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https://api.github.com/repos/huggingface/datasets/issues/1234 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1234/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1234/comments | https://api.github.com/repos/huggingface/datasets/issues/1234/events | https://github.com/huggingface/datasets/pull/1234 | 758,229,304 | MDExOlB1bGxSZXF1ZXN0NTMzNDM0ODkz | 1,234 | Added ade_corpus_v2, with 3 configs for relation extraction and classification task | {
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"@lhoestq I have added the tags they are in separate files for 3 different configs",
"@lhoestq thanks for the review I added your suggested changes.",
"merging since the CI is fixed on master"
] | 2020-12-07T07:05:14Z | 2020-12-14T17:49:14Z | 2020-12-14T17:49:14Z | CONTRIBUTOR | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/1311 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1311/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1311/comments | https://api.github.com/repos/huggingface/datasets/issues/1311/events | https://github.com/huggingface/datasets/pull/1311 | 759,514,819 | MDExOlB1bGxSZXF1ZXN0NTM0NTA3NjM1 | 1,311 | Add OPUS Bible Corpus (102 Languages) | {
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"@lhoestq done"
] | 2020-12-08T14:57:08Z | 2020-12-09T15:30:57Z | 2020-12-09T15:30:56Z | MEMBER | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/192 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/192/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/192/comments | https://api.github.com/repos/huggingface/datasets/issues/192/events | https://github.com/huggingface/datasets/issues/192 | 624,397,592 | MDU6SXNzdWU2MjQzOTc1OTI= | 192 | [Question] Create Apache Arrow dataset from raw text file | {
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"We store every dataset in the Arrow format. This is convenient as it supports nested types and memory mapping. If you are curious feel free to check the [pyarrow documentation](https://arrow.apache.org/docs/python/)\r\n\r\nYou can use this library to load your covid papers by creating a dataset script. You can fin... | 2020-05-25T16:42:47Z | 2021-12-18T01:45:34Z | 2020-10-27T15:20:22Z | CONTRIBUTOR | null | null | null | Hi guys, I have gathered and preprocessed about 2GB of COVID papers from CORD dataset @ Kggle. I have seen you have a text dataset as "Crime and punishment" in Apache arrow format. Do you have any script to do it from a raw txt file (preprocessed as for BERT like) or any guide?
Is the worth of send it to you and add it to the NLP library?
Thanks, Manu
| {
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https://api.github.com/repos/huggingface/datasets/issues/1318 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1318/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1318/comments | https://api.github.com/repos/huggingface/datasets/issues/1318/events | https://github.com/huggingface/datasets/pull/1318 | 759,565,629 | MDExOlB1bGxSZXF1ZXN0NTM0NTQ5NjE3 | 1,318 | ethos first commit | {
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"> Nice thanks !\r\n> \r\n> I left a few comments\r\n> \r\n> Also it looks like this PR includes changes about other files than the ones for ethos\r\n> \r\n> Can you create another branch and another PR please ?\r\n\r\n@lhoestq Should I close this PR? The new one is the: #1453",
"You can create another PR and clo... | 2020-12-08T15:59:47Z | 2020-12-10T14:45:57Z | 2020-12-10T14:45:57Z | CONTRIBUTOR | null | 0 | {
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} | Ethos passed all the tests except from this one:
RUN_SLOW=1 pytest tests/test_dataset_common.py::LocalDatasetTest::test_load_dataset_all_configs_<your-dataset-name>
with this error:
E OSError: Cannot find data file.
E Original error:
E [Errno 2] No such file or directory: | {
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https://api.github.com/repos/huggingface/datasets/issues/2380 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2380/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2380/comments | https://api.github.com/repos/huggingface/datasets/issues/2380/events | https://github.com/huggingface/datasets/pull/2380 | 895,367,201 | MDExOlB1bGxSZXF1ZXN0NjQ3NTk3NTc3 | 2,380 | maintain YAML structure reading from README | {
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} | How YAML used be loaded earlier in the string (structure of YAML was affected because of this and YAML for datasets with multiple configs was not being loaded correctly):
```
annotations_creators:
labeled_final:
- expert-generated
labeled_swap:
- expert-generated
unlabeled_final:
- machine-generated
language_creators:
- machine-generated
languages:
- en
licenses:
- other
multilinguality:
- monolingual
size_categories:
labeled_final:
- 10K<n<100K
labeled_swap:
- 10K<n<100K
unlabeled_final:
- 100K<n<1M
source_datasets:
- original
task_categories:
- text-classification
- text-scoring
task_ids:
- semantic-similarity-classification
- semantic-similarity-scoring
- text-scoring-other-paraphrase-identification
```
How YAML is loaded in string now:
```
annotations_creators:
labeled_final:
- expert-generated
labeled_swap:
- expert-generated
unlabeled_final:
- machine-generated
language_creators:
- machine-generated
languages:
- en
licenses:
- other
multilinguality:
- monolingual
size_categories:
labeled_final:
- 10K<n<100K
labeled_swap:
- 10K<n<100K
unlabeled_final:
- 100K<n<1M
source_datasets:
- original
task_categories:
- text-classification
- text-scoring
task_ids:
- semantic-similarity-classification
- semantic-similarity-scoring
- text-scoring-other-paraphrase-identification
``` | {
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"Google's version of WIT is now available here: https://huggingface.co/datasets/google/wit"
] | 2021-08-16T19:34:09Z | 2022-05-06T12:27:29Z | 2022-05-06T12:26:16Z | NONE | null | 1 | {
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https://api.github.com/repos/huggingface/datasets/issues/6318 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6318/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6318/comments | https://api.github.com/repos/huggingface/datasets/issues/6318/events | https://github.com/huggingface/datasets/pull/6318 | 1,952,100,706 | PR_kwDODunzps5dRC9V | 6,318 | Deterministic set hash | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"<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 | rea... | 2023-10-19T12:19:13Z | 2023-10-19T16:27:20Z | 2023-10-19T16:16:31Z | MEMBER | null | 0 | {
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} | Sort the items in a set according to their `datasets.fingerprint.Hasher.hash` hash to get a deterministic hash of sets.
This is useful to get deterministic hashes of tokenizers that use a trie based on python sets.
reported in https://github.com/huggingface/datasets/issues/3847 | {
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https://api.github.com/repos/huggingface/datasets/issues/4690 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4690/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4690/comments | https://api.github.com/repos/huggingface/datasets/issues/4690/events | https://github.com/huggingface/datasets/pull/4690 | 1,306,321,975 | PR_kwDODunzps47fG6w | 4,690 | Refactor base extractors | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-07-15T17:47:48Z | 2022-07-18T08:46:56Z | 2022-07-18T08:34:49Z | MEMBER | null | 0 | {
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} | This PR:
- Refactors base extractors as subclasses of `BaseExtractor`:
- this is an abstract class defining the interface with:
- `is_extractable`: abstract class method
- `extract`: abstract static method
- Implements abstract `MagicNumberBaseExtractor` (as subclass of `BaseExtractor`):
- this has a default implementation of `is_extractable`
- this improves performance (reducing the number of file reads) by allowing passing already read `magic_number`
- Refactors `Extractor`:
- reads magic number from file only once
This PR deprecates:
```python
is_extractable, extractor = self.extractor.is_extractable(input_path, return_extractor=True)
self.extractor.extract(input_path, output_path, extractor=extractor)
```
and uses more Pythonic instead:
```python
extractor_format = self.extractor.infer_extractor_format(input_path)
self.extractor.extract(input_path, output_path, extractor_format)
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/4568 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4568/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4568/comments | https://api.github.com/repos/huggingface/datasets/issues/4568/events | https://github.com/huggingface/datasets/issues/4568 | 1,284,655,624 | I_kwDODunzps5MkkoI | 4,568 | XNLI cache reload is very slow | {
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"Hi,\r\nCould you tell us how you are running this code?\r\nI tested on my machine (M1 Mac). And it is running fine both on and off internet.\r\n\r\n<img width=\"1033\" alt=\"Screen Shot 2022-07-03 at 1 32 25 AM\" src=\"https://user-images.githubusercontent.com/8711912/177026364-4ad7cedb-e524-4513-97f7-7961bbb34c90... | 2022-06-25T16:43:56Z | 2022-07-04T14:29:40Z | 2022-07-04T14:29:40Z | CONTRIBUTOR | null | null | null | ### Reproduce
Using `2.3.3.dev0`
`from datasets import load_dataset`
`load_dataset("xnli", "en")`
Turn off Internet
`load_dataset("xnli", "en")`
I cancelled the second `load_dataset` eventually cuz it took super long. It would be great to have something to specify e.g. `only_load_from_cache` and avoid the library trying to download when there is no Internet. If I leave it running it works but takes way longer than when there is Internet. I would expect loading from cache to take the same amount of time regardless of whether there is Internet.
```
---------------------------------------------------------------------------
gaierror Traceback (most recent call last)
/opt/conda/lib/python3.7/site-packages/urllib3/connection.py in _new_conn(self)
174 conn = connection.create_connection(
--> 175 (self._dns_host, self.port), self.timeout, **extra_kw
176 )
/opt/conda/lib/python3.7/site-packages/urllib3/util/connection.py in create_connection(address, timeout, source_address, socket_options)
71
---> 72 for res in socket.getaddrinfo(host, port, family, socket.SOCK_STREAM):
73 af, socktype, proto, canonname, sa = res
/opt/conda/lib/python3.7/socket.py in getaddrinfo(host, port, family, type, proto, flags)
751 addrlist = []
--> 752 for res in _socket.getaddrinfo(host, port, family, type, proto, flags):
753 af, socktype, proto, canonname, sa = res
gaierror: [Errno -3] Temporary failure in name resolution
During handling of the above exception, another exception occurred:
KeyboardInterrupt Traceback (most recent call last)
/tmp/ipykernel_33/3594208039.py in <module>
----> 1 load_dataset("xnli", "en")
/opt/conda/lib/python3.7/site-packages/datasets/load.py in load_dataset(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, ignore_verifications, keep_in_memory, save_infos, revision, use_auth_token, task, streaming, **config_kwargs)
1673 revision=revision,
1674 use_auth_token=use_auth_token,
-> 1675 **config_kwargs,
1676 )
1677
/opt/conda/lib/python3.7/site-packages/datasets/load.py in load_dataset_builder(path, name, data_dir, data_files, cache_dir, features, download_config, download_mode, revision, use_auth_token, **config_kwargs)
1494 download_mode=download_mode,
1495 data_dir=data_dir,
-> 1496 data_files=data_files,
1497 )
1498
/opt/conda/lib/python3.7/site-packages/datasets/load.py in dataset_module_factory(path, revision, download_config, download_mode, force_local_path, dynamic_modules_path, data_dir, data_files, **download_kwargs)
1182 download_config=download_config,
1183 download_mode=download_mode,
-> 1184 dynamic_modules_path=dynamic_modules_path,
1185 ).get_module()
1186 elif path.count("/") == 1: # community dataset on the Hub
/opt/conda/lib/python3.7/site-packages/datasets/load.py in __init__(self, name, revision, download_config, download_mode, dynamic_modules_path)
506 self.dynamic_modules_path = dynamic_modules_path
507 assert self.name.count("/") == 0
--> 508 increase_load_count(name, resource_type="dataset")
509
510 def download_loading_script(self, revision: Optional[str]) -> str:
/opt/conda/lib/python3.7/site-packages/datasets/load.py in increase_load_count(name, resource_type)
166 if not config.HF_DATASETS_OFFLINE and config.HF_UPDATE_DOWNLOAD_COUNTS:
167 try:
--> 168 head_hf_s3(name, filename=name + ".py", dataset=(resource_type == "dataset"))
169 except Exception:
170 pass
/opt/conda/lib/python3.7/site-packages/datasets/utils/file_utils.py in head_hf_s3(identifier, filename, use_cdn, dataset, max_retries)
93 return http_head(
94 hf_bucket_url(identifier=identifier, filename=filename, use_cdn=use_cdn, dataset=dataset),
---> 95 max_retries=max_retries,
96 )
97
/opt/conda/lib/python3.7/site-packages/datasets/utils/file_utils.py in http_head(url, proxies, headers, cookies, allow_redirects, timeout, max_retries)
445 allow_redirects=allow_redirects,
446 timeout=timeout,
--> 447 max_retries=max_retries,
448 )
449 return response
/opt/conda/lib/python3.7/site-packages/datasets/utils/file_utils.py in _request_with_retry(method, url, max_retries, base_wait_time, max_wait_time, timeout, **params)
366 tries += 1
367 try:
--> 368 response = requests.request(method=method.upper(), url=url, timeout=timeout, **params)
369 success = True
370 except (requests.exceptions.ConnectTimeout, requests.exceptions.ConnectionError) as err:
/opt/conda/lib/python3.7/site-packages/requests/api.py in request(method, url, **kwargs)
59 # cases, and look like a memory leak in others.
60 with sessions.Session() as session:
---> 61 return session.request(method=method, url=url, **kwargs)
62
63
/opt/conda/lib/python3.7/site-packages/requests/sessions.py in request(self, method, url, params, data, headers, cookies, files, auth, timeout, allow_redirects, proxies, hooks, stream, verify, cert, json)
527 }
528 send_kwargs.update(settings)
--> 529 resp = self.send(prep, **send_kwargs)
530
531 return resp
/opt/conda/lib/python3.7/site-packages/requests/sessions.py in send(self, request, **kwargs)
643
644 # Send the request
--> 645 r = adapter.send(request, **kwargs)
646
647 # Total elapsed time of the request (approximately)
/opt/conda/lib/python3.7/site-packages/requests/adapters.py in send(self, request, stream, timeout, verify, cert, proxies)
448 decode_content=False,
449 retries=self.max_retries,
--> 450 timeout=timeout
451 )
452
/opt/conda/lib/python3.7/site-packages/urllib3/connectionpool.py in urlopen(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, **response_kw)
708 body=body,
709 headers=headers,
--> 710 chunked=chunked,
711 )
712
/opt/conda/lib/python3.7/site-packages/urllib3/connectionpool.py in _make_request(self, conn, method, url, timeout, chunked, **httplib_request_kw)
384 # Trigger any extra validation we need to do.
385 try:
--> 386 self._validate_conn(conn)
387 except (SocketTimeout, BaseSSLError) as e:
388 # Py2 raises this as a BaseSSLError, Py3 raises it as socket timeout.
/opt/conda/lib/python3.7/site-packages/urllib3/connectionpool.py in _validate_conn(self, conn)
1038 # Force connect early to allow us to validate the connection.
1039 if not getattr(conn, "sock", None): # AppEngine might not have `.sock`
-> 1040 conn.connect()
1041
1042 if not conn.is_verified:
/opt/conda/lib/python3.7/site-packages/urllib3/connection.py in connect(self)
356 def connect(self):
357 # Add certificate verification
--> 358 self.sock = conn = self._new_conn()
359 hostname = self.host
360 tls_in_tls = False
/opt/conda/lib/python3.7/site-packages/urllib3/connection.py in _new_conn(self)
173 try:
174 conn = connection.create_connection(
--> 175 (self._dns_host, self.port), self.timeout, **extra_kw
176 )
177
KeyboardInterrupt:
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/4827 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4827/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4827/comments | https://api.github.com/repos/huggingface/datasets/issues/4827/events | https://github.com/huggingface/datasets/pull/4827 | 1,335,994,312 | PR_kwDODunzps49B1zi | 4,827 | Add license metadata to pg19 | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-08-11T13:52:20Z | 2022-08-11T15:01:03Z | 2022-08-11T14:46:38Z | MEMBER | null | 0 | {
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} | As reported over email by Roy Rijkers | {
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https://api.github.com/repos/huggingface/datasets/issues/2801 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2801/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2801/comments | https://api.github.com/repos/huggingface/datasets/issues/2801/events | https://github.com/huggingface/datasets/pull/2801 | 970,844,617 | MDExOlB1bGxSZXF1ZXN0NzEyNzMwODEz | 2,801 | add books3 | {
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"> When I was creating dataset card. I found there is room for creating / editing dataset card. I've made it an issue. #2797\r\n\r\nThanks for the message, we'll definitely improve this\r\n\r\n> Also I am wondering whether the import of The Pile dataset is actively undertaken (because I may need it recently)? #1675... | 2021-08-14T07:04:25Z | 2021-08-19T16:43:09Z | 2021-08-18T15:36:59Z | CONTRIBUTOR | null | 0 | {
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} | books3 is part of EleutherAI/The Pile, but AFAIK, The Pile dataset blend all sub datasets together thus we are not able to use just one of its sub dataset from The Pile data. So I create an independent dataset using The Pile preliminary components.
When I was creating dataset card. I found there is room for creating / editing dataset card. I've made it an issue. #2797
Also I am wondering whether the import of The Pile dataset is actively undertaken (because I may need it recently)? #1675 | {
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https://api.github.com/repos/huggingface/datasets/issues/5438 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5438/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5438/comments | https://api.github.com/repos/huggingface/datasets/issues/5438/events | https://github.com/huggingface/datasets/pull/5438 | 1,537,489,730 | PR_kwDODunzps5HmWA8 | 5,438 | Update actions/checkout in CD Conda release | {
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"_The documentation is not available anymore as the PR was closed or merged._",
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https://api.github.com/repos/huggingface/datasets/issues/254 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/254/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/254/comments | https://api.github.com/repos/huggingface/datasets/issues/254/events | https://github.com/huggingface/datasets/issues/254 | 635,057,568 | MDU6SXNzdWU2MzUwNTc1Njg= | 254 | [Feature request] Be able to remove a specific sample of the dataset | {
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"Oh yes you can now do that with the `dataset.filter()` method that was added in #214 "
] | 2020-06-09T02:22:13Z | 2020-06-09T08:41:38Z | 2020-06-09T08:41:38Z | NONE | null | null | null | As mentioned in #117, it's currently not possible to remove a sample of the dataset.
But it is a important use case : After applying some preprocessing, some samples might be empty for example. We should be able to remove these samples from the dataset, or at least mark them as `removed` so when iterating the dataset, we don't iterate these samples.
I think it should be a feature. What do you think ?
---
Any work-around in the meantime ? | {
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https://api.github.com/repos/huggingface/datasets/issues/6420 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6420/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6420/comments | https://api.github.com/repos/huggingface/datasets/issues/6420/events | https://github.com/huggingface/datasets/pull/6420 | 1,994,278,903 | PR_kwDODunzps5ffhdi | 6,420 | Set dev version | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6420). All of your documentation changes will be reflected on that endpoint.",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchma... | 2023-11-15T08:22:19Z | 2023-11-15T08:33:36Z | 2023-11-15T08:22:33Z | MEMBER | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/5473 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5473/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5473/comments | https://api.github.com/repos/huggingface/datasets/issues/5473/events | https://github.com/huggingface/datasets/pull/5473 | 1,558,668,197 | PR_kwDODunzps5Inm9h | 5,473 | Set dev version | {
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https://api.github.com/repos/huggingface/datasets/issues/2101 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2101/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2101/comments | https://api.github.com/repos/huggingface/datasets/issues/2101/events | https://github.com/huggingface/datasets/pull/2101 | 838,586,184 | MDExOlB1bGxSZXF1ZXN0NTk4NzQzMDM4 | 2,101 | MIAM dataset - new citation details | {
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"Hi !\r\nLooks like there's a unicode error in the new citation in the miam.py file.\r\nCould you try to fix it ? Not sure from which character it comes from though\r\n\r\nYou can test if it works on your side with\r\n```\r\nRUN_SLOW=1 pytest tests/test_dataset_common.py::LocalDatasetTest::test_load_dataset_all_con... | 2021-03-23T10:41:23Z | 2021-03-23T18:08:10Z | 2021-03-23T18:08:10Z | CONTRIBUTOR | null | 0 | {
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} | Hi @lhoestq, I have updated the citations to reference an OpenReview preprint. | {
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https://api.github.com/repos/huggingface/datasets/issues/4765 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4765/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4765/comments | https://api.github.com/repos/huggingface/datasets/issues/4765/events | https://github.com/huggingface/datasets/pull/4765 | 1,321,787,428 | PR_kwDODunzps48S2rM | 4,765 | Fix version in map_nested docstring | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-07-29T05:44:32Z | 2022-07-29T11:51:25Z | 2022-07-29T11:38:36Z | MEMBER | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/5092 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5092/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5092/comments | https://api.github.com/repos/huggingface/datasets/issues/5092/events | https://github.com/huggingface/datasets/pull/5092 | 1,402,713,517 | PR_kwDODunzps5AeIsS | 5,092 | Use HTML relative paths for tiles in the docs | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"> Good catch, @lewtun. Thanks for the fix.\r\n> \r\n> Do you know if there are other absolute paths in the docs that should be fixed as well?\r\n\r\nI found a few more in [0d4796b](https://github.com/huggingface/datasets/pull/5092/co... | 2022-10-10T07:24:27Z | 2022-10-11T13:25:45Z | 2022-10-11T13:23:23Z | MEMBER | null | 0 | {
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} | This PR replaces the absolute paths in the landing page tiles with relative ones so that one can test navigation both locally in and in future PRs (see [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_5084/en/index) for an example PR where the links don't work).
I encountered this while working on the `optimum` docs and figured I'd fix it elsewhere too :)
Internal Slack thread: https://huggingface.slack.com/archives/C02GLJ5S0E9/p1665129710176619 | {
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https://api.github.com/repos/huggingface/datasets/issues/2871 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2871/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2871/comments | https://api.github.com/repos/huggingface/datasets/issues/2871/events | https://github.com/huggingface/datasets/issues/2871 | 989,436,088 | MDU6SXNzdWU5ODk0MzYwODg= | 2,871 | datasets.config.PYARROW_VERSION has no attribute 'major' | {
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"I have changed line 288 to `if int(datasets.config.PYARROW_VERSION.split(\".\")[0]) < 3:` just to get around it.",
"Hi @bwang482,\r\n\r\nI'm sorry but I'm not able to reproduce your bug.\r\n\r\nPlease note that in our current master branch, we made a commit (d03223d4d64b89e76b48b00602aba5aa2f817f1e) that simulta... | 2021-09-06T21:06:57Z | 2021-09-08T08:51:52Z | 2021-09-08T08:51:52Z | CONTRIBUTOR | null | null | null | In the test_dataset_common.py script, line 288-289
```
if datasets.config.PYARROW_VERSION.major < 3:
packaged_datasets = [pd for pd in packaged_datasets if pd["dataset_name"] != "parquet"]
```
which throws the error below. `datasets.config.PYARROW_VERSION` itself return the string '4.0.1'. I have tested this on both datasets.__version_=='1.11.0' and '1.9.0'. I am using Mac OS.
```
import datasets
datasets.config.PYARROW_VERSION.major
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
/var/folders/1f/0wqmlgp90qjd5mpj53fnjq440000gn/T/ipykernel_73361/2547517336.py in <module>
1 import datasets
----> 2 datasets.config.PYARROW_VERSION.major
AttributeError: 'str' object has no attribute 'major'
```
## Environment info
- `datasets` version: 1.11.0
- Platform: Darwin-20.6.0-x86_64-i386-64bit
- Python version: 3.7.11
- PyArrow version: 4.0.1
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https://api.github.com/repos/huggingface/datasets/issues/5285 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5285/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5285/comments | https://api.github.com/repos/huggingface/datasets/issues/5285/events | https://github.com/huggingface/datasets/pull/5285 | 1,461,521,215 | PR_kwDODunzps5DjLgG | 5,285 | Save file name in embed_storage | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"I updated the tests, met le know if it sounds good to you now :)"
] | 2022-11-23T10:55:54Z | 2022-11-24T14:11:41Z | 2022-11-24T14:08:37Z | MEMBER | null | 0 | {
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} | Having the file name is useful in case we need to check the extension of the file (e.g. mp3), or in general in case it includes some metadata information (track id, image id etc.)
Related to https://github.com/huggingface/datasets/issues/5276 | {
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https://api.github.com/repos/huggingface/datasets/issues/4630 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4630/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4630/comments | https://api.github.com/repos/huggingface/datasets/issues/4630/events | https://github.com/huggingface/datasets/pull/4630 | 1,293,470,728 | PR_kwDODunzps460HFM | 4,630 | fix(dataset_wrappers): Fixes access to fsspec.asyn in torch_iterable_dataset.py. | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-07-04T18:26:55Z | 2022-07-05T15:19:52Z | 2022-07-05T15:08:21Z | CONTRIBUTOR | null | 0 | {
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} | Fix #4612.
Apparently, newest `fsspec` versions do not allow access to attribute-based modules if they are not imported, such as `fsspec.async`.
Thus, @mariosasko suggested to add the missing part to the module import to allow for its access. | {
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https://api.github.com/repos/huggingface/datasets/issues/3716 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3716/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3716/comments | https://api.github.com/repos/huggingface/datasets/issues/3716/events | https://github.com/huggingface/datasets/issues/3716 | 1,136,831,092 | I_kwDODunzps5Dwqp0 | 3,716 | `FaissIndex` to support multiple GPU and `custom_index` | {
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"Hi @rentruewang, thansk for reporting and for your PR!!! We should definitely support this. ",
"@albertvillanova Great! :)"
] | 2022-02-14T06:21:43Z | 2022-03-07T16:28:56Z | 2022-03-07T16:28:56Z | CONTRIBUTOR | null | null | null | **Is your feature request related to a problem? Please describe.**
Currently, because `device` is of the type `int | None`, to leverage `faiss-gpu`'s multi-gpu support, you need to create a `custom_index`. However, if using a `custom_index` created by e.g. `faiss.index_cpu_to_all_gpus`, then `FaissIndex.save` does not work properly because it checks the device id (which is an int, so no multiple GPUs).
**Describe the solution you'd like**
I would like `FaissIndex` to support multiple GPUs, by passing in a list to `add_faiss_index`.
**Describe alternatives you've considered**
Alternatively, I would like it to at least provide a warning cause it wasn't the behavior that I expected.
**Additional context**
Relavent source code here:
https://github.com/huggingface/datasets/blob/6ed6ac9448311930557810383d2cfd4fe6aae269/src/datasets/search.py#L340-L349
Device management needs changing to support multiple GPUs, probably by `isinstance` calls.
I can provide a PR if you like :)
Thanks for reading!
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"We want to keep the repo as light as possible so that it doesn't take ages to clone, that's why we ask for small dummy data files (especially when there are many of them). Let me know if you have questions or if we can help you on this",
"Hello @lhoestq , made the changes as you suggested and pushed, please revi... | 2020-12-09T18:42:58Z | 2020-12-13T19:11:18Z | 2020-12-13T19:11:18Z | CONTRIBUTOR | null | 0 | {
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} | Most parts of the "Dataset Structure" section can be generated automatically. This PR adds some code to do so. | {
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} | As noticed in #900 the cache_dir parameter was not followed to the downloader in the case of an already processed dataset hosted on our google storage (one of them is natural questions).
Fix #900 | {
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"For each dataset, If there exist a `dataset_info.json`, then the command `nlp-cli test path/to/my/dataset --al_configs` is successful only if the `dataset_infos.json` is correct. The infos are correct if the size and checksums of the downloaded file are correct, and if the number of examples in each split are corr... | 2020-05-15T09:12:25Z | 2020-05-15T10:06:12Z | 2020-05-15T10:03:26Z | MEMBER | null | 0 | {
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} | ## Change default Test from local => aws
As a default we set` aws=True`, `Local=False`, `slow=False`
### 1. RUN_AWS=1 (default)
This runs 4 tests per dataset script.
a) Does the dataset script have a valid etag / Can it be reached on AWS?
b) Can we load its `builder_class`?
c) Can we load **all** dataset configs?
d) _Most importantly_: Can we load the dataset?
Important - we currently only test the first config of each dataset to reduce test time. Total test time is around 1min20s.
### 2. RUN_LOCAL=1 RUN_AWS=0
***This should be done when debugging dataset scripts of the ./datasets folder***
This only runs 1 test per dataset test, which is equivalent to aws d) - Can we load the dataset from the local `datasets` directory?
### 3. RUN_SLOW=1
We should set up to run these tests maybe 1 time per week ? @thomwolf
The `slow` tests include two more important tests.
e) Can we load the dataset with all possible configs? This test will probably fail at the moment because a lot of dummy data is missing. We should add the dummy data step by step to be sure that all configs work.
f) Test that the actual dataset can be loaded. This will take quite some time to run, but is important to make sure that the "real" data can be loaded. It will also test whether the dataset script has the correct checksums file which is currently not tested with `aws=True`. @lhoestq - is there an easy way to check cheaply whether the `dataset_info.json` is correct for each dataset script? | {
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https://api.github.com/repos/huggingface/datasets/issues/2998 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2998/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2998/comments | https://api.github.com/repos/huggingface/datasets/issues/2998/events | https://github.com/huggingface/datasets/issues/2998 | 1,013,372,871 | I_kwDODunzps48ZtfH | 2,998 | cannot shuffle dataset loaded from disk | {
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] | open | false | null | [] | null | [] | 2021-10-01T13:49:52Z | 2021-10-01T13:49:52Z | null | NONE | null | null | null | ## Describe the bug
dataset loaded from disk cannot be shuffled.
## Steps to reproduce the bug
```
my_dataset = load_from_disk('s3://my_file/validate', fs=s3)
sample = my_dataset.select(range(100)).shuffle(seed=1234)
```
## Actual results
```
sample = my_dataset .select(range(100)).shuffle(seed=1234)
File "/home/ubuntu/anaconda3/envs/pytorch_p37/lib/python3.7/site-packages/datasets/arrow_dataset.py", line 185, in wrapper
out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs)
File "/home/ubuntu/anaconda3/envs/pytorch_p37/lib/python3.7/site-packages/datasets/fingerprint.py", line 398, in wrapper
out = func(self, *args, **kwargs)
File "/home/ubuntu/anaconda3/envs/pytorch_p37/lib/python3.7/site-packages/datasets/arrow_dataset.py", line 2494, in shuffle
new_fingerprint=new_fingerprint,
File "/home/ubuntu/anaconda3/envs/pytorch_p37/lib/python3.7/site-packages/datasets/arrow_dataset.py", line 185, in wrapper
out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs)
File "/home/ubuntu/anaconda3/envs/pytorch_p37/lib/python3.7/site-packages/datasets/fingerprint.py", line 398, in wrapper
out = func(self, *args, **kwargs)
File "/home/ubuntu/anaconda3/envs/pytorch_p37/lib/python3.7/site-packages/datasets/arrow_dataset.py", line 2303, in select
tmp_file = tempfile.NamedTemporaryFile("wb", dir=os.path.dirname(indices_cache_file_name), delete=False)
File "/home/ubuntu/anaconda3/envs/pytorch_p37/lib/python3.7/tempfile.py", line 547, in NamedTemporaryFile
(fd, name) = _mkstemp_inner(dir, prefix, suffix, flags, output_type)
File "/home/ubuntu/anaconda3/envs/pytorch_p37/lib/python3.7/tempfile.py", line 258, in _mkstemp_inner
fd = _os.open(file, flags, 0o600)
FileNotFoundError: [Errno 2] No such file or directory: '/tmp/tmpnnu5uhnx/my_file/validate/tmpy76d70g4'
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.12.1
- Python version: 3.7
- PyArrow version: 5.0.0
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https://api.github.com/repos/huggingface/datasets/issues/1063 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1063/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1063/comments | https://api.github.com/repos/huggingface/datasets/issues/1063/events | https://github.com/huggingface/datasets/pull/1063 | 756,376,374 | MDExOlB1bGxSZXF1ZXN0NTMxOTMxMTMz | 1,063 | Add the Ud treebank | {
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"merging since the CI is fixed on master"
] | 2020-12-03T16:56:41Z | 2020-12-04T16:11:54Z | 2020-12-04T15:51:46Z | CONTRIBUTOR | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/3001 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3001/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3001/comments | https://api.github.com/repos/huggingface/datasets/issues/3001/events | https://github.com/huggingface/datasets/pull/3001 | 1,014,024,982 | PR_kwDODunzps4sl0BY | 3,001 | Fix cast to Python scalar in Matthews Correlation metric | {
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} | This PR is motivated by issue #2964.
The Matthews Correlation metric relies on sklearn's `matthews_corrcoef` function to compute the result. This function returns either `float` or `np.float64` (see the [source](https://github.com/scikit-learn/scikit-learn/blob/844b4be24d20fc42cc13b957374c718956a0db39/sklearn/metrics/_classification.py#L906-L909)). Obviously, calling `.item()` on the float value will fail, so I'm fixing this with the built-in `float()` function, which covers both cases. Surprisingly, on my machine, casting `np.float64` to a Python scalar with `float()` is even faster than with the `.item()` method. | {
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"+1 \r\n```\r\nFound cached dataset csv (file:///home/ubuntu/.cache/huggingface/datasets/theSquarePond___csv/theSquarePond--XXXXX-bbf0a8365d693d2c/0.0.0/eea64c71ca8b46dd3f537ed218fc9bf495d5707789152eb2764f5c78fa66d59d)\r\n---------------------------------------------------------------------------\r\nNotImplementedE... | 2023-10-25T21:55:31Z | 2023-11-07T07:26:54Z | 2023-11-07T07:26:54Z | NONE | null | null | null | I was trying to load the wiki dataset, but i got this error
traindata = load_dataset('wikitext', 'wikitext-2-raw-v1', split='train')
File "/home/aelkordy/.conda/envs/prune_llm/lib/python3.9/site-packages/datasets/load.py", line 1804, in load_dataset
ds = builder_instance.as_dataset(split=split, verification_mode=verification_mode, in_memory=keep_in_memory)
File "/home/aelkordy/.conda/envs/prune_llm/lib/python3.9/site-packages/datasets/builder.py", line 1108, in as_dataset
raise NotImplementedError(f"Loading a dataset cached in a {type(self._fs).__name__} is not supported.")
NotImplementedError: Loading a dataset cached in a LocalFileSystem is not supported. | {
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https://api.github.com/repos/huggingface/datasets/issues/504 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/504/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/504/comments | https://api.github.com/repos/huggingface/datasets/issues/504/events | https://github.com/huggingface/datasets/pull/504 | 678,756,211 | MDExOlB1bGxSZXF1ZXN0NDY3NjUxOTA5 | 504 | Added downloading to Hyperpartisan news detection | {
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"Thank you @ghomasHudson for making our dataset available! This is great!",
"The test passes since #527 :)"
] | 2020-08-13T21:53:46Z | 2020-08-27T08:18:41Z | 2020-08-27T08:18:41Z | CONTRIBUTOR | null | 0 | {
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} | Following the discussion on Slack and #349, I've updated the hyperpartisan dataset to pull directly from Zenodo rather than manual install, which should make this dataset much more accessible. Many thanks to @johanneskiesel !
Currently doesn't pass `test_load_real_dataset` - I'm using `self.config.name` which is `default` in this test. Might be related to #474 | {
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"LGTM, don't forget the tags ;)"
] | 2020-12-01T05:02:11Z | 2020-12-04T09:29:40Z | 2020-12-01T07:25:53Z | CONTRIBUTOR | null | 0 | {
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} | The dataset was added in #1761 but not in the right directory. I'm moving it to /datasets | {
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https://api.github.com/repos/huggingface/datasets/issues/1565 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1565/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1565/comments | https://api.github.com/repos/huggingface/datasets/issues/1565/events | https://github.com/huggingface/datasets/pull/1565 | 766,333,940 | MDExOlB1bGxSZXF1ZXN0NTM5Mzg2MzEx | 1,565 | Create README.md | {
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"@ManuelFay thanks you so much for adding a dataset card, this is such a cool contribution!\r\n\r\nThis looks like it uses an old template for the card we've moved things around a bit and we have an app you should be using to get the tags and the structure of the Data Fields paragraph :) Would you mind moving your ... | 2020-12-14T11:40:23Z | 2021-03-25T14:01:49Z | 2021-03-25T14:01:49Z | CONTRIBUTOR | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/6114 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6114/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6114/comments | https://api.github.com/repos/huggingface/datasets/issues/6114/events | https://github.com/huggingface/datasets/issues/6114 | 1,834,015,584 | I_kwDODunzps5tUNtg | 6,114 | Cache not being used when loading commonvoice 8.0.0 | {
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"You can avoid this by using the `revision` parameter in `load_dataset` to always force downloading a specific commit (if not specified it defaults to HEAD, hence the redownload).",
"Thanks @mariosasko this works well, looks like I should have read the documentation a bit more carefully. \r\n\r\nIt is still a bi... | 2023-08-02T23:18:11Z | 2023-08-18T23:59:00Z | 2023-08-18T23:59:00Z | NONE | null | null | null | ### Describe the bug
I have commonvoice 8.0.0 downloaded in `~/.cache/huggingface/datasets/mozilla-foundation___common_voice_8_0/en/8.0.0/b2f8b72f8f30b2e98c41ccf855954d9e35a5fa498c43332df198534ff9797a4a`. The folder contains all the arrow files etc, and was used as the cached version last time I touched the ec2 instance I'm working on. Now, with the same command that downloaded it initially:
```
dataset = load_dataset("mozilla-foundation/common_voice_8_0", "en", use_auth_token="<mytoken>")
```
it tries to redownload the dataset to `~/.cache/huggingface/datasets/mozilla-foundation___common_voice_8_0/en/8.0.0/05bdc7940b0a336ceeaeef13470c89522c29a8e4494cbeece64fb472a87acb32`
### Steps to reproduce the bug
Steps to reproduce the behavior:
1. ```dataset = load_dataset("mozilla-foundation/common_voice_8_0", "en", use_auth_token="<mytoken>")```
2. dataset is updated by maintainers
3. ```dataset = load_dataset("mozilla-foundation/common_voice_8_0", "en", use_auth_token="<mytoken>")```
### Expected behavior
I expect that it uses the already downloaded data in `~/.cache/huggingface/datasets/mozilla-foundation___common_voice_8_0/en/8.0.0/b2f8b72f8f30b2e98c41ccf855954d9e35a5fa498c43332df198534ff9797a4a`.
Not sure what's happening in 2. but if, say it's an issue with the dataset referenced by "mozilla-foundation/common_voice_8_0" being modified by the maintainers, how would I force datasets to point to the original version I downloaded?
EDIT: It was indeed that the maintainers had updated the dataset (v 8.0.0). However I still cant load the dataset from disk instead of redownloading, with for example:
```
load_dataset(".cache/huggingface/datasets/downloads/extracted/<hash>/cv-corpus-8.0-2022-01-19/en/", "en")
> ...
> File [~/miniconda3/envs/aa_torch2/lib/python3.10/site-packages/datasets/table.py:1938](.../ python3.10/site-packages/datasets/table.py:1938), in cast_array_to_feature(array, feature, allow_number_to_str)
1937 elif not isinstance(feature, (Sequence, dict, list, tuple)):
-> 1938 return array_cast(array, feature(), allow_number_to_str=allow_number_to_str)
...
1794 e = e.__context__
-> 1795 raise DatasetGenerationError("An error occurred while generating the dataset") from e
1797 yield job_id, True, (total_num_examples, total_num_bytes, writer._features, num_shards, shard_lengths)
DatasetGenerationError: An error occurred while generating the dataset
```
### Environment info
datasets==2.7.0
python==3.10.8
OS: AWS Linux | {
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https://api.github.com/repos/huggingface/datasets/issues/6170 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6170/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6170/comments | https://api.github.com/repos/huggingface/datasets/issues/6170/events | https://github.com/huggingface/datasets/pull/6170 | 1,862,705,731 | PR_kwDODunzps5YkJOV | 6,170 | feat: Return the name of the currently loaded file | {
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"Your change adds a new element in the key used to avoid duplicates when generating the examples of a dataset. I don't think it fixes the issue you're trying to solve."
] | 2023-08-23T07:08:17Z | 2023-08-29T12:41:05Z | null | NONE | null | 0 | {
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} | Added an optional parameter return_file_name in the load_dataset function. When it is set to True, the function will include the name of the file corresponding to the current line as a feature in the returned output.
I added this here https://github.com/huggingface/datasets/blob/main/src/datasets/packaged_modules/json/json.py#L92.
fixes #5806 | {
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https://api.github.com/repos/huggingface/datasets/issues/6057 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6057/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6057/comments | https://api.github.com/repos/huggingface/datasets/issues/6057/events | https://github.com/huggingface/datasets/issues/6057 | 1,815,100,151 | I_kwDODunzps5sMDr3 | 6,057 | Why is the speed difference of gen example so big? | {
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"Hi!\r\n\r\nIt's hard to explain this behavior without more information. Can you profile the slower version with the following code\r\n```python\r\nimport cProfile, pstats\r\nfrom datasets import load_dataset\r\n\r\nwith cProfile.Profile() as profiler:\r\n ds = load_dataset(...)\r\n\r\nstats = pstats.Stats(profi... | 2023-07-21T03:34:49Z | 2023-10-04T18:06:16Z | 2023-10-04T18:06:15Z | NONE | null | null | null | ```python
def _generate_examples(self, metadata_path, images_dir, conditioning_images_dir):
with open(metadata_path, 'r') as file:
metadata = json.load(file)
for idx, item in enumerate(metadata):
image_path = item.get('image_path')
text_content = item.get('text_content')
image_data = open(image_path, "rb").read()
yield idx, {
"text": text_content,
"image": {
"path": image_path,
"bytes": image_data,
},
"conditioning_image": {
"path": image_path,
"bytes": image_data,
},
}
```
Hello,
I use the above function to deal with my local data set, but I am very surprised that the speed at which I generate example is very different. When I start a training task, **sometimes 1000examples/s, sometimes only 10examples/s.**
I'm not saying that speed is changing all the time. I mean, the reading speed is different in different training, which will cause me to start training over and over again until the speed of this generation of examples is normal.
| {
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https://api.github.com/repos/huggingface/datasets/issues/5918 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5918/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5918/comments | https://api.github.com/repos/huggingface/datasets/issues/5918/events | https://github.com/huggingface/datasets/issues/5918 | 1,735,313,549 | I_kwDODunzps5nbsiN | 5,918 | File not found for audio dataset | {
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"load_dataset () did not work for loading local files either "
] | 2023-06-01T02:15:29Z | 2023-06-11T06:02:25Z | null | NONE | null | null | null | ### Describe the bug
After loading an audio dataset, and looking at a sample entry, the `path` element, which is supposed to be the path to the audio file, doesn't actually exist.
### Steps to reproduce the bug
Run bug.py:
```py
import os.path
from datasets import load_dataset
def run() -> None:
cv13 = load_dataset(
"mozilla-foundation/common_voice_13_0",
"hi",
split="train",
)
print(cv13[0])
audio_file = cv13[0]["path"]
if not os.path.exists(audio_file):
raise ValueError(f'File {audio_file} does not exist.')
if __name__ == "__main__":
run()
```
The result (on my machine):
```json
{'client_id': '0f018a99663f33afbb7d38aee281fb1afcfd07f9e7acd00383f604e1e17c38d6ed8adf1bd2ccbf927a52c5adefb8ac4b158ce27a7c2ed9581e71202eb302dfb3', 'path': 'C:\\Users\\rober\\.cache\\huggingface\\datasets\\downloads\\extracted\\8d1479bc09b4609bc2675bd02d6869a4d5e09f7e6616f540bd55eacef46c6e2b\\common_voice_hi_26008353.mp3', 'audio': {'path': 'C:\\Users\\rober\\.cache\\huggingface\\datasets\\downloads\\extracted\\8d1479bc09b4609bc2675bd02d6869a4d5e09f7e6616f540bd55eacef46c6e2b\\common_voice_hi_26008353.mp3', 'array': array([ 6.46234854e-26, -1.35709319e-25, -8.07793567e-26, ...,
1.06425944e-07, 4.46417090e-08, 2.61451660e-09]), 'sampling_rate': 48000}, 'sentence': 'हमने उसका जन्मदिन मनाया।', 'up_votes': 2, 'down_votes': 0, 'age': '', 'gender': '', 'accent': '', 'locale': 'hi', 'segment': '' ', 'variant': ''}
```
```txt
Traceback (most recent call last):
File "F:\eo-reco\bug.py", line 18, in <module>
run()
File "F:\eo-reco\bug.py", line 15, in run
raise ValueError(f'File {audio_file} does not exist.')
ValueError: File C:\Users\rober\.cache\huggingface\datasets\downloads\extracted\8d1479bc09b4609bc2675bd02d6869a4d5e09f7e6616f540bd55eacef46c6e2b\common_voice_hi_26008353.mp3 does not exist.
```
### Expected behavior
The `path` element points to the correct file, which happens to be:
```
C:\Users\rober\.cache\huggingface\datasets\downloads\extracted\8d1479bc09b4609bc2675bd02d6869a4d5e09f7e6616f540bd55eacef46c6e2b\hi_train_0\common_voice_hi_26008353.mp3
```
That is, there's an extra directory `hi_train_0` that is not in the `path` element.
### Environment info
- `datasets` version: 2.12.0
- Platform: Windows-10-10.0.22621-SP0
- Python version: 3.11.3
- Huggingface_hub version: 0.14.1
- PyArrow version: 12.0.0
- Pandas version: 2.0.1
- | {
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https://api.github.com/repos/huggingface/datasets/issues/4390 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4390/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4390/comments | https://api.github.com/repos/huggingface/datasets/issues/4390/events | https://github.com/huggingface/datasets/pull/4390 | 1,244,835,877 | PR_kwDODunzps44RoXs | 4,390 | Fix metadata validation | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-05-23T09:11:20Z | 2022-06-01T09:27:52Z | 2022-06-01T09:19:25Z | MEMBER | null | 0 | {
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} | Since Python 3.8, the typing module:
- raises an AttributeError when trying to access `__args__` on any type, e.g.: `List.__args__`
- provides the `get_args` function instead: `get_args(List)`
This PR implements a fix for Python >=3.8 whereas maintaining backward compatibility. | {
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https://api.github.com/repos/huggingface/datasets/issues/2672 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2672/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2672/comments | https://api.github.com/repos/huggingface/datasets/issues/2672/events | https://github.com/huggingface/datasets/pull/2672 | 947,294,605 | MDExOlB1bGxSZXF1ZXN0NjkyMjk2NDQ4 | 2,672 | Fix potential DuplicatedKeysError in LibriSpeech | {
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} | DONE:
- Fix unnecessary path join.
- Fix potential DiplicatedKeysError by ensuring keys are unique.
We should promote as a good practice, that the keys should be programmatically generated as unique, instead of read from data (which might be not unique). | {
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https://api.github.com/repos/huggingface/datasets/issues/536 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/536/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/536/comments | https://api.github.com/repos/huggingface/datasets/issues/536/events | https://github.com/huggingface/datasets/pull/536 | 687,378,332 | MDExOlB1bGxSZXF1ZXN0NDc0ODE0NzY1 | 536 | Fingerprint | {
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"I changed the way I implemented fingerprint updates to use decorator functions.\r\n\r\nI also added a new attribute called `_inplace_history` that stores the in-place history of transforms (like cast_, rename_columns, etc.). This history is useful to replay the changes that were done in-place when unpickling a dat... | 2020-08-27T16:27:09Z | 2020-08-31T14:20:40Z | 2020-08-31T14:20:39Z | MEMBER | null | 0 | {
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} | This PR is a continuation of #513 , in which many in-place functions were introduced or updated (cast_, flatten_) etc.
However the caching didn't handle these changes. Indeed the caching took into account only the previous cache file name of the table, and not the possible in-place transforms of the table.
To fix that, I added the concept of dataset fingerprint, that is updated after each transform (in place or not), and stored inside the table metadata.
When a dataset is created, an initial fingerprint is computed. If the dataset is memory-mapped, then the fingerprint generator doesn't read the table and only looks at the filename. However if the table is in-memory, then the fingerprint generator reads the content of the table using a batched non-crypto hashing.
I added a utility class to compute hashes of arbitrary python objects in `fingerprint.py` : `Hasher`. The API is close to standard hashing tools (`.update`, `.hexdigest`). It also supports custom hashing functions depending on object types using a registry like pickle. I added a custom hashing function to hash a `pa.Table` in a batched way, and also for `nlp.DatasetInfo` to leverage its json serialization feature.
Note about this PR:
This is a draft PR because #513 needs to be merged first.
The diff that is shown is for branches fingerprint -> indices (and not master, for now) | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"<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 | rea... | 2023-11-01T17:57:11Z | 2023-11-02T16:02:52Z | 2023-11-02T15:52:09Z | CONTRIBUTOR | null | 0 | {
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} | As discussed in #613 , this PR aims at making NER feature names consistent across datasets.
I changed the feature names of LinCE and XTREME/PAN-X | {
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https://api.github.com/repos/huggingface/datasets/issues/4375 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4375/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4375/comments | https://api.github.com/repos/huggingface/datasets/issues/4375/events | https://github.com/huggingface/datasets/pull/4375 | 1,241,921,147 | PR_kwDODunzps44IMCS | 4,375 | Support DataLoader with num_workers > 0 in streaming mode | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"Alright this is finally ready for review ! It's quite long I'm sorry, but it's not easy to disentangle everything ^^'\r\n\r\nThe main additions are in\r\n- src/datasets/formatting/dataset_wrappers/torch_iterable_dataset.py\r\n- src/d... | 2022-05-19T15:00:31Z | 2022-07-04T16:05:14Z | 2022-06-10T20:47:27Z | MEMBER | null | 0 | {
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} | ### Issue
It's currently not possible to properly stream a dataset using multiple `torch.utils.data.DataLoader` workers:
- the `TorchIterableDataset` can't be pickled and passed to the subprocesses: https://github.com/huggingface/datasets/issues/3950
- streaming extension is failing: https://github.com/huggingface/datasets/issues/3951
- `fsspec` doesn't work out of the box in subprocesses
### Solution in this PR
I fixed these to enable passing an `IterableDataset` to a `torch.utils.data.DataLoader` with `num_workers > 0`.
I also had to shard the `IterableDataset` to give each worker a shard, otherwise data would be duplicated. This is implemented in `TorchIterableDataset.__iter__` and uses the new `IterableDataset._iter_shard(shard_idx)` method
I also had to do a few changes the patching that enable streaming in dataset scripts:
- the patches are now always applied - not just for streaming mode. They're applied when a builder is instantiated
- I improved it to also check for renamed modules or attributes (ex: pandas vs pd)
- I grouped all the patches of pathlib.Path into a class `xPath`, so that `Path` outside of dataset scripts stay unchanged - otherwise I didn't change the content of the extended Path methods for streaming
- I fixed a bug with the `pd.read_csv` patch, opening the file in "rb" mode was missing and causing some datasets to not work in streaming mode, and compression inference was missing
### A few details regarding `fsspec` in multiprocessing
From https://github.com/fsspec/filesystem_spec/pull/963#issuecomment-1131709948 :
> Non-async instances might be safe in the forked child, if they hold no open files/sockets etc.; I'm not sure any implementations pass this test!
> If any async instance has been created, the newly forked processes must:
> 1. discard references to locks, threads and event loops and make new ones
> 2. not use any async fsspec instances from the parent process
> 3. clear all class instance caches
Therefore in a DataLoader's worker, I clear the reference to the loop and thread (1). We should be fine for 2 and 3 already since we don't use fsspec class instances from the parent process.
Fix https://github.com/huggingface/datasets/issues/3950
Fix https://github.com/huggingface/datasets/issues/3951
TODO:
- [x] fix tests | {
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"Hi ! You're right this can can useful.\r\nThis should be easy to add, so feel free to give it a try if you want to contribute :)\r\nI think we just need to add it to the _generate_examples method of the OpenSubtitles dataset builder [here](https://github.com/huggingface/datasets/blob/master/datasets/open_subtitles... | 2021-02-08T13:55:13Z | 2021-02-12T17:38:58Z | 2021-02-12T17:38:58Z | CONTRIBUTOR | null | null | null | Hi! It would be great if you could add the original sentence ids to [Open Subtitles](https://huggingface.co/datasets/open_subtitles).
I can think of two reasons: first, it's possible to gather sentences for an entire document (the original ids contain media id, subtitle file id and sentence id), therefore somewhat allowing for document-level machine translation (and other document-level stuff which could be cool to have); second, it's possible to have parallel sentences in multiple languages, as they share the same ids across bitexts.
I think I should tag @abhishekkrthakur as he's the one who added it in the first place.
Thanks! | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"Thansk for the fix ! Can you regenerate the datasets_infos.json please ? This way it will update the expected number of examples in the test and val splits",
"ah yes!"
] | 2022-06-15T11:51:02Z | 2022-06-15T14:55:56Z | 2022-06-15T14:45:13Z | CONTRIBUTOR | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/3737 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3737/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3737/comments | https://api.github.com/repos/huggingface/datasets/issues/3737/events | https://github.com/huggingface/datasets/pull/3737 | 1,140,148,050 | PR_kwDODunzps4y7uFf | 3,737 | Make RedCaps streamable | {
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@lhoestq Using `data/redcaps_v1.0_annotations.zip` as a download URL gives an error locally when running `datasets-cli test` (will investigate this another time) | {
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https://api.github.com/repos/huggingface/datasets/issues/4331 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4331/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4331/comments | https://api.github.com/repos/huggingface/datasets/issues/4331/events | https://github.com/huggingface/datasets/pull/4331 | 1,234,016,110 | PR_kwDODunzps43uN2R | 4,331 | Adding eval metadata to Amazon Polarity | {
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https://api.github.com/repos/huggingface/datasets/issues/1683 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1683/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1683/comments | https://api.github.com/repos/huggingface/datasets/issues/1683/events | https://github.com/huggingface/datasets/issues/1683 | 778,287,612 | MDU6SXNzdWU3NzgyODc2MTI= | 1,683 | `ArrowInvalid` occurs while running `Dataset.map()` function for DPRContext | {
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"Looks like the mapping function returns a dictionary with a 768-dim array in the `embeddings` field. Since the map is batched, we actually expect the `embeddings` field to be an array of shape (batch_size, 768) to have one embedding per example in the batch.\r\n\r\nTo fix that can you try to remove one of the `[0]... | 2021-01-04T18:47:53Z | 2021-01-04T19:04:45Z | 2021-01-04T19:04:45Z | CONTRIBUTOR | null | null | null | It seems to fail the final batch ):
steps to reproduce:
```
from datasets import load_dataset
from elasticsearch import Elasticsearch
import torch
from transformers import file_utils, set_seed
from transformers import DPRContextEncoder, DPRContextEncoderTokenizerFast
MAX_SEQ_LENGTH = 256
ctx_encoder = DPRContextEncoder.from_pretrained("facebook/dpr-ctx_encoder-single-nq-base", cache_dir="../datasets/")
ctx_tokenizer = DPRContextEncoderTokenizerFast.from_pretrained(
"facebook/dpr-ctx_encoder-single-nq-base",
cache_dir="..datasets/"
)
dataset = load_dataset('text',
data_files='data/raw/ARC_Corpus.txt',
cache_dir='../datasets')
torch.set_grad_enabled(False)
ds_with_embeddings = dataset.map(
lambda example: {
'embeddings': ctx_encoder(
**ctx_tokenizer(
example["text"],
padding='max_length',
truncation=True,
max_length=MAX_SEQ_LENGTH,
return_tensors="pt"
)
)[0][0].numpy(),
},
batched=True,
load_from_cache_file=False,
batch_size=1000
)
```
ARC Corpus can be obtained from [here](https://ai2-datasets.s3-us-west-2.amazonaws.com/arc/ARC-V1-Feb2018.zip)
And then the error:
```
---------------------------------------------------------------------------
ArrowInvalid Traceback (most recent call last)
<ipython-input-13-67d139bb2ed3> in <module>
14 batched=True,
15 load_from_cache_file=False,
---> 16 batch_size=1000
17 )
~/.cache/pypoetry/virtualenvs/masters-utTTC0p8-py3.7/lib/python3.7/site-packages/datasets/dataset_dict.py in map(self, function, with_indices, input_columns, batched, batch_size, remove_columns, keep_in_memory, load_from_cache_file, cache_file_names, writer_batch_size, features, disable_nullable, fn_kwargs, num_proc)
301 num_proc=num_proc,
302 )
--> 303 for k, dataset in self.items()
304 }
305 )
~/.cache/pypoetry/virtualenvs/masters-utTTC0p8-py3.7/lib/python3.7/site-packages/datasets/dataset_dict.py in <dictcomp>(.0)
301 num_proc=num_proc,
302 )
--> 303 for k, dataset in self.items()
304 }
305 )
~/.cache/pypoetry/virtualenvs/masters-utTTC0p8-py3.7/lib/python3.7/site-packages/datasets/arrow_dataset.py in map(self, function, with_indices, input_columns, batched, batch_size, drop_last_batch, remove_columns, keep_in_memory, load_from_cache_file, cache_file_name, writer_batch_size, features, disable_nullable, fn_kwargs, num_proc, suffix_template, new_fingerprint)
1257 fn_kwargs=fn_kwargs,
1258 new_fingerprint=new_fingerprint,
-> 1259 update_data=update_data,
1260 )
1261 else:
~/.cache/pypoetry/virtualenvs/masters-utTTC0p8-py3.7/lib/python3.7/site-packages/datasets/arrow_dataset.py in wrapper(*args, **kwargs)
155 }
156 # apply actual function
--> 157 out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs)
158 datasets: List["Dataset"] = list(out.values()) if isinstance(out, dict) else [out]
159 # re-apply format to the output
~/.cache/pypoetry/virtualenvs/masters-utTTC0p8-py3.7/lib/python3.7/site-packages/datasets/fingerprint.py in wrapper(*args, **kwargs)
161 # Call actual function
162
--> 163 out = func(self, *args, **kwargs)
164
165 # Update fingerprint of in-place transforms + update in-place history of transforms
~/.cache/pypoetry/virtualenvs/masters-utTTC0p8-py3.7/lib/python3.7/site-packages/datasets/arrow_dataset.py in _map_single(self, function, with_indices, input_columns, batched, batch_size, drop_last_batch, remove_columns, keep_in_memory, load_from_cache_file, cache_file_name, writer_batch_size, features, disable_nullable, fn_kwargs, new_fingerprint, rank, offset, update_data)
1526 if update_data:
1527 batch = cast_to_python_objects(batch)
-> 1528 writer.write_batch(batch)
1529 if update_data:
1530 writer.finalize() # close_stream=bool(buf_writer is None)) # We only close if we are writing in a file
~/.cache/pypoetry/virtualenvs/masters-utTTC0p8-py3.7/lib/python3.7/site-packages/datasets/arrow_writer.py in write_batch(self, batch_examples, writer_batch_size)
276 typed_sequence = TypedSequence(batch_examples[col], type=col_type, try_type=col_try_type)
277 typed_sequence_examples[col] = typed_sequence
--> 278 pa_table = pa.Table.from_pydict(typed_sequence_examples)
279 self.write_table(pa_table)
280
~/.cache/pypoetry/virtualenvs/masters-utTTC0p8-py3.7/lib/python3.7/site-packages/pyarrow/table.pxi in pyarrow.lib.Table.from_pydict()
~/.cache/pypoetry/virtualenvs/masters-utTTC0p8-py3.7/lib/python3.7/site-packages/pyarrow/table.pxi in pyarrow.lib.Table.from_arrays()
~/.cache/pypoetry/virtualenvs/masters-utTTC0p8-py3.7/lib/python3.7/site-packages/pyarrow/table.pxi in pyarrow.lib.Table.validate()
~/.cache/pypoetry/virtualenvs/masters-utTTC0p8-py3.7/lib/python3.7/site-packages/pyarrow/error.pxi in pyarrow.lib.check_status()
ArrowInvalid: Column 1 named text expected length 768 but got length 1000
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https://api.github.com/repos/huggingface/datasets/issues/3225 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3225/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3225/comments | https://api.github.com/repos/huggingface/datasets/issues/3225/events | https://github.com/huggingface/datasets/pull/3225 | 1,046,530,493 | PR_kwDODunzps4uLrB3 | 3,225 | Update tatoeba to v2021-07-22 | {
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"How about this? @lhoestq @abhishekkrthakur ",
"Hi ! I think it would be nice if people could still be able to load the old version.\r\nMaybe this can be a parameter ? For example to load the old version they could do\r\n```python\r\nload_dataset(\"tatoeba\", lang1=\"en\", lang2=\"mr\", date=\"v2020-11-09\")\r\n`... | 2021-11-06T15:14:31Z | 2021-11-12T11:13:13Z | 2021-11-12T11:13:13Z | CONTRIBUTOR | null | 0 | {
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} | Tatoeba's latest version is v2021-07-22 | {
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https://api.github.com/repos/huggingface/datasets/issues/6081 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6081/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6081/comments | https://api.github.com/repos/huggingface/datasets/issues/6081/events | https://github.com/huggingface/datasets/pull/6081 | 1,824,486,278 | PR_kwDODunzps5WjU0k | 6,081 | Deprecate `Dataset.export` | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"<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 | rea... | 2023-07-27T14:22:18Z | 2023-07-28T11:09:54Z | 2023-07-28T11:01:04Z | CONTRIBUTOR | null | 0 | {
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} | Deprecate `Dataset.export` that generates a TFRecord file from a dataset as this method is undocumented, and the usage seems low. Users should use [TFRecordWriter](https://www.tensorflow.org/api_docs/python/tf/io/TFRecordWriter#write) or the official [TFRecord](https://www.tensorflow.org/tutorials/load_data/tfrecord) tutorial (on which this method is based) to write TFRecord files instead. | {
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https://api.github.com/repos/huggingface/datasets/issues/5132 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5132/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5132/comments | https://api.github.com/repos/huggingface/datasets/issues/5132/events | https://github.com/huggingface/datasets/issues/5132 | 1,413,607,306 | I_kwDODunzps5UQe-K | 5,132 | Depracate `num_proc` parameter in `DownloadManager.extract` | {
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"I can take this! #self-assign",
"#self-assign",
"@lazarust i'm already working on this issue :smile: ",
"#self-assign",
"hey @mariosasko , i made a pr for this issue. Could you please review it."
] | 2022-10-18T17:41:05Z | 2022-10-25T15:56:46Z | 2022-10-25T15:56:46Z | CONTRIBUTOR | null | null | null | The `num_proc` parameter is only present in `DownloadManager.extract` but not in `StreamingDownloadManager.extract`, making it impossible to support streaming in the dataset scripts that use it (`openwebtext` and `the_pile_stack_exchange`). We can avoid this situation by deprecating this parameter and passing `DownloadConfig`'s `num_proc` to `map_nested` instead, as it's done in `DownloadManager.download`. | {
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https://api.github.com/repos/huggingface/datasets/issues/2937 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2937/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2937/comments | https://api.github.com/repos/huggingface/datasets/issues/2937/events | https://github.com/huggingface/datasets/issues/2937 | 999,548,277 | I_kwDODunzps47k-V1 | 2,937 | load_dataset using default cache on Windows causes PermissionError: [WinError 5] Access is denied | {
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"Hi @daqieq, thanks for reporting.\r\n\r\nUnfortunately, I was not able to reproduce this bug:\r\n```ipython\r\nIn [1]: from datasets import load_dataset\r\n ...: ds = load_dataset('wiki_bio')\r\nDownloading: 7.58kB [00:00, 26.3kB/s]\r\nDownloading: 2.71kB [00:00, ?B/s]\r\nUsing custom data configuration default\... | 2021-09-17T16:52:10Z | 2022-08-24T13:09:08Z | 2022-08-24T13:09:08Z | NONE | null | null | null | ## Describe the bug
Standard process to download and load the wiki_bio dataset causes PermissionError in Windows 10 and 11.
## Steps to reproduce the bug
```python
from datasets import load_dataset
ds = load_dataset('wiki_bio')
```
## Expected results
It is expected that the dataset downloads without any errors.
## Actual results
PermissionError see trace below:
```
Using custom data configuration default
Downloading and preparing dataset wiki_bio/default (download: 318.53 MiB, generated: 736.94 MiB, post-processed: Unknown size, total: 1.03 GiB) to C:\Users\username\.cache\huggingface\datasets\wiki_bio\default\1.1.0\5293ce565954ba965dada626f1e79684e98172d950371d266bf3caaf87e911c9...
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "C:\Users\username\.conda\envs\hf\lib\site-packages\datasets\load.py", line 1112, in load_dataset
builder_instance.download_and_prepare(
File "C:\Users\username\.conda\envs\hf\lib\site-packages\datasets\builder.py", line 644, in download_and_prepare
self._save_info()
File "C:\Users\username\.conda\envs\hf\lib\contextlib.py", line 120, in __exit__
next(self.gen)
File "C:\Users\username\.conda\envs\hf\lib\site-packages\datasets\builder.py", line 598, in incomplete_dir
os.rename(tmp_dir, dirname)
PermissionError: [WinError 5] Access is denied: 'C:\\Users\\username\\.cache\\huggingface\\datasets\\wiki_bio\\default\\1.1.0\\5293ce565954ba965dada626f1e79684e98172d950371d266bf3caaf87e911c9.incomplete' -> 'C:\\Users\\username\\.cache\\huggingface\\datasets\\wiki_bio\\default\\1.1.0\\5293ce565954ba965dada626f1e79684e98172d950371d266bf3caaf87e911c9'
```
By commenting out the os.rename() [L604](https://github.com/huggingface/datasets/blob/master/src/datasets/builder.py#L604) and the shutil.rmtree() [L607](https://github.com/huggingface/datasets/blob/master/src/datasets/builder.py#L607) lines, in my virtual environment, I was able to get the load process to complete, rename the directory manually and then rerun the `load_dataset('wiki_bio')` to get what I needed.
It seems that os.rename() in the `incomplete_dir` content manager is the culprit. Here's another project [Conan](https://github.com/conan-io/conan/issues/6560) with similar issue with os.rename() if it helps debug this issue.
## Environment info
- `datasets` version: 1.12.1
- Platform: Windows-10-10.0.22449-SP0
- Python version: 3.8.12
- PyArrow version: 5.0.0
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-11-07T09:25:05Z | 2022-11-08T06:51:20Z | 2022-11-08T06:49:17Z | MEMBER | null | 0 | {
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"This is probably a Windows issue, we need to specify the encoding when `load_dataset()` reads the original CSV file.\r\nTry to find the `open()` statement called by `load_dataset()` and add an `encoding='utf-8'` parameter.\r\nSee issues #242 and #307 ",
"It should be in `xtreme.py:L755`:\r\n```python\r\n ... | 2020-07-07T08:14:23Z | 2020-09-07T14:51:45Z | 2020-09-07T14:51:45Z | CONTRIBUTOR | null | null | null | 
I guess the error is related to python source encoding issue that my PC is trying to decode the source code with wrong encoding-decoding tools, perhaps :
https://www.python.org/dev/peps/pep-0263/
I guess the error was triggered by the code " module = importlib.import_module(module_path)" at line 57 in the source code: nlp/src/nlp/load.py / (https://github.com/huggingface/nlp/blob/911d5596f9b500e39af8642fe3d1b891758999c7/src/nlp/load.py#L51)
Any ideas?
p.s. tried the same code on colab, that runs perfectly
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```
pip install git+http://github.com/huggingface/nlp.git
```
or
```
git clone http://github.com/huggingface/nlp.git
pip install -e ./nlp
```
will use the latest scripts, and not the ones from the previous version. | {
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https://api.github.com/repos/huggingface/datasets/issues/3974 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3974/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3974/comments | https://api.github.com/repos/huggingface/datasets/issues/3974/events | https://github.com/huggingface/datasets/pull/3974 | 1,174,485,044 | PR_kwDODunzps40ssrA | 3,974 | Add XFUN dataset | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"Not sure how to generate dummy data.\r\n\r\nThe downloaded file structure is \r\n\r\n- document file paths\r\n - (a json file containing all documents info, document images folder)\r\n - (a json file containing all documents in... | 2022-03-20T09:24:54Z | 2022-10-03T09:38:16Z | 2022-10-03T09:36:22Z | CONTRIBUTOR | null | 0 | {
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} | This PR adds XFUN dataset.
Home page and repository: https://github.com/doc-analysis/XFUND
Source code: https://github.com/microsoft/unilm/blob/master/layoutlmft/layoutlmft/data/datasets/xfun.py | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6508). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update."
] | 2023-12-18T04:50:37Z | 2023-12-18T10:36:34Z | null | NONE | null | 0 | {
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} | Let GeoParquet files with the file extension `*.geoparquet` or `*.gpq` be readable by the default parquet reader.
Those two file extensions are the ones most commonly used for GeoParquet files, and is included in the `gpq` validator tool at https://github.com/planetlabs/gpq/blob/e5576b4ee7306b4d2259d56c879465a9364dab90/cmd/gpq/command/convert.go#L73-L75
Addresses https://github.com/huggingface/datasets/issues/6438 | {
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https://api.github.com/repos/huggingface/datasets/issues/5992 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5992/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5992/comments | https://api.github.com/repos/huggingface/datasets/issues/5992/events | https://github.com/huggingface/datasets/pull/5992 | 1,776,460,964 | PR_kwDODunzps5UAk3C | 5,992 | speedup | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_5992). All of your documentation changes will be reflected on that endpoint."
] | 2023-06-27T09:17:58Z | 2023-06-27T09:23:07Z | 2023-06-27T09:18:04Z | CONTRIBUTOR | null | 1 | {
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} | [] | open | false | null | [] | null | [] | 2023-12-12T23:07:51Z | 2023-12-13T13:24:22Z | null | NONE | null | null | null | ### System Info
- `transformers` version: 4.32.1
- Platform: Windows-10-10.0.19045-SP0
- Python version: 3.11.5
- Huggingface_hub version: 0.15.1
- Safetensors version: 0.3.2
- Accelerate version: not installed
- Accelerate config: not found
- PyTorch version (GPU?): 2.1.1+cpu (False)
- Tensorflow version (GPU?): 2.15.0 (False)
- Flax version (CPU?/GPU?/TPU?): not installed (NA)
- Jax version: not installed
- JaxLib version: not installed
- Using GPU in script?: no
- Using distributed or parallel set-up in script?: no
### Who can help?
@marios
### Information
- [X] The official example scripts
- [ ] My own modified scripts
### Tasks
- [X] An officially supported task in the `examples` folder (such as GLUE/SQuAD, ...)
- [ ] My own task or dataset (give details below)
### Reproduction
[Source](https://huggingface.co/docs/datasets/v2.2.1/en/access)
```
from datasets import load_dataset
dataset = load_dataset('glue', 'mrpc', split='train')
dataset.info
```
DatasetInfo(description='GLUE, the General Language Understanding Evaluation benchmark\n(https://gluebenchmark.com/) is a collection of resources for training,\nevaluating, and analyzing natural language understanding systems.\n\n', citation='@inproceedings{dolan2005automatically,\n title={Automatically constructing a corpus of sentential paraphrases},\n author={Dolan, William B and Brockett, Chris},\n booktitle={Proceedings of the Third International Workshop on Paraphrasing (IWP2005)},\n year={2005}\n}\n@inproceedings{wang2019glue,\n title={{GLUE}: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding},\n author={Wang, Alex and Singh, Amanpreet and Michael, Julian and Hill, Felix and Levy, Omer and Bowman, Samuel R.},\n note={In the Proceedings of ICLR.},\n year={2019}\n}\n', homepage='https://www.microsoft.com/en-us/download/details.aspx?id=52398', license='', features={'sentence1': Value(dtype='string', id=None), 'sentence2': Value(dtype='string', id=None), 'label': ClassLabel(names=['not_equivalent', 'equivalent'], id=None), 'idx': Value(dtype='int32', id=None)}, post_processed=None, supervised_keys=None, task_templates=None, builder_name='glue', dataset_name=None, config_name='mrpc', version=1.0.0, splits={'train': SplitInfo(name='train', num_bytes=943843, num_examples=3668, shard_lengths=None, dataset_name='glue'), 'validation': SplitInfo(name='validation', num_bytes=105879, num_examples=408, shard_lengths=None, dataset_name='glue'), 'test': SplitInfo(name='test', num_bytes=442410, num_examples=1725, shard_lengths=None, dataset_name='glue')}, download_checksums={'https://dl.fbaipublicfiles.com/glue/data/mrpc_dev_ids.tsv': {'num_bytes': 6222, 'checksum': None}, 'https://dl.fbaipublicfiles.com/senteval/senteval_data/msr_paraphrase_train.txt': {'num_bytes': 1047044, 'checksum': None}, 'https://dl.fbaipublicfiles.com/senteval/senteval_data/msr_paraphrase_test.txt': {'num_bytes': 441275, 'checksum': None}}, download_size=1494541, post_processing_size=None, dataset_size=1492132, size_in_bytes=2986673)
### Expected behavior
```
from datasets import load_dataset
dataset = load_dataset('glue', 'mrpc', split='train')
dataset.info
```
DatasetInfo(
description='GLUE, the General Language Understanding Evaluation benchmark\n(https://gluebenchmark.com/) is a collection of resources for training,\nevaluating, and analyzing natural language understanding systems.\n\n',
citation='@inproceedings{dolan2005automatically,\n title={Automatically constructing a corpus of sentential paraphrases},\n author={Dolan, William B and Brockett, Chris},\n booktitle={Proceedings of the Third International Workshop on Paraphrasing (IWP2005)},\n year={2005}\n}\n@inproceedings{wang2019glue,\n title={{GLUE}: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding},\n author={Wang, Alex and Singh, Amanpreet and Michael, Julian and Hill, Felix and Levy, Omer and Bowman, Samuel R.},\n note={In the Proceedings of ICLR.},\n year={2019}\n}\n', homepage='https://www.microsoft.com/en-us/download/details.aspx?id=52398',
license='',
features={'sentence1': Value(dtype='string', id=None), 'sentence2': Value(dtype='string', id=None), 'label': ClassLabel(num_classes=2, names=['not_equivalent', 'equivalent'], names_file=None, id=None), 'idx': Value(dtype='int32', id=None)}, post_processed=None, supervised_keys=None, builder_name='glue', config_name='mrpc', version=1.0.0, splits={'train': SplitInfo(name='train', num_bytes=943851, num_examples=3668, dataset_name='glue'), 'validation': SplitInfo(name='validation', num_bytes=105887, num_examples=408, dataset_name='glue'), 'test': SplitInfo(name='test', num_bytes=442418, num_examples=1725, dataset_name='glue')},
download_checksums={'https://dl.fbaipublicfiles.com/glue/data/mrpc_dev_ids.tsv': {'num_bytes': 6222, 'checksum': '971d7767d81b997fd9060ade0ec23c4fc31cbb226a55d1bd4a1bac474eb81dc7'}, 'https://dl.fbaipublicfiles.com/senteval/senteval_data/msr_paraphrase_train.txt': {'num_bytes': 1047044, 'checksum': '60a9b09084528f0673eedee2b69cb941920f0b8cd0eeccefc464a98768457f89'}, 'https://dl.fbaipublicfiles.com/senteval/senteval_data/msr_paraphrase_test.txt': {'num_bytes': 441275, 'checksum': 'a04e271090879aaba6423d65b94950c089298587d9c084bf9cd7439bd785f784'}},
download_size=1494541,
post_processing_size=None,
dataset_size=1492156,
size_in_bytes=2986697
) | {
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https://api.github.com/repos/huggingface/datasets/issues/2895 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2895/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2895/comments | https://api.github.com/repos/huggingface/datasets/issues/2895/events | https://github.com/huggingface/datasets/pull/2895 | 993,462,274 | MDExOlB1bGxSZXF1ZXN0NzMxNjQ0NTY2 | 2,895 | Use pyarrow.Table.replace_schema_metadata instead of pyarrow.Table.cast | {
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} | This PR partially addresses #2252.
``update_metadata_with_features`` uses ``Table.cast`` which slows down ``load_from_disk`` (and possibly other methods that use it) for very large datasets. Since ``update_metadata_with_features`` is only updating the schema metadata, it makes more sense to use ``pyarrow.Table.replace_schema_metadata`` which is much faster. This PR adds a ``replace_schema_metadata`` method to all table classes, and modifies ``update_metadata_with_features`` to use it instead of ``cast``. | {
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https://api.github.com/repos/huggingface/datasets/issues/6004 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6004/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6004/comments | https://api.github.com/repos/huggingface/datasets/issues/6004/events | https://github.com/huggingface/datasets/pull/6004 | 1,786,636,368 | PR_kwDODunzps5UjN2h | 6,004 | Misc improvements | {
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"<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_a... | 2023-07-03T18:29:14Z | 2023-07-06T17:04:11Z | 2023-07-06T16:55:25Z | CONTRIBUTOR | null | 0 | {
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} | Contains the following improvements:
* fixes a "share dataset" link in README and modifies the "hosting" part in the disclaimer section
* updates `Makefile` to also run the style checks on `utils` and `setup.py`
* deletes a test for GH-hosted datasets (no longer supported)
* deletes `convert_dataset.sh` (outdated)
* aligns `utils/release.py` with `transformers` (the current version is outdated) | {
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https://api.github.com/repos/huggingface/datasets/issues/1971 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1971/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1971/comments | https://api.github.com/repos/huggingface/datasets/issues/1971/events | https://github.com/huggingface/datasets/pull/1971 | 819,714,231 | MDExOlB1bGxSZXF1ZXN0NTgyNzgyNTU0 | 1,971 | Fix ArrowWriter closes stream at exit | {
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"Oh nice thanks for adding the context manager ! All the streams and RecordBatchWriter will be properly closed now. Hopefully this gives a better experience on windows on which it's super important to close stuff.\r\n\r\nNot sure about the error, it looks like a process crashed silently.\r\nLet me take a look",
"... | 2021-03-02T07:12:34Z | 2021-03-10T16:36:57Z | 2021-03-10T16:36:57Z | MEMBER | null | 0 | {
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} | Current implementation of ArrowWriter does not properly release the `stream` resource (by closing it) if its `finalize()` method is not called and/or an Exception is raised before/during the call to its `finalize()` method.
Therefore, ArrowWriter should be used as a context manager that properly closes its `stream` resource at exit. | {
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https://api.github.com/repos/huggingface/datasets/issues/4784 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4784/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4784/comments | https://api.github.com/repos/huggingface/datasets/issues/4784/events | https://github.com/huggingface/datasets/issues/4784 | 1,326,395,280 | I_kwDODunzps5PDy-Q | 4,784 | Add Multiface dataset | {
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"color": "bfdadc",... | open | false | null | [] | null | [
"Hi @osanseviero I would like to add this dataset.",
"Hey @nandwalritik! Thanks for offering to help!\r\n\r\nThis dataset might be somewhat complex and I'm concerned about it being 65 TB, which would be quite expensive to host. @lhoestq @mariosasko I would love your input if you think it's worth adding this datas... | 2022-08-02T21:00:22Z | 2022-08-08T14:42:36Z | null | MEMBER | null | null | null | ## Adding a Dataset
- **Name:** Multiface dataset
- **Description:** f high quality recordings of the faces of 13 identities, each captured in a multi-view capture stage performing various facial expressions. An average of 12,200 (v1 scripts) to 23,000 (v2 scripts) frames per subject with capture rate at 30 fps
- **Data:** https://github.com/facebookresearch/multiface
The whole dataset is 65TB though, so I'm not sure
Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/main/ADD_NEW_DATASET.md).
| {
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https://api.github.com/repos/huggingface/datasets/issues/1542 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1542/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1542/comments | https://api.github.com/repos/huggingface/datasets/issues/1542/events | https://github.com/huggingface/datasets/pull/1542 | 765,439,746 | MDExOlB1bGxSZXF1ZXN0NTM4OTYyMjAx | 1,542 | fix typo readme | {
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https://api.github.com/repos/huggingface/datasets/issues/5220 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5220/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5220/comments | https://api.github.com/repos/huggingface/datasets/issues/5220/events | https://github.com/huggingface/datasets/issues/5220 | 1,441,664,377 | I_kwDODunzps5V7g15 | 5,220 | Implicit type conversion of lists in to_pandas | {
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"I think this behavior comes from PyArrow:\r\n```python\r\nimport pyarrow as pa\r\nt = pa.table({\"a\": [[0]]})\r\nt.to_pandas().a.values[0]\r\n# array([0])\r\n```\r\n\r\nI believe this has to do with zero-copy: you can get a pandas DataFrame without copying the buffers from arrow, and therefore end up with numpy a... | 2022-11-09T08:40:18Z | 2022-11-10T16:12:26Z | 2022-11-10T16:12:26Z | CONTRIBUTOR | null | null | null | ### Describe the bug
```
ds = Dataset.from_list([{'a':[1,2,3]}])
ds.to_pandas().a.values[0]
```
Results in `array([1, 2, 3])` -- a rather unexpected conversion of types which made downstream tools expecting lists not happy.
### Steps to reproduce the bug
See snippet
### Expected behavior
Keep the original type
### Environment info
datasets 2.6.1
python 3.8.10 | {
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https://api.github.com/repos/huggingface/datasets/issues/3410 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3410/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3410/comments | https://api.github.com/repos/huggingface/datasets/issues/3410/events | https://github.com/huggingface/datasets/pull/3410 | 1,075,815,415 | PR_kwDODunzps4voFG7 | 3,410 | Fix dependencies conflicts in Windows CI after conda update to 4.11 | {
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} | For some reason the CI wasn't using python 3.6 but python 3.7 after the update to conda 4.11 | {
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https://api.github.com/repos/huggingface/datasets/issues/6103 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6103/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6103/comments | https://api.github.com/repos/huggingface/datasets/issues/6103/events | https://github.com/huggingface/datasets/pull/6103 | 1,828,515,165 | PR_kwDODunzps5Ww2gV | 6,103 | Set dev version | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6103). All of your documentation changes will be reflected on that endpoint.",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchma... | 2023-07-31T06:44:05Z | 2023-07-31T06:55:58Z | 2023-07-31T06:45:41Z | MEMBER | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/299 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/299/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/299/comments | https://api.github.com/repos/huggingface/datasets/issues/299/events | https://github.com/huggingface/datasets/pull/299 | 643,611,557 | MDExOlB1bGxSZXF1ZXN0NDM4Mzg0NDgw | 299 | remove some print in snli file | {
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"I guess you can just rebase from master to fix the CI"
] | 2020-06-23T07:46:06Z | 2020-06-23T08:10:46Z | 2020-06-23T08:10:44Z | CONTRIBUTOR | null | 0 | {
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} | This PR removes unwanted `print` statements in some files such as `snli.py` | {
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https://api.github.com/repos/huggingface/datasets/issues/577 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/577/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/577/comments | https://api.github.com/repos/huggingface/datasets/issues/577/events | https://github.com/huggingface/datasets/issues/577 | 694,607,148 | MDU6SXNzdWU2OTQ2MDcxNDg= | 577 | Some languages in wikipedia dataset are not loading | {
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"Some wikipedia languages have already been processed by us and are hosted on our google storage. This is the case for \"fr\" and \"en\" for example.\r\n\r\nFor other smaller languages (in terms of bytes), they are directly downloaded and parsed from the wikipedia dump site.\r\nParsing can take some time for langua... | 2020-09-07T01:16:29Z | 2023-04-11T22:50:48Z | 2022-10-11T11:16:04Z | CONTRIBUTOR | null | null | null | Hi,
I am working with the `wikipedia` dataset and I have a script that goes over 92 of the available languages in that dataset. So far I have detected that `ar`, `af`, `an` are not loading. Other languages like `fr` and `en` are working fine. Here's how I am loading them:
```
import nlp
langs = ['ar'. 'af', 'an']
for lang in langs:
data = nlp.load_dataset('wikipedia', f'20200501.{lang}', beam_runner='DirectRunner', split='train')
print(lang, len(data))
```
Here's what I see for 'ar' (it gets stuck there):
```
Downloading and preparing dataset wikipedia/20200501.ar (download: Unknown size, generated: Unknown size, post-processed: Unknown sizetotal: Unknown size) to /home/gaguilar/.cache/huggingface/datasets/wikipedia/20200501.ar/1.0.0/7be7f4324255faf70687be8692de57cf79197afdc33ff08d6a04ed602df32d50...
```
Note that those languages are indeed in the list of expected languages. Any suggestions on how to work around this? Thanks! | {
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https://api.github.com/repos/huggingface/datasets/issues/1764 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1764/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1764/comments | https://api.github.com/repos/huggingface/datasets/issues/1764/events | https://github.com/huggingface/datasets/issues/1764 | 791,486,860 | MDU6SXNzdWU3OTE0ODY4NjA= | 1,764 | Connection Issues | {
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"Academic WIFI was blocking."
] | 2021-01-21T20:56:09Z | 2021-01-21T21:00:19Z | 2021-01-21T21:00:02Z | NONE | null | null | null | Today, I am getting connection issues while loading a dataset and the metric.
```
Traceback (most recent call last):
File "src/train.py", line 180, in <module>
train_dataset, dev_dataset, test_dataset = create_race_dataset()
File "src/train.py", line 130, in create_race_dataset
train_dataset = load_dataset("race", "all", split="train")
File "/Users/saeed/Desktop/codes/repos/dreamscape-qa/env/lib/python3.7/site-packages/datasets/load.py", line 591, in load_dataset
path, script_version=script_version, download_config=download_config, download_mode=download_mode, dataset=True
File "/Users/saeed/Desktop/codes/repos/dreamscape-qa/env/lib/python3.7/site-packages/datasets/load.py", line 267, in prepare_module
local_path = cached_path(file_path, download_config=download_config)
File "/Users/saeed/Desktop/codes/repos/dreamscape-qa/env/lib/python3.7/site-packages/datasets/utils/file_utils.py", line 343, in cached_path
max_retries=download_config.max_retries,
File "/Users/saeed/Desktop/codes/repos/dreamscape-qa/env/lib/python3.7/site-packages/datasets/utils/file_utils.py", line 617, in get_from_cache
raise ConnectionError("Couldn't reach {}".format(url))
ConnectionError: Couldn't reach https://raw.githubusercontent.com/huggingface/datasets/1.2.1/datasets/race/race.py
```
Or
```
Traceback (most recent call last):
File "src/train.py", line 105, in <module>
rouge = datasets.load_metric("rouge")
File "/Users/saeed/Desktop/codes/repos/dreamscape-qa/env/lib/python3.7/site-packages/datasets/load.py", line 500, in load_metric
dataset=False,
File "/Users/saeed/Desktop/codes/repos/dreamscape-qa/env/lib/python3.7/site-packages/datasets/load.py", line 267, in prepare_module
local_path = cached_path(file_path, download_config=download_config)
File "/Users/saeed/Desktop/codes/repos/dreamscape-qa/env/lib/python3.7/site-packages/datasets/utils/file_utils.py", line 343, in cached_path
max_retries=download_config.max_retries,
File "/Users/saeed/Desktop/codes/repos/dreamscape-qa/env/lib/python3.7/site-packages/datasets/utils/file_utils.py", line 617, in get_from_cache
raise ConnectionError("Couldn't reach {}".format(url))
ConnectionError: Couldn't reach https://raw.githubusercontent.com/huggingface/datasets/1.2.1/metrics/rouge/rouge.py
``` | {
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"Can I use instructions present in below link for time series dataset as well? \r\nhttps://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md ",
"cc'ing @kashif and @NielsRogge for visibility!",
"@INF800 happy to add this dataset! I will try to set a PR by the end of the day... if you can kindly poi... | 2022-04-06T05:46:58Z | 2022-04-11T09:07:10Z | null | NONE | null | null | null | ## Adding a Time Series Dataset
- **Name:** 2min ticker data for stock market
- **Description:** 8 stocks' data collected for 1month post ukraine-russia war. 4 NSE stocks and 4 NASDAQ stocks. Along with technical indicators (additional features) as shown in below image
- **Data:** Collected by myself from investing.com
- **Motivation:** Test applicability of transformer based model on stock market / time series problem
 | {
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https://sites.google.com/view/felipe-soares/datasets#h.p_92uSCyAjWSRB | {
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https://api.github.com/repos/huggingface/datasets/issues/6485 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6485/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6485/comments | https://api.github.com/repos/huggingface/datasets/issues/6485/events | https://github.com/huggingface/datasets/issues/6485 | 2,035,141,884 | I_kwDODunzps55Tcz8 | 6,485 | FileNotFoundError: [Errno 2] No such file or directory: 'nul' | {
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"Hi! It seems like the problem is your environment. Maybe this issue can help: https://github.com/pytest-dev/pytest/issues/9519. "
] | 2023-12-11T08:52:13Z | 2023-12-14T08:09:08Z | 2023-12-14T08:09:08Z | NONE | null | null | null | ### Describe the bug
it seems that sth wrong with my terrible "bug body" life, When i run this code, "import datasets"
i meet this error FileNotFoundError: [Errno 2] No such file or directory: 'nul'
### Steps to reproduce the bug
1.import datasets
### Expected behavior
i just run a single line code and stuct in this bug
### Environment info
OS: Windows10
Datasets==2.15.0
python=3.10 | {
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https://api.github.com/repos/huggingface/datasets/issues/2017 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2017/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2017/comments | https://api.github.com/repos/huggingface/datasets/issues/2017/events | https://github.com/huggingface/datasets/pull/2017 | 826,428,578 | MDExOlB1bGxSZXF1ZXN0NTg4NDMyNDc2 | 2,017 | Add TF-based Features to handle different modes of data | {
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I am creating this draft PR to work on add features similar to [TF datasets](https://github.com/tensorflow/datasets/tree/master/tensorflow_datasets/core/features). I'll be starting with `Tensor` and `FeatureConnector` classes, and build upon them to add other features as well. This is a work in progress. | {
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https://api.github.com/repos/huggingface/datasets/issues/6172 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6172/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6172/comments | https://api.github.com/repos/huggingface/datasets/issues/6172/events | https://github.com/huggingface/datasets/issues/6172 | 1,863,318,027 | I_kwDODunzps5vD_oL | 6,172 | Make Dataset streaming queries retryable | {
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"Hi! The streaming mode also retries requests - `datasets.config.STREAMING_READ_MAX_RETRIES` (20 sec by default) controls the number of retries and `datasets.config.STREAMING_READ_RETRY_INTERVAL` (5 sec) the sleep time between retries.\r\n\r\n> At step 1800 I got a 504 HTTP status code error from Huggingface hub fo... | 2023-08-23T13:15:38Z | 2023-11-06T13:54:16Z | null | NONE | null | null | null | ### Feature request
Streaming datasets, as intended, do not load the entire dataset in memory or disk. However, while querying the next data chunk from the remote, sometimes it is possible that the service is down or there might be other issues that may cause the query to fail. In such a scenario, it would be nice to make these queries retryable (perhaps with a backoff strategy).
### Motivation
I was working on a model and the model checkpoints after every 1000 steps. At step 1800 I got a 504 HTTP status code error from Huggingface hub for my pytorch `dataloader`. Given the size of my model and data, it took around 2 hours to reach 1800 steps and now it will take about an hour to recover the lost 800. It would be better to get a retryable querying strategy.
### Your contribution
It would be better if someone having experience in this area takes this up as this would require some testing. | {
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https://api.github.com/repos/huggingface/datasets/issues/1480 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1480/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1480/comments | https://api.github.com/repos/huggingface/datasets/issues/1480/events | https://github.com/huggingface/datasets/pull/1480 | 762,530,805 | MDExOlB1bGxSZXF1ZXN0NTM3MDY1NDMx | 1,480 | Adding the Mac-Morpho dataset | {
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"Hi ! Why do we need the custom `readline` for exactly ? feel free to add a comment to say why it's needed"
] | 2021-08-14T04:40:17Z | 2021-08-26T10:02:30Z | 2021-08-14T04:55:57Z | MEMBER | null | 0 | {
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It also uses the custom `readline` implemented in PR #2786.
The corresponding test is implemented in PR #2786. | {
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"Thanks for reporting @dgcnz.\r\n\r\nI have checked that the dataset works fine in streaming mode.\r\n\r\nAdditionally, other datasets containing timestamps are properly rendered by the viewer: https://huggingface.co/datasets/blbooks\r\n\r\nI have tried to force the refresh of the preview, but the endpoint is not r... | 2022-05-27T02:12:35Z | 2022-06-15T07:30:46Z | 2022-06-15T07:30:46Z | NONE | null | null | null | ### Link
https://huggingface.co/datasets/ett
### Description
Timestamp is not JSON serializable.
```
Status code: 500
Exception: Status500Error
Message: Type is not JSON serializable: Timestamp
```
### Owner
No | {
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https://api.github.com/repos/huggingface/datasets/issues/2194 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2194/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2194/comments | https://api.github.com/repos/huggingface/datasets/issues/2194/events | https://github.com/huggingface/datasets/issues/2194 | 853,909,452 | MDU6SXNzdWU4NTM5MDk0NTI= | 2,194 | py3.7: TypeError: can't pickle _LazyModule objects | {
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"\r\nThis wasn't a `datasets` problem, but `transformers`' and it was solved here https://github.com/huggingface/transformers/pull/11168\r\n"
] | 2021-04-08T21:02:48Z | 2021-04-09T16:56:50Z | 2021-04-09T01:52:57Z | CONTRIBUTOR | null | null | null | While this works fine with py3.8, under py3.7, with a totally new conda env and transformers install:
```
git clone https://github.com/huggingface/transformers
cd transformers
pip install -e .[testing]
export BS=1; rm -rf /tmp/test-clm; PYTHONPATH=src USE_TF=0 CUDA_VISIBLE_DEVICES=0 python \
examples/language-modeling/run_clm.py --model_name_or_path distilgpt2 --dataset_name wikitext \
--dataset_config_name wikitext-2-raw-v1 --do_train --max_train_samples 1 \
--per_device_train_batch_size $BS --output_dir /tmp/test-clm --block_size 128 --logging_steps 1 \
--fp16
```
```
Traceback (most recent call last):
File "examples/language-modeling/run_clm.py", line 453, in <module>
main()
File "examples/language-modeling/run_clm.py", line 336, in main
load_from_cache_file=not data_args.overwrite_cache,
File "/home/stas/anaconda3/lib/python3.7/site-packages/datasets/dataset_dict.py", line 303, in map
for k, dataset in self.items()
File "/home/stas/anaconda3/lib/python3.7/site-packages/datasets/dataset_dict.py", line 303, in <dictcomp>
for k, dataset in self.items()
File "/home/stas/anaconda3/lib/python3.7/site-packages/datasets/arrow_dataset.py", line 1259, in map
update_data=update_data,
File "/home/stas/anaconda3/lib/python3.7/site-packages/datasets/arrow_dataset.py", line 157, in wrapper
out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs)
File "/home/stas/anaconda3/lib/python3.7/site-packages/datasets/fingerprint.py", line 158, in wrapper
self._fingerprint, transform, kwargs_for_fingerprint
File "/home/stas/anaconda3/lib/python3.7/site-packages/datasets/fingerprint.py", line 105, in update_fingerprint
hasher.update(transform_args[key])
File "/home/stas/anaconda3/lib/python3.7/site-packages/datasets/fingerprint.py", line 57, in update
self.m.update(self.hash(value).encode("utf-8"))
File "/home/stas/anaconda3/lib/python3.7/site-packages/datasets/fingerprint.py", line 53, in hash
return cls.hash_default(value)
File "/home/stas/anaconda3/lib/python3.7/site-packages/datasets/fingerprint.py", line 46, in hash_default
return cls.hash_bytes(dumps(value))
File "/home/stas/anaconda3/lib/python3.7/site-packages/datasets/utils/py_utils.py", line 389, in dumps
dump(obj, file)
File "/home/stas/anaconda3/lib/python3.7/site-packages/datasets/utils/py_utils.py", line 361, in dump
Pickler(file, recurse=True).dump(obj)
File "/home/stas/anaconda3/lib/python3.7/site-packages/dill/_dill.py", line 454, in dump
StockPickler.dump(self, obj)
File "/home/stas/anaconda3/lib/python3.7/pickle.py", line 437, in dump
self.save(obj)
File "/home/stas/anaconda3/lib/python3.7/pickle.py", line 504, in save
f(self, obj) # Call unbound method with explicit self
File "/home/stas/anaconda3/lib/python3.7/site-packages/datasets/utils/py_utils.py", line 556, in save_function
obj=obj,
File "/home/stas/anaconda3/lib/python3.7/pickle.py", line 638, in save_reduce
save(args)
File "/home/stas/anaconda3/lib/python3.7/pickle.py", line 504, in save
f(self, obj) # Call unbound method with explicit self
File "/home/stas/anaconda3/lib/python3.7/pickle.py", line 789, in save_tuple
save(element)
File "/home/stas/anaconda3/lib/python3.7/pickle.py", line 504, in save
f(self, obj) # Call unbound method with explicit self
File "/home/stas/anaconda3/lib/python3.7/site-packages/dill/_dill.py", line 941, in save_module_dict
StockPickler.save_dict(pickler, obj)
File "/home/stas/anaconda3/lib/python3.7/pickle.py", line 859, in save_dict
self._batch_setitems(obj.items())
File "/home/stas/anaconda3/lib/python3.7/pickle.py", line 885, in _batch_setitems
save(v)
File "/home/stas/anaconda3/lib/python3.7/pickle.py", line 524, in save
rv = reduce(self.proto)
TypeError: can't pickle _LazyModule objects
```
```
$ python --version
Python 3.7.4
$ python -m torch.utils.collect_env
Collecting environment information...
PyTorch version: 1.8.0.dev20210110+cu110
Is debug build: False
CUDA used to build PyTorch: 11.0
ROCM used to build PyTorch: N/A
OS: Ubuntu 20.04.2 LTS (x86_64)
GCC version: (Ubuntu 9.3.0-17ubuntu1~20.04) 9.3.0
Clang version: 10.0.0-4ubuntu1
CMake version: version 3.16.3
```
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https://api.github.com/repos/huggingface/datasets/issues/5353 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5353/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5353/comments | https://api.github.com/repos/huggingface/datasets/issues/5353/events | https://github.com/huggingface/datasets/issues/5353 | 1,491,880,500 | I_kwDODunzps5Y7Eo0 | 5,353 | Support remote file systems for `Audio` | {
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"Just seen https://github.com/huggingface/datasets/issues/5281"
] | 2022-12-12T13:22:13Z | 2022-12-12T13:37:14Z | 2022-12-12T13:37:14Z | NONE | null | null | null | ### Feature request
Hi there!
It would be super cool if `Audio()`, and potentially other features, could read files from a remote file system.
### Motivation
Large amounts of data is often stored in buckets. `load_from_disk` is able to retrieve data from cloud storage but to my knowledge actually copies the datasets across first, so if you're working off a system with smaller disk specs (like a VM), you can run out of space very quickly.
### Your contribution
Something like this (for Google Cloud Platform in this instance):
```python
from datasets import Dataset, Audio
import gcsfs
fs = gcsfs.GCSFileSystem()
list_of_audio_fp = {'audio': ['1', '2', '3']}
ds = Dataset.from_dict(list_of_audio_fp)
ds = ds.cast_column("audio", Audio(sampling_rate=16000, fs=fs))
```
Under the hood:
```python
import librosa
from io import BytesIO
def load_audio(fp, sampling_rate=None, fs=None):
if fs is not None:
with fs.open(fp, 'rb') as f:
arr, sr = librosa.load(BytesIO(f), sr=sampling_rate)
else:
# Perform existing io operations
```
Written from memory so some things could be wrong. | {
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"Same here !"
] | 2021-09-15T19:59:46Z | 2021-11-24T21:42:31Z | null | NONE | null | null | null | ## Describe the bug
When the cache directory is linked (soft link) to a directory on a NetApp device, the download fails.
## Steps to reproduce the bug
```bash
ln -s /path/to/netapp/.cache ~/.cache
```
```python
load_dataset("imdb")
```
## Expected results
Successfully loading IMDB dataset
## Actual results
```
datasets.utils.info_utils.NonMatchingSplitsSizesError: [{'expected': SplitInfo(name='train', num_bytes=33432835,
num_examples=25000, dataset_name='imdb'), 'recorded': SplitInfo(name='train', num_bytes=0, num_examples=0,
dataset_name='imdb')}, {'expected': SplitInfo(name='test', num_bytes=32650697, num_examples=25000, dataset_name='imdb'),
'recorded': SplitInfo(name='test', num_bytes=659932, num_examples=503, dataset_name='imdb')}, {'expected':
SplitInfo(name='unsupervised', num_bytes=67106814, num_examples=50000, dataset_name='imdb'), 'recorded':
SplitInfo(name='unsupervised', num_bytes=0, num_examples=0, dataset_name='imdb')}]
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.1.2
- Platform: Ubuntu
- Python version: 3.8
## Extra notes
Stranger yet, trying to debug the phenomenon, I found the range of results to vary a lot without clear direction:
- With `cache_dir="/path/to/netapp/.cache"` the same thing happens.
- However, when linking `~/netapp/` to `/path/to/netapp` *and* setting `cache_dir="~/netapp/.cache/huggingface/datasets"` - it does work
- On the other hand, when linking `~/.cache` to `~/netapp/.cache` without using `cache_dir`, it does work anymore.
While I could test it only for a NetApp device, it might have to do with any other mounted FS.
Thanks :)
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} | During config creation, we need to iterate through the data files of all the splits to compute a hash.
To make sure the hash is unique given a certain combination of files/splits, we sort the split names.
However the `NamedSplit` objects can't be passed to `sorted` and currently it raises an error: we need to sort the string of their names instead.
Fix #705 | {
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https://api.github.com/repos/huggingface/datasets/issues/4029 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4029/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4029/comments | https://api.github.com/repos/huggingface/datasets/issues/4029/events | https://github.com/huggingface/datasets/issues/4029 | 1,181,057,011 | I_kwDODunzps5GZX_z | 4,029 | Add FAISS .range_search() method for retrieving all texts from dataset above similarity threshold | {
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"Hi ! You can access the faiss index with\r\n```python\r\nfaiss_index = my_dataset.get_index(\"my_index_name\").faiss_index\r\n```\r\nand then do whatever you want with it, e.g. query it using range_search:\r\n```python\r\nthreshold = 0.95\r\nlimits, distances, indices = faiss_index.range_search(x=xq, thresh=thresh... | 2022-03-25T17:31:33Z | 2022-05-06T08:35:52Z | 2022-05-06T08:35:52Z | NONE | null | null | null | **Is your feature request related to a problem? Please describe.**
I would like to retrieve all texts from a dataset, which are semantically similar to a specific input text (query), above a certain (cosine) similarity threshold. My dataset is very large (Wikipedia), so I need to use Datasets and FAISS for this. I would like to be able to repeat many different queries on the dataset quickly.
**Describe the solution you'd like**
dataset objects currently have the .get_nearest_examples() method for text retrieval via FAISS. But this only allows retrieving a specific number of K texts instead of everything above a specified similarity threshold.
It would be great if HF Datasets would also support the FAISS method .range_search() for retrieving texts above a certain similarity threshold.
see details here: https://github.com/facebookresearch/faiss/issues/1273
**Describe alternatives you've considered**
I've considered using native FAISS, but doing this via HF datasets would be better. My assumption is that Dataset features like dataset streaming make it easier to work with large datasets
**Additional context**
The concrete use-case is: I have a large dataset (wikipedia) and I would like to retrieve all paragraphs which are similar to a query. I will use sentence-transformers for encoding the texts.
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https://api.github.com/repos/huggingface/datasets/issues/3308 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3308/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3308/comments | https://api.github.com/repos/huggingface/datasets/issues/3308/events | https://github.com/huggingface/datasets/issues/3308 | 1,059,255,705 | I_kwDODunzps4_IvWZ | 3,308 | "dataset_infos.json" missing for chr_en and mc4 | {
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"Hi ! Thanks for reporting :) \r\nWe can easily add the metadata for `chr_en` IMO, but for mC4 it will take more time, since it requires to count the number of examples in each language",
"No problem. I am trying to do some analysis on the metadata of all available datasets. Is reading `metadata_infos.json` for e... | 2021-11-21T00:07:22Z | 2022-01-19T13:55:32Z | null | NONE | null | null | null | ## Describe the bug
In the repository, every dataset has its metadata in a file called`dataset_infos.json`. But, this file is missing for two datasets: `chr_en` and `mc4`.
## Steps to reproduce the bug
Check [chr_en](https://github.com/huggingface/datasets/tree/master/datasets/chr_en) and [mc4](https://github.com/huggingface/datasets/tree/master/datasets/mc4) | {
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https://api.github.com/repos/huggingface/datasets/issues/5929 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5929/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5929/comments | https://api.github.com/repos/huggingface/datasets/issues/5929/events | https://github.com/huggingface/datasets/issues/5929 | 1,744,478,456 | I_kwDODunzps5n-qD4 | 5,929 | Importing PyTorch reduces multiprocessing performance for map | {
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"Hi! The times match when I run this code locally or on Colab.\r\n\r\nAlso, we use `multiprocess`, not `multiprocessing`, for parallelization, and torch's `__init__.py` (executed on `import torch` ) slightly modifies the latter.",
"Hey Mariosasko,\r\n\r\nThanks for looking into it. We further did some investigati... | 2023-06-06T19:42:25Z | 2023-06-16T13:09:12Z | 2023-06-16T13:09:12Z | NONE | null | null | null | ### Describe the bug
I noticed that the performance of my dataset preprocessing with `map(...,num_proc=32)` decreases when PyTorch is imported.
### Steps to reproduce the bug
I created two example scripts to reproduce this behavior:
```
import datasets
datasets.disable_caching()
from datasets import Dataset
import time
PROC=32
if __name__ == "__main__":
dataset = [True] * 10000000
dataset = Dataset.from_dict({'train': dataset})
start = time.time()
dataset.map(lambda x: x, num_proc=PROC)
end = time.time()
print(end - start)
```
Takes around 4 seconds on my machine.
While the same code, but with an `import torch`:
```
import datasets
datasets.disable_caching()
from datasets import Dataset
import time
import torch
PROC=32
if __name__ == "__main__":
dataset = [True] * 10000000
dataset = Dataset.from_dict({'train': dataset})
start = time.time()
dataset.map(lambda x: x, num_proc=PROC)
end = time.time()
print(end - start)
```
takes around 22 seconds.
### Expected behavior
I would expect that the import of torch to not have such a significant effect on the performance of map using multiprocessing.
### Environment info
- `datasets` version: 2.12.0
- Platform: Linux-5.15.0-56-generic-x86_64-with-glibc2.35
- Python version: 3.11.3
- Huggingface_hub version: 0.15.1
- PyArrow version: 12.0.0
- Pandas version: 2.0.2
- torch: 2.0.1 | {
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https://api.github.com/repos/huggingface/datasets/issues/4828 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4828/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4828/comments | https://api.github.com/repos/huggingface/datasets/issues/4828/events | https://github.com/huggingface/datasets/pull/4828 | 1,336,040,168 | PR_kwDODunzps49B_vb | 4,828 | Support PIL Image objects in `add_item`/`add_column` | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_4828). All of your documentation changes will be reflected on that endpoint.",
"Hey @mariosasko could we please merge this? I'm still getting the original error at #4796 .",
"Are you planning to continue working on this?"
] | 2022-08-11T14:25:45Z | 2023-09-24T10:15:33Z | null | CONTRIBUTOR | null | 0 | {
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} | Fix #4796
PS: We should also improve the type inference in `OptimizedTypeSequence` to make it possible to also infer the complex types (only `Image` currently) in nested arrays (e.g. `[[pil_image], [pil_image, pil_image]]` or `[{"img": pil_image}`]), but I plan to address this in a separate PR. | {
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https://api.github.com/repos/huggingface/datasets/issues/5190 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5190/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5190/comments | https://api.github.com/repos/huggingface/datasets/issues/5190/events | https://github.com/huggingface/datasets/issues/5190 | 1,433,014,626 | I_kwDODunzps5VahFi | 5,190 | `path` is `None` when downloading a custom audio dataset from the Hub | {
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"Hi! Yes, this is expected behavior - we do this as a security measure to not leak local paths (this info would be useless on other users' machines anyways) and only push audio bytes. \r\n"
] | 2022-11-02T11:51:25Z | 2022-11-02T12:55:02Z | 2022-11-02T12:55:02Z | MEMBER | null | null | null | ### Describe the bug
I've created an [audio dataset](https://huggingface.co/datasets/lewtun/audio-test-push) using the `audiofolder` feature desribed in the [docs](https://huggingface.co/docs/datasets/audio_dataset#audiofolder) and then pushed it to the Hub.
Locally, I can see the `audio.path` feature is of the expected form `path/to/data_dir`, but when I download the dataset from the Hub, I see `audio.path` is `None`
Here's an example:
```python
from datasets import load_dataset
ds = load_dataset("lewtun/audio-test-push")
ds["train"][0]
# {
# "audio": {
# "path": None, <-- Is this expected?
# "array": array(
# [
# 3.97140226e-07,
# 7.30310290e-07,
# 7.56406735e-07,
# ...,
# -1.19636677e-01,
# -1.16811886e-01,
# -1.12441722e-01,
# ]
# ),
# "sampling_rate": 44100,
# },
# "song_id": 0,
# "genre_id": 0,
# "genre": "Electronic",
# }
```
Is this expected behaviour? If yes, feel free to close this issue as it's not a true bug then :)
### Steps to reproduce the bug
1. Create an audio dataset with the `audiofolder` feature
2. Push the dataset to the Hub with `push_to_hub()`
3. Download the Hub dataset and inspect the `audio.path` feature
### Expected behavior
`audio.path` points to the file associated with the audio data
### Environment info
- `datasets` version: 2.6.2.dev0
- Platform: macOS-10.16-x86_64-i386-64bit
- Python version: 3.8.13
- PyArrow version: 9.0.0
- Pandas version: 1.5.1 | {
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https://api.github.com/repos/huggingface/datasets/issues/1166 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1166/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1166/comments | https://api.github.com/repos/huggingface/datasets/issues/1166/events | https://github.com/huggingface/datasets/pull/1166 | 757,721,208 | MDExOlB1bGxSZXF1ZXN0NTMzMDQ1NDUy | 1,166 | Opus montenegrinsubs | {
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"merging since the CI is fixed on master"
] | 2020-12-05T17:00:44Z | 2020-12-07T11:02:49Z | 2020-12-07T11:02:49Z | CONTRIBUTOR | null | 0 | {
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} | Opus montenegrinsubs - language pair en-me
more info : http://opus.nlpl.eu/MontenegrinSubs.php | {
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"Hi,\r\n\r\nthis was fixed by #1995, so you can wait for the next release or install the package directly from the master branch with the following command: \r\n```bash\r\npip install git+https://github.com/huggingface/datasets\r\n```",
"Ty!"
] | 2021-03-14T11:43:43Z | 2021-03-15T10:37:16Z | 2021-03-15T10:37:16Z | NONE | null | null | null | Summary
When loading timit_asr dataset on datasets 1.4+, every row in the dataset is the same
Steps to reproduce
As an example, on this code there is the text from the training part:
Code snippet:
```
from datasets import load_dataset, load_metric
timit = load_dataset("timit_asr")
timit['train']['text']
#['Would such an act of refusal be useful?',
# 'Would such an act of refusal be useful?',
# 'Would such an act of refusal be useful?',
# 'Would such an act of refusal be useful?',
# 'Would such an act of refusal be useful?',
# 'Would such an act of refusal be useful?',
```
The same behavior happens for other columns
Expected behavior:
Different info on the actual timit_asr dataset
Actual behavior:
When loading timit_asr dataset on datasets 1.4+, every row in the dataset is the same. I've checked datasets 1.3 and the rows are different
Debug info
Streamlit version: (get it with $ streamlit version)
Python version: Python 3.6.12
Using Conda? PipEnv? PyEnv? Pex? Using pip
OS version: Centos-release-7-9.2009.1.el7.centos.x86_64
Additional information
You can check the same behavior on https://huggingface.co/datasets/viewer/?dataset=timit_asr | {
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} | Adds the Winograd Schema Challenge, including configs for the more canonical wsc273 as well as wsc285 with 12 new examples.
- https://cs.nyu.edu/faculty/davise/papers/WinogradSchemas/WS.html
The data format was a bit of a nightmare but I think I got it to a workable format. | {
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https://api.github.com/repos/huggingface/datasets/issues/3003 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3003/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3003/comments | https://api.github.com/repos/huggingface/datasets/issues/3003/events | https://github.com/huggingface/datasets/pull/3003 | 1,014,137,933 | PR_kwDODunzps4smExP | 3,003 | common_language: Fix license in README.md | {
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"Locally the `make quality` passes with the same dependencies. I would suggest upgrading flake8. (I can take care of it in another PR)\r\ncc @lhoestq ",
"Thank you for fixing flake8! I think we are ready to merge then. "
] | 2021-12-04T20:54:49Z | 2021-12-14T10:28:55Z | 2021-12-14T10:28:55Z | CONTRIBUTOR | null | 0 | {
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} | Add typing overloads to Dataset.__getitem__ for mypy
Fixes #3337
**Iterable**
Iterable from `collections` cannot have a type, so you can't do `Iterable[int]` for example. `typing` has a Generic version that builds upon the one from `collections`.
**Flake8**
I had to add `# noqa: F811`, this is a bug from Flake8.
datasets uses flake8==3.7.9 which released in October 2019 if I update flake8 (4.0.1), I no longer get these errors, but I did not want to make the update without your approval. (It also triggers other errors like no args in f-strings.) | {
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Related to #2884, #2783 and #2619. | {
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https://api.github.com/repos/huggingface/datasets/issues/3223 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3223/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3223/comments | https://api.github.com/repos/huggingface/datasets/issues/3223/events | https://github.com/huggingface/datasets/pull/3223 | 1,046,445,507 | PR_kwDODunzps4uLb1E | 3,223 | Update BibTeX entry | {
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