Title: Fix tests based on datasets that used to have scripts
State: closed

...now that `squad` and `paws` don't have a script anymore

Comments: The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6574). 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) | 0.005447 / 0.011353 (-0.005906) | 0.004030 / 0.011008 (-0.006978) | 0.063770 / 0.038508 (0.025262) | 0.032602 / 0.023109 (0.009493) | 0.247722 / 0.275898 (-0.028176) | 0.286507 / 0.323480 (-0.036973) | 0.003035 / 0.007986 (-0.004951) | 0.003638 / 0.004328 (-0.000690) | 0.048790 / 0.004250 (0.044540) | 0.045358 / 0.037052 (0.008306) | 0.256308 / 0.258489 (-0.002181) | 0.286601 / 0.293841 (-0.007239) | 0.028644 / 0.128546 (-0.099903) | 0.011149 / 0.075646 (-0.064497) | 0.209796 / 0.419271 (-0.209475) | 0.036737 / 0.043533 (-0.006796) | 0.247427 / 0.255139 (-0.007712) | 0.274564 / 0.283200 (-0.008636) | 0.019717 / 0.141683 (-0.121966) | 1.107423 / 1.452155 (-0.344732) | 1.167830 / 1.492716 (-0.324886) |

### 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) | 0.095695 / 0.018006 (0.077688) | 0.305675 / 0.000490 (0.305185) | 0.000211 / 0.000200 (0.000011) | 0.000054 / 0.000054 (-0.000000) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.018969 / 0.037411 (-0.018443) | 0.063764 / 0.014526 (0.049239) | 0.075831 / 0.176557 (-0.100726) | 0.125340 / 0.737135 (-0.611795) | 0.077585 / 0.296338 (-0.218753) |

### 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) | 0.280876 / 0.215209 (0.065667) | 2.748107 / 2.077655 (0.670452) | 1.452201 / 1.504120 (-0.051919) | 1.328001 / 1.541195 (-0.213194) | 1.415581 / 1.468490 (-0.052909) | 0.568228 / 4.584777 (-4.016549) | 2.410486 / 3.745712 (-1.335226) | 2.975157 / 5.269862 (-2.294704) | 1.854096 / 4.565676 (-2.711581) | 0.063275 / 0.424275 (-0.361000) | 0.005121 / 0.007607 (-0.002487) | 0.340006 / 0.226044 (0.113961) | 3.362404 / 2.268929 (1.093476) | 1.803913 / 55.444624 (-53.640711) | 1.540557 / 6.876477 (-5.335919) | 1.629240 / 2.142072 (-0.512833) | 0.653595 / 4.805227 (-4.151632) | 0.119558 / 6.500664 (-6.381107) | 0.044365 / 0.075469 (-0.031104) |

### 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) | 0.964557 / 1.841788 (-0.877231) | 12.550303 / 8.074308 (4.475995) | 10.261302 / 10.191392 (0.069910) | 0.130834 / 0.680424 (-0.549589) | 0.014458 / 0.534201 (-0.519743) | 0.294833 / 0.579283 (-0.284450) | 0.268141 / 0.434364 (-0.166223) | 0.332492 / 0.540337 (-0.207845) | 0.427835 / 1.386936 (-0.959101) |

</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) | 0.005577 / 0.011353 (-0.005776) | 0.003823 / 0.011008 (-0.007185) | 0.050815 / 0.038508 (0.012307) | 0.031197 / 0.023109 (0.008088) | 0.269869 / 0.275898 (-0.006029) | 0.294371 / 0.323480 (-0.029109) | 0.004153 / 0.007986 (-0.003833) | 0.002884 / 0.004328 (-0.001445) | 0.048985 / 0.004250 (0.044735) | 0.047824 / 0.037052 (0.010772) | 0.270062 / 0.258489 (0.011573) | 0.306354 / 0.293841 (0.012514) | 0.030614 / 0.128546 (-0.097932) | 0.011209 / 0.075646 (-0.064438) | 0.058943 / 0.419271 (-0.360329) | 0.060824 / 0.043533 (0.017291) | 0.273580 / 0.255139 (0.018441) | 0.288375 / 0.283200 (0.005175) | 0.022097 / 0.141683 (-0.119585) | 1.159109 / 1.452155 (-0.293046) | 1.201463 / 1.492716 (-0.291253) |

### 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) | 0.093024 / 0.018006 (0.075018) | 0.302838 / 0.000490 (0.302348) | 0.000223 / 0.000200 (0.000023) | 0.000053 / 0.000054 (-0.000001) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.022991 / 0.037411 (-0.014420) | 0.081575 / 0.014526 (0.067050) | 0.090134 / 0.176557 (-0.086423) | 0.129506 / 0.737135 (-0.607629) | 0.091747 / 0.296338 (-0.204592) |

### 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) | 0.294735 / 0.215209 (0.079525) | 2.857557 / 2.077655 (0.779902) | 1.590577 / 1.504120 (0.086457) | 1.479404 / 1.541195 (-0.061790) | 1.515746 / 1.468490 (0.047256) | 0.579934 / 4.584777 (-4.004843) | 2.462790 / 3.745712 (-1.282922) | 2.944498 / 5.269862 (-2.325363) | 1.836767 / 4.565676 (-2.728909) | 0.064899 / 0.424275 (-0.359376) | 0.005232 / 0.007607 (-0.002375) | 0.349708 / 0.226044 (0.123664) | 3.424801 / 2.268929 (1.155873) | 1.945331 / 55.444624 (-53.499294) | 1.688862 / 6.876477 (-5.187615) | 1.712593 / 2.142072 (-0.429480) | 0.665894 / 4.805227 (-4.139333) | 0.121356 / 6.500664 (-6.379308) | 0.046908 / 0.075469 (-0.028561) |

### 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) | 0.983507 / 1.841788 (-0.858280) | 13.279790 / 8.074308 (5.205482) | 11.623531 / 10.191392 (1.432139) | 0.144567 / 0.680424 (-0.535857) | 0.016253 / 0.534201 (-0.517948) | 0.291842 / 0.579283 (-0.287441) | 0.278389 / 0.434364 (-0.155975) | 0.328971 / 0.540337 (-0.211366) | 0.443204 / 1.386936 (-0.943732) |

</details>
</details>

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