Fix wrong type hints in data_files

[albertvillanova]

Fix wrong type hints in data_files introduced in:

• Lazy data files resolution and offline cache reload #6493

[HuggingFaceDocBuilderDev]

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[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)	0.005135 / 0.011353 (-0.006218)	0.003757 / 0.011008 (-0.007251)	0.063122 / 0.038508 (0.024614)	0.029837 / 0.023109 (0.006727)	0.246120 / 0.275898 (-0.029778)	0.268529 / 0.323480 (-0.054951)	0.004136 / 0.007986 (-0.003849)	0.002650 / 0.004328 (-0.001678)	0.048749 / 0.004250 (0.044499)	0.045279 / 0.037052 (0.008226)	0.257970 / 0.258489 (-0.000519)	0.285993 / 0.293841 (-0.007848)	0.027612 / 0.128546 (-0.100935)	0.010175 / 0.075646 (-0.065471)	0.207373 / 0.419271 (-0.211899)	0.037672 / 0.043533 (-0.005861)	0.249603 / 0.255139 (-0.005536)	0.271081 / 0.283200 (-0.012119)	0.018174 / 0.141683 (-0.123509)	1.116703 / 1.452155 (-0.335452)	1.169261 / 1.492716 (-0.323455)

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)	0.095161 / 0.018006 (0.077155)	0.301112 / 0.000490 (0.300623)	0.000221 / 0.000200 (0.000021)	0.000042 / 0.000054 (-0.000012)

Benchmark: benchmark_indices_mapping.json

metric	select	shard	shuffle	sort	train_test_split
new / old (diff)	0.023218 / 0.037411 (-0.014193)	0.063125 / 0.014526 (0.048599)	0.075857 / 0.176557 (-0.100699)	0.137922 / 0.737135 (-0.599213)	0.076989 / 0.296338 (-0.219349)

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)	0.279272 / 0.215209 (0.064063)	2.776463 / 2.077655 (0.698809)	1.472220 / 1.504120 (-0.031900)	1.347105 / 1.541195 (-0.194090)	1.361014 / 1.468490 (-0.107476)	0.589233 / 4.584777 (-3.995544)	2.395212 / 3.745712 (-1.350500)	2.794855 / 5.269862 (-2.475007)	1.698350 / 4.565676 (-2.867327)	0.063328 / 0.424275 (-0.360947)	0.005020 / 0.007607 (-0.002588)	0.335872 / 0.226044 (0.109828)	3.293486 / 2.268929 (1.024558)	1.837270 / 55.444624 (-53.607354)	1.535694 / 6.876477 (-5.340782)	1.559696 / 2.142072 (-0.582376)	0.639302 / 4.805227 (-4.165925)	0.116554 / 6.500664 (-6.384110)	0.042305 / 0.075469 (-0.033164)

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)	0.971562 / 1.841788 (-0.870226)	11.710500 / 8.074308 (3.636192)	9.505935 / 10.191392 (-0.685457)	0.139161 / 0.680424 (-0.541263)	0.014351 / 0.534201 (-0.519850)	0.285790 / 0.579283 (-0.293493)	0.265718 / 0.434364 (-0.168646)	0.323558 / 0.540337 (-0.216780)	0.412635 / 1.386936 (-0.974301)

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)	0.005987 / 0.011353 (-0.005366)	0.003787 / 0.011008 (-0.007221)	0.049839 / 0.038508 (0.011331)	0.032817 / 0.023109 (0.009708)	0.268304 / 0.275898 (-0.007594)	0.303409 / 0.323480 (-0.020071)	0.004924 / 0.007986 (-0.003061)	0.002740 / 0.004328 (-0.001589)	0.048906 / 0.004250 (0.044655)	0.044266 / 0.037052 (0.007213)	0.290506 / 0.258489 (0.032017)	0.314124 / 0.293841 (0.020283)	0.030242 / 0.128546 (-0.098304)	0.010555 / 0.075646 (-0.065091)	0.058849 / 0.419271 (-0.360423)	0.033540 / 0.043533 (-0.009993)	0.267833 / 0.255139 (0.012694)	0.291056 / 0.283200 (0.007857)	0.018611 / 0.141683 (-0.123072)	1.137620 / 1.452155 (-0.314534)	1.199554 / 1.492716 (-0.293162)

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)	0.096716 / 0.018006 (0.078709)	0.302033 / 0.000490 (0.301543)	0.000217 / 0.000200 (0.000017)	0.000044 / 0.000054 (-0.000010)

Benchmark: benchmark_indices_mapping.json

metric	select	shard	shuffle	sort	train_test_split
new / old (diff)	0.023208 / 0.037411 (-0.014203)	0.076231 / 0.014526 (0.061705)	0.088672 / 0.176557 (-0.087884)	0.129033 / 0.737135 (-0.608103)	0.090709 / 0.296338 (-0.205630)

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)	0.297033 / 0.215209 (0.081824)	2.951181 / 2.077655 (0.873526)	1.567690 / 1.504120 (0.063570)	1.436809 / 1.541195 (-0.104385)	1.469696 / 1.468490 (0.001206)	0.567963 / 4.584777 (-4.016813)	0.954168 / 3.745712 (-2.791544)	2.700473 / 5.269862 (-2.569389)	1.742144 / 4.565676 (-2.823532)	0.065027 / 0.424275 (-0.359248)	0.005319 / 0.007607 (-0.002288)	0.346459 / 0.226044 (0.120415)	3.446117 / 2.268929 (1.177189)	1.953142 / 55.444624 (-53.491483)	1.639131 / 6.876477 (-5.237346)	1.830664 / 2.142072 (-0.311409)	0.657807 / 4.805227 (-4.147420)	0.117987 / 6.500664 (-6.382678)	0.040726 / 0.075469 (-0.034744)

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)	0.992666 / 1.841788 (-0.849122)	12.305377 / 8.074308 (4.231069)	10.274829 / 10.191392 (0.083437)	0.141731 / 0.680424 (-0.538692)	0.015100 / 0.534201 (-0.519101)	0.282298 / 0.579283 (-0.296985)	0.124301 / 0.434364 (-0.310063)	0.320914 / 0.540337 (-0.219424)	0.445855 / 1.386936 (-0.941081)