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https://api.github.com/repos/huggingface/datasets/issues/2976 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2976/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2976/comments | https://api.github.com/repos/huggingface/datasets/issues/2976/events | https://github.com/huggingface/datasets/issues/2976 | 1,008,647,889 | I_kwDODunzps48Hr7R | 2,976 | Can't load dataset | {
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"Hi @mskovalova, \r\n\r\nSome datasets have multiple configurations. Therefore, in order to load them, you have to specify both the *dataset name* and the *configuration name*.\r\n\r\nIn the error message you got, you have a usage example:\r\n- To load the 'wikitext-103-raw-v1' configuration of the 'wikitext' datas... | 2021-09-27T21:38:14Z | 2022-12-01T09:12:29Z | 2021-09-28T06:53:01Z | NONE | null | null | null | I'm trying to load a wikitext dataset
```
from datasets import load_dataset
raw_datasets = load_dataset("wikitext")
```
ValueError: Config name is missing.
Please pick one among the available configs: ['wikitext-103-raw-v1', 'wikitext-2-raw-v1', 'wikitext-103-v1', 'wikitext-2-v1']
Example of usage:
`load_dataset('wikitext', 'wikitext-103-raw-v1')`.
If I try
```
from datasets import load_dataset
raw_datasets = load_dataset("wikitext-2-v1")
```
FileNotFoundError: Couldn't find file at https://raw.githubusercontent.com/huggingface/datasets/1.12.1/datasets/wikitext-2-v1/wikitext-2-v1.py
#### Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.12.1
- Platform: Linux-5.4.104+-x86_64-with-Ubuntu-18.04-bionic (colab)
- Python version: 3.7.12
- PyArrow version: 3.0.0
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https://api.github.com/repos/huggingface/datasets/issues/1833 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1833/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1833/comments | https://api.github.com/repos/huggingface/datasets/issues/1833/events | https://github.com/huggingface/datasets/pull/1833 | 803,120,978 | MDExOlB1bGxSZXF1ZXN0NTY5MDk5MTUx | 1,833 | Add OSCAR dataset card | {
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"@lhoestq Thanks for the suggestions! I agree with all of them. Should I accept them one by one or can I accept them all at once? When I try to load the whole diff GitHub is complaining and it does no render them well (probably my browser?) 😅 ",
"I just merged the tables as suggested 😄 . However I noticed somet... | 2021-02-08T01:39:49Z | 2021-02-12T14:09:25Z | 2021-02-12T14:08:24Z | CONTRIBUTOR | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/5057 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5057/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5057/comments | https://api.github.com/repos/huggingface/datasets/issues/5057/events | https://github.com/huggingface/datasets/pull/5057 | 1,394,827,216 | PR_kwDODunzps5AD4c6 | 5,057 | Support `converters` in `CsvBuilder` | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-10-03T14:23:21Z | 2022-10-04T11:19:28Z | 2022-10-04T11:17:32Z | CONTRIBUTOR | null | 0 | {
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} | Add the `converters` param to `CsvBuilder`, to help in situations like [this one](https://discuss.huggingface.co/t/typeerror-in-load-dataset-related-to-a-sequence-of-strings/23545).
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https://api.github.com/repos/huggingface/datasets/issues/4481 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4481/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4481/comments | https://api.github.com/repos/huggingface/datasets/issues/4481/events | https://github.com/huggingface/datasets/pull/4481 | 1,269,187,792 | PR_kwDODunzps45jIRi | 4,481 | Fix iwslt2017 | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"CI fails are just abut missing tags in the dataset card, merging !",
"FYI, \r\n\r\nThe checksums have not been edited from the changes of .tgz to .zip files, and as a result a `ExpectedMoreDownloadedFiles` error occurs. Updating th... | 2022-06-13T09:51:21Z | 2022-10-26T09:09:31Z | 2022-06-13T10:40:18Z | MEMBER | null | 0 | {
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} | The files were moved to google drive, I hosted them on the Hub instead (ok according to the license)
I also updated the `datasets_infos.json` | {
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https://api.github.com/repos/huggingface/datasets/issues/2439 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2439/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2439/comments | https://api.github.com/repos/huggingface/datasets/issues/2439/events | https://github.com/huggingface/datasets/pull/2439 | 908,511,983 | MDExOlB1bGxSZXF1ZXN0NjU5MTkzMDE3 | 2,439 | Better error message when trying to access elements of a DatasetDict without specifying the split | {
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} | As mentioned in #2437 it'd be nice to to have an indication to the users when they try to access an element of a DatasetDict without specifying the split name.
cc @thomwolf | {
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https://api.github.com/repos/huggingface/datasets/issues/3375 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3375/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3375/comments | https://api.github.com/repos/huggingface/datasets/issues/3375/events | https://github.com/huggingface/datasets/pull/3375 | 1,070,454,913 | PR_kwDODunzps4vWrXz | 3,375 | Support streaming zipped dataset repo by passing only repo name | {
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"I just tested and I think this only opens one file ? If there are several files in the ZIP, only the first one is opened. To open several files from a ZIP, one has to call `open` several times.\r\n\r\nWhat about updating the CSV loader to make it `download_and_extract` zip files, and open each extracted file ?",
... | 2021-12-03T10:43:05Z | 2021-12-16T18:03:32Z | 2021-12-16T18:03:31Z | MEMBER | null | 0 | {
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} | Proposed solution:
- I have added the method `iter_files` to DownloadManager and StreamingDownloadManager
- I use this in modules: "csv", "json", "text"
- I test for CSV/JSONL/TXT zipped (and non-zipped) files, both in streaming and non-streaming modes
Fix #3373. | {
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"@mariosasko @lhoestq Could you give me an update on how to load the dataset after the fix?\r\nThanks.",
"Hi @arda-vianai,\r\n\r\nfirst, you can try:\r\n```python\r\nimport datasets\r\ndataset = datasets.load_dataset('tuple_ie', 'all', revision=\"master\")\r\n```\r\nIf this doesn't work, your version of `datasets... | 2021-11-03T14:56:55Z | 2021-11-05T15:51:15Z | 2021-11-05T14:16:05Z | NONE | null | null | null | Hi,
`dataset = datasets.load_dataset('tuple_ie', 'all')`
returns a FileNotFound error. Is the data not available?
Many thanks.
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https://api.github.com/repos/huggingface/datasets/issues/2388 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2388/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2388/comments | https://api.github.com/repos/huggingface/datasets/issues/2388/events | https://github.com/huggingface/datasets/issues/2388 | 897,767,470 | MDU6SXNzdWU4OTc3Njc0NzA= | 2,388 | Incorrect URLs for some datasets | {
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"gists_ur... | null | [] | 2021-05-21T07:22:35Z | 2021-06-04T17:39:45Z | 2021-06-04T17:39:45Z | MEMBER | null | null | null | ## Describe the bug
It seems that the URLs for the following datasets are invalid:
- [ ] `bn_hate_speech` has been renamed: https://github.com/rezacsedu/Bengali-Hate-Speech-Dataset/commit/c67ecfc4184911e12814f6b36901f9828df8a63a
- [ ] `covid_tweets_japanese` has been renamed: http://www.db.info.gifu-u.ac.jp/covid-19-twitter-dataset/
As a result we can no longer load these datasets using `load_dataset`. The simple fix is to rename the URL in the dataset script - will do this asap.
## Steps to reproduce the bug
```python
from datasets import load_dataset
# pick one of the datasets from the list above
ds = load_dataset("bn_hate_speech")
```
## Expected results
Dataset loads without error.
## Actual results
```
Downloading: 3.36kB [00:00, 1.07MB/s]
Downloading: 2.03kB [00:00, 678kB/s]
Using custom data configuration default
Downloading and preparing dataset bn_hate_speech/default (download: 951.48 KiB, generated: 949.84 KiB, post-processed: Unknown size, total: 1.86 MiB) to /Users/lewtun/.cache/huggingface/datasets/bn_hate_speech/default/0.0.0/a2dc726e511a2177523301bcad196af05d4d8a2cff30d2769ba8aacc1f5fdb5c...
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/Users/lewtun/miniconda3/envs/hf-hub_eval/lib/python3.8/site-packages/datasets/load.py", line 744, in load_dataset
builder_instance.download_and_prepare(
File "/Users/lewtun/miniconda3/envs/hf-hub_eval/lib/python3.8/site-packages/datasets/builder.py", line 574, in download_and_prepare
self._download_and_prepare(
File "/Users/lewtun/miniconda3/envs/hf-hub_eval/lib/python3.8/site-packages/datasets/builder.py", line 630, in _download_and_prepare
split_generators = self._split_generators(dl_manager, **split_generators_kwargs)
File "/Users/lewtun/.cache/huggingface/modules/datasets_modules/datasets/bn_hate_speech/a2dc726e511a2177523301bcad196af05d4d8a2cff30d2769ba8aacc1f5fdb5c/bn_hate_speech.py", line 76, in _split_generators
train_path = dl_manager.download_and_extract(_URL)
File "/Users/lewtun/miniconda3/envs/hf-hub_eval/lib/python3.8/site-packages/datasets/utils/download_manager.py", line 287, in download_and_extract
return self.extract(self.download(url_or_urls))
File "/Users/lewtun/miniconda3/envs/hf-hub_eval/lib/python3.8/site-packages/datasets/utils/download_manager.py", line 195, in download
downloaded_path_or_paths = map_nested(
File "/Users/lewtun/miniconda3/envs/hf-hub_eval/lib/python3.8/site-packages/datasets/utils/py_utils.py", line 195, in map_nested
return function(data_struct)
File "/Users/lewtun/miniconda3/envs/hf-hub_eval/lib/python3.8/site-packages/datasets/utils/download_manager.py", line 218, in _download
return cached_path(url_or_filename, download_config=download_config)
File "/Users/lewtun/miniconda3/envs/hf-hub_eval/lib/python3.8/site-packages/datasets/utils/file_utils.py", line 281, in cached_path
output_path = get_from_cache(
File "/Users/lewtun/miniconda3/envs/hf-hub_eval/lib/python3.8/site-packages/datasets/utils/file_utils.py", line 621, in get_from_cache
raise FileNotFoundError("Couldn't find file at {}".format(url))
FileNotFoundError: Couldn't find file at https://raw.githubusercontent.com/rezacsedu/Bengali-Hate-Speech-Dataset/main/Bengali_%20Hate_Speech_Dataset_Subset.csv
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.6.2.dev0
- Platform: macOS-10.16-x86_64-i386-64bit
- Python version: 3.8.8
- PyArrow version: 3.0.0
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"Hi! We've recently made some improvements to `save_to_disk`/`list_to_disk` (100x faster in some scenarios), so it would help if you could install `datasets` directly from `main` (`pip install git+https://github.com/huggingface/datasets.git`) and re-run the \"benchmark\".",
"Great to hear! I'll give it a try when... | 2023-03-05T05:27:15Z | 2023-07-13T18:48:05Z | null | NONE | null | null | null | ### Describe the bug
I have downloaded `openwebtext` (~12GB) and filtered out a small amount of junk (it's still huge). Now, I would like to use this filtered version for future work. It seems I have two choices:
1. Use `load_dataset` each time, relying on the cache mechanism, and re-run my filtering.
2. `save_to_disk` and then use `load_from_disk` to load the filtered version.
The performance of these two approaches is wildly different:
* Using `load_dataset` takes about 20 seconds to load the dataset, and a few seconds to re-filter (thanks to the brilliant filter/map caching)
* Using `load_from_disk` takes 14 minutes! And the second time I tried, the session just crashed (on a machine with 32GB of RAM)
I don't know if you'd call this a bug, but it seems like there shouldn't need to be two methods to load from disk, or that they should not take such wildly different amounts of time, or that one should not crash. Or maybe that the docs could offer some guidance about when to pick which method and why two methods exist, or just how do most people do it?
Something I couldn't work out from reading the docs was this: can I modify a dataset from the hub, save it (locally) and use `load_dataset` to load it? This [post seemed to suggest that the answer is no](https://discuss.huggingface.co/t/save-and-load-datasets/9260).
### Steps to reproduce the bug
See above
### Expected behavior
Load times should be about the same.
### Environment info
- `datasets` version: 2.9.0
- Platform: Linux-5.10.102.1-microsoft-standard-WSL2-x86_64-with-glibc2.31
- Python version: 3.10.8
- PyArrow version: 11.0.0
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-08-12T17:39:06Z | 2022-08-14T10:43:18Z | 2022-08-14T10:28:49Z | CONTRIBUTOR | null | 0 | {
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"Thanks @JieyuZhao.\r\n\r\nI think this PR was superseded by your other PRs:\r\n- #1930\r\n- #2152 \r\n\r\nI'm closing this."
] | 2021-02-22T18:51:34Z | 2022-09-23T13:35:09Z | 2022-09-23T13:35:08Z | CONTRIBUTOR | null | 0 | {
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"Hi! This should be fixed in the latest (patch) release (run `pip install -U datasets` to install it). This behavior was due to a bug in our authentication logic."
] | 2023-08-02T20:20:26Z | 2023-08-21T18:18:27Z | 2023-08-21T18:18:27Z | NONE | null | null | null | ### Describe the bug
When calling `load_dataset` in a streamlit application running within a docker container, get a failure with the error message:
EmptyDatasetError: The directory at hf://datasets/fetch-rewards/inc-rings-2000@bea27cf60842b3641eae418f38864a2ec4cde684 doesn't contain any data files
Traceback:
File "/opt/conda/lib/python3.10/site-packages/streamlit/runtime/scriptrunner/script_runner.py", line 552, in _run_script
exec(code, module.__dict__)
File "/home/user/app/app.py", line 62, in <module>
dashboard()
File "/home/user/app/app.py", line 47, in dashboard
feat_dict, path_gml = load_data(hf_repo, model_gml_dict[selected_model], hf_token)
File "/opt/conda/lib/python3.10/site-packages/streamlit/runtime/caching/cache_utils.py", line 211, in wrapper
return cached_func(*args, **kwargs)
File "/opt/conda/lib/python3.10/site-packages/streamlit/runtime/caching/cache_utils.py", line 240, in __call__
return self._get_or_create_cached_value(args, kwargs)
File "/opt/conda/lib/python3.10/site-packages/streamlit/runtime/caching/cache_utils.py", line 266, in _get_or_create_cached_value
return self._handle_cache_miss(cache, value_key, func_args, func_kwargs)
File "/opt/conda/lib/python3.10/site-packages/streamlit/runtime/caching/cache_utils.py", line 320, in _handle_cache_miss
computed_value = self._info.func(*func_args, **func_kwargs)
File "/home/user/app/hf_interface.py", line 16, in load_data
hf_dataset = load_dataset(repo_id, use_auth_token=hf_token)
File "/opt/conda/lib/python3.10/site-packages/datasets/load.py", line 2109, in load_dataset
builder_instance = load_dataset_builder(
File "/opt/conda/lib/python3.10/site-packages/datasets/load.py", line 1795, in load_dataset_builder
dataset_module = dataset_module_factory(
File "/opt/conda/lib/python3.10/site-packages/datasets/load.py", line 1486, in dataset_module_factory
raise e1 from None
File "/opt/conda/lib/python3.10/site-packages/datasets/load.py", line 1476, in dataset_module_factory
).get_module()
File "/opt/conda/lib/python3.10/site-packages/datasets/load.py", line 1032, in get_module
else get_data_patterns(base_path, download_config=self.download_config)
File "/opt/conda/lib/python3.10/site-packages/datasets/data_files.py", line 458, in get_data_patterns
raise EmptyDatasetError(f"The directory at {base_path} doesn't contain any data files") from None
### Steps to reproduce the bug
```python
@st.cache_resource
def load_data(repo_id: str, hf_token=None):
"""Load data from HuggingFace Hub
"""
hf_dataset = load_dataset(repo_id, use_auth_token=hf_token)
hf_dataset = hf_dataset.map(lambda x: json.loads(x["ground_truth"]), remove_columns=["ground_truth"])
return hf_dataset
```
### Expected behavior
Expect to load.
Note: works fine with datasets==2.13.1
### Environment info
datasets==2.14.2,
Ubuntu bionic-based Docker container. | {
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https://api.github.com/repos/huggingface/datasets/issues/2971 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2971/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2971/comments | https://api.github.com/repos/huggingface/datasets/issues/2971/events | https://github.com/huggingface/datasets/issues/2971 | 1,007,696,522 | I_kwDODunzps48EDqK | 2,971 | masakhaner dataset load problem | {
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"Thanks for reporting, @ontocord. We are fixing the wrong metadata."
] | 2021-09-27T04:59:07Z | 2021-09-27T12:59:59Z | 2021-09-27T12:59:59Z | CONTRIBUTOR | null | null | null | ## Describe the bug
Masakhaner dataset is not loading
## Steps to reproduce the bug
```
from datasets import load_dataset
dataset = load_dataset("masakhaner",'amh')
```
## Expected results
Expected the return of a dataset
## Actual results
```
NonMatchingSplitsSizesError Traceback (most recent call last)
<ipython-input-3-a6abc1161d4c> in <module>()
1 from datasets import load_dataset
2
----> 3 dataset = load_dataset("masakhaner",'amh')
3 frames
/usr/local/lib/python3.7/dist-packages/datasets/utils/info_utils.py
in verify_splits(expected_splits, recorded_splits)
72 ]
73 if len(bad_splits) > 0:
---> 74 raise NonMatchingSplitsSizesError(str(bad_splits))
75 logger.info("All the splits matched successfully.")
76
NonMatchingSplitsSizesError: [{'expected': SplitInfo(name='train', num_bytes=639927, num_examples=1751, dataset_name='masakhaner'), 'recorded': SplitInfo(name='train', num_bytes=639911, num_examples=1750, dataset_name='masakhaner')}, {'expected': SplitInfo(name='validation', num_bytes=92768, num_examples=251, dataset_name='masakhaner'), 'recorded': SplitInfo(name='validation', num_bytes=92753, num_examples=250, dataset_name='masakhaner')}, {'expected': SplitInfo(name='test', num_bytes=184286, num_examples=501, dataset_name='masakhaner'), 'recorded': SplitInfo(name='test', num_bytes=184271, num_examples=500, dataset_name='masakhaner')}]
```
## Environment info
Google Colab
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} | ### What this fixes:
This PR resolves several issues I discovered in the documentation on the `datasets.filesystems` module ([this page](https://huggingface.co/docs/datasets/filesystems.html)).
### What were the issues?
When I originally tried implementing the code examples I faced several bugs attributed to:
- out of date [botocore](https://github.com/boto/botocore) call signatures
- capitalization errors in the `S3FileSystem` class name (written as `S3Filesystem` in one place)
- call signature errors for the `S3FileSystem` class constructor (uses parameter `sessions` instead of `session` in some places) (see [`s3fs`](https://s3fs.readthedocs.io/en/latest/api.html#s3fs.core.S3FileSystem) for where this constructor signature is defined)
### Testing/reviewing notes
Instructions for generating the documentation locally: [here](https://github.com/huggingface/datasets/tree/master/docs#generating-the-documentation). | {
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__Originally posted by @dependabot in https://github.com/discourse/discourse/pull/11373#issuecomment-738993432__ | {
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https://api.github.com/repos/huggingface/datasets/issues/2775 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2775/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2775/comments | https://api.github.com/repos/huggingface/datasets/issues/2775/events | https://github.com/huggingface/datasets/issues/2775 | 964,303,626 | MDU6SXNzdWU5NjQzMDM2MjY= | 2,775 | `generate_random_fingerprint()` deterministic with 🤗Transformers' `set_seed()` | {
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"I dug into what I believe is the root of this issue and added a repro in my comment. If this is better addressed as a cross-team issue, let me know and I can open an issue in the Transformers repo",
"Hi !\r\n\r\nIMO we shouldn't try to modify `set_seed` from transformers but maybe make `datasets` have its own RN... | 2021-08-09T19:28:51Z | 2021-08-26T08:30:54Z | null | NONE | null | null | null | ## Describe the bug
**Update:** I dug into this to try to reproduce the underlying issue, and I believe it's that `set_seed()` from the `transformers` library makes the "random" fingerprint identical each time. I believe this is still a bug, because `datasets` is used exactly this way in `transformers` after `set_seed()` has been called, and I think that using `set_seed()` is a standard procedure to aid reproducibility. I've added more details to reproduce this below.
Hi there! I'm using my own local dataset and custom preprocessing function. My preprocessing function seems to be unpickle-able, perhaps because it is from a closure (will debug this separately). I get this warning, which is expected:
https://github.com/huggingface/datasets/blob/450b9174765374111e5c6daab0ed294bc3d9b639/src/datasets/fingerprint.py#L260-L265
However, what's not expected is that the `datasets` actually _does_ seem to cache and reuse this dataset between runs! After that line, the next thing that's logged looks like:
```text
Loading cached processed dataset at /home/xxx/.cache/huggingface/datasets/csv/default-xxx/0.0.0/xxx/cache-xxx.arrow
```
The path is exactly the same each run (e.g., last 26 runs).
This becomes a problem because I'll pass in the `--max_eval_samples` flag to the HuggingFace example script I'm running off of ([run_swag.py](https://github.com/huggingface/transformers/blob/master/examples/pytorch/multiple-choice/run_swag.py)). The fact that the cached dataset is reused means this flag gets ignored. I'll try to load 100 examples, and it will load the full cached 1,000,000.
I think that
https://github.com/huggingface/datasets/blob/450b9174765374111e5c6daab0ed294bc3d9b639/src/datasets/fingerprint.py#L248
... is actually consistent because randomness is being controlled in HuggingFace/Transformers for reproducibility. I've added a demo of this below.
## Steps to reproduce the bug
```python
# Contents of print_fingerprint.py
from transformers import set_seed
from datasets.fingerprint import generate_random_fingerprint
set_seed(42)
print(generate_random_fingerprint())
```
```bash
for i in {0..10}; do
python print_fingerprint.py
done
1c80317fa3b1799d
1c80317fa3b1799d
1c80317fa3b1799d
1c80317fa3b1799d
1c80317fa3b1799d
1c80317fa3b1799d
1c80317fa3b1799d
1c80317fa3b1799d
1c80317fa3b1799d
1c80317fa3b1799d
1c80317fa3b1799d
```
## Expected results
After the "random hash" warning is emitted, a random hash is generated, and no outdated cached datasets are reused.
## Actual results
After the "random hash" warning is emitted, an identical hash is generated each time, and an outdated cached dataset is reused each run.
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.9.0
- Platform: Linux-5.8.0-1038-gcp-x86_64-with-glibc2.31
- Python version: 3.9.6
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"Thanks for pushing this :)\r\nOne minor comment regarding the PR itself - I noticed that some changes are coming from the upstream master, this might be due to a rebase. Would be nice if this PR doesn't include them for readabily, feel free to open a new one if necessary",
"Closing in favour https://github.com/h... | 2022-02-13T11:26:31Z | 2022-02-17T10:18:46Z | 2022-02-17T10:12:09Z | CONTRIBUTOR | null | 0 | {
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} | Checklist
- [x] Update circle ci yaml
- [x] Delete sphinx static & python files in docs dir
- [x] Update readme in docs dir
- [ ] Update docs config in setup.py | {
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https://api.github.com/repos/huggingface/datasets/issues/5250 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5250/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5250/comments | https://api.github.com/repos/huggingface/datasets/issues/5250/events | https://github.com/huggingface/datasets/pull/5250 | 1,451,720,030 | PR_kwDODunzps5DB-1y | 5,250 | Change release procedure to use only pull requests | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_5250). All of your documentation changes will be reflected on that endpoint.",
"The docs for this PR live [here](https://moon-ci-docs.huggingface... | 2022-11-16T14:35:32Z | 2022-11-22T16:30:58Z | 2022-11-22T16:27:48Z | MEMBER | null | 0 | {
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} | This PR changes the release procedure so that:
- it only make changes to main branch via pull requests
- it is no longer necessary to directly commit/push to main branch
Close #5251.
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"Thanks for opening a discussion :)\r\n\r\nNote that you can use `.remove_columns(...)` to keep only the ones you're interested in before calling `.to_pandas()`",
"Yes I can do that thank you!\r\n\r\nDo you think that conceptually my example should work? If not, I'm happy to close this issue. \r\n\r\nIf yes, I ca... | 2022-06-10T20:25:31Z | 2022-06-15T17:41:41Z | 2022-06-15T17:41:41Z | CONTRIBUTOR | null | null | null | **Is your feature request related to a problem? Please describe.**
I have a large dataset that I need to convert part of to pandas to do some further analysis. Calling `to_pandas` directly on it is expensive. So I thought I could simply select the columns that I want and then call `to_pandas`.
**Describe the solution you'd like**
```python
from datasets import Dataset
ds = Dataset.from_dict({'a': [1,2,3], 'b': [5,6,7], 'c': [8,9,10]})
pandas_df = ds.with_format(columns=['a', 'b']).to_pandas()
# I would expect `pandas_df` to only include a,b as column.
```
**Describe alternatives you've considered**
I could remove all columns that I don't want? But I don't know all of them in advance.
**Additional context**
I can probably make a PR with some pointers.
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https://api.github.com/repos/huggingface/datasets/issues/1810 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1810/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1810/comments | https://api.github.com/repos/huggingface/datasets/issues/1810/events | https://github.com/huggingface/datasets/issues/1810 | 799,168,650 | MDU6SXNzdWU3OTkxNjg2NTA= | 1,810 | Add Hateful Memes Dataset | {
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"I am not sure, but would `datasets.Sequence(datasets.Sequence(datasets.Sequence(datasets.Value(\"int\")))` work?",
"Also, I found the information for loading only subsets of the data [here](https://github.com/huggingface/datasets/blob/master/docs/source/splits.rst).",
"Hi @lhoestq,\r\n\r\nRequest you to check ... | 2021-02-02T10:53:59Z | 2021-12-08T12:03:59Z | null | CONTRIBUTOR | null | null | null | ## Add Hateful Memes Dataset
- **Name:** Hateful Memes
- **Description:** [https://ai.facebook.com/blog/hateful-memes-challenge-and-data-set]( https://ai.facebook.com/blog/hateful-memes-challenge-and-data-set)
- **Paper:** [https://arxiv.org/pdf/2005.04790.pdf](https://arxiv.org/pdf/2005.04790.pdf)
- **Data:** [This link](https://drivendata-competition-fb-hateful-memes-data.s3.amazonaws.com/XjiOc5ycDBRRNwbhRlgH.zip?AWSAccessKeyId=AKIARVBOBDCY4MWEDJKS&Signature=DaUuGgZWUgDHzEPPbyJ2PhSJ56Q%3D&Expires=1612816874)
- **Motivation:** Including multi-modal datasets to 🤗 datasets.
I will be adding this dataset. It requires the user to sign an agreement on DrivenData. So, it will be used with a manual download.
The issue with this dataset is that the images are of different sizes. The image datasets added so far (CIFAR-10 and MNIST) have a uniform shape throughout.
So something like
```python
datasets.Array2D(shape=(28, 28), dtype="uint8")
```
won't work for the images. How would I add image features then? I checked `datasets/features.py` but couldn't figure out the appropriate class for this. I'm assuming I would want to avoid re-sizing at all since we want the user to be able to access the original images.
Also, in case I want to load only a subset of the data, since the actual data is around 8.8GB, how would that be possible?
Thanks,
Gunjan | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-03-31T18:34:34Z | 2022-04-12T20:43:45Z | 2022-04-12T20:37:38Z | CONTRIBUTOR | null | 0 | {
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I've left the 'Values from popular papers' section empty for the time being because I don't know the summarization literature very well and am therefore not sure which paper(s) to pull from (note that the original rouge paper does not seem to present specific values, just correlations with human judgements). Any suggestions on which paper(s) to pull from would be helpful! :) | {
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https://api.github.com/repos/huggingface/datasets/issues/1637 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1637/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1637/comments | https://api.github.com/repos/huggingface/datasets/issues/1637/events | https://github.com/huggingface/datasets/pull/1637 | 774,710,014 | MDExOlB1bGxSZXF1ZXN0NTQ1NTc1NTMw | 1,637 | Added `pn_summary` dataset | {
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"As always, I got stuck in the correct order of imports 😅\r\n@lhoestq, It's finished!",
"@lhoestq, It's done! Is there anything else that needs changes?"
] | 2020-12-25T11:01:24Z | 2021-01-04T13:43:19Z | 2021-01-04T13:43:19Z | CONTRIBUTOR | null | 0 | {
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} | #1635
You did a great job with the fluent procedure regarding adding a dataset. I took the chance to add the dataset on my own. Thank you for your awesome job, and I hope this dataset found the researchers happy, specifically those interested in Persian Language (Farsi)! | {
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https://api.github.com/repos/huggingface/datasets/issues/4216 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4216/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4216/comments | https://api.github.com/repos/huggingface/datasets/issues/4216/events | https://github.com/huggingface/datasets/pull/4216 | 1,214,614,029 | PR_kwDODunzps42u1_w | 4,216 | Avoid recursion error in map if example is returned as dict value | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-04-25T14:40:32Z | 2022-05-04T17:20:06Z | 2022-05-04T17:12:52Z | CONTRIBUTOR | null | 0 | {
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} | I noticed this bug while answering [this question](https://discuss.huggingface.co/t/correct-way-to-create-a-dataset-from-a-csv-file/15686/11?u=mariosasko).
This code replicates the bug:
```python
from datasets import Dataset
dset = Dataset.from_dict({"en": ["aa", "bb"], "fr": ["cc", "dd"]})
dset.map(lambda ex: {"translation": ex})
```
and this is the fix for it (before this PR):
```python
from datasets import Dataset
dset = Dataset.from_dict({"en": ["aa", "bb"], "fr": ["cc", "dd"]})
dset.map(lambda ex: {"translation": dict(ex)})
```
Internally, this can be fixed by merging two dicts via dict unpacking (instead of `dict.update) `in `Dataset.map`, which avoids creating recursive dictionaries.
P.S. `{**a, **b}` is slightly more performant than `a.update(b)` in my bencmarks. | {
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https://api.github.com/repos/huggingface/datasets/issues/3525 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3525/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3525/comments | https://api.github.com/repos/huggingface/datasets/issues/3525/events | https://github.com/huggingface/datasets/pull/3525 | 1,093,831,268 | PR_kwDODunzps4wiL8p | 3,525 | Adding license information for Openbookcorpus | {
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"The MIT license seems to be for the crawling code, no ? Then maybe we can also redirect users to the [terms of smashwords.com](https://www.smashwords.com/about/tos) regarding copyrights, in particular the paragraph 10 for end-users. In particular it seems that end users can download and use the content \"for their... | 2022-01-04T23:20:36Z | 2022-04-20T09:54:30Z | 2022-04-20T09:48:10Z | CONTRIBUTOR | null | 0 | {
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} | Not entirely sure, following the links here, but it seems the relevant license is at https://github.com/soskek/bookcorpus/blob/master/LICENSE | {
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https://api.github.com/repos/huggingface/datasets/issues/1530 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1530/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1530/comments | https://api.github.com/repos/huggingface/datasets/issues/1530/events | https://github.com/huggingface/datasets/pull/1530 | 764,749,507 | MDExOlB1bGxSZXF1ZXN0NTM4NjY4ODI3 | 1,530 | add indonlu benchmark datasets | {
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} | The IndoNLU benchmark is a collection of resources for training, evaluating, and analyzing natural language understanding systems for the Indonesian language. There are 12 datasets in IndoNLU.
This is a new clean PR from [#1322](https://github.com/huggingface/datasets/pull/1322) | {
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https://api.github.com/repos/huggingface/datasets/issues/2556 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2556/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2556/comments | https://api.github.com/repos/huggingface/datasets/issues/2556/events | https://github.com/huggingface/datasets/issues/2556 | 931,595,872 | MDU6SXNzdWU5MzE1OTU4NzI= | 2,556 | Better DuplicateKeysError error to help the user debug the issue | {
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"excuse me, my `datasets` version is `2.2.2`, but I also just see the error info like \r\n```\r\nDuplicatedKeysError: FAILURE TO GENERATE DATASET !\r\nFound duplicate Key: 0\r\nKeys should be unique and deterministic in nature\r\n```",
"Hi ! for which dataset do you have this error ?\r\n\r\nAlso note that this is... | 2021-06-28T13:50:57Z | 2022-06-28T09:26:04Z | 2022-06-28T09:26:04Z | MEMBER | null | null | null | As mentioned in https://github.com/huggingface/datasets/issues/2552 it would be nice to improve the error message when a dataset fails to build because there are duplicate example keys.
The current one is
```python
datasets.keyhash.DuplicatedKeysError: FAILURE TO GENERATE DATASET !
Found duplicate Key: 48
Keys should be unique and deterministic in nature
```
and we could have something that guides the user to debugging the issue:
```python
DuplicateKeysError: both 42th and 1337th examples have the same keys `48`.
Please fix the dataset script at <path/to/the/dataset/script>
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/5741 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5741/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5741/comments | https://api.github.com/repos/huggingface/datasets/issues/5741/events | https://github.com/huggingface/datasets/pull/5741 | 1,665,860,919 | PR_kwDODunzps5OM9nZ | 5,741 | Fix CI warnings | {
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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... | 2023-04-13T07:17:02Z | 2023-04-13T09:48:10Z | 2023-04-13T09:40:50Z | MEMBER | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/2568 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2568/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2568/comments | https://api.github.com/repos/huggingface/datasets/issues/2568/events | https://github.com/huggingface/datasets/pull/2568 | 932,934,795 | MDExOlB1bGxSZXF1ZXN0NjgwMjE5MDU2 | 2,568 | Add interleave_datasets for map-style datasets | {
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} | ### Add interleave_datasets for map-style datasets
Add support for map-style datasets (i.e. `Dataset` objects) in `interleave_datasets`.
It was only supporting iterable datasets (i.e. `IterableDataset` objects).
### Implementation details
It works by concatenating the datasets and then re-order the indices to make the new dataset.
### TODO
- [x] tests
- [x] docs
Close #2563 | {
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https://api.github.com/repos/huggingface/datasets/issues/2428 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2428/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2428/comments | https://api.github.com/repos/huggingface/datasets/issues/2428/events | https://github.com/huggingface/datasets/pull/2428 | 907,169,746 | MDExOlB1bGxSZXF1ZXN0NjU4MDU2MjI3 | 2,428 | Add copyright info for wiki_lingua dataset | {
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"Build fails but this change should not be the reason...",
"rebased on master",
"rebased on master"
] | 2021-05-31T07:22:52Z | 2021-06-04T10:22:33Z | 2021-06-04T10:22:33Z | CONTRIBUTOR | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/5971 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5971/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5971/comments | https://api.github.com/repos/huggingface/datasets/issues/5971/events | https://github.com/huggingface/datasets/issues/5971 | 1,767,053,635 | I_kwDODunzps5pUxlD | 5,971 | Docs: make "repository structure" easier to find | {
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"Loading a local dataset also works the same way when `data_files` are not specified, so I agree we should make this info easier to discover \r\n\r\ncc @stevhliu ",
"Is this issue open? If so, I will self assign. ",
"@benjaminbrown038 Yes, it is. Maybe @stevhliu can give some pointers on improving this doc pag... | 2023-06-21T08:26:44Z | 2023-07-05T06:51:38Z | null | CONTRIBUTOR | null | null | null | The page https://huggingface.co/docs/datasets/repository_structure explains how to create a simple repository structure without a dataset script.
It's the simplest way to create a dataset and should be easier to find, particularly on the docs' first pages. | {
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https://api.github.com/repos/huggingface/datasets/issues/5916 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5916/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5916/comments | https://api.github.com/repos/huggingface/datasets/issues/5916/events | https://github.com/huggingface/datasets/pull/5916 | 1,732,456,392 | PR_kwDODunzps5RskTb | 5,916 | Unpin responses | {
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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... | 2023-05-30T14:59:48Z | 2023-05-30T18:03:10Z | 2023-05-30T17:53:29Z | CONTRIBUTOR | null | 0 | {
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} | Fix #5906 | {
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https://api.github.com/repos/huggingface/datasets/issues/3965 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3965/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3965/comments | https://api.github.com/repos/huggingface/datasets/issues/3965/events | https://github.com/huggingface/datasets/issues/3965 | 1,173,708,739 | I_kwDODunzps5F9V_D | 3,965 | TypeError: Couldn't cast array of type for JSONLines dataset | {
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"Hi @lewtun, thanks for reporting.\r\n\r\nIt seems that our library fails at inferring the dtype of the columns:\r\n- `milestone`\r\n- `performed_via_github_app` \r\n\r\n(and assigns them `null` dtype)."
] | 2022-03-18T15:17:53Z | 2022-05-06T16:13:51Z | 2022-05-06T16:13:51Z | MEMBER | null | null | null | ## Describe the bug
One of the [course participants](https://discuss.huggingface.co/t/chapter-5-questions/11744/20?u=lewtun) is having trouble loading a JSONLines dataset that's composed of the GitHub issues from `spacy` (see stack trace below).
This reminds me a bit of #2799 where one can load the dataset in `pandas` but not in `datasets` and perhaps increasing the `block_size` is needed again.
## Steps to reproduce the bug
```python
from datasets import load_dataset
from huggingface_hub import hf_hub_url
import pandas as pd
# returns 'https://huggingface.co/datasets/Evan/spaCy-github-issues/resolve/main/spacy-issues.jsonl'
data_files = hf_hub_url(repo_id="Evan/spaCy-github-issues", filename="spacy-issues.jsonl", repo_type="dataset")
# throws TypeError: Couldn't cast array of type
dset = load_dataset("json", data_files=data_files, split="test")
# no problem with pandas - note this take a while as the file is >2GB
df = pd.read_json(data_files, orient="records", lines=True)
df.head()
```
## Expected results
I can load any line-separated JSON file, similar to pandas.
## Actual results
```
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/Users/lewtun/miniconda3/envs/hf/lib/python3.9/site-packages/datasets/load.py", line 1702, in load_dataset
builder_instance.download_and_prepare(
File "/Users/lewtun/miniconda3/envs/hf/lib/python3.9/site-packages/datasets/builder.py", line 594, in download_and_prepare
self._download_and_prepare(
File "/Users/lewtun/miniconda3/envs/hf/lib/python3.9/site-packages/datasets/builder.py", line 683, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/Users/lewtun/miniconda3/envs/hf/lib/python3.9/site-packages/datasets/builder.py", line 1136, in _prepare_split
writer.write_table(table)
File "/Users/lewtun/miniconda3/envs/hf/lib/python3.9/site-packages/datasets/arrow_writer.py", line 511, in write_table
pa_table = table_cast(pa_table, self._schema)
File "/Users/lewtun/miniconda3/envs/hf/lib/python3.9/site-packages/datasets/table.py", line 1121, in table_cast
return cast_table_to_features(table, Features.from_arrow_schema(schema))
File "/Users/lewtun/miniconda3/envs/hf/lib/python3.9/site-packages/datasets/table.py", line 1102, in cast_table_to_features
arrays = [cast_array_to_feature(table[name], feature) for name, feature in features.items()]
File "/Users/lewtun/miniconda3/envs/hf/lib/python3.9/site-packages/datasets/table.py", line 1102, in <listcomp>
arrays = [cast_array_to_feature(table[name], feature) for name, feature in features.items()]
File "/Users/lewtun/miniconda3/envs/hf/lib/python3.9/site-packages/datasets/table.py", line 944, in wrapper
return func(array, *args, **kwargs)
File "/Users/lewtun/miniconda3/envs/hf/lib/python3.9/site-packages/datasets/table.py", line 918, in wrapper
return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
File "/Users/lewtun/miniconda3/envs/hf/lib/python3.9/site-packages/datasets/table.py", line 918, in <listcomp>
return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
File "/Users/lewtun/miniconda3/envs/hf/lib/python3.9/site-packages/datasets/table.py", line 1086, in cast_array_to_feature
return array_cast(array, feature(), allow_number_to_str=allow_number_to_str)
File "/Users/lewtun/miniconda3/envs/hf/lib/python3.9/site-packages/datasets/table.py", line 944, in wrapper
return func(array, *args, **kwargs)
File "/Users/lewtun/miniconda3/envs/hf/lib/python3.9/site-packages/datasets/table.py", line 920, in wrapper
return func(array, *args, **kwargs)
File "/Users/lewtun/miniconda3/envs/hf/lib/python3.9/site-packages/datasets/table.py", line 1019, in array_cast
raise TypeError(f"Couldn't cast array of type\n{array.type}\nto\n{pa_type}")
TypeError: Couldn't cast array of type
struct<url: string, html_url: string, labels_url: string, id: int64, node_id: string, number: int64, title: string, description: string, creator: struct<login: string, id: int64, node_id: string, avatar_url: string, gravatar_id: string, url: string, html_url: string, followers_url: string, following_url: string, gists_url: string, starred_url: string, subscriptions_url: string, organizations_url: string, repos_url: string, events_url: string, received_events_url: string, type: string, site_admin: bool>, open_issues: int64, closed_issues: int64, state: string, created_at: timestamp[s], updated_at: timestamp[s], due_on: null, closed_at: timestamp[s]>
to
null
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 2.0.0
- Platform: macOS-10.16-x86_64-i386-64bit
- Python version: 3.9.7
- PyArrow version: 7.0.0
- Pandas version: 1.4.1
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https://api.github.com/repos/huggingface/datasets/issues/5724 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5724/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5724/comments | https://api.github.com/repos/huggingface/datasets/issues/5724/events | https://github.com/huggingface/datasets/issues/5724 | 1,659,938,135 | I_kwDODunzps5i8KVX | 5,724 | Error after shuffling streaming IterableDatasets with downloaded dataset | {
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"Moving `\"en\"` to the end of the path instead of passing it as a config name should fix the error:\r\n```python\r\nimport datasets\r\ndataset = datasets.load_dataset('/path/to/your/data/dir/en', streaming=True, split='train')\r\ndataset = dataset.shuffle(buffer_size=10_000, seed=42)\r\nnext(iter(dataset))\r\n```\... | 2023-04-09T16:58:44Z | 2023-04-20T20:37:30Z | 2023-04-20T20:37:30Z | NONE | null | null | null | ### Describe the bug
I downloaded the C4 dataset, and used streaming IterableDatasets to read it. Everything went normal until I used `dataset = dataset.shuffle(seed=42, buffer_size=10_000)` to shuffle the dataset. Shuffled dataset will throw the following error when it is used by `next(iter(dataset))`:
```
File "/data/miniconda3/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 937, in __iter__
for key, example in ex_iterable:
File "/data/miniconda3/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 627, in __iter__
for x in self.ex_iterable:
File "/data/miniconda3/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 138, in __iter__
yield from self.generate_examples_fn(**kwargs_with_shuffled_shards)
File "/data/miniconda3/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 763, in wrapper
for key, table in generate_tables_fn(**kwargs):
File "/data/miniconda3/lib/python3.9/site-packages/datasets/packaged_modules/json/json.py", line 101, in _generate_tables
batch = f.read(self.config.chunksize)
File "/data/miniconda3/lib/python3.9/site-packages/datasets/download/streaming_download_manager.py", line 372, in read_with_retries
out = read(*args, **kwargs)
File "/data/miniconda3/lib/python3.9/gzip.py", line 300, in read
return self._buffer.read(size)
File "/data/miniconda3/lib/python3.9/_compression.py", line 68, in readinto
data = self.read(len(byte_view))
File "/data/miniconda3/lib/python3.9/gzip.py", line 487, in read
if not self._read_gzip_header():
File "/data/miniconda3/lib/python3.9/gzip.py", line 435, in _read_gzip_header
raise BadGzipFile('Not a gzipped file (%r)' % magic)
gzip.BadGzipFile: Not a gzipped file (b've')
```
I found that there is no problem to use the dataset in this way without shuffling. Also, use `dataset = datasets.load_dataset('c4', 'en', split='train', streaming=True)`, which will download the dataset on-the-fly instead of loading from the local file, will also not have problems even after shuffle.
### Steps to reproduce the bug
1. Download C4 dataset from https://huggingface.co/datasets/allenai/c4
2.
```
import datasets
dataset = datasets.load_dataset('/path/to/your/data/dir', 'en', streaming=True, split='train')
dataset = dataset.shuffle(buffer_size=10_000, seed=42)
next(iter(dataset))
```
### Expected behavior
`next(iter(dataset))` should give me a sample from the dataset
### Environment info
- `datasets` version: 2.11.0
- Platform: Linux-5.4.32-1-tlinux4-0001-x86_64-with-glibc2.28
- Python version: 3.9.16
- Huggingface_hub version: 0.13.1
- PyArrow version: 11.0.0
- Pandas version: 1.5.3 | {
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https://api.github.com/repos/huggingface/datasets/issues/5780 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5780/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5780/comments | https://api.github.com/repos/huggingface/datasets/issues/5780/events | https://github.com/huggingface/datasets/issues/5780 | 1,679,367,149 | I_kwDODunzps5kGRvt | 5,780 | TypeError: 'NoneType' object does not support item assignment | {
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} | [] | closed | false | null | [] | null | [] | 2023-04-22T06:22:43Z | 2023-04-23T08:49:18Z | 2023-04-23T08:49:18Z | NONE | null | null | null | command：
```
def load_datasets(formats, data_dir=datadir, data_files=datafile）：
dataset = load_dataset(formats, data_dir=datadir, data_files=datafile, split=split, streaming=True, **kwargs)
return dataset
raw_datasets = DatasetDict()
raw_datasets["train"] = load_datasets(“csv”, args.datadir, "train.csv", split=train_split)
raw_datasets["test"] = load_datasets(“csv”, args.datadir, "dev.csv", split=test_split)
raw_datasets = raw_datasets.cast_column("audio", Audio(sampling_rate=16000))
```
error：
```
main()
File "peft_adalora_whisper_large_training.py", line 502, in main
raw_datasets = raw_datasets.cast_column("audio", Audio(sampling_rate=16000))
File "/home/ybZhang/miniconda3/envs/whister/lib/python3.8/site-packages/datasets/dataset_dict.py", line 2015, in cast_column
info.features[column] = feature
TypeError: 'NoneType' object does not support item assignment
```
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https://api.github.com/repos/huggingface/datasets/issues/1788 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1788/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1788/comments | https://api.github.com/repos/huggingface/datasets/issues/1788/events | https://github.com/huggingface/datasets/pull/1788 | 795,544,422 | MDExOlB1bGxSZXF1ZXN0NTYyODc1NzA2 | 1,788 | Doc2dial rc | {
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} | [] | closed | false | null | [] | null | [] | 2021-01-27T23:51:00Z | 2021-01-28T18:46:13Z | 2021-01-28T18:46:13Z | CONTRIBUTOR | null | 1 | {
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https://api.github.com/repos/huggingface/datasets/issues/5725 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5725/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5725/comments | https://api.github.com/repos/huggingface/datasets/issues/5725/events | https://github.com/huggingface/datasets/issues/5725 | 1,660,455,202 | I_kwDODunzps5i-Iki | 5,725 | How to limit the number of examples in dataset, for testing? | {
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"Hi! You can use the `nrows` parameter for this:\r\n```python\r\ndata = load_dataset(\"json\", data_files=data_path, nrows=10)\r\n```",
"@mariosasko I get:\r\n\r\n`TypeError: __init__() got an unexpected keyword argument 'nrows'`",
"I misread the format in which the dataset is stored - the `nrows` parameter wo... | 2023-04-10T08:41:43Z | 2023-04-21T06:16:24Z | 2023-04-21T06:16:24Z | NONE | null | null | null | ### Describe the bug
I am using this command:
`data = load_dataset("json", data_files=data_path)`
However, I want to add a parameter, to limit the number of loaded examples to be 10, for development purposes, but can't find this simple parameter.
### Steps to reproduce the bug
In the description.
### Expected behavior
To be able to limit the number of examples
### Environment info
Nothing special | {
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https://api.github.com/repos/huggingface/datasets/issues/6118 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6118/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6118/comments | https://api.github.com/repos/huggingface/datasets/issues/6118/events | https://github.com/huggingface/datasets/issues/6118 | 1,835,940,417 | I_kwDODunzps5tbjpB | 6,118 | IterableDataset.from_generator() fails with pickle error when provided a generator or iterator | {
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} | [] | open | false | null | [] | null | [
"Hi! `IterableDataset.from_generator` expects a generator function, not the object (to be consistent with `Dataset.from_generator`).\r\n\r\nYou can fix the above snippet as follows:\r\n```python\r\ntrain_dataset = IterableDataset.from_generator(line_generator, fn_kwargs={\"files\": model_training_files})\r\n```"
] | 2023-08-04T01:45:04Z | 2023-08-17T17:58:27Z | null | NONE | null | null | null | ### Describe the bug
**Description**
Providing a generator in an instantiation of IterableDataset.from_generator() fails with `TypeError: cannot pickle 'generator' object` when the generator argument is supplied with a generator.
**Code example**
```
def line_generator(files: List[Path]):
if isinstance(files, str):
files = [Path(files)]
for file in files:
if isinstance(file, str):
file = Path(file)
yield from open(file,'r').readlines()
...
model_training_files = ['file1.txt', 'file2.txt', 'file3.txt']
train_dataset = IterableDataset.from_generator(generator=line_generator(model_training_files))
```
**Traceback**
Traceback (most recent call last):
File "/Library/Developer/CommandLineTools/Library/Frameworks/Python3.framework/Versions/3.9/lib/python3.9/contextlib.py", line 135, in __exit__
self.gen.throw(type, value, traceback)
File "/Users/d3p692/code/clem_bert/venv/lib/python3.9/site-packages/datasets/utils/py_utils.py", line 691, in _no_cache_fields
yield
File "/Users/d3p692/code/clem_bert/venv/lib/python3.9/site-packages/datasets/utils/py_utils.py", line 701, in dumps
dump(obj, file)
File "/Users/d3p692/code/clem_bert/venv/lib/python3.9/site-packages/datasets/utils/py_utils.py", line 676, in dump
Pickler(file, recurse=True).dump(obj)
File "/Users/d3p692/code/clem_bert/venv/lib/python3.9/site-packages/dill/_dill.py", line 394, in dump
StockPickler.dump(self, obj)
File "/Library/Developer/CommandLineTools/Library/Frameworks/Python3.framework/Versions/3.9/lib/python3.9/pickle.py", line 487, in dump
self.save(obj)
File "/Users/d3p692/code/clem_bert/venv/lib/python3.9/site-packages/datasets/utils/py_utils.py", line 666, in save
dill.Pickler.save(self, obj, save_persistent_id=save_persistent_id)
File "/Users/d3p692/code/clem_bert/venv/lib/python3.9/site-packages/dill/_dill.py", line 388, in save
StockPickler.save(self, obj, save_persistent_id)
File "/Library/Developer/CommandLineTools/Library/Frameworks/Python3.framework/Versions/3.9/lib/python3.9/pickle.py", line 560, in save
f(self, obj) # Call unbound method with explicit self
File "/Users/d3p692/code/clem_bert/venv/lib/python3.9/site-packages/dill/_dill.py", line 1186, in save_module_dict
StockPickler.save_dict(pickler, obj)
File "/Library/Developer/CommandLineTools/Library/Frameworks/Python3.framework/Versions/3.9/lib/python3.9/pickle.py", line 971, in save_dict
self._batch_setitems(obj.items())
File "/Library/Developer/CommandLineTools/Library/Frameworks/Python3.framework/Versions/3.9/lib/python3.9/pickle.py", line 997, in _batch_setitems
save(v)
File "/Users/d3p692/code/clem_bert/venv/lib/python3.9/site-packages/datasets/utils/py_utils.py", line 666, in save
dill.Pickler.save(self, obj, save_persistent_id=save_persistent_id)
File "/Users/d3p692/code/clem_bert/venv/lib/python3.9/site-packages/dill/_dill.py", line 388, in save
StockPickler.save(self, obj, save_persistent_id)
File "/Library/Developer/CommandLineTools/Library/Frameworks/Python3.framework/Versions/3.9/lib/python3.9/pickle.py", line 578, in save
rv = reduce(self.proto)
TypeError: cannot pickle 'generator' object
### Steps to reproduce the bug
1. Create a set of text files to iterate over.
2. Create a generator that returns the lines in each file until all files are exhausted.
3. Instantiate the dataset over the generator by instantiating an IterableDataset.from_generator().
4. Wait for the explosion.
### Expected behavior
I would expect that since the function claims to accept a generator that there would be no crash. Instead, I would expect the dataset to return all the lines in the files as queued up in the `line_generator()` function.
### Environment info
datasets.__version__ == '2.13.1'
Python 3.9.6
Platform: Darwin WE35261 22.5.0 Darwin Kernel Version 22.5.0: Thu Jun 8 22:22:22 PDT 2023; root:xnu-8796.121.3~7/RELEASE_X86_64 x86_64
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https://api.github.com/repos/huggingface/datasets/issues/1922 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1922/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1922/comments | https://api.github.com/repos/huggingface/datasets/issues/1922/events | https://github.com/huggingface/datasets/issues/1922 | 813,140,806 | MDU6SXNzdWU4MTMxNDA4MDY= | 1,922 | How to update the "wino_bias" dataset | {
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} | [] | open | false | null | [] | null | [
"Hi @JieyuZhao !\r\n\r\nYou can edit the dataset card of wino_bias to update the URL via a Pull Request. This would be really appreciated :)\r\n\r\nThe dataset card is the README.md file you can find at https://github.com/huggingface/datasets/tree/master/datasets/wino_bias\r\nAlso the homepage url is also mentioned... | 2021-02-22T05:39:39Z | 2021-02-22T10:35:59Z | null | CONTRIBUTOR | null | null | null | Hi all,
Thanks for the efforts to collect all the datasets! But I think there is a problem with the wino_bias dataset. The current link is not correct. How can I update that?
Thanks! | {
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https://api.github.com/repos/huggingface/datasets/issues/5589 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5589/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5589/comments | https://api.github.com/repos/huggingface/datasets/issues/5589/events | https://github.com/huggingface/datasets/pull/5589 | 1,603,535,704 | PR_kwDODunzps5K9K1i | 5,589 | Revert "pass the dataset features to the IterableDataset.from_generator" | {
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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==6.0.0\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... | 2023-02-28T17:52:04Z | 2023-09-24T10:07:33Z | 2023-03-21T14:18:18Z | MEMBER | null | 0 | {
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} | This reverts commit b91070b9c09673e2e148eec458036ab6a62ac042 (temporarily)
It hurts iterable dataset performance a lot (e.g. x4 slower because it encodes+decodes images unnecessarily). I think we need to fix this before re-adding it
cc @mariosasko @Hubert-Bonisseur | {
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} | The host of `docred` dataset has updated the `dev` data file. This PR:
- Updates the dev URL
- Updates dataset metadata
This PR also fixes the URL of the `train_distant` split, which was wrong.
Fix #2882. | {
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"Hi! \r\n\r\n`Dataset.sort` calls `df.sort_values` internally, and `df.sort_values` brings all the \"sort\" columns in memory, so sorting on multiple keys could be very expensive. This makes me think that maybe we can replace `df.sort_values` with `pyarrow.compute.sort_indices` - the latter can also sort on multipl... | 2023-01-16T09:22:26Z | 2023-02-24T16:15:11Z | 2023-02-24T16:15:11Z | NONE | null | null | null | ### Feature request
From discussion on forum: https://discuss.huggingface.co/t/datasets-dataset-sort-does-not-preserve-ordering/29065/1
`sort()` does not preserve ordering, and it does not support sorting on multiple columns, nor a key function.
The suggested solution:
> ... having something similar to pandas and be able to specify multiple columns for sorting. We’re already using pandas under the hood to do the sorting in datasets.
The suggested workaround:
> convert your dataset to pandas and use `df.sort_values()`
### Motivation
Preserved ordering when sorting is very handy when one needs to sort on multiple columns, A and B, so that e.g. whenever A is equal for two or more rows, B is kept sorted.
Having a parameter to do this in 🤗datasets would be cleaner than going through pandas and back, and it wouldn't add much complexity to the library.
Alternatives:
- the possibility to specify multiple keys to sort by with decreasing priority (suggested solution),
- the ability to provide a key function for sorting, so that one can manually specify the sorting criteria.
### Your contribution
I'll be happy to contribute by submitting a PR. Will get documented on `CONTRIBUTING.MD`.
Would love to get thoughts on this, if anyone has anything to add. | {
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"Sorry, it was us:[^1] https://github.com/iterative/cml/pull/1317 & https://github.com/iterative/cml/issues/1319#issuecomment-1385599559; should be fixed with [v0.18.17](https://github.com/iterative/cml/releases/tag/v0.18.17).\r\n\r\n[^1]: More or less, see https://github.com/yargs/yargs/issues/873.",
"Opened htt... | 2023-01-17T09:06:08Z | 2023-01-18T06:29:08Z | 2023-01-18T06:29:08Z | MEMBER | null | null | null | Once we find out the root cause of:
- #5431
we should revert the temporary pin on the Docker image version introduced by:
- #5432 | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-05-26T06:17:35Z | 2022-05-26T06:48:42Z | 2022-05-26T06:40:12Z | MEMBER | null | 0 | {
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} | The `spider` dataset is distributed under the [CC BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/legalcode) license.
Fix #4401. | {
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"We no longer host datasets in this repo. You should use the HF Hub instead."
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} | Fix missing tags in dataset cards:
- aslg_pc12
- librispeech_lm
- mwsc
- opus100
- qasc
- quail
- squadshifts
- winograd_wsc
This PR partially fixes the missing tags in dataset cards. Subsequent PRs will follow to complete this task.
Related to:
- #4833
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https://api.github.com/repos/huggingface/datasets/issues/2810 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2810/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2810/comments | https://api.github.com/repos/huggingface/datasets/issues/2810/events | https://github.com/huggingface/datasets/pull/2810 | 972,040,022 | MDExOlB1bGxSZXF1ZXN0NzEzNjkzMTI1 | 2,810 | Add WIT Dataset | {
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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/3557 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3557/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3557/comments | https://api.github.com/repos/huggingface/datasets/issues/3557/events | https://github.com/huggingface/datasets/pull/3557 | 1,097,946,034 | PR_kwDODunzps4wvIHl | 3,557 | Fix bug in `ImageClassifcation` task template | {
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"The CI failures are unrelated to the changes in this PR.",
"> The CI failures are unrelated to the changes in this PR.\r\n\r\nIt seems that some of the failures are due to the tests on the dataset cards (e.g. CIFAR, MNIST, FASHION_MNIST). Perhaps it's worth addressing those in this PR to avoid confusing downstre... | 2022-01-10T14:09:59Z | 2022-01-11T15:47:52Z | 2022-01-11T15:47:52Z | CONTRIBUTOR | null | 0 | {
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} | Fixes a bug in the `ImageClassification` task template which requires specifying class labels twice in dataset scripts. Additionally, this PR refactors the API around the classification task templates for cleaner `labels` handling.
CC: @lewtun @nateraw | {
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https://api.github.com/repos/huggingface/datasets/issues/5843 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5843/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5843/comments | https://api.github.com/repos/huggingface/datasets/issues/5843/events | https://github.com/huggingface/datasets/issues/5843 | 1,705,514,551 | I_kwDODunzps5lqBY3 | 5,843 | Can't add iterable datasets to a Dataset Dict. | {
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"Transferring as this is relating to the 🤗 Datasets library",
"You need to use `IterableDatasetDict` instead of `DatasetDict` for iterable datasets."
] | 2023-05-11T02:09:29Z | 2023-05-25T04:51:59Z | 2023-05-25T04:51:59Z | NONE | null | null | null | ### System Info
standard env
### Who can help?
_No response_
### Information
- [ ] The official example scripts
- [X] My own modified scripts
### Tasks
- [ ] An officially supported task in the `examples` folder (such as GLUE/SQuAD, ...)
- [ ] My own task or dataset (give details below)
### Reproduction
Get the following error:
TypeError: Values in `DatasetDict` should be of type `Dataset` but got type '<class 'datasets.iterable_dataset.IterableDataset'>'
### Expected behavior
should be able to add iterable datasets to a dataset dict | {
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https://api.github.com/repos/huggingface/datasets/issues/1533 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1533/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1533/comments | https://api.github.com/repos/huggingface/datasets/issues/1533/events | https://github.com/huggingface/datasets/pull/1533 | 764,835,913 | MDExOlB1bGxSZXF1ZXN0NTM4NzE4MDAz | 1,533 | add id_panl_bppt, a parallel corpus for en-id | {
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"Hi @lhoestq, thanks for the review. I will have a look and update it accordingly.",
"Strange error message :-)\r\n\r\n```\r\n> tf_context = tf.python.context.context() # eager mode context\r\nE AttributeError: module 'tensorflow' has no attribute 'python'\r\n```\r\n"
] | 2020-12-13T03:11:27Z | 2020-12-21T10:40:36Z | 2020-12-21T10:40:36Z | CONTRIBUTOR | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/3667 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3667/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3667/comments | https://api.github.com/repos/huggingface/datasets/issues/3667/events | https://github.com/huggingface/datasets/pull/3667 | 1,122,060,630 | PR_kwDODunzps4x-Ujt | 3,667 | Process .opus files with torchaudio | {
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"Note that torchaudio is maybe less practical to use for TF or JAX users.\r\nThis is not in the scope of this PR, but in the future if we manage to find a way to let the user control the decoding it would be nice",
"> Note that torchaudio is maybe less practical to use for TF or JAX users. This is not in the scop... | 2022-02-02T15:23:14Z | 2022-02-04T15:29:38Z | 2022-02-04T15:29:38Z | CONTRIBUTOR | null | 1 | {
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} | @anton-l suggested to proccess .opus files with `torchaudio` instead of `soundfile` as it's faster:
(moreover, I didn't manage to load .opus files with `soundfile` / `librosa` locally on any my machine anyway for some reason, even with `ffmpeg` installed).
For now my current changes work with locally stored file:
```python
# download sample opus file (from MultilingualSpokenWords dataset)
!wget https://huggingface.co/datasets/polinaeterna/test_opus/resolve/main/common_voice_tt_17737010.opus
from datasets import Dataset, Audio
audio_path = "common_voice_tt_17737010.opus"
dataset = Dataset.from_dict({"audio": [audio_path]}).cast_column("audio", Audio(48000))
dataset[0]
# {'audio': {'path': 'common_voice_tt_17737010.opus',
# 'array': array([ 0.0000000e+00, 0.0000000e+00, 3.0517578e-05, ...,
# -6.1035156e-05, 6.1035156e-05, 0.0000000e+00], dtype=float32),
# 'sampling_rate': 48000}}
```
But it doesn't work when loading inside s dataset from bytes (I checked on [MultilingualSpokenWords](https://github.com/huggingface/datasets/pull/3666), the PR is a draft now, maybe the bug is somewhere there )
```python
import torchaudio
with open(audio_path, "rb") as b:
print(torchaudio.load(b))
# RuntimeError: Error loading audio file: failed to open file <in memory buffer>
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/4832 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4832/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4832/comments | https://api.github.com/repos/huggingface/datasets/issues/4832/events | https://github.com/huggingface/datasets/pull/4832 | 1,336,727,389 | PR_kwDODunzps49EQav | 4,832 | Fix tags in dataset cards | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"The non-passing tests are caused by other missing information in the dataset cards."
] | 2022-08-12T04:11:23Z | 2022-08-12T04:41:55Z | 2022-08-12T04:27:24Z | MEMBER | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/3337 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3337/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3337/comments | https://api.github.com/repos/huggingface/datasets/issues/3337/events | https://github.com/huggingface/datasets/issues/3337 | 1,066,232,936 | I_kwDODunzps4_jWxo | 3,337 | Typing of Dataset.__getitem__ could be improved. | {
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"Hi ! Thanks for the suggestion, I didn't know about this decorator.\r\n\r\nIf you are interesting in contributing, feel free to open a pull request to add the overload methods for each typing combination :) To assign you to this issue, you can comment `#self-assign` in this thread.\r\n\r\n`Dataset.__getitem__` is ... | 2021-11-29T16:20:11Z | 2021-12-14T10:28:54Z | 2021-12-14T10:28:54Z | CONTRIBUTOR | null | null | null | ## Describe the bug
The newly added typing for Dataset.__getitem__ is Union[Dict, List]. This makes tools like mypy a bit awkward to use as we need to check the type manually. We could use type overloading to make this easier. [Documentation](https://docs.python.org/3/library/typing.html#typing.overload)
## Steps to reproduce the bug
Let's have a file `test.py`
```python
from typing import List, Dict, Any
from datasets import Dataset
ds = Dataset.from_dict({
'a': [1,2,3],
'b': ["1", "2", "3"]
})
one_colum: List[str] = ds['a']
some_index: Dict[Any, Any] = ds[1]
```
## Expected results
Running `mypy test.py` should not give any error.
## Actual results
```
test.py:10: error: Incompatible types in assignment (expression has type "Union[Dict[Any, Any], List[Any]]", variable has type "List[str]")
test.py:11: error: Incompatible types in assignment (expression has type "Union[Dict[Any, Any], List[Any]]", variable has type "Dict[Any, Any]")
Found 2 errors in 1 file (checked 1 source file)
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.13.3
- Platform: macOS-10.16-x86_64-i386-64bit
- Python version: 3.8.8
- PyArrow version: 6.0.1
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-08-25T10:16:40Z | 2022-08-30T06:21:54Z | 2022-08-25T13:19:41Z | MEMBER | null | 0 | {
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- https://github.com/zeerakahmed/makhzan/issues/43 | {
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https://api.github.com/repos/huggingface/datasets/issues/1211 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1211/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1211/comments | https://api.github.com/repos/huggingface/datasets/issues/1211/events | https://github.com/huggingface/datasets/pull/1211 | 757,973,719 | MDExOlB1bGxSZXF1ZXN0NTMzMjMxNDY3 | 1,211 | Add large spanish corpus | {
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} | Adds a collection of Spanish corpora that can be useful for pretraining language models.
Following a nice suggestion from @yjernite we provide the user with three main ways to preprocess / load either
* the whole corpus (17GB!)
* one specific sub-corpus
* the whole corpus, but return a single split. this is useful if you want to cache the whole preprocessing step once and interact with individual sub-corpora
See the dataset card for more details.
Ready for review! | {
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https://api.github.com/repos/huggingface/datasets/issues/5877 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5877/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5877/comments | https://api.github.com/repos/huggingface/datasets/issues/5877/events | https://github.com/huggingface/datasets/issues/5877 | 1,717,983,961 | I_kwDODunzps5mZlrZ | 5,877 | Request for text deduplication feature | {
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"The \"exact match\" deduplication will be possible when we resolve https://github.com/huggingface/datasets/issues/2514 (first, https://github.com/apache/arrow/issues/30950 needs to be addressed on the Arrow side). In the meantime, you can use Polars or DuckDB (e.g., via [datasets-sql](https://github.com/mariosasko... | 2023-05-20T01:56:00Z | 2023-07-26T21:42:14Z | null | NONE | null | null | null | ### Feature request
It would be great if there would be support for high performance, highly scalable text deduplication algorithms as part of the datasets library.
### Motivation
Motivated by this blog post https://huggingface.co/blog/dedup and this library https://github.com/google-research/deduplicate-text-datasets, but slightly frustrated by how its not very easy to work with these tools I am proposing this feature.
### Your contribution
I would be happy to contribute to the development effort of this feature. would love to collaborate with others in the development effort. | {
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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... | 2023-03-23T15:41:09Z | 2023-03-23T16:23:11Z | 2023-03-23T16:14:52Z | MEMBER | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/4821 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4821/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4821/comments | https://api.github.com/repos/huggingface/datasets/issues/4821/events | https://github.com/huggingface/datasets/pull/4821 | 1,335,664,588 | PR_kwDODunzps49AvaE | 4,821 | Fix train_test_split docs | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-08-11T08:55:45Z | 2022-08-11T09:59:29Z | 2022-08-11T09:45:40Z | CONTRIBUTOR | null | 0 | {
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} | I saw that `stratify` is added to the `train_test_split` method as per #4322, hence the docs can be updated. | {
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**Link:** *link to the dataset viewer page*
*short description of the issue*
Am I the one who added this dataset ? Yes-No
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"Hi @Shilpac20,\r\n\r\nAs explained in the Wikipedia dataset card: https://huggingface.co/datasets/wikipedia\r\n> You can find the full list of languages and dates [here](https://dumps.wikimedia.org/backup-index.html).\r\n\r\nThis means that, before passing a specific date, you should first make sure it is availabl... | 2022-08-30T16:15:46Z | 2022-12-04T22:20:33Z | null | NONE | null | null | null | ## Describe the bug
Hi, I am currently trying to download wikipedia dataset using
load_dataset("wikipedia", language="aa", date="20220401", split="train",beam_runner='DirectRunner'). However, I end up in getting filenotfound error. I get this error for any language I try to download.
Environment:
## Steps to reproduce the bug
```python
from datasets import load_dataset
load_dataset("wikipedia", language="aa", date="20220401", split="train",beam_runner='DirectRunner')
```
## Expected results
to load the dataset
## Actual results
I am pasting the error trace here:
Downloading builder script: 35.9kB [00:00, ?B/s]
Downloading metadata: 30.4kB [00:00, 1.94MB/s]
Using custom data configuration 20220401.aa-date=20220401,language=aa
Downloading and preparing dataset wikipedia/20220401.aa to C:\Users\Shilpa\.cache\huggingface\datasets\wikipedia\20220401.aa-date=20220401,language=aa\2.0.0\aa542ed919df55cc5d3347f42dd4521d05ca68751f50dbc32bae2a7f1e167559...
Downloading data: 100%|████████████████████████████████████████████████████████████| 11.1k/11.1k [00:00<00:00, 712kB/s]
Downloading data files: 100%|████████████████████████████████████████████████████████████| 1/1 [00:02<00:00, 2.82s/it]
Extracting data files: 100%|█████████████████████████████████████████████████████████████████████| 1/1 [00:00<?, ?it/s]
Downloading data: 100%|███████████████████████████████████████████████████████████| 35.6k/35.6k [00:00<00:00, 84.3kB/s]
Downloading data files: 100%|████████████████████████████████████████████████████████████| 1/1 [00:02<00:00, 2.93s/it]
Traceback (most recent call last):
File "apache_beam\runners\common.py", line 1417, in apache_beam.runners.common.DoFnRunner.process
File "apache_beam\runners\common.py", line 837, in apache_beam.runners.common.PerWindowInvoker.invoke_process
File "apache_beam\runners\common.py", line 981, in apache_beam.runners.common.PerWindowInvoker._invoke_process_per_window
File "apache_beam\runners\common.py", line 1571, in apache_beam.runners.common._OutputHandler.handle_process_outputs
File "G:\Python3.7\lib\site-packages\apache_beam\io\iobase.py", line 1193, in process
self.writer = self.sink.open_writer(init_result, str(uuid.uuid4()))
File "G:\Python3.7\lib\site-packages\apache_beam\options\value_provider.py", line 193, in _f
return fnc(self, *args, **kwargs)
File "G:\Python3.7\lib\site-packages\apache_beam\io\filebasedsink.py", line 202, in open_writer
return FileBasedSinkWriter(self, writer_path)
File "G:\Python3.7\lib\site-packages\apache_beam\io\filebasedsink.py", line 419, in __init__
self.temp_handle = self.sink.open(temp_shard_path)
File "G:\Python3.7\lib\site-packages\apache_beam\io\parquetio.py", line 553, in open
self._file_handle = super().open(temp_path)
File "G:\Python3.7\lib\site-packages\apache_beam\options\value_provider.py", line 193, in _f
return fnc(self, *args, **kwargs)
File "G:\Python3.7\lib\site-packages\apache_beam\io\filebasedsink.py", line 139, in open
temp_path, self.mime_type, self.compression_type)
File "G:\Python3.7\lib\site-packages\apache_beam\io\filesystems.py", line 224, in create
return filesystem.create(path, mime_type, compression_type)
File "G:\Python3.7\lib\site-packages\apache_beam\io\localfilesystem.py", line 163, in create
return self._path_open(path, 'wb', mime_type, compression_type)
File "G:\Python3.7\lib\site-packages\apache_beam\io\localfilesystem.py", line 140, in _path_open
raw_file = io.open(path, mode)
FileNotFoundError: [Errno 2] No such file or directory: 'C:\\Users\\Shilpa\\.cache\\huggingface\\datasets\\wikipedia\\20220401.aa-date=20220401,language=aa\\2.0.0\\aa542ed919df55cc5d3347f42dd4521d05ca68751f50dbc32bae2a7f1e167559.incomplete\\beam-temp-wikipedia-train-880233e8287e11edaf9d3ca067f2714e\\20a05238-6106-4420-a713-4eca6dd5959a.wikipedia-train'
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "G:/abc/temp.py", line 32, in <module>
beam_runner='DirectRunner')
File "G:\Python3.7\lib\site-packages\datasets\load.py", line 1751, in load_dataset
use_auth_token=use_auth_token,
File "G:\Python3.7\lib\site-packages\datasets\builder.py", line 705, in download_and_prepare
dl_manager=dl_manager, verify_infos=verify_infos, **download_and_prepare_kwargs
File "G:\Python3.7\lib\site-packages\datasets\builder.py", line 1394, in _download_and_prepare
pipeline_results = pipeline.run()
File "G:\Python3.7\lib\site-packages\apache_beam\pipeline.py", line 574, in run
return self.runner.run_pipeline(self, self._options)
File "G:\Python3.7\lib\site-packages\apache_beam\runners\direct\direct_runner.py", line 131, in run_pipeline
return runner.run_pipeline(pipeline, options)
File "G:\Python3.7\lib\site-packages\apache_beam\runners\portability\fn_api_runner\fn_runner.py", line 201, in run_pipeline
options)
File "G:\Python3.7\lib\site-packages\apache_beam\runners\portability\fn_api_runner\fn_runner.py", line 212, in run_via_runner_api
return self.run_stages(stage_context, stages)
File "G:\Python3.7\lib\site-packages\apache_beam\runners\portability\fn_api_runner\fn_runner.py", line 443, in run_stages
runner_execution_context, bundle_context_manager, bundle_input)
File "G:\Python3.7\lib\site-packages\apache_beam\runners\portability\fn_api_runner\fn_runner.py", line 776, in _execute_bundle
bundle_manager))
File "G:\Python3.7\lib\site-packages\apache_beam\runners\portability\fn_api_runner\fn_runner.py", line 1000, in _run_bundle
data_input, data_output, input_timers, expected_timer_output)
File "G:\Python3.7\lib\site-packages\apache_beam\runners\portability\fn_api_runner\fn_runner.py", line 1309, in process_bundle
result_future = self._worker_handler.control_conn.push(process_bundle_req)
File "G:\Python3.7\lib\site-packages\apache_beam\runners\portability\fn_api_runner\worker_handlers.py", line 380, in push
response = self.worker.do_instruction(request)
File "G:\Python3.7\lib\site-packages\apache_beam\runners\worker\sdk_worker.py", line 598, in do_instruction
getattr(request, request_type), request.instruction_id)
File "G:\Python3.7\lib\site-packages\apache_beam\runners\worker\sdk_worker.py", line 635, in process_bundle
bundle_processor.process_bundle(instruction_id))
File "G:\Python3.7\lib\site-packages\apache_beam\runners\worker\bundle_processor.py", line 1004, in process_bundle
element.data)
File "G:\Python3.7\lib\site-packages\apache_beam\runners\worker\bundle_processor.py", line 227, in process_encoded
self.output(decoded_value)
File "apache_beam\runners\worker\operations.py", line 526, in apache_beam.runners.worker.operations.Operation.output
File "apache_beam\runners\worker\operations.py", line 528, in apache_beam.runners.worker.operations.Operation.output
File "apache_beam\runners\worker\operations.py", line 237, in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
File "apache_beam\runners\worker\operations.py", line 240, in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
File "apache_beam\runners\worker\operations.py", line 907, in apache_beam.runners.worker.operations.DoOperation.process
File "apache_beam\runners\worker\operations.py", line 908, in apache_beam.runners.worker.operations.DoOperation.process
File "apache_beam\runners\common.py", line 1419, in apache_beam.runners.common.DoFnRunner.process
File "apache_beam\runners\common.py", line 1491, in apache_beam.runners.common.DoFnRunner._reraise_augmented
File "apache_beam\runners\common.py", line 1417, in apache_beam.runners.common.DoFnRunner.process
File "apache_beam\runners\common.py", line 623, in apache_beam.runners.common.SimpleInvoker.invoke_process
File "apache_beam\runners\common.py", line 1581, in apache_beam.runners.common._OutputHandler.handle_process_outputs
File "apache_beam\runners\common.py", line 1694, in apache_beam.runners.common._OutputHandler._write_value_to_tag
File "apache_beam\runners\worker\operations.py", line 240, in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
File "apache_beam\runners\worker\operations.py", line 907, in apache_beam.runners.worker.operations.DoOperation.process
File "apache_beam\runners\worker\operations.py", line 908, in apache_beam.runners.worker.operations.DoOperation.process
File "apache_beam\runners\common.py", line 1419, in apache_beam.runners.common.DoFnRunner.process
File "apache_beam\runners\common.py", line 1491, in apache_beam.runners.common.DoFnRunner._reraise_augmented
File "apache_beam\runners\common.py", line 1417, in apache_beam.runners.common.DoFnRunner.process
File "apache_beam\runners\common.py", line 623, in apache_beam.runners.common.SimpleInvoker.invoke_process
File "apache_beam\runners\common.py", line 1581, in apache_beam.runners.common._OutputHandler.handle_process_outputs
File "apache_beam\runners\common.py", line 1694, in apache_beam.runners.common._OutputHandler._write_value_to_tag
File "apache_beam\runners\worker\operations.py", line 240, in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
File "apache_beam\runners\worker\operations.py", line 907, in apache_beam.runners.worker.operations.DoOperation.process
File "apache_beam\runners\worker\operations.py", line 908, in apache_beam.runners.worker.operations.DoOperation.process
File "apache_beam\runners\common.py", line 1419, in apache_beam.runners.common.DoFnRunner.process
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File "apache_beam\runners\common.py", line 837, in apache_beam.runners.common.PerWindowInvoker.invoke_process
File "apache_beam\runners\common.py", line 981, in apache_beam.runners.common.PerWindowInvoker._invoke_process_per_window
File "apache_beam\runners\common.py", line 1581, in apache_beam.runners.common._OutputHandler.handle_process_outputs
File "apache_beam\runners\common.py", line 1694, in apache_beam.runners.common._OutputHandler._write_value_to_tag
File "apache_beam\runners\worker\operations.py", line 240, in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
File "apache_beam\runners\worker\operations.py", line 907, in apache_beam.runners.worker.operations.DoOperation.process
File "apache_beam\runners\worker\operations.py", line 908, in apache_beam.runners.worker.operations.DoOperation.process
File "apache_beam\runners\common.py", line 1419, in apache_beam.runners.common.DoFnRunner.process
File "apache_beam\runners\common.py", line 1491, in apache_beam.runners.common.DoFnRunner._reraise_augmented
File "apache_beam\runners\common.py", line 1417, in apache_beam.runners.common.DoFnRunner.process
File "apache_beam\runners\common.py", line 623, in apache_beam.runners.common.SimpleInvoker.invoke_process
File "apache_beam\runners\common.py", line 1581, in apache_beam.runners.common._OutputHandler.handle_process_outputs
File "apache_beam\runners\common.py", line 1694, in apache_beam.runners.common._OutputHandler._write_value_to_tag
File "apache_beam\runners\worker\operations.py", line 324, in apache_beam.runners.worker.operations.GeneralPurposeConsumerSet.receive
File "apache_beam\runners\worker\operations.py", line 905, in apache_beam.runners.worker.operations.DoOperation.process
File "apache_beam\runners\worker\operations.py", line 907, in apache_beam.runners.worker.operations.DoOperation.process
File "apache_beam\runners\worker\operations.py", line 908, in apache_beam.runners.worker.operations.DoOperation.process
File "apache_beam\runners\common.py", line 1419, in apache_beam.runners.common.DoFnRunner.process
File "apache_beam\runners\common.py", line 1491, in apache_beam.runners.common.DoFnRunner._reraise_augmented
File "apache_beam\runners\common.py", line 1417, in apache_beam.runners.common.DoFnRunner.process
File "apache_beam\runners\common.py", line 623, in apache_beam.runners.common.SimpleInvoker.invoke_process
File "apache_beam\runners\common.py", line 1581, in apache_beam.runners.common._OutputHandler.handle_process_outputs
File "apache_beam\runners\common.py", line 1694, in apache_beam.runners.common._OutputHandler._write_value_to_tag
File "apache_beam\runners\worker\operations.py", line 240, in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
File "apache_beam\runners\worker\operations.py", line 907, in apache_beam.runners.worker.operations.DoOperation.process
File "apache_beam\runners\worker\operations.py", line 908, in apache_beam.runners.worker.operations.DoOperation.process
File "apache_beam\runners\common.py", line 1419, in apache_beam.runners.common.DoFnRunner.process
File "apache_beam\runners\common.py", line 1491, in apache_beam.runners.common.DoFnRunner._reraise_augmented
File "apache_beam\runners\common.py", line 1417, in apache_beam.runners.common.DoFnRunner.process
File "apache_beam\runners\common.py", line 837, in apache_beam.runners.common.PerWindowInvoker.invoke_process
File "apache_beam\runners\common.py", line 981, in apache_beam.runners.common.PerWindowInvoker._invoke_process_per_window
File "apache_beam\runners\common.py", line 1581, in apache_beam.runners.common._OutputHandler.handle_process_outputs
File "apache_beam\runners\common.py", line 1694, in apache_beam.runners.common._OutputHandler._write_value_to_tag
File "apache_beam\runners\worker\operations.py", line 240, in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
File "apache_beam\runners\worker\operations.py", line 907, in apache_beam.runners.worker.operations.DoOperation.process
File "apache_beam\runners\worker\operations.py", line 908, in apache_beam.runners.worker.operations.DoOperation.process
File "apache_beam\runners\common.py", line 1419, in apache_beam.runners.common.DoFnRunner.process
File "apache_beam\runners\common.py", line 1507, in apache_beam.runners.common.DoFnRunner._reraise_augmented
File "apache_beam\runners\common.py", line 1417, in apache_beam.runners.common.DoFnRunner.process
File "apache_beam\runners\common.py", line 837, in apache_beam.runners.common.PerWindowInvoker.invoke_process
File "apache_beam\runners\common.py", line 981, in apache_beam.runners.common.PerWindowInvoker._invoke_process_per_window
File "apache_beam\runners\common.py", line 1571, in apache_beam.runners.common._OutputHandler.handle_process_outputs
File "G:\Python3.7\lib\site-packages\apache_beam\io\iobase.py", line 1193, in process
self.writer = self.sink.open_writer(init_result, str(uuid.uuid4()))
File "G:\Python3.7\lib\site-packages\apache_beam\options\value_provider.py", line 193, in _f
return fnc(self, *args, **kwargs)
File "G:\Python3.7\lib\site-packages\apache_beam\io\filebasedsink.py", line 202, in open_writer
return FileBasedSinkWriter(self, writer_path)
File "G:\Python3.7\lib\site-packages\apache_beam\io\filebasedsink.py", line 419, in __init__
self.temp_handle = self.sink.open(temp_shard_path)
File "G:\Python3.7\lib\site-packages\apache_beam\io\parquetio.py", line 553, in open
self._file_handle = super().open(temp_path)
File "G:\Python3.7\lib\site-packages\apache_beam\options\value_provider.py", line 193, in _f
return fnc(self, *args, **kwargs)
File "G:\Python3.7\lib\site-packages\apache_beam\io\filebasedsink.py", line 139, in open
temp_path, self.mime_type, self.compression_type)
File "G:\Python3.7\lib\site-packages\apache_beam\io\filesystems.py", line 224, in create
return filesystem.create(path, mime_type, compression_type)
File "G:\Python3.7\lib\site-packages\apache_beam\io\localfilesystem.py", line 163, in create
return self._path_open(path, 'wb', mime_type, compression_type)
File "G:\Python3.7\lib\site-packages\apache_beam\io\localfilesystem.py", line 140, in _path_open
raw_file = io.open(path, mode)
RuntimeError: FileNotFoundError: [Errno 2] No such file or directory: 'C:\\Users\\Shilpa\\.cache\\huggingface\\datasets\\wikipedia\\20220401.aa-date=20220401,language=aa\\2.0.0\\aa542ed919df55cc5d3347f42dd4521d05ca68751f50dbc32bae2a7f1e167559.incomplete\\beam-temp-wikipedia-train-880233e8287e11edaf9d3ca067f2714e\\20a05238-6106-4420-a713-4eca6dd5959a.wikipedia-train' [while running 'train/Save to parquet/Write/WriteImpl/WriteBundles']
## Environment info
Python: 3.7.6
Windows 10 Pro
datasets :2.4.0
apache_beam: 2.41.0
mwparserfromhell: 0.6.4
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https://api.github.com/repos/huggingface/datasets/issues/2099 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2099/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2099/comments | https://api.github.com/repos/huggingface/datasets/issues/2099/events | https://github.com/huggingface/datasets/issues/2099 | 838,523,819 | MDU6SXNzdWU4Mzg1MjM4MTk= | 2,099 | load_from_disk takes a long time to load local dataset | {
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"Hi !\r\nCan you share more information about the features of your dataset ? You can get them by printing `my_dataset.features`\r\nCan you also share the code of your `map` function ?",
"It is actually just the tokenized `wikipedia` dataset with `input_ids`, `attention_mask`, etc, with one extra column which is a... | 2021-03-23T09:28:37Z | 2021-03-23T17:12:16Z | 2021-03-23T17:12:16Z | NONE | null | null | null | I have an extremely large tokenized dataset (24M examples) that loads in a few minutes. However, after adding a column similar to `input_ids` (basically a list of integers) and saving the dataset to disk, the load time goes to >1 hour. I've even tried using `np.uint8` after seeing #1985 but it doesn't seem to be helping (the total size seems to be smaller though).
Does anyone know what could be the issue? Or does the casting of that column to `int8` need to happen in the function that writes the arrow table instead of in the `map` where I create the list of integers?
Tagging @lhoestq since you seem to be working on these issues and PRs :) | {
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https://api.github.com/repos/huggingface/datasets/issues/2033 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2033/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2033/comments | https://api.github.com/repos/huggingface/datasets/issues/2033/events | https://github.com/huggingface/datasets/pull/2033 | 829,295,339 | MDExOlB1bGxSZXF1ZXN0NTkwOTgzMDAy | 2,033 | Raise an error for outdated sacrebleu versions | {
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} | The `sacrebleu` metric seem to only work for sacrecleu>=1.4.12
For example using sacrebleu==1.2.10, an error is raised (from metric/sacrebleu/sacrebleu.py):
```python
def _compute(
self,
predictions,
references,
smooth_method="exp",
smooth_value=None,
force=False,
lowercase=False,
tokenize=scb.DEFAULT_TOKENIZER,
use_effective_order=False,
):
references_per_prediction = len(references[0])
if any(len(refs) != references_per_prediction for refs in references):
raise ValueError("Sacrebleu requires the same number of references for each prediction")
transformed_references = [[refs[i] for refs in references] for i in range(references_per_prediction)]
> output = scb.corpus_bleu(
sys_stream=predictions,
ref_streams=transformed_references,
smooth_method=smooth_method,
smooth_value=smooth_value,
force=force,
lowercase=lowercase,
tokenize=tokenize,
use_effective_order=use_effective_order,
)
E TypeError: corpus_bleu() got an unexpected keyword argument 'smooth_method'
/mnt/cache/modules/datasets_modules/metrics/sacrebleu/b390045b3d1dd4abf6a95c4a2a11ee3bcc2b7620b076204d0ddc353fa649fd86/sacrebleu.py:114: TypeError
```
I improved the error message when users have an outdated version of sacrebleu.
The new error message tells the user to update sacrebleu.
cc @LysandreJik | {
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https://api.github.com/repos/huggingface/datasets/issues/4377 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4377/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4377/comments | https://api.github.com/repos/huggingface/datasets/issues/4377/events | https://github.com/huggingface/datasets/pull/4377 | 1,242,746,186 | PR_kwDODunzps44K4OY | 4,377 | Fix checksum and bug in irc_disentangle dataset | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-05-20T07:29:28Z | 2022-05-20T09:34:36Z | 2022-05-20T09:26:32Z | MEMBER | null | 0 | {
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} | There was a bug in filepath segment:
- wrong: `jkkummerfeld-irc-disentanglement-fd379e9`
- right: `jkkummerfeld-irc-disentanglement-35f0a40`
Also there was a bug in the checksum of the downloaded file.
This PR fixes these issues.
Fix partially #4376.
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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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https://api.github.com/repos/huggingface/datasets/issues/2124 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2124/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2124/comments | https://api.github.com/repos/huggingface/datasets/issues/2124/events | https://github.com/huggingface/datasets/issues/2124 | 842,627,729 | MDU6SXNzdWU4NDI2Mjc3Mjk= | 2,124 | Adding ScaNN library to do MIPS? | {
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"I haven't played with it (yet) but it sounds really cool !\r\n"
] | 2021-03-28T00:07:00Z | 2021-03-29T13:23:43Z | null | NONE | null | null | null | @lhoestq Hi I am thinking of adding this new google library to do the MIPS similar to **add_faiss_idex**. As the paper suggests, it is really fast when it comes to retrieving the nearest neighbors.
https://github.com/google-research/google-research/tree/master/scann
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https://api.github.com/repos/huggingface/datasets/issues/5421 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5421/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5421/comments | https://api.github.com/repos/huggingface/datasets/issues/5421/events | https://github.com/huggingface/datasets/issues/5421 | 1,532,278,307 | I_kwDODunzps5bVLYj | 5,421 | Support case-insensitive Hub dataset name in load_dataset | {
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] | closed | false | null | [] | null | [
"Closing as case-insensitivity should be only for URL redirection on the Hub. In the APIs, we will only support the canonical name (https://github.com/huggingface/moon-landing/pull/2399#issuecomment-1382085611)"
] | 2023-01-13T13:07:07Z | 2023-01-13T20:12:32Z | 2023-01-13T20:12:32Z | CONTRIBUTOR | null | null | null | ### Feature request
The dataset name on the Hub is case-insensitive (see https://github.com/huggingface/moon-landing/pull/2399, internal issue), i.e., https://huggingface.co/datasets/GLUE redirects to https://huggingface.co/datasets/glue.
Ideally, we could load the glue dataset using the following:
```
from datasets import load_dataset
load_dataset('GLUE', 'cola')
```
It breaks because the loading script `GLUE.py` does not exist (`glue.py` should be selected instead).
Minor additional comment: in other cases without a loading script, we can load the dataset, but the automatically generated config name depends on the casing:
- `load_dataset('severo/danish-wit')` generates the config name `severo--danish-wit-e6fda5b070deb133`, while
- `load_dataset('severo/danish-WIT')` generates the config name `severo--danish-WIT-e6fda5b070deb133`
### Motivation
To follow the same UX on the Hub and in the datasets library.
### Your contribution
... | {
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https://api.github.com/repos/huggingface/datasets/issues/2820 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2820/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2820/comments | https://api.github.com/repos/huggingface/datasets/issues/2820/events | https://github.com/huggingface/datasets/issues/2820 | 975,210,712 | MDU6SXNzdWU5NzUyMTA3MTI= | 2,820 | Downloading “reddit” dataset keeps timing out. | {
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] | closed | false | null | [] | null | [
"```\r\nUsing custom data configuration default\r\nDownloading and preparing dataset reddit/default (download: 2.93 GiB, generated: 17.64 GiB, post-processed: Unknown size, total: 20.57 GiB) to /Volumes/My Passport for Mac/og-chat-data/reddit/default/1.0.0/98ba5abea674d3178f7588aa6518a5510dc0c6fa8176d9653a3546d5afc... | 2021-08-20T02:52:36Z | 2021-09-08T14:52:02Z | 2021-09-08T14:52:02Z | NONE | null | null | null | ## Describe the bug
A clear and concise description of what the bug is.
Everytime I try and download the reddit dataset it times out before finishing and I have to try again.
There is some timeout error that I will post once it happens again.
## Steps to reproduce the bug
```python
from datasets import load_dataset
dataset = load_dataset("reddit", ignore_verifications=True, cache_dir="/Volumes/My Passport for Mac/og-chat-data")
```
## Expected results
A clear and concise description of the expected results.
I would expect the download to finish, or at least provide a parameter to extend the read timeout window.
## Actual results
Specify the actual results or traceback.
Shown below in error message.
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.11.0
- Platform: macOS
- Python version: 3.9.6 (conda env)
- PyArrow version: N/A
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https://api.github.com/repos/huggingface/datasets/issues/5803 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5803/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5803/comments | https://api.github.com/repos/huggingface/datasets/issues/5803/events | https://github.com/huggingface/datasets/pull/5803 | 1,688,256,290 | PR_kwDODunzps5PXtte | 5,803 | Release: 2.12.0 | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_5803). 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... | 2023-04-28T09:52:11Z | 2023-04-28T10:18:56Z | 2023-04-28T09:54:43Z | MEMBER | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/1848 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1848/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1848/comments | https://api.github.com/repos/huggingface/datasets/issues/1848/events | https://github.com/huggingface/datasets/pull/1848 | 803,826,506 | MDExOlB1bGxSZXF1ZXN0NTY5Njg5ODU1 | 1,848 | Refactoring: Create config module | {
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This could be seen as a Pythonic singleton-like approach. Eventually a config instance class might be created. | {
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https://api.github.com/repos/huggingface/datasets/issues/1217 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1217/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1217/comments | https://api.github.com/repos/huggingface/datasets/issues/1217/events | https://github.com/huggingface/datasets/pull/1217 | 758,008,321 | MDExOlB1bGxSZXF1ZXN0NTMzMjU2MjU4 | 1,217 | adding DataCommons fact checking | {
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} | Adding the data from: https://datacommons.org/factcheck/
Had to cheat a bit with the dummy data as the test doesn't recognize `.txt.gz`: had to rename uncompressed files with the `.gz` extension manually without actually compressing | {
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https://api.github.com/repos/huggingface/datasets/issues/2592 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2592/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2592/comments | https://api.github.com/repos/huggingface/datasets/issues/2592/events | https://github.com/huggingface/datasets/pull/2592 | 937,060,559 | MDExOlB1bGxSZXF1ZXN0NjgzNjc2MjA4 | 2,592 | Add c4.noclean infos | {
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https://api.github.com/repos/huggingface/datasets/issues/5397 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5397/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5397/comments | https://api.github.com/repos/huggingface/datasets/issues/5397/events | https://github.com/huggingface/datasets/pull/5397 | 1,514,412,246 | PR_kwDODunzps5GYirs | 5,397 | Unpin pydantic test dependency | {
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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==6.0.0\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... | 2022-12-30T10:22:09Z | 2022-12-30T10:53:11Z | 2022-12-30T10:43:40Z | MEMBER | null | 0 | {
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} | Once pydantic-1.10.3 has been yanked, we can unpin it: https://pypi.org/project/pydantic/1.10.3/
See reply by pydantic team https://github.com/pydantic/pydantic/issues/4885#issuecomment-1367819807
```
v1.10.3 has been yanked.
```
in response to spacy request: https://github.com/pydantic/pydantic/issues/4885#issuecomment-1367810049
```
On behalf of spacy-related packages: would it be possible for you to temporarily yank v1.10.3?
To address this and be compatible with v1.10.4, we'd have to release new versions of a whole series of packages and nearly everyone (including me) is currently on vacation. Even if v1.10.4 is released with a fix, pip would still back off to v1.10.3 for spacy, etc. because of its current pins for typing_extensions. If it could instead back off to v1.10.2, we'd have a bit more breathing room to make the updates on our end.
```
Close #5398.
| {
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https://api.github.com/repos/huggingface/datasets/issues/2173 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2173/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2173/comments | https://api.github.com/repos/huggingface/datasets/issues/2173/events | https://github.com/huggingface/datasets/pull/2173 | 851,359,284 | MDExOlB1bGxSZXF1ZXN0NjA5Nzk2NzI2 | 2,173 | Add OpenSLR dataset | {
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} | OpenSLR (https://openslr.org/) is a site devoted to hosting speech and language resources, such as training corpora for speech recognition, and software related to speech recognition. There are around 80 speech datasets listed in OpenSLR, currently this PR includes only 9 speech datasets SLR41, SLR42, SLR43, SLR44, SLR63, SLR64, SLR65, SLR66 and SLR69 (Javanese, Khmer, Nepali and Sundanese, Malayalam, Marathi, Tamil, Telugu and Catalan). I can add other speech datasets gradually next time. | {
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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/2466 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2466/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2466/comments | https://api.github.com/repos/huggingface/datasets/issues/2466/events | https://github.com/huggingface/datasets/pull/2466 | 915,914,098 | MDExOlB1bGxSZXF1ZXN0NjY1NjY1MjQy | 2,466 | change udpos features structure | {
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"Let's add the tags in another PR. Thanks again !",
"Close #2061 , close #2444."
] | 2021-06-09T08:03:31Z | 2021-06-18T11:55:09Z | 2021-06-16T10:41:37Z | CONTRIBUTOR | null | 0 | {
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} | The structure is change such that each example is a sentence
The change is done for issues:
#2061
#2444
Close #2061 , close #2444. | {
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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 | rea... | 2023-04-26T17:39:43Z | 2023-04-27T16:41:50Z | 2023-04-27T16:34:45Z | MEMBER | null | 0 | {
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} | Added a "Use with Spark" doc page to document `Dataset.from_spark` following https://github.com/huggingface/datasets/pull/5701
cc @maddiedawson | {
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https://api.github.com/repos/huggingface/datasets/issues/5866 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5866/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5866/comments | https://api.github.com/repos/huggingface/datasets/issues/5866/events | https://github.com/huggingface/datasets/issues/5866 | 1,710,496,993 | I_kwDODunzps5l9Bzh | 5,866 | Issue with Sequence features | {
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"Thanks for reporting! I've opened a PR with a fix."
] | 2023-05-15T17:13:29Z | 2023-05-26T11:57:17Z | 2023-05-26T11:57:17Z | NONE | null | null | null | ### Describe the bug
Sequences features sometimes causes errors when the specified length is not -1
### Steps to reproduce the bug
```python
import numpy as np
from datasets import Features, ClassLabel, Sequence, Value, Dataset
feats = Features(**{'target': ClassLabel(names=[0, 1]),'x': Sequence(feature=Value(dtype='float64',id=None), length=2, id=None)})
Dataset.from_dict({"target": np.ones(2000).astype(int), "x": np.random.rand(2000,2)},features = feats).flatten_indices()
```
Throws:
```
TypeError: Couldn't cast array of type
fixed_size_list<item: double>[2]
to
Sequence(feature=Value(dtype='float64', id=None), length=2, id=None)
```
The same code works without any issues when `length = -1`
EDIT: The error seems to happen only when the length of the dataset is bigger than 1000 for some reason
### Expected behavior
No exception
### Environment info
- `datasets` version: 2.10.1
- Python version: 3.9.5
- PyArrow version: 11.0.0
- Pandas version: 1.4.1 | {
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https://api.github.com/repos/huggingface/datasets/issues/1972 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1972/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1972/comments | https://api.github.com/repos/huggingface/datasets/issues/1972/events | https://github.com/huggingface/datasets/issues/1972 | 819,752,761 | MDU6SXNzdWU4MTk3NTI3NjE= | 1,972 | 'Dataset' object has no attribute 'rename_column' | {
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"Hi ! `rename_column` has been added recently and will be available in the next release"
] | 2021-03-02T08:01:49Z | 2022-06-01T16:08:47Z | 2022-06-01T16:08:47Z | NONE | null | null | null | 'Dataset' object has no attribute 'rename_column' | {
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https://api.github.com/repos/huggingface/datasets/issues/4263 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4263/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4263/comments | https://api.github.com/repos/huggingface/datasets/issues/4263/events | https://github.com/huggingface/datasets/pull/4263 | 1,222,723,083 | PR_kwDODunzps43KLnD | 4,263 | Rename imagenet2012 -> imagenet-1k | {
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"> Later we can add imagenet-21k as a new dataset if we want.\r\n\r\nisn't it what models refer to as `imagenet` already?",
"> isn't it what models refer to as imagenet already?\r\n\r\nI wasn't sure, but it looks like it indeed. Therefore having a dataset `imagenet` for ImageNet 21k makes sense actually.\r\n\r\nE... | 2022-05-02T10:26:21Z | 2022-05-02T17:50:46Z | 2022-05-02T16:32:57Z | MEMBER | null | 0 | {
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} | On the Hugging Face Hub, users refer to imagenet2012 (from #4178 ) as imagenet-1k in their model tags.
To correctly link models to imagenet, we should rename this dataset `imagenet-1k`.
Later we can add `imagenet-21k` as a new dataset if we want.
Once this one is merged we can delete the `imagenet2012` dataset repository on the Hub.
EDIT: to complete the rationale on why we should name it `imagenet-1k`:
If users specifically added the tag `imagenet-1k` , then it could be for two reasons (not sure which one is predominant), either they
- wanted to make it explicit that it’s not 21k -> the distinction is important for the community
- or they have been following this convention from other models -> the convention implicitly exists already | {
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https://api.github.com/repos/huggingface/datasets/issues/1260 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1260/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1260/comments | https://api.github.com/repos/huggingface/datasets/issues/1260/events | https://github.com/huggingface/datasets/pull/1260 | 758,601,828 | MDExOlB1bGxSZXF1ZXN0NTMzNzQ4ODM3 | 1,260 | Added NewsPH Raw Dataset | {
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"looks like this PR has changes to many files other than the ones for `NewsPH`\r\n\r\nCan you create another branch and another PR please ?"
] | 2020-12-07T15:17:53Z | 2020-12-08T16:27:15Z | 2020-12-08T16:27:15Z | NONE | null | 0 | {
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Paper: https://arxiv.org/abs/2010.11574
Repo: https://github.com/jcblaisecruz02/Filipino-Text-Benchmarks | {
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"Hi! \r\n\r\nThis behavior stems from the fact that we don't always embed image bytes in the underlying arrow table, which can lead to bad size estimation (we use the first 1000 table rows to [estimate](https://github.com/huggingface/datasets/blob/9a7272cd4222383a5b932b0083a4cc173fda44e8/src/datasets/arrow_dataset.... | 2022-12-22T21:50:58Z | 2022-12-26T23:45:51Z | 2022-12-26T23:45:51Z | NONE | null | null | null | ### Describe the bug
`max_shard_size` parameter for `datasets.push_to_hub()` works unreliably with large files, generating shard files that are way past the specified limit.
In my private dataset, which contains unprocessed images of all sizes (up to `~100MB` per file), I've encountered cases where `max_shard_size='100MB'` results in shard files that are `>2GB` in size. Setting `max_shard_size` to another value, such as `1GB` or `500MB` does not fix this problem.
**The real problem is this:** When the shard file size grows too big, the entire dataset breaks because of #4721 and ultimately https://issues.apache.org/jira/browse/ARROW-5030. Since `max_shard_size` does not let one accurately control the size of the shard files, it becomes very easy to build a large dataset without any warnings that it will be broken -- even when you think you are mitigating this problem by setting `max_shard_size`.
```
File " /path/to/sd-test-suite-v1/venv/lib/site-packages/datasets/builder.py", line 1763, in _prepare_split_single
for _, table in generator:
File " /path/to/sd-test-suite-v1/venv/lib/site-packages/datasets/packaged_modules/parquet/parquet.py", line 69, in _generate_tables
for batch_idx, record_batch in enumerate(
File "pyarrow/_parquet.pyx", line 1323, in iter_batches
File "pyarrow/error.pxi", line 121, in pyarrow.lib.check_status
pyarrow.lib.ArrowNotImplementedError: Nested data conversions not implemented for chunked array outputs
```
### Steps to reproduce the bug
1. Clone [example repo](https://github.com/salieri/hf-dataset-shard-size-bug)
2. Follow steps in [README.md](https://github.com/salieri/hf-dataset-shard-size-bug/blob/main/README.md)
3. After uploading the dataset, you will see that the shard file size varies between `30MB` and `200MB` -- way beyond the `max_shard_size='75MB'` limit (example: `train-00003-of-00131...` is `155MB` in [here](https://huggingface.co/datasets/slri/shard-size-test/tree/main/data))
(Note that this example repo does not generate shard files that are so large that they would trigger #4721)
### Expected behavior
The shard file size should remain below or equal to `max_shard_size`.
### Environment info
- `datasets` version: 2.8.0
- Platform: Linux-5.10.157-139.675.amzn2.aarch64-aarch64-with-glibc2.17
- Python version: 3.7.15
- PyArrow version: 10.0.1
- Pandas version: 1.3.5 | {
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} | reference [PR#1317](https://github.com/huggingface/datasets/pull/1317) | {
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"The dataset maintainers (https://huggingface.co/datasets/ubuntu_dialogs_corpus) decided to forbid the dataset from being downloaded automatically (https://huggingface.co/docs/datasets/v2.4.0/en/loading#manual-download), and the dataset viewer respects this.\r\nWe will try to improve the error display though. Thank... | 2022-09-06T12:41:50Z | 2022-09-06T12:51:25Z | 2022-09-06T12:51:25Z | NONE | null | null | null | ### Link
_No response_
### Description
_No response_
### Owner
_No response_ | {
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https://api.github.com/repos/huggingface/datasets/issues/3580 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3580/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3580/comments | https://api.github.com/repos/huggingface/datasets/issues/3580/events | https://github.com/huggingface/datasets/issues/3580 | 1,104,663,242 | I_kwDODunzps5B19LK | 3,580 | Bug in wiki bio load | {
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"+1, here's the error I got: \r\n\r\n```\r\n>>> from datasets import load_dataset\r\n>>>\r\n>>> load_dataset(\"wiki_bio\")\r\nDownloading: 7.58kB [00:00, 4.42MB/s]\r\nDownloading: 2.71kB [00:00, 1.30MB/s]\r\nUsing custom data configuration default\r\nDownloading and preparing dataset wiki_bio/default (download: 318... | 2022-01-15T10:04:33Z | 2022-01-31T08:38:09Z | 2022-01-31T08:38:09Z | NONE | null | null | null |
wiki_bio is failing to load because of a failing drive link . Can someone fix this ?
a | {
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https://api.github.com/repos/huggingface/datasets/issues/1652 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1652/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1652/comments | https://api.github.com/repos/huggingface/datasets/issues/1652/events | https://github.com/huggingface/datasets/pull/1652 | 775,571,813 | MDExOlB1bGxSZXF1ZXN0NTQ2MjI1NTM1 | 1,652 | Update dataset cards from previous sprint | {
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} | UPDATE2 (3797ce5): Updated for multi-configs
UPDATE (7018082): manually created the dummy_datasets. All tests were cleared locally. Pushed it to origin/master
DRAFT VERSION (57fdb20): (_no longer draft_)
Uploaded the air_dialogue database.
dummy_data creation was failing in local, since the original downloaded file has some nested folders. Pushing it since the tests with real data was cleared. Will re-check & update via manually creating some dummy_data | {
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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/5156 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5156/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5156/comments | https://api.github.com/repos/huggingface/datasets/issues/5156/events | https://github.com/huggingface/datasets/issues/5156 | 1,421,667,125 | I_kwDODunzps5UvOs1 | 5,156 | Unable to download dataset using Azure Data Lake Gen 2 | {
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"Hi ! From the `adlfs` docs, there are two filesystems you can use:\r\n> To use the Gen1 filesystem:\r\n> - known_implementations[‘adl’] = {‘class’: ‘adlfs.AzureDatalakeFileSystem’}\r\n> \r\n> To use the Gen2 filesystem:\r\n> - known_implementations[‘abfs’] = {‘class’: ‘adlfs.AzureBlobFileSystem’}\r\n\r\nIf I'm no... | 2022-10-25T00:43:18Z | 2022-11-17T23:37:09Z | 2022-11-17T23:37:08Z | NONE | null | null | null | ### Describe the bug
When using the DatasetBuilder method with the credentials for the cloud storage Azure Data Lake (adl) Gen2, the following error is showed:
```
Traceback (most recent call last):
File "download_hf_dataset.py", line 143, in <module>
main()
File "download_hf_dataset.py", line 102, in main
builder.download_and_prepare(save_dir, storage_options=storage_options, max_shard_size="250MB", file_format="parquet")
File "/home/clarisses/miniconda3/envs/hf_datasets_env/lib/python3.8/site-packages/datasets/builder.py", line 671, in download_and_prepare
fs_token_paths = fsspec.get_fs_token_paths(output_dir, storage_options=storage_options)
File "/home/clarisses/miniconda3/envs/hf_datasets_env/lib/python3.8/site-packages/fsspec/core.py", line 639, in get_fs_token_paths
fs = cls(**options)
File "/home/clarisses/miniconda3/envs/hf_datasets_env/lib/python3.8/site-packages/fsspec/spec.py", line 76, in __call__
obj = super().__call__(*args, **kwargs)
TypeError: __init__() got an unexpected keyword argument 'account_name'
```
If I don't pass the storage_options argument (leave it as None), it requires the credentials used in ADL Gen 1:
`TypeError: __init__() missing 3 required positional arguments: 'tenant_id', 'client_id', and 'client_secret'`
Thus, it is not possible to download a dataset from the cloud using Azure Data Lake (adl) Gen2.
### Steps to reproduce the bug
Assuming that you have an account on Azure and at Storage Account that can be used for reproduce:
1. Create a dict with the format to connect to Azure Data Lake Gen 2
```
storage_options = {"account_name": ACCOUNT_NAME, "account_key": ACCOUNT_KEY) # gen 2 filesystem
```
2. Create a dataset builder for any HF hosted dataset
```
builder = load_dataset_builder(dataset_name)
```
3. Try to download the dataset passing the storage_options as an argument
```
save_dir = 'adl://my_save_dir'
builder.download_and_prepare(save_dir, storage_options=storage_options, max_shard_size="250MB", file_format="parquet")
```
### Expected behavior
Not seeing the error mentioned above and being able to download the dataset to the provided path on ADL
### Environment info
- `datasets` version: 2.6.1
- Platform: Linux-5.15.0-46-generic-x86_64-with-glibc2.17
- 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/1717 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1717/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1717/comments | https://api.github.com/repos/huggingface/datasets/issues/1717/events | https://github.com/huggingface/datasets/issues/1717 | 783,074,255 | MDU6SXNzdWU3ODMwNzQyNTU= | 1,717 | SciFact dataset - minor changes | {
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"Hi Dave,\r\nYou are more than welcome to open a PR to make these changes! 🤗\r\nYou will find the relevant information about opening a PR in the [contributing guide](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md) and in the [dataset addition guide](https://github.com/huggingface/datasets/blob... | 2021-01-11T05:26:40Z | 2021-01-26T02:52:17Z | 2021-01-26T02:52:17Z | CONTRIBUTOR | null | null | null | Hi,
SciFact dataset creator here. First of all, thanks for adding the dataset to Huggingface, much appreciated!
I'd like to make a few minor changes, including the citation information and the `_URL` from which to download the dataset. Can I submit a PR for this?
It also looks like the dataset is being downloaded directly from Huggingface's Google cloud account rather than via the `_URL` in [scifact.py](https://github.com/huggingface/datasets/blob/master/datasets/scifact/scifact.py). Can you help me update the version on gcloud?
Thanks,
Dave | {
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https://api.github.com/repos/huggingface/datasets/issues/6199 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6199/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6199/comments | https://api.github.com/repos/huggingface/datasets/issues/6199/events | https://github.com/huggingface/datasets/issues/6199 | 1,875,165,185 | I_kwDODunzps5vxMAB | 6,199 | Use load_dataset for local json files, but it not works | {
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"Hugging Face's datasets library may prioritize remote configurations. Make sure there are no conflicting configurations causing the library to prefer downloading data\r\nMay be try debugging\r\nraw_datasets = load_dataset('json', data_files=data_files)\r\nprint(raw_datasets)\r\n",
"It doesn't download them but ... | 2023-08-31T09:42:34Z | 2023-08-31T19:05:07Z | null | NONE | null | null | null | ### Describe the bug
when I use load_dataset to load my local datasets，it always goes to Hugging Face to download the data instead of loading the local dataset.
### Steps to reproduce the bug
`raw_datasets = load_dataset(
‘json’,
data_files=data_files)`
### Expected behavior
### Environment info
python version 3.8.5
datasets version 2.12
os version unbuntu 18.04 | {
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https://api.github.com/repos/huggingface/datasets/issues/6138 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6138/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6138/comments | https://api.github.com/repos/huggingface/datasets/issues/6138/events | https://github.com/huggingface/datasets/pull/6138 | 1,844,952,496 | PR_kwDODunzps5XoH2V | 6,138 | Ignore CI lint rule violation in Pickler.memoize | {
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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... | 2023-08-10T11:03:15Z | 2023-08-10T11:31:45Z | 2023-08-10T11:22:56Z | MEMBER | null | 0 | {
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} | This PR ignores the violation of the lint rule E721 in `Pickler.memoize`.
The lint rule violation was introduced in this PR:
- #3182
@lhoestq is there a reason you did not use `isinstance` instead?
As a hotfix, we just ignore the violation of the lint rule.
Fix #6136. | {
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https://api.github.com/repos/huggingface/datasets/issues/1602 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1602/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1602/comments | https://api.github.com/repos/huggingface/datasets/issues/1602/events | https://github.com/huggingface/datasets/pull/1602 | 770,841,810 | MDExOlB1bGxSZXF1ZXN0NTQyNTA4NTM4 | 1,602 | second update of id_newspapers_2018 | {
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} | The feature "url" is currently set wrongly to data["date"], this PR fix it to data["url"].
I added also an additional POC. | {
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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/1303 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1303/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1303/comments | https://api.github.com/repos/huggingface/datasets/issues/1303/events | https://github.com/huggingface/datasets/pull/1303 | 759,440,484 | MDExOlB1bGxSZXF1ZXN0NTM0NDQ2NDg0 | 1,303 | adding opus_openoffice | {
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} | Adding Opus OpenOffice: http://opus.nlpl.eu/OpenOffice.php
8 languages, 28 bitexts | {
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