Fix ConnectionError for gated datasets and unauthenticated users
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2024-08-20T05:30:52Z
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Note that the CI error is unrelated to this PR and should be addressed in another PR. See:
- #7111
2024-08-20T05:49:44Z
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<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) | 0.005354 / 0.011353 (-0.005999) | 0.004031 / 0.011008 (-0.006977) | 0.062470 / 0.038508 (0.023962) | 0.030882 / 0.023109 (0.007773) | 0.244816 / 0.275898 (-0.031082) | 0.264324 / 0.323480 (-0.059156) | 0.004164 / 0.007986 (-0.003822) | 0.002858 / 0.004328 (-0.001471) | 0.049008 / 0.004250 (0.044758) | 0.042139 / 0.037052 (0.005086) | 0.279496 / 0.258489 (0.021007) | 0.279408 / 0.293841 (-0.014433) | 0.029701 / 0.128546 (-0.098845) | 0.012501 / 0.075646 (-0.063145) | 0.203267 / 0.419271 (-0.216004) | 0.035964 / 0.043533 (-0.007569) | 0.239361 / 0.255139 (-0.015778) | 0.258942 / 0.283200 (-0.024257) | 0.017956 / 0.141683 (-0.123727) | 1.160468 / 1.452155 (-0.291687) | 1.203475 / 1.492716 (-0.289242) |

### 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) | 0.004639 / 0.018006 (-0.013367) | 0.298020 / 0.000490 (0.297530) | 0.000212 / 0.000200 (0.000012) | 0.000043 / 0.000054 (-0.000012) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.019371 / 0.037411 (-0.018040) | 0.063311 / 0.014526 (0.048785) | 0.076412 / 0.176557 (-0.100145) | 0.122574 / 0.737135 (-0.614561) | 0.078076 / 0.296338 (-0.218263) |

### 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) | 0.275381 / 0.215209 (0.060172) | 2.713220 / 2.077655 (0.635565) | 1.441940 / 1.504120 (-0.062179) | 1.325545 / 1.541195 (-0.215650) | 1.363859 / 1.468490 (-0.104631) | 0.715147 / 4.584777 (-3.869630) | 2.356482 / 3.745712 (-1.389230) | 2.882792 / 5.269862 (-2.387069) | 1.833399 / 4.565676 (-2.732278) | 0.077872 / 0.424275 (-0.346403) | 0.005172 / 0.007607 (-0.002435) | 0.326361 / 0.226044 (0.100316) | 3.239202 / 2.268929 (0.970273) | 1.837745 / 55.444624 (-53.606879) | 1.517299 / 6.876477 (-5.359178) | 1.552938 / 2.142072 (-0.589134) | 0.801496 / 4.805227 (-4.003731) | 0.133351 / 6.500664 (-6.367314) | 0.042052 / 0.075469 (-0.033418) |

### 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) | 0.957887 / 1.841788 (-0.883901) | 11.625291 / 8.074308 (3.550983) | 9.679413 / 10.191392 (-0.511979) | 0.140271 / 0.680424 (-0.540153) | 0.013991 / 0.534201 (-0.520210) | 0.299874 / 0.579283 (-0.279409) | 0.267164 / 0.434364 (-0.167200) | 0.338143 / 0.540337 (-0.202194) | 0.434105 / 1.386936 (-0.952831) |

</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) | 0.005833 / 0.011353 (-0.005520) | 0.003761 / 0.011008 (-0.007247) | 0.049699 / 0.038508 (0.011191) | 0.032786 / 0.023109 (0.009677) | 0.265100 / 0.275898 (-0.010798) | 0.291045 / 0.323480 (-0.032435) | 0.004281 / 0.007986 (-0.003705) | 0.002737 / 0.004328 (-0.001591) | 0.048524 / 0.004250 (0.044274) | 0.040783 / 0.037052 (0.003731) | 0.281122 / 0.258489 (0.022633) | 0.311349 / 0.293841 (0.017508) | 0.032143 / 0.128546 (-0.096403) | 0.011747 / 0.075646 (-0.063899) | 0.059432 / 0.419271 (-0.359840) | 0.034362 / 0.043533 (-0.009171) | 0.261061 / 0.255139 (0.005922) | 0.279536 / 0.283200 (-0.003663) | 0.019172 / 0.141683 (-0.122510) | 1.160069 / 1.452155 (-0.292086) | 1.224160 / 1.492716 (-0.268556) |

### 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) | 0.093596 / 0.018006 (0.075590) | 0.302862 / 0.000490 (0.302372) | 0.000208 / 0.000200 (0.000008) | 0.000047 / 0.000054 (-0.000007) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.022785 / 0.037411 (-0.014626) | 0.079263 / 0.014526 (0.064737) | 0.091340 / 0.176557 (-0.085216) | 0.129453 / 0.737135 (-0.607682) | 0.091349 / 0.296338 (-0.204989) |

### 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) | 0.298166 / 0.215209 (0.082957) | 3.003146 / 2.077655 (0.925491) | 1.575903 / 1.504120 (0.071783) | 1.445231 / 1.541195 (-0.095963) | 1.477116 / 1.468490 (0.008625) | 0.726496 / 4.584777 (-3.858281) | 0.959827 / 3.745712 (-2.785885) | 2.941142 / 5.269862 (-2.328720) | 1.878581 / 4.565676 (-2.687096) | 0.078475 / 0.424275 (-0.345800) | 0.005137 / 0.007607 (-0.002470) | 0.352078 / 0.226044 (0.126034) | 3.486113 / 2.268929 (1.217184) | 1.965024 / 55.444624 (-53.479600) | 1.667223 / 6.876477 (-5.209254) | 1.665254 / 2.142072 (-0.476819) | 0.803543 / 4.805227 (-4.001684) | 0.133003 / 6.500664 (-6.367661) | 0.041462 / 0.075469 (-0.034008) |

### 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) | 1.045534 / 1.841788 (-0.796254) | 12.124988 / 8.074308 (4.050680) | 10.418723 / 10.191392 (0.227331) | 0.142453 / 0.680424 (-0.537971) | 0.015686 / 0.534201 (-0.518515) | 0.300557 / 0.579283 (-0.278726) | 0.119851 / 0.434364 (-0.314512) | 0.342297 / 0.540337 (-0.198040) | 0.441263 / 1.386936 (-0.945673) |

</details>
</details>

![](https://cml.dev/watermark.png#90b1d94ef419cb26f0bb24d982897dca39aa8a46 "CML watermark")

2024-08-20T09:20:36Z
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Fix `ConnectionError` for gated datasets and unauthenticated users. See:
- https://github.com/huggingface/dataset-viewer/issues/3025

Note that a recent change in the Hub returns dataset info for gated datasets and unauthenticated users, instead of raising a `GatedRepoError` as before. See:
- https://github.com/huggingface/huggingface_hub/issues/2457

This PR adds an additional check (/auth-check) for gated datasets and raises `DatasetNotFoundError` for unauthenticated users, as it was the case before the change in the Hub.
- Fix suggested by @Pierrci (thanks @Wauplin for pointing it out).

Fix #7109.