Title: Revert ci user
Author: lhoestq (MEMBER)
State: closed
Created: 2024-05-30T10:45:26Z


Comments:
The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6934). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.

<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) | 0.005218 / 0.011353 (-0.006135) | 0.003313 / 0.011008 (-0.007695) | 0.062992 / 0.038508 (0.024484) | 0.029621 / 0.023109 (0.006512) | 0.244421 / 0.275898 (-0.031477) | 0.267178 / 0.323480 (-0.056302) | 0.002986 / 0.007986 (-0.005000) | 0.002607 / 0.004328 (-0.001721) | 0.049149 / 0.004250 (0.044898) | 0.045362 / 0.037052 (0.008310) | 0.252862 / 0.258489 (-0.005627) | 0.286326 / 0.293841 (-0.007515) | 0.027888 / 0.128546 (-0.100658) | 0.010295 / 0.075646 (-0.065352) | 0.205525 / 0.419271 (-0.213746) | 0.036696 / 0.043533 (-0.006837) | 0.248716 / 0.255139 (-0.006423) | 0.263803 / 0.283200 (-0.019397) | 0.016926 / 0.141683 (-0.124757) | 1.123093 / 1.452155 (-0.329062) | 1.155434 / 1.492716 (-0.337282) |

### 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) | 0.092349 / 0.018006 (0.074343) | 0.298154 / 0.000490 (0.297664) | 0.000213 / 0.000200 (0.000013) | 0.000052 / 0.000054 (-0.000003) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.018496 / 0.037411 (-0.018915) | 0.061983 / 0.014526 (0.047457) | 0.075043 / 0.176557 (-0.101514) | 0.120678 / 0.737135 (-0.616457) | 0.074917 / 0.296338 (-0.221422) |

### 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) | 0.290558 / 0.215209 (0.075349) | 2.842635 / 2.077655 (0.764981) | 1.485761 / 1.504120 (-0.018359) | 1.346948 / 1.541195 (-0.194247) | 1.352424 / 1.468490 (-0.116066) | 0.564567 / 4.584777 (-4.020210) | 2.393583 / 3.745712 (-1.352129) | 2.654061 / 5.269862 (-2.615800) | 1.729154 / 4.565676 (-2.836523) | 0.064652 / 0.424275 (-0.359623) | 0.004973 / 0.007607 (-0.002634) | 0.334924 / 0.226044 (0.108879) | 3.330518 / 2.268929 (1.061590) | 1.773848 / 55.444624 (-53.670776) | 1.513796 / 6.876477 (-5.362681) | 1.676492 / 2.142072 (-0.465580) | 0.650551 / 4.805227 (-4.154677) | 0.118423 / 6.500664 (-6.382241) | 0.042700 / 0.075469 (-0.032769) |

### 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) | 0.943394 / 1.841788 (-0.898394) | 11.235766 / 8.074308 (3.161458) | 9.896586 / 10.191392 (-0.294806) | 0.130174 / 0.680424 (-0.550249) | 0.014148 / 0.534201 (-0.520053) | 0.284002 / 0.579283 (-0.295281) | 0.261354 / 0.434364 (-0.173010) | 0.320839 / 0.540337 (-0.219499) | 0.422399 / 1.386936 (-0.964537) |

</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) | 0.005496 / 0.011353 (-0.005857) | 0.003603 / 0.011008 (-0.007406) | 0.050104 / 0.038508 (0.011596) | 0.032939 / 0.023109 (0.009830) | 0.265643 / 0.275898 (-0.010255) | 0.291819 / 0.323480 (-0.031661) | 0.004273 / 0.007986 (-0.003713) | 0.002715 / 0.004328 (-0.001613) | 0.049191 / 0.004250 (0.044941) | 0.040782 / 0.037052 (0.003730) | 0.276562 / 0.258489 (0.018072) | 0.314307 / 0.293841 (0.020466) | 0.029878 / 0.128546 (-0.098669) | 0.010134 / 0.075646 (-0.065513) | 0.058686 / 0.419271 (-0.360585) | 0.033562 / 0.043533 (-0.009971) | 0.265961 / 0.255139 (0.010822) | 0.282009 / 0.283200 (-0.001191) | 0.018956 / 0.141683 (-0.122727) | 1.149668 / 1.452155 (-0.302487) | 1.192242 / 1.492716 (-0.300474) |

### 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) | 0.089449 / 0.018006 (0.071443) | 0.300346 / 0.000490 (0.299856) | 0.000198 / 0.000200 (-0.000001) | 0.000044 / 0.000054 (-0.000011) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.022094 / 0.037411 (-0.015317) | 0.075987 / 0.014526 (0.061461) | 0.088191 / 0.176557 (-0.088365) | 0.127698 / 0.737135 (-0.609437) | 0.089642 / 0.296338 (-0.206696) |

### 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) | 0.299127 / 0.215209 (0.083918) | 2.961219 / 2.077655 (0.883565) | 1.589108 / 1.504120 (0.084988) | 1.464060 / 1.541195 (-0.077135) | 1.475249 / 1.468490 (0.006759) | 0.569041 / 4.584777 (-4.015736) | 0.966965 / 3.745712 (-2.778747) | 2.653049 / 5.269862 (-2.616813) | 1.733650 / 4.565676 (-2.832026) | 0.062537 / 0.424275 (-0.361738) | 0.005003 / 0.007607 (-0.002605) | 0.353345 / 0.226044 (0.127301) | 3.432888 / 2.268929 (1.163960) | 1.953217 / 55.444624 (-53.491407) | 1.651995 / 6.876477 (-5.224482) | 1.764549 / 2.142072 (-0.377523) | 0.647255 / 4.805227 (-4.157973) | 0.116827 / 6.500664 (-6.383837) | 0.040765 / 0.075469 (-0.034704) |

### 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) | 0.985490 / 1.841788 (-0.856298) | 11.965147 / 8.074308 (3.890839) | 10.488286 / 10.191392 (0.296894) | 0.142134 / 0.680424 (-0.538290) | 0.015415 / 0.534201 (-0.518786) | 0.289864 / 0.579283 (-0.289419) | 0.122778 / 0.434364 (-0.311586) | 0.328691 / 0.540337 (-0.211647) | 0.422677 / 1.386936 (-0.964259) |

</details>
</details>

![](https://cml.dev/watermark.png#456f790d2c2e9181bc305ab3d54fe2ca58742b9b "CML watermark")


There was an incident in hub-ci that invalidated our token. It's been fixed so I reverted this change