Update required soxr version from pre-release to release

[albertvillanova]

Update required soxr version from pre-release to release 0.4.0: https://github.com/dofuuz/python-soxr/releases/tag/v0.4.0

[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.

[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)	0.005717 / 0.011353 (-0.005636)	0.004102 / 0.011008 (-0.006906)	0.064343 / 0.038508 (0.025835)	0.031510 / 0.023109 (0.008400)	0.254534 / 0.275898 (-0.021364)	0.275080 / 0.323480 (-0.048400)	0.004243 / 0.007986 (-0.003742)	0.002782 / 0.004328 (-0.001546)	0.049554 / 0.004250 (0.045303)	0.045291 / 0.037052 (0.008239)	0.264118 / 0.258489 (0.005629)	0.296476 / 0.293841 (0.002635)	0.030298 / 0.128546 (-0.098248)	0.012646 / 0.075646 (-0.063000)	0.208403 / 0.419271 (-0.210869)	0.036365 / 0.043533 (-0.007168)	0.250294 / 0.255139 (-0.004845)	0.276057 / 0.283200 (-0.007143)	0.018687 / 0.141683 (-0.122996)	1.128970 / 1.452155 (-0.323184)	1.170923 / 1.492716 (-0.321793)

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)	0.134953 / 0.018006 (0.116947)	0.301722 / 0.000490 (0.301232)	0.000242 / 0.000200 (0.000042)	0.000050 / 0.000054 (-0.000005)

Benchmark: benchmark_indices_mapping.json

metric	select	shard	shuffle	sort	train_test_split
new / old (diff)	0.019650 / 0.037411 (-0.017761)	0.063404 / 0.014526 (0.048878)	0.074883 / 0.176557 (-0.101674)	0.122846 / 0.737135 (-0.614289)	0.077410 / 0.296338 (-0.218928)

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)	0.287710 / 0.215209 (0.072501)	2.813834 / 2.077655 (0.736179)	1.454710 / 1.504120 (-0.049410)	1.327303 / 1.541195 (-0.213891)	1.375064 / 1.468490 (-0.093426)	0.746831 / 4.584777 (-3.837946)	2.361008 / 3.745712 (-1.384705)	3.080869 / 5.269862 (-2.188993)	1.969927 / 4.565676 (-2.595749)	0.081045 / 0.424275 (-0.343230)	0.005168 / 0.007607 (-0.002440)	0.342657 / 0.226044 (0.116613)	3.404883 / 2.268929 (1.135955)	1.840761 / 55.444624 (-53.603863)	1.535400 / 6.876477 (-5.341076)	1.584613 / 2.142072 (-0.557460)	0.828003 / 4.805227 (-3.977224)	0.135564 / 6.500664 (-6.365100)	0.042717 / 0.075469 (-0.032752)

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)	0.985301 / 1.841788 (-0.856487)	11.945913 / 8.074308 (3.871605)	9.887577 / 10.191392 (-0.303815)	0.141261 / 0.680424 (-0.539163)	0.014961 / 0.534201 (-0.519240)	0.304134 / 0.579283 (-0.275150)	0.264733 / 0.434364 (-0.169631)	0.349993 / 0.540337 (-0.190345)	0.440390 / 1.386936 (-0.946546)

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)	0.006145 / 0.011353 (-0.005207)	0.004259 / 0.011008 (-0.006749)	0.051245 / 0.038508 (0.012737)	0.034873 / 0.023109 (0.011764)	0.274149 / 0.275898 (-0.001749)	0.299761 / 0.323480 (-0.023719)	0.004457 / 0.007986 (-0.003529)	0.002938 / 0.004328 (-0.001390)	0.049547 / 0.004250 (0.045297)	0.042441 / 0.037052 (0.005389)	0.284961 / 0.258489 (0.026472)	0.322197 / 0.293841 (0.028356)	0.033850 / 0.128546 (-0.094696)	0.012615 / 0.075646 (-0.063031)	0.061967 / 0.419271 (-0.357304)	0.035229 / 0.043533 (-0.008304)	0.273941 / 0.255139 (0.018802)	0.293395 / 0.283200 (0.010195)	0.020566 / 0.141683 (-0.121117)	1.173423 / 1.452155 (-0.278732)	1.219948 / 1.492716 (-0.272768)

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)	0.096131 / 0.018006 (0.078125)	0.305548 / 0.000490 (0.305059)	0.000217 / 0.000200 (0.000017)	0.000044 / 0.000054 (-0.000011)

Benchmark: benchmark_indices_mapping.json

metric	select	shard	shuffle	sort	train_test_split
new / old (diff)	0.023847 / 0.037411 (-0.013564)	0.079536 / 0.014526 (0.065010)	0.088889 / 0.176557 (-0.087667)	0.129181 / 0.737135 (-0.607954)	0.090879 / 0.296338 (-0.205460)

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)	0.299315 / 0.215209 (0.084106)	2.952656 / 2.077655 (0.875001)	1.587354 / 1.504120 (0.083234)	1.453420 / 1.541195 (-0.087774)	1.501784 / 1.468490 (0.033294)	0.711481 / 4.584777 (-3.873296)	0.971790 / 3.745712 (-2.773922)	2.897636 / 5.269862 (-2.372226)	1.947086 / 4.565676 (-2.618591)	0.079700 / 0.424275 (-0.344575)	0.005395 / 0.007607 (-0.002212)	0.351340 / 0.226044 (0.125296)	3.416472 / 2.268929 (1.147543)	2.007559 / 55.444624 (-53.437066)	1.660401 / 6.876477 (-5.216076)	1.837049 / 2.142072 (-0.305024)	0.817306 / 4.805227 (-3.987921)	0.135176 / 6.500664 (-6.365488)	0.041477 / 0.075469 (-0.033992)

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)	1.030033 / 1.841788 (-0.811755)	12.528661 / 8.074308 (4.454353)	10.603212 / 10.191392 (0.411820)	0.142434 / 0.680424 (-0.537989)	0.015603 / 0.534201 (-0.518598)	0.304516 / 0.579283 (-0.274767)	0.125324 / 0.434364 (-0.309040)	0.343092 / 0.540337 (-0.197245)	0.443359 / 1.386936 (-0.943577)