Fix deprecation of use_auth_token in DownloadConfig
Opened by albertvillanova (closed)

This PR fixes an issue with the deprecation of `use_auth_token` in `DownloadConfig` introduced by:
- #5996

```python
In [1]: from datasets import DownloadConfig

In [2]: DownloadConfig(use_auth_token=False)
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-3-41927b449e72> in <module>
----> 1 DownloadConfig(use_auth_token=False)

TypeError: __init__() got an unexpected keyword argument 'use_auth_token'
```

```python
In [1]: from datasets import get_dataset_config_names
In [2]: get_dataset_config_names("squad", use_auth_token=False)
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-22-4671992ead50> in <module>
----> 1 get_dataset_config_names("squad", use_auth_token=False)

~/huggingface/datasets/src/datasets/inspect.py in get_dataset_config_names(path, revision, download_config, download_mode, dynamic_modules_path, data_files, **download_kwargs)
    349     ```
    350     """
--> 351     dataset_module = dataset_module_factory(
    352         path,
    353         revision=revision,

~/huggingface/datasets/src/datasets/load.py in dataset_module_factory(path, revision, download_config, download_mode, dynamic_modules_path, data_dir, data_files, **download_kwargs)
   1374     """
   1375     if download_config is None:
-> 1376         download_config = DownloadConfig(**download_kwargs)
   1377     download_mode = DownloadMode(download_mode or DownloadMode.REUSE_DATASET_IF_EXISTS)
   1378     download_config.extract_compressed_file = True

TypeError: __init__() got an unexpected keyword argument 'use_auth_token'
```

Comments:
_The documentation is not available anymore as the PR was closed or merged._

<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) | 0.008996 / 0.011353 (-0.002357) | 0.004976 / 0.011008 (-0.006033) | 0.114495 / 0.038508 (0.075987) | 0.083958 / 0.023109 (0.060849) | 0.408395 / 0.275898 (0.132497) | 0.456757 / 0.323480 (0.133278) | 0.006396 / 0.007986 (-0.001589) | 0.004315 / 0.004328 (-0.000014) | 0.093558 / 0.004250 (0.089307) | 0.062067 / 0.037052 (0.025014) | 0.423452 / 0.258489 (0.164963) | 0.463947 / 0.293841 (0.170106) | 0.049934 / 0.128546 (-0.078613) | 0.013937 / 0.075646 (-0.061709) | 0.365809 / 0.419271 (-0.053463) | 0.067382 / 0.043533 (0.023849) | 0.418860 / 0.255139 (0.163721) | 0.463264 / 0.283200 (0.180065) | 0.034392 / 0.141683 (-0.107291) | 1.870685 / 1.452155 (0.418530) | 1.975313 / 1.492716 (0.482597) |

### 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) | 0.261748 / 0.018006 (0.243742) | 0.645510 / 0.000490 (0.645020) | 0.000376 / 0.000200 (0.000176) | 0.000077 / 0.000054 (0.000023) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.032129 / 0.037411 (-0.005282) | 0.104309 / 0.014526 (0.089783) | 0.113154 / 0.176557 (-0.063403) | 0.186795 / 0.737135 (-0.550341) | 0.115584 / 0.296338 (-0.180755) |

### 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) | 0.577755 / 0.215209 (0.362546) | 5.984988 / 2.077655 (3.907333) | 2.581967 / 1.504120 (1.077848) | 2.305744 / 1.541195 (0.764549) | 2.359618 / 1.468490 (0.891128) | 0.882892 / 4.584777 (-3.701885) | 5.755578 / 3.745712 (2.009866) | 8.718373 / 5.269862 (3.448511) | 5.217586 / 4.565676 (0.651909) | 0.099785 / 0.424275 (-0.324490) | 0.009008 / 0.007607 (0.001401) | 0.730937 / 0.226044 (0.504892) | 7.265309 / 2.268929 (4.996381) | 3.487167 / 55.444624 (-51.957457) | 2.750090 / 6.876477 (-4.126386) | 3.060198 / 2.142072 (0.918125) | 1.069945 / 4.805227 (-3.735282) | 0.227143 / 6.500664 (-6.273521) | 0.083601 / 0.075469 (0.008132) |

### 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) | 1.754375 / 1.841788 (-0.087412) | 25.448731 / 8.074308 (17.374423) | 22.385943 / 10.191392 (12.194551) | 0.249921 / 0.680424 (-0.430503) | 0.034138 / 0.534201 (-0.500063) | 0.535170 / 0.579283 (-0.044113) | 0.605474 / 0.434364 (0.171110) | 0.580025 / 0.540337 (0.039688) | 0.810537 / 1.386936 (-0.576399) |

</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) | 0.009117 / 0.011353 (-0.002236) | 0.005029 / 0.011008 (-0.005979) | 0.082200 / 0.038508 (0.043691) | 0.082386 / 0.023109 (0.059277) | 0.491869 / 0.275898 (0.215971) | 0.546735 / 0.323480 (0.223255) | 0.006893 / 0.007986 (-0.001093) | 0.004571 / 0.004328 (0.000243) | 0.085361 / 0.004250 (0.081111) | 0.063342 / 0.037052 (0.026290) | 0.522522 / 0.258489 (0.264033) | 0.560784 / 0.293841 (0.266943) | 0.047685 / 0.128546 (-0.080861) | 0.017741 / 0.075646 (-0.057905) | 0.098204 / 0.419271 (-0.321067) | 0.062919 / 0.043533 (0.019386) | 0.504005 / 0.255139 (0.248866) | 0.547022 / 0.283200 (0.263823) | 0.033731 / 0.141683 (-0.107952) | 1.869765 / 1.452155 (0.417610) | 1.935867 / 1.492716 (0.443151) |

### 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) | 0.304756 / 0.018006 (0.286750) | 0.623647 / 0.000490 (0.623157) | 0.000508 / 0.000200 (0.000308) | 0.000090 / 0.000054 (0.000035) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.043627 / 0.037411 (0.006216) | 0.107183 / 0.014526 (0.092657) | 0.119304 / 0.176557 (-0.057253) | 0.192651 / 0.737135 (-0.544485) | 0.125118 / 0.296338 (-0.171221) |

### 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) | 0.669980 / 0.215209 (0.454771) | 6.566068 / 2.077655 (4.488413) | 3.136271 / 1.504120 (1.632152) | 2.964643 / 1.541195 (1.423448) | 2.936772 / 1.468490 (1.468282) | 0.885205 / 4.584777 (-3.699572) | 5.539062 / 3.745712 (1.793350) | 5.006133 / 5.269862 (-0.263729) | 3.313697 / 4.565676 (-1.251979) | 0.102975 / 0.424275 (-0.321301) | 0.010759 / 0.007607 (0.003152) | 0.791176 / 0.226044 (0.565132) | 7.822195 / 2.268929 (5.553266) | 3.982315 / 55.444624 (-51.462309) | 3.357026 / 6.876477 (-3.519451) | 3.561307 / 2.142072 (1.419234) | 1.056966 / 4.805227 (-3.748261) | 0.220476 / 6.500664 (-6.280188) | 0.090535 / 0.075469 (0.015066) |

### 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) | 1.897984 / 1.841788 (0.056196) | 26.411411 / 8.074308 (18.337103) | 22.951939 / 10.191392 (12.760547) | 0.216091 / 0.680424 (-0.464333) | 0.037005 / 0.534201 (-0.497196) | 0.505585 / 0.579283 (-0.073698) | 0.617794 / 0.434364 (0.183430) | 0.604631 / 0.540337 (0.064293) | 0.826356 / 1.386936 (-0.560580) |

</details>
</details>

![](https://cml.dev/watermark.png#ca6342c0177adc3a1d114740444e207b8525ed6e "CML watermark")


<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) | 0.006850 / 0.011353 (-0.004503) | 0.004062 / 0.011008 (-0.006947) | 0.086587 / 0.038508 (0.048079) | 0.079587 / 0.023109 (0.056478) | 0.353601 / 0.275898 (0.077702) | 0.396399 / 0.323480 (0.072919) | 0.004182 / 0.007986 (-0.003804) | 0.004445 / 0.004328 (0.000117) | 0.065100 / 0.004250 (0.060849) | 0.057386 / 0.037052 (0.020334) | 0.356945 / 0.258489 (0.098456) | 0.407093 / 0.293841 (0.113252) | 0.031949 / 0.128546 (-0.096597) | 0.008525 / 0.075646 (-0.067121) | 0.291310 / 0.419271 (-0.127961) | 0.053638 / 0.043533 (0.010105) | 0.359381 / 0.255139 (0.104242) | 0.399473 / 0.283200 (0.116273) | 0.025880 / 0.141683 (-0.115803) | 1.487604 / 1.452155 (0.035449) | 1.550528 / 1.492716 (0.057812) |

### 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) | 0.201106 / 0.018006 (0.183099) | 0.457538 / 0.000490 (0.457048) | 0.003995 / 0.000200 (0.003795) | 0.000087 / 0.000054 (0.000032) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.030365 / 0.037411 (-0.007046) | 0.088064 / 0.014526 (0.073538) | 0.096432 / 0.176557 (-0.080124) | 0.158063 / 0.737135 (-0.579072) | 0.098258 / 0.296338 (-0.198080) |

### 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) | 0.405351 / 0.215209 (0.190142) | 4.032639 / 2.077655 (1.954984) | 2.018357 / 1.504120 (0.514237) | 1.848493 / 1.541195 (0.307298) | 1.929401 / 1.468490 (0.460910) | 0.488729 / 4.584777 (-4.096048) | 3.586114 / 3.745712 (-0.159598) | 5.279054 / 5.269862 (0.009193) | 3.113275 / 4.565676 (-1.452402) | 0.057373 / 0.424275 (-0.366902) | 0.007416 / 0.007607 (-0.000191) | 0.485514 / 0.226044 (0.259470) | 4.854389 / 2.268929 (2.585461) | 2.493113 / 55.444624 (-52.951512) | 2.128836 / 6.876477 (-4.747641) | 2.383669 / 2.142072 (0.241596) | 0.588266 / 4.805227 (-4.216962) | 0.133603 / 6.500664 (-6.367061) | 0.061812 / 0.075469 (-0.013657) |

### 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) | 1.260841 / 1.841788 (-0.580947) | 20.086954 / 8.074308 (12.012646) | 14.620932 / 10.191392 (4.429540) | 0.161525 / 0.680424 (-0.518899) | 0.018102 / 0.534201 (-0.516099) | 0.393810 / 0.579283 (-0.185473) | 0.406974 / 0.434364 (-0.027390) | 0.462732 / 0.540337 (-0.077606) | 0.634221 / 1.386936 (-0.752715) |

</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) | 0.006692 / 0.011353 (-0.004661) | 0.004068 / 0.011008 (-0.006940) | 0.068009 / 0.038508 (0.029501) | 0.081298 / 0.023109 (0.058189) | 0.363531 / 0.275898 (0.087633) | 0.408482 / 0.323480 (0.085002) | 0.005601 / 0.007986 (-0.002384) | 0.003385 / 0.004328 (-0.000943) | 0.068043 / 0.004250 (0.063792) | 0.059739 / 0.037052 (0.022687) | 0.374043 / 0.258489 (0.115553) | 0.407219 / 0.293841 (0.113378) | 0.031194 / 0.128546 (-0.097352) | 0.008630 / 0.075646 (-0.067017) | 0.073755 / 0.419271 (-0.345517) | 0.049831 / 0.043533 (0.006298) | 0.363664 / 0.255139 (0.108525) | 0.381515 / 0.283200 (0.098315) | 0.026331 / 0.141683 (-0.115352) | 1.507771 / 1.452155 (0.055617) | 1.554403 / 1.492716 (0.061686) |

### 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) | 0.226309 / 0.018006 (0.208302) | 0.452428 / 0.000490 (0.451938) | 0.000937 / 0.000200 (0.000737) | 0.000069 / 0.000054 (0.000015) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.031899 / 0.037411 (-0.005513) | 0.092090 / 0.014526 (0.077564) | 0.100838 / 0.176557 (-0.075718) | 0.153722 / 0.737135 (-0.583413) | 0.101950 / 0.296338 (-0.194389) |

### 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) | 0.417879 / 0.215209 (0.202669) | 4.171939 / 2.077655 (2.094284) | 2.312937 / 1.504120 (0.808817) | 2.209991 / 1.541195 (0.668796) | 2.329469 / 1.468490 (0.860979) | 0.484576 / 4.584777 (-4.100201) | 3.659198 / 3.745712 (-0.086514) | 5.255227 / 5.269862 (-0.014634) | 3.047430 / 4.565676 (-1.518247) | 0.057029 / 0.424275 (-0.367246) | 0.007735 / 0.007607 (0.000127) | 0.499962 / 0.226044 (0.273918) | 4.991655 / 2.268929 (2.722727) | 2.755999 / 55.444624 (-52.688625) | 2.374034 / 6.876477 (-4.502443) | 2.599759 / 2.142072 (0.457687) | 0.600319 / 4.805227 (-4.204908) | 0.146176 / 6.500664 (-6.354488) | 0.062328 / 0.075469 (-0.013142) |

### 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) | 1.346065 / 1.841788 (-0.495722) | 20.430343 / 8.074308 (12.356035) | 14.632959 / 10.191392 (4.441567) | 0.167007 / 0.680424 (-0.513417) | 0.018588 / 0.534201 (-0.515613) | 0.396015 / 0.579283 (-0.183268) | 0.429384 / 0.434364 (-0.004980) | 0.467746 / 0.540337 (-0.072591) | 0.615166 / 1.386936 (-0.771770) |

</details>
</details>

![](https://cml.dev/watermark.png#289bcc2ae9bf98c9414b6846ae603178a1816d3f "CML watermark")