Fix missing download_config in get_data_patterns
State: closed | Author: lhoestq (MEMBER)

Reported in https://github.com/huggingface/datasets-server/issues/2607

Comments: The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6742). 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) | 0.005394 / 0.011353 (-0.005959) | 0.003780 / 0.011008 (-0.007228) | 0.063459 / 0.038508 (0.024951) | 0.028883 / 0.023109 (0.005774) | 0.239159 / 0.275898 (-0.036739) | 0.258123 / 0.323480 (-0.065357) | 0.003134 / 0.007986 (-0.004851) | 0.003452 / 0.004328 (-0.000876) | 0.049255 / 0.004250 (0.045005) | 0.042727 / 0.037052 (0.005675) | 0.257387 / 0.258489 (-0.001102) | 0.280762 / 0.293841 (-0.013079) | 0.027921 / 0.128546 (-0.100625) | 0.010867 / 0.075646 (-0.064779) | 0.207878 / 0.419271 (-0.211393) | 0.036003 / 0.043533 (-0.007530) | 0.247457 / 0.255139 (-0.007682) | 0.260231 / 0.283200 (-0.022969) | 0.019741 / 0.141683 (-0.121942) | 1.143645 / 1.452155 (-0.308510) | 1.188789 / 1.492716 (-0.303927) |

### 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) | 0.092065 / 0.018006 (0.074059) | 0.286021 / 0.000490 (0.285531) | 0.000220 / 0.000200 (0.000020) | 0.000048 / 0.000054 (-0.000006) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.018934 / 0.037411 (-0.018477) | 0.062474 / 0.014526 (0.047949) | 0.073384 / 0.176557 (-0.103172) | 0.121276 / 0.737135 (-0.615860) | 0.077792 / 0.296338 (-0.218546) |

### 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) | 0.285352 / 0.215209 (0.070143) | 2.783110 / 2.077655 (0.705456) | 1.487983 / 1.504120 (-0.016137) | 1.364264 / 1.541195 (-0.176930) | 1.388757 / 1.468490 (-0.079733) | 0.568347 / 4.584777 (-4.016430) | 2.402451 / 3.745712 (-1.343261) | 2.835577 / 5.269862 (-2.434285) | 1.754853 / 4.565676 (-2.810824) | 0.063355 / 0.424275 (-0.360920) | 0.005010 / 0.007607 (-0.002598) | 0.332061 / 0.226044 (0.106016) | 3.287121 / 2.268929 (1.018193) | 1.829520 / 55.444624 (-53.615104) | 1.542669 / 6.876477 (-5.333808) | 1.560679 / 2.142072 (-0.581393) | 0.642371 / 4.805227 (-4.162856) | 0.118636 / 6.500664 (-6.382028) | 0.042262 / 0.075469 (-0.033207) |

### 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) | 0.984803 / 1.841788 (-0.856985) | 11.578044 / 8.074308 (3.503735) | 9.383428 / 10.191392 (-0.807964) | 0.141367 / 0.680424 (-0.539057) | 0.014047 / 0.534201 (-0.520154) | 0.291505 / 0.579283 (-0.287778) | 0.270199 / 0.434364 (-0.164165) | 0.329874 / 0.540337 (-0.210463) | 0.429386 / 1.386936 (-0.957550) |

</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) | 0.005322 / 0.011353 (-0.006031) | 0.004023 / 0.011008 (-0.006986) | 0.050126 / 0.038508 (0.011618) | 0.029937 / 0.023109 (0.006828) | 0.275985 / 0.275898 (0.000087) | 0.297965 / 0.323480 (-0.025515) | 0.004429 / 0.007986 (-0.003557) | 0.002729 / 0.004328 (-0.001599) | 0.048995 / 0.004250 (0.044744) | 0.044940 / 0.037052 (0.007888) | 0.288397 / 0.258489 (0.029908) | 0.317716 / 0.293841 (0.023875) | 0.029705 / 0.128546 (-0.098841) | 0.010972 / 0.075646 (-0.064674) | 0.058592 / 0.419271 (-0.360680) | 0.054640 / 0.043533 (0.011108) | 0.276456 / 0.255139 (0.021317) | 0.295119 / 0.283200 (0.011919) | 0.020032 / 0.141683 (-0.121651) | 1.175740 / 1.452155 (-0.276415) | 1.227246 / 1.492716 (-0.265471) |

### 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) | 0.092204 / 0.018006 (0.074197) | 0.300344 / 0.000490 (0.299855) | 0.000213 / 0.000200 (0.000013) | 0.000050 / 0.000054 (-0.000004) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.021540 / 0.037411 (-0.015871) | 0.076252 / 0.014526 (0.061726) | 0.087582 / 0.176557 (-0.088975) | 0.125977 / 0.737135 (-0.611159) | 0.090649 / 0.296338 (-0.205689) |

### 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) | 0.294544 / 0.215209 (0.079335) | 2.883736 / 2.077655 (0.806082) | 1.570932 / 1.504120 (0.066812) | 1.449082 / 1.541195 (-0.092113) | 1.463262 / 1.468490 (-0.005228) | 0.559625 / 4.584777 (-4.025152) | 2.448593 / 3.745712 (-1.297119) | 2.663857 / 5.269862 (-2.606005) | 1.757812 / 4.565676 (-2.807865) | 0.061999 / 0.424275 (-0.362276) | 0.005100 / 0.007607 (-0.002507) | 0.343620 / 0.226044 (0.117575) | 3.487059 / 2.268929 (1.218130) | 1.963078 / 55.444624 (-53.481546) | 1.661758 / 6.876477 (-5.214719) | 1.799130 / 2.142072 (-0.342942) | 0.650194 / 4.805227 (-4.155034) | 0.117375 / 6.500664 (-6.383289) | 0.040957 / 0.075469 (-0.034512) |

### 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) | 1.037882 / 1.841788 (-0.803906) | 12.239784 / 8.074308 (4.165476) | 10.478186 / 10.191392 (0.286794) | 0.164446 / 0.680424 (-0.515978) | 0.014901 / 0.534201 (-0.519300) | 0.302485 / 0.579283 (-0.276798) | 0.283994 / 0.434364 (-0.150370) | 0.338473 / 0.540337 (-0.201864) | 0.468901 / 1.386936 (-0.918035) |

</details>
</details>

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