Skip to content

Commit

Permalink
CI test
Browse files Browse the repository at this point in the history
  • Loading branch information
@mariosasko
mariosasko committed Jul 22, 2022
1 parent 30de7fa commit 983b04e
Showing 0 changed files with 0 additions and 0 deletions.

1 comment on commit 983b04e

@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) 0.009102 / 0.011353 (-0.002251) 0.004379 / 0.011008 (-0.006629) 0.036700 / 0.038508 (-0.001808) 0.032873 / 0.023109 (0.009763) 0.345171 / 0.275898 (0.069273) 0.434115 / 0.323480 (0.110635) 0.006326 / 0.007986 (-0.001660) 0.004088 / 0.004328 (-0.000240) 0.007434 / 0.004250 (0.003184) 0.044137 / 0.037052 (0.007084) 0.363266 / 0.258489 (0.104777) 0.407857 / 0.293841 (0.114016) 0.045302 / 0.128546 (-0.083244) 0.014615 / 0.075646 (-0.061031) 0.302883 / 0.419271 (-0.116388) 0.063732 / 0.043533 (0.020200) 0.360722 / 0.255139 (0.105583) 0.368705 / 0.283200 (0.085505) 0.095597 / 0.141683 (-0.046085) 1.759146 / 1.452155 (0.306991) 1.744536 / 1.492716 (0.251820)

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) 0.213925 / 0.018006 (0.195919) 0.510206 / 0.000490 (0.509716) 0.008786 / 0.000200 (0.008586) 0.000099 / 0.000054 (0.000045)

Benchmark: benchmark_indices_mapping.json

metric select shard shuffle sort train_test_split
new / old (diff) 0.027662 / 0.037411 (-0.009749) 0.109216 / 0.014526 (0.094690) 0.138701 / 0.176557 (-0.037856) 0.192187 / 0.737135 (-0.544948) 0.123008 / 0.296338 (-0.173331)

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) 0.544335 / 0.215209 (0.329126) 5.478456 / 2.077655 (3.400801) 2.177737 / 1.504120 (0.673617) 1.928672 / 1.541195 (0.387477) 1.847770 / 1.468490 (0.379280) 0.686620 / 4.584777 (-3.898157) 5.126157 / 3.745712 (1.380445) 4.939491 / 5.269862 (-0.330371) 2.574788 / 4.565676 (-1.990888) 0.078776 / 0.424275 (-0.345499) 0.012859 / 0.007607 (0.005252) 0.701520 / 0.226044 (0.475476) 7.226141 / 2.268929 (4.957212) 2.963737 / 55.444624 (-52.480887) 2.171700 / 6.876477 (-4.704777) 2.315500 / 2.142072 (0.173427) 0.879775 / 4.805227 (-3.925453) 0.173196 / 6.500664 (-6.327468) 0.072016 / 0.075469 (-0.003453)

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) 1.707667 / 1.841788 (-0.134121) 15.346019 / 8.074308 (7.271711) 40.461269 / 10.191392 (30.269877) 1.014481 / 0.680424 (0.334057) 0.616486 / 0.534201 (0.082285) 0.427791 / 0.579283 (-0.151492) 0.570256 / 0.434364 (0.135892) 0.316468 / 0.540337 (-0.223870) 0.333142 / 1.386936 (-1.053794)
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) 0.006797 / 0.011353 (-0.004555) 0.004234 / 0.011008 (-0.006774) 0.033797 / 0.038508 (-0.004712) 0.032647 / 0.023109 (0.009538) 0.336087 / 0.275898 (0.060189) 0.395631 / 0.323480 (0.072151) 0.004600 / 0.007986 (-0.003386) 0.004034 / 0.004328 (-0.000294) 0.006055 / 0.004250 (0.001805) 0.044020 / 0.037052 (0.006967) 0.349544 / 0.258489 (0.091055) 0.408589 / 0.293841 (0.114748) 0.043918 / 0.128546 (-0.084629) 0.015484 / 0.075646 (-0.060162) 0.285926 / 0.419271 (-0.133345) 0.064931 / 0.043533 (0.021398) 0.346228 / 0.255139 (0.091089) 0.383755 / 0.283200 (0.100555) 0.101923 / 0.141683 (-0.039760) 1.691983 / 1.452155 (0.239828) 1.688745 / 1.492716 (0.196029)

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) 0.200426 / 0.018006 (0.182420) 0.505784 / 0.000490 (0.505294) 0.016435 / 0.000200 (0.016235) 0.000595 / 0.000054 (0.000541)

Benchmark: benchmark_indices_mapping.json

metric select shard shuffle sort train_test_split
new / old (diff) 0.028158 / 0.037411 (-0.009254) 0.115780 / 0.014526 (0.101254) 0.126937 / 0.176557 (-0.049620) 0.181754 / 0.737135 (-0.555381) 0.125468 / 0.296338 (-0.170871)

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) 0.583302 / 0.215209 (0.368093) 5.832269 / 2.077655 (3.754615) 2.513316 / 1.504120 (1.009196) 2.225504 / 1.541195 (0.684310) 2.147312 / 1.468490 (0.678822) 0.715967 / 4.584777 (-3.868810) 5.174251 / 3.745712 (1.428539) 2.808039 / 5.269862 (-2.461823) 1.810640 / 4.565676 (-2.755037) 0.084138 / 0.424275 (-0.340137) 0.013035 / 0.007607 (0.005428) 0.743485 / 0.226044 (0.517440) 7.388951 / 2.268929 (5.120022) 3.155949 / 55.444624 (-52.288675) 2.470623 / 6.876477 (-4.405854) 2.713799 / 2.142072 (0.571727) 0.872024 / 4.805227 (-3.933203) 0.180278 / 6.500664 (-6.320386) 0.069055 / 0.075469 (-0.006414)

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) 1.756761 / 1.841788 (-0.085026) 15.342849 / 8.074308 (7.268540) 39.998791 / 10.191392 (29.807399) 1.078096 / 0.680424 (0.397672) 0.658233 / 0.534201 (0.124032) 0.457176 / 0.579283 (-0.122107) 0.599035 / 0.434364 (0.164671) 0.336273 / 0.540337 (-0.204064) 0.336004 / 1.386936 (-1.050932)

CML watermark

Please sign in to comment.