Fix metrics dead link

[qgallouedec]

No description provided.

[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.

[lhoestq]

good catch :p

[github-actions]

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)	0.005193 / 0.011353 (-0.006160)	0.003246 / 0.011008 (-0.007762)	0.063053 / 0.038508 (0.024545)	0.049636 / 0.023109 (0.026527)	0.240990 / 0.275898 (-0.034908)	0.263732 / 0.323480 (-0.059747)	0.004062 / 0.007986 (-0.003923)	0.002681 / 0.004328 (-0.001648)	0.048527 / 0.004250 (0.044277)	0.044159 / 0.037052 (0.007107)	0.248031 / 0.258489 (-0.010458)	0.275705 / 0.293841 (-0.018136)	0.028210 / 0.128546 (-0.100336)	0.010314 / 0.075646 (-0.065332)	0.209887 / 0.419271 (-0.209384)	0.035649 / 0.043533 (-0.007884)	0.251321 / 0.255139 (-0.003818)	0.266672 / 0.283200 (-0.016528)	0.017382 / 0.141683 (-0.124301)	1.088937 / 1.452155 (-0.363217)	1.143692 / 1.492716 (-0.349024)

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)	0.092558 / 0.018006 (0.074552)	0.301648 / 0.000490 (0.301159)	0.000208 / 0.000200 (0.000008)	0.000043 / 0.000054 (-0.000012)

Benchmark: benchmark_indices_mapping.json

metric	select	shard	shuffle	sort	train_test_split
new / old (diff)	0.018305 / 0.037411 (-0.019106)	0.059836 / 0.014526 (0.045310)	0.072926 / 0.176557 (-0.103631)	0.119826 / 0.737135 (-0.617309)	0.074357 / 0.296338 (-0.221982)

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)	0.279051 / 0.215209 (0.063842)	2.711402 / 2.077655 (0.633747)	1.431782 / 1.504120 (-0.072338)	1.316592 / 1.541195 (-0.224603)	1.352062 / 1.468490 (-0.116428)	0.562553 / 4.584777 (-4.022224)	2.387719 / 3.745712 (-1.357993)	2.693330 / 5.269862 (-2.576532)	1.682040 / 4.565676 (-2.883636)	0.061832 / 0.424275 (-0.362443)	0.005066 / 0.007607 (-0.002541)	0.332730 / 0.226044 (0.106685)	3.315503 / 2.268929 (1.046575)	1.787129 / 55.444624 (-53.657496)	1.508955 / 6.876477 (-5.367522)	1.512620 / 2.142072 (-0.629453)	0.637120 / 4.805227 (-4.168107)	0.116005 / 6.500664 (-6.384660)	0.041973 / 0.075469 (-0.033496)

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)	0.936996 / 1.841788 (-0.904792)	11.485975 / 8.074308 (3.411667)	10.604481 / 10.191392 (0.413089)	0.130803 / 0.680424 (-0.549621)	0.014561 / 0.534201 (-0.519640)	0.285905 / 0.579283 (-0.293378)	0.271573 / 0.434364 (-0.162791)	0.329206 / 0.540337 (-0.211132)	0.411977 / 1.386936 (-0.974959)

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)	0.005333 / 0.011353 (-0.006020)	0.003519 / 0.011008 (-0.007489)	0.050880 / 0.038508 (0.012372)	0.053681 / 0.023109 (0.030571)	0.269359 / 0.275898 (-0.006539)	0.291498 / 0.323480 (-0.031982)	0.004006 / 0.007986 (-0.003979)	0.002676 / 0.004328 (-0.001653)	0.049652 / 0.004250 (0.045401)	0.040588 / 0.037052 (0.003536)	0.271701 / 0.258489 (0.013212)	0.308384 / 0.293841 (0.014543)	0.028713 / 0.128546 (-0.099833)	0.010423 / 0.075646 (-0.065223)	0.058099 / 0.419271 (-0.361172)	0.032372 / 0.043533 (-0.011161)	0.269395 / 0.255139 (0.014256)	0.292252 / 0.283200 (0.009052)	0.020038 / 0.141683 (-0.121645)	1.124761 / 1.452155 (-0.327393)	1.177609 / 1.492716 (-0.315107)

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)	0.092187 / 0.018006 (0.074181)	0.301936 / 0.000490 (0.301446)	0.000230 / 0.000200 (0.000030)	0.000052 / 0.000054 (-0.000002)

Benchmark: benchmark_indices_mapping.json

metric	select	shard	shuffle	sort	train_test_split
new / old (diff)	0.022932 / 0.037411 (-0.014480)	0.076552 / 0.014526 (0.062027)	0.088729 / 0.176557 (-0.087827)	0.127198 / 0.737135 (-0.609937)	0.091902 / 0.296338 (-0.204436)

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)	0.299964 / 0.215209 (0.084755)	2.929352 / 2.077655 (0.851697)	1.598715 / 1.504120 (0.094595)	1.462438 / 1.541195 (-0.078756)	1.474308 / 1.468490 (0.005818)	0.567120 / 4.584777 (-4.017657)	2.481757 / 3.745712 (-1.263955)	2.795375 / 5.269862 (-2.474487)	1.740346 / 4.565676 (-2.825331)	0.064048 / 0.424275 (-0.360227)	0.004995 / 0.007607 (-0.002612)	0.349084 / 0.226044 (0.123040)	3.417679 / 2.268929 (1.148750)	1.910615 / 55.444624 (-53.534009)	1.694120 / 6.876477 (-5.182356)	1.658654 / 2.142072 (-0.483419)	0.638158 / 4.805227 (-4.167069)	0.115509 / 6.500664 (-6.385156)	0.040650 / 0.075469 (-0.034819)

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)	0.988081 / 1.841788 (-0.853707)	12.210089 / 8.074308 (4.135781)	11.090203 / 10.191392 (0.898811)	0.131861 / 0.680424 (-0.548563)	0.015461 / 0.534201 (-0.518740)	0.287737 / 0.579283 (-0.291546)	0.284170 / 0.434364 (-0.150194)	0.324949 / 0.540337 (-0.215388)	0.414912 / 1.386936 (-0.972024)