3.745712 (1.648844) | 4.818523 / 5.269862 (-0.451338) | 2.965827 / 4.565676 (-1.599850) | 0.101967 / 0.424275 (-0.322308) | 0.008506 / 0.007607 (0.000899) | 0.803476 / 0.226044 (0.577432) | 8.614426 / 2.268929 (6.345497) | 4.169113 / 55.444624 (-51.275511) | 3.346346 / 6.876477 (-3.530130) | 3.418206 / 2.142072 (1.276134) | 1.111718 / 4.805227 (-3.693509) | 0.211302 / 6.500664 (-6.289362) | 0.072524 / 0.075469 (-0.002945) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.792705 / 1.841788 (-0.049083) | 24.442484 / 8.074308 (16.368176) | 23.375008 / 10.191392 (13.183616) | 0.227946 / 0.680424 (-0.452478) | 0.034376 / 0.534201 (-0.499825) | 0.489260 / 0.579283 (-0.090023) | 0.563220 / 0.434364 (0.128856) | 0.617405 / 0.540337 (0.077068) | 0.850577 / 1.386936 (-0.536359) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#b4413ea1eaca5023ace1e62ddf1070de2d41b4f6 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006594 / 0.011353 (-0.004759) | 0.004366 / 0.011008 (-0.006642) | 0.084241 / 0.038508 (0.045733) | 0.071876 / 0.023109 (0.048767) | 0.321604 / 0.275898 (0.045706) | 0.343501 / 0.323480 (0.020021) | 0.004069 / 0.007986 (-0.003917) | 0.003311 / 0.004328 (-0.001017) | 0.065079 / 0.004250 (0.060829) | 0.053754 / 0.037052 (0.016702) | 0.326199 / 0.258489 (0.067710) | 0.356552 / 0.293841 (0.062711) | 0.031568 / 0.128546 (-0.096979) | 0.008581 / 0.075646 (-0.067065) | 0.289170 / 0.419271 (-0.130101) | 0.053097 / 0.043533 (0.009564) | 0.309678 / 0.255139 (0.054539) | 0.345717 / 0.283200 (0.062517) | 0.024144 / 0.141683 (-0.117539) | 1.497351 / 1.452155 (0.045196) | 1.584691 / 1.492716 (0.091975) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.206357 / 0.018006 (0.188351) | 0.459611 / 0.000490 (0.459121) | 0.002586 / 0.000200 (0.002386) | 0.000079 / 0.000054 (0.000024) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.027459 / 0.037411 (-0.009952) | 0.082197 / 0.014526 (0.067671) | 0.095004 / 0.176557 (-0.081553) | 0.151063 / 0.737135 (-0.586072) | 0.095107 / 0.296338 (-0.201231) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.384363 / 0.215209 (0.169154) | 3.836187 / 2.077655 (1.758533) | 1.898312 / 1.504120 (0.394192) | 1.727310 / 1.541195 (0.186115) | 1.803579 / 1.468490 (0.335089) | 0.485946 / 4.584777 (-4.098831) | 3.619134 / 3.745712 (-0.126578) | 3.255274 / 5.269862 (-2.014588) | 2.004603 / 4.565676 (-2.561074) | 0.057107 / 0.424275 (-0.367168) | 0.007601 / 0.007607 (-0.000006) | 0.456545 / 0.226044 (0.230500) | 4.556857 / 2.268929 (2.287929) | 2.379954 / 55.444624 (-53.064671) | 2.045874 / 6.876477 (-4.830603) | 2.203090 / 2.142072 (0.061018) | 0.585400 / 4.805227 (-4.219827) | 0.133018 / 6.500664 (-6.367646) | 0.059457 / 0.075469 (-0.016012) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.292581 / 1.841788 (-0.549207) | 19.360057 / 8.074308 (11.285749) | 14.105359 / 10.191392 (3.913967) | 0.166028 / 0.680424 (-0.514396) | 0.018243 / 0.534201 (-0.515958) | 0.392026 / 0.579283 (-0.187257) | 0.412735 / 0.434364 (-0.021629) | 0.459791 / 0.540337 (-0.080547) | 0.624539 / 1.386936 (-0.762397) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006677 / 0.011353 (-0.004676) | 0.003897 / 0.011008 (-0.007111) | 0.064139 / 0.038508 (0.025631) | 0.071346 / 0.023109 (0.048237) | 0.431180 / 0.275898 (0.155282) | 0.470870 / 0.323480 (0.147390) | 0.005562 / 0.007986 (-0.002423) | 0.003405 / 0.004328 (-0.000924) | 0.064532 / 0.004250 (0.060282) | 0.055317 / 0.037052 (0.018265) | 0.434667 / 0.258489 (0.176178) | 0.475765 / 0.293841 (0.181924) | 0.032392 / 0.128546 (-0.096154) | 0.008418 / 0.075646 (-0.067228) | 0.071069 / 0.419271 (-0.348203) | 0.047963 / 0.043533 (0.004430) | 0.440225 / 0.255139 (0.185086) | 0.454860 / 0.283200 (0.171661) | 0.022653 / 0.141683 (-0.119029) | 1.489444 / 1.452155 (0.037289) | 1.556913 / 1.492716 (0.064196) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.226733 / 0.018006 (0.208727) | 0.452005 / 0.000490 (0.451516) | 0.004715 / 0.000200 (0.004515) | 0.000099 / 0.000054 (0.000044) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.032042 / 0.037411 (-0.005369) | 0.091226 / 0.014526 (0.076700) | 0.103639 / 0.176557 (-0.072917) | 0.157772 / 0.737135 (-0.579363) | 0.105466 / 0.296338 (-0.190872) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.439751 / 0.215209 (0.224542) | 4.357102 / 2.077655 (2.279448) | 2.362857 / 1.504120 (0.858737) | 2.180559 / 1.541195 (0.639364) | 2.279601 / 1.468490 (0.811111) | 0.495161 / 4.584777 (-4.089616) | 3.729199 / 3.745712 (-0.016513) | 3.334839 / 5.269862 (-1.935023) | 2.099315 / 4.565676 (-2.466362) | 0.058178 / 0.424275 (-0.366097) | 0.007303 / 0.007607 (-0.000304) | 0.506968 / 0.226044 (0.280924) | 5.078600 / 2.268929 (2.809671) | 2.846420 / 55.444624 (-52.598204) | 2.480644 / 6.876477 (-4.395833) | 2.693204 / 2.142072 (0.551132) | 0.590118 / 4.805227 (-4.215109) | 0.132900 / 6.500664 (-6.367764) | 0.060053 / 0.075469 (-0.015416) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.356713 / 1.841788 (-0.485075) | 20.380573 / 8.074308 (12.306265) | 15.066507 / 10.191392 (4.875115) | 0.180655 / 0.680424 (-0.499769) | 0.020954 / 0.534201 (-0.513247) | 0.399638 / 0.579283 (-0.179645) | 0.420694 / 0.434364 (-0.013670) | 0.476124 / 0.540337 (-0.064213) | 0.647192 / 1.386936 (-0.739744) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#0f8c58002481568eb1aa4f6f86c4509cf476800a \"CML watermark\")\n" ]

"2023-08-31T09:45:17Z"

"2023-08-31T10:33:24Z"

"2023-08-31T10:24:38Z"

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[ "Hugging Face's datasets library may prioritize remote configurations. Make sure there are no conflicting configurations causing the library to prefer downloading data\r\nMay be try debugging\r\nraw_datasets = load_dataset('json', data_files=data_files)\r\nprint(raw_datasets)\r\n", "It doesn't download them but writes them to the local HF cache. The logging could indeed be better. Does loading the dataset succeed? If it doesn't, can you share the error stack trace?" ]

"2023-08-31T09:42:34Z"

"2023-08-31T19:05:07Z"

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[ "_The documentation is not available anymore as the PR was closed or merged._", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007621 / 0.011353 (-0.003732) | 0.004534 / 0.011008 (-0.006475) | 0.099834 / 0.038508 (0.061326) | 0.083029 / 0.023109 (0.059920) | 0.387559 / 0.275898 (0.111661) | 0.422453 / 0.323480 (0.098973) | 0.006070 / 0.007986 (-0.001916) | 0.003725 / 0.004328 (-0.000604) | 0.075923 / 0.004250 (0.071672) | 0.060578 / 0.037052 (0.023525) | 0.403569 / 0.258489 (0.145079) | 0.444991 / 0.293841 (0.151150) | 0.035847 / 0.128546 (-0.092699) | 0.009872 / 0.075646 (-0.065774) | 0.335506 / 0.419271 (-0.083766) | 0.060509 / 0.043533 (0.016976) | 0.381034 / 0.255139 (0.125895) | 0.426938 / 0.283200 (0.143738) | 0.027662 / 0.141683 (-0.114021) | 1.729565 / 1.452155 (0.277410) | 1.842082 / 1.492716 (0.349366) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.230371 / 0.018006 (0.212365) | 0.518216 / 0.000490 (0.517726) | 0.003897 / 0.000200 (0.003697) | 0.000087 / 0.000054 (0.000033) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.031942 / 0.037411 (-0.005470) | 0.096609 / 0.014526 (0.082083) | 0.112707 / 0.176557 (-0.063850) | 0.178849 / 0.737135 (-0.558286) | 0.112793 / 0.296338 (-0.183546) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.445896 / 0.215209 (0.230687) | 4.451173 / 2.077655 (2.373519) | 2.183380 / 1.504120 (0.679260) | 1.991583 / 1.541195 (0.450388) | 2.096219 / 1.468490 (0.627729) | 0.566692 / 4.584777 (-4.018085) | 4.078278 / 3.745712 (0.332566) | 3.787950 / 5.269862 (-1.481911) | 2.372651 / 4.565676 (-2.193025) | 0.065500 / 0.424275 (-0.358775) | 0.008918 / 0.007607 (0.001311) | 0.535589 / 0.226044 (0.309545) | 5.364130 / 2.268929 (3.095201) | 2.805381 / 55.444624 (-52.639244) | 2.350769 / 6.876477 (-4.525708) | 2.592887 / 2.142072 (0.450814) | 0.675475 / 4.805227 (-4.129752) | 0.153907 / 6.500664 (-6.346757) | 0.071138 / 0.075469 (-0.004331) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.498236 / 1.841788 (-0.343552) | 22.810460 / 8.074308 (14.736152) | 16.275035 / 10.191392 (6.083643) | 0.200242 / 0.680424 (-0.480182) | 0.021553 / 0.534201 (-0.512648) | 0.469437 / 0.579283 (-0.109846) | 0.477752 / 0.434364 (0.043388) | 0.537411 / 0.540337 (-0.002927) | 0.741730 / 1.386936 (-0.645206) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008009 / 0.011353 (-0.003344) | 0.004626 / 0.011008 (-0.006382) | 0.074871 / 0.038508 (0.036363) | 0.085214 / 0.023109 (0.062105) | 0.478057 / 0.275898 (0.202159) | 0.522038 / 0.323480 (0.198558) | 0.007055 / 0.007986 (-0.000931) | 0.003813 / 0.004328 (-0.000515) | 0.076238 / 0.004250 (0.071988) | 0.065738 / 0.037052 (0.028686) | 0.484391 / 0.258489 (0.225902) | 0.524425 / 0.293841 (0.230584) | 0.038375 / 0.128546 (-0.090171) | 0.009964 / 0.075646 (-0.065682) | 0.084027 / 0.419271 (-0.335245) | 0.056979 / 0.043533 (0.013447) | 0.486910 / 0.255139 (0.231771) | 0.501185 / 0.283200 (0.217985) | 0.027000 / 0.141683 (-0.114683) | 1.767378 / 1.452155 (0.315224) | 1.870511 / 1.492716 (0.377795) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.267067 / 0.018006 (0.249061) | 0.501714 / 0.000490 (0.501224) | 0.012379 / 0.000200 (0.012179) | 0.000129 / 0.000054 (0.000075) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.036706 / 0.037411 (-0.000706) | 0.110064 / 0.014526 (0.095538) | 0.124896 / 0.176557 (-0.051660) | 0.186730 / 0.737135 (-0.550405) | 0.123501 / 0.296338 (-0.172837) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.510793 / 0.215209 (0.295583) | 5.133056 / 2.077655 (3.055401) | 2.776456 / 1.504120 (1.272336) | 2.595557 / 1.541195 (1.054362) | 2.717922 / 1.468490 (1.249432) | 0.578333 / 4.584777 (-4.006444) | 4.169935 / 3.745712 (0.424223) | 3.800078 / 5.269862 (-1.469784) | 2.385866 / 4.565676 (-2.179810) | 0.068114 / 0.424275 (-0.356161) | 0.008771 / 0.007607 (0.001164) | 0.597894 / 0.226044 (0.371850) | 5.970293 / 2.268929 (3.701364) | 3.352715 / 55.444624 (-52.091909) | 2.972062 / 6.876477 (-3.904415) | 3.179232 / 2.142072 (1.037160) | 0.689838 / 4.805227 (-4.115389) | 0.154890 / 6.500664 (-6.345774) | 0.072321 / 0.075469 (-0.003148) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.613666 / 1.841788 (-0.228121) | 23.441538 / 8.074308 (15.367230) | 17.105417 / 10.191392 (6.914025) | 0.171449 / 0.680424 (-0.508975) | 0.023257 / 0.534201 (-0.510944) | 0.466724 / 0.579283 (-0.112559) | 0.470835 / 0.434364 (0.036471) | 0.561860 / 0.540337 (0.021523) | 0.759048 / 1.386936 (-0.627888) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#0f3b6eaf69d3352394d3bf3c4d6ed01dd2af5860 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007557 / 0.011353 (-0.003796) | 0.004211 / 0.011008 (-0.006797) | 0.096243 / 0.038508 (0.057735) | 0.083603 / 0.023109 (0.060493) | 0.367114 / 0.275898 (0.091216) | 0.415182 / 0.323480 (0.091702) | 0.005796 / 0.007986 (-0.002189) | 0.003791 / 0.004328 (-0.000537) | 0.073505 / 0.004250 (0.069254) | 0.060335 / 0.037052 (0.023283) | 0.392182 / 0.258489 (0.133693) | 0.421315 / 0.293841 (0.127474) | 0.036128 / 0.128546 (-0.092419) | 0.009953 / 0.075646 (-0.065693) | 0.338965 / 0.419271 (-0.080307) | 0.061006 / 0.043533 (0.017473) | 0.372317 / 0.255139 (0.117178) | 0.414367 / 0.283200 (0.131167) | 0.026970 / 0.141683 (-0.114713) | 1.730381 / 1.452155 (0.278227) | 1.808340 / 1.492716 (0.315624) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.222622 / 0.018006 (0.204615) | 0.474064 / 0.000490 (0.473574) | 0.004817 / 0.000200 (0.004617) | 0.000089 / 0.000054 (0.000034) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.032528 / 0.037411 (-0.004883) | 0.097457 / 0.014526 (0.082931) | 0.112273 / 0.176557 (-0.064283) | 0.177953 / 0.737135 (-0.559182) | 0.112358 / 0.296338 (-0.183981) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.442601 / 0.215209 (0.227392) | 4.442065 / 2.077655 (2.364410) | 2.156813 / 1.504120 (0.652694) | 1.970289 / 1.541195 (0.429094) | 2.052878 / 1.468490 (0.584388) | 0.562661 / 4.584777 (-4.022116) | 4.255529 / 3.745712 (0.509817) | 3.767650 / 5.269862 (-1.502212) | 2.431078 / 4.565676 (-2.134598) | 0.065624 / 0.424275 (-0.358651) | 0.008738 / 0.007607 (0.001131) | 0.546839 / 0.226044 (0.320795) | 5.362863 / 2.268929 (3.093934) | 2.695924 / 55.444624 (-52.748701) | 2.334589 / 6.876477 (-4.541888) | 2.530757 / 2.142072 (0.388685) | 0.675991 / 4.805227 (-4.129236) | 0.153852 / 6.500664 (-6.346813) | 0.069189 / 0.075469 (-0.006280) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.522916 / 1.841788 (-0.318872) | 21.515907 / 8.074308 (13.441599) | 16.411708 / 10.191392 (6.220316) | 0.168245 / 0.680424 (-0.512179) | 0.021165 / 0.534201 (-0.513036) | 0.461838 / 0.579283 (-0.117446) | 0.488867 / 0.434364 (0.054503) | 0.536278 / 0.540337 (-0.004059) | 0.766690 / 1.386936 (-0.620246) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007683 / 0.011353 (-0.003670) | 0.004401 / 0.011008 (-0.006608) | 0.075463 / 0.038508 (0.036955) | 0.081737 / 0.023109 (0.058628) | 0.466469 / 0.275898 (0.190571) | 0.514909 / 0.323480 (0.191429) | 0.006106 / 0.007986 (-0.001880) | 0.003936 / 0.004328 (-0.000393) | 0.076773 / 0.004250 (0.072523) | 0.061025 / 0.037052 (0.023973) | 0.473348 / 0.258489 (0.214858) | 0.525326 / 0.293841 (0.231485) | 0.038224 / 0.128546 (-0.090322) | 0.009559 / 0.075646 (-0.066087) | 0.080847 / 0.419271 (-0.338424) | 0.056738 / 0.043533 (0.013205) | 0.475116 / 0.255139 (0.219977) | 0.494689 / 0.283200 (0.211490) | 0.029364 / 0.141683 (-0.112319) | 1.796681 / 1.452155 (0.344527) | 1.850600 / 1.492716 (0.357884) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.327126 / 0.018006 (0.309119) | 0.469186 / 0.000490 (0.468696) | 0.050600 / 0.000200 (0.050400) | 0.000439 / 0.000054 (0.000385) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.036710 / 0.037411 (-0.000701) | 0.108669 / 0.014526 (0.094143) | 0.119808 / 0.176557 (-0.056748) | 0.181501 / 0.737135 (-0.555634) | 0.121487 / 0.296338 (-0.174852) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.509076 / 0.215209 (0.293867) | 5.056970 / 2.077655 (2.979316) | 2.775958 / 1.504120 (1.271838) | 2.592548 / 1.541195 (1.051353) | 2.654381 / 1.468490 (1.185890) | 0.557407 / 4.584777 (-4.027370) | 4.418232 / 3.745712 (0.672519) | 3.698072 / 5.269862 (-1.571790) | 2.380607 / 4.565676 (-2.185069) | 0.066242 / 0.424275 (-0.358034) | 0.008350 / 0.007607 (0.000743) | 0.572354 / 0.226044 (0.346309) | 5.857637 / 2.268929 (3.588709) | 3.242512 / 55.444624 (-52.202112) | 2.891144 / 6.876477 (-3.985332) | 3.217987 / 2.142072 (1.075915) | 0.676049 / 4.805227 (-4.129178) | 0.155515 / 6.500664 (-6.345149) | 0.068616 / 0.075469 (-0.006853) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.670048 / 1.841788 (-0.171740) | 22.629573 / 8.074308 (14.555265) | 16.887676 / 10.191392 (6.696284) | 0.168571 / 0.680424 (-0.511853) | 0.023361 / 0.534201 (-0.510840) | 0.463358 / 0.579283 (-0.115925) | 0.463278 / 0.434364 (0.028914) | 0.602397 / 0.540337 (0.062060) | 0.793249 / 1.386936 (-0.593687) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#eee318573aba6574a43d457aa0347348c1f3e4aa \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006693 / 0.011353 (-0.004660) | 0.004100 / 0.011008 (-0.006908) | 0.084166 / 0.038508 (0.045658) | 0.074469 / 0.023109 (0.051360) | 0.356092 / 0.275898 (0.080194) | 0.392389 / 0.323480 (0.068909) | 0.003996 / 0.007986 (-0.003990) | 0.004020 / 0.004328 (-0.000308) | 0.064997 / 0.004250 (0.060747) | 0.053897 / 0.037052 (0.016845) | 0.362942 / 0.258489 (0.104453) | 0.408694 / 0.293841 (0.114854) | 0.031656 / 0.128546 (-0.096890) | 0.008713 / 0.075646 (-0.066933) | 0.289306 / 0.419271 (-0.129966) | 0.053067 / 0.043533 (0.009534) | 0.358740 / 0.255139 (0.103601) | 0.393347 / 0.283200 (0.110147) | 0.025430 / 0.141683 (-0.116253) | 1.486114 / 1.452155 (0.033959) | 1.572698 / 1.492716 (0.079981) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.215423 / 0.018006 (0.197417) | 0.467694 / 0.000490 (0.467204) | 0.003965 / 0.000200 (0.003765) | 0.000112 / 0.000054 (0.000057) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.027936 / 0.037411 (-0.009475) | 0.084235 / 0.014526 (0.069709) | 0.136275 / 0.176557 (-0.040282) | 0.151154 / 0.737135 (-0.585982) | 0.185592 / 0.296338 (-0.110747) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.393784 / 0.215209 (0.178575) | 3.927878 / 2.077655 (1.850223) | 1.961216 / 1.504120 (0.457096) | 1.802264 / 1.541195 (0.261069) | 1.971186 / 1.468490 (0.502696) | 0.487981 / 4.584777 (-4.096796) | 3.649046 / 3.745712 (-0.096666) | 3.302471 / 5.269862 (-1.967391) | 2.058075 / 4.565676 (-2.507602) | 0.057072 / 0.424275 (-0.367203) | 0.007624 / 0.007607 (0.000017) | 0.470139 / 0.226044 (0.244095) | 4.697711 / 2.268929 (2.428783) | 2.494813 / 55.444624 (-52.949811) | 2.133084 / 6.876477 (-4.743393) | 2.329740 / 2.142072 (0.187667) | 0.585857 / 4.805227 (-4.219371) | 0.134442 / 6.500664 (-6.366223) | 0.060860 / 0.075469 (-0.014609) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.248504 / 1.841788 (-0.593283) | 19.448427 / 8.074308 (11.374119) | 14.446139 / 10.191392 (4.254747) | 0.168081 / 0.680424 (-0.512342) | 0.018028 / 0.534201 (-0.516173) | 0.395061 / 0.579283 (-0.184222) | 0.418777 / 0.434364 (-0.015587) | 0.454509 / 0.540337 (-0.085828) | 0.628488 / 1.386936 (-0.758448) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006946 / 0.011353 (-0.004406) | 0.004096 / 0.011008 (-0.006912) | 0.065322 / 0.038508 (0.026813) | 0.074336 / 0.023109 (0.051227) | 0.405327 / 0.275898 (0.129429) | 0.436878 / 0.323480 (0.113398) | 0.006083 / 0.007986 (-0.001902) | 0.003345 / 0.004328 (-0.000984) | 0.065725 / 0.004250 (0.061474) | 0.056398 / 0.037052 (0.019345) | 0.406906 / 0.258489 (0.148417) | 0.443330 / 0.293841 (0.149489) | 0.033036 / 0.128546 (-0.095510) | 0.008503 / 0.075646 (-0.067144) | 0.071865 / 0.419271 (-0.347406) | 0.048956 / 0.043533 (0.005423) | 0.404579 / 0.255139 (0.149440) | 0.424904 / 0.283200 (0.141704) | 0.021786 / 0.141683 (-0.119897) | 1.491868 / 1.452155 (0.039713) | 1.565252 / 1.492716 (0.072536) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.231363 / 0.018006 (0.213357) | 0.454962 / 0.000490 (0.454472) | 0.004680 / 0.000200 (0.004480) | 0.000100 / 0.000054 (0.000045) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.032569 / 0.037411 (-0.004843) | 0.094928 / 0.014526 (0.080402) | 0.108096 / 0.176557 (-0.068461) | 0.158727 / 0.737135 (-0.578409) | 0.106951 / 0.296338 (-0.189387) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.431469 / 0.215209 (0.216260) | 4.283929 / 2.077655 (2.206274) | 2.283891 / 1.504120 (0.779771) | 2.118172 / 1.541195 (0.576977) | 2.192628 / 1.468490 (0.724138) | 0.492026 / 4.584777 (-4.092751) | 3.692126 / 3.745712 (-0.053587) | 3.269827 / 5.269862 (-2.000035) | 2.028948 / 4.565676 (-2.536728) | 0.057932 / 0.424275 (-0.366344) | 0.007301 / 0.007607 (-0.000306) | 0.508411 / 0.226044 (0.282367) | 5.072803 / 2.268929 (2.803875) | 2.756532 / 55.444624 (-52.688092) | 2.432192 / 6.876477 (-4.444285) | 2.654864 / 2.142072 (0.512791) | 0.589458 / 4.805227 (-4.215769) | 0.133924 / 6.500664 (-6.366740) | 0.060764 / 0.075469 (-0.014705) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.350737 / 1.841788 (-0.491051) | 20.265217 / 8.074308 (12.190909) | 14.969039 / 10.191392 (4.777647) | 0.164226 / 0.680424 (-0.516198) | 0.020090 / 0.534201 (-0.514111) | 0.397010 / 0.579283 (-0.182273) | 0.412927 / 0.434364 (-0.021437) | 0.473931 / 0.540337 (-0.066406) | 0.653462 / 1.386936 (-0.733474) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#00cb5cc57337cdff338d7a54396bf25c5c5abd67 \"CML watermark\")\n" ]

"2023-08-31T09:00:26Z"

"2023-08-31T13:57:31Z"

"2023-08-31T13:48:42Z"

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[ "Thanks for reporting. We are investigating it.", "This issue is caused by latest `pandas` release 2.1.0 (released yesterday Aug 30).\r\n\r\nSee: https://github.com/huggingface/datasets/actions/runs/6035484010/job/16375932085?pr=6198\r\n", "People using previous releases of `datasets` should pin `pandas` in their local environment:\r\n```\r\npython -m pip install 'pandas<2.1.0'\r\n```" ]

"2023-08-31T08:51:50Z"

"2023-09-01T10:35:10Z"

"2023-08-31T10:24:40Z"

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"2023-08-31T08:47:16Z"

"2023-08-31T13:48:43Z"

"2023-08-31T13:48:43Z"

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[ "realized that need to pass the path at `cache_file_name` like\r\n\r\n```python\r\ntokenized_datasets = raw_datasets[\"train\"].map(\r\n tokenize_function,\r\n batched=True,\r\n num_proc=data_args.preprocessing_num_workers,\r\n remove_columns=[text_column_name],\r\n load_from_cache_file=True,\r\n desc=\"Running tokenizer on dataset line_by_line\",\r\n # cache_file_names= {\"train\": \"cache-1982fea76aa54a13.arrow\"}\r\n cache_file_name=\"/project/huggingface_cache/datasets/..../cache-1982fea76aa54a13.arrow\",\r\n new_fingerprint=\"1982fea76aa54a13\"\r\n )\r\n```" ]

"2023-08-30T18:44:54Z"

"2023-08-30T19:00:45Z"

"2023-08-30T19:00:45Z"

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[ "The `fingerprint` parameter serves a slightly different purpose - we use it to inject a new fingerprint after transforming a `Dataset` (computed from the previous fingerprint + transform + transform args), e.g., to be able to compute the cache file for a transform. There is no concept of `fingerprint` before a `Dataset` is fully initialized, but we still need to hash the args (e.g., generator func) of the \"dataset creation methods\" (`from_generator`, `from_csv`, etc.) to compute the cache directory (to store the initial version and transformed dataset versions)\r\n\r\nI agree it should be easier to bypass the hashing mechanism in this instance, too. However, we should probably first address https://github.com/huggingface/datasets/issues/5080 before solving this (e.g., maybe exposing `hash` in `load_dataset`/`load_dataset_builder`.", "Adding +1 here:\r\n\r\nIf the generator needs to access some external resources or state, then it's not always straightforward to make it pickle-able. So I'd like to be able to override how the default cache key derivation needs to pickle the generator (and of course, I'd accept responsibility for that part of cache consistency).\r\n\r\nAppears to be a recurrent roadbump: #6118 #5963 #5819 #5750 #4983 ", "Silly hack incoming:\r\n\r\n```python\r\nimport uuid\r\n\r\nclass _DatasetGeneratorPickleHack:\r\n def __init__(self, generator, generator_id=None):\r\n self.generator = generator\r\n self.generator_id = (\r\n generator_id if generator_id is not None else str(uuid.uuid4())\r\n )\r\n\r\n def __call__(self, *args, **kwargs):\r\n return self.generator(*kwargs, **kwargs)\r\n\r\n def __reduce__(self):\r\n return (_DatasetGeneratorPickleHack_raise, (self.generator_id,))\r\n\r\n\r\ndef _DatasetGeneratorPickleHack_raise(*args, **kwargs):\r\n raise AssertionError(\"cannot actually unpickle _DatasetGeneratorPickleHack!\")\r\n```\r\n\r\nNow `Dataset.from_generator(_DatasetGeneratorPickleHack(gen))` works even if `gen` is unpicklable, because Dataset just pickles the shim object that avoids actually traversing `gen`. Then, one can work out how to set `generator_id` meaningfully to allow cache reuse." ]

"2023-08-29T22:43:13Z"

"2023-09-06T10:28:44Z"

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[ "Before dynamically loading `.py` scripts with `importlib.import_module`, we also parse their contents to check imports, which is tricky to implement for binary `.pyc` files (requires parsing bytecode), so I don't think this is something we want to support (unless more users request it ofc) as this use case is a bit too specific.\r\n\r\n@lhoestq What's your opinion on this?", "> Before dynamically loading .py scripts with importlib.import_module, we also parse their contents to check imports, which is tricky to implement for binary .pyc files (requires parsing bytecode), so I don't think this is something we want to support (unless more users request it ofc) as this use case is a bit too specific.\r\n\r\nYes indeed. Though you can use a .py that imports a package that contains your .pyc code and that you previously installed", "Hi @lhoestq ,\r\nCould you share some example code related to the approach that you are suggesting? " ]

"2023-08-29T19:35:06Z"

"2023-08-31T19:47:29Z"

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[ "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.005972 / 0.011353 (-0.005381) | 0.003636 / 0.011008 (-0.007372) | 0.080254 / 0.038508 (0.041746) | 0.059564 / 0.023109 (0.036455) | 0.310615 / 0.275898 (0.034717) | 0.359307 / 0.323480 (0.035827) | 0.003408 / 0.007986 (-0.004578) | 0.002941 / 0.004328 (-0.001388) | 0.063699 / 0.004250 (0.059449) | 0.046072 / 0.037052 (0.009020) | 0.318670 / 0.258489 (0.060181) | 0.369677 / 0.293841 (0.075836) | 0.026995 / 0.128546 (-0.101552) | 0.007954 / 0.075646 (-0.067693) | 0.261667 / 0.419271 (-0.157604) | 0.045167 / 0.043533 (0.001634) | 0.314276 / 0.255139 (0.059137) | 0.348871 / 0.283200 (0.065672) | 0.021748 / 0.141683 (-0.119935) | 1.438598 / 1.452155 (-0.013557) | 1.530119 / 1.492716 (0.037403) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.196894 / 0.018006 (0.178888) | 0.445757 / 0.000490 (0.445267) | 0.002842 / 0.000200 (0.002642) | 0.000069 / 0.000054 (0.000015) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.024923 / 0.037411 (-0.012488) | 0.075186 / 0.014526 (0.060661) | 0.087193 / 0.176557 (-0.089364) | 0.147496 / 0.737135 (-0.589639) | 0.087083 / 0.296338 (-0.209255) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.423545 / 0.215209 (0.208336) | 4.187927 / 2.077655 (2.110273) | 2.008656 / 1.504120 (0.504536) | 1.791313 / 1.541195 (0.250119) | 1.849836 / 1.468490 (0.381346) | 0.499458 / 4.584777 (-4.085318) | 2.983206 / 3.745712 (-0.762506) | 2.801005 / 5.269862 (-2.468856) | 1.886207 / 4.565676 (-2.679469) | 0.057343 / 0.424275 (-0.366932) | 0.006666 / 0.007607 (-0.000941) | 0.483948 / 0.226044 (0.257904) | 4.874818 / 2.268929 (2.605890) | 2.439393 / 55.444624 (-53.005231) | 2.049861 / 6.876477 (-4.826616) | 2.217050 / 2.142072 (0.074977) | 0.589760 / 4.805227 (-4.215467) | 0.125298 / 6.500664 (-6.375366) | 0.061123 / 0.075469 (-0.014347) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.234721 / 1.841788 (-0.607067) | 18.193756 / 8.074308 (10.119448) | 13.682835 / 10.191392 (3.491443) | 0.129345 / 0.680424 (-0.551078) | 0.016589 / 0.534201 (-0.517612) | 0.332355 / 0.579283 (-0.246928) | 0.358408 / 0.434364 (-0.075955) | 0.382044 / 0.540337 (-0.158293) | 0.535403 / 1.386936 (-0.851533) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006193 / 0.011353 (-0.005160) | 0.003674 / 0.011008 (-0.007335) | 0.062481 / 0.038508 (0.023973) | 0.062096 / 0.023109 (0.038987) | 0.449592 / 0.275898 (0.173694) | 0.479245 / 0.323480 (0.155765) | 0.004793 / 0.007986 (-0.003193) | 0.002896 / 0.004328 (-0.001433) | 0.062887 / 0.004250 (0.058636) | 0.050049 / 0.037052 (0.012997) | 0.454940 / 0.258489 (0.196451) | 0.486115 / 0.293841 (0.192274) | 0.028585 / 0.128546 (-0.099961) | 0.007954 / 0.075646 (-0.067692) | 0.067744 / 0.419271 (-0.351528) | 0.040473 / 0.043533 (-0.003060) | 0.448408 / 0.255139 (0.193269) | 0.472423 / 0.283200 (0.189223) | 0.020549 / 0.141683 (-0.121133) | 1.563618 / 1.452155 (0.111463) | 1.520149 / 1.492716 (0.027432) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.226604 / 0.018006 (0.208598) | 0.417615 / 0.000490 (0.417126) | 0.003386 / 0.000200 (0.003186) | 0.000074 / 0.000054 (0.000019) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.027264 / 0.037411 (-0.010147) | 0.081709 / 0.014526 (0.067184) | 0.091793 / 0.176557 (-0.084763) | 0.145559 / 0.737135 (-0.591576) | 0.091869 / 0.296338 (-0.204469) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.462917 / 0.215209 (0.247708) | 4.629512 / 2.077655 (2.551857) | 2.555715 / 1.504120 (1.051595) | 2.388064 / 1.541195 (0.846870) | 2.458320 / 1.468490 (0.989830) | 0.511615 / 4.584777 (-4.073162) | 3.124566 / 3.745712 (-0.621146) | 2.839190 / 5.269862 (-2.430672) | 1.894551 / 4.565676 (-2.671126) | 0.059565 / 0.424275 (-0.364710) | 0.006481 / 0.007607 (-0.001126) | 0.532023 / 0.226044 (0.305979) | 5.361507 / 2.268929 (3.092579) | 2.982594 / 55.444624 (-52.462031) | 2.644870 / 6.876477 (-4.231606) | 2.831476 / 2.142072 (0.689404) | 0.607381 / 4.805227 (-4.197846) | 0.126067 / 6.500664 (-6.374597) | 0.062130 / 0.075469 (-0.013339) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.350442 / 1.841788 (-0.491345) | 18.829553 / 8.074308 (10.755245) | 14.796701 / 10.191392 (4.605309) | 0.145393 / 0.680424 (-0.535031) | 0.018218 / 0.534201 (-0.515983) | 0.335500 / 0.579283 (-0.243783) | 0.359190 / 0.434364 (-0.075174) | 0.388377 / 0.540337 (-0.151960) | 0.534994 / 1.386936 (-0.851942) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#ff7629eb72f499d841d64aa03f97e0b1707d1cc7 \"CML watermark\")\n", "_The documentation is not available anymore as the PR was closed or merged._", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006741 / 0.011353 (-0.004612) | 0.004097 / 0.011008 (-0.006911) | 0.084513 / 0.038508 (0.046005) | 0.074216 / 0.023109 (0.051107) | 0.352481 / 0.275898 (0.076583) | 0.394806 / 0.323480 (0.071326) | 0.005603 / 0.007986 (-0.002383) | 0.003482 / 0.004328 (-0.000847) | 0.065165 / 0.004250 (0.060914) | 0.054065 / 0.037052 (0.017013) | 0.359399 / 0.258489 (0.100910) | 0.409776 / 0.293841 (0.115935) | 0.030997 / 0.128546 (-0.097550) | 0.008717 / 0.075646 (-0.066929) | 0.288692 / 0.419271 (-0.130579) | 0.052372 / 0.043533 (0.008840) | 0.353867 / 0.255139 (0.098728) | 0.391212 / 0.283200 (0.108012) | 0.024033 / 0.141683 (-0.117650) | 1.496552 / 1.452155 (0.044398) | 1.567267 / 1.492716 (0.074550) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.294074 / 0.018006 (0.276067) | 0.595421 / 0.000490 (0.594931) | 0.003826 / 0.000200 (0.003626) | 0.000085 / 0.000054 (0.000030) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.028676 / 0.037411 (-0.008736) | 0.082064 / 0.014526 (0.067538) | 0.542399 / 0.176557 (0.365842) | 0.217188 / 0.737135 (-0.519947) | 0.099364 / 0.296338 (-0.196975) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.384282 / 0.215209 (0.169073) | 3.832204 / 2.077655 (1.754550) | 1.842500 / 1.504120 (0.338380) | 1.668192 / 1.541195 (0.126997) | 1.745207 / 1.468490 (0.276717) | 0.481881 / 4.584777 (-4.102896) | 3.677819 / 3.745712 (-0.067893) | 3.329062 / 5.269862 (-1.940799) | 2.056882 / 4.565676 (-2.508795) | 0.056898 / 0.424275 (-0.367377) | 0.007624 / 0.007607 (0.000016) | 0.459712 / 0.226044 (0.233667) | 4.611100 / 2.268929 (2.342171) | 2.370244 / 55.444624 (-53.074381) | 2.032756 / 6.876477 (-4.843721) | 2.336056 / 2.142072 (0.193984) | 0.583503 / 4.805227 (-4.221725) | 0.135041 / 6.500664 (-6.365623) | 0.062245 / 0.075469 (-0.013224) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.303894 / 1.841788 (-0.537894) | 20.315185 / 8.074308 (12.240876) | 14.388779 / 10.191392 (4.197387) | 0.169060 / 0.680424 (-0.511364) | 0.018609 / 0.534201 (-0.515592) | 0.395140 / 0.579283 (-0.184143) | 0.418231 / 0.434364 (-0.016133) | 0.461496 / 0.540337 (-0.078842) | 0.630298 / 1.386936 (-0.756638) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006999 / 0.011353 (-0.004354) | 0.004197 / 0.011008 (-0.006812) | 0.064524 / 0.038508 (0.026016) | 0.078791 / 0.023109 (0.055682) | 0.397563 / 0.275898 (0.121665) | 0.423056 / 0.323480 (0.099576) | 0.005697 / 0.007986 (-0.002288) | 0.003592 / 0.004328 (-0.000736) | 0.066178 / 0.004250 (0.061928) | 0.058114 / 0.037052 (0.021062) | 0.398619 / 0.258489 (0.140130) | 0.435496 / 0.293841 (0.141655) | 0.032758 / 0.128546 (-0.095788) | 0.008677 / 0.075646 (-0.066970) | 0.071359 / 0.419271 (-0.347913) | 0.048636 / 0.043533 (0.005103) | 0.389762 / 0.255139 (0.134623) | 0.412109 / 0.283200 (0.128910) | 0.023511 / 0.141683 (-0.118172) | 1.514768 / 1.452155 (0.062613) | 1.580163 / 1.492716 (0.087446) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.370491 / 0.018006 (0.352485) | 0.529751 / 0.000490 (0.529261) | 0.016959 / 0.000200 (0.016759) | 0.000112 / 0.000054 (0.000057) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.033361 / 0.037411 (-0.004051) | 0.091610 / 0.014526 (0.077084) | 0.106642 / 0.176557 (-0.069915) | 0.160906 / 0.737135 (-0.576229) | 0.106894 / 0.296338 (-0.189444) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.429932 / 0.215209 (0.214723) | 4.276459 / 2.077655 (2.198804) | 2.268518 / 1.504120 (0.764398) | 2.092512 / 1.541195 (0.551317) | 2.182218 / 1.468490 (0.713728) | 0.494464 / 4.584777 (-4.090313) | 3.750731 / 3.745712 (0.005019) | 3.352370 / 5.269862 (-1.917492) | 2.105630 / 4.565676 (-2.460046) | 0.058465 / 0.424275 (-0.365810) | 0.007449 / 0.007607 (-0.000158) | 0.506896 / 0.226044 (0.280851) | 5.070201 / 2.268929 (2.801272) | 2.758128 / 55.444624 (-52.686496) | 2.408378 / 6.876477 (-4.468099) | 2.690633 / 2.142072 (0.548561) | 0.595662 / 4.805227 (-4.209565) | 0.134355 / 6.500664 (-6.366309) | 0.060113 / 0.075469 (-0.015356) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.380413 / 1.841788 (-0.461375) | 20.691210 / 8.074308 (12.616901) | 15.682282 / 10.191392 (5.490890) | 0.165887 / 0.680424 (-0.514536) | 0.020541 / 0.534201 (-0.513660) | 0.397846 / 0.579283 (-0.181437) | 0.425374 / 0.434364 (-0.008990) | 0.476261 / 0.540337 (-0.064076) | 0.648617 / 1.386936 (-0.738319) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#88797b8827334674d7f78c39171c00f0a28ceed6 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008787 / 0.011353 (-0.002566) | 0.007569 / 0.011008 (-0.003439) | 0.103918 / 0.038508 (0.065410) | 0.083347 / 0.023109 (0.060238) | 0.441838 / 0.275898 (0.165940) | 0.420202 / 0.323480 (0.096722) | 0.007295 / 0.007986 (-0.000690) | 0.005366 / 0.004328 (0.001037) | 0.082659 / 0.004250 (0.078409) | 0.059711 / 0.037052 (0.022658) | 0.401821 / 0.258489 (0.143332) | 0.432906 / 0.293841 (0.139065) | 0.048662 / 0.128546 (-0.079885) | 0.014091 / 0.075646 (-0.061555) | 0.352583 / 0.419271 (-0.066689) | 0.064739 / 0.043533 (0.021206) | 0.410890 / 0.255139 (0.155751) | 0.443450 / 0.283200 (0.160251) | 0.035817 / 0.141683 (-0.105866) | 1.754687 / 1.452155 (0.302532) | 1.887338 / 1.492716 (0.394622) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.209440 / 0.018006 (0.191434) | 0.519641 / 0.000490 (0.519152) | 0.005726 / 0.000200 (0.005526) | 0.000107 / 0.000054 (0.000052) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.031027 / 0.037411 (-0.006384) | 0.097503 / 0.014526 (0.082977) | 0.106985 / 0.176557 (-0.069572) | 0.178235 / 0.737135 (-0.558900) | 0.108110 / 0.296338 (-0.188228) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.594325 / 0.215209 (0.379116) | 6.159414 / 2.077655 (4.081759) | 2.664892 / 1.504120 (1.160772) | 2.363355 / 1.541195 (0.822160) | 2.410754 / 1.468490 (0.942264) | 0.842557 / 4.584777 (-3.742220) | 5.112059 / 3.745712 (1.366347) | 4.633152 / 5.269862 (-0.636709) | 2.965891 / 4.565676 (-1.599785) | 0.097922 / 0.424275 (-0.326353) | 0.008602 / 0.007607 (0.000995) | 0.773029 / 0.226044 (0.546985) | 7.462314 / 2.268929 (5.193386) | 3.584776 / 55.444624 (-51.859848) | 2.752375 / 6.876477 (-4.124102) | 2.976345 / 2.142072 (0.834272) | 1.049423 / 4.805227 (-3.755804) | 0.212001 / 6.500664 (-6.288663) | 0.074095 / 0.075469 (-0.001374) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.577905 / 1.841788 (-0.263883) | 23.280931 / 8.074308 (15.206623) | 21.017946 / 10.191392 (10.826554) | 0.228746 / 0.680424 (-0.451678) | 0.027877 / 0.534201 (-0.506324) | 0.469173 / 0.579283 (-0.110110) | 0.567614 / 0.434364 (0.133250) | 0.545041 / 0.540337 (0.004704) | 0.754743 / 1.386936 (-0.632194) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008958 / 0.011353 (-0.002395) | 0.005077 / 0.011008 (-0.005931) | 0.083990 / 0.038508 (0.045482) | 0.078586 / 0.023109 (0.055476) | 0.482164 / 0.275898 (0.206266) | 0.525575 / 0.323480 (0.202095) | 0.006031 / 0.007986 (-0.001955) | 0.003922 / 0.004328 (-0.000407) | 0.084547 / 0.004250 (0.080296) | 0.064539 / 0.037052 (0.027487) | 0.501256 / 0.258489 (0.242767) | 0.531985 / 0.293841 (0.238144) | 0.050438 / 0.128546 (-0.078109) | 0.014004 / 0.075646 (-0.061642) | 0.091269 / 0.419271 (-0.328003) | 0.060825 / 0.043533 (0.017292) | 0.492573 / 0.255139 (0.237434) | 0.517060 / 0.283200 (0.233861) | 0.033576 / 0.141683 (-0.108107) | 1.775719 / 1.452155 (0.323564) | 1.866865 / 1.492716 (0.374149) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.225026 / 0.018006 (0.207020) | 0.510715 / 0.000490 (0.510225) | 0.005791 / 0.000200 (0.005591) | 0.000116 / 0.000054 (0.000061) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.032795 / 0.037411 (-0.004616) | 0.109206 / 0.014526 (0.094680) | 0.121441 / 0.176557 (-0.055115) | 0.179735 / 0.737135 (-0.557401) | 0.115825 / 0.296338 (-0.180514) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.633259 / 0.215209 (0.418050) | 6.298084 / 2.077655 (4.220430) | 2.892604 / 1.504120 (1.388484) | 2.570858 / 1.541195 (1.029663) | 2.611441 / 1.468490 (1.142951) | 0.897801 / 4.584777 (-3.686976) | 5.185863 / 3.745712 (1.440151) | 4.656897 / 5.269862 (-0.612965) | 3.078575 / 4.565676 (-1.487101) | 0.100563 / 0.424275 (-0.323712) | 0.008368 / 0.007607 (0.000761) | 0.749152 / 0.226044 (0.523108) | 7.687484 / 2.268929 (5.418556) | 3.689238 / 55.444624 (-51.755387) | 2.896779 / 6.876477 (-3.979698) | 3.158688 / 2.142072 (1.016615) | 1.083490 / 4.805227 (-3.721737) | 0.216994 / 6.500664 (-6.283670) | 0.074053 / 0.075469 (-0.001416) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.732812 / 1.841788 (-0.108976) | 23.952127 / 8.074308 (15.877819) | 22.078140 / 10.191392 (11.886748) | 0.229491 / 0.680424 (-0.450933) | 0.032070 / 0.534201 (-0.502131) | 0.503344 / 0.579283 (-0.075939) | 0.588489 / 0.434364 (0.154125) | 0.550199 / 0.540337 (0.009861) | 0.778203 / 1.386936 (-0.608733) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#7e95a508b8d1747b5331bdbbd3e1021e97602c49 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007569 / 0.011353 (-0.003784) | 0.004447 / 0.011008 (-0.006561) | 0.098573 / 0.038508 (0.060064) | 0.081743 / 0.023109 (0.058634) | 0.379912 / 0.275898 (0.104013) | 0.411203 / 0.323480 (0.087723) | 0.004492 / 0.007986 (-0.003494) | 0.005627 / 0.004328 (0.001298) | 0.075974 / 0.004250 (0.071724) | 0.062512 / 0.037052 (0.025459) | 0.386971 / 0.258489 (0.128482) | 0.433299 / 0.293841 (0.139458) | 0.035935 / 0.128546 (-0.092611) | 0.009845 / 0.075646 (-0.065801) | 0.342940 / 0.419271 (-0.076331) | 0.061343 / 0.043533 (0.017810) | 0.381984 / 0.255139 (0.126845) | 0.417921 / 0.283200 (0.134721) | 0.028469 / 0.141683 (-0.113214) | 1.758472 / 1.452155 (0.306317) | 1.847768 / 1.492716 (0.355051) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.234297 / 0.018006 (0.216291) | 0.520020 / 0.000490 (0.519531) | 0.007375 / 0.000200 (0.007175) | 0.000767 / 0.000054 (0.000713) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.032738 / 0.037411 (-0.004673) | 0.097656 / 0.014526 (0.083130) | 0.112476 / 0.176557 (-0.064080) | 0.179222 / 0.737135 (-0.557913) | 0.113638 / 0.296338 (-0.182700) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.453677 / 0.215209 (0.238467) | 4.528143 / 2.077655 (2.450489) | 2.243874 / 1.504120 (0.739754) | 2.051546 / 1.541195 (0.510351) | 2.196050 / 1.468490 (0.727560) | 0.567345 / 4.584777 (-4.017432) | 4.133591 / 3.745712 (0.387879) | 3.855286 / 5.269862 (-1.414576) | 2.393496 / 4.565676 (-2.172180) | 0.066567 / 0.424275 (-0.357708) | 0.009038 / 0.007607 (0.001431) | 0.549166 / 0.226044 (0.323122) | 5.472767 / 2.268929 (3.203839) | 2.788012 / 55.444624 (-52.656612) | 2.426132 / 6.876477 (-4.450345) | 2.684856 / 2.142072 (0.542784) | 0.680198 / 4.805227 (-4.125029) | 0.157782 / 6.500664 (-6.342882) | 0.073000 / 0.075469 (-0.002469) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.622435 / 1.841788 (-0.219352) | 22.965715 / 8.074308 (14.891407) | 16.626903 / 10.191392 (6.435511) | 0.197156 / 0.680424 (-0.483268) | 0.025599 / 0.534201 (-0.508602) | 0.495550 / 0.579283 (-0.083733) | 0.466575 / 0.434364 (0.032211) | 0.565862 / 0.540337 (0.025525) | 0.793835 / 1.386936 (-0.593102) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007721 / 0.011353 (-0.003632) | 0.004652 / 0.011008 (-0.006356) | 0.076636 / 0.038508 (0.038127) | 0.082183 / 0.023109 (0.059074) | 0.474665 / 0.275898 (0.198767) | 0.511593 / 0.323480 (0.188113) | 0.006240 / 0.007986 (-0.001746) | 0.003750 / 0.004328 (-0.000578) | 0.076939 / 0.004250 (0.072689) | 0.063333 / 0.037052 (0.026281) | 0.476469 / 0.258489 (0.217980) | 0.512514 / 0.293841 (0.218674) | 0.037802 / 0.128546 (-0.090744) | 0.009975 / 0.075646 (-0.065671) | 0.084190 / 0.419271 (-0.335081) | 0.056705 / 0.043533 (0.013172) | 0.475429 / 0.255139 (0.220290) | 0.496414 / 0.283200 (0.213215) | 0.026039 / 0.141683 (-0.115644) | 1.796059 / 1.452155 (0.343905) | 1.867461 / 1.492716 (0.374745) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.285219 / 0.018006 (0.267213) | 0.506311 / 0.000490 (0.505821) | 0.018545 / 0.000200 (0.018345) | 0.000142 / 0.000054 (0.000088) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.037832 / 0.037411 (0.000420) | 0.110437 / 0.014526 (0.095911) | 0.122953 / 0.176557 (-0.053604) | 0.187049 / 0.737135 (-0.550087) | 0.123539 / 0.296338 (-0.172800) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.508120 / 0.215209 (0.292911) | 5.082836 / 2.077655 (3.005182) | 2.800411 / 1.504120 (1.296291) | 2.579457 / 1.541195 (1.038262) | 2.645945 / 1.468490 (1.177455) | 0.578574 / 4.584777 (-4.006203) | 4.163401 / 3.745712 (0.417689) | 3.858575 / 5.269862 (-1.411286) | 2.389892 / 4.565676 (-2.175785) | 0.068639 / 0.424275 (-0.355636) | 0.008779 / 0.007607 (0.001172) | 0.598925 / 0.226044 (0.372880) | 5.987147 / 2.268929 (3.718219) | 3.361791 / 55.444624 (-52.082833) | 2.910425 / 6.876477 (-3.966051) | 3.156849 / 2.142072 (1.014776) | 0.690945 / 4.805227 (-4.114283) | 0.157441 / 6.500664 (-6.343223) | 0.071596 / 0.075469 (-0.003873) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.672763 / 1.841788 (-0.169025) | 23.599525 / 8.074308 (15.525217) | 17.520087 / 10.191392 (7.328695) | 0.169174 / 0.680424 (-0.511250) | 0.023470 / 0.534201 (-0.510731) | 0.469234 / 0.579283 (-0.110050) | 0.470020 / 0.434364 (0.035656) | 0.579949 / 0.540337 (0.039611) | 0.771353 / 1.386936 (-0.615583) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#029227a116c14720afca71b9b22e78eb2a1c09a6 \"CML watermark\")\n" ]

"2023-08-29T15:23:41Z"

"2023-08-30T14:01:56Z"

"2023-08-30T13:51:32Z"

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[ "_The documentation is not available anymore as the PR was closed or merged._", "I have found the same issue. Good fix. Should be merged as soon as possible.", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006258 / 0.011353 (-0.005095) | 0.003717 / 0.011008 (-0.007291) | 0.079444 / 0.038508 (0.040936) | 0.066318 / 0.023109 (0.043209) | 0.310129 / 0.275898 (0.034231) | 0.346948 / 0.323480 (0.023469) | 0.003505 / 0.007986 (-0.004480) | 0.002855 / 0.004328 (-0.001474) | 0.062447 / 0.004250 (0.058197) | 0.050191 / 0.037052 (0.013139) | 0.314550 / 0.258489 (0.056061) | 0.357883 / 0.293841 (0.064042) | 0.027754 / 0.128546 (-0.100792) | 0.008068 / 0.075646 (-0.067578) | 0.262170 / 0.419271 (-0.157102) | 0.045834 / 0.043533 (0.002301) | 0.306938 / 0.255139 (0.051799) | 0.339229 / 0.283200 (0.056030) | 0.021188 / 0.141683 (-0.120495) | 1.430904 / 1.452155 (-0.021251) | 1.542038 / 1.492716 (0.049321) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.201232 / 0.018006 (0.183226) | 0.432848 / 0.000490 (0.432358) | 0.002403 / 0.000200 (0.002203) | 0.000070 / 0.000054 (0.000015) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.024068 / 0.037411 (-0.013344) | 0.074077 / 0.014526 (0.059551) | 0.083578 / 0.176557 (-0.092978) | 0.144497 / 0.737135 (-0.592638) | 0.085386 / 0.296338 (-0.210952) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.397912 / 0.215209 (0.182702) | 3.940953 / 2.077655 (1.863299) | 1.935914 / 1.504120 (0.431794) | 1.753688 / 1.541195 (0.212493) | 1.832916 / 1.468490 (0.364426) | 0.503320 / 4.584777 (-4.081457) | 3.068693 / 3.745712 (-0.677019) | 2.867543 / 5.269862 (-2.402318) | 1.876265 / 4.565676 (-2.689412) | 0.057234 / 0.424275 (-0.367041) | 0.006753 / 0.007607 (-0.000854) | 0.468456 / 0.226044 (0.242411) | 4.681671 / 2.268929 (2.412742) | 2.445141 / 55.444624 (-52.999483) | 2.182366 / 6.876477 (-4.694110) | 2.399365 / 2.142072 (0.257293) | 0.591880 / 4.805227 (-4.213347) | 0.126176 / 6.500664 (-6.374488) | 0.061488 / 0.075469 (-0.013982) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.244013 / 1.841788 (-0.597775) | 18.534720 / 8.074308 (10.460412) | 13.853267 / 10.191392 (3.661875) | 0.154167 / 0.680424 (-0.526257) | 0.016685 / 0.534201 (-0.517515) | 0.331044 / 0.579283 (-0.248239) | 0.341399 / 0.434364 (-0.092965) | 0.378878 / 0.540337 (-0.161459) | 0.535707 / 1.386936 (-0.851230) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006284 / 0.011353 (-0.005069) | 0.003707 / 0.011008 (-0.007301) | 0.062481 / 0.038508 (0.023973) | 0.063342 / 0.023109 (0.040233) | 0.445465 / 0.275898 (0.169567) | 0.482021 / 0.323480 (0.158541) | 0.004909 / 0.007986 (-0.003076) | 0.002908 / 0.004328 (-0.001420) | 0.063111 / 0.004250 (0.058860) | 0.050197 / 0.037052 (0.013145) | 0.453367 / 0.258489 (0.194878) | 0.485249 / 0.293841 (0.191408) | 0.028532 / 0.128546 (-0.100014) | 0.008157 / 0.075646 (-0.067490) | 0.068033 / 0.419271 (-0.351238) | 0.041093 / 0.043533 (-0.002440) | 0.446555 / 0.255139 (0.191416) | 0.469103 / 0.283200 (0.185904) | 0.019529 / 0.141683 (-0.122154) | 1.503135 / 1.452155 (0.050980) | 1.545819 / 1.492716 (0.053103) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.257274 / 0.018006 (0.239268) | 0.418643 / 0.000490 (0.418153) | 0.011604 / 0.000200 (0.011405) | 0.000094 / 0.000054 (0.000040) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.026286 / 0.037411 (-0.011125) | 0.082459 / 0.014526 (0.067933) | 0.090007 / 0.176557 (-0.086550) | 0.144963 / 0.737135 (-0.592173) | 0.093236 / 0.296338 (-0.203102) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.456331 / 0.215209 (0.241122) | 4.559469 / 2.077655 (2.481814) | 2.503452 / 1.504120 (0.999333) | 2.326579 / 1.541195 (0.785384) | 2.387551 / 1.468490 (0.919061) | 0.508683 / 4.584777 (-4.076094) | 3.071293 / 3.745712 (-0.674419) | 2.872820 / 5.269862 (-2.397041) | 1.891674 / 4.565676 (-2.674003) | 0.058951 / 0.424275 (-0.365324) | 0.006493 / 0.007607 (-0.001114) | 0.526747 / 0.226044 (0.300703) | 5.279985 / 2.268929 (3.011057) | 2.986146 / 55.444624 (-52.458478) | 2.603462 / 6.876477 (-4.273015) | 2.766776 / 2.142072 (0.624704) | 0.594685 / 4.805227 (-4.210542) | 0.125174 / 6.500664 (-6.375490) | 0.061430 / 0.075469 (-0.014039) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.350012 / 1.841788 (-0.491776) | 18.991941 / 8.074308 (10.917633) | 14.903483 / 10.191392 (4.712091) | 0.145918 / 0.680424 (-0.534506) | 0.017766 / 0.534201 (-0.516435) | 0.335350 / 0.579283 (-0.243933) | 0.357936 / 0.434364 (-0.076428) | 0.392355 / 0.540337 (-0.147983) | 0.545787 / 1.386936 (-0.841149) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#439e115d34a2d8737af719660c1b586ac32279dc \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.005927 / 0.011353 (-0.005426) | 0.003497 / 0.011008 (-0.007512) | 0.079802 / 0.038508 (0.041294) | 0.058994 / 0.023109 (0.035885) | 0.309349 / 0.275898 (0.033451) | 0.344876 / 0.323480 (0.021396) | 0.004631 / 0.007986 (-0.003354) | 0.002814 / 0.004328 (-0.001515) | 0.062228 / 0.004250 (0.057978) | 0.046001 / 0.037052 (0.008949) | 0.312196 / 0.258489 (0.053707) | 0.356283 / 0.293841 (0.062442) | 0.027264 / 0.128546 (-0.101282) | 0.007992 / 0.075646 (-0.067654) | 0.260746 / 0.419271 (-0.158526) | 0.045112 / 0.043533 (0.001579) | 0.310463 / 0.255139 (0.055324) | 0.336456 / 0.283200 (0.053256) | 0.020364 / 0.141683 (-0.121319) | 1.482159 / 1.452155 (0.030005) | 1.541586 / 1.492716 (0.048870) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.185035 / 0.018006 (0.167028) | 0.432104 / 0.000490 (0.431615) | 0.002911 / 0.000200 (0.002711) | 0.000070 / 0.000054 (0.000016) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.023674 / 0.037411 (-0.013737) | 0.072462 / 0.014526 (0.057936) | 0.080154 / 0.176557 (-0.096402) | 0.143022 / 0.737135 (-0.594114) | 0.082909 / 0.296338 (-0.213430) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.436977 / 0.215209 (0.221768) | 4.359633 / 2.077655 (2.281979) | 2.321479 / 1.504120 (0.817359) | 2.115277 / 1.541195 (0.574082) | 2.172303 / 1.468490 (0.703813) | 0.495735 / 4.584777 (-4.089042) | 3.006773 / 3.745712 (-0.738939) | 2.866560 / 5.269862 (-2.403302) | 1.839339 / 4.565676 (-2.726337) | 0.056925 / 0.424275 (-0.367350) | 0.006777 / 0.007607 (-0.000830) | 0.507217 / 0.226044 (0.281172) | 5.064933 / 2.268929 (2.796004) | 2.737542 / 55.444624 (-52.707082) | 2.386227 / 6.876477 (-4.490250) | 2.566375 / 2.142072 (0.424302) | 0.582965 / 4.805227 (-4.222262) | 0.124715 / 6.500664 (-6.375949) | 0.061560 / 0.075469 (-0.013909) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.295684 / 1.841788 (-0.546103) | 18.178345 / 8.074308 (10.104037) | 13.795886 / 10.191392 (3.604494) | 0.131464 / 0.680424 (-0.548960) | 0.016808 / 0.534201 (-0.517393) | 0.334190 / 0.579283 (-0.245093) | 0.347358 / 0.434364 (-0.087006) | 0.386198 / 0.540337 (-0.154139) | 0.527807 / 1.386936 (-0.859129) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006118 / 0.011353 (-0.005235) | 0.003634 / 0.011008 (-0.007374) | 0.062117 / 0.038508 (0.023609) | 0.061407 / 0.023109 (0.038298) | 0.448047 / 0.275898 (0.172149) | 0.483382 / 0.323480 (0.159902) | 0.004849 / 0.007986 (-0.003137) | 0.002859 / 0.004328 (-0.001469) | 0.061714 / 0.004250 (0.057463) | 0.047959 / 0.037052 (0.010907) | 0.452038 / 0.258489 (0.193549) | 0.485206 / 0.293841 (0.191365) | 0.028254 / 0.128546 (-0.100292) | 0.008055 / 0.075646 (-0.067591) | 0.067752 / 0.419271 (-0.351519) | 0.040355 / 0.043533 (-0.003178) | 0.446986 / 0.255139 (0.191847) | 0.472554 / 0.283200 (0.189354) | 0.019461 / 0.141683 (-0.122222) | 1.459048 / 1.452155 (0.006893) | 1.497283 / 1.492716 (0.004566) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.241788 / 0.018006 (0.223782) | 0.457352 / 0.000490 (0.456862) | 0.003841 / 0.000200 (0.003641) | 0.000081 / 0.000054 (0.000027) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.026429 / 0.037411 (-0.010982) | 0.081604 / 0.014526 (0.067078) | 0.092881 / 0.176557 (-0.083675) | 0.146057 / 0.737135 (-0.591078) | 0.092987 / 0.296338 (-0.203352) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.456641 / 0.215209 (0.241432) | 4.567853 / 2.077655 (2.490198) | 2.491684 / 1.504120 (0.987564) | 2.323647 / 1.541195 (0.782452) | 2.387689 / 1.468490 (0.919198) | 0.505114 / 4.584777 (-4.079663) | 3.071615 / 3.745712 (-0.674098) | 2.912391 / 5.269862 (-2.357471) | 1.922350 / 4.565676 (-2.643326) | 0.057785 / 0.424275 (-0.366490) | 0.006642 / 0.007607 (-0.000965) | 0.532463 / 0.226044 (0.306418) | 5.344084 / 2.268929 (3.075155) | 2.970182 / 55.444624 (-52.474442) | 2.601733 / 6.876477 (-4.274744) | 2.763803 / 2.142072 (0.621731) | 0.596333 / 4.805227 (-4.208894) | 0.127047 / 6.500664 (-6.373617) | 0.062516 / 0.075469 (-0.012953) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.343206 / 1.841788 (-0.498581) | 19.405215 / 8.074308 (11.330907) | 15.406568 / 10.191392 (5.215176) | 0.132328 / 0.680424 (-0.548096) | 0.017882 / 0.534201 (-0.516318) | 0.336393 / 0.579283 (-0.242890) | 0.361989 / 0.434364 (-0.072375) | 0.394336 / 0.540337 (-0.146001) | 0.545166 / 1.386936 (-0.841770) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#439e115d34a2d8737af719660c1b586ac32279dc \"CML watermark\")\n" ]

"2023-08-29T13:05:04Z"

"2023-09-04T06:38:17Z"

"2023-08-31T13:50:00Z"

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[]

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[ "This is because `download_config.use_auth_token` is deprecated - you should use `download_config.token` instead", "Works! Thanks for the quick fix! <3" ]

"2023-08-29T12:37:03Z"

"2023-08-29T13:01:10Z"

"2023-08-29T13:01:09Z"

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[ "_The documentation is not available anymore as the PR was closed or merged._", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006166 / 0.011353 (-0.005187) | 0.003643 / 0.011008 (-0.007365) | 0.080966 / 0.038508 (0.042458) | 0.060538 / 0.023109 (0.037429) | 0.309205 / 0.275898 (0.033307) | 0.351007 / 0.323480 (0.027527) | 0.003592 / 0.007986 (-0.004393) | 0.002880 / 0.004328 (-0.001448) | 0.062957 / 0.004250 (0.058707) | 0.049015 / 0.037052 (0.011963) | 0.309436 / 0.258489 (0.050947) | 0.362695 / 0.293841 (0.068854) | 0.027818 / 0.128546 (-0.100728) | 0.008030 / 0.075646 (-0.067616) | 0.262678 / 0.419271 (-0.156594) | 0.046024 / 0.043533 (0.002491) | 0.316246 / 0.255139 (0.061107) | 0.337454 / 0.283200 (0.054254) | 0.022529 / 0.141683 (-0.119154) | 1.432492 / 1.452155 (-0.019662) | 1.499646 / 1.492716 (0.006929) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.190931 / 0.018006 (0.172925) | 0.428053 / 0.000490 (0.427564) | 0.002839 / 0.000200 (0.002639) | 0.000069 / 0.000054 (0.000014) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.024042 / 0.037411 (-0.013370) | 0.073952 / 0.014526 (0.059426) | 0.905973 / 0.176557 (0.729417) | 0.177767 / 0.737135 (-0.559368) | 0.125779 / 0.296338 (-0.170559) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.398997 / 0.215209 (0.183788) | 3.959575 / 2.077655 (1.881920) | 1.907038 / 1.504120 (0.402918) | 1.732908 / 1.541195 (0.191713) | 1.757038 / 1.468490 (0.288548) | 0.495917 / 4.584777 (-4.088860) | 3.021437 / 3.745712 (-0.724275) | 2.793960 / 5.269862 (-2.475901) | 1.827753 / 4.565676 (-2.737923) | 0.057143 / 0.424275 (-0.367132) | 0.006583 / 0.007607 (-0.001024) | 0.469402 / 0.226044 (0.243357) | 4.685623 / 2.268929 (2.416695) | 2.325200 / 55.444624 (-53.119424) | 1.985559 / 6.876477 (-4.890918) | 2.151208 / 2.142072 (0.009136) | 0.589498 / 4.805227 (-4.215730) | 0.125433 / 6.500664 (-6.375231) | 0.060834 / 0.075469 (-0.014636) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.228217 / 1.841788 (-0.613571) | 18.076089 / 8.074308 (10.001780) | 13.814460 / 10.191392 (3.623068) | 0.144674 / 0.680424 (-0.535750) | 0.016749 / 0.534201 (-0.517452) | 0.332839 / 0.579283 (-0.246444) | 0.357211 / 0.434364 (-0.077153) | 0.380367 / 0.540337 (-0.159971) | 0.531177 / 1.386936 (-0.855759) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006006 / 0.011353 (-0.005347) | 0.003552 / 0.011008 (-0.007456) | 0.061822 / 0.038508 (0.023313) | 0.057724 / 0.023109 (0.034615) | 0.462326 / 0.275898 (0.186428) | 0.492842 / 0.323480 (0.169362) | 0.004833 / 0.007986 (-0.003152) | 0.002847 / 0.004328 (-0.001481) | 0.062278 / 0.004250 (0.058028) | 0.046754 / 0.037052 (0.009702) | 0.464185 / 0.258489 (0.205696) | 0.496416 / 0.293841 (0.202576) | 0.028949 / 0.128546 (-0.099597) | 0.008038 / 0.075646 (-0.067608) | 0.067572 / 0.419271 (-0.351700) | 0.041176 / 0.043533 (-0.002356) | 0.460047 / 0.255139 (0.204908) | 0.482728 / 0.283200 (0.199528) | 0.020047 / 0.141683 (-0.121635) | 1.455958 / 1.452155 (0.003804) | 1.525730 / 1.492716 (0.033014) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.283643 / 0.018006 (0.265637) | 0.443046 / 0.000490 (0.442556) | 0.041019 / 0.000200 (0.040819) | 0.000340 / 0.000054 (0.000286) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.026229 / 0.037411 (-0.011182) | 0.081498 / 0.014526 (0.066972) | 0.091412 / 0.176557 (-0.085145) | 0.146621 / 0.737135 (-0.590514) | 0.092113 / 0.296338 (-0.204225) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.463525 / 0.215209 (0.248315) | 4.629852 / 2.077655 (2.552198) | 2.564831 / 1.504120 (1.060711) | 2.386976 / 1.541195 (0.845781) | 2.457757 / 1.468490 (0.989266) | 0.507317 / 4.584777 (-4.077460) | 3.142418 / 3.745712 (-0.603294) | 2.851642 / 5.269862 (-2.418219) | 1.894444 / 4.565676 (-2.671233) | 0.058495 / 0.424275 (-0.365780) | 0.006453 / 0.007607 (-0.001154) | 0.545363 / 0.226044 (0.319319) | 5.448092 / 2.268929 (3.179164) | 2.996328 / 55.444624 (-52.448296) | 2.664666 / 6.876477 (-4.211811) | 2.832247 / 2.142072 (0.690174) | 0.597631 / 4.805227 (-4.207596) | 0.126101 / 6.500664 (-6.374563) | 0.062573 / 0.075469 (-0.012896) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.366502 / 1.841788 (-0.475286) | 18.872990 / 8.074308 (10.798682) | 14.892114 / 10.191392 (4.700722) | 0.146668 / 0.680424 (-0.533756) | 0.017876 / 0.534201 (-0.516325) | 0.338490 / 0.579283 (-0.240793) | 0.357471 / 0.434364 (-0.076893) | 0.398730 / 0.540337 (-0.141608) | 0.542464 / 1.386936 (-0.844472) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#a6ff3e846d86814fa6962326e9346a4f1f1e8a80 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.009132 / 0.011353 (-0.002221) | 0.005796 / 0.011008 (-0.005212) | 0.119495 / 0.038508 (0.080987) | 0.081708 / 0.023109 (0.058599) | 0.432940 / 0.275898 (0.157042) | 0.466793 / 0.323480 (0.143313) | 0.006464 / 0.007986 (-0.001521) | 0.004308 / 0.004328 (-0.000021) | 0.086344 / 0.004250 (0.082093) | 0.065987 / 0.037052 (0.028935) | 0.445213 / 0.258489 (0.186724) | 0.482405 / 0.293841 (0.188564) | 0.053553 / 0.128546 (-0.074993) | 0.015320 / 0.075646 (-0.060326) | 0.455669 / 0.419271 (0.036397) | 0.071619 / 0.043533 (0.028086) | 0.434843 / 0.255139 (0.179704) | 0.503224 / 0.283200 (0.220025) | 0.038280 / 0.141683 (-0.103403) | 1.901877 / 1.452155 (0.449722) | 2.040406 / 1.492716 (0.547690) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.268275 / 0.018006 (0.250269) | 0.622795 / 0.000490 (0.622305) | 0.004572 / 0.000200 (0.004372) | 0.000107 / 0.000054 (0.000053) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.032514 / 0.037411 (-0.004898) | 0.100619 / 0.014526 (0.086093) | 0.118407 / 0.176557 (-0.058149) | 0.190311 / 0.737135 (-0.546824) | 0.117160 / 0.296338 (-0.179178) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.629836 / 0.215209 (0.414627) | 6.236124 / 2.077655 (4.158470) | 2.750775 / 1.504120 (1.246655) | 2.380111 / 1.541195 (0.838916) | 2.487279 / 1.468490 (1.018789) | 0.849568 / 4.584777 (-3.735209) | 5.571308 / 3.745712 (1.825596) | 4.934114 / 5.269862 (-0.335747) | 3.205478 / 4.565676 (-1.360198) | 0.104804 / 0.424275 (-0.319471) | 0.009856 / 0.007607 (0.002248) | 0.753352 / 0.226044 (0.527308) | 7.523482 / 2.268929 (5.254554) | 3.660088 / 55.444624 (-51.784537) | 2.726493 / 6.876477 (-4.149984) | 3.011344 / 2.142072 (0.869271) | 1.093410 / 4.805227 (-3.711817) | 0.229758 / 6.500664 (-6.270906) | 0.081516 / 0.075469 (0.006047) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.700199 / 1.841788 (-0.141588) | 25.238736 / 8.074308 (17.164428) | 23.188131 / 10.191392 (12.996739) | 0.257862 / 0.680424 (-0.422562) | 0.028885 / 0.534201 (-0.505316) | 0.510693 / 0.579283 (-0.068590) | 0.648474 / 0.434364 (0.214110) | 0.576314 / 0.540337 (0.035976) | 0.800606 / 1.386936 (-0.586330) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.009426 / 0.011353 (-0.001927) | 0.006205 / 0.011008 (-0.004803) | 0.083947 / 0.038508 (0.045438) | 0.089164 / 0.023109 (0.066055) | 0.540500 / 0.275898 (0.264602) | 0.578825 / 0.323480 (0.255345) | 0.006792 / 0.007986 (-0.001194) | 0.005125 / 0.004328 (0.000797) | 0.083284 / 0.004250 (0.079034) | 0.067539 / 0.037052 (0.030487) | 0.544330 / 0.258489 (0.285841) | 0.593836 / 0.293841 (0.299995) | 0.050647 / 0.128546 (-0.077899) | 0.014688 / 0.075646 (-0.060959) | 0.095977 / 0.419271 (-0.323295) | 0.062326 / 0.043533 (0.018793) | 0.536096 / 0.255139 (0.280957) | 0.578691 / 0.283200 (0.295492) | 0.035488 / 0.141683 (-0.106194) | 1.911145 / 1.452155 (0.458990) | 1.977647 / 1.492716 (0.484931) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.368365 / 0.018006 (0.350359) | 0.609836 / 0.000490 (0.609346) | 0.054720 / 0.000200 (0.054520) | 0.000465 / 0.000054 (0.000411) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.036057 / 0.037411 (-0.001355) | 0.126434 / 0.014526 (0.111908) | 0.124740 / 0.176557 (-0.051817) | 0.198907 / 0.737135 (-0.538228) | 0.138201 / 0.296338 (-0.158137) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.684814 / 0.215209 (0.469605) | 6.738182 / 2.077655 (4.660527) | 3.231054 / 1.504120 (1.726934) | 2.889550 / 1.541195 (1.348355) | 2.933985 / 1.468490 (1.465495) | 0.867176 / 4.584777 (-3.717601) | 5.465475 / 3.745712 (1.719763) | 4.928370 / 5.269862 (-0.341492) | 3.126382 / 4.565676 (-1.439294) | 0.129673 / 0.424275 (-0.294603) | 0.009755 / 0.007607 (0.002148) | 0.797860 / 0.226044 (0.571816) | 8.003178 / 2.268929 (5.734250) | 4.081658 / 55.444624 (-51.362966) | 3.303837 / 6.876477 (-3.572640) | 3.574577 / 2.142072 (1.432505) | 1.064674 / 4.805227 (-3.740554) | 0.232894 / 6.500664 (-6.267770) | 0.082298 / 0.075469 (0.006829) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.858701 / 1.841788 (0.016913) | 25.839794 / 8.074308 (17.765485) | 24.291425 / 10.191392 (14.100033) | 0.250181 / 0.680424 (-0.430243) | 0.034479 / 0.534201 (-0.499722) | 0.540754 / 0.579283 (-0.038529) | 0.615996 / 0.434364 (0.181632) | 0.631499 / 0.540337 (0.091161) | 0.838719 / 1.386936 (-0.548217) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#0b6bb2f0e7a460d4ed04855eafe1184a7ce7c09c \"CML watermark\")\n" ]

"2023-08-29T12:29:47Z"

"2023-08-29T13:04:59Z"

"2023-08-29T12:52:48Z"

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[ "I think this error means you filter all examples within an (input) batch by deleting its columns. In that case, to avoid the error, you can set the column value to an empty list (`input_batch[\"col\"] = []`) instead." ]

"2023-08-29T06:37:34Z"

"2023-08-30T13:37:14Z"

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[ "Hi! You can load this dataset with:\r\n```python\r\ndata_files = {\r\n \"train\": \"/content/PUBHEALTH/train.tsv\",\r\n \"validation\": \"/content/PUBHEALTH/dev.tsv\",\r\n \"test\": \"/content/PUBHEALTH/test.tsv\",\r\n}\r\n\r\ntsv_datasets_reloaded = load_dataset(\"csv\", data_files=data_files, sep=\"\\t\")\r\n```\r\n\r\nTo support your `load_dataset` call, defining aliases for the packaged builders, as suggested in https://github.com/huggingface/datasets/issues/5625, must be implemented. We can consider adding this feature if more people request it.\r\n \r\n(Also answered on the Discord [here](https://discord.com/channels/879548962464493619/1145956791134470224/1146071491260186744))" ]

"2023-08-29T05:49:56Z"

"2023-08-29T16:21:45Z"

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[ "That'd be a great idea! @mariosasko or @lhoestq, would it be possible to fix the code snippet or do you have another suggested way for doing this?", "Indeed `if __name__ == \"__main__\"` is important in this case.\r\n\r\nNot sure about the imbalanced GPU usage though, but maybe you can try using the `torch.cuda.device` context manager ?\r\n\r\n> also, should I do it like this or use nn.DataParallel?\r\n\r\nIn this case you wouldn't need a multiprocessed map no ? Since nn.DataParallel would take care of parallelism" ]

"2023-08-28T10:00:59Z"

"2023-08-30T13:34:14Z"

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[ "You can cast the `input_image` column to the `Image` type to fix the issue:\r\n```python\r\nds.cast_column(\"input_image\", datasets.Image())\r\n```" ]

"2023-08-26T12:15:57Z"

"2023-08-29T14:49:58Z"

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[]

[ "This issue is a duplicate of https://github.com/huggingface/datasets/issues/3297. This is a limitation of `dill`, a package we use for caching (non-`__main__` module objects are serialized by reference). You can find more info about it here: https://github.com/uqfoundation/dill/issues/424.\r\n\r\nIn your case, moving \r\n```\r\ndata = datasets.load_dataset('json', data_files=['/tmp/test.json'], split='train')\r\ndata = data.map(transform)\r\n``` \r\nto `test.py` and setting `transform.__module__ = None` at the end of `dataset.py` should fix the issue.", "I understand this may be a limitation of an upstream tool, but for a user for datasets this is very annoying, as when you have dozens of different datasets with different preprocessing functions you can't really move them all into the same file. It may be worth seeing if there is a way to specialize the dependency (eg. subclass it) and enforce behaviors that makes sense for your product.\r\n\r\nI was able to work around this for now by setting `__module__ = None`. If such workarounds are required for now it may be better to document it somewhere than a single obscure issue from a long time ago.\r\n\r\nAs this is a duplicate issue I'm closing it.\r\n\r\nI have another issue with the cache https://github.com/huggingface/datasets/issues/6179 can you take a look?" ]

"2023-08-25T22:59:14Z"

"2023-08-29T20:57:07Z"

"2023-08-29T20:56:49Z"

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[ "Same problem", "This was fixed in https://github.com/huggingface/datasets/pull/6155, which will be included in the next release (or you can install `datasets` from source to use it immediately)." ]

"2023-08-25T22:21:22Z"

"2023-08-29T13:26:22Z"

"2023-08-29T13:26:22Z"

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[ "Our minimal Python version requirement is 3.8, so we dropped `importlib_metadata`. \r\n\r\nFeel free to open a PR in the `evaluate` repo to replace the problematic import with\r\n```python\r\nif PY_VERSION < version.parse(\"3.8\"):\r\n import importlib_metadata\r\nelse:\r\n import importlib.metadata as importlib_metadata\r\n```", "Any idea when you guys will release the next version which deals with this problem?\r\nI'm still having the same issue with py 3.10 when I install the lib with pip.\r\nI'm assuming that it has not yet been updated since the merge was 3 days ago.", "Yes, this requires a new `evaluate` release (cc @lvwerra for this). \r\n\r\nIn the meantime, you can get the fixed version by installing `evaluate` from `main`: `pip install git+https://github.com/huggingface/evaluate.git`", "I'll aim for a release this week!" ]

"2023-08-25T14:54:06Z"

"2023-09-04T16:41:11Z"

"2023-08-31T14:38:23Z"

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[ "_The documentation is not available anymore as the PR was closed or merged._", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.009072 / 0.011353 (-0.002281) | 0.006088 / 0.011008 (-0.004920) | 0.134520 / 0.038508 (0.096011) | 0.074935 / 0.023109 (0.051826) | 0.480364 / 0.275898 (0.204466) | 0.568943 / 0.323480 (0.245464) | 0.006821 / 0.007986 (-0.001164) | 0.004941 / 0.004328 (0.000612) | 0.083274 / 0.004250 (0.079023) | 0.061080 / 0.037052 (0.024028) | 0.478960 / 0.258489 (0.220471) | 0.542720 / 0.293841 (0.248879) | 0.058023 / 0.128546 (-0.070524) | 0.020120 / 0.075646 (-0.055526) | 0.492680 / 0.419271 (0.073409) | 0.079118 / 0.043533 (0.035585) | 0.425087 / 0.255139 (0.169948) | 0.603228 / 0.283200 (0.320028) | 0.044102 / 0.141683 (-0.097581) | 2.138848 / 1.452155 (0.686693) | 2.454418 / 1.492716 (0.961702) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.255745 / 0.018006 (0.237738) | 0.587559 / 0.000490 (0.587069) | 0.006872 / 0.000200 (0.006672) | 0.000111 / 0.000054 (0.000056) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.038480 / 0.037411 (0.001069) | 0.115479 / 0.014526 (0.100953) | 0.138395 / 0.176557 (-0.038161) | 0.218007 / 0.737135 (-0.519129) | 0.128866 / 0.296338 (-0.167472) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.756089 / 0.215209 (0.540880) | 7.754631 / 2.077655 (5.676976) | 3.615716 / 1.504120 (2.111596) | 2.994327 / 1.541195 (1.453132) | 3.196169 / 1.468490 (1.727679) | 1.066937 / 4.584777 (-3.517840) | 6.079595 / 3.745712 (2.333883) | 5.455523 / 5.269862 (0.185661) | 3.559036 / 4.565676 (-1.006640) | 0.113044 / 0.424275 (-0.311231) | 0.011401 / 0.007607 (0.003794) | 0.961475 / 0.226044 (0.735430) | 8.664226 / 2.268929 (6.395298) | 4.203804 / 55.444624 (-51.240821) | 3.122437 / 6.876477 (-3.754039) | 3.549168 / 2.142072 (1.407095) | 1.213035 / 4.805227 (-3.592193) | 0.274725 / 6.500664 (-6.225939) | 0.094499 / 0.075469 (0.019030) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.770299 / 1.841788 (-0.071489) | 27.644591 / 8.074308 (19.570283) | 23.239529 / 10.191392 (13.048137) | 0.270185 / 0.680424 (-0.410238) | 0.033563 / 0.534201 (-0.500638) | 0.588301 / 0.579283 (0.009018) | 0.658746 / 0.434364 (0.224382) | 0.644476 / 0.540337 (0.104139) | 0.834314 / 1.386936 (-0.552622) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.011021 / 0.011353 (-0.000332) | 0.006719 / 0.011008 (-0.004289) | 0.087669 / 0.038508 (0.049161) | 0.088905 / 0.023109 (0.065796) | 0.594230 / 0.275898 (0.318332) | 0.620929 / 0.323480 (0.297449) | 0.006776 / 0.007986 (-0.001210) | 0.004725 / 0.004328 (0.000396) | 0.082006 / 0.004250 (0.077756) | 0.072164 / 0.037052 (0.035111) | 0.604489 / 0.258489 (0.346000) | 0.598520 / 0.293841 (0.304679) | 0.057534 / 0.128546 (-0.071013) | 0.016799 / 0.075646 (-0.058847) | 0.115029 / 0.419271 (-0.304243) | 0.070013 / 0.043533 (0.026481) | 0.561773 / 0.255139 (0.306634) | 0.624097 / 0.283200 (0.340897) | 0.043518 / 0.141683 (-0.098164) | 2.017089 / 1.452155 (0.564934) | 2.188159 / 1.492716 (0.695443) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.386476 / 0.018006 (0.368469) | 0.633195 / 0.000490 (0.632705) | 0.028469 / 0.000200 (0.028269) | 0.000159 / 0.000054 (0.000104) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.040020 / 0.037411 (0.002609) | 0.112927 / 0.014526 (0.098402) | 0.143663 / 0.176557 (-0.032894) | 0.205931 / 0.737135 (-0.531204) | 0.177814 / 0.296338 (-0.118524) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.711542 / 0.215209 (0.496333) | 7.518535 / 2.077655 (5.440880) | 3.714930 / 1.504120 (2.210810) | 3.031999 / 1.541195 (1.490804) | 3.328497 / 1.468490 (1.860006) | 0.858912 / 4.584777 (-3.725865) | 6.108384 / 3.745712 (2.362672) | 5.184329 / 5.269862 (-0.085532) | 3.622589 / 4.565676 (-0.943087) | 0.096933 / 0.424275 (-0.327342) | 0.008727 / 0.007607 (0.001120) | 0.830102 / 0.226044 (0.604057) | 8.331959 / 2.268929 (6.063030) | 4.165106 / 55.444624 (-51.279519) | 3.477003 / 6.876477 (-3.399474) | 3.794225 / 2.142072 (1.652153) | 1.237667 / 4.805227 (-3.567561) | 0.233731 / 6.500664 (-6.266933) | 0.076682 / 0.075469 (0.001213) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.944813 / 1.841788 (0.103026) | 27.666997 / 8.074308 (19.592689) | 24.562677 / 10.191392 (14.371285) | 0.279320 / 0.680424 (-0.401104) | 0.037802 / 0.534201 (-0.496399) | 0.553579 / 0.579283 (-0.025704) | 0.718229 / 0.434364 (0.283865) | 0.623456 / 0.540337 (0.083118) | 0.856777 / 1.386936 (-0.530159) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#4c2a9d31d5e720e85976af8b457d45755a7e6911 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007716 / 0.011353 (-0.003637) | 0.004624 / 0.011008 (-0.006384) | 0.099987 / 0.038508 (0.061479) | 0.082651 / 0.023109 (0.059542) | 0.376277 / 0.275898 (0.100379) | 0.401210 / 0.323480 (0.077730) | 0.004528 / 0.007986 (-0.003458) | 0.003763 / 0.004328 (-0.000566) | 0.076274 / 0.004250 (0.072024) | 0.062933 / 0.037052 (0.025881) | 0.393881 / 0.258489 (0.135392) | 0.431695 / 0.293841 (0.137854) | 0.036795 / 0.128546 (-0.091752) | 0.009935 / 0.075646 (-0.065712) | 0.343638 / 0.419271 (-0.075634) | 0.061456 / 0.043533 (0.017923) | 0.372235 / 0.255139 (0.117096) | 0.412994 / 0.283200 (0.129794) | 0.027993 / 0.141683 (-0.113690) | 1.798018 / 1.452155 (0.345863) | 1.898502 / 1.492716 (0.405786) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.237330 / 0.018006 (0.219324) | 0.494956 / 0.000490 (0.494467) | 0.003543 / 0.000200 (0.003343) | 0.000113 / 0.000054 (0.000059) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.034084 / 0.037411 (-0.003327) | 0.093407 / 0.014526 (0.078881) | 0.108378 / 0.176557 (-0.068179) | 0.177016 / 0.737135 (-0.560119) | 0.108622 / 0.296338 (-0.187716) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.456449 / 0.215209 (0.241240) | 4.522405 / 2.077655 (2.444750) | 2.206564 / 1.504120 (0.702444) | 1.994185 / 1.541195 (0.452990) | 2.083785 / 1.468490 (0.615295) | 0.563352 / 4.584777 (-4.021425) | 4.207295 / 3.745712 (0.461583) | 3.783061 / 5.269862 (-1.486800) | 2.372874 / 4.565676 (-2.192802) | 0.066907 / 0.424275 (-0.357368) | 0.009013 / 0.007607 (0.001406) | 0.537852 / 0.226044 (0.311808) | 5.349928 / 2.268929 (3.081000) | 2.759409 / 55.444624 (-52.685215) | 2.345972 / 6.876477 (-4.530505) | 2.630559 / 2.142072 (0.488486) | 0.681134 / 4.805227 (-4.124093) | 0.157898 / 6.500664 (-6.342766) | 0.071638 / 0.075469 (-0.003831) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.470730 / 1.841788 (-0.371058) | 22.479252 / 8.074308 (14.404944) | 16.543080 / 10.191392 (6.351688) | 0.191943 / 0.680424 (-0.488481) | 0.021641 / 0.534201 (-0.512560) | 0.467571 / 0.579283 (-0.111712) | 0.486728 / 0.434364 (0.052364) | 0.543359 / 0.540337 (0.003021) | 0.733968 / 1.386936 (-0.652968) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008135 / 0.011353 (-0.003218) | 0.004662 / 0.011008 (-0.006347) | 0.077218 / 0.038508 (0.038710) | 0.092220 / 0.023109 (0.069111) | 0.481219 / 0.275898 (0.205321) | 0.530373 / 0.323480 (0.206893) | 0.006418 / 0.007986 (-0.001568) | 0.003924 / 0.004328 (-0.000404) | 0.076681 / 0.004250 (0.072431) | 0.068693 / 0.037052 (0.031641) | 0.491938 / 0.258489 (0.233449) | 0.540501 / 0.293841 (0.246660) | 0.038106 / 0.128546 (-0.090441) | 0.010035 / 0.075646 (-0.065611) | 0.084502 / 0.419271 (-0.334769) | 0.057234 / 0.043533 (0.013701) | 0.483239 / 0.255139 (0.228100) | 0.510026 / 0.283200 (0.226826) | 0.028770 / 0.141683 (-0.112913) | 1.854937 / 1.452155 (0.402783) | 1.948268 / 1.492716 (0.455552) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.380192 / 0.018006 (0.362186) | 0.523318 / 0.000490 (0.522828) | 0.051153 / 0.000200 (0.050953) | 0.000691 / 0.000054 (0.000637) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.036838 / 0.037411 (-0.000573) | 0.109202 / 0.014526 (0.094676) | 0.124110 / 0.176557 (-0.052446) | 0.186717 / 0.737135 (-0.550419) | 0.124088 / 0.296338 (-0.172250) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.506411 / 0.215209 (0.291202) | 5.045421 / 2.077655 (2.967766) | 2.711911 / 1.504120 (1.207791) | 2.531668 / 1.541195 (0.990474) | 2.635680 / 1.468490 (1.167190) | 0.578395 / 4.584777 (-4.006382) | 4.206891 / 3.745712 (0.461178) | 3.851063 / 5.269862 (-1.418799) | 2.388327 / 4.565676 (-2.177350) | 0.068041 / 0.424275 (-0.356234) | 0.008769 / 0.007607 (0.001162) | 0.594170 / 0.226044 (0.368125) | 5.953138 / 2.268929 (3.684210) | 3.290586 / 55.444624 (-52.154038) | 2.877086 / 6.876477 (-3.999390) | 3.138600 / 2.142072 (0.996528) | 0.686393 / 4.805227 (-4.118834) | 0.156541 / 6.500664 (-6.344123) | 0.071514 / 0.075469 (-0.003955) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.613514 / 1.841788 (-0.228274) | 23.593185 / 8.074308 (15.518877) | 17.146647 / 10.191392 (6.955255) | 0.177230 / 0.680424 (-0.503193) | 0.023661 / 0.534201 (-0.510540) | 0.472367 / 0.579283 (-0.106916) | 0.484614 / 0.434364 (0.050250) | 0.547150 / 0.540337 (0.006813) | 0.843726 / 1.386936 (-0.543210) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#dba64cd381bfe384cb64ab9826f6054a0f1df1ff \"CML watermark\")\n" ]

"2023-08-25T13:12:19Z"

"2023-08-25T16:12:46Z"

"2023-08-25T16:02:24Z"

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[ "_The documentation is not available anymore as the PR was closed or merged._", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006505 / 0.011353 (-0.004847) | 0.003950 / 0.011008 (-0.007058) | 0.084554 / 0.038508 (0.046046) | 0.074376 / 0.023109 (0.051267) | 0.350184 / 0.275898 (0.074286) | 0.380704 / 0.323480 (0.057224) | 0.004011 / 0.007986 (-0.003975) | 0.003890 / 0.004328 (-0.000438) | 0.065483 / 0.004250 (0.061232) | 0.054912 / 0.037052 (0.017860) | 0.359586 / 0.258489 (0.101097) | 0.403360 / 0.293841 (0.109519) | 0.030614 / 0.128546 (-0.097932) | 0.008530 / 0.075646 (-0.067117) | 0.288220 / 0.419271 (-0.131052) | 0.052270 / 0.043533 (0.008737) | 0.352557 / 0.255139 (0.097418) | 0.380509 / 0.283200 (0.097309) | 0.025513 / 0.141683 (-0.116170) | 1.488469 / 1.452155 (0.036315) | 1.559182 / 1.492716 (0.066466) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.266163 / 0.018006 (0.248157) | 0.596345 / 0.000490 (0.595855) | 0.004368 / 0.000200 (0.004168) | 0.000211 / 0.000054 (0.000156) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.027137 / 0.037411 (-0.010274) | 0.082251 / 0.014526 (0.067725) | 0.094745 / 0.176557 (-0.081812) | 0.148756 / 0.737135 (-0.588379) | 0.094580 / 0.296338 (-0.201758) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.383506 / 0.215209 (0.168297) | 3.823147 / 2.077655 (1.745493) | 1.859627 / 1.504120 (0.355507) | 1.687969 / 1.541195 (0.146775) | 1.720786 / 1.468490 (0.252296) | 0.476552 / 4.584777 (-4.108225) | 3.539558 / 3.745712 (-0.206154) | 3.209032 / 5.269862 (-2.060830) | 1.999643 / 4.565676 (-2.566034) | 0.056484 / 0.424275 (-0.367791) | 0.007443 / 0.007607 (-0.000164) | 0.456089 / 0.226044 (0.230044) | 4.562522 / 2.268929 (2.293593) | 2.348286 / 55.444624 (-53.096338) | 1.984323 / 6.876477 (-4.892154) | 2.148988 / 2.142072 (0.006915) | 0.570761 / 4.805227 (-4.234466) | 0.131439 / 6.500664 (-6.369225) | 0.059752 / 0.075469 (-0.015717) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.276803 / 1.841788 (-0.564985) | 19.406812 / 8.074308 (11.332504) | 13.979088 / 10.191392 (3.787696) | 0.157418 / 0.680424 (-0.523006) | 0.018051 / 0.534201 (-0.516150) | 0.392307 / 0.579283 (-0.186976) | 0.406603 / 0.434364 (-0.027760) | 0.458450 / 0.540337 (-0.081888) | 0.622569 / 1.386936 (-0.764367) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006552 / 0.011353 (-0.004800) | 0.004060 / 0.011008 (-0.006948) | 0.063522 / 0.038508 (0.025014) | 0.072537 / 0.023109 (0.049428) | 0.398452 / 0.275898 (0.122554) | 0.422059 / 0.323480 (0.098579) | 0.005577 / 0.007986 (-0.002409) | 0.003413 / 0.004328 (-0.000916) | 0.064095 / 0.004250 (0.059845) | 0.056883 / 0.037052 (0.019831) | 0.407119 / 0.258489 (0.148630) | 0.435889 / 0.293841 (0.142048) | 0.031549 / 0.128546 (-0.096998) | 0.008418 / 0.075646 (-0.067228) | 0.070315 / 0.419271 (-0.348957) | 0.047828 / 0.043533 (0.004295) | 0.398705 / 0.255139 (0.143566) | 0.416986 / 0.283200 (0.133786) | 0.022304 / 0.141683 (-0.119379) | 1.512597 / 1.452155 (0.060442) | 1.570588 / 1.492716 (0.077871) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.295100 / 0.018006 (0.277094) | 0.541883 / 0.000490 (0.541393) | 0.007375 / 0.000200 (0.007175) | 0.000100 / 0.000054 (0.000045) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.030877 / 0.037411 (-0.006534) | 0.090807 / 0.014526 (0.076281) | 0.106155 / 0.176557 (-0.070402) | 0.155546 / 0.737135 (-0.581589) | 0.103847 / 0.296338 (-0.192492) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.441176 / 0.215209 (0.225967) | 4.401025 / 2.077655 (2.323371) | 2.394764 / 1.504120 (0.890644) | 2.226434 / 1.541195 (0.685239) | 2.247248 / 1.468490 (0.778758) | 0.489149 / 4.584777 (-4.095628) | 3.642468 / 3.745712 (-0.103244) | 3.235597 / 5.269862 (-2.034265) | 1.992660 / 4.565676 (-2.573016) | 0.057457 / 0.424275 (-0.366818) | 0.007192 / 0.007607 (-0.000415) | 0.515978 / 0.226044 (0.289934) | 5.147728 / 2.268929 (2.878800) | 2.837394 / 55.444624 (-52.607230) | 2.505753 / 6.876477 (-4.370723) | 2.653090 / 2.142072 (0.511018) | 0.583274 / 4.805227 (-4.221954) | 0.132116 / 6.500664 (-6.368548) | 0.058794 / 0.075469 (-0.016675) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.331630 / 1.841788 (-0.510158) | 20.056890 / 8.074308 (11.982582) | 14.950561 / 10.191392 (4.759169) | 0.165449 / 0.680424 (-0.514975) | 0.020161 / 0.534201 (-0.514040) | 0.395791 / 0.579283 (-0.183492) | 0.415631 / 0.434364 (-0.018733) | 0.474440 / 0.540337 (-0.065898) | 0.643060 / 1.386936 (-0.743876) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#712185ed5e9cb3ff6d6528b4528882d51935f334 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007440 / 0.011353 (-0.003913) | 0.004456 / 0.011008 (-0.006552) | 0.099498 / 0.038508 (0.060990) | 0.077579 / 0.023109 (0.054470) | 0.374934 / 0.275898 (0.099036) | 0.409590 / 0.323480 (0.086110) | 0.005876 / 0.007986 (-0.002110) | 0.003642 / 0.004328 (-0.000687) | 0.076781 / 0.004250 (0.072531) | 0.060185 / 0.037052 (0.023133) | 0.374762 / 0.258489 (0.116273) | 0.445608 / 0.293841 (0.151767) | 0.036557 / 0.128546 (-0.091990) | 0.009941 / 0.075646 (-0.065706) | 0.345214 / 0.419271 (-0.074058) | 0.061912 / 0.043533 (0.018379) | 0.378346 / 0.255139 (0.123207) | 0.415275 / 0.283200 (0.132076) | 0.027396 / 0.141683 (-0.114287) | 1.776602 / 1.452155 (0.324447) | 1.827683 / 1.492716 (0.334967) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.235227 / 0.018006 (0.217221) | 0.491846 / 0.000490 (0.491356) | 0.004987 / 0.000200 (0.004787) | 0.000127 / 0.000054 (0.000073) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.032517 / 0.037411 (-0.004894) | 0.099217 / 0.014526 (0.084691) | 0.109749 / 0.176557 (-0.066807) | 0.176190 / 0.737135 (-0.560946) | 0.109868 / 0.296338 (-0.186471) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.455188 / 0.215209 (0.239979) | 4.560143 / 2.077655 (2.482489) | 2.249928 / 1.504120 (0.745809) | 2.032808 / 1.541195 (0.491614) | 2.090096 / 1.468490 (0.621605) | 0.567813 / 4.584777 (-4.016964) | 4.338299 / 3.745712 (0.592587) | 3.701589 / 5.269862 (-1.568273) | 2.404805 / 4.565676 (-2.160871) | 0.067931 / 0.424275 (-0.356344) | 0.009011 / 0.007607 (0.001404) | 0.542565 / 0.226044 (0.316521) | 5.406578 / 2.268929 (3.137650) | 2.773508 / 55.444624 (-52.671116) | 2.402926 / 6.876477 (-4.473550) | 2.679318 / 2.142072 (0.537246) | 0.683781 / 4.805227 (-4.121446) | 0.155970 / 6.500664 (-6.344694) | 0.070108 / 0.075469 (-0.005361) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.541583 / 1.841788 (-0.300205) | 21.592562 / 8.074308 (13.518254) | 16.426868 / 10.191392 (6.235476) | 0.168618 / 0.680424 (-0.511806) | 0.021560 / 0.534201 (-0.512641) | 0.467062 / 0.579283 (-0.112221) | 0.479968 / 0.434364 (0.045604) | 0.540747 / 0.540337 (0.000410) | 0.775502 / 1.386936 (-0.611434) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008632 / 0.011353 (-0.002721) | 0.004523 / 0.011008 (-0.006485) | 0.075814 / 0.038508 (0.037306) | 0.087096 / 0.023109 (0.063987) | 0.482136 / 0.275898 (0.206238) | 0.529969 / 0.323480 (0.206489) | 0.006882 / 0.007986 (-0.001103) | 0.003720 / 0.004328 (-0.000609) | 0.076232 / 0.004250 (0.071981) | 0.069307 / 0.037052 (0.032254) | 0.491554 / 0.258489 (0.233065) | 0.528989 / 0.293841 (0.235148) | 0.042219 / 0.128546 (-0.086327) | 0.009717 / 0.075646 (-0.065929) | 0.103006 / 0.419271 (-0.316266) | 0.060377 / 0.043533 (0.016844) | 0.484454 / 0.255139 (0.229315) | 0.536072 / 0.283200 (0.252872) | 0.027482 / 0.141683 (-0.114201) | 1.844677 / 1.452155 (0.392522) | 2.001800 / 1.492716 (0.509083) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.252367 / 0.018006 (0.234361) | 0.483601 / 0.000490 (0.483111) | 0.007445 / 0.000200 (0.007245) | 0.000163 / 0.000054 (0.000108) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.036463 / 0.037411 (-0.000948) | 0.108837 / 0.014526 (0.094311) | 0.122256 / 0.176557 (-0.054300) | 0.186455 / 0.737135 (-0.550681) | 0.122270 / 0.296338 (-0.174069) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.506291 / 0.215209 (0.291082) | 5.038044 / 2.077655 (2.960389) | 2.751017 / 1.504120 (1.246897) | 2.553655 / 1.541195 (1.012460) | 2.612724 / 1.468490 (1.144234) | 0.581755 / 4.584777 (-4.003022) | 4.376012 / 3.745712 (0.630300) | 3.749755 / 5.269862 (-1.520107) | 2.394059 / 4.565676 (-2.171618) | 0.068727 / 0.424275 (-0.355548) | 0.008714 / 0.007607 (0.001107) | 0.607371 / 0.226044 (0.381326) | 6.062053 / 2.268929 (3.793125) | 3.278378 / 55.444624 (-52.166247) | 2.866417 / 6.876477 (-4.010060) | 3.056150 / 2.142072 (0.914077) | 0.695090 / 4.805227 (-4.110137) | 0.155274 / 6.500664 (-6.345390) | 0.071106 / 0.075469 (-0.004363) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.584552 / 1.841788 (-0.257236) | 23.092569 / 8.074308 (15.018260) | 17.381905 / 10.191392 (7.190513) | 0.206535 / 0.680424 (-0.473888) | 0.025401 / 0.534201 (-0.508800) | 0.514297 / 0.579283 (-0.064986) | 0.507487 / 0.434364 (0.073123) | 0.566883 / 0.540337 (0.026545) | 0.811074 / 1.386936 (-0.575862) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#5fb01295bff860f09a4c466e745f3840f851efdc \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008400 / 0.011353 (-0.002953) | 0.004872 / 0.011008 (-0.006136) | 0.104434 / 0.038508 (0.065926) | 0.074411 / 0.023109 (0.051302) | 0.395970 / 0.275898 (0.120072) | 0.431661 / 0.323480 (0.108181) | 0.005365 / 0.007986 (-0.002621) | 0.005495 / 0.004328 (0.001167) | 0.081255 / 0.004250 (0.077004) | 0.057141 / 0.037052 (0.020089) | 0.397242 / 0.258489 (0.138753) | 0.456052 / 0.293841 (0.162211) | 0.048362 / 0.128546 (-0.080184) | 0.014077 / 0.075646 (-0.061569) | 0.351128 / 0.419271 (-0.068143) | 0.067842 / 0.043533 (0.024309) | 0.372820 / 0.255139 (0.117681) | 0.407917 / 0.283200 (0.124717) | 0.037707 / 0.141683 (-0.103976) | 1.677136 / 1.452155 (0.224981) | 1.764614 / 1.492716 (0.271897) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.269850 / 0.018006 (0.251844) | 0.601458 / 0.000490 (0.600969) | 0.006500 / 0.000200 (0.006300) | 0.000107 / 0.000054 (0.000053) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.030340 / 0.037411 (-0.007072) | 0.098041 / 0.014526 (0.083515) | 0.107270 / 0.176557 (-0.069287) | 0.173502 / 0.737135 (-0.563633) | 0.113296 / 0.296338 (-0.183043) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.575788 / 0.215209 (0.360579) | 5.723878 / 2.077655 (3.646223) | 2.326339 / 1.504120 (0.822219) | 2.130667 / 1.541195 (0.589472) | 2.080885 / 1.468490 (0.612395) | 0.800936 / 4.584777 (-3.783841) | 5.227888 / 3.745712 (1.482176) | 4.592647 / 5.269862 (-0.677214) | 2.935765 / 4.565676 (-1.629911) | 0.095909 / 0.424275 (-0.328367) | 0.008763 / 0.007607 (0.001156) | 0.697362 / 0.226044 (0.471318) | 6.968105 / 2.268929 (4.699176) | 3.129070 / 55.444624 (-52.315554) | 2.554818 / 6.876477 (-4.321658) | 2.776005 / 2.142072 (0.633933) | 1.017064 / 4.805227 (-3.788163) | 0.211552 / 6.500664 (-6.289112) | 0.072132 / 0.075469 (-0.003338) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.517072 / 1.841788 (-0.324716) | 23.737742 / 8.074308 (15.663433) | 22.236447 / 10.191392 (12.045055) | 0.235408 / 0.680424 (-0.445016) | 0.031889 / 0.534201 (-0.502312) | 0.458997 / 0.579283 (-0.120286) | 0.610513 / 0.434364 (0.176149) | 0.536508 / 0.540337 (-0.003830) | 0.750137 / 1.386936 (-0.636799) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008696 / 0.011353 (-0.002657) | 0.005374 / 0.011008 (-0.005634) | 0.077974 / 0.038508 (0.039466) | 0.083471 / 0.023109 (0.060362) | 0.498890 / 0.275898 (0.222992) | 0.517570 / 0.323480 (0.194090) | 0.006523 / 0.007986 (-0.001462) | 0.004315 / 0.004328 (-0.000013) | 0.082262 / 0.004250 (0.078012) | 0.064828 / 0.037052 (0.027776) | 0.473101 / 0.258489 (0.214612) | 0.534172 / 0.293841 (0.240331) | 0.051884 / 0.128546 (-0.076662) | 0.015191 / 0.075646 (-0.060455) | 0.084307 / 0.419271 (-0.334965) | 0.066050 / 0.043533 (0.022517) | 0.518007 / 0.255139 (0.262868) | 0.511145 / 0.283200 (0.227946) | 0.045302 / 0.141683 (-0.096381) | 1.670973 / 1.452155 (0.218818) | 1.829225 / 1.492716 (0.336509) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.436537 / 0.018006 (0.418531) | 0.608380 / 0.000490 (0.607890) | 0.075211 / 0.000200 (0.075011) | 0.000733 / 0.000054 (0.000679) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.039117 / 0.037411 (0.001706) | 0.103525 / 0.014526 (0.088999) | 0.124413 / 0.176557 (-0.052144) | 0.192352 / 0.737135 (-0.544783) | 0.120379 / 0.296338 (-0.175959) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.673338 / 0.215209 (0.458129) | 6.799435 / 2.077655 (4.721780) | 3.600913 / 1.504120 (2.096793) | 2.881008 / 1.541195 (1.339814) | 2.667154 / 1.468490 (1.198664) | 0.868775 / 4.584777 (-3.716002) | 5.517063 / 3.745712 (1.771351) | 4.646706 / 5.269862 (-0.623156) | 2.914825 / 4.565676 (-1.650852) | 0.098784 / 0.424275 (-0.325491) | 0.011504 / 0.007607 (0.003897) | 0.724233 / 0.226044 (0.498188) | 7.311045 / 2.268929 (5.042117) | 3.685490 / 55.444624 (-51.759135) | 2.892360 / 6.876477 (-3.984117) | 3.253189 / 2.142072 (1.111117) | 0.983065 / 4.805227 (-3.822162) | 0.201097 / 6.500664 (-6.299567) | 0.068020 / 0.075469 (-0.007450) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.793904 / 1.841788 (-0.047884) | 24.451356 / 8.074308 (16.377048) | 21.697191 / 10.191392 (11.505799) | 0.228545 / 0.680424 (-0.451879) | 0.034600 / 0.534201 (-0.499601) | 0.483253 / 0.579283 (-0.096030) | 0.615103 / 0.434364 (0.180739) | 0.564600 / 0.540337 (0.024262) | 0.799688 / 1.386936 (-0.587248) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#74d60213dcbd7c99484c62ce1d3dfd90a1df0770 \"CML watermark\")\n" ]

"2023-08-25T13:10:26Z"

"2023-08-25T16:58:02Z"

"2023-08-25T16:46:22Z"

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[ "https://github.com/huggingface/datasets/issues/5147 may be a solution, by passing in the tokenizer in a fn_kwargs and ignoring it in the fingerprint calculations", "I have a similar issue. I was using a Jupyter Notebook and every time I call the map function it performs tokenization from scratch again although the cache files of last run still exists. \r\n\r\nI ran with 20 processes and now in the cache folder there are two groups of cached results of tokenized dataset:\r\n\r\n```\r\n.rw-r--r-- fad3ew bii_dsc_community 240 MB Sat Aug 26 12:56:46 2023 cache-1982fea76aa54a13_00001_of_00020.arrow\r\n.rw-r--r-- fad3ew bii_dsc_community 240 MB Sat Aug 26 13:02:08 2023 cache-1982fea76aa54a13_00004_of_00020.arrow\r\n.rw-r--r-- fad3ew bii_dsc_community 240 MB Sat Aug 26 12:56:40 2023 cache-1982fea76aa54a13_00005_of_00020.arrow\r\n.rw-r--r-- fad3ew bii_dsc_community 241 MB Sat Aug 26 12:50:59 2023 cache-1982fea76aa54a13_00006_of_00020.arrow\r\n.rw-r--r-- fad3ew bii_dsc_community 240 MB Sat Aug 26 12:57:37 2023 cache-1982fea76aa54a13_00007_of_00020.arrow\r\n.rw-r--r-- fad3ew bii_dsc_community 240 MB Sat Aug 26 12:57:31 2023 cache-1982fea76aa54a13_00008_of_00020.arrow\r\n.rw-r--r-- fad3ew bii_dsc_community 240 MB Sat Aug 26 12:59:47 2023 cache-1982fea76aa54a13_00010_of_00020.arrow\r\n.rw-r--r-- fad3ew bii_dsc_community 241 MB Sat Aug 26 12:59:44 2023 cache-1982fea76aa54a13_00011_of_00020.arrow\r\n.rw-r--r-- fad3ew bii_dsc_community 241 MB Sat Aug 26 12:55:24 2023 cache-1982fea76aa54a13_00012_of_00020.arrow\r\n.rw-r--r-- fad3ew bii_dsc_community 241 MB Sat Aug 26 12:56:21 2023 cache-1982fea76aa54a13_00013_of_00020.arrow\r\n.rw-r--r-- fad3ew bii_dsc_community 240 MB Sat Aug 26 12:57:24 2023 cache-1982fea76aa54a13_00014_of_00020.arrow\r\n.rw-r--r-- fad3ew bii_dsc_community 240 MB Sat Aug 26 13:00:48 2023 cache-1982fea76aa54a13_00015_of_00020.arrow\r\n.rw-r--r-- fad3ew bii_dsc_community 240 MB Sat Aug 26 12:56:56 2023 cache-1982fea76aa54a13_00017_of_00020.arrow\r\n.rw-r--r-- fad3ew bii_dsc_community 240 MB Sat Aug 26 12:56:54 2023 cache-1982fea76aa54a13_00018_of_00020.arrow\r\n.rw-r--r-- fad3ew bii_dsc_community 240 MB Sat Aug 26 12:57:27 2023 cache-1982fea76aa54a13_00019_of_00020.arrow\r\n.rw-r--r-- fad3ew bii_dsc_community 240 MB Wed Aug 23 19:15:40 2023 cache-454431f643cdc5e8_00000_of_00020.arrow\r\n.rw-r--r-- fad3ew bii_dsc_community 240 MB Wed Aug 23 19:16:46 2023 cache-454431f643cdc5e8_00001_of_00020.arrow\r\n.rw-r--r-- fad3ew bii_dsc_community 240 MB Wed Aug 23 19:14:53 2023 cache-454431f643cdc5e8_00002_of_00020.arrow\r\n.rw-r--r-- fad3ew bii_dsc_community 240 MB Wed Aug 23 19:13:10 2023 cache-454431f643cdc5e8_00003_of_00020.arrow\r\n.rw-r--r-- fad3ew bii_dsc_community 240 MB Wed Aug 23 19:13:04 2023 cache-454431f643cdc5e8_00004_of_00020.arrow\r\n.rw-r--r-- fad3ew bii_dsc_community 240 MB Wed Aug 23 19:16:42 2023 cache-454431f643cdc5e8_00005_of_00020.arrow\r\n.rw-r--r-- fad3ew bii_dsc_community 241 MB Wed Aug 23 19:01:29 2023 cache-454431f643cdc5e8_00006_of_00020.arrow\r\n.rw-r--r-- fad3ew bii_dsc_community 240 MB Wed Aug 23 19:16:41 2023 cache-454431f643cdc5e8_00007_of_00020.arrow\r\n.rw-r--r-- fad3ew bii_dsc_community 240 MB Wed Aug 23 19:14:04 2023 cache-454431f643cdc5e8_00008_of_00020.arrow\r\n.rw-r--r-- fad3ew bii_dsc_community 240 MB Wed Aug 23 19:17:41 2023 cache-454431f643cdc5e8_00009_of_00020.arrow\r\n.rw-r--r-- fad3ew bii_dsc_community 240 MB Wed Aug 23 19:17:06 2023 cache-454431f643cdc5e8_00010_of_00020.arrow\r\n.rw-r--r-- fad3ew bii_dsc_community 241 MB Wed Aug 23 19:17:16 2023 cache-454431f643cdc5e8_00011_of_00020.arrow\r\n.rw-r--r-- fad3ew bii_dsc_community 241 MB Wed Aug 23 19:15:13 2023 cache-454431f643cdc5e8_00012_of_00020.arrow\r\n.rw-r--r-- fad3ew bii_dsc_community 241 MB Wed Aug 23 19:16:01 2023 cache-454431f643cdc5e8_00013_of_00020.arrow\r\n.rw-r--r-- fad3ew bii_dsc_community 240 MB Wed Aug 23 19:16:35 2023 cache-454431f643cdc5e8_00014_of_00020.arrow\r\n.rw-r--r-- fad3ew bii_dsc_community 240 MB Wed Aug 23 19:16:20 2023 cache-454431f643cdc5e8_00015_of_00020.arrow\r\n.rw-r--r-- fad3ew bii_dsc_community 240 MB Wed Aug 23 19:14:48 2023 cache-454431f643cdc5e8_00016_of_00020.arrow\r\n.rw-r--r-- fad3ew bii_dsc_community 240 MB Wed Aug 23 18:59:32 2023 cache-454431f643cdc5e8_00017_of_00020.arrow\r\n.rw-r--r-- fad3ew bii_dsc_community 240 MB Wed Aug 23 19:17:58 2023 cache-454431f643cdc5e8_00018_of_00020.arrow\r\n.rw-r--r-- fad3ew bii_dsc_community 240 MB Wed Aug 23 19:15:25 2023 cache-454431f643cdc5e8_00019_of_00020.arrow\r\n```\r\n\r\ncan we specify the cache file for map so that it won't redo everything again?", "@Luosuu [map](https://huggingface.co/docs/datasets/v2.14.4/en/package_reference/main_classes#datasets.Dataset.map) has cache_file_name parameter\r\n\r\nIn my case, I do want the cache to detect when the map function changes, so I can't pass a constant cache file name.", "Implementing a proper hashing function for the (fast) tokenizers is currently impossible for the reasons mentioned in the referenced issues. So the only alternative to the `cache_file_name` (or `new_fingerprint`) parameter is a custom serializer (e.g., that deserializes the tokenizer from a local save path) defined using `copyreg` or a class that wraps the tokenizer object and has `__reduce__`(`__setstate__`/`__getstate__`) " ]

"2023-08-25T12:55:18Z"

"2023-08-31T15:17:24Z"

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[ "This seems to be related to your environment and not the `datasets` code (e.g., this could happen when exposing the Python 3.9 site packages to a lower Python version (interpreter))" ]

"2023-08-25T08:35:14Z"

"2023-08-29T14:57:17Z"

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[ "_The documentation is not available anymore as the PR was closed or merged._", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.005847 / 0.011353 (-0.005506) | 0.003488 / 0.011008 (-0.007521) | 0.079545 / 0.038508 (0.041037) | 0.055114 / 0.023109 (0.032005) | 0.312694 / 0.275898 (0.036796) | 0.338808 / 0.323480 (0.015329) | 0.004573 / 0.007986 (-0.003413) | 0.002818 / 0.004328 (-0.001510) | 0.062102 / 0.004250 (0.057852) | 0.044072 / 0.037052 (0.007019) | 0.317682 / 0.258489 (0.059192) | 0.354139 / 0.293841 (0.060298) | 0.026905 / 0.128546 (-0.101641) | 0.007990 / 0.075646 (-0.067656) | 0.260071 / 0.419271 (-0.159201) | 0.043658 / 0.043533 (0.000125) | 0.313828 / 0.255139 (0.058689) | 0.339678 / 0.283200 (0.056478) | 0.020076 / 0.141683 (-0.121607) | 1.446321 / 1.452155 (-0.005834) | 1.527046 / 1.492716 (0.034330) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.197801 / 0.018006 (0.179795) | 0.432874 / 0.000490 (0.432385) | 0.004093 / 0.000200 (0.003893) | 0.000069 / 0.000054 (0.000014) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.023505 / 0.037411 (-0.013906) | 0.072377 / 0.014526 (0.057852) | 0.081058 / 0.176557 (-0.095498) | 0.141628 / 0.737135 (-0.595507) | 0.081622 / 0.296338 (-0.214716) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.395005 / 0.215209 (0.179795) | 3.949006 / 2.077655 (1.871352) | 1.934028 / 1.504120 (0.429908) | 1.756065 / 1.541195 (0.214871) | 1.778719 / 1.468490 (0.310229) | 0.501279 / 4.584777 (-4.083498) | 3.032120 / 3.745712 (-0.713592) | 2.859751 / 5.269862 (-2.410110) | 1.885924 / 4.565676 (-2.679753) | 0.057236 / 0.424275 (-0.367039) | 0.006704 / 0.007607 (-0.000903) | 0.465794 / 0.226044 (0.239750) | 4.648622 / 2.268929 (2.379694) | 2.345649 / 55.444624 (-53.098975) | 1.981122 / 6.876477 (-4.895355) | 2.148235 / 2.142072 (0.006163) | 0.591466 / 4.805227 (-4.213761) | 0.125262 / 6.500664 (-6.375402) | 0.061305 / 0.075469 (-0.014164) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.243932 / 1.841788 (-0.597856) | 17.912110 / 8.074308 (9.837802) | 13.662097 / 10.191392 (3.470705) | 0.148051 / 0.680424 (-0.532373) | 0.016778 / 0.534201 (-0.517423) | 0.340342 / 0.579283 (-0.238941) | 0.351720 / 0.434364 (-0.082644) | 0.377837 / 0.540337 (-0.162501) | 0.521163 / 1.386936 (-0.865774) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006011 / 0.011353 (-0.005342) | 0.003549 / 0.011008 (-0.007459) | 0.063579 / 0.038508 (0.025071) | 0.056196 / 0.023109 (0.033087) | 0.448879 / 0.275898 (0.172981) | 0.491542 / 0.323480 (0.168062) | 0.004597 / 0.007986 (-0.003389) | 0.002790 / 0.004328 (-0.001539) | 0.063257 / 0.004250 (0.059006) | 0.045653 / 0.037052 (0.008600) | 0.459714 / 0.258489 (0.201225) | 0.491371 / 0.293841 (0.197530) | 0.028124 / 0.128546 (-0.100422) | 0.008016 / 0.075646 (-0.067630) | 0.069418 / 0.419271 (-0.349853) | 0.040393 / 0.043533 (-0.003140) | 0.450978 / 0.255139 (0.195839) | 0.472075 / 0.283200 (0.188875) | 0.020006 / 0.141683 (-0.121677) | 1.451946 / 1.452155 (-0.000209) | 1.513557 / 1.492716 (0.020840) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.225416 / 0.018006 (0.207410) | 0.412287 / 0.000490 (0.411797) | 0.004075 / 0.000200 (0.003875) | 0.000073 / 0.000054 (0.000019) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.025949 / 0.037411 (-0.011463) | 0.080633 / 0.014526 (0.066108) | 0.089960 / 0.176557 (-0.086597) | 0.144530 / 0.737135 (-0.592606) | 0.091427 / 0.296338 (-0.204911) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.462311 / 0.215209 (0.247102) | 4.605063 / 2.077655 (2.527408) | 2.541083 / 1.504120 (1.036963) | 2.356341 / 1.541195 (0.815147) | 2.389824 / 1.468490 (0.921334) | 0.507397 / 4.584777 (-4.077380) | 3.079023 / 3.745712 (-0.666689) | 2.792025 / 5.269862 (-2.477837) | 1.846931 / 4.565676 (-2.718746) | 0.058422 / 0.424275 (-0.365853) | 0.006409 / 0.007607 (-0.001199) | 0.530648 / 0.226044 (0.304604) | 5.321030 / 2.268929 (3.052101) | 2.978335 / 55.444624 (-52.466289) | 2.641188 / 6.876477 (-4.235288) | 2.780450 / 2.142072 (0.638378) | 0.593864 / 4.805227 (-4.211363) | 0.125394 / 6.500664 (-6.375270) | 0.061432 / 0.075469 (-0.014037) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.337142 / 1.841788 (-0.504646) | 18.841575 / 8.074308 (10.767267) | 14.678622 / 10.191392 (4.487230) | 0.144491 / 0.680424 (-0.535933) | 0.018145 / 0.534201 (-0.516056) | 0.339376 / 0.579283 (-0.239907) | 0.339129 / 0.434364 (-0.095235) | 0.394842 / 0.540337 (-0.145495) | 0.547924 / 1.386936 (-0.839012) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#57af0ab30796df59d28bf933e756ffbe5f34db1e \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006478 / 0.011353 (-0.004875) | 0.003845 / 0.011008 (-0.007163) | 0.084179 / 0.038508 (0.045671) | 0.071327 / 0.023109 (0.048217) | 0.315206 / 0.275898 (0.039308) | 0.353477 / 0.323480 (0.029997) | 0.005267 / 0.007986 (-0.002719) | 0.003282 / 0.004328 (-0.001046) | 0.064062 / 0.004250 (0.059811) | 0.051940 / 0.037052 (0.014888) | 0.332004 / 0.258489 (0.073515) | 0.363199 / 0.293841 (0.069358) | 0.030546 / 0.128546 (-0.098000) | 0.008453 / 0.075646 (-0.067193) | 0.287636 / 0.419271 (-0.131636) | 0.051999 / 0.043533 (0.008466) | 0.325220 / 0.255139 (0.070081) | 0.355324 / 0.283200 (0.072125) | 0.023417 / 0.141683 (-0.118266) | 1.473370 / 1.452155 (0.021215) | 1.596903 / 1.492716 (0.104186) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.212645 / 0.018006 (0.194638) | 0.463766 / 0.000490 (0.463276) | 0.002834 / 0.000200 (0.002634) | 0.000079 / 0.000054 (0.000024) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.028424 / 0.037411 (-0.008987) | 0.082188 / 0.014526 (0.067662) | 0.777186 / 0.176557 (0.600629) | 0.218290 / 0.737135 (-0.518845) | 0.099098 / 0.296338 (-0.197240) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.387138 / 0.215209 (0.171929) | 3.845655 / 2.077655 (1.768000) | 1.929812 / 1.504120 (0.425692) | 1.718263 / 1.541195 (0.177069) | 1.760933 / 1.468490 (0.292443) | 0.475171 / 4.584777 (-4.109606) | 3.523366 / 3.745712 (-0.222346) | 3.167322 / 5.269862 (-2.102540) | 1.975164 / 4.565676 (-2.590513) | 0.056106 / 0.424275 (-0.368169) | 0.007448 / 0.007607 (-0.000159) | 0.459824 / 0.226044 (0.233779) | 4.590566 / 2.268929 (2.321638) | 2.377968 / 55.444624 (-53.066656) | 2.034052 / 6.876477 (-4.842425) | 2.224976 / 2.142072 (0.082904) | 0.575901 / 4.805227 (-4.229326) | 0.131546 / 6.500664 (-6.369118) | 0.059266 / 0.075469 (-0.016203) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.254783 / 1.841788 (-0.587005) | 19.497795 / 8.074308 (11.423487) | 13.937672 / 10.191392 (3.746280) | 0.164092 / 0.680424 (-0.516332) | 0.017915 / 0.534201 (-0.516286) | 0.391430 / 0.579283 (-0.187853) | 0.403681 / 0.434364 (-0.030683) | 0.457711 / 0.540337 (-0.082626) | 0.620395 / 1.386936 (-0.766541) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006793 / 0.011353 (-0.004560) | 0.004101 / 0.011008 (-0.006907) | 0.064780 / 0.038508 (0.026272) | 0.071087 / 0.023109 (0.047977) | 0.401963 / 0.275898 (0.126065) | 0.433085 / 0.323480 (0.109605) | 0.005348 / 0.007986 (-0.002638) | 0.003289 / 0.004328 (-0.001039) | 0.065209 / 0.004250 (0.060958) | 0.054202 / 0.037052 (0.017150) | 0.405629 / 0.258489 (0.147140) | 0.440326 / 0.293841 (0.146485) | 0.032283 / 0.128546 (-0.096263) | 0.008510 / 0.075646 (-0.067137) | 0.071144 / 0.419271 (-0.348127) | 0.047414 / 0.043533 (0.003881) | 0.402065 / 0.255139 (0.146926) | 0.421217 / 0.283200 (0.138017) | 0.021924 / 0.141683 (-0.119759) | 1.490067 / 1.452155 (0.037913) | 1.539134 / 1.492716 (0.046417) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.280072 / 0.018006 (0.262066) | 0.456130 / 0.000490 (0.455641) | 0.020926 / 0.000200 (0.020726) | 0.000107 / 0.000054 (0.000053) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.032040 / 0.037411 (-0.005371) | 0.092343 / 0.014526 (0.077817) | 0.104866 / 0.176557 (-0.071690) | 0.156631 / 0.737135 (-0.580505) | 0.107203 / 0.296338 (-0.189136) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.426268 / 0.215209 (0.211059) | 4.255539 / 2.077655 (2.177884) | 2.285077 / 1.504120 (0.780957) | 2.114277 / 1.541195 (0.573083) | 2.159242 / 1.468490 (0.690752) | 0.489421 / 4.584777 (-4.095356) | 3.630797 / 3.745712 (-0.114915) | 3.205238 / 5.269862 (-2.064624) | 1.985846 / 4.565676 (-2.579830) | 0.057436 / 0.424275 (-0.366839) | 0.007154 / 0.007607 (-0.000454) | 0.507294 / 0.226044 (0.281250) | 5.050105 / 2.268929 (2.781176) | 2.750474 / 55.444624 (-52.694151) | 2.404116 / 6.876477 (-4.472360) | 2.576483 / 2.142072 (0.434411) | 0.584909 / 4.805227 (-4.220318) | 0.130695 / 6.500664 (-6.369969) | 0.059743 / 0.075469 (-0.015726) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.352702 / 1.841788 (-0.489086) | 19.687944 / 8.074308 (11.613636) | 14.991847 / 10.191392 (4.800455) | 0.185164 / 0.680424 (-0.495260) | 0.020314 / 0.534201 (-0.513887) | 0.395162 / 0.579283 (-0.184121) | 0.408917 / 0.434364 (-0.025447) | 0.467049 / 0.540337 (-0.073288) | 0.649209 / 1.386936 (-0.737727) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#885518608ceab83b7ed8ceba7a0b72bc68096026 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006142 / 0.011353 (-0.005211) | 0.003621 / 0.011008 (-0.007387) | 0.079880 / 0.038508 (0.041372) | 0.059283 / 0.023109 (0.036173) | 0.310971 / 0.275898 (0.035072) | 0.351620 / 0.323480 (0.028140) | 0.003453 / 0.007986 (-0.004532) | 0.003785 / 0.004328 (-0.000543) | 0.062395 / 0.004250 (0.058145) | 0.047614 / 0.037052 (0.010562) | 0.312688 / 0.258489 (0.054199) | 0.363762 / 0.293841 (0.069921) | 0.027051 / 0.128546 (-0.101495) | 0.007920 / 0.075646 (-0.067726) | 0.261080 / 0.419271 (-0.158192) | 0.044476 / 0.043533 (0.000943) | 0.312615 / 0.255139 (0.057476) | 0.343672 / 0.283200 (0.060472) | 0.022723 / 0.141683 (-0.118960) | 1.441449 / 1.452155 (-0.010706) | 1.509253 / 1.492716 (0.016536) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.193171 / 0.018006 (0.175165) | 0.434771 / 0.000490 (0.434281) | 0.003114 / 0.000200 (0.002914) | 0.000065 / 0.000054 (0.000011) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.024209 / 0.037411 (-0.013203) | 0.073891 / 0.014526 (0.059365) | 0.083497 / 0.176557 (-0.093060) | 0.144962 / 0.737135 (-0.592173) | 0.084594 / 0.296338 (-0.211745) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.392512 / 0.215209 (0.177303) | 3.912692 / 2.077655 (1.835037) | 1.914010 / 1.504120 (0.409890) | 1.743827 / 1.541195 (0.202632) | 1.829244 / 1.468490 (0.360753) | 0.497740 / 4.584777 (-4.087037) | 2.979222 / 3.745712 (-0.766490) | 2.849786 / 5.269862 (-2.420076) | 1.874411 / 4.565676 (-2.691265) | 0.057270 / 0.424275 (-0.367005) | 0.006673 / 0.007607 (-0.000934) | 0.460724 / 0.226044 (0.234679) | 4.600617 / 2.268929 (2.331689) | 2.333178 / 55.444624 (-53.111446) | 1.999902 / 6.876477 (-4.876575) | 2.170600 / 2.142072 (0.028528) | 0.587716 / 4.805227 (-4.217511) | 0.126374 / 6.500664 (-6.374290) | 0.061926 / 0.075469 (-0.013543) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.229767 / 1.841788 (-0.612021) | 18.494462 / 8.074308 (10.420154) | 13.799801 / 10.191392 (3.608409) | 0.137952 / 0.680424 (-0.542472) | 0.017037 / 0.534201 (-0.517164) | 0.333252 / 0.579283 (-0.246031) | 0.357276 / 0.434364 (-0.077088) | 0.380069 / 0.540337 (-0.160268) | 0.526968 / 1.386936 (-0.859968) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006185 / 0.011353 (-0.005168) | 0.003595 / 0.011008 (-0.007413) | 0.063371 / 0.038508 (0.024863) | 0.060461 / 0.023109 (0.037351) | 0.455016 / 0.275898 (0.179118) | 0.490505 / 0.323480 (0.167026) | 0.004738 / 0.007986 (-0.003247) | 0.002852 / 0.004328 (-0.001477) | 0.064161 / 0.004250 (0.059910) | 0.047411 / 0.037052 (0.010359) | 0.453815 / 0.258489 (0.195326) | 0.485354 / 0.293841 (0.191513) | 0.028358 / 0.128546 (-0.100188) | 0.008101 / 0.075646 (-0.067545) | 0.068399 / 0.419271 (-0.350873) | 0.040928 / 0.043533 (-0.002605) | 0.462263 / 0.255139 (0.207124) | 0.478773 / 0.283200 (0.195574) | 0.019787 / 0.141683 (-0.121896) | 1.475798 / 1.452155 (0.023643) | 1.563890 / 1.492716 (0.071174) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.239701 / 0.018006 (0.221695) | 0.417442 / 0.000490 (0.416953) | 0.005895 / 0.000200 (0.005695) | 0.000087 / 0.000054 (0.000033) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.026155 / 0.037411 (-0.011256) | 0.081264 / 0.014526 (0.066738) | 0.089734 / 0.176557 (-0.086822) | 0.143965 / 0.737135 (-0.593171) | 0.092156 / 0.296338 (-0.204182) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.456420 / 0.215209 (0.241211) | 4.545675 / 2.077655 (2.468020) | 2.477141 / 1.504120 (0.973022) | 2.295142 / 1.541195 (0.753947) | 2.349525 / 1.468490 (0.881035) | 0.502485 / 4.584777 (-4.082292) | 3.072347 / 3.745712 (-0.673365) | 2.798565 / 5.269862 (-2.471296) | 1.849030 / 4.565676 (-2.716647) | 0.057789 / 0.424275 (-0.366487) | 0.006436 / 0.007607 (-0.001172) | 0.529648 / 0.226044 (0.303604) | 5.285670 / 2.268929 (3.016741) | 2.954964 / 55.444624 (-52.489660) | 2.593161 / 6.876477 (-4.283316) | 2.735254 / 2.142072 (0.593181) | 0.587635 / 4.805227 (-4.217592) | 0.124732 / 6.500664 (-6.375932) | 0.060999 / 0.075469 (-0.014470) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.354957 / 1.841788 (-0.486831) | 18.803998 / 8.074308 (10.729690) | 14.902712 / 10.191392 (4.711320) | 0.146729 / 0.680424 (-0.533695) | 0.017989 / 0.534201 (-0.516212) | 0.333633 / 0.579283 (-0.245650) | 0.347685 / 0.434364 (-0.086679) | 0.386497 / 0.540337 (-0.153840) | 0.590885 / 1.386936 (-0.796051) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#392d8a46f4da066408785281d9b87760f7273254 \"CML watermark\")\n" ]

"2023-08-24T16:16:09Z"

"2023-08-25T16:30:00Z"

"2023-08-25T16:21:17Z"

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[ "Hi! Can you share the error this reproducer throws in your environment? `streaming=True` streams the dataset as it's iterated over without creating a memory-map file.", "The trace of the error. Streaming works but is slower.\r\n```\r\nRoot Cause (first observed failure):\r\n[0]:\r\n time : 2023-08-24_06:06:01\r\n host : compute-126.cm.cluster\r\n rank : 0 (local_rank: 0)\r\n exitcode : 1 (pid: 48442)\r\n error_file: /tmp/torchelastic_4fqzcuuz/none_rx2470jl/attempt_0/0/error.json\r\n traceback : Traceback (most recent call last):\r\n File \"/users/yli7/.conda/envs/pytorch2.0/lib/python3.8/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py\", line 346, in wrapper\r\n return f(*args, **kwargs)\r\n File \"Pretrain.py\", line 214, in main\r\n pair_dataset, c4_dataset = create_dataset('pretrain', config)\r\n File \"/dcs05/qiao/data/william/project/DaVinci/dataset/__init__.py\", line 109, in create_dataset\r\n c4_dataset = load_dataset(\"c4\", \"en\", split=\"train\").to_iterable_dataset(num_shards=1024).map(pre_caption_huggingface)\r\n File \"/users/yli7/.local/lib/python3.8/site-packages/datasets/load.py\", line 1810, in load_dataset\r\n ds = builder_instance.as_dataset(split=split, verification_mode=verification_mode, in_memory=keep_in_memory)\r\n File \"/users/yli7/.local/lib/python3.8/site-packages/datasets/builder.py\", line 1145, in as_dataset\r\n datasets = map_nested(\r\n File \"/users/yli7/.local/lib/python3.8/site-packages/datasets/utils/py_utils.py\", line 436, in map_nested\r\n return function(data_struct)\r\n File \"/users/yli7/.local/lib/python3.8/site-packages/datasets/builder.py\", line 1175, in _build_single_dataset\r\n ds = self._as_dataset(\r\n File \"/users/yli7/.local/lib/python3.8/site-packages/datasets/builder.py\", line 1246, in _as_dataset\r\n dataset_kwargs = ArrowReader(cache_dir, self.info).read(\r\n File \"/users/yli7/.local/lib/python3.8/site-packages/datasets/arrow_reader.py\", line 244, in read\r\n return self.read_files(files=files, original_instructions=instructions, in_memory=in_memory)\r\n File \"/users/yli7/.local/lib/python3.8/site-packages/datasets/arrow_reader.py\", line 265, in read_files\r\n pa_table = self._read_files(files, in_memory=in_memory)\r\n File \"/users/yli7/.local/lib/python3.8/site-packages/datasets/arrow_reader.py\", line 200, in _read_files\r\n pa_table: Table = self._get_table_from_filename(f_dict, in_memory=in_memory)\r\n File \"/users/yli7/.local/lib/python3.8/site-packages/datasets/arrow_reader.py\", line 336, in _get_table_from_filename\r\n table = ArrowReader.read_table(filename, in_memory=in_memory)\r\n File \"/users/yli7/.local/lib/python3.8/site-packages/datasets/arrow_reader.py\", line 357, in read_table\r\n return table_cls.from_file(filename)\r\n File \"/users/yli7/.local/lib/python3.8/site-packages/datasets/table.py\", line 1059, in from_file\r\n table = _memory_mapped_arrow_table_from_file(filename)\r\n File \"/users/yli7/.local/lib/python3.8/site-packages/datasets/table.py\", line 65, in _memory_mapped_arrow_table_from_file\r\n opened_stream = _memory_mapped_record_batch_reader_from_file(filename)\r\n File \"/users/yli7/.local/lib/python3.8/site-packages/datasets/table.py\", line 50, in _memory_mapped_record_batch_reader_from_file\r\n memory_mapped_stream = pa.memory_map(filename)\r\n File \"pyarrow/io.pxi\", line 1009, in pyarrow.lib.memory_map\r\n File \"pyarrow/io.pxi\", line 956, in pyarrow.lib.MemoryMappedFile._open\r\n File \"pyarrow/error.pxi\", line 144, in pyarrow.lib.pyarrow_internal_check_status\r\n File \"pyarrow/error.pxi\", line 115, in pyarrow.lib.check_status\r\n OSError: Memory mapping file failed: Cannot allocate memory\r\n```", "This issue has previously been reported here: https://github.com/huggingface/datasets/issues/5710. Reporting it in the Arrow repo makes more sense as they have control over memory mapping.\r\n\r\nPS: this is the API to reduce the size of the generated Arrow file:\r\n```python\r\nfrom datasets import load_dataset\r\nbuilder = load_dataset_builder(\"c4\", \"en\")\r\nbuilder.download_and_prepare(max_shard_size=\"5GB\")\r\ndataset = builder.as_dataset()\r\n```\r\n\r\nIf this resolves the issue, we can consider exposing `max_shard_size` in `load_dataset`.", "Thanks for the response. The problem seems not resolved. The memory I allocated to the environment is 64G and the following error still occurs\r\n`Python 3.8.16 (default, Jun 12 2023, 18:09:05) \r\n[GCC 11.2.0] :: Anaconda, Inc. on linux\r\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\r\n>>> from datasets import load_dataset_builder\r\n>>> builder = load_dataset_builder(\"c4\", \"en\")\r\n>>> builder.download_and_prepare(max_shard_size=\"5GB\")\r\nFound cached dataset c4 (/users/yli7/.cache/huggingface/datasets/c4/en/0.0.0/df532b158939272d032cc63ef19cd5b83e9b4d00c922b833e4cb18b2e9869b01)\r\n>>> dataset = builder.as_dataset()\r\n 0%| | 0/2 [00:00<?, ?it/s]Traceback (most recent call last):\r\n File \"<stdin>\", line 1, in <module>\r\n File \"/users/yli7/.local/lib/python3.8/site-packages/datasets/builder.py\", line 1145, in as_dataset\r\n datasets = map_nested(\r\n File \"/users/yli7/.local/lib/python3.8/site-packages/datasets/utils/py_utils.py\", line 444, in map_nested\r\n mapped = [\r\n File \"/users/yli7/.local/lib/python3.8/site-packages/datasets/utils/py_utils.py\", line 445, in <listcomp>\r\n _single_map_nested((function, obj, types, None, True, None))\r\n File \"/users/yli7/.local/lib/python3.8/site-packages/datasets/utils/py_utils.py\", line 347, in _single_map_nested\r\n return function(data_struct)\r\n File \"/users/yli7/.local/lib/python3.8/site-packages/datasets/builder.py\", line 1175, in _build_single_dataset\r\n ds = self._as_dataset(\r\n File \"/users/yli7/.local/lib/python3.8/site-packages/datasets/builder.py\", line 1246, in _as_dataset\r\n dataset_kwargs = ArrowReader(cache_dir, self.info).read(\r\n File \"/users/yli7/.local/lib/python3.8/site-packages/datasets/arrow_reader.py\", line 244, in read\r\n return self.read_files(files=files, original_instructions=instructions, in_memory=in_memory)\r\n File \"/users/yli7/.local/lib/python3.8/site-packages/datasets/arrow_reader.py\", line 265, in read_files\r\n pa_table = self._read_files(files, in_memory=in_memory)\r\n File \"/users/yli7/.local/lib/python3.8/site-packages/datasets/arrow_reader.py\", line 200, in _read_files\r\n pa_table: Table = self._get_table_from_filename(f_dict, in_memory=in_memory)\r\n File \"/users/yli7/.local/lib/python3.8/site-packages/datasets/arrow_reader.py\", line 336, in _get_table_from_filename\r\n table = ArrowReader.read_table(filename, in_memory=in_memory)\r\n File \"/users/yli7/.local/lib/python3.8/site-packages/datasets/arrow_reader.py\", line 357, in read_table\r\n return table_cls.from_file(filename)\r\n File \"/users/yli7/.local/lib/python3.8/site-packages/datasets/table.py\", line 1059, in from_file\r\n table = _memory_mapped_arrow_table_from_file(filename)\r\n File \"/users/yli7/.local/lib/python3.8/site-packages/datasets/table.py\", line 65, in _memory_mapped_arrow_table_from_file\r\n opened_stream = _memory_mapped_record_batch_reader_from_file(filename)\r\n File \"/users/yli7/.local/lib/python3.8/site-packages/datasets/table.py\", line 50, in _memory_mapped_record_batch_reader_from_file\r\n memory_mapped_stream = pa.memory_map(filename)\r\n File \"pyarrow/io.pxi\", line 1009, in pyarrow.lib.memory_map\r\n File \"pyarrow/io.pxi\", line 956, in pyarrow.lib.MemoryMappedFile._open\r\n File \"pyarrow/error.pxi\", line 144, in pyarrow.lib.pyarrow_internal_check_status\r\n File \"pyarrow/error.pxi\", line 115, in pyarrow.lib.check_status\r\nOSError: Memory mapping file failed: Cannot allocate memory`" ]

"2023-08-24T05:33:45Z"

"2023-08-26T05:09:56Z"

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[ "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006095 / 0.011353 (-0.005258) | 0.003580 / 0.011008 (-0.007429) | 0.080146 / 0.038508 (0.041638) | 0.063445 / 0.023109 (0.040336) | 0.321930 / 0.275898 (0.046032) | 0.397933 / 0.323480 (0.074453) | 0.003455 / 0.007986 (-0.004531) | 0.002856 / 0.004328 (-0.001472) | 0.062938 / 0.004250 (0.058687) | 0.048896 / 0.037052 (0.011843) | 0.333070 / 0.258489 (0.074581) | 0.404485 / 0.293841 (0.110644) | 0.027156 / 0.128546 (-0.101390) | 0.007974 / 0.075646 (-0.067672) | 0.261505 / 0.419271 (-0.157766) | 0.045328 / 0.043533 (0.001795) | 0.311203 / 0.255139 (0.056064) | 0.390006 / 0.283200 (0.106806) | 0.023650 / 0.141683 (-0.118033) | 1.468856 / 1.452155 (0.016701) | 1.503867 / 1.492716 (0.011151) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.202110 / 0.018006 (0.184103) | 0.436433 / 0.000490 (0.435944) | 0.002278 / 0.000200 (0.002078) | 0.000070 / 0.000054 (0.000016) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.024575 / 0.037411 (-0.012836) | 0.073005 / 0.014526 (0.058479) | 0.083609 / 0.176557 (-0.092947) | 0.144881 / 0.737135 (-0.592254) | 0.083495 / 0.296338 (-0.212844) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.398911 / 0.215209 (0.183702) | 3.994035 / 2.077655 (1.916381) | 2.056768 / 1.504120 (0.552649) | 1.913242 / 1.541195 (0.372047) | 1.932934 / 1.468490 (0.464444) | 0.498953 / 4.584777 (-4.085824) | 3.031107 / 3.745712 (-0.714605) | 2.817165 / 5.269862 (-2.452696) | 1.858886 / 4.565676 (-2.706790) | 0.056977 / 0.424275 (-0.367299) | 0.006634 / 0.007607 (-0.000973) | 0.472580 / 0.226044 (0.246536) | 4.738301 / 2.268929 (2.469372) | 2.373938 / 55.444624 (-53.070686) | 2.021057 / 6.876477 (-4.855420) | 2.195419 / 2.142072 (0.053346) | 0.585182 / 4.805227 (-4.220045) | 0.124260 / 6.500664 (-6.376405) | 0.060250 / 0.075469 (-0.015219) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.227350 / 1.841788 (-0.614438) | 18.496525 / 8.074308 (10.422216) | 13.946658 / 10.191392 (3.755266) | 0.140024 / 0.680424 (-0.540399) | 0.017077 / 0.534201 (-0.517124) | 0.334415 / 0.579283 (-0.244868) | 0.351118 / 0.434364 (-0.083246) | 0.379556 / 0.540337 (-0.160782) | 0.525064 / 1.386936 (-0.861872) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006176 / 0.011353 (-0.005177) | 0.003648 / 0.011008 (-0.007360) | 0.063461 / 0.038508 (0.024953) | 0.062770 / 0.023109 (0.039660) | 0.448786 / 0.275898 (0.172888) | 0.486490 / 0.323480 (0.163010) | 0.005527 / 0.007986 (-0.002458) | 0.002860 / 0.004328 (-0.001469) | 0.063803 / 0.004250 (0.059553) | 0.049657 / 0.037052 (0.012604) | 0.449625 / 0.258489 (0.191136) | 0.489378 / 0.293841 (0.195537) | 0.028406 / 0.128546 (-0.100140) | 0.008062 / 0.075646 (-0.067584) | 0.068417 / 0.419271 (-0.350854) | 0.040854 / 0.043533 (-0.002678) | 0.461670 / 0.255139 (0.206531) | 0.481622 / 0.283200 (0.198423) | 0.021018 / 0.141683 (-0.120665) | 1.450328 / 1.452155 (-0.001826) | 1.501283 / 1.492716 (0.008567) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.269824 / 0.018006 (0.251817) | 0.412296 / 0.000490 (0.411807) | 0.039582 / 0.000200 (0.039382) | 0.000266 / 0.000054 (0.000211) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.026436 / 0.037411 (-0.010976) | 0.080633 / 0.014526 (0.066107) | 0.089786 / 0.176557 (-0.086770) | 0.145020 / 0.737135 (-0.592115) | 0.092327 / 0.296338 (-0.204012) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.464349 / 0.215209 (0.249140) | 4.630631 / 2.077655 (2.552976) | 2.560527 / 1.504120 (1.056407) | 2.374195 / 1.541195 (0.833000) | 2.424774 / 1.468490 (0.956284) | 0.510428 / 4.584777 (-4.074349) | 3.099805 / 3.745712 (-0.645907) | 2.781096 / 5.269862 (-2.488765) | 1.854276 / 4.565676 (-2.711400) | 0.058102 / 0.424275 (-0.366173) | 0.006365 / 0.007607 (-0.001242) | 0.534082 / 0.226044 (0.308038) | 5.355003 / 2.268929 (3.086074) | 3.012546 / 55.444624 (-52.432078) | 2.665222 / 6.876477 (-4.211255) | 2.821014 / 2.142072 (0.678942) | 0.597733 / 4.805227 (-4.207494) | 0.125433 / 6.500664 (-6.375231) | 0.060802 / 0.075469 (-0.014667) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.345699 / 1.841788 (-0.496088) | 18.836083 / 8.074308 (10.761774) | 14.895458 / 10.191392 (4.704066) | 0.146843 / 0.680424 (-0.533581) | 0.018082 / 0.534201 (-0.516119) | 0.335729 / 0.579283 (-0.243554) | 0.351013 / 0.434364 (-0.083351) | 0.388435 / 0.540337 (-0.151902) | 0.543826 / 1.386936 (-0.843110) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#d0c7e8c4808a1fb6ee7234b4caa25aa9fcfdc88f \"CML watermark\")\n", "_The documentation is not available anymore as the PR was closed or merged._", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006593 / 0.011353 (-0.004760) | 0.004089 / 0.011008 (-0.006919) | 0.084753 / 0.038508 (0.046245) | 0.079899 / 0.023109 (0.056790) | 0.311528 / 0.275898 (0.035630) | 0.349722 / 0.323480 (0.026243) | 0.004288 / 0.007986 (-0.003698) | 0.004552 / 0.004328 (0.000224) | 0.065896 / 0.004250 (0.061646) | 0.053813 / 0.037052 (0.016760) | 0.316958 / 0.258489 (0.058469) | 0.367011 / 0.293841 (0.073170) | 0.031082 / 0.128546 (-0.097464) | 0.008684 / 0.075646 (-0.066963) | 0.288003 / 0.419271 (-0.131268) | 0.052560 / 0.043533 (0.009027) | 0.305589 / 0.255139 (0.050450) | 0.349656 / 0.283200 (0.066457) | 0.023857 / 0.141683 (-0.117826) | 1.462360 / 1.452155 (0.010205) | 1.568170 / 1.492716 (0.075454) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.272342 / 0.018006 (0.254336) | 0.585108 / 0.000490 (0.584618) | 0.003427 / 0.000200 (0.003227) | 0.000078 / 0.000054 (0.000023) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.030347 / 0.037411 (-0.007064) | 0.086325 / 0.014526 (0.071799) | 0.100958 / 0.176557 (-0.075598) | 0.156534 / 0.737135 (-0.580601) | 0.102506 / 0.296338 (-0.193832) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.406625 / 0.215209 (0.191416) | 4.065957 / 2.077655 (1.988302) | 2.075867 / 1.504120 (0.571747) | 1.914390 / 1.541195 (0.373196) | 2.013321 / 1.468490 (0.544831) | 0.486832 / 4.584777 (-4.097945) | 3.545940 / 3.745712 (-0.199772) | 3.323226 / 5.269862 (-1.946635) | 2.067742 / 4.565676 (-2.497934) | 0.057884 / 0.424275 (-0.366391) | 0.007751 / 0.007607 (0.000144) | 0.484923 / 0.226044 (0.258878) | 4.844885 / 2.268929 (2.575956) | 2.569828 / 55.444624 (-52.874796) | 2.224058 / 6.876477 (-4.652419) | 2.485587 / 2.142072 (0.343515) | 0.584311 / 4.805227 (-4.220916) | 0.134984 / 6.500664 (-6.365680) | 0.062164 / 0.075469 (-0.013305) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.247182 / 1.841788 (-0.594605) | 20.107500 / 8.074308 (12.033192) | 14.194444 / 10.191392 (4.003052) | 0.147134 / 0.680424 (-0.533290) | 0.018062 / 0.534201 (-0.516138) | 0.392029 / 0.579283 (-0.187254) | 0.402991 / 0.434364 (-0.031373) | 0.457600 / 0.540337 (-0.082737) | 0.632553 / 1.386936 (-0.754383) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006920 / 0.011353 (-0.004433) | 0.004257 / 0.011008 (-0.006751) | 0.065233 / 0.038508 (0.026725) | 0.078151 / 0.023109 (0.055042) | 0.389141 / 0.275898 (0.113243) | 0.431518 / 0.323480 (0.108038) | 0.005752 / 0.007986 (-0.002234) | 0.003584 / 0.004328 (-0.000745) | 0.065173 / 0.004250 (0.060922) | 0.059113 / 0.037052 (0.022060) | 0.398225 / 0.258489 (0.139736) | 0.430980 / 0.293841 (0.137139) | 0.032802 / 0.128546 (-0.095744) | 0.008702 / 0.075646 (-0.066945) | 0.071345 / 0.419271 (-0.347926) | 0.048269 / 0.043533 (0.004736) | 0.389264 / 0.255139 (0.134125) | 0.416008 / 0.283200 (0.132809) | 0.024845 / 0.141683 (-0.116838) | 1.499100 / 1.452155 (0.046945) | 1.576397 / 1.492716 (0.083681) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.296674 / 0.018006 (0.278668) | 0.540108 / 0.000490 (0.539619) | 0.004293 / 0.000200 (0.004093) | 0.000151 / 0.000054 (0.000096) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.034108 / 0.037411 (-0.003303) | 0.092747 / 0.014526 (0.078221) | 0.112203 / 0.176557 (-0.064354) | 0.162728 / 0.737135 (-0.574407) | 0.109955 / 0.296338 (-0.186383) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.432006 / 0.215209 (0.216797) | 4.297591 / 2.077655 (2.219937) | 2.379645 / 1.504120 (0.875525) | 2.218680 / 1.541195 (0.677485) | 2.314608 / 1.468490 (0.846117) | 0.495562 / 4.584777 (-4.089215) | 3.589787 / 3.745712 (-0.155925) | 3.349593 / 5.269862 (-1.920268) | 2.119893 / 4.565676 (-2.445783) | 0.057976 / 0.424275 (-0.366299) | 0.007612 / 0.007607 (0.000005) | 0.509422 / 0.226044 (0.283378) | 5.101444 / 2.268929 (2.832515) | 2.794532 / 55.444624 (-52.650092) | 2.459033 / 6.876477 (-4.417444) | 2.714424 / 2.142072 (0.572352) | 0.588444 / 4.805227 (-4.216784) | 0.135763 / 6.500664 (-6.364901) | 0.062593 / 0.075469 (-0.012876) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.361415 / 1.841788 (-0.480372) | 20.940684 / 8.074308 (12.866376) | 15.161364 / 10.191392 (4.969972) | 0.154243 / 0.680424 (-0.526181) | 0.020305 / 0.534201 (-0.513896) | 0.397438 / 0.579283 (-0.181845) | 0.415047 / 0.434364 (-0.019317) | 0.473250 / 0.540337 (-0.067088) | 0.740681 / 1.386936 (-0.646255) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#6e84937af4f24194bf61f09244ebef6528fb7c4c \"CML watermark\")\n" ]

"2023-08-23T15:45:53Z"

"2023-08-25T13:15:59Z"

"2023-08-25T13:06:52Z"

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"2023-08-23T14:11:20Z"

"2023-08-25T13:06:53Z"

"2023-08-25T13:06:53Z"

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[ { "color": "a2eeef", "default": true, "description": "New feature or request", "id": 1935892871, "name": "enhancement", "node_id": "MDU6TGFiZWwxOTM1ODkyODcx", "url": "https://api.github.com/repos/huggingface/datasets/labels/enhancement" } ]

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[ "Hi! The streaming mode also retries requests - `datasets.config.STREAMING_READ_MAX_RETRIES` (20 sec by default) controls the number of retries and `datasets.config.STREAMING_READ_RETRY_INTERVAL` (5 sec) the sleep time between retries.\r\n\r\n> At step 1800 I got a 504 HTTP status code error from Huggingface hub for my pytorch dataloader\r\n\r\nA minor Hub outage that we experienced yesterday could be the cause.", "I wanted something similar. I have a huge dataset I want to process (laion-2b), but after processing several batches, it sometimes fails with this error: `HTTP 502 Bad Gateway for url`. I had the following code to handle it but this way I believe it restarts processing the data from the first batch? How can I set the attribute values you mention above?\r\n\r\n```\r\niterable_dataset = load_dataset(\"laion/laion2B-multi\", streaming=True, split='train')\r\ndataloader = DataLoader(iterable_dataset, batch_size=131072, collate_fn=custom_collate_fn, num_workers=8)\r\n\r\nMAX_RETRIES = 5\r\nRETRY_WAIT = 10 # wait 10 seconds before retry\r\n\r\n for retry in range(MAX_RETRIES):\r\n try:\r\n for j, batch in enumerate(dataloader):\r\n < process batch>\r\n\r\n except HfHubHTTPError as e:\r\n if \"502\" in str(e) and retry < MAX_RETRIES - 1:\r\n logging.warning(f\"Encountered a 502 error on batch {j}. Waiting for {RETRY_WAIT} seconds before retrying.\")\r\n time.sleep(RETRY_WAIT)\r\n continue\r\n else:\r\n raise" ]

"2023-08-23T13:15:38Z"

"2023-09-10T20:22:15Z"

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6171). All of your documentation changes will be reflected on that endpoint.", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.009315 / 0.011353 (-0.002038) | 0.004931 / 0.011008 (-0.006077) | 0.100534 / 0.038508 (0.062026) | 0.089270 / 0.023109 (0.066161) | 0.394995 / 0.275898 (0.119097) | 0.440244 / 0.323480 (0.116764) | 0.006026 / 0.007986 (-0.001959) | 0.004252 / 0.004328 (-0.000077) | 0.078828 / 0.004250 (0.074577) | 0.066770 / 0.037052 (0.029718) | 0.411152 / 0.258489 (0.152663) | 0.445616 / 0.293841 (0.151775) | 0.048344 / 0.128546 (-0.080203) | 0.013700 / 0.075646 (-0.061946) | 0.361205 / 0.419271 (-0.058066) | 0.072085 / 0.043533 (0.028552) | 0.399173 / 0.255139 (0.144034) | 0.439334 / 0.283200 (0.156134) | 0.035815 / 0.141683 (-0.105868) | 1.779023 / 1.452155 (0.326868) | 1.865099 / 1.492716 (0.372383) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.275978 / 0.018006 (0.257972) | 0.588850 / 0.000490 (0.588360) | 0.004953 / 0.000200 (0.004754) | 0.000109 / 0.000054 (0.000055) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.031329 / 0.037411 (-0.006082) | 0.095435 / 0.014526 (0.080910) | 0.111182 / 0.176557 (-0.065375) | 0.177692 / 0.737135 (-0.559444) | 0.113345 / 0.296338 (-0.182993) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.577882 / 0.215209 (0.362673) | 5.865872 / 2.077655 (3.788217) | 2.664218 / 1.504120 (1.160098) | 2.383354 / 1.541195 (0.842159) | 2.336821 / 1.468490 (0.868331) | 0.834585 / 4.584777 (-3.750192) | 5.418720 / 3.745712 (1.673008) | 4.551790 / 5.269862 (-0.718072) | 2.921874 / 4.565676 (-1.643803) | 0.095738 / 0.424275 (-0.328537) | 0.009625 / 0.007607 (0.002018) | 0.688317 / 0.226044 (0.462273) | 6.831826 / 2.268929 (4.562897) | 3.482607 / 55.444624 (-51.962017) | 2.633482 / 6.876477 (-4.242995) | 2.878786 / 2.142072 (0.736714) | 0.971615 / 4.805227 (-3.833613) | 0.208661 / 6.500664 (-6.292003) | 0.080271 / 0.075469 (0.004802) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.661193 / 1.841788 (-0.180594) | 24.223041 / 8.074308 (16.148733) | 21.621791 / 10.191392 (11.430399) | 0.243809 / 0.680424 (-0.436614) | 0.031630 / 0.534201 (-0.502571) | 0.501408 / 0.579283 (-0.077875) | 0.600002 / 0.434364 (0.165638) | 0.572066 / 0.540337 (0.031728) | 0.791992 / 1.386936 (-0.594944) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.009410 / 0.011353 (-0.001943) | 0.005255 / 0.011008 (-0.005753) | 0.079202 / 0.038508 (0.040693) | 0.078973 / 0.023109 (0.055863) | 0.557416 / 0.275898 (0.281518) | 0.560417 / 0.323480 (0.236937) | 0.007066 / 0.007986 (-0.000920) | 0.004560 / 0.004328 (0.000232) | 0.080359 / 0.004250 (0.076109) | 0.060071 / 0.037052 (0.023019) | 0.538441 / 0.258489 (0.279952) | 0.592486 / 0.293841 (0.298645) | 0.053221 / 0.128546 (-0.075325) | 0.014056 / 0.075646 (-0.061591) | 0.094084 / 0.419271 (-0.325188) | 0.066721 / 0.043533 (0.023188) | 0.521873 / 0.255139 (0.266734) | 0.579637 / 0.283200 (0.296437) | 0.041476 / 0.141683 (-0.100206) | 1.829681 / 1.452155 (0.377527) | 1.948418 / 1.492716 (0.455702) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.347594 / 0.018006 (0.329588) | 0.606906 / 0.000490 (0.606417) | 0.035413 / 0.000200 (0.035213) | 0.000371 / 0.000054 (0.000317) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.031987 / 0.037411 (-0.005425) | 0.096985 / 0.014526 (0.082459) | 0.109275 / 0.176557 (-0.067282) | 0.175340 / 0.737135 (-0.561795) | 0.110763 / 0.296338 (-0.185575) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.634823 / 0.215209 (0.419614) | 6.527172 / 2.077655 (4.449517) | 3.135709 / 1.504120 (1.631589) | 2.634357 / 1.541195 (1.093162) | 2.670583 / 1.468490 (1.202093) | 0.888686 / 4.584777 (-3.696091) | 5.382289 / 3.745712 (1.636577) | 4.701189 / 5.269862 (-0.568673) | 3.161290 / 4.565676 (-1.404386) | 0.112414 / 0.424275 (-0.311861) | 0.009443 / 0.007607 (0.001836) | 0.774703 / 0.226044 (0.548658) | 7.905334 / 2.268929 (5.636405) | 3.689548 / 55.444624 (-51.755076) | 3.087263 / 6.876477 (-3.789214) | 3.366568 / 2.142072 (1.224496) | 1.185951 / 4.805227 (-3.619277) | 0.248638 / 6.500664 (-6.252026) | 0.104598 / 0.075469 (0.029129) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.820667 / 1.841788 (-0.021120) | 24.536703 / 8.074308 (16.462395) | 23.083964 / 10.191392 (12.892572) | 0.252897 / 0.680424 (-0.427527) | 0.032954 / 0.534201 (-0.501247) | 0.482467 / 0.579283 (-0.096816) | 0.602247 / 0.434364 (0.167883) | 0.600563 / 0.540337 (0.060225) | 0.824013 / 1.386936 (-0.562923) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#c07a54ed4d570c5842d7bbe467025805be16ef51 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.009242 / 0.011353 (-0.002111) | 0.005244 / 0.011008 (-0.005764) | 0.112678 / 0.038508 (0.074170) | 0.089176 / 0.023109 (0.066067) | 0.405823 / 0.275898 (0.129925) | 0.465703 / 0.323480 (0.142223) | 0.005227 / 0.007986 (-0.002758) | 0.004296 / 0.004328 (-0.000032) | 0.082961 / 0.004250 (0.078711) | 0.063144 / 0.037052 (0.026092) | 0.422369 / 0.258489 (0.163880) | 0.478185 / 0.293841 (0.184344) | 0.049770 / 0.128546 (-0.078776) | 0.016561 / 0.075646 (-0.059086) | 0.380172 / 0.419271 (-0.039100) | 0.068698 / 0.043533 (0.025165) | 0.397773 / 0.255139 (0.142634) | 0.461284 / 0.283200 (0.178084) | 0.036907 / 0.141683 (-0.104775) | 1.828017 / 1.452155 (0.375862) | 2.028385 / 1.492716 (0.535669) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.291245 / 0.018006 (0.273239) | 0.605519 / 0.000490 (0.605030) | 0.003790 / 0.000200 (0.003590) | 0.000094 / 0.000054 (0.000040) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.029269 / 0.037411 (-0.008142) | 0.087014 / 0.014526 (0.072488) | 0.116984 / 0.176557 (-0.059573) | 0.170644 / 0.737135 (-0.566491) | 0.109011 / 0.296338 (-0.187328) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.603045 / 0.215209 (0.387836) | 6.125308 / 2.077655 (4.047653) | 2.637127 / 1.504120 (1.133007) | 2.468636 / 1.541195 (0.927441) | 2.383773 / 1.468490 (0.915283) | 0.838139 / 4.584777 (-3.746638) | 5.355777 / 3.745712 (1.610065) | 4.753015 / 5.269862 (-0.516846) | 3.097486 / 4.565676 (-1.468191) | 0.094749 / 0.424275 (-0.329526) | 0.009040 / 0.007607 (0.001433) | 0.699987 / 0.226044 (0.473942) | 7.111671 / 2.268929 (4.842742) | 3.297798 / 55.444624 (-52.146827) | 2.614578 / 6.876477 (-4.261898) | 2.927717 / 2.142072 (0.785645) | 1.037292 / 4.805227 (-3.767935) | 0.218025 / 6.500664 (-6.282639) | 0.086306 / 0.075469 (0.010836) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.645146 / 1.841788 (-0.196642) | 24.191875 / 8.074308 (16.117567) | 21.844371 / 10.191392 (11.652979) | 0.245369 / 0.680424 (-0.435055) | 0.031776 / 0.534201 (-0.502425) | 0.465634 / 0.579283 (-0.113649) | 0.565498 / 0.434364 (0.131134) | 0.497409 / 0.540337 (-0.042929) | 0.748048 / 1.386936 (-0.638889) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.009239 / 0.011353 (-0.002114) | 0.005345 / 0.011008 (-0.005663) | 0.072732 / 0.038508 (0.034224) | 0.099880 / 0.023109 (0.076770) | 0.466933 / 0.275898 (0.191035) | 0.471730 / 0.323480 (0.148250) | 0.006164 / 0.007986 (-0.001821) | 0.004486 / 0.004328 (0.000158) | 0.075475 / 0.004250 (0.071224) | 0.068291 / 0.037052 (0.031238) | 0.465925 / 0.258489 (0.207436) | 0.469198 / 0.293841 (0.175357) | 0.047304 / 0.128546 (-0.081242) | 0.013368 / 0.075646 (-0.062278) | 0.083563 / 0.419271 (-0.335708) | 0.063204 / 0.043533 (0.019671) | 0.457422 / 0.255139 (0.202283) | 0.478793 / 0.283200 (0.195593) | 0.036120 / 0.141683 (-0.105563) | 1.841209 / 1.452155 (0.389054) | 1.955984 / 1.492716 (0.463267) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.369160 / 0.018006 (0.351154) | 0.607140 / 0.000490 (0.606650) | 0.047253 / 0.000200 (0.047054) | 0.000475 / 0.000054 (0.000420) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.040226 / 0.037411 (0.002815) | 0.107361 / 0.014526 (0.092835) | 0.122424 / 0.176557 (-0.054133) | 0.186447 / 0.737135 (-0.550688) | 0.127060 / 0.296338 (-0.169279) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.706737 / 0.215209 (0.491528) | 6.791287 / 2.077655 (4.713632) | 3.194471 / 1.504120 (1.690352) | 2.928145 / 1.541195 (1.386950) | 2.829078 / 1.468490 (1.360588) | 0.929797 / 4.584777 (-3.654980) | 5.484638 / 3.745712 (1.738926) | 4.841570 / 5.269862 (-0.428292) | 2.995247 / 4.565676 (-1.570430) | 0.104709 / 0.424275 (-0.319566) | 0.009543 / 0.007607 (0.001936) | 0.817605 / 0.226044 (0.591561) | 7.879234 / 2.268929 (5.610305) | 3.838073 / 55.444624 (-51.606551) | 3.189728 / 6.876477 (-3.686749) | 3.483775 / 2.142072 (1.341703) | 1.092823 / 4.805227 (-3.712404) | 0.227660 / 6.500664 (-6.273004) | 0.082452 / 0.075469 (0.006983) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.750413 / 1.841788 (-0.091374) | 27.078082 / 8.074308 (19.003774) | 23.968038 / 10.191392 (13.776646) | 0.248065 / 0.680424 (-0.432359) | 0.029961 / 0.534201 (-0.504240) | 0.508630 / 0.579283 (-0.070653) | 0.608707 / 0.434364 (0.174343) | 0.611062 / 0.540337 (0.070725) | 0.830797 / 1.386936 (-0.556139) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#9d793220dd8cbaa099a3928c2132c94c9f7453bc \"CML watermark\")\n" ]

"2023-08-23T09:21:11Z"

"2023-08-23T09:32:59Z"

"2023-08-23T09:21:19Z"

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[ "Your change adds a new element in the key used to avoid duplicates when generating the examples of a dataset. I don't think it fixes the issue you're trying to solve." ]

"2023-08-23T07:08:17Z"

"2023-08-29T12:41:05Z"

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[ "Unfortunately, I cannot reproduce this behavior on my machine or Colab - the reproducer returns `['main_data', 'additional_data']` as expected.", "Thank you for looking into this, Mario. Is this on [my repository](https://huggingface.co/datasets/tsor13/test), or on another one that you have reproduced? Would you mind pointing me to it if so?", "Whoa, in colab I received the correct behavior using my dataset. It must have something to do with my local copy of `datasets` (which again just failed).\r\n\r\nI've tried uninstalling/reinstnalling to no avail", "hi @tsor13 , I haven't been able to reproduce your issue on `tsor13/test` dataset locally either. reinstalling doesn't help?" ]

"2023-08-23T00:13:22Z"

"2023-08-23T15:35:31Z"

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6168). All of your documentation changes will be reflected on that endpoint.", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.009350 / 0.011353 (-0.002003) | 0.005658 / 0.011008 (-0.005350) | 0.123173 / 0.038508 (0.084664) | 0.096354 / 0.023109 (0.073244) | 0.464398 / 0.275898 (0.188500) | 0.544455 / 0.323480 (0.220975) | 0.007337 / 0.007986 (-0.000648) | 0.004424 / 0.004328 (0.000096) | 0.089715 / 0.004250 (0.085465) | 0.072462 / 0.037052 (0.035410) | 0.460601 / 0.258489 (0.202112) | 0.544384 / 0.293841 (0.250543) | 0.052994 / 0.128546 (-0.075552) | 0.014459 / 0.075646 (-0.061187) | 0.464368 / 0.419271 (0.045096) | 0.072889 / 0.043533 (0.029356) | 0.471387 / 0.255139 (0.216248) | 0.560982 / 0.283200 (0.277783) | 0.041398 / 0.141683 (-0.100285) | 1.964688 / 1.452155 (0.512533) | 2.240727 / 1.492716 (0.748011) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.308524 / 0.018006 (0.290518) | 0.669306 / 0.000490 (0.668816) | 0.006644 / 0.000200 (0.006444) | 0.000108 / 0.000054 (0.000053) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.037395 / 0.037411 (-0.000016) | 0.111303 / 0.014526 (0.096777) | 0.158988 / 0.176557 (-0.017569) | 0.236155 / 0.737135 (-0.500980) | 0.134775 / 0.296338 (-0.161564) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.648830 / 0.215209 (0.433621) | 6.614794 / 2.077655 (4.537139) | 2.867526 / 1.504120 (1.363407) | 2.472967 / 1.541195 (0.931772) | 2.488419 / 1.468490 (1.019929) | 0.915785 / 4.584777 (-3.668992) | 6.010754 / 3.745712 (2.265042) | 5.468873 / 5.269862 (0.199011) | 3.446535 / 4.565676 (-1.119141) | 0.118592 / 0.424275 (-0.305684) | 0.012005 / 0.007607 (0.004398) | 0.808467 / 0.226044 (0.582423) | 8.152122 / 2.268929 (5.883193) | 3.751282 / 55.444624 (-51.693342) | 3.009569 / 6.876477 (-3.866908) | 3.282613 / 2.142072 (1.140540) | 1.152727 / 4.805227 (-3.652500) | 0.240224 / 6.500664 (-6.260440) | 0.097871 / 0.075469 (0.022402) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.824944 / 1.841788 (-0.016843) | 27.840842 / 8.074308 (19.766533) | 24.368669 / 10.191392 (14.177277) | 0.260621 / 0.680424 (-0.419803) | 0.033730 / 0.534201 (-0.500471) | 0.552494 / 0.579283 (-0.026789) | 0.666921 / 0.434364 (0.232557) | 0.648812 / 0.540337 (0.108475) | 0.912602 / 1.386936 (-0.474334) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.011688 / 0.011353 (0.000335) | 0.005794 / 0.011008 (-0.005215) | 0.093466 / 0.038508 (0.054958) | 0.102583 / 0.023109 (0.079474) | 0.593572 / 0.275898 (0.317674) | 0.614351 / 0.323480 (0.290871) | 0.007006 / 0.007986 (-0.000980) | 0.005557 / 0.004328 (0.001229) | 0.087779 / 0.004250 (0.083529) | 0.072639 / 0.037052 (0.035586) | 0.577464 / 0.258489 (0.318975) | 0.628240 / 0.293841 (0.334399) | 0.053876 / 0.128546 (-0.074670) | 0.015383 / 0.075646 (-0.060263) | 0.110633 / 0.419271 (-0.308639) | 0.067467 / 0.043533 (0.023934) | 0.613457 / 0.255139 (0.358318) | 0.604939 / 0.283200 (0.321739) | 0.041738 / 0.141683 (-0.099945) | 1.967167 / 1.452155 (0.515012) | 2.121009 / 1.492716 (0.628293) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.449937 / 0.018006 (0.431930) | 0.694410 / 0.000490 (0.693921) | 0.064051 / 0.000200 (0.063851) | 0.000810 / 0.000054 (0.000756) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.045138 / 0.037411 (0.007727) | 0.116831 / 0.014526 (0.102306) | 0.131906 / 0.176557 (-0.044651) | 0.202421 / 0.737135 (-0.534714) | 0.132568 / 0.296338 (-0.163770) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.698046 / 0.215209 (0.482837) | 7.112591 / 2.077655 (5.034936) | 3.332679 / 1.504120 (1.828559) | 2.946384 / 1.541195 (1.405189) | 3.074484 / 1.468490 (1.605994) | 0.970917 / 4.584777 (-3.613859) | 6.143506 / 3.745712 (2.397794) | 5.572496 / 5.269862 (0.302634) | 3.602673 / 4.565676 (-0.963004) | 0.115068 / 0.424275 (-0.309207) | 0.009971 / 0.007607 (0.002364) | 0.891090 / 0.226044 (0.665046) | 8.761788 / 2.268929 (6.492859) | 4.362685 / 55.444624 (-51.081939) | 3.612893 / 6.876477 (-3.263583) | 3.797948 / 2.142072 (1.655876) | 1.202890 / 4.805227 (-3.602337) | 0.238120 / 6.500664 (-6.262544) | 0.095612 / 0.075469 (0.020143) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.958880 / 1.841788 (0.117092) | 28.216454 / 8.074308 (20.142146) | 25.361424 / 10.191392 (15.170032) | 0.308203 / 0.680424 (-0.372221) | 0.032903 / 0.534201 (-0.501298) | 0.539714 / 0.579283 (-0.039569) | 0.688278 / 0.434364 (0.253914) | 0.644818 / 0.540337 (0.104481) | 0.905694 / 1.386936 (-0.481242) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#a5289345e5b23548fee680a0bbc047c0b9a5ee8c \"CML watermark\")\n", "Maybe convert all the tuples by default instead of hardcoding a logic specific to ArrayXD ?" ]

"2023-08-22T17:02:54Z"