Title: Fix dl_manager.extract returning FileNotFoundError
State: closed

The dl_manager base path is remote (e.g. a hf:// path), so local cached paths should be passed as absolute paths.
This could happen if users provide a relative path as `cache_dir`

fix https://github.com/huggingface/datasets/issues/6536

Comments:
The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6543). 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) | 0.004950 / 0.011353 (-0.006403) | 0.003502 / 0.011008 (-0.007506) | 0.062517 / 0.038508 (0.024009) | 0.030965 / 0.023109 (0.007856) | 0.250661 / 0.275898 (-0.025237) | 0.279165 / 0.323480 (-0.044314) | 0.002960 / 0.007986 (-0.005026) | 0.003382 / 0.004328 (-0.000946) | 0.048174 / 0.004250 (0.043923) | 0.042975 / 0.037052 (0.005922) | 0.248079 / 0.258489 (-0.010410) | 0.283770 / 0.293841 (-0.010070) | 0.027935 / 0.128546 (-0.100611) | 0.010634 / 0.075646 (-0.065012) | 0.207039 / 0.419271 (-0.212233) | 0.035863 / 0.043533 (-0.007670) | 0.257426 / 0.255139 (0.002287) | 0.274222 / 0.283200 (-0.008978) | 0.017590 / 0.141683 (-0.124093) | 1.126889 / 1.452155 (-0.325266) | 1.160795 / 1.492716 (-0.331921) |

### 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) | 0.004298 / 0.018006 (-0.013708) | 0.301366 / 0.000490 (0.300876) | 0.000202 / 0.000200 (0.000002) | 0.000050 / 0.000054 (-0.000005) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.018159 / 0.037411 (-0.019252) | 0.060566 / 0.014526 (0.046041) | 0.072500 / 0.176557 (-0.104057) | 0.119612 / 0.737135 (-0.617523) | 0.074467 / 0.296338 (-0.221871) |

### 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) | 0.281859 / 0.215209 (0.066650) | 2.760157 / 2.077655 (0.682502) | 1.450632 / 1.504120 (-0.053487) | 1.326636 / 1.541195 (-0.214559) | 1.363381 / 1.468490 (-0.105109) | 0.576199 / 4.584777 (-4.008578) | 2.355776 / 3.745712 (-1.389936) | 2.807308 / 5.269862 (-2.462553) | 1.745449 / 4.565676 (-2.820228) | 0.063413 / 0.424275 (-0.360862) | 0.004978 / 0.007607 (-0.002630) | 0.332738 / 0.226044 (0.106693) | 3.267677 / 2.268929 (0.998748) | 1.766074 / 55.444624 (-53.678551) | 1.500853 / 6.876477 (-5.375624) | 1.532434 / 2.142072 (-0.609639) | 0.648238 / 4.805227 (-4.156989) | 0.116030 / 6.500664 (-6.384634) | 0.042018 / 0.075469 (-0.033451) |

### 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) | 0.934325 / 1.841788 (-0.907463) | 11.439765 / 8.074308 (3.365457) | 9.958624 / 10.191392 (-0.232768) | 0.130295 / 0.680424 (-0.550129) | 0.014437 / 0.534201 (-0.519764) | 0.286073 / 0.579283 (-0.293210) | 0.262430 / 0.434364 (-0.171934) | 0.323905 / 0.540337 (-0.216432) | 0.416615 / 1.386936 (-0.970321) |

</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) | 0.005149 / 0.011353 (-0.006204) | 0.003517 / 0.011008 (-0.007491) | 0.048658 / 0.038508 (0.010150) | 0.029638 / 0.023109 (0.006529) | 0.271002 / 0.275898 (-0.004896) | 0.324910 / 0.323480 (0.001430) | 0.004086 / 0.007986 (-0.003900) | 0.002609 / 0.004328 (-0.001719) | 0.047806 / 0.004250 (0.043556) | 0.045422 / 0.037052 (0.008369) | 0.274317 / 0.258489 (0.015828) | 0.304544 / 0.293841 (0.010703) | 0.029318 / 0.128546 (-0.099229) | 0.010626 / 0.075646 (-0.065020) | 0.057838 / 0.419271 (-0.361434) | 0.052408 / 0.043533 (0.008875) | 0.267736 / 0.255139 (0.012597) | 0.292024 / 0.283200 (0.008824) | 0.019244 / 0.141683 (-0.122439) | 1.167728 / 1.452155 (-0.284427) | 1.226364 / 1.492716 (-0.266352) |

### 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) | 0.092441 / 0.018006 (0.074435) | 0.310316 / 0.000490 (0.309827) | 0.000218 / 0.000200 (0.000018) | 0.000049 / 0.000054 (-0.000005) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.021818 / 0.037411 (-0.015594) | 0.076515 / 0.014526 (0.061989) | 0.089179 / 0.176557 (-0.087377) | 0.127034 / 0.737135 (-0.610102) | 0.089646 / 0.296338 (-0.206692) |

### 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) | 0.292056 / 0.215209 (0.076847) | 2.841410 / 2.077655 (0.763756) | 1.550626 / 1.504120 (0.046506) | 1.426204 / 1.541195 (-0.114990) | 1.445838 / 1.468490 (-0.022652) | 0.555777 / 4.584777 (-4.029000) | 2.441077 / 3.745712 (-1.304635) | 2.773445 / 5.269862 (-2.496416) | 1.728951 / 4.565676 (-2.836726) | 0.062579 / 0.424275 (-0.361697) | 0.005063 / 0.007607 (-0.002544) | 0.350749 / 0.226044 (0.124705) | 3.461702 / 2.268929 (1.192773) | 1.892506 / 55.444624 (-53.552118) | 1.625958 / 6.876477 (-5.250519) | 1.649175 / 2.142072 (-0.492898) | 0.636123 / 4.805227 (-4.169105) | 0.116548 / 6.500664 (-6.384116) | 0.041174 / 0.075469 (-0.034295) |

### 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) | 0.973468 / 1.841788 (-0.868320) | 12.104761 / 8.074308 (4.030453) | 11.131691 / 10.191392 (0.940299) | 0.132309 / 0.680424 (-0.548115) | 0.016191 / 0.534201 (-0.518010) | 0.284748 / 0.579283 (-0.294535) | 0.282661 / 0.434364 (-0.151703) | 0.323797 / 0.540337 (-0.216540) | 0.417767 / 1.386936 (-0.969169) |

</details>
</details>

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