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Release: 1.0.2
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lhoestq committed Sep 21, 2020
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2 changes: 1 addition & 1 deletion docs/source/conf.py
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# The short X.Y version
version = u''
# The full version, including alpha/beta/rc tags
release = '1.0.1'
release = '1.0.2'


# -- General configuration ---------------------------------------------------
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2 changes: 1 addition & 1 deletion setup.py
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setup(
name='datasets',
version="1.0.1",
version="1.0.2",
description=DOCLINES[0],
long_description='\n'.join(DOCLINES[2:]),
author='HuggingFace Inc.',
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2 changes: 1 addition & 1 deletion src/datasets/__init__.py
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# pylint: enable=line-too-long
# pylint: disable=g-import-not-at-top,g-bad-import-order,wrong-import-position

__version__ = "1.0.1"
__version__ = "1.0.2"

import pyarrow
from pyarrow import total_allocated_bytes
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Show benchmarks

PyArrow==0.17.1

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) 0.017517 / 0.011353 (0.006165) 0.014686 / 0.011008 (0.003678) 0.044546 / 0.038508 (0.006038) 0.028691 / 0.023109 (0.005582) 0.211335 / 0.275898 (-0.064563) 0.231019 / 0.323480 (-0.092461) 0.009572 / 0.007986 (0.001586) 0.004259 / 0.004328 (-0.000069) 0.006284 / 0.004250 (0.002034) 0.048099 / 0.037052 (0.011047) 0.201204 / 0.258489 (-0.057285) 0.236148 / 0.293841 (-0.057693) 0.152724 / 0.128546 (0.024178) 0.124807 / 0.075646 (0.049160) 0.439945 / 0.419271 (0.020674) 0.522148 / 0.043533 (0.478615) 0.213597 / 0.255139 (-0.041542) 0.215379 / 0.283200 (-0.067821) 0.080389 / 0.141683 (-0.061294) 1.868844 / 1.452155 (0.416690) 1.820780 / 1.492716 (0.328064)

Benchmark: benchmark_indices_mapping.json

metric select shard shuffle sort train_test_split
new / old (diff) 0.040076 / 0.037411 (0.002664) 0.021807 / 0.014526 (0.007281) 0.024786 / 0.176557 (-0.151771) 0.087563 / 0.737135 (-0.649572) 0.054144 / 0.296338 (-0.242194)

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) 0.233280 / 0.215209 (0.018071) 2.246511 / 2.077655 (0.168856) 1.266847 / 1.504120 (-0.237273) 1.168708 / 1.541195 (-0.372486) 1.170396 / 1.468490 (-0.298094) 6.915757 / 4.584777 (2.330980) 5.808448 / 3.745712 (2.062736) 8.606561 / 5.269862 (3.336699) 7.210716 / 4.565676 (2.645039) 0.690530 / 0.424275 (0.266255) 0.011527 / 0.007607 (0.003920) 0.280563 / 0.226044 (0.054519) 2.592837 / 2.268929 (0.323909) 1.715309 / 55.444624 (-53.729315) 1.583657 / 6.876477 (-5.292820) 1.636722 / 2.142072 (-0.505350) 6.897301 / 4.805227 (2.092074) 4.834709 / 6.500664 (-1.665955) 6.828747 / 0.075469 (6.753278)

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) 12.002632 / 1.841788 (10.160844) 14.358254 / 8.074308 (6.283946) 17.944185 / 10.191392 (7.752793) 0.454770 / 0.680424 (-0.225654) 0.290859 / 0.534201 (-0.243341) 0.781453 / 0.579283 (0.202170) 0.586412 / 0.434364 (0.152048) 0.757897 / 0.540337 (0.217560) 1.685401 / 1.386936 (0.298465)
PyArrow==1.0
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) 0.018045 / 0.011353 (0.006692) 0.015619 / 0.011008 (0.004610) 0.044719 / 0.038508 (0.006211) 0.031813 / 0.023109 (0.008704) 0.319050 / 0.275898 (0.043152) 0.350029 / 0.323480 (0.026549) 0.009682 / 0.007986 (0.001696) 0.004651 / 0.004328 (0.000322) 0.006668 / 0.004250 (0.002417) 0.050148 / 0.037052 (0.013095) 0.346335 / 0.258489 (0.087846) 0.366431 / 0.293841 (0.072590) 0.153204 / 0.128546 (0.024658) 0.141167 / 0.075646 (0.065521) 0.450117 / 0.419271 (0.030846) 0.418988 / 0.043533 (0.375455) 0.339781 / 0.255139 (0.084642) 0.345025 / 0.283200 (0.061825) 0.092614 / 0.141683 (-0.049069) 1.952272 / 1.452155 (0.500117) 1.969818 / 1.492716 (0.477101)

Benchmark: benchmark_indices_mapping.json

metric select shard shuffle sort train_test_split
new / old (diff) 0.040976 / 0.037411 (0.003565) 0.019989 / 0.014526 (0.005463) 0.024703 / 0.176557 (-0.151854) 0.078625 / 0.737135 (-0.658511) 0.025577 / 0.296338 (-0.270761)

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) 0.257447 / 0.215209 (0.042238) 2.589936 / 2.077655 (0.512281) 1.902704 / 1.504120 (0.398584) 1.827887 / 1.541195 (0.286692) 1.822600 / 1.468490 (0.354110) 6.913351 / 4.584777 (2.328574) 6.010252 / 3.745712 (2.264540) 8.097792 / 5.269862 (2.827930) 6.838945 / 4.565676 (2.273269) 0.673982 / 0.424275 (0.249707) 0.010886 / 0.007607 (0.003279) 0.289144 / 0.226044 (0.063099) 3.148939 / 2.268929 (0.880010) 2.217841 / 55.444624 (-53.226783) 2.130783 / 6.876477 (-4.745694) 2.268670 / 2.142072 (0.126597) 7.184861 / 4.805227 (2.379633) 6.131559 / 6.500664 (-0.369105) 6.883467 / 0.075469 (6.807998)

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) 11.538035 / 1.841788 (9.696247) 14.717337 / 8.074308 (6.643028) 15.507355 / 10.191392 (5.315963) 1.157759 / 0.680424 (0.477335) 0.566495 / 0.534201 (0.032294) 0.817001 / 0.579283 (0.237718) 0.603285 / 0.434364 (0.168921) 0.802129 / 0.540337 (0.261792) 1.702298 / 1.386936 (0.315362)

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Show benchmarks

PyArrow==0.17.1

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) 0.018342 / 0.011353 (0.006989) 0.015936 / 0.011008 (0.004928) 0.058387 / 0.038508 (0.019879) 0.029600 / 0.023109 (0.006490) 0.208623 / 0.275898 (-0.067275) 0.243342 / 0.323480 (-0.080138) 0.008694 / 0.007986 (0.000708) 0.004484 / 0.004328 (0.000156) 0.006316 / 0.004250 (0.002066) 0.050508 / 0.037052 (0.013455) 0.218533 / 0.258489 (-0.039956) 0.238500 / 0.293841 (-0.055341) 0.162551 / 0.128546 (0.034005) 0.137020 / 0.075646 (0.061374) 0.481597 / 0.419271 (0.062325) 0.540914 / 0.043533 (0.497381) 0.218836 / 0.255139 (-0.036303) 0.247535 / 0.283200 (-0.035665) 0.086909 / 0.141683 (-0.054774) 1.852763 / 1.452155 (0.400608) 1.978096 / 1.492716 (0.485380)

Benchmark: benchmark_indices_mapping.json

metric select shard shuffle sort train_test_split
new / old (diff) 0.041684 / 0.037411 (0.004273) 0.021637 / 0.014526 (0.007111) 0.131287 / 0.176557 (-0.045270) 0.824893 / 0.737135 (0.087758) 0.151306 / 0.296338 (-0.145033)

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) 0.231241 / 0.215209 (0.016032) 2.274731 / 2.077655 (0.197076) 1.351204 / 1.504120 (-0.152916) 1.287851 / 1.541195 (-0.253344) 1.283696 / 1.468490 (-0.184794) 7.274305 / 4.584777 (2.689528) 6.073168 / 3.745712 (2.327456) 8.725166 / 5.269862 (3.455305) 7.633306 / 4.565676 (3.067629) 0.737687 / 0.424275 (0.313412) 0.012024 / 0.007607 (0.004417) 0.268569 / 0.226044 (0.042525) 2.796468 / 2.268929 (0.527539) 1.913522 / 55.444624 (-53.531102) 1.698895 / 6.876477 (-5.177582) 1.799267 / 2.142072 (-0.342805) 7.436428 / 4.805227 (2.631201) 11.384505 / 6.500664 (4.883841) 7.819267 / 0.075469 (7.743798)

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) 12.374582 / 1.841788 (10.532794) 32.682348 / 8.074308 (24.608040) 15.944372 / 10.191392 (5.752980) 0.497807 / 0.680424 (-0.182617) 0.318038 / 0.534201 (-0.216163) 0.880079 / 0.579283 (0.300796) 0.655726 / 0.434364 (0.221362) 0.824921 / 0.540337 (0.284584) 1.767440 / 1.386936 (0.380504)
PyArrow==1.0
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) 0.020223 / 0.011353 (0.008870) 0.016776 / 0.011008 (0.005767) 0.049614 / 0.038508 (0.011106) 0.033322 / 0.023109 (0.010213) 0.357126 / 0.275898 (0.081228) 0.392324 / 0.323480 (0.068844) 0.009716 / 0.007986 (0.001730) 0.004932 / 0.004328 (0.000603) 0.007161 / 0.004250 (0.002911) 0.054447 / 0.037052 (0.017395) 0.357727 / 0.258489 (0.099237) 0.395505 / 0.293841 (0.101664) 0.167621 / 0.128546 (0.039074) 0.132917 / 0.075646 (0.057271) 0.479182 / 0.419271 (0.059910) 0.474593 / 0.043533 (0.431060) 0.365637 / 0.255139 (0.110498) 0.395301 / 0.283200 (0.112101) 0.102557 / 0.141683 (-0.039126) 1.945049 / 1.452155 (0.492894) 2.069868 / 1.492716 (0.577152)

Benchmark: benchmark_indices_mapping.json

metric select shard shuffle sort train_test_split
new / old (diff) 0.046704 / 0.037411 (0.009293) 0.022734 / 0.014526 (0.008208) 0.027966 / 0.176557 (-0.148590) 0.094047 / 0.737135 (-0.643088) 0.030258 / 0.296338 (-0.266081)

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) 0.268428 / 0.215209 (0.053218) 2.737745 / 2.077655 (0.660090) 2.020311 / 1.504120 (0.516191) 1.884463 / 1.541195 (0.343268) 1.975436 / 1.468490 (0.506946) 7.428766 / 4.584777 (2.843989) 6.343407 / 3.745712 (2.597695) 8.907672 / 5.269862 (3.637811) 7.756281 / 4.565676 (3.190605) 0.738926 / 0.424275 (0.314650) 0.011389 / 0.007607 (0.003782) 0.366026 / 0.226044 (0.139982) 3.551572 / 2.268929 (1.282644) 2.637733 / 55.444624 (-52.806891) 2.503064 / 6.876477 (-4.373413) 2.399149 / 2.142072 (0.257076) 7.508566 / 4.805227 (2.703339) 5.467306 / 6.500664 (-1.033358) 7.160707 / 0.075469 (7.085238)

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) 12.492845 / 1.841788 (10.651057) 14.680753 / 8.074308 (6.606445) 16.485027 / 10.191392 (6.293635) 1.011702 / 0.680424 (0.331278) 0.657891 / 0.534201 (0.123690) 0.952473 / 0.579283 (0.373190) 0.716704 / 0.434364 (0.282340) 0.864711 / 0.540337 (0.324373) 1.824882 / 1.386936 (0.437946)

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