Title: Fix CI
Author: mariosasko (COLLABORATOR)
State: closed
Created: 2024-04-04T17:45:04Z

Updates the `wmt_t2t` test to pin the `revision` to the version with a loading script (cc @albertvillanova). 

Additionally, it replaces the occurrences of the `lhoestq/test` repo id with `hf-internal-testing/dataset_with_script` and re-enables logging checks in the `Dataset.from_sql` tests.

Comments:
The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6780). 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) | 0.005074 / 0.011353 (-0.006279) | 0.003395 / 0.011008 (-0.007614) | 0.062358 / 0.038508 (0.023849) | 0.031041 / 0.023109 (0.007932) | 0.244039 / 0.275898 (-0.031859) | 0.266361 / 0.323480 (-0.057119) | 0.003201 / 0.007986 (-0.004785) | 0.002609 / 0.004328 (-0.001719) | 0.049269 / 0.004250 (0.045018) | 0.045713 / 0.037052 (0.008661) | 0.264075 / 0.258489 (0.005586) | 0.295428 / 0.293841 (0.001587) | 0.027882 / 0.128546 (-0.100664) | 0.010424 / 0.075646 (-0.065222) | 0.208417 / 0.419271 (-0.210854) | 0.035728 / 0.043533 (-0.007805) | 0.246803 / 0.255139 (-0.008336) | 0.267169 / 0.283200 (-0.016031) | 0.019797 / 0.141683 (-0.121885) | 1.163299 / 1.452155 (-0.288856) | 1.196118 / 1.492716 (-0.296599) |

### 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) | 0.106091 / 0.018006 (0.088085) | 0.303970 / 0.000490 (0.303480) | 0.000219 / 0.000200 (0.000019) | 0.000042 / 0.000054 (-0.000012) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.017955 / 0.037411 (-0.019456) | 0.060539 / 0.014526 (0.046013) | 0.072884 / 0.176557 (-0.103673) | 0.119205 / 0.737135 (-0.617931) | 0.074072 / 0.296338 (-0.222266) |

### 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) | 0.272676 / 0.215209 (0.057467) | 2.715169 / 2.077655 (0.637514) | 1.419090 / 1.504120 (-0.085030) | 1.303903 / 1.541195 (-0.237292) | 1.311903 / 1.468490 (-0.156587) | 0.562005 / 4.584777 (-4.022772) | 2.432817 / 3.745712 (-1.312896) | 2.770599 / 5.269862 (-2.499263) | 1.723043 / 4.565676 (-2.842633) | 0.064341 / 0.424275 (-0.359934) | 0.004923 / 0.007607 (-0.002684) | 0.330507 / 0.226044 (0.104463) | 3.240829 / 2.268929 (0.971901) | 1.787638 / 55.444624 (-53.656986) | 1.522971 / 6.876477 (-5.353506) | 1.529496 / 2.142072 (-0.612576) | 0.645768 / 4.805227 (-4.159459) | 0.116405 / 6.500664 (-6.384259) | 0.041524 / 0.075469 (-0.033945) |

### 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) | 0.968515 / 1.841788 (-0.873272) | 11.628911 / 8.074308 (3.554603) | 9.495023 / 10.191392 (-0.696369) | 0.142219 / 0.680424 (-0.538204) | 0.013859 / 0.534201 (-0.520342) | 0.285727 / 0.579283 (-0.293556) | 0.276842 / 0.434364 (-0.157522) | 0.321247 / 0.540337 (-0.219090) | 0.409958 / 1.386936 (-0.976978) |

</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) | 0.005102 / 0.011353 (-0.006251) | 0.003213 / 0.011008 (-0.007796) | 0.049250 / 0.038508 (0.010742) | 0.030649 / 0.023109 (0.007540) | 0.276629 / 0.275898 (0.000731) | 0.297315 / 0.323480 (-0.026165) | 0.004198 / 0.007986 (-0.003787) | 0.002744 / 0.004328 (-0.001585) | 0.047899 / 0.004250 (0.043649) | 0.040596 / 0.037052 (0.003544) | 0.287248 / 0.258489 (0.028759) | 0.313573 / 0.293841 (0.019732) | 0.029067 / 0.128546 (-0.099480) | 0.010122 / 0.075646 (-0.065524) | 0.058869 / 0.419271 (-0.360402) | 0.033012 / 0.043533 (-0.010521) | 0.272995 / 0.255139 (0.017856) | 0.297102 / 0.283200 (0.013903) | 0.018209 / 0.141683 (-0.123474) | 1.157785 / 1.452155 (-0.294369) | 1.184999 / 1.492716 (-0.307717) |

### 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) | 0.094228 / 0.018006 (0.076221) | 0.302055 / 0.000490 (0.301565) | 0.000221 / 0.000200 (0.000021) | 0.000044 / 0.000054 (-0.000010) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.022020 / 0.037411 (-0.015391) | 0.074970 / 0.014526 (0.060444) | 0.087682 / 0.176557 (-0.088875) | 0.126506 / 0.737135 (-0.610629) | 0.092046 / 0.296338 (-0.204293) |

### 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) | 0.295634 / 0.215209 (0.080425) | 2.891554 / 2.077655 (0.813899) | 1.579963 / 1.504120 (0.075843) | 1.462924 / 1.541195 (-0.078271) | 1.463806 / 1.468490 (-0.004684) | 0.558371 / 4.584777 (-4.026406) | 2.513500 / 3.745712 (-1.232212) | 2.754146 / 5.269862 (-2.515716) | 1.762317 / 4.565676 (-2.803360) | 0.063965 / 0.424275 (-0.360310) | 0.005538 / 0.007607 (-0.002069) | 0.348114 / 0.226044 (0.122070) | 3.484558 / 2.268929 (1.215630) | 1.940002 / 55.444624 (-53.504623) | 1.658469 / 6.876477 (-5.218008) | 1.645777 / 2.142072 (-0.496295) | 0.639367 / 4.805227 (-4.165861) | 0.115605 / 6.500664 (-6.385059) | 0.040647 / 0.075469 (-0.034822) |

### 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) | 1.036002 / 1.841788 (-0.805786) | 12.286895 / 8.074308 (4.212587) | 10.146719 / 10.191392 (-0.044673) | 0.140867 / 0.680424 (-0.539557) | 0.015517 / 0.534201 (-0.518684) | 0.290126 / 0.579283 (-0.289157) | 0.298702 / 0.434364 (-0.135662) | 0.325518 / 0.540337 (-0.214819) | 0.412597 / 1.386936 (-0.974339) |

</details>
</details>

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