Minor multi gpu doc improvement
State: closed | Author: lhoestq (MEMBER)

just added torch.no_grad and eval()

Comments: The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6649). 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) | 0.005197 / 0.011353 (-0.006156) | 0.003469 / 0.011008 (-0.007539) | 0.062306 / 0.038508 (0.023798) | 0.028417 / 0.023109 (0.005308) | 0.241147 / 0.275898 (-0.034751) | 0.270910 / 0.323480 (-0.052569) | 0.003053 / 0.007986 (-0.004933) | 0.003343 / 0.004328 (-0.000985) | 0.048044 / 0.004250 (0.043794) | 0.043738 / 0.037052 (0.006686) | 0.259274 / 0.258489 (0.000785) | 0.282522 / 0.293841 (-0.011319) | 0.027807 / 0.128546 (-0.100739) | 0.010413 / 0.075646 (-0.065234) | 0.206322 / 0.419271 (-0.212950) | 0.035770 / 0.043533 (-0.007763) | 0.243465 / 0.255139 (-0.011674) | 0.261596 / 0.283200 (-0.021604) | 0.018613 / 0.141683 (-0.123070) | 1.115509 / 1.452155 (-0.336645) | 1.189403 / 1.492716 (-0.303314) |

### 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) | 0.086075 / 0.018006 (0.068069) | 0.296140 / 0.000490 (0.295650) | 0.000198 / 0.000200 (-0.000002) | 0.000050 / 0.000054 (-0.000004) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.018238 / 0.037411 (-0.019173) | 0.061783 / 0.014526 (0.047257) | 0.072014 / 0.176557 (-0.104543) | 0.118746 / 0.737135 (-0.618389) | 0.073279 / 0.296338 (-0.223060) |

### 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) | 0.278281 / 0.215209 (0.063072) | 2.772209 / 2.077655 (0.694555) | 1.404503 / 1.504120 (-0.099617) | 1.274753 / 1.541195 (-0.266441) | 1.304394 / 1.468490 (-0.164096) | 0.556903 / 4.584777 (-4.027874) | 2.335428 / 3.745712 (-1.410284) | 2.712255 / 5.269862 (-2.557606) | 1.722252 / 4.565676 (-2.843425) | 0.061268 / 0.424275 (-0.363007) | 0.005029 / 0.007607 (-0.002578) | 0.326112 / 0.226044 (0.100067) | 3.207917 / 2.268929 (0.938988) | 1.743513 / 55.444624 (-53.701111) | 1.476418 / 6.876477 (-5.400059) | 1.489776 / 2.142072 (-0.652297) | 0.628181 / 4.805227 (-4.177046) | 0.115959 / 6.500664 (-6.384706) | 0.041854 / 0.075469 (-0.033615) |

### 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) | 0.969039 / 1.841788 (-0.872749) | 11.178646 / 8.074308 (3.104338) | 9.639716 / 10.191392 (-0.551676) | 0.139750 / 0.680424 (-0.540674) | 0.014230 / 0.534201 (-0.519971) | 0.285318 / 0.579283 (-0.293965) | 0.260788 / 0.434364 (-0.173576) | 0.324183 / 0.540337 (-0.216154) | 0.416326 / 1.386936 (-0.970610) |

</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) | 0.005149 / 0.011353 (-0.006204) | 0.003469 / 0.011008 (-0.007539) | 0.049761 / 0.038508 (0.011253) | 0.030723 / 0.023109 (0.007614) | 0.271562 / 0.275898 (-0.004336) | 0.297843 / 0.323480 (-0.025637) | 0.004296 / 0.007986 (-0.003690) | 0.002704 / 0.004328 (-0.001624) | 0.048890 / 0.004250 (0.044640) | 0.044776 / 0.037052 (0.007723) | 0.285490 / 0.258489 (0.027001) | 0.312888 / 0.293841 (0.019047) | 0.046239 / 0.128546 (-0.082307) | 0.010238 / 0.075646 (-0.065408) | 0.057968 / 0.419271 (-0.361304) | 0.033295 / 0.043533 (-0.010238) | 0.274320 / 0.255139 (0.019181) | 0.296199 / 0.283200 (0.012999) | 0.017856 / 0.141683 (-0.123827) | 1.147532 / 1.452155 (-0.304622) | 1.211647 / 1.492716 (-0.281070) |

### 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) | 0.089655 / 0.018006 (0.071649) | 0.297275 / 0.000490 (0.296785) | 0.000207 / 0.000200 (0.000007) | 0.000043 / 0.000054 (-0.000012) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.021739 / 0.037411 (-0.015672) | 0.075041 / 0.014526 (0.060515) | 0.085754 / 0.176557 (-0.090802) | 0.124512 / 0.737135 (-0.612623) | 0.086926 / 0.296338 (-0.209412) |

### 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) | 0.290306 / 0.215209 (0.075097) | 2.847404 / 2.077655 (0.769749) | 1.606175 / 1.504120 (0.102055) | 1.483220 / 1.541195 (-0.057974) | 1.514551 / 1.468490 (0.046061) | 0.559332 / 4.584777 (-4.025445) | 2.403089 / 3.745712 (-1.342624) | 2.715179 / 5.269862 (-2.554683) | 1.688340 / 4.565676 (-2.877337) | 0.062057 / 0.424275 (-0.362218) | 0.004955 / 0.007607 (-0.002652) | 0.338909 / 0.226044 (0.112865) | 3.356882 / 2.268929 (1.087954) | 1.942259 / 55.444624 (-53.502366) | 1.675195 / 6.876477 (-5.201282) | 1.688158 / 2.142072 (-0.453914) | 0.637270 / 4.805227 (-4.167957) | 0.114314 / 6.500664 (-6.386350) | 0.040677 / 0.075469 (-0.034792) |

### 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) | 1.022126 / 1.841788 (-0.819661) | 11.783359 / 8.074308 (3.709051) | 10.247652 / 10.191392 (0.056260) | 0.138188 / 0.680424 (-0.542236) | 0.014850 / 0.534201 (-0.519351) | 0.287414 / 0.579283 (-0.291869) | 0.274393 / 0.434364 (-0.159971) | 0.327255 / 0.540337 (-0.213082) | 0.416355 / 1.386936 (-0.970581) |

</details>
</details>

![](https://cml.dev/watermark.png#727a952367966a98b759d54f333b1e2c28cfd4d4 "CML watermark")