Fix fsspec tqdm callback
Opened by lhoestq (closed)

Following changes at https://github.com/fsspec/filesystem_spec/pull/1497 for `fsspec>=2024.2.0`

Comments:
The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6749). 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) | 0.005017 / 0.011353 (-0.006336) | 0.002958 / 0.011008 (-0.008050) | 0.063455 / 0.038508 (0.024946) | 0.028206 / 0.023109 (0.005096) | 0.230884 / 0.275898 (-0.045014) | 0.252688 / 0.323480 (-0.070792) | 0.002995 / 0.007986 (-0.004991) | 0.002613 / 0.004328 (-0.001716) | 0.046477 / 0.004250 (0.042226) | 0.040662 / 0.037052 (0.003609) | 0.241824 / 0.258489 (-0.016665) | 0.269063 / 0.293841 (-0.024778) | 0.027336 / 0.128546 (-0.101210) | 0.010614 / 0.075646 (-0.065032) | 0.216087 / 0.419271 (-0.203184) | 0.035667 / 0.043533 (-0.007866) | 0.238657 / 0.255139 (-0.016482) | 0.253433 / 0.283200 (-0.029767) | 0.017433 / 0.141683 (-0.124250) | 1.120856 / 1.452155 (-0.331299) | 1.157415 / 1.492716 (-0.335302) |

### 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) | 0.088028 / 0.018006 (0.070022) | 0.277368 / 0.000490 (0.276878) | 0.000204 / 0.000200 (0.000004) | 0.000049 / 0.000054 (-0.000005) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.017956 / 0.037411 (-0.019455) | 0.061061 / 0.014526 (0.046535) | 0.073323 / 0.176557 (-0.103234) | 0.119254 / 0.737135 (-0.617881) | 0.074308 / 0.296338 (-0.222031) |

### 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) | 0.285118 / 0.215209 (0.069908) | 2.785796 / 2.077655 (0.708142) | 1.476436 / 1.504120 (-0.027684) | 1.356505 / 1.541195 (-0.184690) | 1.362505 / 1.468490 (-0.105985) | 0.554064 / 4.584777 (-4.030713) | 2.395774 / 3.745712 (-1.349938) | 2.713703 / 5.269862 (-2.556159) | 1.701020 / 4.565676 (-2.864657) | 0.062370 / 0.424275 (-0.361905) | 0.004944 / 0.007607 (-0.002663) | 0.327948 / 0.226044 (0.101904) | 3.243739 / 2.268929 (0.974811) | 1.803881 / 55.444624 (-53.640743) | 1.551635 / 6.876477 (-5.324841) | 1.560627 / 2.142072 (-0.581446) | 0.628187 / 4.805227 (-4.177040) | 0.115824 / 6.500664 (-6.384840) | 0.041655 / 0.075469 (-0.033814) |

### 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) | 0.968797 / 1.841788 (-0.872991) | 11.220905 / 8.074308 (3.146597) | 9.322584 / 10.191392 (-0.868808) | 0.139629 / 0.680424 (-0.540795) | 0.013823 / 0.534201 (-0.520378) | 0.286700 / 0.579283 (-0.292583) | 0.263517 / 0.434364 (-0.170847) | 0.341264 / 0.540337 (-0.199074) | 0.418834 / 1.386936 (-0.968102) |

</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) | 0.005404 / 0.011353 (-0.005949) | 0.003630 / 0.011008 (-0.007378) | 0.048977 / 0.038508 (0.010469) | 0.029980 / 0.023109 (0.006871) | 0.274671 / 0.275898 (-0.001227) | 0.295671 / 0.323480 (-0.027808) | 0.004230 / 0.007986 (-0.003756) | 0.002656 / 0.004328 (-0.001672) | 0.048603 / 0.004250 (0.044353) | 0.044323 / 0.037052 (0.007271) | 0.286499 / 0.258489 (0.028010) | 0.313199 / 0.293841 (0.019358) | 0.030079 / 0.128546 (-0.098468) | 0.010480 / 0.075646 (-0.065166) | 0.058226 / 0.419271 (-0.361045) | 0.054920 / 0.043533 (0.011387) | 0.274921 / 0.255139 (0.019783) | 0.296559 / 0.283200 (0.013360) | 0.019164 / 0.141683 (-0.122519) | 1.154703 / 1.452155 (-0.297452) | 1.207015 / 1.492716 (-0.285701) |

### 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) | 0.089368 / 0.018006 (0.071362) | 0.301196 / 0.000490 (0.300706) | 0.000208 / 0.000200 (0.000008) | 0.000047 / 0.000054 (-0.000008) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.021355 / 0.037411 (-0.016056) | 0.074688 / 0.014526 (0.060162) | 0.085840 / 0.176557 (-0.090716) | 0.125784 / 0.737135 (-0.611351) | 0.087103 / 0.296338 (-0.209235) |

### 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) | 0.296727 / 0.215209 (0.081518) | 2.884922 / 2.077655 (0.807267) | 1.586515 / 1.504120 (0.082395) | 1.474417 / 1.541195 (-0.066777) | 1.492105 / 1.468490 (0.023615) | 0.570016 / 4.584777 (-4.014761) | 2.435760 / 3.745712 (-1.309952) | 2.657999 / 5.269862 (-2.611863) | 1.740160 / 4.565676 (-2.825516) | 0.063743 / 0.424275 (-0.360532) | 0.005048 / 0.007607 (-0.002559) | 0.341279 / 0.226044 (0.115235) | 3.396185 / 2.268929 (1.127256) | 1.952825 / 55.444624 (-53.491800) | 1.676669 / 6.876477 (-5.199808) | 1.773158 / 2.142072 (-0.368915) | 0.650664 / 4.805227 (-4.154563) | 0.116815 / 6.500664 (-6.383849) | 0.040813 / 0.075469 (-0.034656) |

### 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) | 0.999836 / 1.841788 (-0.841952) | 11.854540 / 8.074308 (3.780232) | 10.245516 / 10.191392 (0.054124) | 0.141235 / 0.680424 (-0.539189) | 0.015562 / 0.534201 (-0.518639) | 0.287556 / 0.579283 (-0.291727) | 0.274946 / 0.434364 (-0.159418) | 0.324652 / 0.540337 (-0.215685) | 0.449204 / 1.386936 (-0.937733) |

</details>
</details>

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