fix(ci): remove unnecessary permissions

[McPatate]

What does this PR do?

Remove unnecessary permissions granted to the actions workflow.

Sorry for the mishap.

[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.

[albertvillanova]

Thanks.

In the previous PR, I was wondering if you were restricting the default permissions...

[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)	0.005520 / 0.011353 (-0.005833)	0.003989 / 0.011008 (-0.007019)	0.064786 / 0.038508 (0.026278)	0.031075 / 0.023109 (0.007966)	0.241619 / 0.275898 (-0.034279)	0.275341 / 0.323480 (-0.048139)	0.003139 / 0.007986 (-0.004847)	0.002820 / 0.004328 (-0.001508)	0.049766 / 0.004250 (0.045515)	0.045047 / 0.037052 (0.007995)	0.251906 / 0.258489 (-0.006583)	0.285889 / 0.293841 (-0.007952)	0.028297 / 0.128546 (-0.100249)	0.010683 / 0.075646 (-0.064963)	0.206467 / 0.419271 (-0.212805)	0.036267 / 0.043533 (-0.007266)	0.250720 / 0.255139 (-0.004419)	0.268565 / 0.283200 (-0.014635)	0.020394 / 0.141683 (-0.121289)	1.114283 / 1.452155 (-0.337872)	1.163884 / 1.492716 (-0.328833)

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)	0.112698 / 0.018006 (0.094692)	0.302740 / 0.000490 (0.302251)	0.000209 / 0.000200 (0.000009)	0.000044 / 0.000054 (-0.000011)

Benchmark: benchmark_indices_mapping.json

metric	select	shard	shuffle	sort	train_test_split
new / old (diff)	0.019337 / 0.037411 (-0.018075)	0.062854 / 0.014526 (0.048328)	0.077088 / 0.176557 (-0.099468)	0.120926 / 0.737135 (-0.616209)	0.075594 / 0.296338 (-0.220744)

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)	0.290787 / 0.215209 (0.075578)	2.867894 / 2.077655 (0.790239)	1.490043 / 1.504120 (-0.014076)	1.356383 / 1.541195 (-0.184812)	1.400229 / 1.468490 (-0.068261)	0.582076 / 4.584777 (-4.002701)	2.398270 / 3.745712 (-1.347442)	2.856459 / 5.269862 (-2.413403)	1.815545 / 4.565676 (-2.750131)	0.063259 / 0.424275 (-0.361016)	0.005056 / 0.007607 (-0.002551)	0.347699 / 0.226044 (0.121655)	3.466511 / 2.268929 (1.197582)	1.862096 / 55.444624 (-53.582528)	1.532324 / 6.876477 (-5.344152)	1.599411 / 2.142072 (-0.542661)	0.657350 / 4.805227 (-4.147878)	0.118981 / 6.500664 (-6.381683)	0.042224 / 0.075469 (-0.033245)

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)	0.965649 / 1.841788 (-0.876139)	11.896501 / 8.074308 (3.822193)	9.873923 / 10.191392 (-0.317469)	0.141165 / 0.680424 (-0.539258)	0.013885 / 0.534201 (-0.520316)	0.291464 / 0.579283 (-0.287819)	0.273153 / 0.434364 (-0.161211)	0.324395 / 0.540337 (-0.215942)	0.422040 / 1.386936 (-0.964897)

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)	0.005640 / 0.011353 (-0.005713)	0.004035 / 0.011008 (-0.006973)	0.050831 / 0.038508 (0.012323)	0.032841 / 0.023109 (0.009732)	0.272226 / 0.275898 (-0.003672)	0.297880 / 0.323480 (-0.025599)	0.004397 / 0.007986 (-0.003588)	0.002762 / 0.004328 (-0.001566)	0.049887 / 0.004250 (0.045637)	0.040372 / 0.037052 (0.003320)	0.286337 / 0.258489 (0.027848)	0.320015 / 0.293841 (0.026174)	0.029992 / 0.128546 (-0.098554)	0.010781 / 0.075646 (-0.064865)	0.059391 / 0.419271 (-0.359880)	0.034410 / 0.043533 (-0.009123)	0.273024 / 0.255139 (0.017885)	0.288953 / 0.283200 (0.005754)	0.018072 / 0.141683 (-0.123611)	1.125742 / 1.452155 (-0.326413)	1.175233 / 1.492716 (-0.317483)

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)	0.093470 / 0.018006 (0.075463)	0.313248 / 0.000490 (0.312758)	0.000324 / 0.000200 (0.000124)	0.000081 / 0.000054 (0.000026)

Benchmark: benchmark_indices_mapping.json

metric	select	shard	shuffle	sort	train_test_split
new / old (diff)	0.023529 / 0.037411 (-0.013882)	0.077305 / 0.014526 (0.062779)	0.088916 / 0.176557 (-0.087640)	0.128792 / 0.737135 (-0.608344)	0.090141 / 0.296338 (-0.206197)

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)	0.291110 / 0.215209 (0.075901)	2.848118 / 2.077655 (0.770464)	1.581664 / 1.504120 (0.077544)	1.446390 / 1.541195 (-0.094804)	1.452594 / 1.468490 (-0.015896)	0.571213 / 4.584777 (-4.013564)	0.976382 / 3.745712 (-2.769330)	2.756192 / 5.269862 (-2.513670)	1.770274 / 4.565676 (-2.795403)	0.064513 / 0.424275 (-0.359763)	0.005334 / 0.007607 (-0.002273)	0.347380 / 0.226044 (0.121335)	3.424800 / 2.268929 (1.155871)	1.942374 / 55.444624 (-53.502250)	1.636069 / 6.876477 (-5.240407)	1.795327 / 2.142072 (-0.346745)	0.658942 / 4.805227 (-4.146285)	0.119542 / 6.500664 (-6.381123)	0.041826 / 0.075469 (-0.033643)

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)	1.007230 / 1.841788 (-0.834558)	12.293084 / 8.074308 (4.218776)	10.618104 / 10.191392 (0.426712)	0.133691 / 0.680424 (-0.546733)	0.015725 / 0.534201 (-0.518476)	0.288860 / 0.579283 (-0.290423)	0.130546 / 0.434364 (-0.303818)	0.327279 / 0.540337 (-0.213059)	0.428768 / 1.386936 (-0.958168)