packaging: Remove useless dependencies

[daskol]

Revert changes in #6396 and #6404. CVE-2023-47248 has been fixed since PyArrow v14.0.1. Meanwhile Python requirements requires pyarrow>=15.0.0.

[HuggingFaceDocBuilderDev]

The docs for this PR live here. All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.

[daskol]

@HuggingFaceDocBuilderDev There is no doc for this change. Call a human.

[lhoestq]

Haha it was me who triggered the CI for your PR

[lhoestq]

Thanks for the update !

[github-actions]

Show benchmarks

PyArrow==8.0.0

Show updated benchmarks!

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)	0.005051 / 0.011353 (-0.006302)	0.004831 / 0.011008 (-0.006178)	0.063006 / 0.038508 (0.024498)	0.031589 / 0.023109 (0.008480)	0.296202 / 0.275898 (0.020304)	0.274274 / 0.323480 (-0.049205)	0.003199 / 0.007986 (-0.004786)	0.002768 / 0.004328 (-0.001561)	0.049422 / 0.004250 (0.045172)	0.045174 / 0.037052 (0.008121)	0.263814 / 0.258489 (0.005325)	0.288125 / 0.293841 (-0.005716)	0.027641 / 0.128546 (-0.100905)	0.010439 / 0.075646 (-0.065207)	0.203075 / 0.419271 (-0.216196)	0.036259 / 0.043533 (-0.007274)	0.245159 / 0.255139 (-0.009980)	0.268897 / 0.283200 (-0.014303)	0.019493 / 0.141683 (-0.122190)	1.108330 / 1.452155 (-0.343824)	1.155835 / 1.492716 (-0.336881)

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)	0.096860 / 0.018006 (0.078854)	0.309428 / 0.000490 (0.308938)	0.000197 / 0.000200 (-0.000003)	0.000044 / 0.000054 (-0.000011)

Benchmark: benchmark_indices_mapping.json

metric	select	shard	shuffle	sort	train_test_split
new / old (diff)	0.019275 / 0.037411 (-0.018136)	0.062623 / 0.014526 (0.048098)	0.073871 / 0.176557 (-0.102686)	0.120410 / 0.737135 (-0.616726)	0.075766 / 0.296338 (-0.220572)

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)	0.279876 / 0.215209 (0.064667)	2.742429 / 2.077655 (0.664774)	1.414368 / 1.504120 (-0.089752)	1.293194 / 1.541195 (-0.248001)	1.318043 / 1.468490 (-0.150447)	0.570904 / 4.584777 (-4.013873)	2.384386 / 3.745712 (-1.361326)	2.757953 / 5.269862 (-2.511908)	1.728766 / 4.565676 (-2.836910)	0.062699 / 0.424275 (-0.361576)	0.004951 / 0.007607 (-0.002656)	0.332222 / 0.226044 (0.106177)	3.407429 / 2.268929 (1.138500)	1.777136 / 55.444624 (-53.667488)	1.521269 / 6.876477 (-5.355207)	1.544814 / 2.142072 (-0.597258)	0.646249 / 4.805227 (-4.158978)	0.117032 / 6.500664 (-6.383632)	0.042274 / 0.075469 (-0.033195)

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)	1.016249 / 1.841788 (-0.825539)	11.794003 / 8.074308 (3.719695)	9.871925 / 10.191392 (-0.319467)	0.133694 / 0.680424 (-0.546730)	0.014904 / 0.534201 (-0.519297)	0.287453 / 0.579283 (-0.291831)	0.271802 / 0.434364 (-0.162561)	0.324711 / 0.540337 (-0.215626)	0.411812 / 1.386936 (-0.975124)

PyArrow==latest

Show updated benchmarks!

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)	0.005376 / 0.011353 (-0.005977)	0.003631 / 0.011008 (-0.007377)	0.050154 / 0.038508 (0.011646)	0.033665 / 0.023109 (0.010556)	0.279062 / 0.275898 (0.003164)	0.298899 / 0.323480 (-0.024581)	0.004388 / 0.007986 (-0.003598)	0.002810 / 0.004328 (-0.001518)	0.049032 / 0.004250 (0.044781)	0.040531 / 0.037052 (0.003478)	0.287220 / 0.258489 (0.028731)	0.319060 / 0.293841 (0.025219)	0.029473 / 0.128546 (-0.099073)	0.010317 / 0.075646 (-0.065329)	0.058483 / 0.419271 (-0.360789)	0.033359 / 0.043533 (-0.010174)	0.276404 / 0.255139 (0.021265)	0.295013 / 0.283200 (0.011813)	0.019372 / 0.141683 (-0.122311)	1.172624 / 1.452155 (-0.279531)	1.176815 / 1.492716 (-0.315902)

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)	0.097347 / 0.018006 (0.079341)	0.306959 / 0.000490 (0.306469)	0.000200 / 0.000200 (-0.000000)	0.000044 / 0.000054 (-0.000011)

Benchmark: benchmark_indices_mapping.json

metric	select	shard	shuffle	sort	train_test_split
new / old (diff)	0.022776 / 0.037411 (-0.014635)	0.077865 / 0.014526 (0.063340)	0.088806 / 0.176557 (-0.087751)	0.130448 / 0.737135 (-0.606687)	0.090973 / 0.296338 (-0.205365)

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)	0.301168 / 0.215209 (0.085959)	2.957634 / 2.077655 (0.879979)	1.556999 / 1.504120 (0.052879)	1.413940 / 1.541195 (-0.127255)	1.427970 / 1.468490 (-0.040520)	0.587653 / 4.584777 (-3.997124)	0.951295 / 3.745712 (-2.794417)	2.691004 / 5.269862 (-2.578858)	1.755826 / 4.565676 (-2.809851)	0.064883 / 0.424275 (-0.359392)	0.005379 / 0.007607 (-0.002228)	0.353790 / 0.226044 (0.127745)	3.457747 / 2.268929 (1.188818)	1.891884 / 55.444624 (-53.552740)	1.616619 / 6.876477 (-5.259858)	1.736167 / 2.142072 (-0.405906)	0.669257 / 4.805227 (-4.135970)	0.119620 / 6.500664 (-6.381044)	0.041390 / 0.075469 (-0.034080)

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)	1.008851 / 1.841788 (-0.832937)	13.151216 / 8.074308 (5.076908)	10.398371 / 10.191392 (0.206979)	0.143420 / 0.680424 (-0.537004)	0.015759 / 0.534201 (-0.518442)	0.293068 / 0.579283 (-0.286215)	0.131449 / 0.434364 (-0.302914)	0.334715 / 0.540337 (-0.205623)	0.445824 / 1.386936 (-0.941112)