Update docs of S3 filesystem with async aiobotocore

[maheshpec]

s3fs has migrated to all async calls.
Updating documentation to use AioSession while using s3fs for download manager as well as working with datasets

[HuggingFaceDocBuilderDev]

The documentation is not available anymore as the PR was closed or merged.

[albertvillanova]

Thanks for the fix, @maheshpec!

[github-actions]

Show benchmarks

PyArrow==6.0.0

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)	0.008587 / 0.011353 (-0.002766)	0.004613 / 0.011008 (-0.006395)	0.100446 / 0.038508 (0.061938)	0.029606 / 0.023109 (0.006497)	0.302102 / 0.275898 (0.026204)	0.357364 / 0.323480 (0.033884)	0.007031 / 0.007986 (-0.000954)	0.003593 / 0.004328 (-0.000735)	0.078110 / 0.004250 (0.073860)	0.035495 / 0.037052 (-0.001557)	0.312522 / 0.258489 (0.054033)	0.349336 / 0.293841 (0.055495)	0.033719 / 0.128546 (-0.094827)	0.011449 / 0.075646 (-0.064197)	0.321760 / 0.419271 (-0.097512)	0.043697 / 0.043533 (0.000165)	0.304476 / 0.255139 (0.049337)	0.333126 / 0.283200 (0.049926)	0.092756 / 0.141683 (-0.048927)	1.506734 / 1.452155 (0.054579)	1.547381 / 1.492716 (0.054664)

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)	0.178177 / 0.018006 (0.160171)	0.427814 / 0.000490 (0.427324)	0.002505 / 0.000200 (0.002305)	0.000074 / 0.000054 (0.000020)

Benchmark: benchmark_indices_mapping.json

metric	select	shard	shuffle	sort	train_test_split
new / old (diff)	0.023039 / 0.037411 (-0.014372)	0.097113 / 0.014526 (0.082587)	0.105014 / 0.176557 (-0.071543)	0.141185 / 0.737135 (-0.595950)	0.108843 / 0.296338 (-0.187495)

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)	0.424148 / 0.215209 (0.208939)	4.247599 / 2.077655 (2.169944)	2.130720 / 1.504120 (0.626600)	1.916349 / 1.541195 (0.375154)	1.831515 / 1.468490 (0.363025)	0.688301 / 4.584777 (-3.896476)	3.381749 / 3.745712 (-0.363963)	2.900045 / 5.269862 (-2.369817)	1.576248 / 4.565676 (-2.989428)	0.082354 / 0.424275 (-0.341921)	0.012200 / 0.007607 (0.004593)	0.525753 / 0.226044 (0.299709)	5.277672 / 2.268929 (3.008743)	2.603870 / 55.444624 (-52.840754)	2.296203 / 6.876477 (-4.580273)	2.308014 / 2.142072 (0.165942)	0.809056 / 4.805227 (-3.996171)	0.148122 / 6.500664 (-6.352542)	0.066097 / 0.075469 (-0.009372)

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)	1.214059 / 1.841788 (-0.627728)	13.671332 / 8.074308 (5.597024)	13.694554 / 10.191392 (3.503162)	0.151454 / 0.680424 (-0.528970)	0.028514 / 0.534201 (-0.505687)	0.391480 / 0.579283 (-0.187804)	0.404499 / 0.434364 (-0.029865)	0.458111 / 0.540337 (-0.082226)	0.539454 / 1.386936 (-0.847482)

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)	0.006795 / 0.011353 (-0.004558)	0.004463 / 0.011008 (-0.006545)	0.099542 / 0.038508 (0.061034)	0.027588 / 0.023109 (0.004479)	0.423023 / 0.275898 (0.147125)	0.458459 / 0.323480 (0.134979)	0.004981 / 0.007986 (-0.003005)	0.003321 / 0.004328 (-0.001008)	0.075727 / 0.004250 (0.071477)	0.040541 / 0.037052 (0.003489)	0.423724 / 0.258489 (0.165235)	0.468334 / 0.293841 (0.174493)	0.031732 / 0.128546 (-0.096814)	0.011478 / 0.075646 (-0.064168)	0.319807 / 0.419271 (-0.099465)	0.041215 / 0.043533 (-0.002318)	0.423060 / 0.255139 (0.167921)	0.446157 / 0.283200 (0.162957)	0.088884 / 0.141683 (-0.052799)	1.553404 / 1.452155 (0.101250)	1.607797 / 1.492716 (0.115080)

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)	0.208314 / 0.018006 (0.190307)	0.411627 / 0.000490 (0.411137)	0.002416 / 0.000200 (0.002216)	0.000078 / 0.000054 (0.000024)

Benchmark: benchmark_indices_mapping.json

metric	select	shard	shuffle	sort	train_test_split
new / old (diff)	0.024641 / 0.037411 (-0.012770)	0.101047 / 0.014526 (0.086521)	0.108410 / 0.176557 (-0.068147)	0.142860 / 0.737135 (-0.594276)	0.112486 / 0.296338 (-0.183852)

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)	0.485520 / 0.215209 (0.270311)	4.864009 / 2.077655 (2.786355)	2.541865 / 1.504120 (1.037745)	2.339569 / 1.541195 (0.798374)	2.378258 / 1.468490 (0.909768)	0.698000 / 4.584777 (-3.886777)	3.343137 / 3.745712 (-0.402575)	1.842264 / 5.269862 (-3.427597)	1.154707 / 4.565676 (-3.410969)	0.082826 / 0.424275 (-0.341449)	0.012379 / 0.007607 (0.004772)	0.583335 / 0.226044 (0.357291)	5.885934 / 2.268929 (3.617006)	2.997769 / 55.444624 (-52.446856)	2.653681 / 6.876477 (-4.222796)	2.761656 / 2.142072 (0.619583)	0.799883 / 4.805227 (-4.005344)	0.151398 / 6.500664 (-6.349266)	0.067445 / 0.075469 (-0.008024)

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)	1.292009 / 1.841788 (-0.549779)	13.976180 / 8.074308 (5.901872)	14.219469 / 10.191392 (4.028077)	0.127810 / 0.680424 (-0.552614)	0.016919 / 0.534201 (-0.517282)	0.376401 / 0.579283 (-0.202882)	0.388563 / 0.434364 (-0.045801)	0.444904 / 0.540337 (-0.095433)	0.532290 / 1.386936 (-0.854646)