Deprecate `use_auth_token` in favor of `token`
Opened by mariosasko (closed)

... to be consistent with `transformers` and `huggingface_hub`.

Comments:
_The documentation is not available anymore as the PR was closed or merged._

<details>
<summary>Show benchmarks</summary>

PyArrow==8.0.0

<details>
<summary>Show updated benchmarks!</summary>

### Benchmark: benchmark_array_xd.json

| 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 |
|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| new / old (diff) | 0.006134 / 0.011353 (-0.005219) | 0.003816 / 0.011008 (-0.007193) | 0.098226 / 0.038508 (0.059718) | 0.036830 / 0.023109 (0.013721) | 0.314551 / 0.275898 (0.038653) | 0.372251 / 0.323480 (0.048771) | 0.004762 / 0.007986 (-0.003224) | 0.003041 / 0.004328 (-0.001287) | 0.077651 / 0.004250 (0.073401) | 0.052445 / 0.037052 (0.015393) | 0.324632 / 0.258489 (0.066143) | 0.365724 / 0.293841 (0.071883) | 0.028069 / 0.128546 (-0.100477) | 0.008444 / 0.075646 (-0.067203) | 0.312767 / 0.419271 (-0.106505) | 0.047773 / 0.043533 (0.004240) | 0.305317 / 0.255139 (0.050178) | 0.332007 / 0.283200 (0.048807) | 0.018985 / 0.141683 (-0.122698) | 1.538022 / 1.452155 (0.085868) | 1.575898 / 1.492716 (0.083182) |

### Benchmark: benchmark_getitem\_100B.json

| metric | get_batch_of\_1024\_random_rows | get_batch_of\_1024\_rows | get_first_row | get_last_row |
|--------|---|---|---|---|
| new / old (diff) | 0.204780 / 0.018006 (0.186774) | 0.428125 / 0.000490 (0.427635) | 0.003454 / 0.000200 (0.003254) | 0.000078 / 0.000054 (0.000024) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.025064 / 0.037411 (-0.012348) | 0.099419 / 0.014526 (0.084893) | 0.111068 / 0.176557 (-0.065489) | 0.169775 / 0.737135 (-0.567361) | 0.112067 / 0.296338 (-0.184271) |

### Benchmark: benchmark_iterating.json

| 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 |
|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| new / old (diff) | 0.429642 / 0.215209 (0.214433) | 4.275556 / 2.077655 (2.197901) | 1.914658 / 1.504120 (0.410539) | 1.706556 / 1.541195 (0.165361) | 1.754228 / 1.468490 (0.285738) | 0.563669 / 4.584777 (-4.021108) | 3.391501 / 3.745712 (-0.354211) | 1.791517 / 5.269862 (-3.478345) | 1.030704 / 4.565676 (-3.534973) | 0.070882 / 0.424275 (-0.353393) | 0.011351 / 0.007607 (0.003744) | 0.529438 / 0.226044 (0.303394) | 5.294316 / 2.268929 (3.025387) | 2.344653 / 55.444624 (-53.099972) | 1.997468 / 6.876477 (-4.879009) | 2.108932 / 2.142072 (-0.033140) | 0.676794 / 4.805227 (-4.128433) | 0.135058 / 6.500664 (-6.365607) | 0.065857 / 0.075469 (-0.009612) |

### Benchmark: benchmark_map_filter.json

| 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 |
|--------|---|---|---|---|---|---|---|---|---|
| new / old (diff) | 1.231864 / 1.841788 (-0.609924) | 13.986694 / 8.074308 (5.912386) | 13.306600 / 10.191392 (3.115208) | 0.145520 / 0.680424 (-0.534904) | 0.016717 / 0.534201 (-0.517484) | 0.366303 / 0.579283 (-0.212980) | 0.391637 / 0.434364 (-0.042727) | 0.425445 / 0.540337 (-0.114892) | 0.507719 / 1.386936 (-0.879217) |

</details>
PyArrow==latest

<details>
<summary>Show updated benchmarks!</summary>

### Benchmark: benchmark_array_xd.json

| 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 |
|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| new / old (diff) | 0.006236 / 0.011353 (-0.005116) | 0.003766 / 0.011008 (-0.007242) | 0.076794 / 0.038508 (0.038286) | 0.037210 / 0.023109 (0.014101) | 0.378387 / 0.275898 (0.102489) | 0.425456 / 0.323480 (0.101977) | 0.004694 / 0.007986 (-0.003291) | 0.002921 / 0.004328 (-0.001407) | 0.076985 / 0.004250 (0.072735) | 0.052188 / 0.037052 (0.015136) | 0.394385 / 0.258489 (0.135896) | 0.432527 / 0.293841 (0.138686) | 0.029091 / 0.128546 (-0.099455) | 0.008364 / 0.075646 (-0.067282) | 0.082583 / 0.419271 (-0.336689) | 0.042928 / 0.043533 (-0.000605) | 0.375321 / 0.255139 (0.120182) | 0.391719 / 0.283200 (0.108519) | 0.019388 / 0.141683 (-0.122295) | 1.550644 / 1.452155 (0.098489) | 1.604882 / 1.492716 (0.112166) |

### Benchmark: benchmark_getitem\_100B.json

| metric | get_batch_of\_1024\_random_rows | get_batch_of\_1024\_rows | get_first_row | get_last_row |
|--------|---|---|---|---|
| new / old (diff) | 0.236859 / 0.018006 (0.218853) | 0.418528 / 0.000490 (0.418039) | 0.000388 / 0.000200 (0.000188) | 0.000059 / 0.000054 (0.000004) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.025548 / 0.037411 (-0.011863) | 0.100644 / 0.014526 (0.086118) | 0.109102 / 0.176557 (-0.067455) | 0.161694 / 0.737135 (-0.575441) | 0.112088 / 0.296338 (-0.184250) |

### Benchmark: benchmark_iterating.json

| 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 |
|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| new / old (diff) | 0.484128 / 0.215209 (0.268919) | 4.849952 / 2.077655 (2.772297) | 2.512769 / 1.504120 (1.008649) | 2.303295 / 1.541195 (0.762100) | 2.356699 / 1.468490 (0.888209) | 0.564181 / 4.584777 (-4.020596) | 3.421393 / 3.745712 (-0.324319) | 2.570875 / 5.269862 (-2.698987) | 1.474307 / 4.565676 (-3.091370) | 0.068035 / 0.424275 (-0.356240) | 0.011300 / 0.007607 (0.003693) | 0.587867 / 0.226044 (0.361823) | 5.862447 / 2.268929 (3.593519) | 3.004017 / 55.444624 (-52.440607) | 2.664989 / 6.876477 (-4.211488) | 2.740020 / 2.142072 (0.597948) | 0.680840 / 4.805227 (-4.124387) | 0.137001 / 6.500664 (-6.363663) | 0.068098 / 0.075469 (-0.007371) |

### Benchmark: benchmark_map_filter.json

| 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 |
|--------|---|---|---|---|---|---|---|---|---|
| new / old (diff) | 1.297362 / 1.841788 (-0.544426) | 14.207891 / 8.074308 (6.133583) | 14.087562 / 10.191392 (3.896170) | 0.149514 / 0.680424 (-0.530910) | 0.016566 / 0.534201 (-0.517635) | 0.367602 / 0.579283 (-0.211681) | 0.400692 / 0.434364 (-0.033671) | 0.432907 / 0.540337 (-0.107431) | 0.525924 / 1.386936 (-0.861012) |

</details>
</details>

![](https://cml.dev/watermark.png#1ec069feaaf6c28d4e4df76d344693b591a74c3f "CML watermark")


<details>
<summary>Show benchmarks</summary>

PyArrow==8.0.0

<details>
<summary>Show updated benchmarks!</summary>

### Benchmark: benchmark_array_xd.json

| 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 |
|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| new / old (diff) | 0.006223 / 0.011353 (-0.005130) | 0.003672 / 0.011008 (-0.007336) | 0.097451 / 0.038508 (0.058943) | 0.036243 / 0.023109 (0.013133) | 0.375650 / 0.275898 (0.099752) | 0.431652 / 0.323480 (0.108172) | 0.004758 / 0.007986 (-0.003227) | 0.002941 / 0.004328 (-0.001387) | 0.077383 / 0.004250 (0.073132) | 0.055342 / 0.037052 (0.018289) | 0.390335 / 0.258489 (0.131846) | 0.427867 / 0.293841 (0.134026) | 0.027619 / 0.128546 (-0.100927) | 0.008244 / 0.075646 (-0.067402) | 0.313499 / 0.419271 (-0.105773) | 0.054987 / 0.043533 (0.011454) | 0.394044 / 0.255139 (0.138905) | 0.398784 / 0.283200 (0.115584) | 0.026499 / 0.141683 (-0.115184) | 1.496907 / 1.452155 (0.044753) | 1.554465 / 1.492716 (0.061749) |

### Benchmark: benchmark_getitem\_100B.json

| metric | get_batch_of\_1024\_random_rows | get_batch_of\_1024\_rows | get_first_row | get_last_row |
|--------|---|---|---|---|
| new / old (diff) | 0.241197 / 0.018006 (0.223190) | 0.427856 / 0.000490 (0.427366) | 0.006264 / 0.000200 (0.006065) | 0.000218 / 0.000054 (0.000164) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.025550 / 0.037411 (-0.011862) | 0.104426 / 0.014526 (0.089901) | 0.110310 / 0.176557 (-0.066246) | 0.173813 / 0.737135 (-0.563322) | 0.112129 / 0.296338 (-0.184209) |

### Benchmark: benchmark_iterating.json

| 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 |
|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| new / old (diff) | 0.458806 / 0.215209 (0.243597) | 4.576351 / 2.077655 (2.498697) | 2.265670 / 1.504120 (0.761550) | 2.073230 / 1.541195 (0.532035) | 2.135283 / 1.468490 (0.666793) | 0.562506 / 4.584777 (-4.022271) | 3.375101 / 3.745712 (-0.370611) | 1.734393 / 5.269862 (-3.535469) | 1.026622 / 4.565676 (-3.539054) | 0.068144 / 0.424275 (-0.356131) | 0.011092 / 0.007607 (0.003485) | 0.562779 / 0.226044 (0.336734) | 5.608256 / 2.268929 (3.339328) | 2.706468 / 55.444624 (-52.738157) | 2.381607 / 6.876477 (-4.494869) | 2.451027 / 2.142072 (0.308954) | 0.671590 / 4.805227 (-4.133637) | 0.135749 / 6.500664 (-6.364915) | 0.065389 / 0.075469 (-0.010080) |

### Benchmark: benchmark_map_filter.json

| 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 |
|--------|---|---|---|---|---|---|---|---|---|
| new / old (diff) | 1.244806 / 1.841788 (-0.596981) | 14.042150 / 8.074308 (5.967841) | 14.246612 / 10.191392 (4.055220) | 0.134309 / 0.680424 (-0.546114) | 0.017082 / 0.534201 (-0.517119) | 0.366043 / 0.579283 (-0.213240) | 0.400748 / 0.434364 (-0.033616) | 0.425695 / 0.540337 (-0.114643) | 0.509355 / 1.386936 (-0.877581) |

</details>
PyArrow==latest

<details>
<summary>Show updated benchmarks!</summary>

### Benchmark: benchmark_array_xd.json

| 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 |
|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| new / old (diff) | 0.006134 / 0.011353 (-0.005219) | 0.003980 / 0.011008 (-0.007028) | 0.078353 / 0.038508 (0.039845) | 0.038011 / 0.023109 (0.014902) | 0.375784 / 0.275898 (0.099886) | 0.433619 / 0.323480 (0.110139) | 0.004897 / 0.007986 (-0.003088) | 0.002981 / 0.004328 (-0.001347) | 0.077362 / 0.004250 (0.073112) | 0.056108 / 0.037052 (0.019056) | 0.395984 / 0.258489 (0.137495) | 0.427397 / 0.293841 (0.133556) | 0.029325 / 0.128546 (-0.099221) | 0.008498 / 0.075646 (-0.067148) | 0.082478 / 0.419271 (-0.336794) | 0.044085 / 0.043533 (0.000552) | 0.389923 / 0.255139 (0.134784) | 0.391180 / 0.283200 (0.107980) | 0.022452 / 0.141683 (-0.119231) | 1.507758 / 1.452155 (0.055603) | 1.530459 / 1.492716 (0.037743) |

### Benchmark: benchmark_getitem\_100B.json

| metric | get_batch_of\_1024\_random_rows | get_batch_of\_1024\_rows | get_first_row | get_last_row |
|--------|---|---|---|---|
| new / old (diff) | 0.230928 / 0.018006 (0.212922) | 0.408484 / 0.000490 (0.407995) | 0.000806 / 0.000200 (0.000606) | 0.000067 / 0.000054 (0.000012) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.025183 / 0.037411 (-0.012228) | 0.102292 / 0.014526 (0.087766) | 0.108142 / 0.176557 (-0.068415) | 0.161172 / 0.737135 (-0.575963) | 0.114476 / 0.296338 (-0.181862) |

### Benchmark: benchmark_iterating.json

| 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 |
|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| new / old (diff) | 0.482978 / 0.215209 (0.267769) | 4.816103 / 2.077655 (2.738448) | 2.505567 / 1.504120 (1.001447) | 2.302598 / 1.541195 (0.761404) | 2.371238 / 1.468490 (0.902748) | 0.567467 / 4.584777 (-4.017310) | 3.363407 / 3.745712 (-0.382306) | 1.746213 / 5.269862 (-3.523649) | 1.035468 / 4.565676 (-3.530208) | 0.068431 / 0.424275 (-0.355844) | 0.011069 / 0.007607 (0.003462) | 0.598241 / 0.226044 (0.372196) | 5.953927 / 2.268929 (3.684999) | 3.007493 / 55.444624 (-52.437132) | 2.629399 / 6.876477 (-4.247078) | 2.737201 / 2.142072 (0.595129) | 0.682456 / 4.805227 (-4.122771) | 0.137613 / 6.500664 (-6.363051) | 0.067941 / 0.075469 (-0.007528) |

### Benchmark: benchmark_map_filter.json

| 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 |
|--------|---|---|---|---|---|---|---|---|---|
| new / old (diff) | 1.306015 / 1.841788 (-0.535772) | 14.359240 / 8.074308 (6.284932) | 14.187601 / 10.191392 (3.996209) | 0.138612 / 0.680424 (-0.541812) | 0.016708 / 0.534201 (-0.517493) | 0.366365 / 0.579283 (-0.212918) | 0.396982 / 0.434364 (-0.037382) | 0.426939 / 0.540337 (-0.113398) | 0.520064 / 1.386936 (-0.866872) |

</details>
</details>

![](https://cml.dev/watermark.png#21d0fd041a5eca02d3ee787396216ac613c662ac "CML watermark")


They use `token` and emit a deprecation warning if `use_auth_token` is passed instead (see https://github.com/huggingface/transformers/blob/78a2b19fc84ed55c65f4bf20a901edb7ceb73c5f/src/transformers/modeling_utils.py#L1933). 

I think we can update the `examples` scripts after merging this PR.

> I think we can update the examples scripts after merging this PR.

We should do a release before updated in the examples scripts no ? That's why it's an option to not have a deprecation warning until transformers and co are updated with the `token` arg

> We should do a release before updated in the examples scripts no ? That's why it's an option to not have a deprecation warning until transformers and co are updated with the token arg

This would avoid the warning only for the latest `datasets` release. TBH, I don't think this is worth the hassle, considering how simple it is to remove it.

<details>
<summary>Show benchmarks</summary>

PyArrow==8.0.0

<details>
<summary>Show updated benchmarks!</summary>

### Benchmark: benchmark_array_xd.json

| 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 |
|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| new / old (diff) | 0.007644 / 0.011353 (-0.003709) | 0.004667 / 0.011008 (-0.006341) | 0.117347 / 0.038508 (0.078839) | 0.050620 / 0.023109 (0.027510) | 0.415402 / 0.275898 (0.139504) | 0.485898 / 0.323480 (0.162418) | 0.005848 / 0.007986 (-0.002138) | 0.003736 / 0.004328 (-0.000592) | 0.089798 / 0.004250 (0.085547) | 0.069344 / 0.037052 (0.032292) | 0.441684 / 0.258489 (0.183195) | 0.468972 / 0.293841 (0.175131) | 0.036637 / 0.128546 (-0.091909) | 0.010219 / 0.075646 (-0.065427) | 0.394293 / 0.419271 (-0.024978) | 0.061462 / 0.043533 (0.017929) | 0.409448 / 0.255139 (0.154309) | 0.431557 / 0.283200 (0.148358) | 0.027795 / 0.141683 (-0.113888) | 1.837844 / 1.452155 (0.385690) | 1.862683 / 1.492716 (0.369967) |

### Benchmark: benchmark_getitem\_100B.json

| metric | get_batch_of\_1024\_random_rows | get_batch_of\_1024\_rows | get_first_row | get_last_row |
|--------|---|---|---|---|
| new / old (diff) | 0.230500 / 0.018006 (0.212494) | 0.483139 / 0.000490 (0.482649) | 0.006517 / 0.000200 (0.006317) | 0.000143 / 0.000054 (0.000088) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.033152 / 0.037411 (-0.004259) | 0.133673 / 0.014526 (0.119147) | 0.143853 / 0.176557 (-0.032704) | 0.215254 / 0.737135 (-0.521882) | 0.150676 / 0.296338 (-0.145662) |

### Benchmark: benchmark_iterating.json

| 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 |
|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| new / old (diff) | 0.503796 / 0.215209 (0.288587) | 5.049981 / 2.077655 (2.972326) | 2.399427 / 1.504120 (0.895307) | 2.167635 / 1.541195 (0.626441) | 2.257448 / 1.468490 (0.788958) | 0.641298 / 4.584777 (-3.943479) | 4.828676 / 3.745712 (1.082964) | 4.346069 / 5.269862 (-0.923793) | 2.103890 / 4.565676 (-2.461786) | 0.079115 / 0.424275 (-0.345160) | 0.013377 / 0.007607 (0.005770) | 0.621207 / 0.226044 (0.395162) | 6.190939 / 2.268929 (3.922011) | 2.920129 / 55.444624 (-52.524495) | 2.549225 / 6.876477 (-4.327252) | 2.719221 / 2.142072 (0.577149) | 0.790949 / 4.805227 (-4.014278) | 0.172032 / 6.500664 (-6.328632) | 0.077779 / 0.075469 (0.002310) |

### Benchmark: benchmark_map_filter.json

| 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 |
|--------|---|---|---|---|---|---|---|---|---|
| new / old (diff) | 1.432572 / 1.841788 (-0.409216) | 21.000031 / 8.074308 (12.925723) | 17.555093 / 10.191392 (7.363701) | 0.166646 / 0.680424 (-0.513778) | 0.020451 / 0.534201 (-0.513750) | 0.488767 / 0.579283 (-0.090516) | 0.737036 / 0.434364 (0.302672) | 0.621694 / 0.540337 (0.081356) | 0.732074 / 1.386936 (-0.654862) |

</details>
PyArrow==latest

<details>
<summary>Show updated benchmarks!</summary>

### Benchmark: benchmark_array_xd.json

| 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 |
|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| new / old (diff) | 0.008198 / 0.011353 (-0.003155) | 0.004987 / 0.011008 (-0.006021) | 0.090714 / 0.038508 (0.052206) | 0.053379 / 0.023109 (0.030270) | 0.425199 / 0.275898 (0.149301) | 0.514036 / 0.323480 (0.190556) | 0.006043 / 0.007986 (-0.001943) | 0.003888 / 0.004328 (-0.000441) | 0.088294 / 0.004250 (0.084043) | 0.073024 / 0.037052 (0.035971) | 0.435983 / 0.258489 (0.177494) | 0.514293 / 0.293841 (0.220452) | 0.039451 / 0.128546 (-0.089095) | 0.010439 / 0.075646 (-0.065207) | 0.096885 / 0.419271 (-0.322387) | 0.060165 / 0.043533 (0.016632) | 0.421053 / 0.255139 (0.165914) | 0.455545 / 0.283200 (0.172345) | 0.027234 / 0.141683 (-0.114449) | 1.768975 / 1.452155 (0.316820) | 1.842853 / 1.492716 (0.350137) |

### Benchmark: benchmark_getitem\_100B.json

| metric | get_batch_of\_1024\_random_rows | get_batch_of\_1024\_rows | get_first_row | get_last_row |
|--------|---|---|---|---|
| new / old (diff) | 0.278940 / 0.018006 (0.260933) | 0.480709 / 0.000490 (0.480219) | 0.000436 / 0.000200 (0.000236) | 0.000070 / 0.000054 (0.000016) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.034900 / 0.037411 (-0.002511) | 0.144893 / 0.014526 (0.130368) | 0.149567 / 0.176557 (-0.026989) | 0.213200 / 0.737135 (-0.523935) | 0.156735 / 0.296338 (-0.139604) |

### Benchmark: benchmark_iterating.json

| 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 |
|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| new / old (diff) | 0.535897 / 0.215209 (0.320687) | 5.336998 / 2.077655 (3.259343) | 2.685854 / 1.504120 (1.181734) | 2.470177 / 1.541195 (0.928983) | 2.547495 / 1.468490 (1.079004) | 0.642830 / 4.584777 (-3.941947) | 4.595866 / 3.745712 (0.850154) | 2.186696 / 5.269862 (-3.083165) | 1.317969 / 4.565676 (-3.247708) | 0.079268 / 0.424275 (-0.345007) | 0.013792 / 0.007607 (0.006185) | 0.662236 / 0.226044 (0.436192) | 6.604775 / 2.268929 (4.335847) | 3.355888 / 55.444624 (-52.088736) | 2.968911 / 6.876477 (-3.907565) | 3.121862 / 2.142072 (0.979790) | 0.794752 / 4.805227 (-4.010475) | 0.170800 / 6.500664 (-6.329864) | 0.078393 / 0.075469 (0.002924) |

### Benchmark: benchmark_map_filter.json

| 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 |
|--------|---|---|---|---|---|---|---|---|---|
| new / old (diff) | 1.601605 / 1.841788 (-0.240183) | 20.743553 / 8.074308 (12.669245) | 17.543968 / 10.191392 (7.352576) | 0.221884 / 0.680424 (-0.458540) | 0.020779 / 0.534201 (-0.513422) | 0.479677 / 0.579283 (-0.099606) | 0.516207 / 0.434364 (0.081843) | 0.564046 / 0.540337 (0.023709) | 0.711336 / 1.386936 (-0.675600) |

</details>
</details>

![](https://cml.dev/watermark.png#819bb4346434912eb405ce3f3e9f21dc25a2fe85 "CML watermark")


Yes, sounds great! Thanks

yup