Fix NonMatchingSplitsSizesError/ExpectedMoreSplits when passing data_dir/data_files in no-code Hub datasets
State: closed

Fix `NonMatchingSplitsSizesError` or `ExpectedMoreSplits` error for no-code Hub datasets if the user passes:
- `data_dir`
- `data_files`

The proposed solution is to avoid using exported dataset info (from Parquet exports) in these cases.
Additionally, also if the user passes `revision` other than "main" (so that no network requests are made).

This PR fixes a bug introduced by:
- #6714

Fix #6918, fix #6939.

Comments:
The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6925). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.

Do you think this is worth making a patch release for?
CC: @huggingface/datasets

I will add some regression tests before merging.

And I will make a patch release afterwards.

<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) | 0.004959 / 0.011353 (-0.006394) | 0.003654 / 0.011008 (-0.007354) | 0.064087 / 0.038508 (0.025579) | 0.031942 / 0.023109 (0.008833) | 0.236830 / 0.275898 (-0.039068) | 0.265359 / 0.323480 (-0.058121) | 0.003108 / 0.007986 (-0.004878) | 0.002824 / 0.004328 (-0.001504) | 0.049102 / 0.004250 (0.044852) | 0.046070 / 0.037052 (0.009017) | 0.248830 / 0.258489 (-0.009659) | 0.283900 / 0.293841 (-0.009941) | 0.027799 / 0.128546 (-0.100747) | 0.010572 / 0.075646 (-0.065074) | 0.223595 / 0.419271 (-0.195677) | 0.036951 / 0.043533 (-0.006582) | 0.238813 / 0.255139 (-0.016326) | 0.253841 / 0.283200 (-0.029359) | 0.018471 / 0.141683 (-0.123212) | 1.131969 / 1.452155 (-0.320186) | 1.173763 / 1.492716 (-0.318954) |

### 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) | 0.095504 / 0.018006 (0.077498) | 0.301469 / 0.000490 (0.300979) | 0.000212 / 0.000200 (0.000012) | 0.000052 / 0.000054 (-0.000003) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.019194 / 0.037411 (-0.018217) | 0.062313 / 0.014526 (0.047787) | 0.075852 / 0.176557 (-0.100704) | 0.121996 / 0.737135 (-0.615140) | 0.076416 / 0.296338 (-0.219923) |

### 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) | 0.292465 / 0.215209 (0.077256) | 2.910234 / 2.077655 (0.832579) | 1.479672 / 1.504120 (-0.024448) | 1.332281 / 1.541195 (-0.208913) | 1.354095 / 1.468490 (-0.114395) | 0.573438 / 4.584777 (-4.011339) | 2.382406 / 3.745712 (-1.363307) | 2.708289 / 5.269862 (-2.561572) | 1.739665 / 4.565676 (-2.826011) | 0.063514 / 0.424275 (-0.360761) | 0.005008 / 0.007607 (-0.002599) | 0.350070 / 0.226044 (0.124025) | 3.475837 / 2.268929 (1.206909) | 1.804639 / 55.444624 (-53.639985) | 1.520472 / 6.876477 (-5.356005) | 1.658061 / 2.142072 (-0.484011) | 0.648495 / 4.805227 (-4.156732) | 0.118394 / 6.500664 (-6.382270) | 0.042557 / 0.075469 (-0.032912) |

### 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) | 0.960772 / 1.841788 (-0.881016) | 11.451629 / 8.074308 (3.377321) | 9.613331 / 10.191392 (-0.578061) | 0.130259 / 0.680424 (-0.550164) | 0.015828 / 0.534201 (-0.518373) | 0.287581 / 0.579283 (-0.291702) | 0.266517 / 0.434364 (-0.167847) | 0.327334 / 0.540337 (-0.213003) | 0.427881 / 1.386936 (-0.959055) |

</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) | 0.005364 / 0.011353 (-0.005989) | 0.003723 / 0.011008 (-0.007285) | 0.049990 / 0.038508 (0.011482) | 0.032023 / 0.023109 (0.008913) | 0.258609 / 0.275898 (-0.017289) | 0.281250 / 0.323480 (-0.042230) | 0.004222 / 0.007986 (-0.003764) | 0.002799 / 0.004328 (-0.001529) | 0.049546 / 0.004250 (0.045296) | 0.040298 / 0.037052 (0.003246) | 0.273552 / 0.258489 (0.015063) | 0.304042 / 0.293841 (0.010201) | 0.030116 / 0.128546 (-0.098430) | 0.010792 / 0.075646 (-0.064855) | 0.058427 / 0.419271 (-0.360845) | 0.033415 / 0.043533 (-0.010118) | 0.258794 / 0.255139 (0.003655) | 0.275304 / 0.283200 (-0.007896) | 0.017944 / 0.141683 (-0.123739) | 1.109291 / 1.452155 (-0.342864) | 1.156627 / 1.492716 (-0.336090) |

### 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) | 0.096700 / 0.018006 (0.078693) | 0.301108 / 0.000490 (0.300618) | 0.000208 / 0.000200 (0.000008) | 0.000054 / 0.000054 (-0.000001) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.022632 / 0.037411 (-0.014779) | 0.075813 / 0.014526 (0.061287) | 0.090302 / 0.176557 (-0.086254) | 0.130375 / 0.737135 (-0.606760) | 0.089710 / 0.296338 (-0.206629) |

### 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) | 0.297091 / 0.215209 (0.081882) | 2.910379 / 2.077655 (0.832725) | 1.570460 / 1.504120 (0.066340) | 1.441619 / 1.541195 (-0.099576) | 1.442417 / 1.468490 (-0.026073) | 0.570034 / 4.584777 (-4.014743) | 0.952613 / 3.745712 (-2.793099) | 2.659274 / 5.269862 (-2.610588) | 1.751013 / 4.565676 (-2.814663) | 0.064639 / 0.424275 (-0.359636) | 0.005145 / 0.007607 (-0.002462) | 0.347478 / 0.226044 (0.121434) | 3.443862 / 2.268929 (1.174933) | 1.897246 / 55.444624 (-53.547379) | 1.609267 / 6.876477 (-5.267210) | 1.755116 / 2.142072 (-0.386956) | 0.658982 / 4.805227 (-4.146245) | 0.117000 / 6.500664 (-6.383664) | 0.041453 / 0.075469 (-0.034016) |

### 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) | 1.005843 / 1.841788 (-0.835944) | 12.101306 / 8.074308 (4.026998) | 10.370706 / 10.191392 (0.179314) | 0.139374 / 0.680424 (-0.541050) | 0.015605 / 0.534201 (-0.518596) | 0.286978 / 0.579283 (-0.292305) | 0.122951 / 0.434364 (-0.311413) | 0.331729 / 0.540337 (-0.208609) | 0.422088 / 1.386936 (-0.964848) |

</details>
</details>

![](https://cml.dev/watermark.png#157585f964b1c7f675860af0d21712555b34aabc "CML watermark")


I'm hitting this error now, using Spaces. Here's what an attempt to just get the 'validation' split is doing:

code:

```

  | import os
  | from huggingface_hub import HfApi
  | from datasets import Dataset, load_dataset, DownloadConfig
  |  
  |  
  | GATED_IMAGENET = os.environ.get("GATED_IMAGENET")
  | api = HfApi(token=GATED_IMAGENET)
  |
  | ds = load_dataset('datacomp/imagenet-1k-random0.0', token=GATED_IMAGENET, data_files={'validation': 'data/val*'}, split='validation', trust_remote_code=True)


```

log:

```
Generating validation split:   0%|          | 0/50000 [00:00<?, ? examples/s]
Generating validation split:  12%|█▏        | 6172/50000 [00:01<00:07, 5804.90 examples/s]
Generating validation split:  25%|██▌       | 12716/50000 [00:02<00:06, 6167.77 examples/s]
Generating validation split:  38%|███▊      | 19060/50000 [00:03<00:04, 6218.99 examples/s]
Generating validation split:  51%|█████     | 25603/50000 [00:04<00:03, 6126.35 examples/s]
Generating validation split:  64%|██████▍   | 32145/50000 [00:05<00:02, 6166.95 examples/s]
Generating validation split:  77%|███████▋  | 38716/50000 [00:06<00:01, 6272.66 examples/s]
Generating validation split:  90%|█████████ | 45158/50000 [00:07<00:00, 6307.44 examples/s]
Generating validation split: 100%|██████████| 50000/50000 [00:08<00:00, 6212.19 examples/s]
Traceback (most recent call last):
  File "/home/user/app/app.py", line 12, in <module>
    ds = load_dataset('datacomp/imagenet-1k-random0.0', token=GATED_IMAGENET, data_files={'validation': 'data/val*'}, split='validation', trust_remote_code=True)
  File "/usr/local/lib/python3.10/site-packages/datasets/load.py", line 2154, in load_dataset
    builder_instance.download_and_prepare(
  File "/usr/local/lib/python3.10/site-packages/datasets/builder.py", line 924, in download_and_prepare
    self._download_and_prepare(
  File "/usr/local/lib/python3.10/site-packages/datasets/builder.py", line 1018, in _download_and_prepare
    verify_splits(self.info.splits, split_dict)
  File "/usr/local/lib/python3.10/site-packages/datasets/utils/info_utils.py", line 68, in verify_splits
    raise ExpectedMoreSplitsError(str(set(expected_splits) - set(recorded_splits)))
datasets.exceptions.ExpectedMoreSplitsError: {'train', 'test'}
```

Hi Meg ! Thanks for reporting, I'll see how I can fix this. In the meantime feel free to pass `verification_mode="no_checks"` to `load_dataset`