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Update github pr docs actions (#5214)
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Mishig authored Nov 8, 2022
1 parent e706514 commit a805ec6
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Showing 2 changed files with 9 additions and 3 deletions.
5 changes: 4 additions & 1 deletion .github/workflows/build_pr_documentation.yml
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Original file line number Diff line number Diff line change
Expand Up @@ -9,8 +9,11 @@ concurrency:

jobs:
build:
uses: huggingface/doc-builder/.github/workflows/build_pr_documentation.yml@main
uses: huggingface/doc-builder/.github/workflows/build_pr_documentation.yml@use_hf_hub
with:
commit_sha: ${{ github.event.pull_request.head.sha }}
pr_number: ${{ github.event.number }}
package: datasets
secrets:
token: ${{ secrets.HF_DOC_PUSH }}
comment_bot_token: ${{ secrets.HUGGINGFACE_PUSH }}
7 changes: 5 additions & 2 deletions .github/workflows/delete_doc_comment.yml
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Original file line number Diff line number Diff line change
Expand Up @@ -7,7 +7,10 @@ on:

jobs:
delete:
uses: huggingface/doc-builder/.github/workflows/delete_doc_comment.yml@main
uses: huggingface/doc-builder/.github/workflows/delete_doc_comment.yml@use_hf_hub
with:
pr_number: ${{ github.event.number }}
package: datasets
package: datasets
secrets:
token: ${{ secrets.HF_DOC_PUSH }}
comment_bot_token: ${{ secrets.HUGGINGFACE_PUSH }}

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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) 0.008663 / 0.011353 (-0.002690) 0.004548 / 0.011008 (-0.006460) 0.098904 / 0.038508 (0.060396) 0.029905 / 0.023109 (0.006796) 0.302140 / 0.275898 (0.026242) 0.360218 / 0.323480 (0.036738) 0.006956 / 0.007986 (-0.001029) 0.003373 / 0.004328 (-0.000956) 0.077012 / 0.004250 (0.072761) 0.039336 / 0.037052 (0.002283) 0.313314 / 0.258489 (0.054825) 0.349743 / 0.293841 (0.055902) 0.037910 / 0.128546 (-0.090636) 0.014418 / 0.075646 (-0.061228) 0.326888 / 0.419271 (-0.092383) 0.044107 / 0.043533 (0.000574) 0.317746 / 0.255139 (0.062607) 0.334195 / 0.283200 (0.050995) 0.090272 / 0.141683 (-0.051411) 1.490575 / 1.452155 (0.038421) 1.528764 / 1.492716 (0.036048)

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) 0.192161 / 0.018006 (0.174155) 0.413319 / 0.000490 (0.412829) 0.003492 / 0.000200 (0.003292) 0.000074 / 0.000054 (0.000020)

Benchmark: benchmark_indices_mapping.json

metric select shard shuffle sort train_test_split
new / old (diff) 0.023369 / 0.037411 (-0.014042) 0.096972 / 0.014526 (0.082446) 0.106561 / 0.176557 (-0.069996) 0.141517 / 0.737135 (-0.595618) 0.108603 / 0.296338 (-0.187736)

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) 0.421831 / 0.215209 (0.206622) 4.178058 / 2.077655 (2.100404) 1.884817 / 1.504120 (0.380697) 1.661347 / 1.541195 (0.120152) 1.734860 / 1.468490 (0.266370) 0.700535 / 4.584777 (-3.884242) 3.381107 / 3.745712 (-0.364605) 1.927202 / 5.269862 (-3.342659) 1.277394 / 4.565676 (-3.288283) 0.081436 / 0.424275 (-0.342839) 0.011461 / 0.007607 (0.003854) 0.523359 / 0.226044 (0.297314) 5.229726 / 2.268929 (2.960797) 2.277614 / 55.444624 (-53.167010) 1.930907 / 6.876477 (-4.945570) 1.957643 / 2.142072 (-0.184429) 0.817754 / 4.805227 (-3.987474) 0.148597 / 6.500664 (-6.352067) 0.063061 / 0.075469 (-0.012409)

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) 1.490759 / 1.841788 (-0.351028) 12.541230 / 8.074308 (4.466922) 26.617028 / 10.191392 (16.425636) 0.831415 / 0.680424 (0.150991) 0.562588 / 0.534201 (0.028387) 0.387316 / 0.579283 (-0.191967) 0.401141 / 0.434364 (-0.033223) 0.232330 / 0.540337 (-0.308007) 0.235634 / 1.386936 (-1.151302)
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) 0.006683 / 0.011353 (-0.004669) 0.004562 / 0.011008 (-0.006446) 0.097248 / 0.038508 (0.058740) 0.027610 / 0.023109 (0.004501) 0.340047 / 0.275898 (0.064149) 0.405651 / 0.323480 (0.082171) 0.004858 / 0.007986 (-0.003128) 0.003327 / 0.004328 (-0.001002) 0.074242 / 0.004250 (0.069992) 0.032492 / 0.037052 (-0.004560) 0.346506 / 0.258489 (0.088017) 0.382357 / 0.293841 (0.088516) 0.033591 / 0.128546 (-0.094955) 0.011540 / 0.075646 (-0.064106) 0.319589 / 0.419271 (-0.099683) 0.041072 / 0.043533 (-0.002461) 0.340405 / 0.255139 (0.085266) 0.369743 / 0.283200 (0.086543) 0.089882 / 0.141683 (-0.051801) 1.552434 / 1.452155 (0.100279) 1.539741 / 1.492716 (0.047024)

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) 0.219924 / 0.018006 (0.201918) 0.401204 / 0.000490 (0.400715) 0.004639 / 0.000200 (0.004439) 0.000080 / 0.000054 (0.000026)

Benchmark: benchmark_indices_mapping.json

metric select shard shuffle sort train_test_split
new / old (diff) 0.025233 / 0.037411 (-0.012178) 0.099717 / 0.014526 (0.085191) 0.110289 / 0.176557 (-0.066268) 0.152248 / 0.737135 (-0.584888) 0.110641 / 0.296338 (-0.185698)

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) 0.453323 / 0.215209 (0.238114) 4.509991 / 2.077655 (2.432336) 2.352719 / 1.504120 (0.848599) 2.183649 / 1.541195 (0.642454) 2.226305 / 1.468490 (0.757815) 0.706460 / 4.584777 (-3.878317) 3.389749 / 3.745712 (-0.355963) 2.550923 / 5.269862 (-2.718938) 1.498924 / 4.565676 (-3.066753) 0.081984 / 0.424275 (-0.342291) 0.012016 / 0.007607 (0.004409) 0.557375 / 0.226044 (0.331330) 5.602057 / 2.268929 (3.333129) 2.785770 / 55.444624 (-52.658854) 2.490857 / 6.876477 (-4.385619) 2.573356 / 2.142072 (0.431283) 0.812245 / 4.805227 (-3.992982) 0.152170 / 6.500664 (-6.348494) 0.065674 / 0.075469 (-0.009795)

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) 1.579365 / 1.841788 (-0.262423) 12.730118 / 8.074308 (4.655810) 12.083019 / 10.191392 (1.891627) 0.896857 / 0.680424 (0.216433) 0.621138 / 0.534201 (0.086937) 0.375031 / 0.579283 (-0.204252) 0.389458 / 0.434364 (-0.044906) 0.224665 / 0.540337 (-0.315672) 0.230018 / 1.386936 (-1.156918)

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