Skip to content

Commit

Permalink
flake8
Browse files Browse the repository at this point in the history
  • Loading branch information
@Wauplin
Wauplin committed Sep 26, 2022
1 parent 2442b4c commit c4c93cf
Showing 1 changed file with 0 additions and 1 deletion.
1 change: 0 additions & 1 deletion tests/fixtures/hub.py
View file
@@ -1,4 +1,3 @@
import os.path
import time
from contextlib import contextmanager
from pathlib import Path
Expand Down

1 comment on commit c4c93cf

@github-actions
Copy link

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

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) 0.008298 / 0.011353 (-0.003055) 0.004098 / 0.011008 (-0.006910) 0.029930 / 0.038508 (-0.008578) 0.035404 / 0.023109 (0.012295) 0.305293 / 0.275898 (0.029395) 0.373914 / 0.323480 (0.050434) 0.006139 / 0.007986 (-0.001847) 0.004981 / 0.004328 (0.000652) 0.007104 / 0.004250 (0.002853) 0.052773 / 0.037052 (0.015720) 0.317656 / 0.258489 (0.059167) 0.365898 / 0.293841 (0.072057) 0.032074 / 0.128546 (-0.096473) 0.009820 / 0.075646 (-0.065826) 0.257549 / 0.419271 (-0.161723) 0.052056 / 0.043533 (0.008523) 0.303163 / 0.255139 (0.048024) 0.319304 / 0.283200 (0.036104) 0.104967 / 0.141683 (-0.036715) 1.460650 / 1.452155 (0.008496) 1.499307 / 1.492716 (0.006590)

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) 0.273296 / 0.018006 (0.255290) 0.534983 / 0.000490 (0.534493) 0.003119 / 0.000200 (0.002919) 0.000092 / 0.000054 (0.000037)

Benchmark: benchmark_indices_mapping.json

metric select shard shuffle sort train_test_split
new / old (diff) 0.024487 / 0.037411 (-0.012924) 0.099819 / 0.014526 (0.085293) 0.114478 / 0.176557 (-0.062078) 0.161694 / 0.737135 (-0.575441) 0.117420 / 0.296338 (-0.178918)

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) 0.399918 / 0.215209 (0.184709) 3.988060 / 2.077655 (1.910405) 1.831172 / 1.504120 (0.327052) 1.651217 / 1.541195 (0.110023) 1.654132 / 1.468490 (0.185642) 0.421271 / 4.584777 (-4.163506) 3.741413 / 3.745712 (-0.004299) 3.350146 / 5.269862 (-1.919715) 1.735354 / 4.565676 (-2.830322) 0.051620 / 0.424275 (-0.372655) 0.011124 / 0.007607 (0.003517) 0.505012 / 0.226044 (0.278968) 5.055045 / 2.268929 (2.786117) 2.252807 / 55.444624 (-53.191817) 1.907270 / 6.876477 (-4.969207) 2.039765 / 2.142072 (-0.102308) 0.538466 / 4.805227 (-4.266762) 0.120411 / 6.500664 (-6.380253) 0.062470 / 0.075469 (-0.012999)

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) 1.497936 / 1.841788 (-0.343852) 13.567576 / 8.074308 (5.493268) 24.916921 / 10.191392 (14.725529) 0.865712 / 0.680424 (0.185289) 0.569391 / 0.534201 (0.035190) 0.384332 / 0.579283 (-0.194951) 0.427510 / 0.434364 (-0.006854) 0.269821 / 0.540337 (-0.270516) 0.270867 / 1.386936 (-1.116069)
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) 0.005885 / 0.011353 (-0.005468) 0.003991 / 0.011008 (-0.007017) 0.027905 / 0.038508 (-0.010603) 0.033054 / 0.023109 (0.009945) 0.337562 / 0.275898 (0.061664) 0.420815 / 0.323480 (0.097335) 0.004064 / 0.007986 (-0.003922) 0.003626 / 0.004328 (-0.000702) 0.005024 / 0.004250 (0.000774) 0.047622 / 0.037052 (0.010570) 0.351954 / 0.258489 (0.093465) 0.400032 / 0.293841 (0.106191) 0.030264 / 0.128546 (-0.098282) 0.009766 / 0.075646 (-0.065881) 0.256616 / 0.419271 (-0.162655) 0.054451 / 0.043533 (0.010918) 0.342228 / 0.255139 (0.087089) 0.361088 / 0.283200 (0.077889) 0.104240 / 0.141683 (-0.037443) 1.467411 / 1.452155 (0.015256) 1.512245 / 1.492716 (0.019529)

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) 0.299383 / 0.018006 (0.281377) 0.516571 / 0.000490 (0.516081) 0.004881 / 0.000200 (0.004681) 0.000101 / 0.000054 (0.000046)

Benchmark: benchmark_indices_mapping.json

metric select shard shuffle sort train_test_split
new / old (diff) 0.023224 / 0.037411 (-0.014188) 0.100695 / 0.014526 (0.086169) 0.112865 / 0.176557 (-0.063692) 0.156695 / 0.737135 (-0.580441) 0.118520 / 0.296338 (-0.177819)

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) 0.424000 / 0.215209 (0.208791) 4.218534 / 2.077655 (2.140879) 2.026214 / 1.504120 (0.522094) 1.845245 / 1.541195 (0.304050) 1.891301 / 1.468490 (0.422811) 0.430172 / 4.584777 (-4.154605) 3.755428 / 3.745712 (0.009716) 2.082090 / 5.269862 (-3.187771) 1.258040 / 4.565676 (-3.307637) 0.051986 / 0.424275 (-0.372289) 0.011292 / 0.007607 (0.003685) 0.525584 / 0.226044 (0.299539) 5.256033 / 2.268929 (2.987105) 2.454373 / 55.444624 (-52.990251) 2.111508 / 6.876477 (-4.764969) 2.282030 / 2.142072 (0.139957) 0.544254 / 4.805227 (-4.260973) 0.120774 / 6.500664 (-6.379890) 0.061821 / 0.075469 (-0.013648)

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) 1.528962 / 1.841788 (-0.312826) 13.818863 / 8.074308 (5.744555) 25.144979 / 10.191392 (14.953587) 0.923953 / 0.680424 (0.243529) 0.597084 / 0.534201 (0.062883) 0.385006 / 0.579283 (-0.194277) 0.430832 / 0.434364 (-0.003532) 0.265541 / 0.540337 (-0.274796) 0.271462 / 1.386936 (-1.115474)

CML watermark

Please sign in to comment.