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serhii-korobchenko

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6639). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update." ]

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[ "Looks like it works with latest datasets repository\r\n```\r\n- `datasets` version: 2.16.2.dev0\r\n- Platform: Linux-5.15.0-92-generic-x86_64-with-glibc2.29\r\n- Python version: 3.8.10\r\n- `huggingface_hub` version: 0.20.3\r\n- PyArrow version: 15.0.0\r\n- Pandas version: 2.0.1\r\n- `fsspec` version: 2023.10.0\r\n```\r\n\r\nCould you explain which is the minimum version that fixes this?\r\nEdit: Looks like that's 2.16.0, will close out issue" ]

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6636). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "Thanks @mariosasko, I made the changes. However, I did some tests with `map` and I still saw that it took ~3.5 minutes per batch on 6000 features when using `dataset.map(lambda x: x, batched=True)`. From the profile, the culprits were mainly with `ArrowWriter.write_batch` and `ArrowWriter._build_writer`. The slow down from `_build_writer` is due to updating existing features with the inferred ones. I don't think this can be optimized any further, but fortunately, I can avoid this by setting the `features` in `map`. On the other hand, `write_batch` selects cols based on intersection and difference between schema names and example keys using two for loops. The same exists in `ArrowWriter.write_examples_on_file`. Optimizing the column selection using set operations effectively brings it from 3.5 minutes per batch down to 6 seconds per batch. Can we add these changes along with this PR?" ]

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6635). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update." ]

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6634). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "@huggingface/datasets, feel free to review this PR so that it can be included in the next release." ]

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6633). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "<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) | 0.005172 / 0.011353 (-0.006181) | 0.003694 / 0.011008 (-0.007314) | 0.063098 / 0.038508 (0.024590) | 0.028161 / 0.023109 (0.005052) | 0.262288 / 0.275898 (-0.013610) | 0.281867 / 0.323480 (-0.041613) | 0.004088 / 0.007986 (-0.003898) | 0.002745 / 0.004328 (-0.001583) | 0.049071 / 0.004250 (0.044820) | 0.040629 / 0.037052 (0.003577) | 0.282766 / 0.258489 (0.024277) | 0.297998 / 0.293841 (0.004157) | 0.028057 / 0.128546 (-0.100489) | 0.010878 / 0.075646 (-0.064768) | 0.207410 / 0.419271 (-0.211861) | 0.035600 / 0.043533 (-0.007933) | 0.260157 / 0.255139 (0.005018) | 0.273252 / 0.283200 (-0.009948) | 0.017403 / 0.141683 (-0.124280) | 1.150798 / 1.452155 (-0.301356) | 1.200485 / 1.492716 (-0.292231) |\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) | 0.093783 / 0.018006 (0.075777) | 0.302112 / 0.000490 (0.301622) | 0.000225 / 0.000200 (0.000025) | 0.000043 / 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) | 0.018254 / 0.037411 (-0.019158) | 0.061083 / 0.014526 (0.046557) | 0.074899 / 0.176557 (-0.101657) | 0.119616 / 0.737135 (-0.617520) | 0.075269 / 0.296338 (-0.221069) |\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) | 0.275878 / 0.215209 (0.060669) | 2.694778 / 2.077655 (0.617123) | 1.423810 / 1.504120 (-0.080310) | 1.309444 / 1.541195 (-0.231750) | 1.327898 / 1.468490 (-0.140592) | 0.568621 / 4.584777 (-4.016155) | 2.345849 / 3.745712 (-1.399863) | 2.901281 / 5.269862 (-2.368580) | 1.777959 / 4.565676 (-2.787717) | 0.063539 / 0.424275 (-0.360736) | 0.005011 / 0.007607 (-0.002596) | 0.331212 / 0.226044 (0.105168) | 3.200379 / 2.268929 (0.931451) | 1.780766 / 55.444624 (-53.663859) | 1.517178 / 6.876477 (-5.359299) | 1.587307 / 2.142072 (-0.554765) | 0.651939 / 4.805227 (-4.153288) | 0.116646 / 6.500664 (-6.384018) | 0.043325 / 0.075469 (-0.032144) |\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) | 0.996894 / 1.841788 (-0.844894) | 11.495397 / 8.074308 (3.421089) | 10.255784 / 10.191392 (0.064392) | 0.129006 / 0.680424 (-0.551418) | 0.013967 / 0.534201 (-0.520234) | 0.284847 / 0.579283 (-0.294436) | 0.265610 / 0.434364 (-0.168754) | 0.320176 / 0.540337 (-0.220162) | 0.429526 / 1.386936 (-0.957410) |\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) | 0.005582 / 0.011353 (-0.005771) | 0.003867 / 0.011008 (-0.007142) | 0.050416 / 0.038508 (0.011908) | 0.030996 / 0.023109 (0.007887) | 0.275987 / 0.275898 (0.000089) | 0.289487 / 0.323480 (-0.033993) | 0.005149 / 0.007986 (-0.002837) | 0.002806 / 0.004328 (-0.001522) | 0.049617 / 0.004250 (0.045366) | 0.046949 / 0.037052 (0.009897) | 0.281596 / 0.258489 (0.023107) | 0.330948 / 0.293841 (0.037108) | 0.049645 / 0.128546 (-0.078901) | 0.010953 / 0.075646 (-0.064693) | 0.058546 / 0.419271 (-0.360725) | 0.034010 / 0.043533 (-0.009523) | 0.270525 / 0.255139 (0.015386) | 0.289749 / 0.283200 (0.006550) | 0.018755 / 0.141683 (-0.122927) | 1.163072 / 1.452155 (-0.289082) | 1.213400 / 1.492716 (-0.279316) |\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) | 0.092397 / 0.018006 (0.074390) | 0.299376 / 0.000490 (0.298886) | 0.000211 / 0.000200 (0.000011) | 0.000044 / 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) | 0.022496 / 0.037411 (-0.014916) | 0.076886 / 0.014526 (0.062361) | 0.087186 / 0.176557 (-0.089371) | 0.126092 / 0.737135 (-0.611044) | 0.088832 / 0.296338 (-0.207507) |\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) | 0.288885 / 0.215209 (0.073676) | 2.839851 / 2.077655 (0.762196) | 1.587556 / 1.504120 (0.083436) | 1.470249 / 1.541195 (-0.070945) | 1.518080 / 1.468490 (0.049590) | 0.569646 / 4.584777 (-4.015131) | 2.417574 / 3.745712 (-1.328138) | 2.737368 / 5.269862 (-2.532494) | 1.784419 / 4.565676 (-2.781257) | 0.064104 / 0.424275 (-0.360171) | 0.005138 / 0.007607 (-0.002469) | 0.346214 / 0.226044 (0.120169) | 3.439541 / 2.268929 (1.170612) | 1.944792 / 55.444624 (-53.499832) | 1.675762 / 6.876477 (-5.200714) | 1.851871 / 2.142072 (-0.290201) | 0.652932 / 4.805227 (-4.152295) | 0.118953 / 6.500664 (-6.381711) | 0.041011 / 0.075469 (-0.034459) |\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) | 1.017690 / 1.841788 (-0.824098) | 12.610531 / 8.074308 (4.536223) | 11.223165 / 10.191392 (1.031773) | 0.131637 / 0.680424 (-0.548786) | 0.016733 / 0.534201 (-0.517468) | 0.288491 / 0.579283 (-0.290792) | 0.275899 / 0.434364 (-0.158465) | 0.331837 / 0.540337 (-0.208500) | 0.421695 / 1.386936 (-0.965241) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#5d9dfa9a8c077c783729a279623926faa9e2f3f1 \"CML watermark\")\n" ]

[]

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6632). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update." ]

[]

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[]

[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6631). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "<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) | 0.005076 / 0.011353 (-0.006277) | 0.003665 / 0.011008 (-0.007343) | 0.063602 / 0.038508 (0.025094) | 0.029103 / 0.023109 (0.005993) | 0.233133 / 0.275898 (-0.042765) | 0.257000 / 0.323480 (-0.066480) | 0.003059 / 0.007986 (-0.004926) | 0.004007 / 0.004328 (-0.000321) | 0.049804 / 0.004250 (0.045553) | 0.039946 / 0.037052 (0.002893) | 0.248003 / 0.258489 (-0.010486) | 0.272729 / 0.293841 (-0.021112) | 0.027542 / 0.128546 (-0.101004) | 0.010745 / 0.075646 (-0.064901) | 0.207686 / 0.419271 (-0.211586) | 0.035438 / 0.043533 (-0.008095) | 0.236864 / 0.255139 (-0.018275) | 0.258610 / 0.283200 (-0.024590) | 0.017225 / 0.141683 (-0.124458) | 1.130894 / 1.452155 (-0.321261) | 1.171266 / 1.492716 (-0.321450) |\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) | 0.092532 / 0.018006 (0.074525) | 0.301650 / 0.000490 (0.301161) | 0.000216 / 0.000200 (0.000016) | 0.000045 / 0.000054 (-0.000010) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.018175 / 0.037411 (-0.019237) | 0.061538 / 0.014526 (0.047012) | 0.073673 / 0.176557 (-0.102884) | 0.120676 / 0.737135 (-0.616460) | 0.074753 / 0.296338 (-0.221586) |\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) | 0.283625 / 0.215209 (0.068416) | 2.794903 / 2.077655 (0.717248) | 1.485149 / 1.504120 (-0.018970) | 1.361154 / 1.541195 (-0.180041) | 1.371436 / 1.468490 (-0.097054) | 0.580401 / 4.584777 (-4.004376) | 2.457068 / 3.745712 (-1.288644) | 2.760878 / 5.269862 (-2.508984) | 1.725507 / 4.565676 (-2.840169) | 0.063632 / 0.424275 (-0.360644) | 0.005036 / 0.007607 (-0.002572) | 0.337167 / 0.226044 (0.111122) | 3.314508 / 2.268929 (1.045579) | 1.863412 / 55.444624 (-53.581213) | 1.621966 / 6.876477 (-5.254511) | 1.600422 / 2.142072 (-0.541651) | 0.647753 / 4.805227 (-4.157475) | 0.117169 / 6.500664 (-6.383495) | 0.042338 / 0.075469 (-0.033131) |\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) | 0.981818 / 1.841788 (-0.859969) | 12.044657 / 8.074308 (3.970349) | 10.654091 / 10.191392 (0.462699) | 0.130693 / 0.680424 (-0.549731) | 0.014733 / 0.534201 (-0.519468) | 0.317432 / 0.579283 (-0.261851) | 0.267196 / 0.434364 (-0.167168) | 0.329310 / 0.540337 (-0.211028) | 0.433379 / 1.386936 (-0.953557) |\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) | 0.005502 / 0.011353 (-0.005851) | 0.003951 / 0.011008 (-0.007057) | 0.050651 / 0.038508 (0.012143) | 0.031802 / 0.023109 (0.008693) | 0.281384 / 0.275898 (0.005485) | 0.303900 / 0.323480 (-0.019580) | 0.004451 / 0.007986 (-0.003534) | 0.002801 / 0.004328 (-0.001527) | 0.048688 / 0.004250 (0.044438) | 0.044717 / 0.037052 (0.007664) | 0.295017 / 0.258489 (0.036528) | 0.328003 / 0.293841 (0.034162) | 0.048421 / 0.128546 (-0.080125) | 0.011254 / 0.075646 (-0.064392) | 0.058223 / 0.419271 (-0.361048) | 0.033915 / 0.043533 (-0.009618) | 0.279893 / 0.255139 (0.024754) | 0.297605 / 0.283200 (0.014405) | 0.017115 / 0.141683 (-0.124568) | 1.146966 / 1.452155 (-0.305189) | 1.191650 / 1.492716 (-0.301066) |\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) | 0.092524 / 0.018006 (0.074518) | 0.309332 / 0.000490 (0.308842) | 0.000212 / 0.000200 (0.000012) | 0.000044 / 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) | 0.022265 / 0.037411 (-0.015146) | 0.075732 / 0.014526 (0.061206) | 0.087340 / 0.176557 (-0.089217) | 0.126079 / 0.737135 (-0.611056) | 0.090349 / 0.296338 (-0.205990) |\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) | 0.288882 / 0.215209 (0.073673) | 2.833046 / 2.077655 (0.755392) | 1.602905 / 1.504120 (0.098785) | 1.473110 / 1.541195 (-0.068085) | 1.491300 / 1.468490 (0.022810) | 0.557799 / 4.584777 (-4.026978) | 2.439526 / 3.745712 (-1.306186) | 2.669336 / 5.269862 (-2.600526) | 1.719472 / 4.565676 (-2.846204) | 0.062456 / 0.424275 (-0.361819) | 0.005058 / 0.007607 (-0.002549) | 0.343706 / 0.226044 (0.117662) | 3.422397 / 2.268929 (1.153469) | 1.983679 / 55.444624 (-53.460946) | 1.673784 / 6.876477 (-5.202693) | 1.785144 / 2.142072 (-0.356928) | 0.643127 / 4.805227 (-4.162100) | 0.115254 / 6.500664 (-6.385410) | 0.041235 / 0.075469 (-0.034235) |\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) | 1.005448 / 1.841788 (-0.836340) | 12.240100 / 8.074308 (4.165792) | 11.051965 / 10.191392 (0.860573) | 0.130438 / 0.680424 (-0.549986) | 0.015918 / 0.534201 (-0.518283) | 0.287468 / 0.579283 (-0.291815) | 0.287699 / 0.434364 (-0.146665) | 0.324561 / 0.540337 (-0.215777) | 0.418820 / 1.386936 (-0.968116) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#237a2a688155e23cfbcdfadd2d491ce1667fa494 \"CML watermark\")\n" ]

[]

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[]

[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6630). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "Hmm these errors look pretty weird... can they be retried?", "Hi, thanks for working on this! To fix the errors, you also need to update [this file](https://github.com/huggingface/datasets/blob/main/src/datasets/utils/_dill.py) (by adding `version.parse(\"0.3.8\").release` to the lists)", "<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) | 0.005068 / 0.011353 (-0.006285) | 0.003657 / 0.011008 (-0.007351) | 0.062914 / 0.038508 (0.024406) | 0.027965 / 0.023109 (0.004855) | 0.241804 / 0.275898 (-0.034094) | 0.268069 / 0.323480 (-0.055411) | 0.004066 / 0.007986 (-0.003920) | 0.002704 / 0.004328 (-0.001624) | 0.048745 / 0.004250 (0.044495) | 0.042158 / 0.037052 (0.005106) | 0.257670 / 0.258489 (-0.000819) | 0.279419 / 0.293841 (-0.014422) | 0.027193 / 0.128546 (-0.101353) | 0.010379 / 0.075646 (-0.065267) | 0.207009 / 0.419271 (-0.212262) | 0.035494 / 0.043533 (-0.008039) | 0.246025 / 0.255139 (-0.009114) | 0.265906 / 0.283200 (-0.017294) | 0.017335 / 0.141683 (-0.124348) | 1.134052 / 1.452155 (-0.318103) | 1.184668 / 1.492716 (-0.308049) |\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) | 0.093137 / 0.018006 (0.075130) | 0.302279 / 0.000490 (0.301789) | 0.000210 / 0.000200 (0.000010) | 0.000047 / 0.000054 (-0.000008) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.018190 / 0.037411 (-0.019221) | 0.061436 / 0.014526 (0.046910) | 0.073102 / 0.176557 (-0.103454) | 0.119782 / 0.737135 (-0.617354) | 0.074292 / 0.296338 (-0.222046) |\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) | 0.285905 / 0.215209 (0.070696) | 2.809051 / 2.077655 (0.731397) | 1.470305 / 1.504120 (-0.033814) | 1.350457 / 1.541195 (-0.190738) | 1.349111 / 1.468490 (-0.119379) | 0.568277 / 4.584777 (-4.016500) | 2.353046 / 3.745712 (-1.392666) | 2.805862 / 5.269862 (-2.463999) | 1.750275 / 4.565676 (-2.815401) | 0.062370 / 0.424275 (-0.361905) | 0.004954 / 0.007607 (-0.002653) | 0.335609 / 0.226044 (0.109564) | 3.367200 / 2.268929 (1.098271) | 1.829431 / 55.444624 (-53.615193) | 1.545093 / 6.876477 (-5.331384) | 1.571107 / 2.142072 (-0.570966) | 0.640279 / 4.805227 (-4.164949) | 0.116209 / 6.500664 (-6.384455) | 0.042308 / 0.075469 (-0.033161) |\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) | 0.982972 / 1.841788 (-0.858816) | 11.424370 / 8.074308 (3.350062) | 10.427111 / 10.191392 (0.235719) | 0.129477 / 0.680424 (-0.550946) | 0.014166 / 0.534201 (-0.520035) | 0.287597 / 0.579283 (-0.291686) | 0.265588 / 0.434364 (-0.168776) | 0.324007 / 0.540337 (-0.216330) | 0.430766 / 1.386936 (-0.956170) |\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) | 0.005347 / 0.011353 (-0.006005) | 0.003733 / 0.011008 (-0.007275) | 0.049520 / 0.038508 (0.011011) | 0.031177 / 0.023109 (0.008068) | 0.281854 / 0.275898 (0.005956) | 0.300937 / 0.323480 (-0.022543) | 0.004385 / 0.007986 (-0.003601) | 0.002841 / 0.004328 (-0.001488) | 0.048661 / 0.004250 (0.044411) | 0.044258 / 0.037052 (0.007205) | 0.295651 / 0.258489 (0.037162) | 0.322872 / 0.293841 (0.029031) | 0.048924 / 0.128546 (-0.079622) | 0.010742 / 0.075646 (-0.064905) | 0.059327 / 0.419271 (-0.359944) | 0.033938 / 0.043533 (-0.009595) | 0.282235 / 0.255139 (0.027096) | 0.297432 / 0.283200 (0.014233) | 0.018295 / 0.141683 (-0.123388) | 1.164459 / 1.452155 (-0.287696) | 1.214511 / 1.492716 (-0.278205) |\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) | 0.091441 / 0.018006 (0.073435) | 0.303023 / 0.000490 (0.302533) | 0.000211 / 0.000200 (0.000011) | 0.000051 / 0.000054 (-0.000004) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.022024 / 0.037411 (-0.015388) | 0.075570 / 0.014526 (0.061044) | 0.086761 / 0.176557 (-0.089796) | 0.126437 / 0.737135 (-0.610698) | 0.088354 / 0.296338 (-0.207984) |\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) | 0.289360 / 0.215209 (0.074151) | 2.816433 / 2.077655 (0.738779) | 1.561442 / 1.504120 (0.057322) | 1.438168 / 1.541195 (-0.103027) | 1.453398 / 1.468490 (-0.015092) | 0.579474 / 4.584777 (-4.005303) | 2.458640 / 3.745712 (-1.287072) | 2.638572 / 5.269862 (-2.631290) | 1.725218 / 4.565676 (-2.840458) | 0.063550 / 0.424275 (-0.360725) | 0.005220 / 0.007607 (-0.002387) | 0.338883 / 0.226044 (0.112838) | 3.353585 / 2.268929 (1.084656) | 1.913186 / 55.444624 (-53.531438) | 1.667445 / 6.876477 (-5.209032) | 1.740085 / 2.142072 (-0.401987) | 0.646369 / 4.805227 (-4.158859) | 0.116737 / 6.500664 (-6.383927) | 0.041052 / 0.075469 (-0.034417) |\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) | 1.023180 / 1.841788 (-0.818608) | 12.078398 / 8.074308 (4.004090) | 10.952012 / 10.191392 (0.760620) | 0.131335 / 0.680424 (-0.549089) | 0.015701 / 0.534201 (-0.518499) | 0.289709 / 0.579283 (-0.289574) | 0.270495 / 0.434364 (-0.163869) | 0.331773 / 0.540337 (-0.208565) | 0.417660 / 1.386936 (-0.969276) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#3b21d74f5c0ab8a85838af04de8ad85e71b0ac4f \"CML watermark\")\n" ]

[]

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[]

[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6629). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "@huggingface/datasets, feel free to review this PR so that it can be included in the next release." ]

[]

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[]

[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6628). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "@huggingface/datasets, feel free to review this PR so that it can be included in the next release." ]

[]

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[]

[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6627). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "<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) | 0.004944 / 0.011353 (-0.006409) | 0.003279 / 0.011008 (-0.007729) | 0.063041 / 0.038508 (0.024533) | 0.029888 / 0.023109 (0.006779) | 0.259138 / 0.275898 (-0.016760) | 0.276907 / 0.323480 (-0.046573) | 0.004015 / 0.007986 (-0.003970) | 0.002647 / 0.004328 (-0.001682) | 0.048944 / 0.004250 (0.044693) | 0.039412 / 0.037052 (0.002360) | 0.278069 / 0.258489 (0.019580) | 0.299139 / 0.293841 (0.005298) | 0.027272 / 0.128546 (-0.101274) | 0.010445 / 0.075646 (-0.065202) | 0.206925 / 0.419271 (-0.212347) | 0.035589 / 0.043533 (-0.007944) | 0.256805 / 0.255139 (0.001666) | 0.275128 / 0.283200 (-0.008072) | 0.017888 / 0.141683 (-0.123795) | 1.136983 / 1.452155 (-0.315172) | 1.167495 / 1.492716 (-0.325222) |\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) | 0.088167 / 0.018006 (0.070161) | 0.297360 / 0.000490 (0.296871) | 0.000231 / 0.000200 (0.000031) | 0.000049 / 0.000054 (-0.000006) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.018114 / 0.037411 (-0.019297) | 0.061217 / 0.014526 (0.046691) | 0.072269 / 0.176557 (-0.104288) | 0.120607 / 0.737135 (-0.616528) | 0.073517 / 0.296338 (-0.222822) |\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) | 0.282580 / 0.215209 (0.067371) | 2.758650 / 2.077655 (0.680995) | 1.425125 / 1.504120 (-0.078995) | 1.303182 / 1.541195 (-0.238013) | 1.341035 / 1.468490 (-0.127455) | 0.549485 / 4.584777 (-4.035292) | 2.346297 / 3.745712 (-1.399415) | 2.686457 / 5.269862 (-2.583405) | 1.684789 / 4.565676 (-2.880888) | 0.061279 / 0.424275 (-0.362996) | 0.004902 / 0.007607 (-0.002705) | 0.333089 / 0.226044 (0.107044) | 3.297016 / 2.268929 (1.028087) | 1.765614 / 55.444624 (-53.679010) | 1.499314 / 6.876477 (-5.377162) | 1.501275 / 2.142072 (-0.640797) | 0.619039 / 4.805227 (-4.186189) | 0.114284 / 6.500664 (-6.386380) | 0.041481 / 0.075469 (-0.033988) |\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) | 0.973924 / 1.841788 (-0.867863) | 11.268266 / 8.074308 (3.193958) | 10.304738 / 10.191392 (0.113346) | 0.129297 / 0.680424 (-0.551127) | 0.014894 / 0.534201 (-0.519307) | 0.287658 / 0.579283 (-0.291626) | 0.266476 / 0.434364 (-0.167888) | 0.322199 / 0.540337 (-0.218138) | 0.419568 / 1.386936 (-0.967368) |\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) | 0.005220 / 0.011353 (-0.006133) | 0.003310 / 0.011008 (-0.007698) | 0.049707 / 0.038508 (0.011199) | 0.031148 / 0.023109 (0.008039) | 0.284644 / 0.275898 (0.008746) | 0.302767 / 0.323480 (-0.020712) | 0.004245 / 0.007986 (-0.003740) | 0.002677 / 0.004328 (-0.001651) | 0.049870 / 0.004250 (0.045620) | 0.043922 / 0.037052 (0.006870) | 0.294955 / 0.258489 (0.036466) | 0.322144 / 0.293841 (0.028303) | 0.047211 / 0.128546 (-0.081336) | 0.010492 / 0.075646 (-0.065155) | 0.058152 / 0.419271 (-0.361120) | 0.033508 / 0.043533 (-0.010025) | 0.281266 / 0.255139 (0.026127) | 0.300010 / 0.283200 (0.016810) | 0.017616 / 0.141683 (-0.124067) | 1.124658 / 1.452155 (-0.327496) | 1.167222 / 1.492716 (-0.325495) |\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) | 0.089085 / 0.018006 (0.071079) | 0.297912 / 0.000490 (0.297423) | 0.000211 / 0.000200 (0.000011) | 0.000056 / 0.000054 (0.000002) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.021669 / 0.037411 (-0.015742) | 0.075648 / 0.014526 (0.061123) | 0.086054 / 0.176557 (-0.090503) | 0.125236 / 0.737135 (-0.611899) | 0.088146 / 0.296338 (-0.208192) |\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) | 0.295238 / 0.215209 (0.080029) | 2.870002 / 2.077655 (0.792347) | 1.582534 / 1.504120 (0.078414) | 1.466710 / 1.541195 (-0.074485) | 1.475352 / 1.468490 (0.006861) | 0.554745 / 4.584777 (-4.030032) | 2.412533 / 3.745712 (-1.333179) | 2.583863 / 5.269862 (-2.685999) | 1.689124 / 4.565676 (-2.876552) | 0.061353 / 0.424275 (-0.362922) | 0.005015 / 0.007607 (-0.002592) | 0.338733 / 0.226044 (0.112688) | 3.356710 / 2.268929 (1.087781) | 1.932143 / 55.444624 (-53.512481) | 1.660081 / 6.876477 (-5.216396) | 1.764961 / 2.142072 (-0.377111) | 0.640002 / 4.805227 (-4.165225) | 0.115251 / 6.500664 (-6.385413) | 0.040627 / 0.075469 (-0.034842) |\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) | 0.992296 / 1.841788 (-0.849492) | 11.821259 / 8.074308 (3.746951) | 10.715570 / 10.191392 (0.524178) | 0.142934 / 0.680424 (-0.537489) | 0.015680 / 0.534201 (-0.518521) | 0.287435 / 0.579283 (-0.291848) | 0.276817 / 0.434364 (-0.157547) | 0.327823 / 0.540337 (-0.212515) | 0.413404 / 1.386936 (-0.973532) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#82c78b614d34ee42180d35a882875a28d6281db0 \"CML watermark\")\n" ]

[]

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6626). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "<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) | 0.005085 / 0.011353 (-0.006268) | 0.003592 / 0.011008 (-0.007417) | 0.062591 / 0.038508 (0.024083) | 0.031063 / 0.023109 (0.007954) | 0.247029 / 0.275898 (-0.028869) | 0.273706 / 0.323480 (-0.049774) | 0.004034 / 0.007986 (-0.003951) | 0.002672 / 0.004328 (-0.001657) | 0.048407 / 0.004250 (0.044156) | 0.049229 / 0.037052 (0.012177) | 0.264316 / 0.258489 (0.005827) | 0.284953 / 0.293841 (-0.008888) | 0.027712 / 0.128546 (-0.100834) | 0.010619 / 0.075646 (-0.065027) | 0.210017 / 0.419271 (-0.209254) | 0.035636 / 0.043533 (-0.007897) | 0.252830 / 0.255139 (-0.002309) | 0.278772 / 0.283200 (-0.004428) | 0.017356 / 0.141683 (-0.124326) | 1.140202 / 1.452155 (-0.311953) | 1.204807 / 1.492716 (-0.287909) |\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) | 0.089130 / 0.018006 (0.071123) | 0.300115 / 0.000490 (0.299626) | 0.000213 / 0.000200 (0.000013) | 0.000042 / 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) | 0.018352 / 0.037411 (-0.019059) | 0.061431 / 0.014526 (0.046905) | 0.073911 / 0.176557 (-0.102646) | 0.121230 / 0.737135 (-0.615906) | 0.074867 / 0.296338 (-0.221471) |\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) | 0.282272 / 0.215209 (0.067063) | 2.737413 / 2.077655 (0.659759) | 1.446651 / 1.504120 (-0.057469) | 1.319686 / 1.541195 (-0.221508) | 1.327479 / 1.468490 (-0.141011) | 0.558003 / 4.584777 (-4.026774) | 2.361623 / 3.745712 (-1.384089) | 2.770436 / 5.269862 (-2.499425) | 1.703450 / 4.565676 (-2.862227) | 0.062034 / 0.424275 (-0.362241) | 0.005070 / 0.007607 (-0.002537) | 0.337265 / 0.226044 (0.111221) | 3.299438 / 2.268929 (1.030509) | 1.781273 / 55.444624 (-53.663351) | 1.512743 / 6.876477 (-5.363734) | 1.530995 / 2.142072 (-0.611077) | 0.630210 / 4.805227 (-4.175017) | 0.116219 / 6.500664 (-6.384445) | 0.042220 / 0.075469 (-0.033249) |\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) | 0.946341 / 1.841788 (-0.895446) | 11.462179 / 8.074308 (3.387871) | 10.603314 / 10.191392 (0.411922) | 0.128826 / 0.680424 (-0.551598) | 0.013994 / 0.534201 (-0.520207) | 0.288142 / 0.579283 (-0.291141) | 0.266941 / 0.434364 (-0.167422) | 0.329392 / 0.540337 (-0.210946) | 0.431720 / 1.386936 (-0.955216) |\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) | 0.005303 / 0.011353 (-0.006050) | 0.003587 / 0.011008 (-0.007422) | 0.049437 / 0.038508 (0.010929) | 0.031940 / 0.023109 (0.008831) | 0.276651 / 0.275898 (0.000752) | 0.297240 / 0.323480 (-0.026240) | 0.004202 / 0.007986 (-0.003784) | 0.002709 / 0.004328 (-0.001619) | 0.048647 / 0.004250 (0.044397) | 0.044147 / 0.037052 (0.007095) | 0.291171 / 0.258489 (0.032682) | 0.319297 / 0.293841 (0.025456) | 0.048167 / 0.128546 (-0.080379) | 0.010630 / 0.075646 (-0.065016) | 0.058402 / 0.419271 (-0.360869) | 0.033817 / 0.043533 (-0.009716) | 0.300546 / 0.255139 (0.045407) | 0.319396 / 0.283200 (0.036197) | 0.017736 / 0.141683 (-0.123946) | 1.159590 / 1.452155 (-0.292565) | 1.191778 / 1.492716 (-0.300939) |\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) | 0.088971 / 0.018006 (0.070965) | 0.299721 / 0.000490 (0.299231) | 0.000219 / 0.000200 (0.000019) | 0.000043 / 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) | 0.021895 / 0.037411 (-0.015516) | 0.075388 / 0.014526 (0.060862) | 0.087446 / 0.176557 (-0.089111) | 0.126339 / 0.737135 (-0.610796) | 0.089329 / 0.296338 (-0.207010) |\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) | 0.296642 / 0.215209 (0.081433) | 2.916023 / 2.077655 (0.838368) | 1.593180 / 1.504120 (0.089060) | 1.470491 / 1.541195 (-0.070704) | 1.485713 / 1.468490 (0.017223) | 0.577204 / 4.584777 (-4.007573) | 2.436463 / 3.745712 (-1.309249) | 2.651004 / 5.269862 (-2.618858) | 1.754026 / 4.565676 (-2.811651) | 0.064943 / 0.424275 (-0.359332) | 0.005115 / 0.007607 (-0.002492) | 0.362082 / 0.226044 (0.136038) | 3.498198 / 2.268929 (1.229270) | 1.951936 / 55.444624 (-53.492688) | 1.682027 / 6.876477 (-5.194450) | 1.751768 / 2.142072 (-0.390304) | 0.668479 / 4.805227 (-4.136748) | 0.119934 / 6.500664 (-6.380730) | 0.041419 / 0.075469 (-0.034050) |\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) | 0.978145 / 1.841788 (-0.863643) | 11.984984 / 8.074308 (3.910676) | 10.732377 / 10.191392 (0.540985) | 0.141868 / 0.680424 (-0.538555) | 0.015256 / 0.534201 (-0.518945) | 0.288488 / 0.579283 (-0.290795) | 0.276091 / 0.434364 (-0.158273) | 0.330429 / 0.540337 (-0.209908) | 0.423964 / 1.386936 (-0.962972) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#bb8497b9dec2a3807c887b8184f902d1d8d7c25a \"CML watermark\")\n" ]

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{ "diff_url": "https://github.com/huggingface/datasets/pull/6626.diff", "html_url": "https://github.com/huggingface/datasets/pull/6626", "merged_at": "2024-01-29T15:12:18Z", "patch_url": "https://github.com/huggingface/datasets/pull/6626.patch", "url": "https://api.github.com/repos/huggingface/datasets/pulls/6626" }

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[ "Hi, this dataset has been disabled by the authors, so unfortunately it's no longer possible to download it." ]

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[ "@mariosasko, @lhoestq, @albertvillanova\r\nhey guys! can anyone help? or can you guys suggest who can help with this?", "Hi ! \r\n\r\n1. When the dataset is running of of examples, the last batches received by the GPU can be incomplete or empty/missing. We haven't implemented yet a way to ignore the last batch. It might require the datasets to provide the number of examples per shard though, so that we can know when to stop.\r\n2. Samplers are not compatible with IterableDatasets in pytorch\r\n3. if `dataset.n_shards % world_size != 0` then all the nodes will read/stream the full dataset in order (possibly reading/streaming the same data multiple times), BUT will only yield one example out of `world_size` so that each example goes to one exactly one GPU.\r\n4. no, sharding should be down up-front and can take some time depending on the dataset size and format", "> if dataset.n_shards % world_size != 0 then all the nodes will read/stream the full dataset in order (possibly reading/streaming the same data multiple times), BUT will only yield one example out of world_size so that each example goes to one exactly one GPU.\r\n\r\nconsidering there's just 1 shard and 2 worker nodes, do you mean each worker node will load the whole dataset but still receive half of that shard while streaming?", "Yes both nodes will stream from the 1 shard, but each node will skip half of the examples. This way in total each example is seen once and exactly once during you distributed training.\r\n\r\nThough it terms of I/O, the dataset is effectively read/streamed twice.", "what if the number of samples in that shard % num_nodes != 0? it will break/get stuck? or is the data repeated in that case for gradient sync?", "In the case one at least one of the noes will get an empty/incomplete batch. The data is not repeated in that case. If the training loop doesn't take this into account it can lead to unexpected behaviors indeed.\r\n\r\nIn the future we'd like to add a feature that would allow the nodes to ignore the last batch, this way all the nodes would only have full batches." ]

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6619). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "<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) | 0.005066 / 0.011353 (-0.006287) | 0.003678 / 0.011008 (-0.007330) | 0.063057 / 0.038508 (0.024549) | 0.031250 / 0.023109 (0.008140) | 0.248856 / 0.275898 (-0.027042) | 0.266932 / 0.323480 (-0.056548) | 0.003814 / 0.007986 (-0.004172) | 0.002843 / 0.004328 (-0.001485) | 0.049210 / 0.004250 (0.044959) | 0.041514 / 0.037052 (0.004462) | 0.264874 / 0.258489 (0.006385) | 0.288834 / 0.293841 (-0.005007) | 0.027457 / 0.128546 (-0.101089) | 0.011071 / 0.075646 (-0.064575) | 0.206433 / 0.419271 (-0.212839) | 0.035381 / 0.043533 (-0.008152) | 0.246829 / 0.255139 (-0.008310) | 0.271094 / 0.283200 (-0.012106) | 0.017790 / 0.141683 (-0.123893) | 1.134618 / 1.452155 (-0.317536) | 1.182600 / 1.492716 (-0.310116) |\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) | 0.094970 / 0.018006 (0.076964) | 0.306438 / 0.000490 (0.305949) | 0.000212 / 0.000200 (0.000012) | 0.000044 / 0.000054 (-0.000010) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.017786 / 0.037411 (-0.019625) | 0.060652 / 0.014526 (0.046127) | 0.072619 / 0.176557 (-0.103937) | 0.119460 / 0.737135 (-0.617676) | 0.073580 / 0.296338 (-0.222759) |\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) | 0.279304 / 0.215209 (0.064095) | 2.747179 / 2.077655 (0.669524) | 1.438291 / 1.504120 (-0.065829) | 1.313405 / 1.541195 (-0.227789) | 1.354569 / 1.468490 (-0.113921) | 0.578375 / 4.584777 (-4.006402) | 2.424576 / 3.745712 (-1.321136) | 2.831513 / 5.269862 (-2.438348) | 1.756062 / 4.565676 (-2.809614) | 0.064460 / 0.424275 (-0.359815) | 0.005065 / 0.007607 (-0.002542) | 0.335003 / 0.226044 (0.108958) | 3.310500 / 2.268929 (1.041571) | 1.778017 / 55.444624 (-53.666607) | 1.504743 / 6.876477 (-5.371734) | 1.532843 / 2.142072 (-0.609229) | 0.662110 / 4.805227 (-4.143118) | 0.118239 / 6.500664 (-6.382425) | 0.042135 / 0.075469 (-0.033335) |\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) | 0.945650 / 1.841788 (-0.896137) | 11.623179 / 8.074308 (3.548871) | 10.927315 / 10.191392 (0.735923) | 0.131050 / 0.680424 (-0.549374) | 0.014725 / 0.534201 (-0.519476) | 0.290716 / 0.579283 (-0.288567) | 0.272357 / 0.434364 (-0.162007) | 0.323274 / 0.540337 (-0.217064) | 0.426692 / 1.386936 (-0.960244) |\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) | 0.005478 / 0.011353 (-0.005875) | 0.003618 / 0.011008 (-0.007390) | 0.049599 / 0.038508 (0.011091) | 0.030814 / 0.023109 (0.007705) | 0.273663 / 0.275898 (-0.002235) | 0.292099 / 0.323480 (-0.031381) | 0.004196 / 0.007986 (-0.003790) | 0.002779 / 0.004328 (-0.001550) | 0.047812 / 0.004250 (0.043562) | 0.045095 / 0.037052 (0.008043) | 0.286288 / 0.258489 (0.027799) | 0.314125 / 0.293841 (0.020284) | 0.047940 / 0.128546 (-0.080606) | 0.010714 / 0.075646 (-0.064932) | 0.057453 / 0.419271 (-0.361819) | 0.033482 / 0.043533 (-0.010051) | 0.273391 / 0.255139 (0.018252) | 0.284936 / 0.283200 (0.001736) | 0.017805 / 0.141683 (-0.123878) | 1.148303 / 1.452155 (-0.303852) | 1.185268 / 1.492716 (-0.307448) |\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) | 0.092442 / 0.018006 (0.074436) | 0.309908 / 0.000490 (0.309418) | 0.000213 / 0.000200 (0.000013) | 0.000043 / 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) | 0.022874 / 0.037411 (-0.014537) | 0.078238 / 0.014526 (0.063712) | 0.088844 / 0.176557 (-0.087713) | 0.127054 / 0.737135 (-0.610081) | 0.089809 / 0.296338 (-0.206530) |\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) | 0.292360 / 0.215209 (0.077151) | 2.842700 / 2.077655 (0.765045) | 1.571071 / 1.504120 (0.066951) | 1.450773 / 1.541195 (-0.090422) | 1.467090 / 1.468490 (-0.001400) | 0.583529 / 4.584777 (-4.001248) | 2.469284 / 3.745712 (-1.276428) | 2.844426 / 5.269862 (-2.425435) | 1.773336 / 4.565676 (-2.792341) | 0.064585 / 0.424275 (-0.359690) | 0.005098 / 0.007607 (-0.002509) | 0.342816 / 0.226044 (0.116771) | 3.363309 / 2.268929 (1.094381) | 1.922834 / 55.444624 (-53.521790) | 1.649702 / 6.876477 (-5.226774) | 1.672727 / 2.142072 (-0.469345) | 0.665015 / 4.805227 (-4.140212) | 0.124764 / 6.500664 (-6.375900) | 0.041564 / 0.075469 (-0.033905) |\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) | 0.988970 / 1.841788 (-0.852818) | 12.148983 / 8.074308 (4.074675) | 11.132697 / 10.191392 (0.941305) | 0.131596 / 0.680424 (-0.548828) | 0.015700 / 0.534201 (-0.518501) | 0.288819 / 0.579283 (-0.290464) | 0.276692 / 0.434364 (-0.157672) | 0.330260 / 0.540337 (-0.210078) | 0.421612 / 1.386936 (-0.965324) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#d627fb8357f39d78d79e704712609c7b34bdeba4 \"CML watermark\")\n" ]

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[ "Hi! Can you please share the error's stack trace so we can see where it comes from?" ]

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6617). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "<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) | 0.004774 / 0.011353 (-0.006579) | 0.003397 / 0.011008 (-0.007611) | 0.063862 / 0.038508 (0.025354) | 0.029353 / 0.023109 (0.006244) | 0.245921 / 0.275898 (-0.029977) | 0.268414 / 0.323480 (-0.055066) | 0.002834 / 0.007986 (-0.005152) | 0.002606 / 0.004328 (-0.001723) | 0.049690 / 0.004250 (0.045439) | 0.041637 / 0.037052 (0.004585) | 0.262526 / 0.258489 (0.004037) | 0.288200 / 0.293841 (-0.005641) | 0.027233 / 0.128546 (-0.101313) | 0.010322 / 0.075646 (-0.065324) | 0.213860 / 0.419271 (-0.205411) | 0.034930 / 0.043533 (-0.008602) | 0.249256 / 0.255139 (-0.005883) | 0.270016 / 0.283200 (-0.013184) | 0.019413 / 0.141683 (-0.122270) | 1.124801 / 1.452155 (-0.327354) | 1.166224 / 1.492716 (-0.326492) |\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) | 0.091641 / 0.018006 (0.073635) | 0.299679 / 0.000490 (0.299189) | 0.000209 / 0.000200 (0.000009) | 0.000051 / 0.000054 (-0.000004) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.018084 / 0.037411 (-0.019327) | 0.060143 / 0.014526 (0.045617) | 0.072556 / 0.176557 (-0.104001) | 0.118555 / 0.737135 (-0.618580) | 0.073786 / 0.296338 (-0.222553) |\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) | 0.278193 / 0.215209 (0.062984) | 2.707954 / 2.077655 (0.630300) | 1.483575 / 1.504120 (-0.020545) | 1.371939 / 1.541195 (-0.169256) | 1.395009 / 1.468490 (-0.073481) | 0.559949 / 4.584777 (-4.024828) | 2.372529 / 3.745712 (-1.373183) | 2.823641 / 5.269862 (-2.446221) | 1.722999 / 4.565676 (-2.842678) | 0.062535 / 0.424275 (-0.361741) | 0.004970 / 0.007607 (-0.002637) | 0.338625 / 0.226044 (0.112580) | 3.317576 / 2.268929 (1.048648) | 1.854552 / 55.444624 (-53.590073) | 1.589323 / 6.876477 (-5.287154) | 1.624630 / 2.142072 (-0.517442) | 0.638388 / 4.805227 (-4.166839) | 0.116675 / 6.500664 (-6.383989) | 0.041850 / 0.075469 (-0.033619) |\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) | 0.938025 / 1.841788 (-0.903763) | 11.450072 / 8.074308 (3.375764) | 10.414943 / 10.191392 (0.223551) | 0.128416 / 0.680424 (-0.552007) | 0.013798 / 0.534201 (-0.520403) | 0.287997 / 0.579283 (-0.291286) | 0.259976 / 0.434364 (-0.174387) | 0.320737 / 0.540337 (-0.219601) | 0.424292 / 1.386936 (-0.962644) |\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) | 0.005107 / 0.011353 (-0.006246) | 0.003374 / 0.011008 (-0.007634) | 0.050067 / 0.038508 (0.011559) | 0.031419 / 0.023109 (0.008310) | 0.275303 / 0.275898 (-0.000595) | 0.286736 / 0.323480 (-0.036744) | 0.004177 / 0.007986 (-0.003808) | 0.002742 / 0.004328 (-0.001586) | 0.049011 / 0.004250 (0.044761) | 0.044373 / 0.037052 (0.007321) | 0.289189 / 0.258489 (0.030700) | 0.320117 / 0.293841 (0.026276) | 0.050154 / 0.128546 (-0.078392) | 0.010541 / 0.075646 (-0.065106) | 0.058318 / 0.419271 (-0.360954) | 0.033090 / 0.043533 (-0.010443) | 0.276820 / 0.255139 (0.021681) | 0.290854 / 0.283200 (0.007654) | 0.017268 / 0.141683 (-0.124415) | 1.159345 / 1.452155 (-0.292809) | 1.224829 / 1.492716 (-0.267887) |\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) | 0.092468 / 0.018006 (0.074462) | 0.301176 / 0.000490 (0.300686) | 0.000216 / 0.000200 (0.000017) | 0.000043 / 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) | 0.021858 / 0.037411 (-0.015553) | 0.074873 / 0.014526 (0.060347) | 0.086238 / 0.176557 (-0.090318) | 0.125555 / 0.737135 (-0.611580) | 0.087791 / 0.296338 (-0.208547) |\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) | 0.292283 / 0.215209 (0.077073) | 2.847306 / 2.077655 (0.769651) | 1.600833 / 1.504120 (0.096713) | 1.474253 / 1.541195 (-0.066942) | 1.474871 / 1.468490 (0.006381) | 0.576427 / 4.584777 (-4.008350) | 2.380116 / 3.745712 (-1.365596) | 2.782059 / 5.269862 (-2.487803) | 1.730642 / 4.565676 (-2.835035) | 0.063860 / 0.424275 (-0.360415) | 0.005019 / 0.007607 (-0.002588) | 0.343247 / 0.226044 (0.117202) | 3.393427 / 2.268929 (1.124498) | 1.935346 / 55.444624 (-53.509278) | 1.680124 / 6.876477 (-5.196353) | 1.665788 / 2.142072 (-0.476285) | 0.648767 / 4.805227 (-4.156460) | 0.121962 / 6.500664 (-6.378702) | 0.040669 / 0.075469 (-0.034800) |\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) | 0.996535 / 1.841788 (-0.845252) | 12.074553 / 8.074308 (4.000245) | 10.812740 / 10.191392 (0.621348) | 0.142690 / 0.680424 (-0.537734) | 0.014977 / 0.534201 (-0.519224) | 0.285619 / 0.579283 (-0.293664) | 0.269401 / 0.434364 (-0.164963) | 0.329882 / 0.540337 (-0.210456) | 0.416169 / 1.386936 (-0.970767) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#129b9e0565e7a2ceaca64b99dcbf39504661cfa9 \"CML watermark\")\n" ]

[]

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[]

[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6616). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "<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) | 0.005382 / 0.011353 (-0.005970) | 0.003853 / 0.011008 (-0.007155) | 0.062629 / 0.038508 (0.024121) | 0.030344 / 0.023109 (0.007234) | 0.245394 / 0.275898 (-0.030505) | 0.266004 / 0.323480 (-0.057476) | 0.003183 / 0.007986 (-0.004802) | 0.002795 / 0.004328 (-0.001533) | 0.048357 / 0.004250 (0.044107) | 0.043834 / 0.037052 (0.006782) | 0.255979 / 0.258489 (-0.002510) | 0.280803 / 0.293841 (-0.013038) | 0.028200 / 0.128546 (-0.100347) | 0.010856 / 0.075646 (-0.064791) | 0.207076 / 0.419271 (-0.212195) | 0.036286 / 0.043533 (-0.007247) | 0.246492 / 0.255139 (-0.008647) | 0.265861 / 0.283200 (-0.017338) | 0.018309 / 0.141683 (-0.123374) | 1.155136 / 1.452155 (-0.297018) | 1.214342 / 1.492716 (-0.278375) |\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) | 0.092530 / 0.018006 (0.074524) | 0.344951 / 0.000490 (0.344461) | 0.000207 / 0.000200 (0.000007) | 0.000043 / 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) | 0.018324 / 0.037411 (-0.019087) | 0.063137 / 0.014526 (0.048611) | 0.074683 / 0.176557 (-0.101874) | 0.120224 / 0.737135 (-0.616912) | 0.083107 / 0.296338 (-0.213232) |\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) | 0.288631 / 0.215209 (0.073422) | 2.817992 / 2.077655 (0.740337) | 1.473609 / 1.504120 (-0.030511) | 1.336610 / 1.541195 (-0.204585) | 1.354807 / 1.468490 (-0.113683) | 0.568776 / 4.584777 (-4.016001) | 2.412607 / 3.745712 (-1.333105) | 2.832816 / 5.269862 (-2.437045) | 1.789899 / 4.565676 (-2.775778) | 0.063602 / 0.424275 (-0.360673) | 0.004993 / 0.007607 (-0.002615) | 0.338830 / 0.226044 (0.112786) | 3.302550 / 2.268929 (1.033621) | 1.827907 / 55.444624 (-53.616717) | 1.589857 / 6.876477 (-5.286620) | 1.647746 / 2.142072 (-0.494326) | 0.658461 / 4.805227 (-4.146766) | 0.120360 / 6.500664 (-6.380304) | 0.042989 / 0.075469 (-0.032480) |\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) | 0.945487 / 1.841788 (-0.896301) | 11.846335 / 8.074308 (3.772027) | 10.483199 / 10.191392 (0.291807) | 0.131853 / 0.680424 (-0.548570) | 0.014230 / 0.534201 (-0.519971) | 0.288700 / 0.579283 (-0.290584) | 0.276086 / 0.434364 (-0.158278) | 0.326225 / 0.540337 (-0.214112) | 0.422874 / 1.386936 (-0.964062) |\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) | 0.006234 / 0.011353 (-0.005118) | 0.004104 / 0.011008 (-0.006904) | 0.049967 / 0.038508 (0.011459) | 0.037157 / 0.023109 (0.014048) | 0.261892 / 0.275898 (-0.014006) | 0.284304 / 0.323480 (-0.039176) | 0.004482 / 0.007986 (-0.003504) | 0.002920 / 0.004328 (-0.001409) | 0.048827 / 0.004250 (0.044577) | 0.052258 / 0.037052 (0.015206) | 0.277121 / 0.258489 (0.018632) | 0.304177 / 0.293841 (0.010336) | 0.053537 / 0.128546 (-0.075009) | 0.011137 / 0.075646 (-0.064509) | 0.058188 / 0.419271 (-0.361083) | 0.034283 / 0.043533 (-0.009250) | 0.261912 / 0.255139 (0.006773) | 0.273851 / 0.283200 (-0.009348) | 0.017824 / 0.141683 (-0.123859) | 1.130454 / 1.452155 (-0.321701) | 1.176834 / 1.492716 (-0.315882) |\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) | 0.102104 / 0.018006 (0.084098) | 0.302873 / 0.000490 (0.302383) | 0.000208 / 0.000200 (0.000008) | 0.000052 / 0.000054 (-0.000003) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.022470 / 0.037411 (-0.014941) | 0.076776 / 0.014526 (0.062250) | 0.088220 / 0.176557 (-0.088337) | 0.130030 / 0.737135 (-0.607105) | 0.089955 / 0.296338 (-0.206383) |\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) | 0.284070 / 0.215209 (0.068861) | 2.769130 / 2.077655 (0.691475) | 1.546379 / 1.504120 (0.042259) | 1.435849 / 1.541195 (-0.105346) | 1.478616 / 1.468490 (0.010126) | 0.569185 / 4.584777 (-4.015592) | 2.504721 / 3.745712 (-1.240992) | 2.778267 / 5.269862 (-2.491595) | 1.860360 / 4.565676 (-2.705316) | 0.073465 / 0.424275 (-0.350810) | 0.005108 / 0.007607 (-0.002499) | 0.335185 / 0.226044 (0.109140) | 3.314799 / 2.268929 (1.045870) | 1.934824 / 55.444624 (-53.509801) | 1.656247 / 6.876477 (-5.220229) | 1.785422 / 2.142072 (-0.356650) | 0.673677 / 4.805227 (-4.131551) | 0.117692 / 6.500664 (-6.382972) | 0.041648 / 0.075469 (-0.033821) |\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) | 0.972143 / 1.841788 (-0.869645) | 12.980353 / 8.074308 (4.906045) | 11.056189 / 10.191392 (0.864797) | 0.134592 / 0.680424 (-0.545832) | 0.015972 / 0.534201 (-0.518229) | 0.301691 / 0.579283 (-0.277593) | 0.286332 / 0.434364 (-0.148032) | 0.329025 / 0.540337 (-0.211312) | 0.422585 / 1.386936 (-0.964351) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#6eb492c7072f21cb417801957c087888f252d2d1 \"CML watermark\")\n" ]

[]

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[ "Sorry I posted in the wrong repo, please delete.. thanks!" ]

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[ "Hi ! We recently updated `cnn_dailymail` and now `datasets>=2.14` is needed to load it.\r\n\r\nYou can update `datasets` with\r\n\r\n```\r\npip install -U datasets\r\n```" ]

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[ "Hi! You are passing the wrong feature type to `cast_column`. This is the fixed call:\r\n```python\r\nais_dataset = ais_dataset.cast_column(\"my_labeled_bbox\", {\"bbox\": Sequence(Value(dtype=\"int64\")), \"label\": ClassLabel(names=[\"cat\", \"dog\"])})\r\n```", "> Hi! You are passing the wrong feature type to `cast_column`. This is the fixed call:\r\n> \r\n> ```python\r\n> ais_dataset = ais_dataset.cast_column(\"my_labeled_bbox\", {\"bbox\": Sequence(Value(dtype=\"int64\")), \"label\": ClassLabel(names=[\"cat\", \"dog\"])})\r\n> ```\r\n\r\nthanks" ]

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[ "+1", "same error in 2.16.1", "@kongjiellx any luck with the issue?", "I opened https://github.com/huggingface/datasets/pull/6632 to fix this issue. Once it's merged we'll do a new release of `datasets`", "Thanks @lhoestq !" ]

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6608). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "<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) | 0.005376 / 0.011353 (-0.005977) | 0.004691 / 0.011008 (-0.006317) | 0.064061 / 0.038508 (0.025553) | 0.030397 / 0.023109 (0.007288) | 0.242656 / 0.275898 (-0.033242) | 0.275586 / 0.323480 (-0.047894) | 0.003460 / 0.007986 (-0.004526) | 0.003125 / 0.004328 (-0.001203) | 0.050496 / 0.004250 (0.046246) | 0.045833 / 0.037052 (0.008781) | 0.255222 / 0.258489 (-0.003267) | 0.287303 / 0.293841 (-0.006538) | 0.027755 / 0.128546 (-0.100791) | 0.011251 / 0.075646 (-0.064396) | 0.208456 / 0.419271 (-0.210816) | 0.037219 / 0.043533 (-0.006314) | 0.249592 / 0.255139 (-0.005547) | 0.261243 / 0.283200 (-0.021957) | 0.020735 / 0.141683 (-0.120948) | 1.130017 / 1.452155 (-0.322137) | 1.208558 / 1.492716 (-0.284158) |\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) | 0.098891 / 0.018006 (0.080885) | 0.439042 / 0.000490 (0.438552) | 0.000333 / 0.000200 (0.000133) | 0.000045 / 0.000054 (-0.000010) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.018356 / 0.037411 (-0.019055) | 0.062416 / 0.014526 (0.047891) | 0.075613 / 0.176557 (-0.100944) | 0.122009 / 0.737135 (-0.615126) | 0.078195 / 0.296338 (-0.218144) |\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) | 0.273804 / 0.215209 (0.058595) | 2.706480 / 2.077655 (0.628826) | 1.456196 / 1.504120 (-0.047924) | 1.353301 / 1.541195 (-0.187893) | 1.378913 / 1.468490 (-0.089577) | 0.556885 / 4.584777 (-4.027892) | 2.358961 / 3.745712 (-1.386752) | 2.871830 / 5.269862 (-2.398031) | 1.765212 / 4.565676 (-2.800464) | 0.062172 / 0.424275 (-0.362103) | 0.004974 / 0.007607 (-0.002633) | 0.330375 / 0.226044 (0.104331) | 3.264550 / 2.268929 (0.995621) | 1.824444 / 55.444624 (-53.620181) | 1.561189 / 6.876477 (-5.315287) | 1.671020 / 2.142072 (-0.471052) | 0.633408 / 4.805227 (-4.171819) | 0.116080 / 6.500664 (-6.384584) | 0.044606 / 0.075469 (-0.030863) |\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) | 0.980757 / 1.841788 (-0.861031) | 12.553534 / 8.074308 (4.479225) | 10.517668 / 10.191392 (0.326276) | 0.130528 / 0.680424 (-0.549896) | 0.013960 / 0.534201 (-0.520241) | 0.289615 / 0.579283 (-0.289668) | 0.267277 / 0.434364 (-0.167087) | 0.324139 / 0.540337 (-0.216198) | 0.440325 / 1.386936 (-0.946611) |\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) | 0.005388 / 0.011353 (-0.005965) | 0.004043 / 0.011008 (-0.006966) | 0.050514 / 0.038508 (0.012005) | 0.031413 / 0.023109 (0.008303) | 0.275122 / 0.275898 (-0.000776) | 0.307518 / 0.323480 (-0.015962) | 0.004440 / 0.007986 (-0.003546) | 0.003301 / 0.004328 (-0.001027) | 0.049200 / 0.004250 (0.044949) | 0.045704 / 0.037052 (0.008651) | 0.285265 / 0.258489 (0.026776) | 0.318942 / 0.293841 (0.025101) | 0.053893 / 0.128546 (-0.074653) | 0.011855 / 0.075646 (-0.063791) | 0.060951 / 0.419271 (-0.358321) | 0.034397 / 0.043533 (-0.009136) | 0.276108 / 0.255139 (0.020969) | 0.290981 / 0.283200 (0.007781) | 0.019986 / 0.141683 (-0.121697) | 1.205695 / 1.452155 (-0.246460) | 1.255942 / 1.492716 (-0.236774) |\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) | 0.101910 / 0.018006 (0.083904) | 0.320551 / 0.000490 (0.320061) | 0.000299 / 0.000200 (0.000099) | 0.000058 / 0.000054 (0.000004) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.022387 / 0.037411 (-0.015024) | 0.076380 / 0.014526 (0.061854) | 0.090404 / 0.176557 (-0.086153) | 0.127106 / 0.737135 (-0.610030) | 0.089873 / 0.296338 (-0.206465) |\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) | 0.288433 / 0.215209 (0.073223) | 2.827005 / 2.077655 (0.749350) | 1.548760 / 1.504120 (0.044640) | 1.419545 / 1.541195 (-0.121650) | 1.456531 / 1.468490 (-0.011959) | 0.570254 / 4.584777 (-4.014523) | 2.441318 / 3.745712 (-1.304394) | 2.778647 / 5.269862 (-2.491215) | 1.755255 / 4.565676 (-2.810422) | 0.062581 / 0.424275 (-0.361694) | 0.005205 / 0.007607 (-0.002402) | 0.342189 / 0.226044 (0.116145) | 3.401208 / 2.268929 (1.132279) | 1.941447 / 55.444624 (-53.503178) | 1.652578 / 6.876477 (-5.223899) | 1.768558 / 2.142072 (-0.373514) | 0.656537 / 4.805227 (-4.148690) | 0.116901 / 6.500664 (-6.383763) | 0.041408 / 0.075469 (-0.034061) |\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) | 1.001715 / 1.841788 (-0.840073) | 12.533073 / 8.074308 (4.458765) | 11.086084 / 10.191392 (0.894692) | 0.134368 / 0.680424 (-0.546055) | 0.015255 / 0.534201 (-0.518946) | 0.291769 / 0.579283 (-0.287514) | 0.283311 / 0.434364 (-0.151053) | 0.327857 / 0.540337 (-0.212481) | 0.413854 / 1.386936 (-0.973083) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#46931085bd8a3fdbc63b68b5ee4b8f62029c7557 \"CML watermark\")\n" ]

[]

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