The full dataset viewer is not available (click to read why). Only showing a preview of the rows.
The dataset generation failed
Error code:   DatasetGenerationError
Exception:    TypeError
Message:      Couldn't cast array of type timestamp[s] to null
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 2011, in _prepare_split_single
                  writer.write_table(table)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 585, in write_table
                  pa_table = table_cast(pa_table, self._schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2302, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2261, in cast_table_to_schema
                  arrays = [cast_array_to_feature(table[name], feature) for name, feature in features.items()]
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2261, in <listcomp>
                  arrays = [cast_array_to_feature(table[name], feature) for name, feature in features.items()]
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1802, in wrapper
                  return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1802, in <listcomp>
                  return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2020, in cast_array_to_feature
                  arrays = [_c(array.field(name), subfeature) for name, subfeature in feature.items()]
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2020, in <listcomp>
                  arrays = [_c(array.field(name), subfeature) for name, subfeature in feature.items()]
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1804, in wrapper
                  return func(array, *args, **kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2116, in cast_array_to_feature
                  return array_cast(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1804, in wrapper
                  return func(array, *args, **kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1962, in array_cast
                  raise TypeError(f"Couldn't cast array of type {_short_str(array.type)} to {_short_str(pa_type)}")
              TypeError: Couldn't cast array of type timestamp[s] to null
              
              The above exception was the direct cause of the following exception:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1529, in compute_config_parquet_and_info_response
                  parquet_operations = convert_to_parquet(builder)
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1154, in convert_to_parquet
                  builder.download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1027, in download_and_prepare
                  self._download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1122, in _download_and_prepare
                  self._prepare_split(split_generator, **prepare_split_kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1882, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 2038, in _prepare_split_single
                  raise DatasetGenerationError("An error occurred while generating the dataset") from e
              datasets.exceptions.DatasetGenerationError: An error occurred while generating the dataset

Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

url
string
repository_url
string
labels_url
string
comments_url
string
events_url
string
html_url
string
id
int64
node_id
string
number
int64
title
string
user
dict
labels
list
state
string
locked
bool
assignee
dict
assignees
list
milestone
null
comments
sequence
created_at
int64
updated_at
int64
closed_at
int64
author_association
string
active_lock_reason
null
draft
float64
pull_request
dict
body
string
reactions
dict
timeline_url
string
performed_via_github_app
null
state_reason
string
is_pull_request
bool
https://api.github.com/repos/huggingface/datasets/issues/6999
https://api.github.com/repos/huggingface/datasets
https://api.github.com/repos/huggingface/datasets/issues/6999/labels{/name}
https://api.github.com/repos/huggingface/datasets/issues/6999/comments
https://api.github.com/repos/huggingface/datasets/issues/6999/events
https://github.com/huggingface/datasets/pull/6999
2,372,124,589
PR_kwDODunzps5zd-ak
6,999
Remove tasks
{ "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "gravatar_id": "", "html_url": "https://github.com/albertvillanova", "id": 8515462, "login": "albertvillanova", "node_id": "MDQ6VXNlcjg1MTU0NjI=", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "repos_url": "https://api.github.com/users/albertvillanova/repos", "site_admin": false, "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "type": "User", "url": "https://api.github.com/users/albertvillanova" }
[]
open
false
null
[]
null
[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6999). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update." ]
1,719,306,376,000
1,719,306,376,000
null
MEMBER
null
0
{ "diff_url": "https://github.com/huggingface/datasets/pull/6999.diff", "html_url": "https://github.com/huggingface/datasets/pull/6999", "merged_at": null, "patch_url": "https://github.com/huggingface/datasets/pull/6999.patch", "url": "https://api.github.com/repos/huggingface/datasets/pulls/6999" }
Remove tasks, as part of the 3.0 release.
{ "+1": 0, "-1": 0, "confused": 0, "eyes": 0, "heart": 0, "hooray": 0, "laugh": 0, "rocket": 0, "total_count": 0, "url": "https://api.github.com/repos/huggingface/datasets/issues/6999/reactions" }
https://api.github.com/repos/huggingface/datasets/issues/6999/timeline
null
null
true
https://api.github.com/repos/huggingface/datasets/issues/6998
https://api.github.com/repos/huggingface/datasets
https://api.github.com/repos/huggingface/datasets/issues/6998/labels{/name}
https://api.github.com/repos/huggingface/datasets/issues/6998/comments
https://api.github.com/repos/huggingface/datasets/issues/6998/events
https://github.com/huggingface/datasets/pull/6998
2,371,973,926
PR_kwDODunzps5zddYG
6,998
Fix tests using hf-internal-testing/librispeech_asr_dummy
{ "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "gravatar_id": "", "html_url": "https://github.com/albertvillanova", "id": 8515462, "login": "albertvillanova", "node_id": "MDQ6VXNlcjg1MTU0NjI=", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "repos_url": "https://api.github.com/users/albertvillanova/repos", "site_admin": false, "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "type": "User", "url": "https://api.github.com/users/albertvillanova" }
[]
closed
false
null
[]
null
[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6998). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| 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 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.005396 / 0.011353 (-0.005957) | 0.003974 / 0.011008 (-0.007034) | 0.063490 / 0.038508 (0.024982) | 0.030299 / 0.023109 (0.007189) | 0.244489 / 0.275898 (-0.031409) | 0.274116 / 0.323480 (-0.049364) | 0.003187 / 0.007986 (-0.004798) | 0.003433 / 0.004328 (-0.000896) | 0.049313 / 0.004250 (0.045062) | 0.043677 / 0.037052 (0.006624) | 0.260198 / 0.258489 (0.001709) | 0.283558 / 0.293841 (-0.010283) | 0.029728 / 0.128546 (-0.098819) | 0.011950 / 0.075646 (-0.063696) | 0.204371 / 0.419271 (-0.214901) | 0.035712 / 0.043533 (-0.007821) | 0.252715 / 0.255139 (-0.002424) | 0.268906 / 0.283200 (-0.014293) | 0.021153 / 0.141683 (-0.120529) | 1.125599 / 1.452155 (-0.326556) | 1.163122 / 1.492716 (-0.329594) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.095089 / 0.018006 (0.077083) | 0.298576 / 0.000490 (0.298086) | 0.000214 / 0.000200 (0.000014) | 0.000051 / 0.000054 (-0.000004) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.018567 / 0.037411 (-0.018844) | 0.062337 / 0.014526 (0.047811) | 0.074231 / 0.176557 (-0.102326) | 0.120960 / 0.737135 (-0.616175) | 0.076124 / 0.296338 (-0.220215) |\n\n### Benchmark: benchmark_iterating.json\n\n| 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 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.286936 / 0.215209 (0.071727) | 2.816656 / 2.077655 (0.739001) | 1.486772 / 1.504120 (-0.017348) | 1.373289 / 1.541195 (-0.167905) | 1.392739 / 1.468490 (-0.075752) | 0.708091 / 4.584777 (-3.876686) | 2.410034 / 3.745712 (-1.335678) | 2.912701 / 5.269862 (-2.357161) | 1.850924 / 4.565676 (-2.714752) | 0.078896 / 0.424275 (-0.345380) | 0.005116 / 0.007607 (-0.002491) | 0.332275 / 0.226044 (0.106231) | 3.306562 / 2.268929 (1.037633) | 1.853051 / 55.444624 (-53.591573) | 1.556210 / 6.876477 (-5.320267) | 1.558892 / 2.142072 (-0.583181) | 0.789917 / 4.805227 (-4.015310) | 0.133683 / 6.500664 (-6.366981) | 0.042566 / 0.075469 (-0.032904) |\n\n### Benchmark: benchmark_map_filter.json\n\n| 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 |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.957050 / 1.841788 (-0.884738) | 11.401462 / 8.074308 (3.327154) | 9.782988 / 10.191392 (-0.408404) | 0.142127 / 0.680424 (-0.538296) | 0.014730 / 0.534201 (-0.519471) | 0.302647 / 0.579283 (-0.276636) | 0.264654 / 0.434364 (-0.169710) | 0.341340 / 0.540337 (-0.198998) | 0.425808 / 1.386936 (-0.961128) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| 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 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.005679 / 0.011353 (-0.005674) | 0.003513 / 0.011008 (-0.007495) | 0.050135 / 0.038508 (0.011627) | 0.031614 / 0.023109 (0.008505) | 0.260064 / 0.275898 (-0.015834) | 0.285816 / 0.323480 (-0.037664) | 0.004428 / 0.007986 (-0.003558) | 0.002816 / 0.004328 (-0.001512) | 0.048441 / 0.004250 (0.044191) | 0.039622 / 0.037052 (0.002570) | 0.274940 / 0.258489 (0.016451) | 0.311837 / 0.293841 (0.017996) | 0.031439 / 0.128546 (-0.097107) | 0.012056 / 0.075646 (-0.063590) | 0.060109 / 0.419271 (-0.359163) | 0.033123 / 0.043533 (-0.010409) | 0.261563 / 0.255139 (0.006424) | 0.282640 / 0.283200 (-0.000560) | 0.017168 / 0.141683 (-0.124515) | 1.127859 / 1.452155 (-0.324295) | 1.182414 / 1.492716 (-0.310303) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.095517 / 0.018006 (0.077510) | 0.300578 / 0.000490 (0.300088) | 0.000212 / 0.000200 (0.000012) | 0.000044 / 0.000054 (-0.000010) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.022192 / 0.037411 (-0.015220) | 0.076617 / 0.014526 (0.062091) | 0.087405 / 0.176557 (-0.089151) | 0.127011 / 0.737135 (-0.610124) | 0.088706 / 0.296338 (-0.207632) |\n\n### Benchmark: benchmark_iterating.json\n\n| 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 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.294260 / 0.215209 (0.079051) | 2.872879 / 2.077655 (0.795224) | 1.531374 / 1.504120 (0.027254) | 1.399232 / 1.541195 (-0.141962) | 1.400708 / 1.468490 (-0.067782) | 0.714003 / 4.584777 (-3.870773) | 0.943144 / 3.745712 (-2.802568) | 2.833396 / 5.269862 (-2.436466) | 1.890570 / 4.565676 (-2.675106) | 0.077664 / 0.424275 (-0.346611) | 0.005651 / 0.007607 (-0.001956) | 0.349476 / 0.226044 (0.123431) | 3.405768 / 2.268929 (1.136840) | 1.869739 / 55.444624 (-53.574885) | 1.575293 / 6.876477 (-5.301184) | 1.692981 / 2.142072 (-0.449092) | 0.795363 / 4.805227 (-4.009865) | 0.131532 / 6.500664 (-6.369132) | 0.041183 / 0.075469 (-0.034286) |\n\n### Benchmark: benchmark_map_filter.json\n\n| 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 |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.000821 / 1.841788 (-0.840967) | 11.987795 / 8.074308 (3.913487) | 10.147652 / 10.191392 (-0.043740) | 0.141314 / 0.680424 (-0.539110) | 0.015506 / 0.534201 (-0.518695) | 0.305090 / 0.579283 (-0.274193) | 0.123403 / 0.434364 (-0.310960) | 0.346507 / 0.540337 (-0.193831) | 0.471318 / 1.386936 (-0.915618) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#186b560eb2393c7d1913f4b3e76e9e04a081e09b \"CML watermark\")\n" ]
1,719,302,384,000
1,719,303,758,000
1,719,303,222,000
MEMBER
null
0
{ "diff_url": "https://github.com/huggingface/datasets/pull/6998.diff", "html_url": "https://github.com/huggingface/datasets/pull/6998", "merged_at": "2024-06-25T08:13:42", "patch_url": "https://github.com/huggingface/datasets/pull/6998.patch", "url": "https://api.github.com/repos/huggingface/datasets/pulls/6998" }
Fix tests using hf-internal-testing/librispeech_asr_dummy once that dataset has been converted to Parquet. Fix #6997.
{ "+1": 0, "-1": 0, "confused": 0, "eyes": 0, "heart": 0, "hooray": 0, "laugh": 0, "rocket": 0, "total_count": 0, "url": "https://api.github.com/repos/huggingface/datasets/issues/6998/reactions" }
https://api.github.com/repos/huggingface/datasets/issues/6998/timeline
null
null
true
https://api.github.com/repos/huggingface/datasets/issues/6997
https://api.github.com/repos/huggingface/datasets
https://api.github.com/repos/huggingface/datasets/issues/6997/labels{/name}
https://api.github.com/repos/huggingface/datasets/issues/6997/comments
https://api.github.com/repos/huggingface/datasets/issues/6997/events
https://github.com/huggingface/datasets/issues/6997
2,371,966,127
I_kwDODunzps6NYVSv
6,997
CI is broken for tests using hf-internal-testing/librispeech_asr_dummy
{ "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "gravatar_id": "", "html_url": "https://github.com/albertvillanova", "id": 8515462, "login": "albertvillanova", "node_id": "MDQ6VXNlcjg1MTU0NjI=", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "repos_url": "https://api.github.com/users/albertvillanova/repos", "site_admin": false, "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "type": "User", "url": "https://api.github.com/users/albertvillanova" }
[ { "color": "d4c5f9", "default": false, "description": "Maintenance tasks", "id": 4296013012, "name": "maintenance", "node_id": "LA_kwDODunzps8AAAABAA_01A", "url": "https://api.github.com/repos/huggingface/datasets/labels/maintenance" } ]
closed
false
{ "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "gravatar_id": "", "html_url": "https://github.com/albertvillanova", "id": 8515462, "login": "albertvillanova", "node_id": "MDQ6VXNlcjg1MTU0NjI=", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "repos_url": "https://api.github.com/users/albertvillanova/repos", "site_admin": false, "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "type": "User", "url": "https://api.github.com/users/albertvillanova" }
[ { "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "gravatar_id": "", "html_url": "https://github.com/albertvillanova", "id": 8515462, "login": "albertvillanova", "node_id": "MDQ6VXNlcjg1MTU0NjI=", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "repos_url": "https://api.github.com/users/albertvillanova/repos", "site_admin": false, "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "type": "User", "url": "https://api.github.com/users/albertvillanova" } ]
null
[]
1,719,302,144,000
1,719,303,223,000
1,719,303,223,000
MEMBER
null
null
null
CI is broken: https://github.com/huggingface/datasets/actions/runs/9657882317/job/26637998686?pr=6996 ``` FAILED tests/test_inspect.py::test_get_dataset_config_names[hf-internal-testing/librispeech_asr_dummy-expected4] - AssertionError: assert ['clean'] == ['clean', 'other'] Right contains one more item: 'other' Full diff: [ 'clean', - 'other', ] FAILED tests/test_inspect.py::test_get_dataset_default_config_name[hf-internal-testing/librispeech_asr_dummy-None] - AssertionError: assert 'clean' is None ``` Note that repository was recently converted to Parquet: https://huggingface.co./datasets/hf-internal-testing/librispeech_asr_dummy/commit/5be91486e11a2d616f4ec5db8d3fd248585ac07a
{ "+1": 0, "-1": 0, "confused": 0, "eyes": 0, "heart": 0, "hooray": 0, "laugh": 0, "rocket": 0, "total_count": 0, "url": "https://api.github.com/repos/huggingface/datasets/issues/6997/reactions" }
https://api.github.com/repos/huggingface/datasets/issues/6997/timeline
null
completed
false
https://api.github.com/repos/huggingface/datasets/issues/6996
https://api.github.com/repos/huggingface/datasets
https://api.github.com/repos/huggingface/datasets/issues/6996/labels{/name}
https://api.github.com/repos/huggingface/datasets/issues/6996/comments
https://api.github.com/repos/huggingface/datasets/issues/6996/events
https://github.com/huggingface/datasets/pull/6996
2,371,841,671
PR_kwDODunzps5zdAg0
6,996
Remove deprecated code
{ "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "gravatar_id": "", "html_url": "https://github.com/albertvillanova", "id": 8515462, "login": "albertvillanova", "node_id": "MDQ6VXNlcjg1MTU0NjI=", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "repos_url": "https://api.github.com/users/albertvillanova/repos", "site_admin": false, "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "type": "User", "url": "https://api.github.com/users/albertvillanova" }
[]
open
false
null
[]
null
[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6996). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update." ]
1,719,298,480,000
1,719,306,481,000
null
MEMBER
null
1
{ "diff_url": "https://github.com/huggingface/datasets/pull/6996.diff", "html_url": "https://github.com/huggingface/datasets/pull/6996", "merged_at": null, "patch_url": "https://github.com/huggingface/datasets/pull/6996.patch", "url": "https://api.github.com/repos/huggingface/datasets/pulls/6996" }
Remove deprecated code, as part of the 3.0 release.
{ "+1": 0, "-1": 0, "confused": 0, "eyes": 0, "heart": 0, "hooray": 0, "laugh": 0, "rocket": 0, "total_count": 0, "url": "https://api.github.com/repos/huggingface/datasets/issues/6996/reactions" }
https://api.github.com/repos/huggingface/datasets/issues/6996/timeline
null
null
true
https://api.github.com/repos/huggingface/datasets/issues/6995
https://api.github.com/repos/huggingface/datasets
https://api.github.com/repos/huggingface/datasets/issues/6995/labels{/name}
https://api.github.com/repos/huggingface/datasets/issues/6995/comments
https://api.github.com/repos/huggingface/datasets/issues/6995/events
https://github.com/huggingface/datasets/issues/6995
2,370,713,475
I_kwDODunzps6NTjeD
6,995
ImportError when importing datasets.load_dataset
{ "avatar_url": "https://avatars.githubusercontent.com/u/124846947?v=4", "events_url": "https://api.github.com/users/Leo-Lsc/events{/privacy}", "followers_url": "https://api.github.com/users/Leo-Lsc/followers", "following_url": "https://api.github.com/users/Leo-Lsc/following{/other_user}", "gists_url": "https://api.github.com/users/Leo-Lsc/gists{/gist_id}", "gravatar_id": "", "html_url": "https://github.com/Leo-Lsc", "id": 124846947, "login": "Leo-Lsc", "node_id": "U_kgDOB3EDYw", "organizations_url": "https://api.github.com/users/Leo-Lsc/orgs", "received_events_url": "https://api.github.com/users/Leo-Lsc/received_events", "repos_url": "https://api.github.com/users/Leo-Lsc/repos", "site_admin": false, "starred_url": "https://api.github.com/users/Leo-Lsc/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/Leo-Lsc/subscriptions", "type": "User", "url": "https://api.github.com/users/Leo-Lsc" }
[]
closed
false
{ "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "gravatar_id": "", "html_url": "https://github.com/albertvillanova", "id": 8515462, "login": "albertvillanova", "node_id": "MDQ6VXNlcjg1MTU0NjI=", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "repos_url": "https://api.github.com/users/albertvillanova/repos", "site_admin": false, "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "type": "User", "url": "https://api.github.com/users/albertvillanova" }
[ { "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "gravatar_id": "", "html_url": "https://github.com/albertvillanova", "id": 8515462, "login": "albertvillanova", "node_id": "MDQ6VXNlcjg1MTU0NjI=", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "repos_url": "https://api.github.com/users/albertvillanova/repos", "site_admin": false, "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "type": "User", "url": "https://api.github.com/users/albertvillanova" } ]
null
[ "What is the version of your installed `huggingface-hub`:\r\n```python\r\nimport huggingface_hub\r\nprint(huggingface_hub.__version__)\r\n```\r\n\r\nIt seems you have a very old version of `huggingface-hub`, where `CommitInfo` was not still implemented. You need to update it:\r\n```\r\npip install -U huggingface-hub\r\n```\r\n\r\nNote that `CommitInfo` was implemented in huggingface-hub 0.10.0 and datasets requires \"huggingface-hub>=0.21.2\"", "The version of my huggingface-hub is 0.23.4.", "The error message says there is no CommitInfo in your installed huggingface-hub library:\r\n```\r\nImportError: cannot import name 'CommitInfo' from 'huggingface_hub' (D:\\Anaconda3\\envs\\CS224S\\Lib\\site-packages\\huggingface_hub_init_.py)\r\n```\r\n\r\nAnd this is implemented since version 0.10.0:\r\n- https://github.com/huggingface/huggingface_hub/pull/1066" ]
1,719,248,842,000
1,719,299,845,000
1,719,295,897,000
NONE
null
null
null
### Describe the bug I encountered an ImportError while trying to import `load_dataset` from the `datasets` module in Hugging Face. The error message indicates a problem with importing 'CommitInfo' from 'huggingface_hub'. ### Steps to reproduce the bug 1. pip install git+https://github.com/huggingface/datasets 2. from datasets import load_dataset ### Expected behavior ImportError Traceback (most recent call last) Cell In[7], [line 1](vscode-notebook-cell:?execution_count=7&line=1) ----> [1](vscode-notebook-cell:?execution_count=7&line=1) from datasets import load_dataset [3](vscode-notebook-cell:?execution_count=7&line=3) train_set = load_dataset("mispeech/speechocean762", split="train") [4](vscode-notebook-cell:?execution_count=7&line=4) test_set = load_dataset("mispeech/speechocean762", split="test") File d:\Anaconda3\envs\CS224S\Lib\site-packages\datasets\__init__.py:[1](file:///D:/Anaconda3/envs/CS224S/Lib/site-packages/datasets/__init__.py:1)7 1 # Copyright 2020 The HuggingFace Datasets Authors and the TensorFlow Datasets Authors. [2](file:///D:/Anaconda3/envs/CS224S/Lib/site-packages/datasets/__init__.py:2) # [3](file:///D:/Anaconda3/envs/CS224S/Lib/site-packages/datasets/__init__.py:3) # Licensed under the Apache License, Version 2.0 (the "License"); (...) [12](file:///D:/Anaconda3/envs/CS224S/Lib/site-packages/datasets/__init__.py:12) # See the License for the specific language governing permissions and [13](file:///D:/Anaconda3/envs/CS224S/Lib/site-packages/datasets/__init__.py:13) # limitations under the License. [15](file:///D:/Anaconda3/envs/CS224S/Lib/site-packages/datasets/__init__.py:15) __version__ = "2.20.1.dev0" ---> [17](file:///D:/Anaconda3/envs/CS224S/Lib/site-packages/datasets/__init__.py:17) from .arrow_dataset import Dataset [18](file:///D:/Anaconda3/envs/CS224S/Lib/site-packages/datasets/__init__.py:18) from .arrow_reader import ReadInstruction [19](file:///D:/Anaconda3/envs/CS224S/Lib/site-packages/datasets/__init__.py:19) from .builder import ArrowBasedBuilder, BeamBasedBuilder, BuilderConfig, DatasetBuilder, GeneratorBasedBuilder File d:\Anaconda3\envs\CS224S\Lib\site-packages\datasets\arrow_dataset.py:63 [61](file:///D:/Anaconda3/envs/CS224S/Lib/site-packages/datasets/arrow_dataset.py:61) import pyarrow.compute as pc [62](file:///D:/Anaconda3/envs/CS224S/Lib/site-packages/datasets/arrow_dataset.py:62) from fsspec.core import url_to_fs ---> [63](file:///D:/Anaconda3/envs/CS224S/Lib/site-packages/datasets/arrow_dataset.py:63) from huggingface_hub import ( [64](file:///D:/Anaconda3/envs/CS224S/Lib/site-packages/datasets/arrow_dataset.py:64) CommitInfo, [65](file:///D:/Anaconda3/envs/CS224S/Lib/site-packages/datasets/arrow_dataset.py:65) CommitOperationAdd, ... [70](file:///D:/Anaconda3/envs/CS224S/Lib/site-packages/datasets/arrow_dataset.py:70) ) [71](file:///D:/Anaconda3/envs/CS224S/Lib/site-packages/datasets/arrow_dataset.py:71) from huggingface_hub.hf_api import RepoFile [72](file:///D:/Anaconda3/envs/CS224S/Lib/site-packages/datasets/arrow_dataset.py:72) from multiprocess import Pool ImportError: cannot import name 'CommitInfo' from 'huggingface_hub' (d:\Anaconda3\envs\CS224S\Lib\site-packages\huggingface_hub\__init__.py) Output is truncated. View as a [scrollable element](command:cellOutput.enableScrolling?580889ab-0f61-4f37-9214-eaa2b3807f85) or open in a [text editor](command:workbench.action.openLargeOutput?580889ab-0f61-4f37-9214-eaa2b3807f85). Adjust cell output [settings](command:workbench.action.openSettings?%5B%22%40tag%3AnotebookOutputLayout%22%5D)... ### Environment info Leo@DESKTOP-9NHUAMI MSYS /d/Anaconda3/envs/CS224S/Lib/site-packages/huggingface_hub $ datasets-cli env Traceback (most recent call last): File "<frozen runpy>", line 198, in _run_module_as_main File "<frozen runpy>", line 88, in _run_code File "D:\Anaconda3\envs\CS224S\Scripts\datasets-cli.exe\__main__.py", line 4, in <module> File "D:\Anaconda3\envs\CS224S\Lib\site-packages\datasets\__init__.py", line 17, in <module> from .arrow_dataset import Dataset File "D:\Anaconda3\envs\CS224S\Lib\site-packages\datasets\arrow_dataset.py", line 63, in <module> from huggingface_hub import ( ImportError: cannot import name 'CommitInfo' from 'huggingface_hub' (D:\Anaconda3\envs\CS224S\Lib\site-packages\huggingface_hub\__init__.py) (CS224S)
{ "+1": 0, "-1": 0, "confused": 0, "eyes": 0, "heart": 0, "hooray": 0, "laugh": 0, "rocket": 0, "total_count": 0, "url": "https://api.github.com/repos/huggingface/datasets/issues/6995/reactions" }
https://api.github.com/repos/huggingface/datasets/issues/6995/timeline
null
completed
false
https://api.github.com/repos/huggingface/datasets/issues/6994
https://api.github.com/repos/huggingface/datasets
https://api.github.com/repos/huggingface/datasets/issues/6994/labels{/name}
https://api.github.com/repos/huggingface/datasets/issues/6994/comments
https://api.github.com/repos/huggingface/datasets/issues/6994/events
https://github.com/huggingface/datasets/pull/6994
2,370,491,689
PR_kwDODunzps5zYYXr
6,994
Fix incorrect rank value in data splitting (#6990)
{ "avatar_url": "https://avatars.githubusercontent.com/u/18402347?v=4", "events_url": "https://api.github.com/users/yzhangcs/events{/privacy}", "followers_url": "https://api.github.com/users/yzhangcs/followers", "following_url": "https://api.github.com/users/yzhangcs/following{/other_user}", "gists_url": "https://api.github.com/users/yzhangcs/gists{/gist_id}", "gravatar_id": "", "html_url": "https://github.com/yzhangcs", "id": 18402347, "login": "yzhangcs", "node_id": "MDQ6VXNlcjE4NDAyMzQ3", "organizations_url": "https://api.github.com/users/yzhangcs/orgs", "received_events_url": "https://api.github.com/users/yzhangcs/received_events", "repos_url": "https://api.github.com/users/yzhangcs/repos", "site_admin": false, "starred_url": "https://api.github.com/users/yzhangcs/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/yzhangcs/subscriptions", "type": "User", "url": "https://api.github.com/users/yzhangcs" }
[]
open
false
null
[]
null
[ "Sure~", "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6994). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| 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 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.005538 / 0.011353 (-0.005815) | 0.003997 / 0.011008 (-0.007011) | 0.063444 / 0.038508 (0.024935) | 0.032552 / 0.023109 (0.009442) | 0.266574 / 0.275898 (-0.009324) | 0.282841 / 0.323480 (-0.040639) | 0.004279 / 0.007986 (-0.003706) | 0.002788 / 0.004328 (-0.001540) | 0.049226 / 0.004250 (0.044976) | 0.044688 / 0.037052 (0.007636) | 0.275464 / 0.258489 (0.016975) | 0.305278 / 0.293841 (0.011437) | 0.030097 / 0.128546 (-0.098450) | 0.012237 / 0.075646 (-0.063410) | 0.205526 / 0.419271 (-0.213745) | 0.036145 / 0.043533 (-0.007388) | 0.267395 / 0.255139 (0.012256) | 0.289149 / 0.283200 (0.005949) | 0.019044 / 0.141683 (-0.122639) | 1.162294 / 1.452155 (-0.289861) | 1.183642 / 1.492716 (-0.309074) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.139125 / 0.018006 (0.121119) | 0.301743 / 0.000490 (0.301253) | 0.000260 / 0.000200 (0.000061) | 0.000053 / 0.000054 (-0.000001) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.019494 / 0.037411 (-0.017917) | 0.063078 / 0.014526 (0.048552) | 0.076989 / 0.176557 (-0.099567) | 0.121363 / 0.737135 (-0.615773) | 0.080040 / 0.296338 (-0.216298) |\n\n### Benchmark: benchmark_iterating.json\n\n| 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 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.284401 / 0.215209 (0.069192) | 2.805397 / 2.077655 (0.727742) | 1.555609 / 1.504120 (0.051489) | 1.405662 / 1.541195 (-0.135533) | 1.459492 / 1.468490 (-0.008999) | 0.718376 / 4.584777 (-3.866401) | 2.395918 / 3.745712 (-1.349794) | 2.976753 / 5.269862 (-2.293108) | 1.883938 / 4.565676 (-2.681738) | 0.078867 / 0.424275 (-0.345408) | 0.005207 / 0.007607 (-0.002400) | 0.335178 / 0.226044 (0.109133) | 3.313414 / 2.268929 (1.044485) | 1.856929 / 55.444624 (-53.587696) | 1.565319 / 6.876477 (-5.311158) | 1.592723 / 2.142072 (-0.549350) | 0.793621 / 4.805227 (-4.011606) | 0.134208 / 6.500664 (-6.366456) | 0.042853 / 0.075469 (-0.032616) |\n\n### Benchmark: benchmark_map_filter.json\n\n| 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 |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.981553 / 1.841788 (-0.860235) | 11.810438 / 8.074308 (3.736130) | 9.529874 / 10.191392 (-0.661518) | 0.142216 / 0.680424 (-0.538207) | 0.014303 / 0.534201 (-0.519898) | 0.304600 / 0.579283 (-0.274684) | 0.261869 / 0.434364 (-0.172495) | 0.347301 / 0.540337 (-0.193036) | 0.437395 / 1.386936 (-0.949541) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| 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 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.005881 / 0.011353 (-0.005472) | 0.004039 / 0.011008 (-0.006969) | 0.050241 / 0.038508 (0.011733) | 0.032670 / 0.023109 (0.009561) | 0.264940 / 0.275898 (-0.010959) | 0.287105 / 0.323480 (-0.036374) | 0.004844 / 0.007986 (-0.003142) | 0.002867 / 0.004328 (-0.001462) | 0.048083 / 0.004250 (0.043833) | 0.040965 / 0.037052 (0.003913) | 0.274390 / 0.258489 (0.015901) | 0.312107 / 0.293841 (0.018266) | 0.031714 / 0.128546 (-0.096832) | 0.012603 / 0.075646 (-0.063043) | 0.060698 / 0.419271 (-0.358573) | 0.033130 / 0.043533 (-0.010402) | 0.264444 / 0.255139 (0.009305) | 0.282797 / 0.283200 (-0.000403) | 0.027872 / 0.141683 (-0.113811) | 1.139026 / 1.452155 (-0.313129) | 1.181431 / 1.492716 (-0.311285) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.097314 / 0.018006 (0.079308) | 0.301326 / 0.000490 (0.300836) | 0.000215 / 0.000200 (0.000015) | 0.000049 / 0.000054 (-0.000005) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.023394 / 0.037411 (-0.014018) | 0.076270 / 0.014526 (0.061744) | 0.089065 / 0.176557 (-0.087491) | 0.129996 / 0.737135 (-0.607139) | 0.089642 / 0.296338 (-0.206697) |\n\n### Benchmark: benchmark_iterating.json\n\n| 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 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.295390 / 0.215209 (0.080181) | 2.877849 / 2.077655 (0.800194) | 1.537129 / 1.504120 (0.033009) | 1.409441 / 1.541195 (-0.131754) | 1.432468 / 1.468490 (-0.036023) | 0.718054 / 4.584777 (-3.866722) | 0.930872 / 3.745712 (-2.814841) | 2.841028 / 5.269862 (-2.428834) | 1.921990 / 4.565676 (-2.643686) | 0.077638 / 0.424275 (-0.346637) | 0.005494 / 0.007607 (-0.002113) | 0.336331 / 0.226044 (0.110287) | 3.330490 / 2.268929 (1.061561) | 1.887994 / 55.444624 (-53.556630) | 1.593332 / 6.876477 (-5.283144) | 1.726956 / 2.142072 (-0.415116) | 0.783612 / 4.805227 (-4.021615) | 0.129926 / 6.500664 (-6.370738) | 0.040792 / 0.075469 (-0.034677) |\n\n### Benchmark: benchmark_map_filter.json\n\n| 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 |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.980274 / 1.841788 (-0.861514) | 12.193871 / 8.074308 (4.119563) | 10.348934 / 10.191392 (0.157542) | 0.141584 / 0.680424 (-0.538840) | 0.015737 / 0.534201 (-0.518464) | 0.300725 / 0.579283 (-0.278558) | 0.127190 / 0.434364 (-0.307174) | 0.341142 / 0.540337 (-0.199196) | 0.459523 / 1.386936 (-0.927413) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#637246baf96f07b19b193ed101f34b65cb35cffb \"CML watermark\")\n" ]
1,719,241,667,000
1,719,241,667,000
null
NONE
null
0
{ "diff_url": "https://github.com/huggingface/datasets/pull/6994.diff", "html_url": "https://github.com/huggingface/datasets/pull/6994", "merged_at": null, "patch_url": "https://github.com/huggingface/datasets/pull/6994.patch", "url": "https://api.github.com/repos/huggingface/datasets/pulls/6994" }
null
{ "+1": 0, "-1": 0, "confused": 0, "eyes": 0, "heart": 0, "hooray": 0, "laugh": 0, "rocket": 0, "total_count": 0, "url": "https://api.github.com/repos/huggingface/datasets/issues/6994/reactions" }
https://api.github.com/repos/huggingface/datasets/issues/6994/timeline
null
null
true
https://api.github.com/repos/huggingface/datasets/issues/6993
https://api.github.com/repos/huggingface/datasets
https://api.github.com/repos/huggingface/datasets/issues/6993/labels{/name}
https://api.github.com/repos/huggingface/datasets/issues/6993/comments
https://api.github.com/repos/huggingface/datasets/issues/6993/events
https://github.com/huggingface/datasets/pull/6993
2,370,444,104
PR_kwDODunzps5zYN7P
6,993
less script docs
{ "avatar_url": "https://avatars.githubusercontent.com/u/42851186?v=4", "events_url": "https://api.github.com/users/lhoestq/events{/privacy}", "followers_url": "https://api.github.com/users/lhoestq/followers", "following_url": "https://api.github.com/users/lhoestq/following{/other_user}", "gists_url": "https://api.github.com/users/lhoestq/gists{/gist_id}", "gravatar_id": "", "html_url": "https://github.com/lhoestq", "id": 42851186, "login": "lhoestq", "node_id": "MDQ6VXNlcjQyODUxMTg2", "organizations_url": "https://api.github.com/users/lhoestq/orgs", "received_events_url": "https://api.github.com/users/lhoestq/received_events", "repos_url": "https://api.github.com/users/lhoestq/repos", "site_admin": false, "starred_url": "https://api.github.com/users/lhoestq/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/lhoestq/subscriptions", "type": "User", "url": "https://api.github.com/users/lhoestq" }
[]
open
false
null
[]
null
[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6993). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update." ]
1,719,240,328,000
1,719,240,470,000
null
MEMBER
null
0
{ "diff_url": "https://github.com/huggingface/datasets/pull/6993.diff", "html_url": "https://github.com/huggingface/datasets/pull/6993", "merged_at": null, "patch_url": "https://github.com/huggingface/datasets/pull/6993.patch", "url": "https://api.github.com/repos/huggingface/datasets/pulls/6993" }
+ mark as legacy in some parts of the docs since we'll not build new features for script datasets
{ "+1": 0, "-1": 0, "confused": 0, "eyes": 0, "heart": 0, "hooray": 0, "laugh": 0, "rocket": 0, "total_count": 0, "url": "https://api.github.com/repos/huggingface/datasets/issues/6993/reactions" }
https://api.github.com/repos/huggingface/datasets/issues/6993/timeline
null
null
true
https://api.github.com/repos/huggingface/datasets/issues/6992
https://api.github.com/repos/huggingface/datasets
https://api.github.com/repos/huggingface/datasets/issues/6992/labels{/name}
https://api.github.com/repos/huggingface/datasets/issues/6992/comments
https://api.github.com/repos/huggingface/datasets/issues/6992/events
https://github.com/huggingface/datasets/issues/6992
2,367,890,622
I_kwDODunzps6NIyS-
6,992
Dataset with streaming doesn't work with proxy
{ "avatar_url": "https://avatars.githubusercontent.com/u/57779173?v=4", "events_url": "https://api.github.com/users/YHL04/events{/privacy}", "followers_url": "https://api.github.com/users/YHL04/followers", "following_url": "https://api.github.com/users/YHL04/following{/other_user}", "gists_url": "https://api.github.com/users/YHL04/gists{/gist_id}", "gravatar_id": "", "html_url": "https://github.com/YHL04", "id": 57779173, "login": "YHL04", "node_id": "MDQ6VXNlcjU3Nzc5MTcz", "organizations_url": "https://api.github.com/users/YHL04/orgs", "received_events_url": "https://api.github.com/users/YHL04/received_events", "repos_url": "https://api.github.com/users/YHL04/repos", "site_admin": false, "starred_url": "https://api.github.com/users/YHL04/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/YHL04/subscriptions", "type": "User", "url": "https://api.github.com/users/YHL04" }
[]
open
false
null
[]
null
[ "Hi ! can you try updating `datasets` and `huggingface_hub` ?\r\n\r\n```\r\npip install -U datasets huggingface_hub\r\n```" ]
1,719,072,728,000
1,719,072,728,000
null
NONE
null
null
null
### Describe the bug I'm currently trying to stream data using dataset since the dataset is too big but it hangs indefinitely without loading the first batch. I use AIMOS which is a supercomputer that uses proxy to connect to the internet. I assume it has to do with the network configurations. I've already set up both HTTP_PROXY and HTTPS_PROXY. streaming = False works fine. ### Steps to reproduce the bug use load_dataset with streaming = True in AIMOS ### Expected behavior does not hang indefinitely and loads batches to start training run ### Environment info _libgcc_mutex 0.1 conda_forge conda-forge _openmp_mutex 4.5 2_gnu conda-forge _pytorch_select 2.0 cuda_2 https://ftp.osuosl.org/pub/open-ce/1.10.0 abseil-cpp 20220623.0 h9888cd1_6 conda-forge absl-py 1.0.0 py311h399429b_0 https://ftp.osuosl.org/pub/open-ce/1.10.0 aiofiles 23.2.1 pyhd8ed1ab_0 conda-forge aiohttp 3.8.6 py311hf118e41_0 aiosignal 1.2.0 pyhd3eb1b0_0 archspec 0.2.3 pyhd8ed1ab_0 conda-forge arrow-cpp 11.0.0 ha3edaa6_5_cpu conda-forge async-timeout 4.0.2 py311h6ffa863_0 attrs 23.1.0 py311h6ffa863_0 av 10.0.0 py311he6153ed_2 https://ftp.osuosl.org/pub/open-ce/1.10.0 aws-c-auth 0.6.24 hb81f6d7_5 conda-forge aws-c-cal 0.5.20 h3c2b4d9_6 conda-forge aws-c-common 0.8.11 h4194056_0 conda-forge aws-c-compression 0.2.16 ha19333d_3 conda-forge aws-c-event-stream 0.2.18 h12a9399_6 conda-forge aws-c-http 0.7.4 ha2cde00_2 conda-forge aws-c-io 0.13.17 h9189062_2 conda-forge aws-c-mqtt 0.8.6 h40d1a04_6 conda-forge aws-c-s3 0.2.4 hbdbe4f0_3 conda-forge aws-c-sdkutils 0.1.7 ha19333d_3 conda-forge aws-checksums 0.1.14 ha19333d_3 conda-forge aws-crt-cpp 0.19.7 hd018011_7 conda-forge aws-sdk-cpp 1.10.57 hb9575ba_4 conda-forge blas 1.0 openblas blinker 1.8.2 pyhd8ed1ab_0 conda-forge boltons 23.0.0 py311h6ffa863_0 boost-cpp 1.82.0 h25e6d66_2 bottleneck 1.3.5 py311h34f6284_0 brotli 1.0.9 hf118e41_7 brotli-bin 1.0.9 hf118e41_7 brotli-python 1.0.9 py311h4a02239_7 bzip2 1.0.8 h7b6447c_0 c-ares 1.19.1 hf118e41_0 ca-certificates 2024.6.2 h0f6029e_0 conda-forge cachetools 5.3.3 pyhd8ed1ab_0 conda-forge certifi 2024.6.2 pyhd8ed1ab_0 conda-forge cffi 1.15.1 py311hf118e41_3 charset-normalizer 2.0.4 pyhd3eb1b0_0 click 8.1.7 unix_pyh707e725_0 conda-forge conda 24.5.0 py311h1af927a_0 conda-forge conda-content-trust 0.2.0 py311h6ffa863_0 conda-libmamba-solver 23.11.1 py311h6ffa863_0 conda-package-handling 2.2.0 py311h6ffa863_0 conda-package-streaming 0.9.0 py311h6ffa863_0 contourpy 1.0.5 py311h25e6d66_0 cryptography 41.0.3 py311hb0e80e7_0 cudatoolkit 11.8.0 hedcfb66_13 conda-forge cudnn 8.9.2_11.8 h9ceb136_1 https://ftp.osuosl.org/pub/open-ce/1.10.0 cycler 0.11.0 pyhd3eb1b0_0 datasets 2.12.0 py311h6ffa863_0 dill 0.3.6 py311h6ffa863_0 distro 1.9.0 pyhd8ed1ab_0 conda-forge ffmpeg 4.2.2 opence_0 https://ftp.osuosl.org/pub/open-ce/1.10.0 filelock 3.9.0 py311h6ffa863_0 fmt 9.1.0 h25e6d66_0 fonttools 4.25.0 pyhd3eb1b0_0 freetype 2.12.1 hd23a775_0 frozendict 2.4.4 py311hb02d432_0 conda-forge frozenlist 1.4.0 py311hf118e41_0 fsspec 2023.9.2 py311h6ffa863_0 gflags 2.2.2 he6710b0_0 giflib 5.2.1 hf118e41_3 glog 0.6.0 hbe088e0_0 conda-forge gmp 6.3.0 h46f38da_0 conda-forge gmpy2 2.1.5 py311h2758da7_1 conda-forge google-auth 2.30.0 pyhff2d567_0 conda-forge google-auth-oauthlib 0.5.3 pyhd8ed1ab_0 conda-forge grpc-cpp 1.51.1 h8ba971d_1 conda-forge grpcio 1.54.3 py311h414e0d3_0 https://ftp.osuosl.org/pub/open-ce/1.10.0 huggingface_hub 0.17.3 py311h6ffa863_0 icu 73.1 h4a02239_0 idna 3.4 py311h6ffa863_0 importlib-metadata 6.0.0 py311h6ffa863_0 jinja2 3.1.4 pyhd8ed1ab_0 conda-forge jpeg 9e hf118e41_1 jsonpatch 1.32 pyhd3eb1b0_0 jsonpointer 2.1 pyhd3eb1b0_0 kiwisolver 1.4.4 py311h4a02239_0 krb5 1.20.1 hc019ccd_1 lame 3.100 hb283c62_1003 conda-forge lcms2 2.12 h2045e0b_0 ld_impl_linux-ppc64le 2.38 hec883e6_1 lerc 3.0 h29c3540_0 leveldb 1.23 h24532b4_1 conda-forge libabseil 20220623.0 cxx17_h9235812_6 conda-forge libarchive 3.6.2 hd8ab008_2 libarrow 11.0.0 h837770b_5_cpu conda-forge libboost 1.82.0 haf51a6a_2 libbrotlicommon 1.0.9 hf118e41_7 libbrotlidec 1.0.9 hf118e41_7 libbrotlienc 1.0.9 hf118e41_7 libcrc32c 1.1.2 h3b9df90_0 conda-forge libcurl 8.4.0 h4d62439_0 libdeflate 1.17 hf118e41_1 libedit 3.1.20221030 hf118e41_0 libev 4.33 h140841e_1 libevent 2.1.10 h19c23f1_4 conda-forge libexpat 2.6.2 h46f38da_0 conda-forge libffi 3.4.4 h4a02239_0 libgcc-ng 13.2.0 h31e42bb_10 conda-forge libgfortran-ng 11.2.0 hb3889a9_1 libgfortran5 11.2.0 h1234567_1 libgomp 13.2.0 h31e42bb_10 conda-forge libgoogle-cloud 2.7.0 h11140b6_1 conda-forge libgrpc 1.51.1 h4d29a31_1 conda-forge libmamba 1.5.3 h7c6fafd_0 libmambapy 1.5.3 py311h828bf7b_0 libnghttp2 1.57.0 h44e5816_0 libnsl 2.0.1 ha17a0cc_0 conda-forge libopenblas 0.3.23 hc5a31fb_2 https://ftp.osuosl.org/pub/open-ce/1.10.0 libopus 1.3.1 h4e0d66e_1 conda-forge libpng 1.6.39 hf118e41_0 libprotobuf 3.21.12 h1776448_0 https://ftp.osuosl.org/pub/open-ce/1.10.0 libsolv 0.7.24 h0f529ac_0 libsqlite 3.45.3 hd4bbf49_0 conda-forge libssh2 1.10.0 h50fa78f_2 libstdcxx-ng 13.2.0 h262982c_10 conda-forge libthrift 0.18.0 h82f1162_0 conda-forge libtiff 4.5.1 h4a02239_0 libutf8proc 2.8.0 hb283c62_0 conda-forge libuuid 2.38.1 h4194056_0 conda-forge libvpx 1.13.1 h46f38da_0 conda-forge libwebp 1.3.2 h0f96ee2_0 libwebp-base 1.3.2 hf118e41_0 libxcrypt 4.4.36 ha17a0cc_1 conda-forge libxml2 2.10.4 h18e3229_1 libzlib 1.2.13 h1f2b957_6 conda-forge llvm-openmp 14.0.6 hc028133_0 https://ftp.osuosl.org/pub/open-ce/1.10.0 lmdb 0.9.31 ha17a0cc_1 conda-forge lz4-c 1.9.4 h4a02239_0 markdown 3.4.4 pyhd8ed1ab_0 conda-forge markupsafe 2.1.5 py311h32d8acf_0 conda-forge matplotlib 3.8.0 py311h6ffa863_0 matplotlib-base 3.8.0 py311h52e1fcc_0 menuinst 2.1.1 py311h1af927a_0 conda-forge mpc 1.3.1 heaf1863_0 conda-forge mpfr 4.2.1 haad2271_1 conda-forge mpmath 1.3.0 pyhd8ed1ab_0 conda-forge multidict 6.0.2 py311hf118e41_0 multiprocess 0.70.14 py311h6ffa863_0 munkres 1.1.4 py_0 mypy_extensions 1.0.0 pyha770c72_0 conda-forge nccl 2.18.3 cuda11.8_1 https://ftp.osuosl.org/pub/open-ce/1.10.0 ncurses 6.4 h4a02239_0 nest-asyncio 1.6.0 pyhd8ed1ab_0 conda-forge networkx 2.8.8 pyhd8ed1ab_0 conda-forge nomkl 3.0 0 https://ftp.osuosl.org/pub/open-ce/1.10.0 numactl 2.0.16 hba61f60_1 https://ftp.osuosl.org/pub/open-ce/1.10.0 numexpr 2.8.7 py311hc46fc55_0 numpy 1.24.3 py311h148a09e_0 numpy-base 1.24.3 py311h06b82f6_0 oauthlib 3.2.2 pyhd8ed1ab_0 conda-forge openjpeg 2.4.0 hfe35807_0 openssl 3.3.1 h1f2b957_0 conda-forge orc 1.8.2 h341c9a4_2 conda-forge packaging 23.1 py311h6ffa863_0 pandas 2.1.1 py311h52e1fcc_0 pcre2 10.42 h280155c_0 pillow 10.0.1 py311he33076b_0 pip 23.3 py311h6ffa863_0 platformdirs 4.2.2 pyhd8ed1ab_0 conda-forge pluggy 1.0.0 py311h6ffa863_1 pooch 1.8.2 pyhd8ed1ab_0 conda-forge protobuf 4.21.12 py311ha7baec7_1 https://ftp.osuosl.org/pub/open-ce/1.10.0 psutil 5.9.8 py311hd26027c_0 conda-forge pyarrow 11.0.0 py311h04a18d5_1 pyasn1 0.6.0 pyhd8ed1ab_0 conda-forge pyasn1-modules 0.4.0 pyhd8ed1ab_0 conda-forge pybind11-abi 4 hd3eb1b0_1 pycosat 0.6.6 py311hf118e41_0 pycparser 2.21 pyhd3eb1b0_0 pyjwt 2.8.0 pyhd8ed1ab_1 conda-forge pyopenssl 23.2.0 py311h6ffa863_0 pyparsing 3.0.9 py311h6ffa863_0 pyre-extensions 0.0.30 pyhd8ed1ab_0 conda-forge pysocks 1.7.1 py311h6ffa863_0 python 3.11.8 h3332dee_0_cpython conda-forge python-dateutil 2.8.2 pyhd3eb1b0_0 python-tzdata 2023.3 pyhd3eb1b0_0 python-xxhash 2.0.2 py311hf118e41_1 python_abi 3.11 4_cp311 conda-forge pytorch 2.0.1 cuda11.8_py311_1 https://ftp.osuosl.org/pub/open-ce/1.10.0 pytorch-base 2.0.1 cuda11.8_py311_pb4.21.12_4 https://ftp.osuosl.org/pub/open-ce/1.10.0 pytz 2023.3.post1 py311h6ffa863_0 pyu2f 0.1.5 pyhd8ed1ab_0 conda-forge pyyaml 6.0.1 py311hf118e41_0 re2 2023.02.01 h883269e_0 conda-forge readline 8.2 hf118e41_0 regex 2023.10.3 py311hf118e41_0 reproc 14.2.4 h29c3540_1 reproc-cpp 14.2.4 h29c3540_1 requests 2.31.0 py311h6ffa863_0 requests-oauthlib 2.0.0 pyhd8ed1ab_0 conda-forge responses 0.13.3 pyhd3eb1b0_0 rsa 4.9 pyhd8ed1ab_0 conda-forge ruamel.yaml 0.17.21 py311hf118e41_0 s2n 1.3.37 h5e47323_0 conda-forge safetensors 0.4.0 py311hda16d9e_0 scipy 1.11.1 py311hd69e9bb_0 https://ftp.osuosl.org/pub/open-ce/1.10.0 sentencepiece 0.1.97 h1e74c73_py311_pb4.21.12_2 https://ftp.osuosl.org/pub/open-ce/1.10.0 setuptools 68.0.0 py311h6ffa863_0 six 1.16.0 pyhd3eb1b0_1 snappy 1.1.9 h29c3540_0 sqlite 3.41.2 hf118e41_0 sympy 1.12.1 pypyh2585a3b_103 conda-forge tabulate 0.8.10 pyhd8ed1ab_0 conda-forge tensorboard 2.13.0 pyhab0730d_pb4.21.12_1 https://ftp.osuosl.org/pub/open-ce/1.10.0 tensorboard-data-server 0.7.0 pyh6f84499_1 https://ftp.osuosl.org/pub/open-ce/1.10.0 tensorboard-plugin-wit 1.6.0 pyh9f0ad1d_0 conda-forge tk 8.6.13 hd4bbf49_0 conda-forge tokenizers 0.13.3 py311h3d4f45a_0 torchdata 0.6.0 py311_2 https://ftp.osuosl.org/pub/open-ce/1.10.0 torchsnapshot 0.1.0 pyhd8ed1ab_0 conda-forge torchtext-base 0.15.2 cuda11.8_py311_1 https://ftp.osuosl.org/pub/open-ce/1.10.0 torchtnt 0.2.4 pyhd8ed1ab_0 conda-forge torchvision-base 0.15.2 cuda11.8_py311_1 https://ftp.osuosl.org/pub/open-ce/1.10.0 tornado 6.3.3 py311hf118e41_0 tqdm 4.65.0 py311h7837921_0 transformers 4.32.1 py311h6ffa863_0 truststore 0.8.0 py311h6ffa863_0 typing-extensions 4.7.1 py311h6ffa863_0 typing_extensions 4.7.1 py311h6ffa863_0 typing_inspect 0.9.0 pyhd8ed1ab_0 conda-forge tzdata 2023c h04d1e81_0 urllib3 1.26.18 py311h6ffa863_0 utf8proc 2.6.1 h140841e_0 werkzeug 2.3.8 pyhd8ed1ab_0 conda-forge wheel 0.41.2 py311h6ffa863_0 xxhash 0.8.0 h140841e_3 xz 5.4.2 hf118e41_0 yaml 0.2.5 h7b6447c_0 yaml-cpp 0.8.0 h4a02239_0 yarl 1.8.1 py311hf118e41_0 zipp 3.11.0 py311h6ffa863_0 zlib 1.2.13 h1f2b957_6 conda-forge zstandard 0.19.0 py311hf118e41_0 zstd 1.5.5 h57e4825_0
{ "+1": 0, "-1": 0, "confused": 0, "eyes": 0, "heart": 0, "hooray": 0, "laugh": 0, "rocket": 0, "total_count": 0, "url": "https://api.github.com/repos/huggingface/datasets/issues/6992/reactions" }
https://api.github.com/repos/huggingface/datasets/issues/6992/timeline
null
null
false
https://api.github.com/repos/huggingface/datasets/issues/6991
https://api.github.com/repos/huggingface/datasets
https://api.github.com/repos/huggingface/datasets/issues/6991/labels{/name}
https://api.github.com/repos/huggingface/datasets/issues/6991/comments
https://api.github.com/repos/huggingface/datasets/issues/6991/events
https://github.com/huggingface/datasets/pull/6991
2,367,711,094
PR_kwDODunzps5zPoQs
6,991
Unblock NumPy 2.0
{ "avatar_url": "https://avatars.githubusercontent.com/u/730137?v=4", "events_url": "https://api.github.com/users/NeilGirdhar/events{/privacy}", "followers_url": "https://api.github.com/users/NeilGirdhar/followers", "following_url": "https://api.github.com/users/NeilGirdhar/following{/other_user}", "gists_url": "https://api.github.com/users/NeilGirdhar/gists{/gist_id}", "gravatar_id": "", "html_url": "https://github.com/NeilGirdhar", "id": 730137, "login": "NeilGirdhar", "node_id": "MDQ6VXNlcjczMDEzNw==", "organizations_url": "https://api.github.com/users/NeilGirdhar/orgs", "received_events_url": "https://api.github.com/users/NeilGirdhar/received_events", "repos_url": "https://api.github.com/users/NeilGirdhar/repos", "site_admin": false, "starred_url": "https://api.github.com/users/NeilGirdhar/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/NeilGirdhar/subscriptions", "type": "User", "url": "https://api.github.com/users/NeilGirdhar" }
[]
open
false
null
[]
null
[]
1,719,047,993,000
1,719,047,993,000
null
NONE
null
0
{ "diff_url": "https://github.com/huggingface/datasets/pull/6991.diff", "html_url": "https://github.com/huggingface/datasets/pull/6991", "merged_at": null, "patch_url": "https://github.com/huggingface/datasets/pull/6991.patch", "url": "https://api.github.com/repos/huggingface/datasets/pulls/6991" }
Fixes https://github.com/huggingface/datasets/issues/6980
{ "+1": 0, "-1": 0, "confused": 0, "eyes": 0, "heart": 0, "hooray": 0, "laugh": 0, "rocket": 0, "total_count": 0, "url": "https://api.github.com/repos/huggingface/datasets/issues/6991/reactions" }
https://api.github.com/repos/huggingface/datasets/issues/6991/timeline
null
null
true
https://api.github.com/repos/huggingface/datasets/issues/6990
https://api.github.com/repos/huggingface/datasets
https://api.github.com/repos/huggingface/datasets/issues/6990/labels{/name}
https://api.github.com/repos/huggingface/datasets/issues/6990/comments
https://api.github.com/repos/huggingface/datasets/issues/6990/events
https://github.com/huggingface/datasets/issues/6990
2,366,660,785
I_kwDODunzps6NEGCx
6,990
Problematic rank after calling `split_dataset_by_node` twice
{ "avatar_url": "https://avatars.githubusercontent.com/u/18402347?v=4", "events_url": "https://api.github.com/users/yzhangcs/events{/privacy}", "followers_url": "https://api.github.com/users/yzhangcs/followers", "following_url": "https://api.github.com/users/yzhangcs/following{/other_user}", "gists_url": "https://api.github.com/users/yzhangcs/gists{/gist_id}", "gravatar_id": "", "html_url": "https://github.com/yzhangcs", "id": 18402347, "login": "yzhangcs", "node_id": "MDQ6VXNlcjE4NDAyMzQ3", "organizations_url": "https://api.github.com/users/yzhangcs/orgs", "received_events_url": "https://api.github.com/users/yzhangcs/received_events", "repos_url": "https://api.github.com/users/yzhangcs/repos", "site_admin": false, "starred_url": "https://api.github.com/users/yzhangcs/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/yzhangcs/subscriptions", "type": "User", "url": "https://api.github.com/users/yzhangcs" }
[]
open
false
null
[]
null
[ "ah yes good catch ! feel free to open a PR with your suggested fix" ]
1,718,979,926,000
1,719,221,137,000
null
NONE
null
null
null
### Describe the bug I'm trying to split `IterableDataset` by `split_dataset_by_node`. But when doing split on a already split dataset, the resulting `rank` is greater than `world_size`. ### Steps to reproduce the bug Here is the minimal code for reproduction: ```py >>> from datasets import load_dataset >>> from datasets.distributed import split_dataset_by_node >>> dataset = load_dataset('fla-hub/slimpajama-test', split='train', streaming=True) >>> dataset = split_dataset_by_node(dataset, 1, 32) >>> dataset._distributed DistributedConfig(rank=1, world_size=32) >>> dataset = split_dataset_by_node(dataset, 1, 15) >>> dataset._distributed DistributedConfig(rank=481, world_size=480) ``` As you can see, the second rank 481 > 480, which is problematic. ### Expected behavior I think this error comes from this line @lhoestq https://github.com/huggingface/datasets/blob/a6ccf944e42c1a84de81bf326accab9999b86c90/src/datasets/iterable_dataset.py#L2943-L2944 We may need to obtain the rank first. Then the above code gives ```py >>> dataset._distributed DistributedConfig(rank=16, world_size=480) ``` ### Environment info datasets==2.20.0
{ "+1": 0, "-1": 0, "confused": 0, "eyes": 0, "heart": 0, "hooray": 0, "laugh": 0, "rocket": 0, "total_count": 0, "url": "https://api.github.com/repos/huggingface/datasets/issues/6990/reactions" }
https://api.github.com/repos/huggingface/datasets/issues/6990/timeline
null
null
false
https://api.github.com/repos/huggingface/datasets/issues/6989
https://api.github.com/repos/huggingface/datasets
https://api.github.com/repos/huggingface/datasets/issues/6989/labels{/name}
https://api.github.com/repos/huggingface/datasets/issues/6989/comments
https://api.github.com/repos/huggingface/datasets/issues/6989/events
https://github.com/huggingface/datasets/issues/6989
2,365,556,449
I_kwDODunzps6M_4bh
6,989
cache in nfs error
{ "avatar_url": "https://avatars.githubusercontent.com/u/66729924?v=4", "events_url": "https://api.github.com/users/simplew2011/events{/privacy}", "followers_url": "https://api.github.com/users/simplew2011/followers", "following_url": "https://api.github.com/users/simplew2011/following{/other_user}", "gists_url": "https://api.github.com/users/simplew2011/gists{/gist_id}", "gravatar_id": "", "html_url": "https://github.com/simplew2011", "id": 66729924, "login": "simplew2011", "node_id": "MDQ6VXNlcjY2NzI5OTI0", "organizations_url": "https://api.github.com/users/simplew2011/orgs", "received_events_url": "https://api.github.com/users/simplew2011/received_events", "repos_url": "https://api.github.com/users/simplew2011/repos", "site_admin": false, "starred_url": "https://api.github.com/users/simplew2011/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/simplew2011/subscriptions", "type": "User", "url": "https://api.github.com/users/simplew2011" }
[]
open
false
null
[]
null
[]
1,718,935,762,000
1,718,935,975,000
null
NONE
null
null
null
### Describe the bug - When reading dataset, a cache will be generated to the ~/. cache/huggingface/datasets directory - When using .map and .filter operations, runtime cache will be generated to the /tmp/hf_datasets-* directory - The default is to use the path of tempfile.tempdir - If I modify this path to the NFS disk, an error will be reported, but the program will continue to run - https://github.com/huggingface/datasets/blob/main/src/datasets/config.py#L257 ``` Traceback (most recent call last): File "/home/wzp/miniconda3/envs/dask/lib/python3.8/site-packages/multiprocess/process.py", line 315, in _bootstrap self.run() File "/home/wzp/miniconda3/envs/dask/lib/python3.8/site-packages/multiprocess/process.py", line 108, in run self._target(*self._args, **self._kwargs) File "/home/wzp/miniconda3/envs/dask/lib/python3.8/site-packages/multiprocess/managers.py", line 616, in _run_server server.serve_forever() File "/home/wzp/miniconda3/envs/dask/lib/python3.8/site-packages/multiprocess/managers.py", line 182, in serve_forever sys.exit(0) SystemExit: 0 During handling of the above exception, another exception occurred: Traceback (most recent call last): File "/home/wzp/miniconda3/envs/dask/lib/python3.8/site-packages/multiprocess/util.py", line 300, in _run_finalizers finalizer() File "/home/wzp/miniconda3/envs/dask/lib/python3.8/site-packages/multiprocess/util.py", line 224, in __call__ res = self._callback(*self._args, **self._kwargs) File "/home/wzp/miniconda3/envs/dask/lib/python3.8/site-packages/multiprocess/util.py", line 133, in _remove_temp_dir rmtree(tempdir) File "/home/wzp/miniconda3/envs/dask/lib/python3.8/shutil.py", line 718, in rmtree _rmtree_safe_fd(fd, path, onerror) File "/home/wzp/miniconda3/envs/dask/lib/python3.8/shutil.py", line 675, in _rmtree_safe_fd onerror(os.unlink, fullname, sys.exc_info()) File "/home/wzp/miniconda3/envs/dask/lib/python3.8/shutil.py", line 673, in _rmtree_safe_fd os.unlink(entry.name, dir_fd=topfd) OSError: [Errno 16] Device or resource busy: '.nfs000000038330a012000030b4' Traceback (most recent call last): File "/home/wzp/miniconda3/envs/dask/lib/python3.8/site-packages/multiprocess/process.py", line 315, in _bootstrap self.run() File "/home/wzp/miniconda3/envs/dask/lib/python3.8/site-packages/multiprocess/process.py", line 108, in run self._target(*self._args, **self._kwargs) File "/home/wzp/miniconda3/envs/dask/lib/python3.8/site-packages/multiprocess/managers.py", line 616, in _run_server server.serve_forever() File "/home/wzp/miniconda3/envs/dask/lib/python3.8/site-packages/multiprocess/managers.py", line 182, in serve_forever sys.exit(0) SystemExit: 0 During handling of the above exception, another exception occurred: Traceback (most recent call last): File "/home/wzp/miniconda3/envs/dask/lib/python3.8/site-packages/multiprocess/util.py", line 300, in _run_finalizers finalizer() File "/home/wzp/miniconda3/envs/dask/lib/python3.8/site-packages/multiprocess/util.py", line 224, in __call__ res = self._callback(*self._args, **self._kwargs) File "/home/wzp/miniconda3/envs/dask/lib/python3.8/site-packages/multiprocess/util.py", line 133, in _remove_temp_dir rmtree(tempdir) File "/home/wzp/miniconda3/envs/dask/lib/python3.8/shutil.py", line 718, in rmtree _rmtree_safe_fd(fd, path, onerror) File "/home/wzp/miniconda3/envs/dask/lib/python3.8/shutil.py", line 675, in _rmtree_safe_fd onerror(os.unlink, fullname, sys.exc_info()) File "/home/wzp/miniconda3/envs/dask/lib/python3.8/shutil.py", line 673, in _rmtree_safe_fd os.unlink(entry.name, dir_fd=topfd) OSError: [Errno 16] Device or resource busy: '.nfs0000000400064d4a000030e5' ``` ### Steps to reproduce the bug ``` import os import time import tempfile from datasets import load_dataset def add_column(sample): # print(type(sample)) # time.sleep(0.1) sample['__ds__stats__'] = {'data': 123} return sample def filt_column(sample): # print(type(sample)) if len(sample['content']) > 10: return True else: return False if __name__ == '__main__': input_dir = '/mnt/temp/CN/small' # some json dataset dataset = load_dataset('json', data_dir=input_dir) temp_dir = '/media/release/release/temp/temp' # a nfs folder os.makedirs(temp_dir, exist_ok=True) # change huggingface-datasets runtime cache in nfs(default in /tmp) tempfile.tempdir = temp_dir aa = dataset.map(add_column, num_proc=64) aa = aa.filter(filt_column, num_proc=64) print(aa) ``` ### Expected behavior no error occur ### Environment info datasets==2.18.0 ubuntu 20.04
{ "+1": 0, "-1": 0, "confused": 0, "eyes": 0, "heart": 0, "hooray": 0, "laugh": 0, "rocket": 0, "total_count": 0, "url": "https://api.github.com/repos/huggingface/datasets/issues/6989/reactions" }
https://api.github.com/repos/huggingface/datasets/issues/6989/timeline
null
null
false
https://api.github.com/repos/huggingface/datasets/issues/6988
https://api.github.com/repos/huggingface/datasets
https://api.github.com/repos/huggingface/datasets/issues/6988/labels{/name}
https://api.github.com/repos/huggingface/datasets/issues/6988/comments
https://api.github.com/repos/huggingface/datasets/issues/6988/events
https://github.com/huggingface/datasets/pull/6988
2,364,129,918
PR_kwDODunzps5zDpXX
6,988
[`feat`] Move dataset card creation to method for easier overriding
{ "avatar_url": "https://avatars.githubusercontent.com/u/37621491?v=4", "events_url": "https://api.github.com/users/tomaarsen/events{/privacy}", "followers_url": "https://api.github.com/users/tomaarsen/followers", "following_url": "https://api.github.com/users/tomaarsen/following{/other_user}", "gists_url": "https://api.github.com/users/tomaarsen/gists{/gist_id}", "gravatar_id": "", "html_url": "https://github.com/tomaarsen", "id": 37621491, "login": "tomaarsen", "node_id": "MDQ6VXNlcjM3NjIxNDkx", "organizations_url": "https://api.github.com/users/tomaarsen/orgs", "received_events_url": "https://api.github.com/users/tomaarsen/received_events", "repos_url": "https://api.github.com/users/tomaarsen/repos", "site_admin": false, "starred_url": "https://api.github.com/users/tomaarsen/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/tomaarsen/subscriptions", "type": "User", "url": "https://api.github.com/users/tomaarsen" }
[]
open
false
null
[]
null
[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6988). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "`Dataset` objects are not made to be subclassed, so I don't think going in that direction is a good idea. In particular there is absolutely no test to make sure it works well, and nothing in the internal has been made to anticipate this use case.\r\n\r\nI'd suggest to use a separate function to push changes to the Dataset card, and call it after `push_to_hub()`. This way people can also use a similar logic with other tools that `datasets`. You can also use composition instead of subclassing.", "Would you consider an alternative where a Dataset instance carries a dataset card template which can be updated?\n\nI don't want to burden my users with having to call another method after `push_to_hub` themselves. If you're not a fan of the template approach above either, then I'll likely subclass `push_to_hub` to once again download the just-uploaded-but-empty dataset card, update it, and reupload it. It'll just be a bit more requests than necessary, but not a big deal overall.\n\n- Tom Aarsen ", "Actually I find the idea of overriding `_create_dataset_card` better than implementing a templating logic. My main concern is that if we go in that direction we better make sure that subclasses of `Dataset` are working well. \r\n\r\nWell if it's been working fine on your side why not, but make sure you test correctly features that could not work because of subclassing (e.g. I'm pretty sure `map()` won't return your subclass of `Dataset`). Or at least the ones that matter for your lib.\r\n\r\nIf it sounds good to you I'm fine with merging your addition to let you override the dataset card.", "> e.g. I'm pretty sure map() won't return your subclass of Dataset\r\n\r\nI understand that there's limitations such as this one. The subclass doesn't have to be robust - I'd just like some simple automatic dataset card generation options directly after generating the dataset. This can be removed if the user does additional steps before pushing the model, e.g. mapping, filtering, saving to disk and uploading the loaded dataset, etc.\r\n\r\n> If it sounds good to you I'm fine with merging your addition to let you override the dataset card.\r\n\r\nThat would be quite useful for me! I appreciate it.\r\n\r\nI'm not very sure what the test failures are caused by, I believe the only change in behaviour is that\r\n```python\r\n DatasetInfosDict({config_name: info_to_dump}).to_dataset_card_data(dataset_card_data)\r\n MetadataConfigs({config_name: metadata_config_to_dump}).to_dataset_card_data(dataset_card_data)\r\n```\r\nare not called when `dataset_card` was already defined. Unless these have side-effects other than updating `dataset_card_data`, it shouldn't be any different than `main`.\r\n\r\n- Tom Aarsen", "Let's try to have this PR merged then !\r\n\r\nIMO your current implementation can be improved since you path both the dataset card data and the dataset card itself, which is redundant. Also I anticipate the failures in the CI to come from your default implementation which doesn't correspond to what it was doing before\r\n\r\n> Unless these have side-effects other than updating dataset_card_data, it shouldn't be any different than main.\r\n\r\nIndeed the dataset_card_data is the value from attribute of the dataset_card from a few lines before your changes, so yes it modifies the dataset_card object too." ]
1,718,880,477,000
1,718,985,898,000
null
MEMBER
null
0
{ "diff_url": "https://github.com/huggingface/datasets/pull/6988.diff", "html_url": "https://github.com/huggingface/datasets/pull/6988", "merged_at": null, "patch_url": "https://github.com/huggingface/datasets/pull/6988.patch", "url": "https://api.github.com/repos/huggingface/datasets/pulls/6988" }
Hello! ## Pull Request overview * Move dataset card creation to method for easier overriding ## Details It's common for me to fully automatically download, reformat, and upload a dataset (e.g. see https://huggingface.co./datasets?other=sentence-transformers), but one aspect that I cannot easily automate is the dataset card generation. This is because during `push_to_hub`, the dataset card is created in 3 lines of code in a much larger method. To automatically generate a dataset card, I need to either: 1. Subclass `Dataset`/`DatasetDict`, copy the entire `push_to_hub` method to override the ~3 lines used to generate the dataset card. This is not viable as the method is likely to change over time. 2. Use `push_to_hub` normally, then separately download the pushed (but empty) dataset card, update it, and reupload the modified dataset. This works fine, but prevents me from being able to return a `Dataset` to my users which will automatically use a nice dataset card. So, in this PR I'm proposing to move the dataset generation into another method so that it can be overridden more easily. For example, imagine the following use case: ````python import json from typing import Any, Dict, Optional from datasets import Dataset, load_dataset from datasets.info import DatasetInfosDict, DatasetInfo from datasets.utils.metadata import MetadataConfigs from huggingface_hub import DatasetCardData, DatasetCard TEMPLATE = r"""--- {dataset_card_data} --- # Dataset Card for {source_dataset_name} with mined hard negatives This dataset is a collection of {column_one}-{column_two}-negative triplets from the {source_dataset_name} dataset. See [{source_dataset_name}](https://huggingface.co./datasets/{source_dataset_id}) for additional information. This dataset can be used directly with Sentence Transformers to train embedding models. ## Mining Parameters The negative samples have been mined using the following parameters: - `range_min`: {range_min}, i.e. we skip the {range_min} most similar samples - `range_max`: {range_max}, i.e. we only look at the top {range_max} most similar samples - `margin`: {margin}, i.e. we require negative similarity + margin < positive similarity, so negative samples can't be more similar than the known true answer - `sampling_strategy`: {sampling_strategy}, i.e. whether to randomly sample from the candidate negatives or take the "top" negatives - `num_negatives`: {num_negatives}, i.e. we mine {num_negatives} negatives per question-answer pair ## Dataset Format - Columns: {column_one}, {column_two}, negative - Column types: str, str, str - Example: ```python {example} ``` """ class HNMDataset(Dataset): @classmethod def from_dict(cls, *args, mining_kwargs: Dict[str, Any], **kwargs) -> "HNMDataset": dataset = super().from_dict(*args, **kwargs) dataset.mining_kwargs = mining_kwargs return dataset def _create_dataset_card( self, dataset_card_data: DatasetCardData, dataset_card: Optional[DatasetCard], config_name: str, info_to_dump: DatasetInfo, metadata_config_to_dump: MetadataConfigs, ) -> DatasetCard: if dataset_card: return dataset_card DatasetInfosDict({config_name: info_to_dump}).to_dataset_card_data(dataset_card_data) MetadataConfigs({config_name: metadata_config_to_dump}).to_dataset_card_data(dataset_card_data) dataset_card_data.tags = ["sentence-transformers"] dataset_name = self.mining_kwargs["source_dataset"].info.dataset_name # Very messy, just as an example: dataset_id = list(self.mining_kwargs["source_dataset"].info.download_checksums.keys())[0].removeprefix("hf://datasets/").split("@")[0] content = TEMPLATE.format(**{ "dataset_card_data": str(dataset_card_data), "source_dataset_name": dataset_name, "source_dataset_id": dataset_id, "range_min": self.mining_kwargs["range_min"], "range_max": self.mining_kwargs["range_max"], "margin": self.mining_kwargs["margin"], "sampling_strategy": self.mining_kwargs["sampling_strategy"], "num_negatives": self.mining_kwargs["num_negatives"], "column_one": self.column_names[0], "column_two": self.column_names[1], "example": json.dumps(self[0], indent=4), }) return DatasetCard(content) source_dataset = load_dataset("sentence-transformers/gooaq", split="train[:100]") dataset = HNMDataset.from_dict({ "query": source_dataset["question"], "answer": source_dataset["answer"], # "negative": ... <- In my case, this column would be 'mined' automatically with these parameters }, mining_kwargs={ "range_min": 10, "range_max": 20, "max_score": 0.9, "margin": 0.1, "sampling_strategy": "random", "num_negatives": 3, "source_dataset": source_dataset, }) dataset.push_to_hub("tomaarsen/mining_demo", private=True) ```` In this script, I've created a subclass which stores some additional information about how the dataset was generated. It's a bit hacky (e.g. setting a `mining_kwargs` parameter in `from_dict` that wasn't created in `__init__`, but that's just a consequence of how the `from_...` methods don't accept kwargs), but it allows me to create a "hard negatives mining" function that returns a dataset which people can use locally like normal, but if they choose to upload it, then it'll automatically include some information, e.g.: https://huggingface.co./datasets/tomaarsen/mining_demo This allows others to actually find this dataset (e.g. via the `sentence-transformers` tag) and get an idea of the quality, source, etc. by looking at the model card. ## Note I'm not fixed on this solution whatsoever: I am also completely fine with other solutions, e.g. a `dataset.set_dataset_card_creator` method that allows me to provide a function without even having to subclass anything. I'm open to all ideas :) cc @albertvillanova @lhoestq cc @LysandreJik - Tom Aarsen
{ "+1": 0, "-1": 0, "confused": 0, "eyes": 1, "heart": 0, "hooray": 0, "laugh": 0, "rocket": 0, "total_count": 1, "url": "https://api.github.com/repos/huggingface/datasets/issues/6988/reactions" }
https://api.github.com/repos/huggingface/datasets/issues/6988/timeline
null
null
true
https://api.github.com/repos/huggingface/datasets/issues/6987
https://api.github.com/repos/huggingface/datasets
https://api.github.com/repos/huggingface/datasets/issues/6987/labels{/name}
https://api.github.com/repos/huggingface/datasets/issues/6987/comments
https://api.github.com/repos/huggingface/datasets/issues/6987/events
https://github.com/huggingface/datasets/pull/6987
2,363,728,190
PR_kwDODunzps5zCRH6
6,987
Remove beam
{ "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "gravatar_id": "", "html_url": "https://github.com/albertvillanova", "id": 8515462, "login": "albertvillanova", "node_id": "MDQ6VXNlcjg1MTU0NjI=", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "repos_url": "https://api.github.com/users/albertvillanova/repos", "site_admin": false, "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "type": "User", "url": "https://api.github.com/users/albertvillanova" }
[]
open
false
null
[]
null
[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6987). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update." ]
1,718,868,434,000
1,718,870,181,000
null
MEMBER
null
0
{ "diff_url": "https://github.com/huggingface/datasets/pull/6987.diff", "html_url": "https://github.com/huggingface/datasets/pull/6987", "merged_at": null, "patch_url": "https://github.com/huggingface/datasets/pull/6987.patch", "url": "https://api.github.com/repos/huggingface/datasets/pulls/6987" }
Remove beam, as part of the 3.0 release.
{ "+1": 0, "-1": 0, "confused": 0, "eyes": 0, "heart": 0, "hooray": 0, "laugh": 0, "rocket": 0, "total_count": 0, "url": "https://api.github.com/repos/huggingface/datasets/issues/6987/reactions" }
https://api.github.com/repos/huggingface/datasets/issues/6987/timeline
null
null
true
https://api.github.com/repos/huggingface/datasets/issues/6986
https://api.github.com/repos/huggingface/datasets
https://api.github.com/repos/huggingface/datasets/issues/6986/labels{/name}
https://api.github.com/repos/huggingface/datasets/issues/6986/comments
https://api.github.com/repos/huggingface/datasets/issues/6986/events
https://github.com/huggingface/datasets/pull/6986
2,362,584,179
PR_kwDODunzps5y-Zi0
6,986
Add large_list type support in string_to_arrow
{ "avatar_url": "https://avatars.githubusercontent.com/u/16257131?v=4", "events_url": "https://api.github.com/users/arthasking123/events{/privacy}", "followers_url": "https://api.github.com/users/arthasking123/followers", "following_url": "https://api.github.com/users/arthasking123/following{/other_user}", "gists_url": "https://api.github.com/users/arthasking123/gists{/gist_id}", "gravatar_id": "", "html_url": "https://github.com/arthasking123", "id": 16257131, "login": "arthasking123", "node_id": "MDQ6VXNlcjE2MjU3MTMx", "organizations_url": "https://api.github.com/users/arthasking123/orgs", "received_events_url": "https://api.github.com/users/arthasking123/received_events", "repos_url": "https://api.github.com/users/arthasking123/repos", "site_admin": false, "starred_url": "https://api.github.com/users/arthasking123/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/arthasking123/subscriptions", "type": "User", "url": "https://api.github.com/users/arthasking123" }
[]
open
false
null
[]
null
[ "@albertvillanova @KennethEnevoldsen" ]
1,718,808,865,000
1,718,863,078,000
null
NONE
null
0
{ "diff_url": "https://github.com/huggingface/datasets/pull/6986.diff", "html_url": "https://github.com/huggingface/datasets/pull/6986", "merged_at": null, "patch_url": "https://github.com/huggingface/datasets/pull/6986.patch", "url": "https://api.github.com/repos/huggingface/datasets/pulls/6986" }
add large_list type support in string_to_arrow() and _arrow_to_datasets_dtype() in features.py Fix #6984
{ "+1": 0, "-1": 0, "confused": 0, "eyes": 0, "heart": 0, "hooray": 0, "laugh": 0, "rocket": 0, "total_count": 0, "url": "https://api.github.com/repos/huggingface/datasets/issues/6986/reactions" }
https://api.github.com/repos/huggingface/datasets/issues/6986/timeline
null
null
true
https://api.github.com/repos/huggingface/datasets/issues/6985
https://api.github.com/repos/huggingface/datasets
https://api.github.com/repos/huggingface/datasets/issues/6985/labels{/name}
https://api.github.com/repos/huggingface/datasets/issues/6985/comments
https://api.github.com/repos/huggingface/datasets/issues/6985/events
https://github.com/huggingface/datasets/issues/6985
2,362,378,276
I_kwDODunzps6Mzwgk
6,985
AttributeError: module 'pyarrow.lib' has no attribute 'ListViewType'
{ "avatar_url": "https://avatars.githubusercontent.com/u/26666267?v=4", "events_url": "https://api.github.com/users/firmai/events{/privacy}", "followers_url": "https://api.github.com/users/firmai/followers", "following_url": "https://api.github.com/users/firmai/following{/other_user}", "gists_url": "https://api.github.com/users/firmai/gists{/gist_id}", "gravatar_id": "", "html_url": "https://github.com/firmai", "id": 26666267, "login": "firmai", "node_id": "MDQ6VXNlcjI2NjY2MjY3", "organizations_url": "https://api.github.com/users/firmai/orgs", "received_events_url": "https://api.github.com/users/firmai/received_events", "repos_url": "https://api.github.com/users/firmai/repos", "site_admin": false, "starred_url": "https://api.github.com/users/firmai/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/firmai/subscriptions", "type": "User", "url": "https://api.github.com/users/firmai" }
[]
closed
false
null
[]
null
[ "Please note that the error is raised just at import:\r\n```python\r\nimport pyarrow.parquet as pq\r\n```\r\n\r\nTherefore it must be caused by some problem with your pyarrow installation. I would recommend you uninstall and install pyarrow again.\r\n\r\nI also see that it seems you use conda to install pyarrow. Please note that pyarrow offers 3 different packages in conda-forge: https://arrow.apache.org/docs/python/install.html#using-conda\r\n```\r\nconda install -c conda-forge pyarrow\r\n```\r\n> While the pyarrow [conda-forge](https://conda-forge.org/) package is the right choice for most users, both a minimal and maximal variant of the package exist, either of which may be better for your use case. See [Differences between conda-forge packages](https://arrow.apache.org/docs/python/install.html#python-conda-differences).\r\n\r\nPlease, make sure you install the right one: I guess it is either `pyarrow` (or `pyarrow-all`).", "I have same issue, please downgrade pyarrow==15.0.2, it seem datasets library need to be fix", "It is not a problem with the `datasets` library: we support latest version of `pyarrow` and our Continuous Integration tests are using pyarrow 16.1.0 without any problem.\r\n\r\nThe error reported here is raised when importing pyarrow.parquet:\r\n```\r\n---> 29 import pyarrow.parquet as pq\r\n```\r\n```\r\nFile /opt/conda/lib/python3.10/site-packages/pyarrow/parquet/__init__.py:20\r\n 1 # Licensed to the Apache Software Foundation (ASF) under one\r\n 2 # or more contributor license agreements. See the NOTICE file\r\n 3 # distributed with this work for additional information\r\n (...)\r\n 17 \r\n 18 # flake8: noqa\r\n---> 20 from .core import *\r\n\r\nFile /opt/conda/lib/python3.10/site-packages/pyarrow/parquet/core.py:33\r\n 30 import pyarrow as pa\r\n 32 try:\r\n---> 33 import pyarrow._parquet as _parquet\r\n 34 except ImportError as exc:\r\n 35 raise ImportError(\r\n 36 \"The pyarrow installation is not built with support \"\r\n 37 f\"for the Parquet file format ({str(exc)})\"\r\n 38 ) from None\r\n\r\nFile /opt/conda/lib/python3.10/site-packages/pyarrow/_parquet.pyx:1, in init pyarrow._parquet()\r\n\r\nAttributeError: module 'pyarrow.lib' has no attribute 'ListViewType'\r\n```\r\n\r\nThis can only be explained if pyarrow was not properly installed. \r\n\r\nIf the user just installed `pyarrow-core` from conda-forge, then its parquet subpackage is not installed and cannot be imported. You can check pyarrow docs:\r\n- Differences between conda-forge packages: https://arrow.apache.org/docs/python/install.html#python-conda-differences\r\n> The `pyarrow-core` package includes the following functionality:\r\n> ...\r\n> The `pyarrow` package adds the following:\r\n> ...\r\n> Parquet (i.e., `pyarrow.parquet`)" ]
1,718,803,348,000
1,719,314,918,000
1,719,294,051,000
NONE
null
null
null
### Describe the bug I have been struggling with this for two days, any help would be appreciated. Python 3.10 ``` from setfit import SetFitModel from huggingface_hub import login access_token_read = "cccxxxccc" # Authenticate with the Hugging Face Hub login(token=access_token_read) # Load the models from the Hugging Face Hub trainer_relv = SetFitModel.from_pretrained("snowdere/trainer_relevance") trainer_trust = SetFitModel.from_pretrained("snowdere/trainer_trust") trainer_sent = SetFitModel.from_pretrained("snowdere/trainer_sent") trainer_topic = SetFitModel.from_pretrained("snowdere/trainer_topic") ``` ``` --------------------------------------------------------------------------- AttributeError Traceback (most recent call last) Cell In[6], line 1 ----> 1 from setfit import SetFitModel 2 from huggingface_hub import login 4 access_token_read = "ccsddsds" File /opt/conda/lib/python3.10/site-packages/setfit/__init__.py:7 4 import os 5 import warnings ----> 7 from .data import get_templated_dataset, sample_dataset 8 from .model_card import SetFitModelCardData 9 from .modeling import SetFitHead, SetFitModel File /opt/conda/lib/python3.10/site-packages/setfit/data.py:5 3 import pandas as pd 4 import torch ----> 5 from datasets import Dataset, DatasetDict, load_dataset 6 from torch.utils.data import Dataset as TorchDataset 8 from . import logging File /opt/conda/lib/python3.10/site-packages/datasets/__init__.py:18 1 # ruff: noqa 2 # Copyright 2020 The HuggingFace Datasets Authors and the TensorFlow Datasets Authors. 3 # (...) 13 # See the License for the specific language governing permissions and 14 # limitations under the License. 16 __version__ = "2.19.0" ---> 18 from .arrow_dataset import Dataset 19 from .arrow_reader import ReadInstruction 20 from .builder import ArrowBasedBuilder, BeamBasedBuilder, BuilderConfig, DatasetBuilder, GeneratorBasedBuilder File /opt/conda/lib/python3.10/site-packages/datasets/arrow_dataset.py:76 73 from tqdm.contrib.concurrent import thread_map 75 from . import config ---> 76 from .arrow_reader import ArrowReader 77 from .arrow_writer import ArrowWriter, OptimizedTypedSequence 78 from .data_files import sanitize_patterns File /opt/conda/lib/python3.10/site-packages/datasets/arrow_reader.py:29 26 from typing import TYPE_CHECKING, List, Optional, Union 28 import pyarrow as pa ---> 29 import pyarrow.parquet as pq 30 from tqdm.contrib.concurrent import thread_map 32 from .download.download_config import DownloadConfig File /opt/conda/lib/python3.10/site-packages/pyarrow/parquet/__init__.py:20 1 # Licensed to the Apache Software Foundation (ASF) under one 2 # or more contributor license agreements. See the NOTICE file 3 # distributed with this work for additional information (...) 17 18 # flake8: noqa ---> 20 from .core import * File /opt/conda/lib/python3.10/site-packages/pyarrow/parquet/core.py:33 30 import pyarrow as pa 32 try: ---> 33 import pyarrow._parquet as _parquet 34 except ImportError as exc: 35 raise ImportError( 36 "The pyarrow installation is not built with support " 37 f"for the Parquet file format ({str(exc)})" 38 ) from None File /opt/conda/lib/python3.10/site-packages/pyarrow/_parquet.pyx:1, in init pyarrow._parquet() AttributeError: module 'pyarrow.lib' has no attribute 'ListViewType' ``` setfit: 1.0.3 transformers: 4.41.2 lingua-language-detector: 2.0.2 polars: 0.20.31 lightning: None google-cloud-bigquery: 3.24.0 shapely: 2.0.4 pyarrow: 16.0.0 ### Steps to reproduce the bug I have tried all version combinations for Dataset and Pyarrow, the all have the same error since a few days ago. This is accross multiple scripts I have. ### Expected behavior Just ron normally. ### Environment info 3.10
{ "+1": 0, "-1": 0, "confused": 0, "eyes": 0, "heart": 0, "hooray": 0, "laugh": 0, "rocket": 0, "total_count": 0, "url": "https://api.github.com/repos/huggingface/datasets/issues/6985/reactions" }
https://api.github.com/repos/huggingface/datasets/issues/6985/timeline
null
completed
false
https://api.github.com/repos/huggingface/datasets/issues/6984
https://api.github.com/repos/huggingface/datasets
https://api.github.com/repos/huggingface/datasets/issues/6984/labels{/name}
https://api.github.com/repos/huggingface/datasets/issues/6984/comments
https://api.github.com/repos/huggingface/datasets/issues/6984/events
https://github.com/huggingface/datasets/issues/6984
2,362,143,554
I_kwDODunzps6My3NC
6,984
Convert polars DataFrame back to datasets
{ "avatar_url": "https://avatars.githubusercontent.com/u/38550511?v=4", "events_url": "https://api.github.com/users/ljw20180420/events{/privacy}", "followers_url": "https://api.github.com/users/ljw20180420/followers", "following_url": "https://api.github.com/users/ljw20180420/following{/other_user}", "gists_url": "https://api.github.com/users/ljw20180420/gists{/gist_id}", "gravatar_id": "", "html_url": "https://github.com/ljw20180420", "id": 38550511, "login": "ljw20180420", "node_id": "MDQ6VXNlcjM4NTUwNTEx", "organizations_url": "https://api.github.com/users/ljw20180420/orgs", "received_events_url": "https://api.github.com/users/ljw20180420/received_events", "repos_url": "https://api.github.com/users/ljw20180420/repos", "site_admin": false, "starred_url": "https://api.github.com/users/ljw20180420/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/ljw20180420/subscriptions", "type": "User", "url": "https://api.github.com/users/ljw20180420" }
[ { "color": "a2eeef", "default": true, "description": "New feature or request", "id": 1935892871, "name": "enhancement", "node_id": "MDU6TGFiZWwxOTM1ODkyODcx", "url": "https://api.github.com/repos/huggingface/datasets/labels/enhancement" } ]
open
false
null
[]
null
[ "Hi ! Thanks for reporting :)\r\n\r\nWe don't support `large_list` yet, though it should be added to `Sequence` IMO (maybe with a parameter `large=True` ?)" ]
1,718,797,128,000
1,718,797,128,000
null
NONE
null
null
null
### Feature request This returns error. ```python from datasets import Dataset dsdf = Dataset.from_dict({"x": [[1, 2], [3, 4, 5]], "y": ["a", "b"]}) Dataset.from_polars(dsdf.to_polars()) ``` ValueError: Arrow type large_list<item: int64> does not have a datasets dtype equivalent. ### Motivation When datasets contain Sequence data type, it will be converted to Arrow type large_list. However, the reverse (from large_list to Sequence) does not work. ### Your contribution No
{ "+1": 0, "-1": 0, "confused": 0, "eyes": 0, "heart": 0, "hooray": 0, "laugh": 0, "rocket": 0, "total_count": 0, "url": "https://api.github.com/repos/huggingface/datasets/issues/6984/reactions" }
https://api.github.com/repos/huggingface/datasets/issues/6984/timeline
null
null
false
https://api.github.com/repos/huggingface/datasets/issues/6983
https://api.github.com/repos/huggingface/datasets
https://api.github.com/repos/huggingface/datasets/issues/6983/labels{/name}
https://api.github.com/repos/huggingface/datasets/issues/6983/comments
https://api.github.com/repos/huggingface/datasets/issues/6983/events
https://github.com/huggingface/datasets/pull/6983
2,361,806,201
PR_kwDODunzps5y7tK7
6,983
Remove metrics
{ "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "gravatar_id": "", "html_url": "https://github.com/albertvillanova", "id": 8515462, "login": "albertvillanova", "node_id": "MDQ6VXNlcjg1MTU0NjI=", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "repos_url": "https://api.github.com/users/albertvillanova/repos", "site_admin": false, "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "type": "User", "url": "https://api.github.com/users/albertvillanova" }
[]
open
false
null
[]
null
[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6983). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update." ]
1,718,788,135,000
1,718,864,842,000
null
MEMBER
null
0
{ "diff_url": "https://github.com/huggingface/datasets/pull/6983.diff", "html_url": "https://github.com/huggingface/datasets/pull/6983", "merged_at": null, "patch_url": "https://github.com/huggingface/datasets/pull/6983.patch", "url": "https://api.github.com/repos/huggingface/datasets/pulls/6983" }
Remove all metrics, as part of the 3.0 release. Note they are deprecated since 2.5.0 version.
{ "+1": 0, "-1": 0, "confused": 0, "eyes": 0, "heart": 0, "hooray": 0, "laugh": 0, "rocket": 0, "total_count": 0, "url": "https://api.github.com/repos/huggingface/datasets/issues/6983/reactions" }
https://api.github.com/repos/huggingface/datasets/issues/6983/timeline
null
null
true
https://api.github.com/repos/huggingface/datasets/issues/6982
https://api.github.com/repos/huggingface/datasets
https://api.github.com/repos/huggingface/datasets/issues/6982/labels{/name}
https://api.github.com/repos/huggingface/datasets/issues/6982/comments
https://api.github.com/repos/huggingface/datasets/issues/6982/events
https://github.com/huggingface/datasets/issues/6982
2,361,661,469
I_kwDODunzps6MxBgd
6,982
cannot split dataset when using load_dataset
{ "avatar_url": "https://avatars.githubusercontent.com/u/17721894?v=4", "events_url": "https://api.github.com/users/cybest0608/events{/privacy}", "followers_url": "https://api.github.com/users/cybest0608/followers", "following_url": "https://api.github.com/users/cybest0608/following{/other_user}", "gists_url": "https://api.github.com/users/cybest0608/gists{/gist_id}", "gravatar_id": "", "html_url": "https://github.com/cybest0608", "id": 17721894, "login": "cybest0608", "node_id": "MDQ6VXNlcjE3NzIxODk0", "organizations_url": "https://api.github.com/users/cybest0608/orgs", "received_events_url": "https://api.github.com/users/cybest0608/received_events", "repos_url": "https://api.github.com/users/cybest0608/repos", "site_admin": false, "starred_url": "https://api.github.com/users/cybest0608/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/cybest0608/subscriptions", "type": "User", "url": "https://api.github.com/users/cybest0608" }
[]
open
false
null
[]
null
[ "it seems the bug will happened in all windows system, I tried it in windows8.1, 10, 11 and all of them failed. But it won't happened in the Linux(Ubuntu and Centos7) and Mac (both my virtual and physical machine). I still don't know what the problem is. May be related to the path? I cannot run the split file in my windows server which created in Linux (even I replace the path in the arrow document)....work for it for a week but still cannot fix it .....upset" ]
1,718,784,436,000
1,718,866,533,000
null
NONE
null
null
null
### Describe the bug when I use load_dataset methods to load mozilla-foundation/common_voice_7_0, it can successfully download and extracted the dataset but It cannot generating the arrow document, This bug happened in my server, my laptop, so as #6906 , but it won't happen in the google colab. I work for it for days, even I load the datasets from local path, it can Generating train split and validation split but bug happen again in test split. ### Steps to reproduce the bug from datasets import load_dataset, load_metric, Audio common_voice_train = load_dataset("mozilla-foundation/common_voice_7_0", "ja", split="train", token=selftoken, trust_remote_code=True) ### Expected behavior ``` { "name": "ValueError", "message": "Instruction \"train\" corresponds to no data!", "stack": "--------------------------------------------------------------------------- ValueError Traceback (most recent call last) Cell In[2], line 3 1 from datasets import load_dataset, load_metric, Audio ----> 3 common_voice_train = load_dataset(\"mozilla-foundation/common_voice_7_0\", \"ja\", split=\"train\",token='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')#,trust_remote_code=True)#,streaming=True) 4 common_voice_test = load_dataset(\"mozilla-foundation/common_voice_7_0\", \"ja\", split=\"test\",token='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')#,trust_remote_code=True)#,streaming=True) File c:\\Users\\cybes\\.conda\\envs\\ECoG\\lib\\site-packages\\datasets\\load.py:2626, in load_dataset(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, verification_mode, ignore_verifications, keep_in_memory, save_infos, revision, token, use_auth_token, task, streaming, num_proc, storage_options, trust_remote_code, **config_kwargs) 2622 # Build dataset for splits 2623 keep_in_memory = ( 2624 keep_in_memory if keep_in_memory is not None else is_small_dataset(builder_instance.info.dataset_size) 2625 ) -> 2626 ds = builder_instance.as_dataset(split=split, verification_mode=verification_mode, in_memory=keep_in_memory) 2627 # Rename and cast features to match task schema 2628 if task is not None: 2629 # To avoid issuing the same warning twice File c:\\Users\\cybes\\.conda\\envs\\ECoG\\lib\\site-packages\\datasets\\builder.py:1266, in DatasetBuilder.as_dataset(self, split, run_post_process, verification_mode, ignore_verifications, in_memory) 1263 verification_mode = VerificationMode(verification_mode or VerificationMode.BASIC_CHECKS) 1265 # Create a dataset for each of the given splits -> 1266 datasets = map_nested( 1267 partial( 1268 self._build_single_dataset, 1269 run_post_process=run_post_process, 1270 verification_mode=verification_mode, 1271 in_memory=in_memory, 1272 ), 1273 split, 1274 map_tuple=True, 1275 disable_tqdm=True, 1276 ) 1277 if isinstance(datasets, dict): 1278 datasets = DatasetDict(datasets) File c:\\Users\\cybes\\.conda\\envs\\ECoG\\lib\\site-packages\\datasets\\utils\\py_utils.py:484, in map_nested(function, data_struct, dict_only, map_list, map_tuple, map_numpy, num_proc, parallel_min_length, batched, batch_size, types, disable_tqdm, desc) 482 if batched: 483 data_struct = [data_struct] --> 484 mapped = function(data_struct) 485 if batched: 486 mapped = mapped[0] File c:\\Users\\cybes\\.conda\\envs\\ECoG\\lib\\site-packages\\datasets\\builder.py:1296, in DatasetBuilder._build_single_dataset(self, split, run_post_process, verification_mode, in_memory) 1293 split = Split(split) 1295 # Build base dataset -> 1296 ds = self._as_dataset( 1297 split=split, 1298 in_memory=in_memory, 1299 ) 1300 if run_post_process: 1301 for resource_file_name in self._post_processing_resources(split).values(): File c:\\Users\\cybes\\.conda\\envs\\ECoG\\lib\\site-packages\\datasets\\builder.py:1370, in DatasetBuilder._as_dataset(self, split, in_memory) 1368 if self._check_legacy_cache(): 1369 dataset_name = self.name -> 1370 dataset_kwargs = ArrowReader(cache_dir, self.info).read( 1371 name=dataset_name, 1372 instructions=split, 1373 split_infos=self.info.splits.values(), 1374 in_memory=in_memory, 1375 ) 1376 fingerprint = self._get_dataset_fingerprint(split) 1377 return Dataset(fingerprint=fingerprint, **dataset_kwargs) File c:\\Users\\cybes\\.conda\\envs\\ECoG\\lib\\site-packages\\datasets\\arrow_reader.py:256, in BaseReader.read(self, name, instructions, split_infos, in_memory) 254 msg = f'Instruction \"{instructions}\" corresponds to no data!' 255 #msg = f'Instruction \"{self._path}\",\"{name}\",\"{instructions}\",\"{split_infos}\" corresponds to no data!' --> 256 raise ValueError(msg) 257 return self.read_files(files=files, original_instructions=instructions, in_memory=in_memory) ValueError: Instruction \"train\" corresponds to no data!" } ``` ### Environment info Environment: python 3.9 windows 11 pro VScode+jupyter
{ "+1": 0, "-1": 0, "confused": 0, "eyes": 0, "heart": 0, "hooray": 0, "laugh": 0, "rocket": 0, "total_count": 0, "url": "https://api.github.com/repos/huggingface/datasets/issues/6982/reactions" }
https://api.github.com/repos/huggingface/datasets/issues/6982/timeline
null
null
false
https://api.github.com/repos/huggingface/datasets/issues/6981
https://api.github.com/repos/huggingface/datasets
https://api.github.com/repos/huggingface/datasets/issues/6981/labels{/name}
https://api.github.com/repos/huggingface/datasets/issues/6981/comments
https://api.github.com/repos/huggingface/datasets/issues/6981/events
https://github.com/huggingface/datasets/pull/6981
2,361,520,022
PR_kwDODunzps5y6tnN
6,981
Update docs on trust_remote_code defaults to False
{ "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "gravatar_id": "", "html_url": "https://github.com/albertvillanova", "id": 8515462, "login": "albertvillanova", "node_id": "MDQ6VXNlcjg1MTU0NjI=", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "repos_url": "https://api.github.com/users/albertvillanova/repos", "site_admin": false, "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "type": "User", "url": "https://api.github.com/users/albertvillanova" }
[]
closed
false
null
[]
null
[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6981). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| 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 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.005578 / 0.011353 (-0.005775) | 0.003946 / 0.011008 (-0.007062) | 0.063317 / 0.038508 (0.024808) | 0.031878 / 0.023109 (0.008769) | 0.312571 / 0.275898 (0.036673) | 0.281415 / 0.323480 (-0.042065) | 0.004139 / 0.007986 (-0.003846) | 0.002730 / 0.004328 (-0.001598) | 0.049539 / 0.004250 (0.045289) | 0.045056 / 0.037052 (0.008003) | 0.263820 / 0.258489 (0.005330) | 0.297817 / 0.293841 (0.003976) | 0.029490 / 0.128546 (-0.099056) | 0.012467 / 0.075646 (-0.063179) | 0.204607 / 0.419271 (-0.214664) | 0.036305 / 0.043533 (-0.007228) | 0.244102 / 0.255139 (-0.011037) | 0.267855 / 0.283200 (-0.015345) | 0.019794 / 0.141683 (-0.121889) | 1.130784 / 1.452155 (-0.321371) | 1.172507 / 1.492716 (-0.320209) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.092430 / 0.018006 (0.074424) | 0.296460 / 0.000490 (0.295970) | 0.000210 / 0.000200 (0.000010) | 0.000042 / 0.000054 (-0.000012) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.019467 / 0.037411 (-0.017944) | 0.062850 / 0.014526 (0.048324) | 0.074067 / 0.176557 (-0.102490) | 0.123280 / 0.737135 (-0.613856) | 0.077036 / 0.296338 (-0.219302) |\n\n### Benchmark: benchmark_iterating.json\n\n| 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 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.282687 / 0.215209 (0.067478) | 2.786715 / 2.077655 (0.709060) | 1.492028 / 1.504120 (-0.012092) | 1.373603 / 1.541195 (-0.167592) | 1.405004 / 1.468490 (-0.063486) | 0.714408 / 4.584777 (-3.870369) | 2.376785 / 3.745712 (-1.368927) | 2.916150 / 5.269862 (-2.353712) | 1.921184 / 4.565676 (-2.644493) | 0.078354 / 0.424275 (-0.345921) | 0.005236 / 0.007607 (-0.002371) | 0.334647 / 0.226044 (0.108603) | 3.262069 / 2.268929 (0.993140) | 1.858300 / 55.444624 (-53.586324) | 1.572968 / 6.876477 (-5.303509) | 1.659145 / 2.142072 (-0.482927) | 0.779546 / 4.805227 (-4.025681) | 0.132623 / 6.500664 (-6.368041) | 0.042423 / 0.075469 (-0.033046) |\n\n### Benchmark: benchmark_map_filter.json\n\n| 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 |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.985516 / 1.841788 (-0.856271) | 12.001321 / 8.074308 (3.927013) | 9.927011 / 10.191392 (-0.264381) | 0.142645 / 0.680424 (-0.537779) | 0.013808 / 0.534201 (-0.520393) | 0.303422 / 0.579283 (-0.275861) | 0.262666 / 0.434364 (-0.171698) | 0.339369 / 0.540337 (-0.200969) | 0.431028 / 1.386936 (-0.955908) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| 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 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.005848 / 0.011353 (-0.005505) | 0.003971 / 0.011008 (-0.007037) | 0.050746 / 0.038508 (0.012238) | 0.031554 / 0.023109 (0.008445) | 0.277678 / 0.275898 (0.001780) | 0.300776 / 0.323480 (-0.022704) | 0.004428 / 0.007986 (-0.003558) | 0.002773 / 0.004328 (-0.001555) | 0.049882 / 0.004250 (0.045632) | 0.039833 / 0.037052 (0.002780) | 0.289143 / 0.258489 (0.030654) | 0.321425 / 0.293841 (0.027584) | 0.031701 / 0.128546 (-0.096845) | 0.012687 / 0.075646 (-0.062960) | 0.060650 / 0.419271 (-0.358621) | 0.033318 / 0.043533 (-0.010215) | 0.277019 / 0.255139 (0.021880) | 0.292345 / 0.283200 (0.009145) | 0.018520 / 0.141683 (-0.123163) | 1.143933 / 1.452155 (-0.308222) | 1.183913 / 1.492716 (-0.308803) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.094467 / 0.018006 (0.076461) | 0.298822 / 0.000490 (0.298332) | 0.000201 / 0.000200 (0.000001) | 0.000045 / 0.000054 (-0.000010) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.022811 / 0.037411 (-0.014601) | 0.078084 / 0.014526 (0.063558) | 0.089079 / 0.176557 (-0.087477) | 0.130229 / 0.737135 (-0.606906) | 0.090851 / 0.296338 (-0.205487) |\n\n### Benchmark: benchmark_iterating.json\n\n| 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 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.294981 / 0.215209 (0.079772) | 2.908294 / 2.077655 (0.830639) | 1.591281 / 1.504120 (0.087161) | 1.446032 / 1.541195 (-0.095162) | 1.469441 / 1.468490 (0.000951) | 0.726477 / 4.584777 (-3.858300) | 0.983086 / 3.745712 (-2.762626) | 2.892715 / 5.269862 (-2.377147) | 1.974092 / 4.565676 (-2.591584) | 0.079500 / 0.424275 (-0.344775) | 0.005497 / 0.007607 (-0.002110) | 0.342220 / 0.226044 (0.116176) | 3.414508 / 2.268929 (1.145579) | 1.941550 / 55.444624 (-53.503074) | 1.645268 / 6.876477 (-5.231209) | 1.805909 / 2.142072 (-0.336163) | 0.814483 / 4.805227 (-3.990744) | 0.135867 / 6.500664 (-6.364797) | 0.041718 / 0.075469 (-0.033751) |\n\n### Benchmark: benchmark_map_filter.json\n\n| 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 |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.999751 / 1.841788 (-0.842036) | 12.488263 / 8.074308 (4.413954) | 10.867040 / 10.191392 (0.675648) | 0.143999 / 0.680424 (-0.536425) | 0.015496 / 0.534201 (-0.518705) | 0.302170 / 0.579283 (-0.277113) | 0.123753 / 0.434364 (-0.310611) | 0.340424 / 0.540337 (-0.199913) | 0.458339 / 1.386936 (-0.928597) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#a6ccf944e42c1a84de81bf326accab9999b86c90 \"CML watermark\")\n" ]
1,718,781,141,000
1,718,807,579,000
1,718,807,197,000
MEMBER
null
0
{ "diff_url": "https://github.com/huggingface/datasets/pull/6981.diff", "html_url": "https://github.com/huggingface/datasets/pull/6981", "merged_at": "2024-06-19T14:26:37", "patch_url": "https://github.com/huggingface/datasets/pull/6981.patch", "url": "https://api.github.com/repos/huggingface/datasets/pulls/6981" }
Update docs on trust_remote_code defaults to False. The docs needed to be updated due to this PR: - #6954
{ "+1": 0, "-1": 0, "confused": 0, "eyes": 0, "heart": 0, "hooray": 0, "laugh": 0, "rocket": 0, "total_count": 0, "url": "https://api.github.com/repos/huggingface/datasets/issues/6981/reactions" }
https://api.github.com/repos/huggingface/datasets/issues/6981/timeline
null
null
true
https://api.github.com/repos/huggingface/datasets/issues/6980
https://api.github.com/repos/huggingface/datasets
https://api.github.com/repos/huggingface/datasets/issues/6980/labels{/name}
https://api.github.com/repos/huggingface/datasets/issues/6980/comments
https://api.github.com/repos/huggingface/datasets/issues/6980/events
https://github.com/huggingface/datasets/issues/6980
2,360,909,930
I_kwDODunzps6MuKBq
6,980
Support NumPy 2.0
{ "avatar_url": "https://avatars.githubusercontent.com/u/730137?v=4", "events_url": "https://api.github.com/users/NeilGirdhar/events{/privacy}", "followers_url": "https://api.github.com/users/NeilGirdhar/followers", "following_url": "https://api.github.com/users/NeilGirdhar/following{/other_user}", "gists_url": "https://api.github.com/users/NeilGirdhar/gists{/gist_id}", "gravatar_id": "", "html_url": "https://github.com/NeilGirdhar", "id": 730137, "login": "NeilGirdhar", "node_id": "MDQ6VXNlcjczMDEzNw==", "organizations_url": "https://api.github.com/users/NeilGirdhar/orgs", "received_events_url": "https://api.github.com/users/NeilGirdhar/received_events", "repos_url": "https://api.github.com/users/NeilGirdhar/repos", "site_admin": false, "starred_url": "https://api.github.com/users/NeilGirdhar/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/NeilGirdhar/subscriptions", "type": "User", "url": "https://api.github.com/users/NeilGirdhar" }
[ { "color": "a2eeef", "default": true, "description": "New feature or request", "id": 1935892871, "name": "enhancement", "node_id": "MDU6TGFiZWwxOTM1ODkyODcx", "url": "https://api.github.com/repos/huggingface/datasets/labels/enhancement" } ]
open
false
null
[]
null
[]
1,718,753,422,000
1,719,048,017,000
null
NONE
null
null
null
### Feature request Support NumPy 2.0. ### Motivation NumPy introduces the Array API, which bridges the gap between machine learning libraries. Many clients of HuggingFace are eager to start using the Array API. Besides that, NumPy 2 provides a cleaner interface than NumPy 1. ### Tasks NumPy 2.0 was released for testing so that libraries could ensure compatibility [since mid-March](https://github.com/numpy/numpy/issues/24300#issuecomment-1986815755). What needs to be done for HuggingFace to support Numpy 2? - [x] Fix use of `array`: https://github.com/huggingface/datasets/pull/6976 - [ ] Remove [NumPy version limit](https://github.com/huggingface/datasets/pull/6975): https://github.com/huggingface/datasets/pull/6991
{ "+1": 0, "-1": 0, "confused": 0, "eyes": 0, "heart": 0, "hooray": 0, "laugh": 0, "rocket": 0, "total_count": 0, "url": "https://api.github.com/repos/huggingface/datasets/issues/6980/reactions" }
https://api.github.com/repos/huggingface/datasets/issues/6980/timeline
null
null
false
https://api.github.com/repos/huggingface/datasets/issues/6979
https://api.github.com/repos/huggingface/datasets
https://api.github.com/repos/huggingface/datasets/issues/6979/labels{/name}
https://api.github.com/repos/huggingface/datasets/issues/6979/comments
https://api.github.com/repos/huggingface/datasets/issues/6979/events
https://github.com/huggingface/datasets/issues/6979
2,360,175,363
I_kwDODunzps6MrWsD
6,979
How can I load partial parquet files only?
{ "avatar_url": "https://avatars.githubusercontent.com/u/21303438?v=4", "events_url": "https://api.github.com/users/lucasjinreal/events{/privacy}", "followers_url": "https://api.github.com/users/lucasjinreal/followers", "following_url": "https://api.github.com/users/lucasjinreal/following{/other_user}", "gists_url": "https://api.github.com/users/lucasjinreal/gists{/gist_id}", "gravatar_id": "", "html_url": "https://github.com/lucasjinreal", "id": 21303438, "login": "lucasjinreal", "node_id": "MDQ6VXNlcjIxMzAzNDM4", "organizations_url": "https://api.github.com/users/lucasjinreal/orgs", "received_events_url": "https://api.github.com/users/lucasjinreal/received_events", "repos_url": "https://api.github.com/users/lucasjinreal/repos", "site_admin": false, "starred_url": "https://api.github.com/users/lucasjinreal/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/lucasjinreal/subscriptions", "type": "User", "url": "https://api.github.com/users/lucasjinreal" }
[]
closed
false
null
[]
null
[ "Hello,\r\n\r\nHave you tried loading the dataset in streaming mode? [Documentation](https://huggingface.co./docs/datasets/v2.20.0/stream)\r\n\r\nThis way you wouldn't have to load it all. Also, let's be nice to Parquet, it's a really nice technology and we don't need to be mean :)", "I have downloaded part of it, just want to know how to load part of it, stream mode is not work for me since my network (in china) not stable, I don't want do it all again and again.\r\n\r\nJust curious, doesn't there a way to load part of it?", "Could you convert the IterableDataset to a Dataset after taking the first 100 rows with `.take`? This way, you would have a local copy of the first 100 rows on your system and thus won't need to download. Would that work?\r\n\r\nHere is a [SO question](https://stackoverflow.com/questions/76227219/can-i-convert-an-iterabledataset-to-dataset) detailing how to do the conversion.", "I mean, the parquet is like:\r\n\r\n00000-0143554\r\n00001-0143554\r\n00002-0143554\r\n...\r\n00100-0143554\r\n...\r\n09100-0143554\r\n\r\nI just downloaded the first 9900 part of it. \r\n\r\nI can not load with load_dataset, it throw an error says my file is not same as parquet all amount.\r\n\r\nHow could I load the only I have? \r\n\r\n( I really don't want downlaod them all, cause, I don't need all, and pulus, its huge.... )\r\n\r\nAs I said, I have donwloaded about 9999... It's not about stream... I just wnat to konw how to load offline... part....", "Hi, @lucasjinreal.\r\n\r\nI am not sure of understanding your issue. What is the error message and stack trace you get? What version of `datasets` are you using? Could you provide a reproducible example?\r\n\r\nWithout knowing all those details, I would naively say that you can load whatever number of Parquet files by using the \"parquet\" loader: https://huggingface.co./docs/datasets/loading#parquet\r\n```python\r\nds = load_dataset(\"parquet\", data_files=\"data/train-001*-of-00314.parquet\", split=\"train\")\r\n```", "@albertvillanova Not sure you have tested with this or not, but I have tried,\r\n\r\nthe only error I got is it still laodding all parquet with a progress bar maxium to the whole number 014354, and it loads my 0 - 000999 part, then throws an error.\r\n\r\nSays Numinfo is not same.\r\n\r\nI am so confused,", "Yes, my code snippet works.\n\nCould you copy-paste your code and the output? Otherwise we are not able to know what the issue is.", "@albertvillanova Hi, thanks for the tracing of the issue.\r\n\r\nThis is the output:\r\n\r\n```\r\nython get_llava_recap_cc3m.py\r\nGenerating train split: 3%|███▋ | 101910/3199866 [00:16<08:30, 6065.67 examples/s]\r\nTraceback (most recent call last):\r\n File \"get_llava_recap_cc3m.py\", line 31, in <module>\r\n dataset = load_dataset(\"llava-recap-cc3m/\", data_files=\"data/train-0000*-of-00314.parquet\")\r\n File \"/usr/local/lib/python3.8/dist-packages/datasets/load.py\", line 2582, in load_dataset\r\n builder_instance.download_and_prepare(\r\n File \"/usr/local/lib/python3.8/dist-packages/datasets/builder.py\", line 1005, in download_and_prepare\r\n self._download_and_prepare(\r\n File \"/usr/local/lib/python3.8/dist-packages/datasets/builder.py\", line 1118, in _download_and_prepare\r\n verify_splits(self.info.splits, split_dict)\r\n File \"/usr/local/lib/python3.8/dist-packages/datasets/utils/info_utils.py\", line 101, in verify_splits\r\n raise NonMatchingSplitsSizesError(str(bad_splits))\r\ndatasets.utils.info_utils.NonMatchingSplitsSizesError: [{'expected': SplitInfo(name='train', num_bytes=156885281898.75, num_examples=3199866, shard_lengths=None, dataset_name=None), 'recorded': SplitInfo(name='train', num_bytes=4994080770, num_examples=101910, shard_lengths=[10191, 10291, 10291, 10291, 10291, 10191, 10191, 10291, 10291, 9591], dataset_name='llava-recap-cc3m')}]\r\n```\r\n\r\nthis is my code:\r\n\r\n```\r\ndataset = load_dataset(\"llava-recap-cc3m/\", data_files=\"data/train-0000*-of-00314.parquet\")\r\n```\r\n\r\nMy situation and requirements:\r\n\r\n00314 is all, but I downlaode about 150, half of it, as you can see, i used `0000*-of-00314.` which should be at most 99 file being loaded.\r\n\r\nBut it just fail.\r\n\r\nCan u understand my issue now?\r\n\r\nIf so, then **do not** suggest me with stream, Just want to know, is there a way to load part if it...... **and please don't say you can not replicate my issue when you have downloaded them all**, my english is not good, but I think all situations and all prerequists I have addressed already.\r\n\r\n", "I see you did not use the \"parquet\" loader as I suggested in my code snippet above: https://github.com/huggingface/datasets/issues/6979#issuecomment-2182031415\r\nPlease try passing \"parquet\" instead of \"llava-recap-cc3m/\" to `load_dataset`, and the complete path to data files in `data_files`:\r\n```python\r\nload_dataset(\"parquet\", data_files=\"llava-recap-cc3m/data/train-001*-of-00314.parquet\")\r\n```", "Let me explain that you get the error because of this content within the `dataset_info` YAML tag in the `llava-recap-cc3m/README.md`:\r\n```\r\n - name: train\r\n num_bytes: 156885281898.75\r\n num_examples: 3199866\r\n```\r\n\r\nBy default, if there is that content in the README file, `load_dataset` performs a basic check to verify it the generated number of examples matches the expected one and raises a `NonMatchingSplitsSizesError` if that is not the case. \r\n\r\nYou can avoid this basic check by passing `verification_mode=\"no_checks\"`:\r\n```python\r\nload_dataset(\"llava-recap-cc3m/\", data_files=\"data/train-0000*-of-00314.parquet\", verification_mode=\"no_checks\")\r\n```", "And please, next time you have an issue, please fill the Bug template issue with all the necessary information: https://github.com/huggingface/datasets/issues/new?assignees=&labels=&projects=&template=bug-report.yml\r\n\r\nOtherwise it is very difficult for us to understand the underlying problem and to propose a pertinent solution.", "thank u albert!\r\n\r\nIt solved my issue!" ]
1,718,725,456,000
1,718,989,772,000
1,718,976,770,000
NONE
null
null
null
I have a HUGE dataset about 14TB, I unable to download all parquet all. I just take about 100 from it. dataset = load_dataset("xx/", data_files="data/train-001*-of-00314.parquet") How can I just using 000 - 100 from a 00314 from all partially? I search whole net didn't found a solution, **this is stupid if they didn't support it, and I swear I wont using stupid parquet any more**
{ "+1": 0, "-1": 0, "confused": 0, "eyes": 0, "heart": 0, "hooray": 0, "laugh": 0, "rocket": 0, "total_count": 0, "url": "https://api.github.com/repos/huggingface/datasets/issues/6979/reactions" }
https://api.github.com/repos/huggingface/datasets/issues/6979/timeline
null
completed
false
https://api.github.com/repos/huggingface/datasets/issues/6978
https://api.github.com/repos/huggingface/datasets
https://api.github.com/repos/huggingface/datasets/issues/6978/labels{/name}
https://api.github.com/repos/huggingface/datasets/issues/6978/comments
https://api.github.com/repos/huggingface/datasets/issues/6978/events
https://github.com/huggingface/datasets/pull/6978
2,359,511,469
PR_kwDODunzps5yz0h6
6,978
Fix regression for pandas < 2.0.0 in JSON loader
{ "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "gravatar_id": "", "html_url": "https://github.com/albertvillanova", "id": 8515462, "login": "albertvillanova", "node_id": "MDQ6VXNlcjg1MTU0NjI=", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "repos_url": "https://api.github.com/users/albertvillanova/repos", "site_admin": false, "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "type": "User", "url": "https://api.github.com/users/albertvillanova" }
[]
closed
false
null
[]
null
[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6978). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| 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 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.005144 / 0.011353 (-0.006209) | 0.003500 / 0.011008 (-0.007509) | 0.063670 / 0.038508 (0.025162) | 0.031793 / 0.023109 (0.008683) | 0.239611 / 0.275898 (-0.036287) | 0.276681 / 0.323480 (-0.046799) | 0.004148 / 0.007986 (-0.003838) | 0.002713 / 0.004328 (-0.001615) | 0.048832 / 0.004250 (0.044582) | 0.043066 / 0.037052 (0.006014) | 0.256835 / 0.258489 (-0.001655) | 0.292224 / 0.293841 (-0.001617) | 0.027530 / 0.128546 (-0.101017) | 0.010509 / 0.075646 (-0.065137) | 0.203370 / 0.419271 (-0.215901) | 0.035643 / 0.043533 (-0.007890) | 0.252161 / 0.255139 (-0.002978) | 0.271883 / 0.283200 (-0.011316) | 0.018658 / 0.141683 (-0.123024) | 1.081676 / 1.452155 (-0.370479) | 1.142146 / 1.492716 (-0.350571) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.093484 / 0.018006 (0.075477) | 0.298607 / 0.000490 (0.298117) | 0.000220 / 0.000200 (0.000020) | 0.000044 / 0.000054 (-0.000010) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.019021 / 0.037411 (-0.018390) | 0.062471 / 0.014526 (0.047946) | 0.075393 / 0.176557 (-0.101163) | 0.121040 / 0.737135 (-0.616095) | 0.077613 / 0.296338 (-0.218726) |\n\n### Benchmark: benchmark_iterating.json\n\n| 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 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.294857 / 0.215209 (0.079648) | 2.931143 / 2.077655 (0.853489) | 1.510866 / 1.504120 (0.006746) | 1.379574 / 1.541195 (-0.161621) | 1.352358 / 1.468490 (-0.116133) | 0.561670 / 4.584777 (-4.023107) | 2.378434 / 3.745712 (-1.367278) | 2.713203 / 5.269862 (-2.556658) | 1.706416 / 4.565676 (-2.859260) | 0.062355 / 0.424275 (-0.361920) | 0.004971 / 0.007607 (-0.002636) | 0.336498 / 0.226044 (0.110453) | 3.316464 / 2.268929 (1.047535) | 1.833035 / 55.444624 (-53.611589) | 1.532808 / 6.876477 (-5.343668) | 1.537323 / 2.142072 (-0.604749) | 0.639430 / 4.805227 (-4.165798) | 0.115808 / 6.500664 (-6.384856) | 0.043545 / 0.075469 (-0.031924) |\n\n### Benchmark: benchmark_map_filter.json\n\n| 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 |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.974428 / 1.841788 (-0.867360) | 11.368914 / 8.074308 (3.294606) | 9.754488 / 10.191392 (-0.436904) | 0.146277 / 0.680424 (-0.534146) | 0.013917 / 0.534201 (-0.520284) | 0.286809 / 0.579283 (-0.292474) | 0.267144 / 0.434364 (-0.167219) | 0.326161 / 0.540337 (-0.214177) | 0.418059 / 1.386936 (-0.968877) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| 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 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.005341 / 0.011353 (-0.006012) | 0.003460 / 0.011008 (-0.007548) | 0.050135 / 0.038508 (0.011627) | 0.032014 / 0.023109 (0.008905) | 0.259835 / 0.275898 (-0.016063) | 0.286275 / 0.323480 (-0.037205) | 0.004350 / 0.007986 (-0.003636) | 0.002800 / 0.004328 (-0.001529) | 0.049358 / 0.004250 (0.045107) | 0.040182 / 0.037052 (0.003130) | 0.278352 / 0.258489 (0.019863) | 0.307869 / 0.293841 (0.014028) | 0.029151 / 0.128546 (-0.099395) | 0.010091 / 0.075646 (-0.065555) | 0.058814 / 0.419271 (-0.360458) | 0.033150 / 0.043533 (-0.010383) | 0.263594 / 0.255139 (0.008455) | 0.284065 / 0.283200 (0.000866) | 0.017968 / 0.141683 (-0.123714) | 1.145605 / 1.452155 (-0.306550) | 1.196884 / 1.492716 (-0.295832) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.094045 / 0.018006 (0.076039) | 0.299031 / 0.000490 (0.298541) | 0.000210 / 0.000200 (0.000011) | 0.000044 / 0.000054 (-0.000010) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.022510 / 0.037411 (-0.014901) | 0.077478 / 0.014526 (0.062953) | 0.087746 / 0.176557 (-0.088811) | 0.129311 / 0.737135 (-0.607825) | 0.089921 / 0.296338 (-0.206418) |\n\n### Benchmark: benchmark_iterating.json\n\n| 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 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.290279 / 0.215209 (0.075070) | 2.880725 / 2.077655 (0.803070) | 1.541262 / 1.504120 (0.037142) | 1.424475 / 1.541195 (-0.116719) | 1.436397 / 1.468490 (-0.032093) | 0.578237 / 4.584777 (-4.006540) | 0.965249 / 3.745712 (-2.780463) | 2.682534 / 5.269862 (-2.587327) | 1.732859 / 4.565676 (-2.832817) | 0.065523 / 0.424275 (-0.358752) | 0.005466 / 0.007607 (-0.002141) | 0.343985 / 0.226044 (0.117940) | 3.397463 / 2.268929 (1.128534) | 1.929370 / 55.444624 (-53.515255) | 1.605135 / 6.876477 (-5.271342) | 1.753926 / 2.142072 (-0.388146) | 0.659929 / 4.805227 (-4.145298) | 0.118093 / 6.500664 (-6.382571) | 0.041252 / 0.075469 (-0.034217) |\n\n### Benchmark: benchmark_map_filter.json\n\n| 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 |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.009177 / 1.841788 (-0.832610) | 11.959624 / 8.074308 (3.885316) | 10.484672 / 10.191392 (0.293280) | 0.142085 / 0.680424 (-0.538339) | 0.015955 / 0.534201 (-0.518245) | 0.283649 / 0.579283 (-0.295634) | 0.125681 / 0.434364 (-0.308683) | 0.320490 / 0.540337 (-0.219847) | 0.440353 / 1.386936 (-0.946583) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#e47a746bcda4b97db2467542b76d3215b3569ff0 \"CML watermark\")\n", "Maybe a patch release will be needed with this fix." ]
1,718,706,394,000
1,718,778,204,000
1,718,776,218,000
MEMBER
null
0
{ "diff_url": "https://github.com/huggingface/datasets/pull/6978.diff", "html_url": "https://github.com/huggingface/datasets/pull/6978", "merged_at": "2024-06-19T05:50:18", "patch_url": "https://github.com/huggingface/datasets/pull/6978.patch", "url": "https://api.github.com/repos/huggingface/datasets/pulls/6978" }
A regression was introduced for pandas < 2.0.0 in PR: - #6914 As described in pandas docs, the `dtype_backend` parameter was first added in pandas 2.0.0: https://pandas.pydata.org/docs/reference/api/pandas.read_json.html This PR fixes the regression by passing (or not) the `dtype_backend` parameter depending on pandas version. Maybe, in a future 3.0 `datasets` release, we could just require pandas > 2.0. Reported by: - #6977
{ "+1": 0, "-1": 0, "confused": 0, "eyes": 0, "heart": 0, "hooray": 0, "laugh": 0, "rocket": 0, "total_count": 0, "url": "https://api.github.com/repos/huggingface/datasets/issues/6978/reactions" }
https://api.github.com/repos/huggingface/datasets/issues/6978/timeline
null
null
true
https://api.github.com/repos/huggingface/datasets/issues/6977
https://api.github.com/repos/huggingface/datasets
https://api.github.com/repos/huggingface/datasets/issues/6977/labels{/name}
https://api.github.com/repos/huggingface/datasets/issues/6977/comments
https://api.github.com/repos/huggingface/datasets/issues/6977/events
https://github.com/huggingface/datasets/issues/6977
2,359,295,045
I_kwDODunzps6Mn_xF
6,977
load json file error with v2.20.0
{ "avatar_url": "https://avatars.githubusercontent.com/u/15037766?v=4", "events_url": "https://api.github.com/users/xiaoyaolangzhi/events{/privacy}", "followers_url": "https://api.github.com/users/xiaoyaolangzhi/followers", "following_url": "https://api.github.com/users/xiaoyaolangzhi/following{/other_user}", "gists_url": "https://api.github.com/users/xiaoyaolangzhi/gists{/gist_id}", "gravatar_id": "", "html_url": "https://github.com/xiaoyaolangzhi", "id": 15037766, "login": "xiaoyaolangzhi", "node_id": "MDQ6VXNlcjE1MDM3NzY2", "organizations_url": "https://api.github.com/users/xiaoyaolangzhi/orgs", "received_events_url": "https://api.github.com/users/xiaoyaolangzhi/received_events", "repos_url": "https://api.github.com/users/xiaoyaolangzhi/repos", "site_admin": false, "starred_url": "https://api.github.com/users/xiaoyaolangzhi/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/xiaoyaolangzhi/subscriptions", "type": "User", "url": "https://api.github.com/users/xiaoyaolangzhi" }
[]
closed
false
{ "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "gravatar_id": "", "html_url": "https://github.com/albertvillanova", "id": 8515462, "login": "albertvillanova", "node_id": "MDQ6VXNlcjg1MTU0NjI=", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "repos_url": "https://api.github.com/users/albertvillanova/repos", "site_admin": false, "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "type": "User", "url": "https://api.github.com/users/albertvillanova" }
[ { "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "gravatar_id": "", "html_url": "https://github.com/albertvillanova", "id": 8515462, "login": "albertvillanova", "node_id": "MDQ6VXNlcjg1MTU0NjI=", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "repos_url": "https://api.github.com/users/albertvillanova/repos", "site_admin": false, "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "type": "User", "url": "https://api.github.com/users/albertvillanova" } ]
null
[ "Thanks for reporting, @xiaoyaolangzhi.\r\n\r\nIndeed, we are currently requiring `pandas` >= 2.0.0.\r\n\r\nYou will need to update pandas in your local environment:\r\n```\r\npip install -U pandas\r\n``` ", "Thank you very much." ]
1,718,700,061,000
1,718,705,170,000
1,718,705,169,000
NONE
null
null
null
### Describe the bug ``` load_dataset(path="json", data_files="./test.json") ``` ``` Generating train split: 0 examples [00:00, ? examples/s] Traceback (most recent call last): File "/usr/local/lib/python3.10/dist-packages/datasets/packaged_modules/json/json.py", line 132, in _generate_tables pa_table = paj.read_json( File "pyarrow/_json.pyx", line 308, in pyarrow._json.read_json File "pyarrow/error.pxi", line 154, in pyarrow.lib.pyarrow_internal_check_status File "pyarrow/error.pxi", line 91, in pyarrow.lib.check_status pyarrow.lib.ArrowInvalid: JSON parse error: Column() changed from object to array in row 0 During handling of the above exception, another exception occurred: Traceback (most recent call last): File "/usr/local/lib/python3.10/dist-packages/datasets/builder.py", line 1997, in _prepare_split_single for _, table in generator: File "/usr/local/lib/python3.10/dist-packages/datasets/packaged_modules/json/json.py", line 155, in _generate_tables df = pd.read_json(f, dtype_backend="pyarrow") File "/usr/local/lib/python3.10/dist-packages/pandas/util/_decorators.py", line 211, in wrapper return func(*args, **kwargs) File "/usr/local/lib/python3.10/dist-packages/pandas/util/_decorators.py", line 331, in wrapper return func(*args, **kwargs) TypeError: read_json() got an unexpected keyword argument 'dtype_backend' The above exception was the direct cause of the following exception: Traceback (most recent call last): File "/app/t1.py", line 11, in <module> load_dataset(path=data_path, data_files="./t2.json") File "/usr/local/lib/python3.10/dist-packages/datasets/load.py", line 2616, in load_dataset builder_instance.download_and_prepare( File "/usr/local/lib/python3.10/dist-packages/datasets/builder.py", line 1029, in download_and_prepare self._download_and_prepare( File "/usr/local/lib/python3.10/dist-packages/datasets/builder.py", line 1124, in _download_and_prepare self._prepare_split(split_generator, **prepare_split_kwargs) File "/usr/local/lib/python3.10/dist-packages/datasets/builder.py", line 1884, in _prepare_split for job_id, done, content in self._prepare_split_single( File "/usr/local/lib/python3.10/dist-packages/datasets/builder.py", line 2040, in _prepare_split_single raise DatasetGenerationError("An error occurred while generating the dataset") from e datasets.exceptions.DatasetGenerationError: An error occurred while generating the dataset ``` ``` import pandas as pd with open("./test.json", "r") as f: df = pd.read_json(f, dtype_backend="pyarrow") ``` ``` Traceback (most recent call last): File "/app/t3.py", line 3, in <module> df = pd.read_json(f, dtype_backend="pyarrow") File "/usr/local/lib/python3.10/dist-packages/pandas/util/_decorators.py", line 211, in wrapper return func(*args, **kwargs) File "/usr/local/lib/python3.10/dist-packages/pandas/util/_decorators.py", line 331, in wrapper return func(*args, **kwargs) TypeError: read_json() got an unexpected keyword argument 'dtype_backend' ``` ### Steps to reproduce the bug . ### Expected behavior . ### Environment info ``` datasets 2.20.0 pandas 1.5.3 ```
{ "+1": 0, "-1": 0, "confused": 0, "eyes": 0, "heart": 0, "hooray": 0, "laugh": 0, "rocket": 0, "total_count": 0, "url": "https://api.github.com/repos/huggingface/datasets/issues/6977/reactions" }
https://api.github.com/repos/huggingface/datasets/issues/6977/timeline
null
completed
false
https://api.github.com/repos/huggingface/datasets/issues/6976
https://api.github.com/repos/huggingface/datasets
https://api.github.com/repos/huggingface/datasets/issues/6976/labels{/name}
https://api.github.com/repos/huggingface/datasets/issues/6976/comments
https://api.github.com/repos/huggingface/datasets/issues/6976/events
https://github.com/huggingface/datasets/pull/6976
2,357,107,203
PR_kwDODunzps5yrmNP
6,976
Ensure compatibility with numpy 2.0.0
{ "avatar_url": "https://avatars.githubusercontent.com/u/23721977?v=4", "events_url": "https://api.github.com/users/KennethEnevoldsen/events{/privacy}", "followers_url": "https://api.github.com/users/KennethEnevoldsen/followers", "following_url": "https://api.github.com/users/KennethEnevoldsen/following{/other_user}", "gists_url": "https://api.github.com/users/KennethEnevoldsen/gists{/gist_id}", "gravatar_id": "", "html_url": "https://github.com/KennethEnevoldsen", "id": 23721977, "login": "KennethEnevoldsen", "node_id": "MDQ6VXNlcjIzNzIxOTc3", "organizations_url": "https://api.github.com/users/KennethEnevoldsen/orgs", "received_events_url": "https://api.github.com/users/KennethEnevoldsen/received_events", "repos_url": "https://api.github.com/users/KennethEnevoldsen/repos", "site_admin": false, "starred_url": "https://api.github.com/users/KennethEnevoldsen/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/KennethEnevoldsen/subscriptions", "type": "User", "url": "https://api.github.com/users/KennethEnevoldsen" }
[]
closed
false
null
[]
null
[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6976). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| 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 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.005361 / 0.011353 (-0.005992) | 0.003983 / 0.011008 (-0.007025) | 0.062865 / 0.038508 (0.024357) | 0.029880 / 0.023109 (0.006771) | 0.261465 / 0.275898 (-0.014433) | 0.269791 / 0.323480 (-0.053689) | 0.004198 / 0.007986 (-0.003788) | 0.002942 / 0.004328 (-0.001387) | 0.049002 / 0.004250 (0.044751) | 0.043232 / 0.037052 (0.006180) | 0.328774 / 0.258489 (0.070285) | 0.297308 / 0.293841 (0.003467) | 0.030552 / 0.128546 (-0.097994) | 0.012632 / 0.075646 (-0.063015) | 0.204156 / 0.419271 (-0.215116) | 0.036014 / 0.043533 (-0.007519) | 0.241224 / 0.255139 (-0.013915) | 0.268358 / 0.283200 (-0.014842) | 0.019227 / 0.141683 (-0.122456) | 1.114515 / 1.452155 (-0.337639) | 1.147029 / 1.492716 (-0.345688) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.094925 / 0.018006 (0.076919) | 0.301548 / 0.000490 (0.301059) | 0.000211 / 0.000200 (0.000011) | 0.000043 / 0.000054 (-0.000011) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.018875 / 0.037411 (-0.018536) | 0.062824 / 0.014526 (0.048298) | 0.075657 / 0.176557 (-0.100900) | 0.121926 / 0.737135 (-0.615209) | 0.077102 / 0.296338 (-0.219236) |\n\n### Benchmark: benchmark_iterating.json\n\n| 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 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.286018 / 0.215209 (0.070808) | 2.832222 / 2.077655 (0.754567) | 1.462629 / 1.504120 (-0.041491) | 1.354746 / 1.541195 (-0.186449) | 1.339504 / 1.468490 (-0.128986) | 0.718381 / 4.584777 (-3.866396) | 2.401456 / 3.745712 (-1.344256) | 3.013518 / 5.269862 (-2.256343) | 1.944892 / 4.565676 (-2.620784) | 0.078793 / 0.424275 (-0.345482) | 0.005219 / 0.007607 (-0.002388) | 0.349551 / 0.226044 (0.123507) | 3.417844 / 2.268929 (1.148916) | 1.830669 / 55.444624 (-53.613956) | 1.502134 / 6.876477 (-5.374343) | 1.529242 / 2.142072 (-0.612830) | 0.793732 / 4.805227 (-4.011495) | 0.133571 / 6.500664 (-6.367093) | 0.042588 / 0.075469 (-0.032881) |\n\n### Benchmark: benchmark_map_filter.json\n\n| 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 |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.988167 / 1.841788 (-0.853620) | 11.926728 / 8.074308 (3.852420) | 9.806971 / 10.191392 (-0.384421) | 0.173951 / 0.680424 (-0.506473) | 0.015308 / 0.534201 (-0.518893) | 0.310768 / 0.579283 (-0.268515) | 0.268261 / 0.434364 (-0.166103) | 0.342962 / 0.540337 (-0.197375) | 0.431255 / 1.386936 (-0.955681) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| 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 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.005680 / 0.011353 (-0.005673) | 0.004231 / 0.011008 (-0.006778) | 0.051009 / 0.038508 (0.012501) | 0.031431 / 0.023109 (0.008322) | 0.268582 / 0.275898 (-0.007316) | 0.287942 / 0.323480 (-0.035538) | 0.004442 / 0.007986 (-0.003543) | 0.002818 / 0.004328 (-0.001511) | 0.050241 / 0.004250 (0.045991) | 0.039933 / 0.037052 (0.002881) | 0.285814 / 0.258489 (0.027325) | 0.316082 / 0.293841 (0.022241) | 0.032416 / 0.128546 (-0.096130) | 0.012398 / 0.075646 (-0.063248) | 0.060779 / 0.419271 (-0.358493) | 0.033706 / 0.043533 (-0.009827) | 0.273915 / 0.255139 (0.018776) | 0.289752 / 0.283200 (0.006553) | 0.017859 / 0.141683 (-0.123824) | 1.150224 / 1.452155 (-0.301930) | 1.197467 / 1.492716 (-0.295250) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.093810 / 0.018006 (0.075803) | 0.302529 / 0.000490 (0.302039) | 0.000221 / 0.000200 (0.000021) | 0.000047 / 0.000054 (-0.000008) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.022903 / 0.037411 (-0.014508) | 0.077445 / 0.014526 (0.062919) | 0.089335 / 0.176557 (-0.087222) | 0.130848 / 0.737135 (-0.606287) | 0.091106 / 0.296338 (-0.205232) |\n\n### Benchmark: benchmark_iterating.json\n\n| 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 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.294194 / 0.215209 (0.078985) | 2.886983 / 2.077655 (0.809328) | 1.557768 / 1.504120 (0.053648) | 1.424467 / 1.541195 (-0.116727) | 1.440625 / 1.468490 (-0.027865) | 0.724793 / 4.584777 (-3.859984) | 0.985216 / 3.745712 (-2.760496) | 2.856826 / 5.269862 (-2.413036) | 1.911638 / 4.565676 (-2.654039) | 0.080350 / 0.424275 (-0.343925) | 0.005616 / 0.007607 (-0.001991) | 0.348713 / 0.226044 (0.122668) | 3.414764 / 2.268929 (1.145835) | 1.925056 / 55.444624 (-53.519568) | 1.635752 / 6.876477 (-5.240725) | 1.761117 / 2.142072 (-0.380955) | 0.808309 / 4.805227 (-3.996918) | 0.136893 / 6.500664 (-6.363771) | 0.042116 / 0.075469 (-0.033354) |\n\n### Benchmark: benchmark_map_filter.json\n\n| 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 |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.004740 / 1.841788 (-0.837048) | 12.495859 / 8.074308 (4.421550) | 10.681233 / 10.191392 (0.489841) | 0.133320 / 0.680424 (-0.547104) | 0.015943 / 0.534201 (-0.518258) | 0.304869 / 0.579283 (-0.274414) | 0.128616 / 0.434364 (-0.305748) | 0.345930 / 0.540337 (-0.194407) | 0.457434 / 1.386936 (-0.929502) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#84d9dea52098c9403efb43d5b542dd6d45000bec \"CML watermark\")\n" ]
1,718,623,762,000
1,718,807,432,000
1,718,805,874,000
CONTRIBUTOR
null
0
{ "diff_url": "https://github.com/huggingface/datasets/pull/6976.diff", "html_url": "https://github.com/huggingface/datasets/pull/6976", "merged_at": "2024-06-19T14:04:34", "patch_url": "https://github.com/huggingface/datasets/pull/6976.patch", "url": "https://api.github.com/repos/huggingface/datasets/pulls/6976" }
Following the conversion guide, copy=False is no longer required and will result in an error: https://numpy.org/devdocs/numpy_2_0_migration_guide.html#adapting-to-changes-in-the-copy-keyword. The following fix should resolve the issue. error found during testing on the MTEB repository e.g. [here](https://github.com/embeddings-benchmark/mteb/pull/938)
{ "+1": 2, "-1": 0, "confused": 0, "eyes": 0, "heart": 0, "hooray": 0, "laugh": 0, "rocket": 0, "total_count": 2, "url": "https://api.github.com/repos/huggingface/datasets/issues/6976/reactions" }
https://api.github.com/repos/huggingface/datasets/issues/6976/timeline
null
null
true
End of preview.