Fix unused DatasetInfosDict code in push_to_hub

[lhoestq]

No description provided.

[HuggingFaceDocBuilderDev]

The documentation is not available anymore as the PR was closed or merged.

[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)	0.008634 / 0.011353 (-0.002719)	0.005147 / 0.011008 (-0.005861)	0.102865 / 0.038508 (0.064357)	0.080245 / 0.023109 (0.057136)	0.401288 / 0.275898 (0.125390)	0.419708 / 0.323480 (0.096228)	0.006342 / 0.007986 (-0.001644)	0.003998 / 0.004328 (-0.000330)	0.078880 / 0.004250 (0.074630)	0.068199 / 0.037052 (0.031147)	0.389573 / 0.258489 (0.131084)	0.417292 / 0.293841 (0.123451)	0.048856 / 0.128546 (-0.079691)	0.014165 / 0.075646 (-0.061481)	0.348063 / 0.419271 (-0.071209)	0.067547 / 0.043533 (0.024014)	0.402251 / 0.255139 (0.147112)	0.419478 / 0.283200 (0.136278)	0.034846 / 0.141683 (-0.106837)	1.773493 / 1.452155 (0.321338)	1.930546 / 1.492716 (0.437830)

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)	0.211835 / 0.018006 (0.193829)	0.545311 / 0.000490 (0.544821)	0.006766 / 0.000200 (0.006566)	0.000104 / 0.000054 (0.000050)

Benchmark: benchmark_indices_mapping.json

metric	select	shard	shuffle	sort	train_test_split
new / old (diff)	0.035406 / 0.037411 (-0.002006)	0.100769 / 0.014526 (0.086243)	0.108667 / 0.176557 (-0.067890)	0.193099 / 0.737135 (-0.544036)	0.113539 / 0.296338 (-0.182799)

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)	0.586935 / 0.215209 (0.371726)	5.895245 / 2.077655 (3.817591)	2.528375 / 1.504120 (1.024255)	2.228617 / 1.541195 (0.687423)	2.295799 / 1.468490 (0.827309)	0.859272 / 4.584777 (-3.725505)	5.033434 / 3.745712 (1.287722)	7.546587 / 5.269862 (2.276726)	4.457137 / 4.565676 (-0.108539)	0.099626 / 0.424275 (-0.324649)	0.009296 / 0.007607 (0.001689)	0.713498 / 0.226044 (0.487454)	7.409385 / 2.268929 (5.140456)	3.361418 / 55.444624 (-52.083206)	2.681111 / 6.876477 (-4.195366)	2.849598 / 2.142072 (0.707526)	1.114863 / 4.805227 (-3.690364)	0.215494 / 6.500664 (-6.285170)	0.075807 / 0.075469 (0.000338)

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)	1.606458 / 1.841788 (-0.235330)	23.751096 / 8.074308 (15.676788)	21.279110 / 10.191392 (11.087718)	0.220785 / 0.680424 (-0.459639)	0.032688 / 0.534201 (-0.501513)	0.530948 / 0.579283 (-0.048335)	0.630056 / 0.434364 (0.195693)	0.572743 / 0.540337 (0.032405)	0.771853 / 1.386936 (-0.615083)

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)	0.008693 / 0.011353 (-0.002660)	0.004750 / 0.011008 (-0.006259)	0.079764 / 0.038508 (0.041256)	0.082096 / 0.023109 (0.058987)	0.467198 / 0.275898 (0.191300)	0.532361 / 0.323480 (0.208881)	0.005836 / 0.007986 (-0.002149)	0.004333 / 0.004328 (0.000005)	0.080444 / 0.004250 (0.076194)	0.065883 / 0.037052 (0.028831)	0.464871 / 0.258489 (0.206382)	0.575026 / 0.293841 (0.281185)	0.057807 / 0.128546 (-0.070739)	0.017462 / 0.075646 (-0.058185)	0.093667 / 0.419271 (-0.325605)	0.071466 / 0.043533 (0.027933)	0.495846 / 0.255139 (0.240707)	0.526100 / 0.283200 (0.242900)	0.034852 / 0.141683 (-0.106831)	1.884152 / 1.452155 (0.431998)	1.922681 / 1.492716 (0.429965)

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)	0.250969 / 0.018006 (0.232963)	0.504979 / 0.000490 (0.504489)	0.000466 / 0.000200 (0.000266)	0.000083 / 0.000054 (0.000028)

Benchmark: benchmark_indices_mapping.json

metric	select	shard	shuffle	sort	train_test_split
new / old (diff)	0.032411 / 0.037411 (-0.005000)	0.093184 / 0.014526 (0.078658)	0.110798 / 0.176557 (-0.065759)	0.165741 / 0.737135 (-0.571394)	0.111022 / 0.296338 (-0.185317)

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)	0.661284 / 0.215209 (0.446075)	6.622388 / 2.077655 (4.544733)	3.095705 / 1.504120 (1.591585)	2.745698 / 1.541195 (1.204503)	2.694103 / 1.468490 (1.225612)	0.862154 / 4.584777 (-3.722623)	5.109985 / 3.745712 (1.364273)	5.040362 / 5.269862 (-0.229499)	3.072837 / 4.565676 (-1.492840)	0.110421 / 0.424275 (-0.313854)	0.008476 / 0.007607 (0.000869)	0.910020 / 0.226044 (0.683975)	8.123626 / 2.268929 (5.854698)	3.813811 / 55.444624 (-51.630813)	3.017244 / 6.876477 (-3.859232)	3.061222 / 2.142072 (0.919150)	1.073548 / 4.805227 (-3.731680)	0.216327 / 6.500664 (-6.284338)	0.072977 / 0.075469 (-0.002492)

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)	1.722482 / 1.841788 (-0.119305)	23.706716 / 8.074308 (15.632407)	23.192134 / 10.191392 (13.000742)	0.276733 / 0.680424 (-0.403691)	0.033538 / 0.534201 (-0.500663)	0.602083 / 0.579283 (0.022799)	0.578718 / 0.434364 (0.144354)	0.558311 / 0.540337 (0.017974)	0.740341 / 1.386936 (-0.646595)

[lhoestq]

it's not used so I removed this line

[lhoestq]

this code needs to be here, because in the previous location it would be run only if there is no README.md and if there is a json file. But it needs to run if there is a json file, no matter if there is a README.md or not

[polinaeterna]

ah lol true good catch!

[polinaeterna]

thank you ❤️

[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)	0.006862 / 0.011353 (-0.004491)	0.004223 / 0.011008 (-0.006786)	0.085931 / 0.038508 (0.047423)	0.081437 / 0.023109 (0.058328)	0.349542 / 0.275898 (0.073644)	0.379881 / 0.323480 (0.056401)	0.005651 / 0.007986 (-0.002334)	0.003662 / 0.004328 (-0.000666)	0.065251 / 0.004250 (0.061001)	0.061599 / 0.037052 (0.024547)	0.359681 / 0.258489 (0.101192)	0.392502 / 0.293841 (0.098661)	0.031300 / 0.128546 (-0.097246)	0.008591 / 0.075646 (-0.067055)	0.288577 / 0.419271 (-0.130694)	0.062920 / 0.043533 (0.019388)	0.348989 / 0.255139 (0.093850)	0.362769 / 0.283200 (0.079569)	0.030087 / 0.141683 (-0.111596)	1.480748 / 1.452155 (0.028594)	1.580413 / 1.492716 (0.087697)

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)	0.205804 / 0.018006 (0.187798)	0.455386 / 0.000490 (0.454897)	0.003134 / 0.000200 (0.002934)	0.000077 / 0.000054 (0.000023)

Benchmark: benchmark_indices_mapping.json

metric	select	shard	shuffle	sort	train_test_split
new / old (diff)	0.030252 / 0.037411 (-0.007159)	0.087566 / 0.014526 (0.073041)	0.098209 / 0.176557 (-0.078347)	0.155816 / 0.737135 (-0.581319)	0.098938 / 0.296338 (-0.197401)

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)	0.386688 / 0.215209 (0.171479)	3.852777 / 2.077655 (1.775123)	1.938688 / 1.504120 (0.434568)	1.779234 / 1.541195 (0.238039)	1.864262 / 1.468490 (0.395772)	0.482472 / 4.584777 (-4.102305)	3.658060 / 3.745712 (-0.087652)	5.206489 / 5.269862 (-0.063373)	3.262498 / 4.565676 (-1.303179)	0.057523 / 0.424275 (-0.366752)	0.007365 / 0.007607 (-0.000242)	0.466886 / 0.226044 (0.240841)	4.671026 / 2.268929 (2.402097)	2.380357 / 55.444624 (-53.064268)	2.096590 / 6.876477 (-4.779887)	2.274415 / 2.142072 (0.132342)	0.579705 / 4.805227 (-4.225522)	0.134522 / 6.500664 (-6.366142)	0.062232 / 0.075469 (-0.013237)

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)	1.245965 / 1.841788 (-0.595823)	20.115180 / 8.074308 (12.040872)	14.602983 / 10.191392 (4.411591)	0.146890 / 0.680424 (-0.533533)	0.018424 / 0.534201 (-0.515777)	0.393941 / 0.579283 (-0.185342)	0.413785 / 0.434364 (-0.020579)	0.453344 / 0.540337 (-0.086993)	0.655446 / 1.386936 (-0.731490)

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)	0.006807 / 0.011353 (-0.004546)	0.004083 / 0.011008 (-0.006925)	0.065389 / 0.038508 (0.026881)	0.081056 / 0.023109 (0.057947)	0.362823 / 0.275898 (0.086925)	0.401928 / 0.323480 (0.078448)	0.005452 / 0.007986 (-0.002533)	0.003413 / 0.004328 (-0.000915)	0.065238 / 0.004250 (0.060987)	0.057264 / 0.037052 (0.020211)	0.375713 / 0.258489 (0.117224)	0.407858 / 0.293841 (0.114017)	0.031580 / 0.128546 (-0.096966)	0.008643 / 0.075646 (-0.067003)	0.071693 / 0.419271 (-0.347578)	0.049392 / 0.043533 (0.005859)	0.370194 / 0.255139 (0.115055)	0.384647 / 0.283200 (0.101447)	0.024805 / 0.141683 (-0.116877)	1.509511 / 1.452155 (0.057356)	1.560193 / 1.492716 (0.067477)

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)	0.234442 / 0.018006 (0.216436)	0.458818 / 0.000490 (0.458329)	0.000407 / 0.000200 (0.000207)	0.000060 / 0.000054 (0.000006)

Benchmark: benchmark_indices_mapping.json

metric	select	shard	shuffle	sort	train_test_split
new / old (diff)	0.031661 / 0.037411 (-0.005750)	0.093143 / 0.014526 (0.078618)	0.102205 / 0.176557 (-0.074352)	0.155850 / 0.737135 (-0.581286)	0.104345 / 0.296338 (-0.191994)

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)	0.419641 / 0.215209 (0.204432)	4.200808 / 2.077655 (2.123153)	2.218227 / 1.504120 (0.714107)	2.052604 / 1.541195 (0.511409)	2.150611 / 1.468490 (0.682121)	0.482665 / 4.584777 (-4.102112)	3.606541 / 3.745712 (-0.139172)	3.310637 / 5.269862 (-1.959224)	2.070200 / 4.565676 (-2.495476)	0.056586 / 0.424275 (-0.367689)	0.007826 / 0.007607 (0.000218)	0.491037 / 0.226044 (0.264992)	4.901538 / 2.268929 (2.632610)	2.676402 / 55.444624 (-52.768223)	2.363935 / 6.876477 (-4.512542)	2.587813 / 2.142072 (0.445741)	0.579302 / 4.805227 (-4.225926)	0.132792 / 6.500664 (-6.367873)	0.061865 / 0.075469 (-0.013604)

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)	1.354315 / 1.841788 (-0.487473)	20.874516 / 8.074308 (12.800208)	14.863559 / 10.191392 (4.672167)	0.183635 / 0.680424 (-0.496789)	0.018636 / 0.534201 (-0.515565)	0.395317 / 0.579283 (-0.183966)	0.410598 / 0.434364 (-0.023766)	0.476485 / 0.540337 (-0.063853)	0.643246 / 1.386936 (-0.743690)