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Fix download for dict of dicts of URLs #6871

Merged
merged 4 commits into from
May 6, 2024
Merged

Fix download for dict of dicts of URLs #6871

merged 4 commits into from
May 6, 2024

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albertvillanova
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@albertvillanova albertvillanova commented May 6, 2024

Fix download for a dict of dicts of URLs when batched (default), introduced by:

This PR also implements regression tests.

Fix #6869, fix #6850.

@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.

@albertvillanova
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Once merged, I think a patch release is needed.

@albertvillanova
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Once the CI is green, I am merging this PR and making a patch release, @huggingface/datasets.

@albertvillanova albertvillanova merged commit 2ebd823 into main May 6, 2024
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@albertvillanova albertvillanova deleted the fix-6869 branch May 6, 2024 09:25
albertvillanova added a commit that referenced this pull request May 6, 2024
* Test DownloadManager.download with dict of dicts

* Test map_nested when batched

* Fix _single_map_nested when batched

* Fix versionadded to 2.19.0 in map_nested docstring
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github-actions bot commented May 6, 2024

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) 0.005352 / 0.011353 (-0.006001) 0.004140 / 0.011008 (-0.006868) 0.063844 / 0.038508 (0.025336) 0.030712 / 0.023109 (0.007603) 0.232790 / 0.275898 (-0.043108) 0.262334 / 0.323480 (-0.061145) 0.003264 / 0.007986 (-0.004721) 0.002654 / 0.004328 (-0.001674) 0.049775 / 0.004250 (0.045524) 0.046803 / 0.037052 (0.009751) 0.250667 / 0.258489 (-0.007822) 0.283581 / 0.293841 (-0.010260) 0.027660 / 0.128546 (-0.100886) 0.010560 / 0.075646 (-0.065087) 0.208676 / 0.419271 (-0.210596) 0.035415 / 0.043533 (-0.008118) 0.235380 / 0.255139 (-0.019759) 0.261220 / 0.283200 (-0.021980) 0.019551 / 0.141683 (-0.122132) 1.140196 / 1.452155 (-0.311959) 1.173021 / 1.492716 (-0.319696)

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) 0.092665 / 0.018006 (0.074659) 0.301524 / 0.000490 (0.301034) 0.000216 / 0.000200 (0.000016) 0.000043 / 0.000054 (-0.000011)

Benchmark: benchmark_indices_mapping.json

metric select shard shuffle sort train_test_split
new / old (diff) 0.018485 / 0.037411 (-0.018927) 0.061722 / 0.014526 (0.047196) 0.074701 / 0.176557 (-0.101855) 0.121443 / 0.737135 (-0.615692) 0.076268 / 0.296338 (-0.220070)

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) 0.284143 / 0.215209 (0.068934) 2.789979 / 2.077655 (0.712324) 1.501156 / 1.504120 (-0.002964) 1.379414 / 1.541195 (-0.161781) 1.419092 / 1.468490 (-0.049398) 0.554107 / 4.584777 (-4.030670) 2.365659 / 3.745712 (-1.380053) 2.763963 / 5.269862 (-2.505898) 1.712587 / 4.565676 (-2.853090) 0.060961 / 0.424275 (-0.363314) 0.005301 / 0.007607 (-0.002306) 0.346253 / 0.226044 (0.120209) 3.351833 / 2.268929 (1.082905) 1.831946 / 55.444624 (-53.612679) 1.556530 / 6.876477 (-5.319947) 1.574185 / 2.142072 (-0.567887) 0.630396 / 4.805227 (-4.174831) 0.116126 / 6.500664 (-6.384538) 0.042391 / 0.075469 (-0.033078)

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) 0.981430 / 1.841788 (-0.860358) 11.619671 / 8.074308 (3.545363) 9.718227 / 10.191392 (-0.473165) 0.130918 / 0.680424 (-0.549506) 0.014116 / 0.534201 (-0.520085) 0.288729 / 0.579283 (-0.290554) 0.259183 / 0.434364 (-0.175181) 0.323764 / 0.540337 (-0.216574) 0.420336 / 1.386936 (-0.966600)
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) 0.005255 / 0.011353 (-0.006098) 0.003664 / 0.011008 (-0.007344) 0.051376 / 0.038508 (0.012868) 0.030429 / 0.023109 (0.007320) 0.263090 / 0.275898 (-0.012808) 0.289959 / 0.323480 (-0.033521) 0.004214 / 0.007986 (-0.003772) 0.002782 / 0.004328 (-0.001546) 0.049043 / 0.004250 (0.044793) 0.041016 / 0.037052 (0.003964) 0.275616 / 0.258489 (0.017127) 0.303350 / 0.293841 (0.009509) 0.029484 / 0.128546 (-0.099062) 0.010329 / 0.075646 (-0.065317) 0.058680 / 0.419271 (-0.360591) 0.032818 / 0.043533 (-0.010715) 0.263368 / 0.255139 (0.008229) 0.286839 / 0.283200 (0.003640) 0.018029 / 0.141683 (-0.123654) 1.169207 / 1.452155 (-0.282948) 1.206568 / 1.492716 (-0.286148)

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) 0.101394 / 0.018006 (0.083387) 0.310414 / 0.000490 (0.309924) 0.000213 / 0.000200 (0.000013) 0.000053 / 0.000054 (-0.000002)

Benchmark: benchmark_indices_mapping.json

metric select shard shuffle sort train_test_split
new / old (diff) 0.021662 / 0.037411 (-0.015749) 0.075320 / 0.014526 (0.060794) 0.086607 / 0.176557 (-0.089949) 0.127268 / 0.737135 (-0.609867) 0.088244 / 0.296338 (-0.208095)

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) 0.293591 / 0.215209 (0.078382) 2.871845 / 2.077655 (0.794190) 1.543624 / 1.504120 (0.039504) 1.426698 / 1.541195 (-0.114497) 1.445348 / 1.468490 (-0.023142) 0.565156 / 4.584777 (-4.019621) 0.961782 / 3.745712 (-2.783930) 2.827904 / 5.269862 (-2.441958) 1.747728 / 4.565676 (-2.817949) 0.063275 / 0.424275 (-0.361000) 0.004987 / 0.007607 (-0.002620) 0.349652 / 0.226044 (0.123607) 3.448635 / 2.268929 (1.179707) 1.891734 / 55.444624 (-53.552890) 1.624274 / 6.876477 (-5.252202) 1.641531 / 2.142072 (-0.500541) 0.642081 / 4.805227 (-4.163146) 0.116136 / 6.500664 (-6.384528) 0.040807 / 0.075469 (-0.034662)

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) 1.002090 / 1.841788 (-0.839697) 12.401097 / 8.074308 (4.326788) 9.799316 / 10.191392 (-0.392076) 0.131770 / 0.680424 (-0.548654) 0.016817 / 0.534201 (-0.517384) 0.301136 / 0.579283 (-0.278147) 0.136810 / 0.434364 (-0.297554) 0.384740 / 0.540337 (-0.155598) 0.423779 / 1.386936 (-0.963157)

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Download is broken for dict of dicts: FileNotFoundError Problem loading voxpopuli dataset
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