Fix concurrent script loading with force_redownload

[lhoestq]

I added lock_importable_file in get_dataset_builder_class and extend_dataset_builder_for_streaming to fix the issue, and I also added a test

cc @clefourrier

[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]

just a variable name change for consistency

[mariosasko]

LGTM!

[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)	0.005074 / 0.011353 (-0.006279)	0.003505 / 0.011008 (-0.007503)	0.063683 / 0.038508 (0.025175)	0.029308 / 0.023109 (0.006199)	0.246648 / 0.275898 (-0.029250)	0.265546 / 0.323480 (-0.057933)	0.004108 / 0.007986 (-0.003878)	0.002683 / 0.004328 (-0.001646)	0.048634 / 0.004250 (0.044383)	0.043786 / 0.037052 (0.006733)	0.262197 / 0.258489 (0.003708)	0.291582 / 0.293841 (-0.002259)	0.027472 / 0.128546 (-0.101074)	0.010213 / 0.075646 (-0.065434)	0.206744 / 0.419271 (-0.212527)	0.036195 / 0.043533 (-0.007337)	0.249090 / 0.255139 (-0.006049)	0.280002 / 0.283200 (-0.003198)	0.018568 / 0.141683 (-0.123115)	1.124844 / 1.452155 (-0.327311)	1.159358 / 1.492716 (-0.333359)

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)	0.093186 / 0.018006 (0.075180)	0.302331 / 0.000490 (0.301842)	0.000217 / 0.000200 (0.000017)	0.000046 / 0.000054 (-0.000008)

Benchmark: benchmark_indices_mapping.json

metric	select	shard	shuffle	sort	train_test_split
new / old (diff)	0.018727 / 0.037411 (-0.018684)	0.061730 / 0.014526 (0.047204)	0.074330 / 0.176557 (-0.102226)	0.119769 / 0.737135 (-0.617366)	0.075611 / 0.296338 (-0.220727)

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)	0.285063 / 0.215209 (0.069854)	2.824809 / 2.077655 (0.747155)	1.481858 / 1.504120 (-0.022262)	1.350193 / 1.541195 (-0.191002)	1.358012 / 1.468490 (-0.110478)	0.557842 / 4.584777 (-4.026935)	2.380729 / 3.745712 (-1.364983)	2.798891 / 5.269862 (-2.470970)	1.719288 / 4.565676 (-2.846388)	0.061705 / 0.424275 (-0.362570)	0.005431 / 0.007607 (-0.002176)	0.343233 / 0.226044 (0.117189)	3.375223 / 2.268929 (1.106295)	1.838188 / 55.444624 (-53.606436)	1.570015 / 6.876477 (-5.306461)	1.573157 / 2.142072 (-0.568915)	0.650678 / 4.805227 (-4.154549)	0.116412 / 6.500664 (-6.384252)	0.041754 / 0.075469 (-0.033715)

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)	0.970431 / 1.841788 (-0.871357)	11.317128 / 8.074308 (3.242819)	9.691240 / 10.191392 (-0.500152)	0.142260 / 0.680424 (-0.538164)	0.014131 / 0.534201 (-0.520070)	0.289910 / 0.579283 (-0.289373)	0.265648 / 0.434364 (-0.168715)	0.323130 / 0.540337 (-0.217208)	0.447005 / 1.386936 (-0.939931)

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)	0.005322 / 0.011353 (-0.006031)	0.003755 / 0.011008 (-0.007253)	0.049646 / 0.038508 (0.011138)	0.029669 / 0.023109 (0.006560)	0.284151 / 0.275898 (0.008253)	0.298351 / 0.323480 (-0.025128)	0.004183 / 0.007986 (-0.003803)	0.002683 / 0.004328 (-0.001645)	0.048814 / 0.004250 (0.044563)	0.045017 / 0.037052 (0.007965)	0.287358 / 0.258489 (0.028869)	0.317394 / 0.293841 (0.023553)	0.030025 / 0.128546 (-0.098521)	0.010854 / 0.075646 (-0.064793)	0.058694 / 0.419271 (-0.360578)	0.052287 / 0.043533 (0.008754)	0.279038 / 0.255139 (0.023899)	0.295442 / 0.283200 (0.012242)	0.019413 / 0.141683 (-0.122270)	1.146106 / 1.452155 (-0.306048)	1.197777 / 1.492716 (-0.294939)

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)	0.092191 / 0.018006 (0.074184)	0.302672 / 0.000490 (0.302182)	0.000623 / 0.000200 (0.000423)	0.000048 / 0.000054 (-0.000006)

Benchmark: benchmark_indices_mapping.json

metric	select	shard	shuffle	sort	train_test_split
new / old (diff)	0.022067 / 0.037411 (-0.015345)	0.081760 / 0.014526 (0.067235)	0.087548 / 0.176557 (-0.089009)	0.126405 / 0.737135 (-0.610730)	0.089331 / 0.296338 (-0.207008)

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)	0.295821 / 0.215209 (0.080612)	2.897930 / 2.077655 (0.820276)	1.604500 / 1.504120 (0.100380)	1.471502 / 1.541195 (-0.069692)	1.497918 / 1.468490 (0.029428)	0.576179 / 4.584777 (-4.008598)	2.452103 / 3.745712 (-1.293609)	2.668043 / 5.269862 (-2.601818)	1.753544 / 4.565676 (-2.812133)	0.064410 / 0.424275 (-0.359865)	0.005027 / 0.007607 (-0.002580)	0.351509 / 0.226044 (0.125465)	3.479208 / 2.268929 (1.210280)	1.990356 / 55.444624 (-53.454269)	1.684920 / 6.876477 (-5.191556)	1.794251 / 2.142072 (-0.347821)	0.662692 / 4.805227 (-4.142535)	0.118589 / 6.500664 (-6.382076)	0.040813 / 0.075469 (-0.034656)

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)	1.002390 / 1.841788 (-0.839398)	12.004617 / 8.074308 (3.930309)	10.216005 / 10.191392 (0.024613)	0.154354 / 0.680424 (-0.526070)	0.015554 / 0.534201 (-0.518647)	0.288741 / 0.579283 (-0.290542)	0.276774 / 0.434364 (-0.157590)	0.327055 / 0.540337 (-0.213282)	0.435121 / 1.386936 (-0.951815)