Issue: Fix hf-internal-testing/dataset_with_script commit SHA in CI test
State: closed
Author: albertvillanova

Fix test using latest commit SHA in hf-internal-testing/dataset_with_script dataset: https://huggingface.co/datasets/hf-internal-testing/dataset_with_script/commits/refs%2Fconvert%2Fparquet

Fix #6796.

Comments:
The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6806). 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) | 0.005068 / 0.011353 (-0.006285) | 0.003613 / 0.011008 (-0.007395) | 0.063226 / 0.038508 (0.024718) | 0.030653 / 0.023109 (0.007544) | 0.243981 / 0.275898 (-0.031918) | 0.268596 / 0.323480 (-0.054884) | 0.003109 / 0.007986 (-0.004876) | 0.003292 / 0.004328 (-0.001036) | 0.048857 / 0.004250 (0.044606) | 0.043929 / 0.037052 (0.006876) | 0.264002 / 0.258489 (0.005513) | 0.289028 / 0.293841 (-0.004813) | 0.028053 / 0.128546 (-0.100493) | 0.010837 / 0.075646 (-0.064809) | 0.208084 / 0.419271 (-0.211188) | 0.035592 / 0.043533 (-0.007941) | 0.252639 / 0.255139 (-0.002500) | 0.267599 / 0.283200 (-0.015600) | 0.018097 / 0.141683 (-0.123585) | 1.150811 / 1.452155 (-0.301344) | 1.219449 / 1.492716 (-0.273267) |

### 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) | 0.095427 / 0.018006 (0.077421) | 0.307270 / 0.000490 (0.306781) | 0.000218 / 0.000200 (0.000018) | 0.000043 / 0.000054 (-0.000011) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.018713 / 0.037411 (-0.018698) | 0.065238 / 0.014526 (0.050712) | 0.074650 / 0.176557 (-0.101906) | 0.120130 / 0.737135 (-0.617005) | 0.078457 / 0.296338 (-0.217882) |

### 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) | 0.283666 / 0.215209 (0.068457) | 2.852818 / 2.077655 (0.775163) | 1.459790 / 1.504120 (-0.044330) | 1.326732 / 1.541195 (-0.214463) | 1.373530 / 1.468490 (-0.094960) | 0.579136 / 4.584777 (-4.005641) | 2.388369 / 3.745712 (-1.357343) | 2.813786 / 5.269862 (-2.456075) | 1.730079 / 4.565676 (-2.835597) | 0.063445 / 0.424275 (-0.360831) | 0.005355 / 0.007607 (-0.002252) | 0.340169 / 0.226044 (0.114124) | 3.391220 / 2.268929 (1.122291) | 1.838003 / 55.444624 (-53.606621) | 1.523518 / 6.876477 (-5.352959) | 1.574007 / 2.142072 (-0.568065) | 0.650265 / 4.805227 (-4.154962) | 0.117114 / 6.500664 (-6.383550) | 0.042430 / 0.075469 (-0.033039) |

### 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) | 0.955596 / 1.841788 (-0.886191) | 11.546544 / 8.074308 (3.472236) | 9.593613 / 10.191392 (-0.597779) | 0.141502 / 0.680424 (-0.538922) | 0.014251 / 0.534201 (-0.519950) | 0.293825 / 0.579283 (-0.285458) | 0.263088 / 0.434364 (-0.171276) | 0.325035 / 0.540337 (-0.215302) | 0.419372 / 1.386936 (-0.967564) |

</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) | 0.005567 / 0.011353 (-0.005785) | 0.003670 / 0.011008 (-0.007338) | 0.050338 / 0.038508 (0.011830) | 0.031730 / 0.023109 (0.008621) | 0.278307 / 0.275898 (0.002409) | 0.303170 / 0.323480 (-0.020310) | 0.004276 / 0.007986 (-0.003709) | 0.002720 / 0.004328 (-0.001609) | 0.048675 / 0.004250 (0.044425) | 0.041026 / 0.037052 (0.003974) | 0.291353 / 0.258489 (0.032864) | 0.318487 / 0.293841 (0.024646) | 0.029676 / 0.128546 (-0.098870) | 0.010428 / 0.075646 (-0.065218) | 0.057443 / 0.419271 (-0.361828) | 0.032735 / 0.043533 (-0.010798) | 0.282900 / 0.255139 (0.027761) | 0.297539 / 0.283200 (0.014339) | 0.018237 / 0.141683 (-0.123446) | 1.188047 / 1.452155 (-0.264107) | 1.223283 / 1.492716 (-0.269433) |

### 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) | 0.090629 / 0.018006 (0.072623) | 0.300898 / 0.000490 (0.300408) | 0.000212 / 0.000200 (0.000012) | 0.000133 / 0.000054 (0.000078) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.022200 / 0.037411 (-0.015211) | 0.075310 / 0.014526 (0.060784) | 0.086790 / 0.176557 (-0.089766) | 0.127392 / 0.737135 (-0.609744) | 0.088435 / 0.296338 (-0.207903) |

### 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) | 0.301308 / 0.215209 (0.086099) | 2.963126 / 2.077655 (0.885471) | 1.639604 / 1.504120 (0.135484) | 1.508776 / 1.541195 (-0.032419) | 1.553280 / 1.468490 (0.084789) | 0.567256 / 4.584777 (-4.017520) | 2.445231 / 3.745712 (-1.300482) | 2.884071 / 5.269862 (-2.385791) | 1.777321 / 4.565676 (-2.788355) | 0.063659 / 0.424275 (-0.360616) | 0.005435 / 0.007607 (-0.002172) | 0.361786 / 0.226044 (0.135742) | 3.624264 / 2.268929 (1.355335) | 2.022661 / 55.444624 (-53.421963) | 1.740581 / 6.876477 (-5.135896) | 1.748503 / 2.142072 (-0.393570) | 0.660783 / 4.805227 (-4.144444) | 0.118045 / 6.500664 (-6.382619) | 0.040940 / 0.075469 (-0.034529) |

### 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) | 1.015614 / 1.841788 (-0.826174) | 12.094985 / 8.074308 (4.020677) | 10.435581 / 10.191392 (0.244189) | 0.140239 / 0.680424 (-0.540185) | 0.014992 / 0.534201 (-0.519209) | 0.290549 / 0.579283 (-0.288735) | 0.274718 / 0.434364 (-0.159645) | 0.334783 / 0.540337 (-0.205554) | 0.426540 / 1.386936 (-0.960396) |

</details>
</details>

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