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https://api.github.com/repos/huggingface/datasets/issues/3991 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3991/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3991/comments | https://api.github.com/repos/huggingface/datasets/issues/3991/events | https://github.com/huggingface/datasets/issues/3991 | 1,177,362,901 | I_kwDODunzps5GLSHV | 3,991 | Add Lung Image Database Consortium image collection (LIDC-IDRI) dataset | {
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"color": "bfdadc",... | open | false | null | [] | null | [] | 2022-03-22T22:16:05Z | 2022-03-23T12:57:16Z | null | NONE | null | null | null | ## Adding a Dataset
- **Name:** *Lung Image Database Consortium image collection (LIDC-IDRI)*
- **Description:** *Consists of diagnostic and lung cancer screening thoracic computed tomography (CT) scans with marked-up annotated lesions. It is a web-accessible international resource for development, training, and evaluation of computer-assisted diagnostic (CAD) methods for lung cancer detection and diagnosis. Initiated by the National Cancer Institute (NCI), further advanced by the Foundation for the National Institutes of Health (FNIH), and accompanied by the Food and Drug Administration (FDA) through active participation, this public-private partnership demonstrates the success of a consortium founded on a consensus-based process.*
- **Data:** *[link to the Github repository or current dataset location](https://wiki.cancerimagingarchive.net/display/Public/LIDC-IDRI)*
- **Motivation:** *Key dataset in the healthcare community*
Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
FYI @osanseviero @abidlabs | {
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https://api.github.com/repos/huggingface/datasets/issues/1224 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1224/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1224/comments | https://api.github.com/repos/huggingface/datasets/issues/1224/events | https://github.com/huggingface/datasets/pull/1224 | 758,022,998 | MDExOlB1bGxSZXF1ZXN0NTMzMjY2Njg1 | 1,224 | adding conceptnet5 | {
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"Thank you. I'll make those changes. but I'm having problems trying to push my changes to my fork\r\n",
"Hi, I've removed the TODO, and added a README.md. How do I push these changes?\r\n",
"Also, what docstring are you recommending?\r\n",
"> Hi, I've removed the TODO, and added a README.md. How do I push the... | 2020-12-06T21:06:53Z | 2020-12-09T16:38:16Z | 2020-12-09T14:37:17Z | CONTRIBUTOR | null | 0 | {
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} | Adding the conceptnet5 and omcs txt files used to create the conceptnet5 dataset. Conceptne5 is a common sense dataset. More info can be found here: https://github.com/commonsense/conceptnet5/wiki | {
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https://api.github.com/repos/huggingface/datasets/issues/2158 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2158/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2158/comments | https://api.github.com/repos/huggingface/datasets/issues/2158/events | https://github.com/huggingface/datasets/issues/2158 | 848,506,746 | MDU6SXNzdWU4NDg1MDY3NDY= | 2,158 | viewer "fake_news_english" error | {
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"Thanks for reporting !\r\nThe viewer doesn't have all the dependencies of the datasets. We may add openpyxl to be able to show this dataset properly",
"This viewer tool is deprecated now and the new viewer at https://huggingface.co/datasets/fake_news_english works fine, so I'm closing this issue"
] | 2021-04-01T14:13:20Z | 2022-10-05T13:22:02Z | 2022-10-05T13:22:02Z | NONE | null | null | null | When I visit the [Huggingface - viewer](https://huggingface.co/datasets/viewer/) web site, under the dataset "fake_news_english" I've got this error:
> ImportError: To be able to use this dataset, you need to install the following dependencies['openpyxl'] using 'pip install # noqa: requires this pandas optional dependency for reading xlsx files' for instance'
as well as the error Traceback.
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https://api.github.com/repos/huggingface/datasets/issues/3918 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3918/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3918/comments | https://api.github.com/repos/huggingface/datasets/issues/3918/events | https://github.com/huggingface/datasets/issues/3918 | 1,169,366,117 | I_kwDODunzps5Fsxxl | 3,918 | datasets.utils.info_utils.NonMatchingChecksumError: Checksums didn't match for dataset source files | {
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"Hi @willowdong! These issues were fixed on master. We will have a new release of `datasets` later today. In the meantime, you can avoid these issues by installing `datasets` from master as follows:\r\n```bash\r\npip install git+https://github.com/huggingface/datasets.git\r\n```",
"You should force redownload:\r\... | 2022-03-15T08:53:45Z | 2022-03-16T15:36:58Z | 2022-03-15T14:01:25Z | NONE | null | null | null | ## Describe the bug
Can't load the dataset
## Steps to reproduce the bug
```python
# Sample code to reproduce the bug
```
from datasets import load_dataset
dataset = load_dataset('multi_news')
dataset_2=load_dataset("reddit_tifu", "long")
## Actual results
raise NonMatchingChecksumError(error_msg + str(bad_urls))
datasets.utils.info_utils.NonMatchingChecksumError: Checksums didn't match for dataset source files:
['https://drive.google.com/uc?export=download&id=1ffWfITKFMJeqjT8loC8aiCLRNJpc_XnF']
## Environment info
- `datasets` version: 1.18.4
- Platform: macOS-10.16-x86_64-i386-64bit
- Python version: 3.8.0
- PyArrow version: 6.0.1
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https://api.github.com/repos/huggingface/datasets/issues/2142 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2142/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2142/comments | https://api.github.com/repos/huggingface/datasets/issues/2142/events | https://github.com/huggingface/datasets/pull/2142 | 843,919,420 | MDExOlB1bGxSZXF1ZXN0NjAzMjQwMzUy | 2,142 | Gem V1.1 | {
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} | This branch updates the GEM benchmark to its 1.1 version which includes:
- challenge sets for most tasks
- detokenized TurkCorpus to match the rest of the text simplification subtasks
- fixed inputs for TurkCorpus and ASSET test sets
- 18 languages in WikiLingua
cc @sebastianGehrmann | {
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https://api.github.com/repos/huggingface/datasets/issues/6103 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6103/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6103/comments | https://api.github.com/repos/huggingface/datasets/issues/6103/events | https://github.com/huggingface/datasets/pull/6103 | 1,828,515,165 | PR_kwDODunzps5Ww2gV | 6,103 | Set dev version | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6103). All of your documentation changes will be reflected on that endpoint.",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchma... | 2023-07-31T06:44:05Z | 2023-07-31T06:55:58Z | 2023-07-31T06:45:41Z | MEMBER | null | 0 | {
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Currently, if `jsonlines` is installed, `datasets` raises a `FileNotFoundError`:
```
FileNotFoundError: [Errno 2] No such file or directory: 'https://...'
```
See:
- https://huggingface.co/datasets/masakhane/afriqa/discussions/1 | {
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https://api.github.com/repos/huggingface/datasets/issues/5422 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5422/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5422/comments | https://api.github.com/repos/huggingface/datasets/issues/5422/events | https://github.com/huggingface/datasets/issues/5422 | 1,533,385,239 | I_kwDODunzps5bZZoX | 5,422 | Datasets load error for saved github issues | {
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"I can confirm that the error exists!\r\nI'm trying to read 3 parquet files locally:\r\n```python\r\nfrom datasets import load_dataset, Features, Value, ClassLabel\r\n\r\nreview_dataset = load_dataset(\r\n \"parquet\",\r\n data_files={\r\n \"train\": os.path.join(sentiment_analysis_data_path, \"train.p... | 2023-01-14T17:29:38Z | 2023-09-14T11:39:57Z | null | NONE | null | null | null | ### Describe the bug
Loading a previously downloaded & saved dataset as described in the HuggingFace course:
issues_dataset = load_dataset("json", data_files="issues/datasets-issues.jsonl", split="train")
Gives this error:
datasets.builder.DatasetGenerationError: An error occurred while generating the dataset
A work-around I found was to use streaming.
### Steps to reproduce the bug
Reproduce by executing the code provided:
https://huggingface.co/course/chapter5/5?fw=pt
From the heading:
'let’s create a function that can download all the issues from a GitHub repository'
### Expected behavior
No error
### Environment info
Datasets version 2.8.0. Note that version 2.6.1 gives the same error (related to null timestamp).
**[EDIT]**
This is the complete error trace confirming the issue is related to the timestamp (`Couldn't cast array of type timestamp[s] to null`)
```
Using custom data configuration default-950028611d2860c8
Downloading and preparing dataset json/default to [...]/.cache/huggingface/datasets/json/default-950028611d2860c8/0.0.0/0f7e3662623656454fcd2b650f34e886a7db4b9104504885bd462096cc7a9f51...
Downloading data files: 100%|██████████| 1/1 [00:00<?, ?it/s]
Extracting data files: 100%|██████████| 1/1 [00:00<00:00, 500.63it/s]
Generating train split: 2619 examples [00:00, 7155.72 examples/s]Traceback (most recent call last):
File "[...]\miniconda3\envs\HuggingFace\lib\site-packages\datasets\builder.py", line 1831, in _prepare_split_single
writer.write_table(table)
File "[...]\miniconda3\envs\HuggingFace\lib\site-packages\datasets\arrow_writer.py", line 567, in write_table
pa_table = table_cast(pa_table, self._schema)
File "[...]\miniconda3\envs\HuggingFace\lib\site-packages\datasets\table.py", line 2282, in table_cast
return cast_table_to_schema(table, schema)
File "[...]\miniconda3\envs\HuggingFace\lib\site-packages\datasets\table.py", line 2241, in cast_table_to_schema
arrays = [cast_array_to_feature(table[name], feature) for name, feature in features.items()]
File "[...]\miniconda3\envs\HuggingFace\lib\site-packages\datasets\table.py", line 2241, in <listcomp>
arrays = [cast_array_to_feature(table[name], feature) for name, feature in features.items()]
File "[...]\miniconda3\envs\HuggingFace\lib\site-packages\datasets\table.py", line 1807, in wrapper
return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
File "[...]\miniconda3\envs\HuggingFace\lib\site-packages\datasets\table.py", line 1807, in <listcomp>
return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
File "[...]\miniconda3\envs\HuggingFace\lib\site-packages\datasets\table.py", line 2035, in cast_array_to_feature
arrays = [_c(array.field(name), subfeature) for name, subfeature in feature.items()]
File "[...]\miniconda3\envs\HuggingFace\lib\site-packages\datasets\table.py", line 2035, in <listcomp>
arrays = [_c(array.field(name), subfeature) for name, subfeature in feature.items()]
File "[...]\miniconda3\envs\HuggingFace\lib\site-packages\datasets\table.py", line 1809, in wrapper
return func(array, *args, **kwargs)
File "[...]\miniconda3\envs\HuggingFace\lib\site-packages\datasets\table.py", line 2101, in cast_array_to_feature
return array_cast(array, feature(), allow_number_to_str=allow_number_to_str)
File "[...]\miniconda3\envs\HuggingFace\lib\site-packages\datasets\table.py", line 1809, in wrapper
return func(array, *args, **kwargs)
File "[...]\miniconda3\envs\HuggingFace\lib\site-packages\datasets\table.py", line 1990, in array_cast
raise TypeError(f"Couldn't cast array of type {array.type} to {pa_type}")
TypeError: Couldn't cast array of type timestamp[s] to null
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "C:\Program Files\JetBrains\PyCharm 2022.1.3\plugins\python\helpers\pydev\pydevconsole.py", line 364, in runcode
coro = func()
File "<input>", line 1, in <module>
File "C:\Program Files\JetBrains\PyCharm 2022.1.3\plugins\python\helpers\pydev\_pydev_bundle\pydev_umd.py", line 198, in runfile
pydev_imports.execfile(filename, global_vars, local_vars) # execute the script
File "C:\Program Files\JetBrains\PyCharm 2022.1.3\plugins\python\helpers\pydev\_pydev_imps\_pydev_execfile.py", line 18, in execfile
exec(compile(contents+"\n", file, 'exec'), glob, loc)
File "[...]\PycharmProjects\TransformersTesting\dataset_issues.py", line 20, in <module>
issues_dataset = load_dataset("json", data_files="issues/datasets-issues.jsonl", split="train")
File "[...]\miniconda3\envs\HuggingFace\lib\site-packages\datasets\load.py", line 1757, in load_dataset
builder_instance.download_and_prepare(
File "[...]\miniconda3\envs\HuggingFace\lib\site-packages\datasets\builder.py", line 860, in download_and_prepare
self._download_and_prepare(
File "[...]\miniconda3\envs\HuggingFace\lib\site-packages\datasets\builder.py", line 953, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "[...]\miniconda3\envs\HuggingFace\lib\site-packages\datasets\builder.py", line 1706, in _prepare_split
for job_id, done, content in self._prepare_split_single(
File "[...]\miniconda3\envs\HuggingFace\lib\site-packages\datasets\builder.py", line 1849, in _prepare_split_single
raise DatasetGenerationError("An error occurred while generating the dataset") from e
datasets.builder.DatasetGenerationError: An error occurred while generating the dataset
Generating train split: 2619 examples [00:19, 7155.72 examples/s]
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/5432 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5432/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5432/comments | https://api.github.com/repos/huggingface/datasets/issues/5432/events | https://github.com/huggingface/datasets/pull/5432 | 1,535,893,019 | PR_kwDODunzps5HhEA8 | 5,432 | Fix CI benchmarks by temporarily pinning Docker image version | {
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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... | 2023-01-17T07:15:31Z | 2023-01-17T08:58:22Z | 2023-01-17T08:51:17Z | MEMBER | null | 0 | {
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} | This PR fixes CI benchmarks, by temporarily pinning Docker image version, instead of "latest" tag.
It also updates deprecated `cml-send-comment` command and using `cml comment create` instead.
Fix #5431. | {
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https://api.github.com/repos/huggingface/datasets/issues/2489 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2489/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2489/comments | https://api.github.com/repos/huggingface/datasets/issues/2489/events | https://github.com/huggingface/datasets/issues/2489 | 919,569,749 | MDU6SXNzdWU5MTk1Njk3NDk= | 2,489 | Allow latest pyarrow version once segfault bug is fixed | {
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"following_url": "https://api.github.com/users/albertvillanova/following{/o... | null | [] | 2021-06-12T14:09:52Z | 2021-06-14T07:53:23Z | 2021-06-14T07:53:23Z | MEMBER | null | null | null | As pointed out by @symeneses (see https://github.com/huggingface/datasets/pull/2268#issuecomment-860048613), pyarrow has fixed the segfault bug present in version 4.0.0 (see https://issues.apache.org/jira/browse/ARROW-12568):
- it was fixed on 3 May 2021
- version 4.0.1 was released on 19 May 2021 with the bug fix | {
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https://api.github.com/repos/huggingface/datasets/issues/3315 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3315/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3315/comments | https://api.github.com/repos/huggingface/datasets/issues/3315/events | https://github.com/huggingface/datasets/pull/3315 | 1,061,678,452 | PR_kwDODunzps4u7WpU | 3,315 | Removing query params for dynamic URL caching | {
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"IMO it makes more sense to have `ignore_url_params` as an attribute of `DownloadConfig` to avoid defining a new argument in `DownloadManger`'s methods.",
"@mariosasko that would make sense to me too, but it seems like `DownloadConfig` wasn't intended to be modified from a dataset loading script. @lhoestq wdyt?",... | 2021-11-23T20:24:12Z | 2021-11-25T14:44:32Z | 2021-11-25T14:44:31Z | MEMBER | null | 0 | {
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} | The main use case for this is to make dynamically generated private URLs (like the ones returned by CommonVoice API) compatible with the datasets' caching logic.
Usage example:
```python
import datasets
class CommonVoice(datasets.GeneratorBasedBuilder):
def _info(self):
return datasets.DatasetInfo()
def _split_generators(self, dl_manager):
dl_manager.download_config.ignore_url_params = True
HUGE_URL = "https://mozilla-common-voice-datasets.s3.dualstack.us-west-2.amazonaws.com/cv-corpus-7.0-2021-07-21/cv-corpus-7.0-2021-07-21-ab.tar.gz?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=ASIAQ3GQRTO3IU5JYB5K%2F20211125%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20211125T131423Z&X-Amz-Expires=43200&X-Amz-Security-Token=FwoGZXIvYXdzEL7%2F%2F%2F%2F%2F%2F%2F%2F%2F%2FwEaDLsZw7Nj0d9h4rgheyKSBJJ6bxo1JdWLXAUhLMrUB8AXfhP8Ge4F8dtjwXmvGJgkIvdMT7P4YOEE1pS3mW8AyKsz7Z7IRVCIGQrOH1AbxGVVcDoCMMswXEOqL3nJFihKLf99%2F6l8iJVZdzftRUNgMhX5Hz0xSIL%2BzRDpH5nYa7C6YpEdOdW81CFVXybx7WUrX13wc8X4ZlUj7zrWcWf5p2VEIU5Utb7YHVi0Y5TQQiZSDoedQl0j4VmMuFkDzoobIO%2BvilgGeE2kIX0E62X423mEGNu4uQV5JsOuLAtv3GVlemsqEH3ZYrXDuxLmnvGj5HfMtySwI4vKv%2BlnnirD29o7hxvtidXiA8JMWhp93aP%2Fw7sod%2BPPbb5EqP%2B4Qb2GJ1myClOKcLEY0cqoy7XWm8NeVljLJojnFJVS5mNFBAzCCTJ%2FidxNsj8fflzkRoAzYaaPBuOTL1dgtZCdslK3FAuEvw0cik7P9A7IYiULV33otSHKMPcVfNHFsWQljs03gDztsIUWxaXvu6ck5vCcGULsHbfe6xoMPm2bR9jtKLONsslPcnzWIf7%2Fch2w%2F%2BjtTCd9IxaH4kytyJ6mIjpV%2FA%2F2h9qeDnDFsCphnMjAzPQn6tqCgTtPcyJ2b8c94ncgUnE4mepx%2FDa%2FanAEsrg9RPdmbdoPswzHn1IClh91IfSN74u95DZUxlPeZrHG5HxVCN3dKO6j%2Ft1xd20L0hEtazDdKOr8%2FYwGMirp8rp%2BII0pYOwQOrYHqH%2FREX2dRJctJtwE86Qj1eU8BAdXuFIkLC4NWXw%3D&X-Amz-Signature=1b8108d29b0e9c2bf6c7246e58ca8d5749a83de0704757ad8e8a44d78194691f&X-Amz-SignedHeaders=host"
dl_path = dl_manager.download_and_extract(HUGE_URL)
print(dl_path)
HUGE_URL += "&some_new_or_changed_param=12345"
dl_path = dl_manager.download_and_extract(HUGE_URL)
print(dl_path)
dl_manager = datasets.DownloadManager(dataset_name="common_voice")
CommonVoice()._split_generators(dl_manager)
```
Output:
```
/home/user/.cache/huggingface/datasets/downloads/6ef2a377398ff3309554be040caa78414e6562d623dbd0ce8fc262459a7f8ec6
/home/user/.cache/huggingface/datasets/downloads/6ef2a377398ff3309554be040caa78414e6562d623dbd0ce8fc262459a7f8ec6
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/1321 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1321/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1321/comments | https://api.github.com/repos/huggingface/datasets/issues/1321/events | https://github.com/huggingface/datasets/pull/1321 | 759,573,610 | MDExOlB1bGxSZXF1ZXN0NTM0NTU1Nzg1 | 1,321 | added dutch_social | {
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"@lhoestq \r\nUpdated the `dummy_data.zip `(<10kb)I had to reduce it to just a few samples. \r\nTrain-Test-Dev (20-5-5 samples) \r\n\r\nBut the push also added changes from other PRs (probably because of a rebase!) So the files changed tab shows 466 files were changed! \r\n",
"Thanks ! The dummy data are all go... | 2020-12-08T16:07:54Z | 2020-12-16T10:14:17Z | 2020-12-16T10:14:17Z | CONTRIBUTOR | null | 0 | {
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} | The Dutch social media tweets dataset. Which has a total of more than 210k tweets in dutch language. These tweets have been machine annotated with sentiment scores (`label` feature) and `industry` and `hisco_codes`
It can be used for sentiment analysis, multi-label classification and entity tagging | {
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https://api.github.com/repos/huggingface/datasets/issues/2017 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2017/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2017/comments | https://api.github.com/repos/huggingface/datasets/issues/2017/events | https://github.com/huggingface/datasets/pull/2017 | 826,428,578 | MDExOlB1bGxSZXF1ZXN0NTg4NDMyNDc2 | 2,017 | Add TF-based Features to handle different modes of data | {
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I am creating this draft PR to work on add features similar to [TF datasets](https://github.com/tensorflow/datasets/tree/master/tensorflow_datasets/core/features). I'll be starting with `Tensor` and `FeatureConnector` classes, and build upon them to add other features as well. This is a work in progress. | {
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https://api.github.com/repos/huggingface/datasets/issues/4426 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4426/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4426/comments | https://api.github.com/repos/huggingface/datasets/issues/4426/events | https://github.com/huggingface/datasets/issues/4426 | 1,253,887,311 | I_kwDODunzps5KvM1P | 4,426 | Add loading variable number of columns for different splits | {
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"Hi! Indeed the column is missing, but you shouldn't get an error? Have you made some modifications (locally) to the loading script? I've opened a PR to add the missing columns to the script. "
] | 2022-05-31T13:40:16Z | 2022-06-03T16:25:25Z | 2022-06-03T16:25:25Z | NONE | null | null | null | **Is your feature request related to a problem? Please describe.**
The original dataset `blended_skill_talk` consists of different sets of columns for the different splits: (test/valid) splits have additional data column `label_candidates` that the (train) doesn't have.
When loading such data, an exception occurs at table.py:cast_table_to_schema, because of mismatched columns. | {
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https://api.github.com/repos/huggingface/datasets/issues/5460 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5460/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5460/comments | https://api.github.com/repos/huggingface/datasets/issues/5460/events | https://github.com/huggingface/datasets/pull/5460 | 1,555,387,532 | PR_kwDODunzps5Icn9C | 5,460 | Document that removing all the columns returns an empty document and the num_row is lost | {
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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... | 2023-01-24T17:33:38Z | 2023-01-25T16:11:10Z | 2023-01-25T16:04:03Z | CONTRIBUTOR | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/6166 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6166/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6166/comments | https://api.github.com/repos/huggingface/datasets/issues/6166/events | https://github.com/huggingface/datasets/pull/6166 | 1,861,259,055 | PR_kwDODunzps5YfOt0 | 6,166 | Document BUILDER_CONFIG_CLASS | {
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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... | 2023-08-22T11:27:41Z | 2023-08-23T14:01:25Z | 2023-08-23T13:52:36Z | MEMBER | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/4526 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4526/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4526/comments | https://api.github.com/repos/huggingface/datasets/issues/4526/events | https://github.com/huggingface/datasets/issues/4526 | 1,276,580,185 | I_kwDODunzps5MFxFZ | 4,526 | split cache used when processing different split | {
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"I was not able to reproduce this behavior (I tried without using pytorch lightning though, since I don't know what code you ran in pytorch lightning to get this).\r\n\r\nIf you can provide a MWE that would be perfect ! :)",
"Hi, I think the issue happened because I was loading datasets under an `if` ... `else` s... | 2022-06-20T08:44:58Z | 2022-06-28T14:04:58Z | null | CONTRIBUTOR | null | null | null | ## Describe the bug`
```
ds1 = load_dataset('squad', split='validation')
ds2 = load_dataset('squad', split='train')
ds1 = ds1.map(some_function)
ds2 = ds2.map(some_function)
assert ds1 == ds2
```
This happens when ds1 and ds2 are created in `pytorch_lightning.DataModule` through
```
class myDataModule:
def train_dataloader(self):
ds = load_dataset('squad', split='train')
ds = ds.map(some_function)
return [ds]
def val_dataloader(self):
ds = load_dataset('squad', split="validation")
ds = ds.map(some_function)
return [ds]
```
I don't know if it depends on `pytorch_lightning` or `datasets` but setting `ds.map(some_function, load_from_cache_file=False)` fixes the issue.
If this is not enough to replicate I will try and provide and MWE, I don't have time now so I thought I wuld open the issue first! | {
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https://api.github.com/repos/huggingface/datasets/issues/1356 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1356/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1356/comments | https://api.github.com/repos/huggingface/datasets/issues/1356/events | https://github.com/huggingface/datasets/pull/1356 | 759,994,457 | MDExOlB1bGxSZXF1ZXN0NTM0ODk3OTQ1 | 1,356 | Add StackOverflow StackSample dataset | {
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"@lhoestq Thanks for the review and suggestions! I've added your comments and pushed the changes. I'm having issues with the dummy data still. When I run the dummy data test\r\n\r\n```bash\r\nRUN_SLOW=1 pytest tests/test_dataset_common.py::LocalDatasetTest::test_load_dataset_all_configs_so_stacksample\r\n```\r\nI g... | 2020-12-09T04:59:51Z | 2020-12-21T14:48:21Z | 2020-12-21T14:48:21Z | NONE | null | 0 | {
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} | This PR adds the StackOverflow StackSample dataset from Kaggle: https://www.kaggle.com/stackoverflow/stacksample
Ran through all of the steps. However, since my dataset requires manually downloading the data, I was unable to run the pytest on the real dataset (the dummy data pytest passed). | {
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https://api.github.com/repos/huggingface/datasets/issues/4271 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4271/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4271/comments | https://api.github.com/repos/huggingface/datasets/issues/4271/events | https://github.com/huggingface/datasets/issues/4271 | 1,224,404,403 | I_kwDODunzps5I-u2z | 4,271 | A typo in docs of datasets.disable_progress_bar | {
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"Hi! Thanks for catching and reporting the typo, a PR has been opened to fix it :)"
] | 2022-05-03T17:44:56Z | 2022-05-04T06:58:35Z | 2022-05-04T06:58:35Z | NONE | null | null | null | ## Describe the bug
in the docs of V2.1.0 datasets.disable_progress_bar, we should replace "enable" with "disable". | {
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https://api.github.com/repos/huggingface/datasets/issues/3864 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3864/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3864/comments | https://api.github.com/repos/huggingface/datasets/issues/3864/events | https://github.com/huggingface/datasets/pull/3864 | 1,162,804,942 | PR_kwDODunzps40HQZ_ | 3,864 | Update image dataset tags | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3864). All of your documentation changes will be reflected on that endpoint."
] | 2022-03-08T15:36:32Z | 2022-03-08T17:04:47Z | 2022-03-08T17:04:46Z | CONTRIBUTOR | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/3648 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3648/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3648/comments | https://api.github.com/repos/huggingface/datasets/issues/3648/events | https://github.com/huggingface/datasets/pull/3648 | 1,117,465,505 | PR_kwDODunzps4xvXig | 3,648 | Fix Windows CI: bump python to 3.7 | {
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https://api.github.com/repos/huggingface/datasets/issues/4673 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4673/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4673/comments | https://api.github.com/repos/huggingface/datasets/issues/4673/events | https://github.com/huggingface/datasets/issues/4673 | 1,301,010,331 | I_kwDODunzps5Ni9eb | 4,673 | load_datasets on csv returns everything as a string | {
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"Hi @courtneysprouse, thanks for reporting.\r\n\r\nYes, you are right: by default the \"csv\" loader loads all columns as strings. \r\n\r\nYou could tweak this behavior by passing the `feature` argument to `load_dataset`, but it is also true that currently it is not possible to perform some kind of casts, due to la... | 2022-07-11T17:30:24Z | 2022-07-12T13:33:09Z | 2022-07-12T13:33:08Z | NONE | null | null | null | ## Describe the bug
If you use:
`conll_dataset.to_csv("ner_conll.csv")`
It will create a csv file with all of your data as expected, however when you load it with:
`conll_dataset = load_dataset("csv", data_files="ner_conll.csv")`
everything is read in as a string. For example if I look at everything in 'ner_tags' I get back `['[3 0 7 0 0 0 7 0 0]', '[1 2]', '[5 0]']` instead of what I originally saved which was `[[3, 0, 7, 0, 0, 0, 7, 0, 0], [1, 2], [5, 0]]`
I think maybe there is something funky going on with the csv delimiter
## Steps to reproduce the bug
```python
# Sample code to reproduce the bug
#load original conll dataset
orig_conll = load_dataset("conll2003")
#save original conll as a csv
orig_conll.to_csv("ner_conll.csv")
#reload conll data as a csv
new_conll = load_dataset("csv", data_files="ner_conll.csv")`
```
## Expected results
A clear and concise description of the expected results.
I would expect the data be returned as the data type I saved it as. I.e. if I save a list of ints
[[3, 0, 7, 0, 0, 0, 7, 0, 0]], I shouldnt get back a string ['[3 0 7 0 0 0 7 0 0]']
I also get back a string when I pass a list of strings ['EU', 'rejects', 'German', 'call', 'to', 'boycott', 'British', 'lamb', '.']
## Actual results
A list of strings `['[3 0 7 0 0 0 7 0 0]', '[1 2]', '[5 0]']`
A string "['EU' 'rejects' 'German' 'call' 'to' 'boycott' 'British' 'lamb' '.']"
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.18.3
- Platform: Linux-5.4.0-121-generic-x86_64-with-glibc2.17
- Python version: 3.8.13
- PyArrow version: 8.0.0
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"Hi @lhoestq,\r\nCould you please help me, I got this error message in all \"ci/circleci: run_dataset_script_tests_pyarrow*\" tests:\r\n```\r\n...\r\n \"\"\"Wrapper classes for various types of tokenization.\"\"\"\r\n \r\n from bleurt.lib import bert_tokenization\r\n import tensorflow.compat.v1 as tf\r\... | 2021-04-13T08:24:07Z | 2021-04-13T14:05:14Z | 2021-04-13T14:05:14Z | CONTRIBUTOR | null | 0 | {
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} | I would like to add [SLR35](https://openslr.org/35/) (18GB) and [SLR36](https://openslr.org/36/) (22GB) which are Large Javanese and Sundanese ASR training data set collected by Google in collaboration with Reykjavik University and Universitas Gadjah Mada in Indonesia. | {
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"Yes that would be awesome. Not only the download speeds are awful, but also some files are missing.\r\nWe list all the URLs in the datasets/wmt19/wmt_utils.py so we can make a script to download them all and host on S3.\r\nAlso I think most of the materials are under the CC BY-NC-SA 3.0 license (must double check)... | 2021-02-16T18:36:11Z | 2021-10-26T06:55:42Z | 2021-03-25T11:53:23Z | CONTRIBUTOR | null | null | null | Would it be possible to mirror the wmt data files under hf? Some of them take hours to download and not because of the local speed. They are all quite small datasets, just extremely slow to download.
Thank you! | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"Some CI fails are unrelated to your PR and fixed on master, feel free to merge master into your branch :)",
"Thanks @nateraw for the addition of this dataset.\r\n\r\nI would suggest to transfer it to the Hugging Face Hub, under a \... | 2022-05-23T16:34:05Z | 2023-09-24T09:37:05Z | 2022-10-03T09:36:56Z | CONTRIBUTOR | null | 0 | {
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} | This PR adds the Pascal VOC dataset in the same way TFDS has it added. I believe we can iterate on this dataset and in future versions include more data, such as segmentation masks, but for now I think it is a good idea to just add it the same way as TFDS to get a solid first version out there. | {
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https://api.github.com/repos/huggingface/datasets/issues/3368 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3368/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3368/comments | https://api.github.com/repos/huggingface/datasets/issues/3368/events | https://github.com/huggingface/datasets/pull/3368 | 1,069,403,624 | PR_kwDODunzps4vTObo | 3,368 | Fix dict source_datasets tagset validator | {
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} | Currently, the `source_datasets` tag validation does not support passing a dict with configuration keys.
This PR:
- Extends `tagset_validator` to support regex tags
- Uses `tagset_validator` to validate dict `source_datasets` | {
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https://api.github.com/repos/huggingface/datasets/issues/5756 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5756/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5756/comments | https://api.github.com/repos/huggingface/datasets/issues/5756/events | https://github.com/huggingface/datasets/issues/5756 | 1,669,678,080 | I_kwDODunzps5jhUQA | 5,756 | Calling shuffle on a IterableDataset with streaming=True, gives "ValueError: cannot reshape array" | {
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"Hi! I've merged a PR on the Hub with a fix: https://huggingface.co/datasets/fashion_mnist/discussions/3",
"Thanks, this appears to have fixed the issue.\r\n\r\nI've created a PR for the same change in the mnist dataset: https://huggingface.co/datasets/mnist/discussions/3/files"
] | 2023-04-16T04:59:47Z | 2023-04-18T03:40:56Z | 2023-04-18T03:40:56Z | NONE | null | null | null | ### Describe the bug
When calling shuffle on a IterableDataset with streaming=True, I get the following error:
```
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/administrator/Documents/Projects/huggingface/jax-diffusers-sprint-consistency-models/virtualenv/lib/python3.10/site-packages/datasets/iterable_dataset.py", line 937, in __iter__
for key, example in ex_iterable:
File "/home/administrator/Documents/Projects/huggingface/jax-diffusers-sprint-consistency-models/virtualenv/lib/python3.10/site-packages/datasets/iterable_dataset.py", line 627, in __iter__
for x in self.ex_iterable:
File "/home/administrator/Documents/Projects/huggingface/jax-diffusers-sprint-consistency-models/virtualenv/lib/python3.10/site-packages/datasets/iterable_dataset.py", line 138, in __iter__
yield from self.generate_examples_fn(**kwargs_with_shuffled_shards)
File "/home/administrator/.cache/huggingface/modules/datasets_modules/datasets/mnist/fda16c03c4ecfb13f165ba7e29cf38129ce035011519968cdaf74894ce91c9d4/mnist.py", line 111, in _generate_examples
images = np.frombuffer(f.read(), dtype=np.uint8).reshape(size, 28, 28)
ValueError: cannot reshape array of size 59992 into shape (60000,28,28)
```
Tested with the fashion_mnist and mnist datasets
### Steps to reproduce the bug
Code to reproduce
```python
from datasets import load_dataset
SHUFFLE_SEED = 42
SHUFFLE_BUFFER_SIZE = 10_000
dataset = load_dataset('fashion_mnist', streaming=True).shuffle(seed=SHUFFLE_SEED, buffer_size=SHUFFLE_BUFFER_SIZE)
next(iter(dataset['train']))
```
### Expected behavior
A random item from the dataset and no error
### Environment info
- `datasets` version: 2.11.0
- Platform: Linux-5.15.0-69-generic-x86_64-with-glibc2.35
- Python version: 3.10.6
- Huggingface_hub version: 0.13.4
- PyArrow version: 11.0.0
- Pandas version: 2.0.0
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https://api.github.com/repos/huggingface/datasets/issues/5097 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5097/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5097/comments | https://api.github.com/repos/huggingface/datasets/issues/5097/events | https://github.com/huggingface/datasets/issues/5097 | 1,403,679,353 | I_kwDODunzps5TqnJ5 | 5,097 | Fatal error with pyarrow/libarrow.so | {
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"Thanks for reporting, @catalys1.\r\n\r\nThis seems a duplicate of:\r\n- #3310 \r\n\r\nThe source of the problem is in PyArrow:\r\n- [ARROW-15141: [C++] Fatal error condition occurred in aws_thread_launch](https://issues.apache.org/jira/browse/ARROW-15141)\r\n- [ARROW-17501: [C++] Fatal error condition occurred in ... | 2022-10-10T20:29:04Z | 2022-10-11T06:56:01Z | 2022-10-11T06:56:00Z | NONE | null | null | null | ## Describe the bug
When using datasets, at the very end of my jobs the program crashes (see trace below).
It doesn't seem to affect anything, as it appears to happen as the program is closing down. Just importing `datasets` is enough to cause the error.
## Steps to reproduce the bug
This is sufficient to reproduce the problem:
```bash
python -c "import datasets"
```
## Expected results
Program should run to completion without an error.
## Actual results
```bash
Fatal error condition occurred in /opt/vcpkg/buildtrees/aws-c-io/src/9e6648842a-364b708815.clean/source/event_loop.c:72: aws_thread_launch(&cleanup_thread, s_event_loop_destroy_async_thread_fn, el_group, &thread_options) == AWS_OP_SUCCESS
Exiting Application
################################################################################
Stack trace:
################################################################################
/u/user/miniconda3/envs/env/lib/python3.10/site-packages/pyarrow/libarrow.so.900(+0x200af06) [0x150dff547f06]
/u/user/miniconda3/envs/env/lib/python3.10/site-packages/pyarrow/libarrow.so.900(+0x20028e5) [0x150dff53f8e5]
/u/user/miniconda3/envs/env/lib/python3.10/site-packages/pyarrow/libarrow.so.900(+0x1f27e09) [0x150dff464e09]
/u/user/miniconda3/envs/env/lib/python3.10/site-packages/pyarrow/libarrow.so.900(+0x200ba3d) [0x150dff548a3d]
/u/user/miniconda3/envs/env/lib/python3.10/site-packages/pyarrow/libarrow.so.900(+0x1f25948) [0x150dff462948]
/u/user/miniconda3/envs/env/lib/python3.10/site-packages/pyarrow/libarrow.so.900(+0x200ba3d) [0x150dff548a3d]
/u/user/miniconda3/envs/env/lib/python3.10/site-packages/pyarrow/libarrow.so.900(+0x1ee0b46) [0x150dff41db46]
/u/user/miniconda3/envs/env/lib/python3.10/site-packages/pyarrow/libarrow.so.900(+0x194546a) [0x150dfee8246a]
/lib64/libc.so.6(+0x39b0c) [0x150e15eadb0c]
/lib64/libc.so.6(on_exit+0) [0x150e15eadc40]
/u/user/miniconda3/envs/env/bin/python(+0x28db18) [0x560ae370eb18]
/u/user/miniconda3/envs/env/bin/python(+0x28db4b) [0x560ae370eb4b]
/u/user/miniconda3/envs/env/bin/python(+0x28db90) [0x560ae370eb90]
/u/user/miniconda3/envs/env/bin/python(_PyRun_SimpleFileObject+0x1e6) [0x560ae37123e6]
/u/user/miniconda3/envs/env/bin/python(_PyRun_AnyFileObject+0x44) [0x560ae37124c4]
/u/user/miniconda3/envs/env/bin/python(Py_RunMain+0x35d) [0x560ae37135bd]
/u/user/miniconda3/envs/env/bin/python(Py_BytesMain+0x39) [0x560ae37137d9]
/lib64/libc.so.6(__libc_start_main+0xf3) [0x150e15e97493]
/u/user/miniconda3/envs/env/bin/python(+0x2125d4) [0x560ae36935d4]
Aborted (core dumped)
```
## Environment info
- `datasets` version: 2.5.1
- Platform: Linux-4.18.0-348.23.1.el8_5.x86_64-x86_64-with-glibc2.28
- Python version: 3.10.4
- PyArrow version: 9.0.0
- Pandas version: 1.4.3
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] | open | false | null | [] | null | [] | 2022-09-08T13:52:37Z | 2022-09-08T13:53:36Z | null | CONTRIBUTOR | null | null | null | See for example:
- https://github.com/huggingface/datasets/issues/3191
- https://github.com/huggingface/datasets/issues/3186
It would help provide clearer information on the Hub and help the dataset maintainer solve the issue by themselves quicker. Currently:
- https://huggingface.co/datasets/compguesswhat
<img width="1029" alt="Capture d’écran 2022-09-08 à 15 51 37" src="https://user-images.githubusercontent.com/1676121/189139946-6deffb91-f21b-4281-8825-a98026c69740.png">
- https://huggingface.co/datasets/nli_tr
<img width="1032" alt="Capture d’écran 2022-09-08 à 15 51 44" src="https://user-images.githubusercontent.com/1676121/189139963-d26490ed-ad23-48ea-9cfc-1ab9c4d08d0c.png">
cc @albertvillanova | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-09-07T17:20:51Z | 2022-09-08T14:59:31Z | 2022-09-08T14:57:15Z | CONTRIBUTOR | null | 0 | {
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"Hi ! Maybe it's possible to have a consistent hash for a function defined in `__main__` and a function define in a notebook.\r\n\r\nHowever for functions imported from another location, pickle uses the location to identify the code, so in that case we can't do much I believe.\r\n\r\nWould it be ok for you if we on... | 2022-10-25T01:34:33Z | 2022-11-02T15:43:22Z | 2022-11-02T15:43:22Z | CONTRIBUTOR | null | null | null | ### Feature request
I hope this is not my mistake, currently if I use `load_dataset` from a python session on a custom dataset to do the preprocessing, it will be saved in the cache and in other python sessions it will be loaded from the cache, however calling the same from a jupyter notebook does not work, meaning the preprocessing starts from scratch.
If adjusting the hashes is impossible, is there a way to manually set dataset fingerprint to "force" this behaviour?
### Motivation
If this is not already the case and I am doing something wrong, it would be useful to have the two fingerprints consistent so one can create the dataset once and then try small things on jupyter without preprocessing everything again.
### Your contribution
I am happy to try a PR if you give me some pointers where the changes should happen | {
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https://api.github.com/repos/huggingface/datasets/issues/3035 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3035/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3035/comments | https://api.github.com/repos/huggingface/datasets/issues/3035/events | https://github.com/huggingface/datasets/issues/3035 | 1,016,770,071 | I_kwDODunzps48mq4X | 3,035 | `load_dataset` does not work with uploaded arrow file | {
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"Hi ! This is not a bug, this is simply not implemented.\r\n`save_to_disk` is for on-disk serialization and was not made compatible for the Hub.\r\nThat being said, I agree we actually should make it work with the Hub x)",
"cc @LysandreJik maybe we can solve this at the same time as adding `push_to_hub`"
] | 2021-10-05T20:15:10Z | 2021-10-06T17:01:37Z | null | MEMBER | null | null | null | ## Describe the bug
I've preprocessed and uploaded a dataset here: https://huggingface.co/datasets/ami-wav2vec2/ami_headset_single_preprocessed . The dataset is in `.arrow` format.
The dataset can correctly be loaded when doing:
```bash
git lfs install
git clone https://huggingface.co/datasets/ami-wav2vec2/ami_headset_single_preprocessed
```
followed by
```python
from datasets import load_from_disk
ds = load_from_disk("./ami_headset_single_preprocessed")
```
However when I try to directly download the dataset as follows:
```python
from datasets import load_dataset
ds = load_dataset("ami-wav2vec2/ami_headset_single_preprocessed")
```
the following error occurs:
```bash
/usr/local/lib/python3.7/dist-packages/datasets/load.py in load_dataset(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, ignore_verifications, keep_in_memory, save_infos, script_version, use_auth_token, task, streaming, **config_kwargs)
1115 ignore_verifications=ignore_verifications,
1116 try_from_hf_gcs=try_from_hf_gcs,
-> 1117 use_auth_token=use_auth_token,
1118 )
1119
/usr/local/lib/python3.7/dist-packages/datasets/builder.py in download_and_prepare(self, download_config, download_mode, ignore_verifications, try_from_hf_gcs, dl_manager, base_path, use_auth_token, **download_and_prepare_kwargs)
635 if not downloaded_from_gcs:
636 self._download_and_prepare(
--> 637 dl_manager=dl_manager, verify_infos=verify_infos, **download_and_prepare_kwargs
638 )
639 # Sync info
/usr/local/lib/python3.7/dist-packages/datasets/builder.py in _download_and_prepare(self, dl_manager, verify_infos, **prepare_split_kwargs)
724 try:
725 # Prepare split will record examples associated to the split
--> 726 self._prepare_split(split_generator, **prepare_split_kwargs)
727 except OSError as e:
728 raise OSError(
/usr/local/lib/python3.7/dist-packages/datasets/builder.py in _prepare_split(self, split_generator)
1186 generator, unit=" tables", leave=False, disable=bool(logging.get_verbosity() == logging.NOTSET)
1187 ):
-> 1188 writer.write_table(table)
1189 num_examples, num_bytes = writer.finalize()
1190
/usr/local/lib/python3.7/dist-packages/datasets/arrow_writer.py in write_table(self, pa_table, writer_batch_size)
424 # reorder the arrays if necessary + cast to self._schema
425 # we can't simply use .cast here because we may need to change the order of the columns
--> 426 pa_table = pa.Table.from_arrays([pa_table[name] for name in self._schema.names], schema=self._schema)
427 batches: List[pa.RecordBatch] = pa_table.to_batches(max_chunksize=writer_batch_size)
428 self._num_bytes += sum(batch.nbytes for batch in batches)
/usr/local/lib/python3.7/dist-packages/pyarrow/table.pxi in pyarrow.lib.Table.from_arrays()
/usr/local/lib/python3.7/dist-packages/pyarrow/table.pxi in pyarrow.lib._sanitize_arrays()
/usr/local/lib/python3.7/dist-packages/pyarrow/array.pxi in pyarrow.lib.asarray()
/usr/local/lib/python3.7/dist-packages/pyarrow/table.pxi in pyarrow.lib.ChunkedArray.cast()
/usr/local/lib/python3.7/dist-packages/pyarrow/compute.py in cast(arr, target_type, safe)
279 else:
280 options = CastOptions.unsafe(target_type)
--> 281 return call_function("cast", [arr], options)
282
283
/usr/local/lib/python3.7/dist-packages/pyarrow/_compute.pyx in pyarrow._compute.call_function()
/usr/local/lib/python3.7/dist-packages/pyarrow/_compute.pyx in pyarrow._compute.Function.call()
/usr/local/lib/python3.7/dist-packages/pyarrow/error.pxi in pyarrow.lib.pyarrow_internal_check_status()
/usr/local/lib/python3.7/dist-packages/pyarrow/error.pxi in pyarrow.lib.check_status()
ArrowNotImplementedError: Unsupported cast from struct<train: struct<name: string, num_bytes: int64, num_examples: int64, dataset_name: string>, validation: struct<name: string, num_bytes: int64, num_examples: int64, dataset_name: string>, test: struct<name: string, num_bytes: int64, num_examples: int64, dataset_name: string>> to list using function cast_list
```
## Expected results
The dataset should be correctly loaded with `load_dataset` IMO.
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.12.2.dev0
- Platform: Linux-5.11.0-34-generic-x86_64-with-glibc2.10
- Python version: 3.8.5
- PyArrow version: 5.0.0
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} | Updates LexGLUE and MultiEURLEX README.md files
- Fix leaderboard in LexGLUE.
- Fix an error in the CaseHOLD data example.
- Turn MultiEURLEX dataset statistics table into HTML to nicely render in HF website. | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-06-30T11:00:31Z | 2022-06-30T13:33:11Z | 2022-06-30T13:22:26Z | MEMBER | null | 0 | {
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} | This PR tries to fix recurrent random CI failures on Windows.
After 2 runs, it seems to have fixed the issue.
Fix #4603. | {
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"cc @sanchit-gandhi @Vaibhavs10 @lhoestq - this is mainly for demos that use Common Voice datasets as done here: https://github.com/facebookresearch/fairseq/tree/main/examples/mms#-transformers\r\n",
"Hi ! the error for me is\r\n\r\n```\r\nFileNotFoundError: Couldn't find a dataset script at /content/mozilla-foun... | 2023-06-14T10:03:39Z | 2023-06-14T16:36:51Z | 2023-06-14T12:26:32Z | MEMBER | null | null | null | ### Describe the bug
When I attempt to download a model from the Hub that is gated without being logged in, I get a nice error message. E.g.:
E.g.
```sh
Repository Not Found for url: https://huggingface.co/api/models/DeepFloyd/IF-I-XL-v1.0.
Please make sure you specified the correct `repo_id` and `repo_type`.
If you are trying to access a private or gated repo, make sure you are authenticated.
Invalid username or password..
Will try to load from local cache.
```
If I do the same for a gated dataset on the Hub, I'm not gated a nice error message IMO:
```sh
File ~/hf/lib/python3.10/site-packages/fsspec/implementations/http.py:430, in HTTPFileSystem._info(self, url, **kwargs)
427 except Exception as exc:
428 if policy == "get":
429 # If get failed, then raise a FileNotFoundError
--> 430 raise FileNotFoundError(url) from exc
431 logger.debug(str(exc))
433 return {"name": url, "size": None, **info, "type": "file"}
FileNotFoundError: https://huggingface.co/datasets/mozilla-foundation/common_voice_13_0/resolve/main/n_shards.json
```
### Steps to reproduce the bug
```
huggingface-cli logout
```
and then:
```py
from datasets import load_dataset, Audio
# English
stream_data = load_dataset("mozilla-foundation/common_voice_13_0", "en", split="test", streaming=True)
stream_data = stream_data.cast_column("audio", Audio(sampling_rate=16000))
en_sample = next(iter(stream_data))["audio"]["array"]
# Swahili
stream_data = load_dataset("mozilla-foundation/common_voice_13_0", "sw", split="test", streaming=True)
stream_data = stream_data.cast_column("audio", Audio(sampling_rate=16000))
sw_sample = next(iter(stream_data))["audio"]["array"]
```
### Expected behavior
Better error message
### Environment info
Copy-and-paste the text below in your GitHub issue.
- `datasets` version: 2.12.0
- Platform: Linux-6.2.0-76060200-generic-x86_64-with-glibc2.35
- Python version: 3.10.6
- Huggingface_hub version: 0.16.0.dev0
- PyArrow version: 11.0.0
- Pandas version: 1.5.3
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"Thanks, looking at it",
"Not sure what happened 😬, but it's fixed"
] | 2022-06-02T19:18:38Z | 2022-06-07T18:50:37Z | 2022-06-07T18:50:37Z | MEMBER | null | null | null | ### Link
https://huggingface.co/datasets/amazon_polarity/viewer/amazon_polarity/test
### Description
For some reason the train split is OK but the test split is not for this dataset:
```
Server error
Status code: 400
Exception: FileNotFoundError
Message: [Errno 2] No such file or directory: '/cache/modules/datasets_modules/datasets/amazon_polarity/__init__.py'
```
### Owner
No | {
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https://api.github.com/repos/huggingface/datasets/issues/6295 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6295/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6295/comments | https://api.github.com/repos/huggingface/datasets/issues/6295/events | https://github.com/huggingface/datasets/pull/6295 | 1,937,362,102 | PR_kwDODunzps5cfiW8 | 6,295 | Fix parquet columns argument in streaming mode | {
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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... | 2023-10-11T10:01:01Z | 2023-10-11T16:30:24Z | 2023-10-11T16:21:36Z | MEMBER | null | 0 | {
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} | It was failing when there's a DatasetInfo with non-None info.features from the YAML (therefore containing columns that should be ignored)
Fix https://github.com/huggingface/datasets/issues/6293 | {
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https://api.github.com/repos/huggingface/datasets/issues/4745 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4745/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4745/comments | https://api.github.com/repos/huggingface/datasets/issues/4745/events | https://github.com/huggingface/datasets/issues/4745 | 1,318,016,655 | I_kwDODunzps5Oj1aP | 4,745 | Allow `list_datasets` to include private datasets | {
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"Thanks for opening this issue :)\r\n\r\nIf it can help, I think you can already use `huggingface_hub` to achieve this:\r\n```python\r\n>>> from huggingface_hub import HfApi\r\n>>> [ds_info.id for ds_info in HfApi().list_datasets(use_auth_token=token) if ds_info.private]\r\n['bigscience/xxxx', 'bigscience-catalogue... | 2022-07-26T10:16:08Z | 2023-07-25T15:01:49Z | 2023-07-25T15:01:49Z | NONE | null | null | null | I am working with a large collection of private datasets, it would be convenient for me to be able to list them.
I would envision extending the convention of using `use_auth_token` keyword argument to `list_datasets` function, then calling:
```
list_datasets(use_auth_token="my_token")
```
would return the list of all datasets I have permissions to view, including private ones. The only current alternative I see is to use the hub website to manually obtain the list of dataset names - this is in the context of BigScience where respective private spaces contain hundreds of datasets, so not very convenient to list manually. | {
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https://api.github.com/repos/huggingface/datasets/issues/2748 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2748/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2748/comments | https://api.github.com/repos/huggingface/datasets/issues/2748/events | https://github.com/huggingface/datasets/pull/2748 | 958,889,041 | MDExOlB1bGxSZXF1ZXN0NzAyMDg4NTk4 | 2,748 | Generate metadata JSON for wikihow dataset | {
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} | Related to #2743. | {
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https://api.github.com/repos/huggingface/datasets/issues/6280 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6280/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6280/comments | https://api.github.com/repos/huggingface/datasets/issues/6280/events | https://github.com/huggingface/datasets/issues/6280 | 1,928,215,278 | I_kwDODunzps5y7jru | 6,280 | Couldn't cast array of type fixed_size_list to Sequence(Value(float64)) | {
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"Thanks for reporting! I've opened a PR with a fix.",
"Thanks for the quick response @mariosasko! I just installed your branch via `poetry add 'git+https://github.com/huggingface/datasets#fix-array_values'` and I can confirm it works on the example provided.\r\n\r\nFollow up question for you, should `None`s be s... | 2023-10-05T12:48:31Z | 2023-10-13T09:41:54Z | null | NONE | null | null | null | ### Describe the bug
I have a dataset with an embedding column, when I try to map that dataset I get the following exception:
```
Traceback (most recent call last):
File "/Users/jmif/.virtualenvs/llm-training/lib/python3.10/site-packages/datasets/arrow_dataset.py", line 3189, in map
for rank, done, content in iflatmap_unordered(
File "/Users/jmif/.virtualenvs/llm-training/lib/python3.10/site-packages/datasets/utils/py_utils.py", line 1387, in iflatmap_unordered
[async_result.get(timeout=0.05) for async_result in async_results]
File "/Users/jmif/.virtualenvs/llm-training/lib/python3.10/site-packages/datasets/utils/py_utils.py", line 1387, in <listcomp>
[async_result.get(timeout=0.05) for async_result in async_results]
File "/Users/jmif/.virtualenvs/llm-training/lib/python3.10/site-packages/multiprocess/pool.py", line 774, in get
raise self._value
TypeError: Couldn't cast array of type
fixed_size_list<item: float>[2]
to
Sequence(feature=Value(dtype='float32', id=None), length=2, id=None)
```
### Steps to reproduce the bug
Here's a simple repro script:
```
from datasets import Features, Value, Sequence, ClassLabel, Dataset
dataset_features = Features({
'text': Value('string'),
'embedding': Sequence(Value('double'), length=2),
'categories': Sequence(ClassLabel(names=sorted([
'one',
'two',
'three'
]))),
})
dataset = Dataset.from_dict(
{
'text': ['A'] * 10000,
'embedding': [[0.0, 0.1]] * 10000,
'categories': [[0]] * 10000,
},
features=dataset_features
)
def test_mapper(r):
r['text'] = list(map(lambda t: t + ' b', r['text']))
return r
dataset = dataset.map(test_mapper, batched=True, batch_size=10, features=dataset_features, num_proc=2)
```
Removing the embedding column fixes the issue!
### Expected behavior
The mapping completes successfully.
### Environment info
- `datasets` version: 2.14.4
- Platform: macOS-14.0-arm64-arm-64bit
- Python version: 3.10.12
- Huggingface_hub version: 0.17.1
- PyArrow version: 13.0.0
- Pandas version: 2.0.3 | {
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https://api.github.com/repos/huggingface/datasets/issues/6276 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6276/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6276/comments | https://api.github.com/repos/huggingface/datasets/issues/6276/events | https://github.com/huggingface/datasets/issues/6276 | 1,925,961,878 | I_kwDODunzps5yy9iW | 6,276 | I'm trying to fine tune the openai/whisper model from huggingface using jupyter notebook and i keep getting this error | {
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"Since you are using Windows, maybe moving the `map` call inside `if __name__ == \"__main__\"` can fix the issue:\r\n```python\r\nif __name__ == \"__main__\":\r\n common_voice = common_voice.map(prepare_dataset, remove_columns=common_voice.column_names[\"train\"], num_proc=4)\r\n```\r\n\r\nOtherwise, the only s... | 2023-10-04T11:03:41Z | 2023-10-04T22:14:38Z | null | NONE | null | null | null | ### Describe the bug
I'm trying to fine tune the openai/whisper model from huggingface using jupyter notebook and i keep getting this error, i'm following the steps in this blog post
https://huggingface.co/blog/fine-tune-whisper
I tried google collab and it works but because I'm on the free version the training doesn't complete
the error comes in jupyter notebook when i run this line
`common_voice = common_voice.map(prepare_dataset, remove_columns=common_voice.column_names["train"], num_proc=4)`
here is the error message
```
Map (num_proc=4): 0% 0/2506 [00:52<?, ? examples/s]
The above exception was the direct cause of the following exception:
NameError Traceback (most recent call last) Cell In[19], line 1 ----> 1 common_voice = common_voice.map(prepare_dataset, remove_columns=common_voice.column_names["train"], num_proc=4)
File ~\anaconda\Lib\site-packages\datasets\dataset_dict.py:853, in DatasetDict.map(self, function, with_indices, with_rank, input_columns, batched, batch_size, drop_last_batch, remove_columns, keep_in_memory, load_from_cache_file, cache_file_names, writer_batch_size, features, disable_nullable, fn_kwargs, num_proc, desc) 850 if cache_file_names is None: 851 cache_file_names = {k: None for k in self} 852 return DatasetDict( --> 853 { 854 k: dataset.map( 855 function=function, 856 with_indices=with_indices, 857 with_rank=with_rank, 858 input_columns=input_columns, 859 batched=batched, 860 batch_size=batch_size, 861 drop_last_batch=drop_last_batch, 862 remove_columns=remove_columns, 863 keep_in_memory=keep_in_memory, 864 load_from_cache_file=load_from_cache_file, 865 cache_file_name=cache_file_names[k], 866 writer_batch_size=writer_batch_size, 867 features=features, 868 disable_nullable=disable_nullable, 869 fn_kwargs=fn_kwargs, 870 num_proc=num_proc, 871 desc=desc, 872 ) 873 for k, dataset in self.items() 874 } 875 )
File ~\anaconda\Lib\site-packages\datasets\dataset_dict.py:854, in <dictcomp>(.0) 850 if cache_file_names is None: 851 cache_file_names = {k: None for k in self} 852 return DatasetDict( 853 { --> 854 k: dataset.map( 855 function=function, 856 with_indices=with_indices, 857 with_rank=with_rank, 858 input_columns=input_columns, 859 batched=batched, 860 batch_size=batch_size, 861 drop_last_batch=drop_last_batch, 862 remove_columns=remove_columns, 863 keep_in_memory=keep_in_memory, 864 load_from_cache_file=load_from_cache_file, 865 cache_file_name=cache_file_names[k], 866 writer_batch_size=writer_batch_size, 867 features=features, 868 disable_nullable=disable_nullable, 869 fn_kwargs=fn_kwargs, 870 num_proc=num_proc, 871 desc=desc, 872 ) 873 for k, dataset in self.items() 874 } 875 )
File ~\anaconda\Lib\site-packages\datasets\arrow_dataset.py:592, in transmit_tasks.<locals>.wrapper(*args, **kwargs) 590 self: "Dataset" = kwargs.pop("self") 591 # apply actual function --> 592 out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs) 593 datasets: List["Dataset"] = list(out.values()) if isinstance(out, dict) else [out] 594 for dataset in datasets: 595 # Remove task templates if a column mapping of the template is no longer valid
File ~\anaconda\Lib\site-packages\datasets\arrow_dataset.py:557, in transmit_format.<locals>.wrapper(*args, **kwargs) 550 self_format = { 551 "type": self._format_type, 552 "format_kwargs": self._format_kwargs, 553 "columns": self._format_columns, 554 "output_all_columns": self._output_all_columns, 555 } 556 # apply actual function --> 557 out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs) 558 datasets: List["Dataset"] = list(out.values()) if isinstance(out, dict) else [out] 559 # re-apply format to the output
File ~\anaconda\Lib\site-packages\datasets\arrow_dataset.py:3189, in Dataset.map(self, function, with_indices, with_rank, input_columns, batched, batch_size, drop_last_batch, remove_columns, keep_in_memory, load_from_cache_file, cache_file_name, writer_batch_size, features, disable_nullable, fn_kwargs, num_proc, suffix_template, new_fingerprint, desc) 3182 logger.info(f"Spawning {num_proc} processes") 3183 with logging.tqdm( 3184 disable=not logging.is_progress_bar_enabled(), 3185 unit=" examples", 3186 total=pbar_total, 3187 desc=(desc or "Map") + f" (num_proc={num_proc})", 3188 ) as pbar: -> 3189 for rank, done, content in iflatmap_unordered( 3190 pool, Dataset._map_single, kwargs_iterable=kwargs_per_job 3191 ): 3192 if done: 3193 shards_done += 1
File ~\anaconda\Lib\site-packages\datasets\utils\py_utils.py:1394, in iflatmap_unordered(pool, func, kwargs_iterable) 1391 finally: 1392 if not pool_changed: 1393 # we get the result in case there's an error to raise -> 1394 [async_result.get(timeout=0.05) for async_result in async_results]
File ~\anaconda\Lib\site-packages\datasets\utils\py_utils.py:1394, in <listcomp>(.0) 1391 finally: 1392 if not pool_changed: 1393 # we get the result in case there's an error to raise -> 1394 [async_result.get(timeout=0.05) for async_result in async_results]
File ~\anaconda\Lib\site-packages\multiprocess\pool.py:774, in ApplyResult.get(self, timeout) 772 return self._value 773 else: --> 774 raise self._value
NameError: name 'feature_extractor' is not defined
```
### Steps to reproduce the bug
1. follow the steps in this blog post
https://huggingface.co/blog/fine-tune-whisper
2. run this line of code
`common_voice = common_voice.map(prepare_dataset, remove_columns=common_voice.column_names["train"], num_proc=4)`
3. I'm using jupyter notebook from anaconda
### Expected behavior
No error message
### Environment info
datasets version: 2.8.0
Python version: 3.11
Windows 10 | {
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https://api.github.com/repos/huggingface/datasets/issues/3057 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3057/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3057/comments | https://api.github.com/repos/huggingface/datasets/issues/3057/events | https://github.com/huggingface/datasets/issues/3057 | 1,022,508,315 | I_kwDODunzps488j0b | 3,057 | Error in per class precision computation | {
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"Hi @tidhamecha2, thanks for reporting.\r\n\r\nIndeed, we fixed this issue just one week ago: #3008\r\n\r\nThe fix will be included in our next version release.\r\n\r\nIn the meantime, you can incorporate the fix by installing `datasets` from the master branch:\r\n```\r\npip install -U git+ssh://git@github.com/hugg... | 2021-10-11T10:05:19Z | 2021-10-11T10:17:44Z | 2021-10-11T10:16:16Z | NONE | null | null | null | ## Describe the bug
When trying to get the per class precision values by providing `average=None`, following error is thrown `ValueError: can only convert an array of size 1 to a Python scalar`
## Steps to reproduce the bug
```python
from datasets import load_dataset, load_metric
precision_metric = load_metric("precision")
predictions = [0, 2, 1, 0, 0, 1]
references = [0, 1, 2, 0, 1, 2]
results = precision_metric.compute(predictions=predictions, references=references, average=None)
```
## Expected results
` {'precision': array([0.66666667, 0. , 0. ])}`
as per https://github.com/huggingface/datasets/blob/master/metrics/precision/precision.py
## Actual results
```
output = self._compute(predictions=predictions, references=references, **kwargs)
File "~/.cache/huggingface/modules/datasets_modules/metrics/precision/94709a71c6fe37171ef49d3466fec24dee9a79846c9f176dff66a649e9811690/precision.py", line 110, in _compute
sample_weight=sample_weight,
ValueError: can only convert an array of size 1 to a Python scalar
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.12.1
- Platform: linux
- Python version: 3.6.9
- PyArrow version: 5.0.0
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https://api.github.com/repos/huggingface/datasets/issues/2287 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2287/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2287/comments | https://api.github.com/repos/huggingface/datasets/issues/2287/events | https://github.com/huggingface/datasets/pull/2287 | 871,063,374 | MDExOlB1bGxSZXF1ZXN0NjI2MTQ0MTQ3 | 2,287 | Avoid copying table's record batches | {
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"Thanks for fixing it. I actually included a similar fix in #2291 along with some updates in tests\r\nI'm closing this one in favor of #2291 if you don't mind.\r\n\r\nThanks again !"
] | 2021-04-29T14:15:01Z | 2021-04-29T16:34:23Z | 2021-04-29T16:34:22Z | CONTRIBUTOR | null | 0 | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"Thanks for the fix.\r\n\r\nI'm wondering how this fixes backward compatibility...\r\n\r\nExecuting this code:\r\n```python\r\nfrom datasets.utils.download_manager import DownloadMode\r\n```\r\nwe will have\r\n```python\r\nDownloadMod... | 2022-06-15T09:44:33Z | 2022-06-15T10:33:28Z | 2022-06-15T10:23:44Z | MEMBER | null | 0 | {
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} | https://github.com/huggingface/datasets/pull/4384 moved `datasets.utils.download_manager` to `datasets.download.download_manager`
This breaks `evaluate` which imports `DownloadMode` from `datasets.utils.download_manager`
This PR re-adds `datasets.utils.download_manager` without circular imports.
We could also show a message that says that accessing it is deprecated, but I think we can do this in a subsequent PR, and just focus on doing a patch release for now | {
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https://api.github.com/repos/huggingface/datasets/issues/2644 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2644/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2644/comments | https://api.github.com/repos/huggingface/datasets/issues/2644/events | https://github.com/huggingface/datasets/issues/2644 | 944,254,748 | MDU6SXNzdWU5NDQyNTQ3NDg= | 2,644 | Batched `map` not allowed to return 0 items | {
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"Hi ! Thanks for reporting. Indeed it looks like type inference makes it fail. We should probably just ignore this step until a non-empty batch is passed.",
"Sounds good! Do you want me to propose a PR? I'm quite busy right now, but if it's not too urgent I could take a look next week.",
"Sure if you're interes... | 2021-07-14T09:58:19Z | 2021-07-26T14:55:15Z | 2021-07-26T14:55:15Z | MEMBER | null | null | null | ## Describe the bug
I'm trying to use `map` to filter a large dataset by selecting rows that match an expensive condition (files referenced by one of the columns need to exist in the filesystem, so we have to `stat` them). According to [the documentation](https://huggingface.co/docs/datasets/processing.html#augmenting-the-dataset), `a batch mapped function can take as input a batch of size N and return a batch of size M where M can be greater or less than N and can even be zero`.
However, when the returned batch has a size of zero (neither item in the batch fulfilled the condition), we get an `index out of bounds` error. I think that `arrow_writer.py` is [trying to infer the returned types using the first element returned](https://github.com/huggingface/datasets/blob/master/src/datasets/arrow_writer.py#L100), but no elements were returned in this case.
For this error to happen, I'm returning a dictionary that contains empty lists for the keys I want to keep, see below. If I return an empty dictionary instead (no keys), then a different error eventually occurs.
## Steps to reproduce the bug
```python
def select_rows(examples):
# `key` is a column name that exists in the original dataset
# The following line simulates no matches found, so we return an empty batch
result = {'key': []}
return result
filtered_dataset = dataset.map(
select_rows,
remove_columns = dataset.column_names,
batched = True,
num_proc = 1,
desc = "Selecting rows with images that exist"
)
```
The code above immediately triggers the exception. If we use the following instead:
```python
def select_rows(examples):
# `key` is a column name that exists in the original dataset
result = {'key': []} # or defaultdict or whatever
# code to check for condition and append elements to result
# some_items_found will be set to True if there were any matching elements in the batch
return result if some_items_found else {}
```
Then it _seems_ to work, but it eventually fails with some sort of schema error. I believe it may happen when an empty batch is followed by a non-empty one, but haven't set up a test to verify it.
In my opinion, returning a dictionary with empty lists and valid column names should be accepted as a valid result with zero items.
## Expected results
The dataset would be filtered and only the matching fields would be returned.
## Actual results
An exception is encountered, as described. Using a workaround makes it fail further along the line.
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.9.1.dev0
- Platform: Linux-5.4.0-53-generic-x86_64-with-glibc2.17
- Python version: 3.8.10
- PyArrow version: 4.0.1
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https://api.github.com/repos/huggingface/datasets/issues/3524 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3524/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3524/comments | https://api.github.com/repos/huggingface/datasets/issues/3524/events | https://github.com/huggingface/datasets/pull/3524 | 1,093,826,723 | PR_kwDODunzps4wiK_v | 3,524 | Adding link to license. | {
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https://api.github.com/repos/huggingface/datasets/issues/1790 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1790/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1790/comments | https://api.github.com/repos/huggingface/datasets/issues/1790/events | https://github.com/huggingface/datasets/issues/1790 | 796,678,157 | MDU6SXNzdWU3OTY2NzgxNTc= | 1,790 | ModuleNotFoundError: No module named 'apache_beam', when specific languages. | {
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"Hi !\r\n\r\nApache Beam is a framework used to define data transformation pipelines. These pipeline can then be run in many runtimes: DataFlow, Spark, Flink, etc. There also exist a local runner called the DirectRunner.\r\nWikipedia is a dataset that requires some parsing, so to allow the processing to be run on t... | 2021-01-29T08:17:24Z | 2021-03-25T12:10:51Z | null | CONTRIBUTOR | null | null | null | ```py
import datasets
wiki = datasets.load_dataset('wikipedia', '20200501.ja', cache_dir='./datasets')
```
then `ModuleNotFoundError: No module named 'apache_beam'` happend.
The error doesn't appear when it's '20200501.en'.
I don't know Apache Beam, but according to #498 it isn't necessary when it's saved to local. is it correct? | {
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https://api.github.com/repos/huggingface/datasets/issues/4494 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4494/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4494/comments | https://api.github.com/repos/huggingface/datasets/issues/4494/events | https://github.com/huggingface/datasets/issues/4494 | 1,271,850,599 | I_kwDODunzps5LzuZn | 4,494 | Patching fails for modules that are not installed or don't exist | {
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When trying to patch `scipy.io.loadmat`:
```python
ModuleNotFoundError: No module named 'scipy'
```
Instead it shouldn't raise an error and do nothing
We use patching to extend such functions to support remote URLs and work in streaming mode | {
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https://api.github.com/repos/huggingface/datasets/issues/5673 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5673/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5673/comments | https://api.github.com/repos/huggingface/datasets/issues/5673/events | https://github.com/huggingface/datasets/pull/5673 | 1,641,066,352 | PR_kwDODunzps5M6wc3 | 5,673 | Pass down storage options | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"> download_and_prepare is not called when streaming a dataset, so we may need to have storage_options in the DatasetBuilder.__init__ ? This way it could also be passed later to as_streaming_dataset and the StreamingDownloadManager\r\... | 2023-03-26T20:09:37Z | 2023-03-28T15:03:38Z | 2023-03-28T14:54:17Z | CONTRIBUTOR | null | 0 | {
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} | Remove implementation-specific kwargs from `file_utils.fsspec_get` and `file_utils.fsspec_head`, instead allowing them to be passed down via `storage_options`. This fixes an issue where s3fs did not recognize a timeout arg as well as fixes an issue mentioned in https://github.com/huggingface/datasets/issues/5281 by allowing users to pass down `storage_options` all the way from `datasets.load_dataset` to support implementation-specific credentials
Supports something like the following to provide credentials explicitly instead of relying on boto's methods of locating them
```
load_dataset(..., data_files=["s3://..."], storage_options={"profile": "..."})
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/5028 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5028/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5028/comments | https://api.github.com/repos/huggingface/datasets/issues/5028/events | https://github.com/huggingface/datasets/issues/5028 | 1,386,272,533 | I_kwDODunzps5SoNcV | 5,028 | passing parameters to the method passed to Dataset.from_generator() | {
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"Hi! Yes, you can either use the `gen_kwargs` param in `Dataset.from_generator` (`ds = Dataset.from_generator(gen, gen_kwargs={\"param1\": val})`) or wrap the generator function with `functools.partial`\r\n(`ds = Dataset.from_generator(functools.partial(gen, param1=\"val\"))`) to pass custom parameters to it.\r\n"
... | 2022-09-26T15:20:06Z | 2022-10-03T13:00:00Z | 2022-10-03T13:00:00Z | NONE | null | null | null | Big thanks for providing dataset creation via a generator.
I want to ask whether there is any way that parameters can be passed to the method Dataset.from_generator() method, like as follows.
```
from datasets import Dataset
def gen(param1):
for idx in len(custom_dataset):
yield custom_dataset[idx] + param1
ds = Dataset.from_generator(gen(param1))
```
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https://api.github.com/repos/huggingface/datasets/issues/1701 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1701/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1701/comments | https://api.github.com/repos/huggingface/datasets/issues/1701/events | https://github.com/huggingface/datasets/issues/1701 | 781,345,717 | MDU6SXNzdWU3ODEzNDU3MTc= | 1,701 | Some datasets miss dataset_infos.json or dummy_data.zip | {
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"Thanks for reporting.\r\nWe should indeed add all the missing dummy_data.zip and also the dataset_infos.json at least for lm1b, reclor and wikihow.\r\n\r\nFor c4 I haven't tested the script and I think we'll require some optimizations regarding beam datasets before processing it.\r\n",
"Closing since the dummy d... | 2021-01-07T14:17:13Z | 2022-11-04T15:11:16Z | 2022-11-04T15:06:00Z | CONTRIBUTOR | null | null | null | While working on dataset REAME generation script at https://github.com/madlag/datasets_readme_generator , I noticed that some datasets miss a dataset_infos.json :
```
c4
lm1b
reclor
wikihow
```
And some does not have a dummy_data.zip :
```
kor_nli
math_dataset
mlqa
ms_marco
newsgroup
qa4mre
qangaroo
reddit_tifu
super_glue
trivia_qa
web_of_science
wmt14
wmt15
wmt16
wmt17
wmt18
wmt19
xtreme
```
But it seems that some of those last do have a "dummy" directory .
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https://api.github.com/repos/huggingface/datasets/issues/1867 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1867/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1867/comments | https://api.github.com/repos/huggingface/datasets/issues/1867/events | https://github.com/huggingface/datasets/issues/1867 | 807,127,181 | MDU6SXNzdWU4MDcxMjcxODE= | 1,867 | ERROR WHEN USING SET_TRANSFORM() | {
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"Hi @alejandrocros it looks like an incompatibility with the current Trainer @sgugger \r\nIndeed currently the Trainer of `transformers` doesn't support a dataset with a transform\r\n\r\nIt looks like it comes from this line: https://github.com/huggingface/transformers/blob/f51188cbe74195c14c5b3e2e8f10c2f435f9751a/... | 2021-02-12T10:38:31Z | 2021-03-01T14:04:24Z | 2021-02-24T12:00:43Z | NONE | null | null | null | Hi, I'm trying to use dataset.set_transform(encode) as @lhoestq told me in this issue: https://github.com/huggingface/datasets/issues/1825#issuecomment-774202797
However, when I try to use Trainer from transformers with such dataset, it throws an error:
```
TypeError: __init__() missing 1 required positional argument: 'transform'
[INFO|trainer.py:357] 2021-02-12 10:18:09,893 >> The following columns in the training set don't have a corresponding argument in `AlbertForMaskedLM.forward` and have been ignored: text.
Exception in device=TPU:0: __init__() missing 1 required positional argument: 'transform'
Traceback (most recent call last):
File "/anaconda3/envs/torch-xla-1.7/lib/python3.6/site-packages/torch_xla/distributed/xla_multiprocessing.py", line 330, in _mp_start_fn
_start_fn(index, pf_cfg, fn, args)
File "/anaconda3/envs/torch-xla-1.7/lib/python3.6/site-packages/torch_xla/distributed/xla_multiprocessing.py", line 324, in _start_fn
fn(gindex, *args)
File "/home/alejandro_vaca/transformers/examples/language-modeling/run_mlm_wwm.py", line 368, in _mp_fn
main()
File "/home/alejandro_vaca/transformers/examples/language-modeling/run_mlm_wwm.py", line 332, in main
data_collator=data_collator,
File "/anaconda3/envs/torch-xla-1.7/lib/python3.6/site-packages/transformers/trainer.py", line 286, in __init__
self._remove_unused_columns(self.train_dataset, description="training")
File "/anaconda3/envs/torch-xla-1.7/lib/python3.6/site-packages/transformers/trainer.py", line 359, in _remove_unused_columns
dataset.set_format(type=dataset.format["type"], columns=columns)
File "/home/alejandro_vaca/datasets/src/datasets/fingerprint.py", line 312, in wrapper
out = func(self, *args, **kwargs)
File "/home/alejandro_vaca/datasets/src/datasets/arrow_dataset.py", line 818, in set_format
_ = get_formatter(type, **format_kwargs)
File "/home/alejandro_vaca/datasets/src/datasets/formatting/__init__.py", line 112, in get_formatter
return _FORMAT_TYPES[format_type](**format_kwargs)
TypeError: __init__() missing 1 required positional argument: 'transform'
```
The code I'm using:
```{python}
def tokenize_function(examples):
# Remove empty lines
examples["text"] = [line for line in examples["text"] if len(line) > 0 and not line.isspace()]
return tokenizer(examples["text"], padding=padding, truncation=True, max_length=data_args.max_seq_length)
datasets.set_transform(tokenize_function)
data_collator = DataCollatorForWholeWordMask(tokenizer=tokenizer, mlm_probability=data_args.mlm_probability)
# Initialize our Trainer
trainer = Trainer(
model=model,
args=training_args,
train_dataset=datasets["train"] if training_args.do_train else None,
eval_dataset=datasets["val"] if training_args.do_eval else None,
tokenizer=tokenizer,
data_collator=data_collator,
)
```
I've installed from source, master branch.
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https://api.github.com/repos/huggingface/datasets/issues/2247 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2247/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2247/comments | https://api.github.com/repos/huggingface/datasets/issues/2247/events | https://github.com/huggingface/datasets/pull/2247 | 864,817,520 | MDExOlB1bGxSZXF1ZXN0NjIwOTgzNzY3 | 2,247 | Implement Dataset from Parquet | {
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"Hi @albertvillanova , I'll implement the parquet builder as an ArrowBasedBuilder if you don't mind",
"closing in favor of #2537 that is already merged"
] | 2021-04-22T11:01:38Z | 2021-07-26T13:28:52Z | 2021-07-26T13:28:51Z | MEMBER | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/5410 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5410/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5410/comments | https://api.github.com/repos/huggingface/datasets/issues/5410/events | https://github.com/huggingface/datasets/pull/5410 | 1,521,168,032 | PR_kwDODunzps5GvnJH | 5,410 | Map-style Dataset to IterableDataset | {
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"<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 | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_a... | 2023-01-05T18:12:17Z | 2023-02-01T18:11:45Z | 2023-02-01T16:36:01Z | MEMBER | null | 0 | {
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} | Added `ds.to_iterable()` to get an iterable dataset from a map-style arrow dataset.
It also has a `num_shards` argument to split the dataset before converting to an iterable dataset. Sharding is important to enable efficient shuffling and parallel loading of iterable datasets.
TODO:
- [x] tests
- [x] docs
Fix https://github.com/huggingface/datasets/issues/5265 | {
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"Associated community discussion is [here](https://huggingface.co/datasets/aeslc/discussions/1).\r\nPaper referenced in the `dataset_infos.json` is [here](https://arxiv.org/pdf/1906.03497.pdf). It mentions the _email-subject-generation_ task, which is not a tag mentioned in any other dataset so it was not added in... | 2022-06-16T18:52:25Z | 2022-07-08T15:14:23Z | 2022-07-08T15:02:31Z | CONTRIBUTOR | null | 0 | {
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} | yaml header at top of README.md file was edited to add task tags because I couldn't find the existing tags in the json
separate Pull Request will modify dataset_infos.json to add these tags
The Enron dataset (dataset id aeslc) is only tagged with:
arxiv:1906.03497'
languages:en
pretty_name:AESLC
Using the email subject_line field as a label or target variable it possible to create models for the following task_ids (in order of relevance):
'task_ids:summarization'
'task_ids:summarization-other-conversations-summarization'
"task_ids:other-other-query-based-multi-document-summarization"
'task_ids:summarization-other-aspect-based-summarization'
'task_ids:summarization--other-headline-generation'
The subject might also be used for the task_category "task_categories:summarization"
E-mail chains might be used for the task category "task_categories:dialogue-system" | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-07-21T20:35:41Z | 2022-07-22T07:01:00Z | 2022-07-22T06:48:42Z | CONTRIBUTOR | null | 0 | {
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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... | 2023-01-20T01:09:14Z | 2023-01-20T15:44:45Z | 2023-01-20T15:37:30Z | MEMBER | null | 0 | {
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} | Based on feedback from discussion #5423, this PR updates the sharing tutorial with a mention of writing your own dataset loading script to support more advanced dataset creation options like multiple configs.
I'll open a separate PR to update the *Create a Dataset card* with the new Hub metadata UI update 😄 | {
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"I'm just retaking and working on #2324. 😉 ",
"Resolved via https://github.com/huggingface/datasets/pull/4006."
] | 2021-06-22T15:07:21Z | 2022-06-01T17:18:16Z | 2022-06-01T17:18:16Z | MEMBER | null | null | null | In #2533 we added a task template for speech recognition that relies on the file paths to the audio files. As pointed out by @SBrandeis this is brittle as it doesn't port easily across different OS'.
The solution is to use dedicated `Audio` features when casting the dataset. These features are not yet available in `datasets`, but should be included in the `AutomaticSpeechRecognition` template once they are. | {
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"AFAIK, there is currently no built-in method on the `Dataset` object to do this.\r\nHowever, a workaround is to directly use the Arrow table backing the dataset, **but it implies loading the whole dataset in memory** (correct me if I'm mistaken @lhoestq).\r\n\r\nYou can convert the Arrow table to a pandas datafram... | 2021-02-02T02:55:40Z | 2022-06-01T15:38:13Z | 2022-06-01T15:38:13Z | NONE | null | null | null | Hi
I see there is a save_to_disk function to save data, but this is not human readable format, is there a way I could save a Dataset object in a human readable format to a file like json? thanks @lhoestq | {
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} | Awesome work on 🤗 Datasets. I found a couple of small typos in the README. Hope this helps.
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} | Here and there in the docs there is still stuff like this:
```python
>>> datasets_list = list_datasets()
>>> print(', '.join(dataset.id for dataset in datasets_list))
```
However, my understanding is that `list_datasets()` returns a list of strings rather than a list of objects. | {
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https://api.github.com/repos/huggingface/datasets/issues/4940 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4940/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4940/comments | https://api.github.com/repos/huggingface/datasets/issues/4940/events | https://github.com/huggingface/datasets/pull/4940 | 1,363,513,058 | PR_kwDODunzps4-c6WY | 4,940 | Fix multilinguality tag and missing sections in xquad_r dataset card | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-09-06T16:05:35Z | 2022-09-12T10:11:07Z | 2022-09-12T10:08:48Z | MEMBER | null | 0 | {
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- Label as multilingual: https://huggingface.co/datasets/xquad_r/discussions/1 | {
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"Hi @Dref360, thanks a lot for your proposal.\r\n\r\nIt totally makes sense to have more flexibility when class encoding, I agree.\r\n\r\nYou could even further customize the class encoding by passing an instance of `ClassLabel` itself (instead of replicating `ClassLabel` instantiation arguments as `Dataset.class_e... | 2022-02-19T21:21:45Z | 2022-02-21T12:16:35Z | 2022-02-21T12:16:35Z | CONTRIBUTOR | null | null | null | I can make a PR, just wanted approval before starting.
**Is your feature request related to a problem? Please describe.**
It is often the case that classes are not ordered in alphabetical order. Current `class_encode_column` sort the classes before indexing.
https://github.com/huggingface/datasets/blob/master/src/datasets/arrow_dataset.py#L1235
**Describe the solution you'd like**
I would like to add a **optional** parameter `class_names` to `class_encode_column` that would be used for the mapping instead of sorting the unique values.
**Describe alternatives you've considered**
One can use map instead. I find it harder to read.
```python
CLASS_NAMES = ['apple', 'orange', 'potato']
ds = ds.map(lambda item: CLASS_NAMES.index(item[label_column]))
# Proposition
ds = ds.class_encode_column(label_column, CLASS_NAMES)
```
**Additional context**
I can make the PR if this feature is accepted.
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As noted in PR #2255, the attributes of `DatasetInfo` are not documented in the [docs](https://huggingface.co/docs/datasets/package_reference/main_classes.html?highlight=datasetinfo#datasetinfo). It would be nice to do so :)
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"Build fails but this change should not be the reason...",
"rebased on master"
] | 2021-05-31T07:15:57Z | 2021-06-04T09:53:50Z | 2021-06-04T09:53:50Z | CONTRIBUTOR | null | 0 | {
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] | closed | false | null | [] | null | [] | 2021-06-27T15:00:58Z | 2021-09-26T13:42:39Z | 2021-09-26T13:42:39Z | CONTRIBUTOR | null | null | null | Currently, using a metric allows for one of the following:
- Per example/batch metrics
- Cumulative metrics over the whole data
What I'd like is to have an efficient way to get cumulative metrics over the examples/batches added so far, in order to display it as part of the progress bar during training/evaluation.
Since most metrics are just an average of per-example metrics (which aren't?), an efficient calculation can be done as follows:
`((score_cumulative * n_cumulative) + (score_new * n_new)) / (n_cumulative+ n_new)`
where `n` and `score` refer to number of examples and metric score, `cumulative` refers to the cumulative metric and `new` refers to the addition of new examples.
If you don't want to add this capability in the library, a simple solution exists so users can do it themselves:
It is easy to implement for a single process setup, but in a distributed one there is no way to get the correct `n_new`.
The solution for this is to return the number of examples that was used to compute the metrics in `.compute()` by adding the following line here:
https://github.com/huggingface/datasets/blob/5a3221785311d0ce86c2785b765e86bd6997d516/src/datasets/metric.py#L402-L403
```
output["number_of_examples"] = len(predictions)
```
and also remove the log message here so it won't spam:
https://github.com/huggingface/datasets/blob/3db67f5ff6cbf807b129d2b4d1107af27623b608/src/datasets/metric.py#L411
If this change is ok with you, I'll open a pull request.
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"Thanks for adding this @mariosasko! It worked for me when running it with a local data file, however, when using the file on Google Drive I get the following error:\r\n```Python\r\nds = load_dataset(\"./ted_talks_iwslt\",\"eu_ca_2014\", streaming=True, split=\"train\", use_auth_token=True)\r\nnext(iter(ds))\r\n```... | 2022-01-26T18:07:56Z | 2022-10-04T09:36:23Z | 2022-10-03T09:44:47Z | CONTRIBUTOR | null | 1 | {
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"Hi @miyamonz \r\nThanks for investigating this issue, good job !\r\nIt would be awesome to integrate your fix in the library, could you open a pull request ?",
"OK! I'll send it later."
] | 2021-03-11T12:51:24Z | 2021-03-22T08:33:52Z | 2021-03-22T08:33:52Z | CONTRIBUTOR | null | null | null | I tried downloading Japanese wikipedia, but it always failed because of out of memory maybe.
I found that the generator function that extracts XML data in wikipedia.py doesn't release memory in the loop.
https://github.com/huggingface/datasets/blob/13a5b7db992ad5cf77895e4c0f76595314390418/datasets/wikipedia/wikipedia.py#L464-L502
`root.clear()` intend to clear memory, but it doesn't.
https://github.com/huggingface/datasets/blob/13a5b7db992ad5cf77895e4c0f76595314390418/datasets/wikipedia/wikipedia.py#L490
https://github.com/huggingface/datasets/blob/13a5b7db992ad5cf77895e4c0f76595314390418/datasets/wikipedia/wikipedia.py#L494
I replaced them with `elem.clear()`, then it seems to work correctly.
here is the notebook to reproduce it.
https://gist.github.com/miyamonz/dc06117302b6e85fa51cbf46dde6bb51#file-xtract_content-ipynb | {
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"@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_l... | 2021-08-12T11:40:18Z | 2021-08-27T15:58:45Z | 2021-08-27T15:58:14Z | CONTRIBUTOR | null | 0 | {
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} | [GooAQ](https://github.com/allenai/gooaq) dataset was recently updated after splits were added for the same. This PR contains new updated GooAQ with train/val/test splits and updated README as well. | {
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"color": "bfdadc",... | open | false | null | [] | null | [] | 2021-11-18T15:34:44Z | 2021-12-08T12:00:02Z | null | MEMBER | null | null | null | ## Adding a Dataset
- **Name:** Natural Adversarial Objects (NAO)
- **Description:** Natural Adversarial Objects (NAO) is a new dataset to evaluate the robustness of object detection models. NAO contains 7,934 images and 9,943 objects that are unmodified and representative of real-world scenarios, but cause state-of-the-art detection models to misclassify with high confidence.
- **Paper:** https://arxiv.org/abs/2111.04204v1
- **Data:** https://drive.google.com/drive/folders/15P8sOWoJku6SSEiHLEts86ORfytGezi8
- **Motivation:** interesting object detection dataset useful for miscclassifications
cc @NielsRogge
Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
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"> all the tests pass, but I'm still not able to import the dataset\r\n\r\nSince it's not merged on `master` yet, you have to provide the path to your local `wiki_bio.py` to use it.\r\nIndeed the library downloads the dataset files from `master` if you have a dev installation of the library.\r\n\r\nI agree it would... | 2022-01-30T16:28:54Z | 2022-01-31T14:50:48Z | 2022-01-31T08:38:09Z | CONTRIBUTOR | null | 0 | {
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} | Fixes #3580 and makes the wiki_bio dataset work again. I changed the link and some documentation, and all the tests pass. Thanks @lhoestq for uploading the dataset to the HuggingFace data bucket.
@lhoestq -- all the tests pass, but I'm still not able to import the dataset, as the old Google Drive link is cached somewhere:
```python
>>> from datasets import load_dataset
load_dataset("wiki_bio>>> load_dataset("wiki_bio")
Using custom data configuration default
Downloading and preparing dataset wiki_bio/default (download: 318.53 MiB, generated: 736.94 MiB, post-processed: Unknown size, total: 1.03 GiB) to /home/jxm3/.cache/huggingface/datasets/wiki_bio/default/1.1.0/5293ce565954ba965dada626f1e79684e98172d950371d266bf3caaf87e911c9...
Traceback (most recent call last):
...
File "/home/jxm3/random/datasets/src/datasets/utils/file_utils.py", line 612, in get_from_cache
raise FileNotFoundError(f"Couldn't find file at {url}")
FileNotFoundError: Couldn't find file at https://drive.google.com/uc?export=download&id=1L7aoUXzHPzyzQ0ns4ApBbYepsjFOtXil
```
what do I have to do to invalidate the cache and actually import the dataset? It's clearly set up correctly, since the data is downloaded and processed by the tests.
As an aside, this caching-loading-scripts behavior makes for a really bad developer experience. I just wasted an hour trying to figure out where the caching was happening and how to disable it, and I don't know. All I wanted to do was update the link and submit a pull request! I recommend that you all either change this behavior (i.e. updating the link to a dataset should "just work") or document it, since I couldn't find any information about this in the contributing.md or readme or anywhere else! Thanks! | {
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"The `fingerprint` parameter serves a slightly different purpose - we use it to inject a new fingerprint after transforming a `Dataset` (computed from the previous fingerprint + transform + transform args), e.g., to be able to compute the cache file for a transform. There is no concept of `fingerprint` before a `Da... | 2023-08-29T22:43:13Z | 2023-09-30T16:56:51Z | null | NONE | null | null | null | ### Feature request
When using `Dataset.from_generator`, the generator is hashed when building the fingerprint. Similar to `.map`, it would be interesting to let the user bypass this hashing by accepting a `fingerprint` argument to `.from_generator`.
### Motivation
Using the `.from_generator` constructor with a non-picklable generator fails. By accepting a `fingerprint` argument to `.from_generator`, the user would have the opportunity to manually fingerprint the dataset and thus bypass the crash.
### Your contribution
If validated, I can try to submit a PR for this. | {
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} | Update dataset with latest verion data files.
Fix #3462.
Close bigscience-workshop/data_tooling#107 | {
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https://api.github.com/repos/huggingface/datasets/issues/3399 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3399/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3399/comments | https://api.github.com/repos/huggingface/datasets/issues/3399/events | https://github.com/huggingface/datasets/issues/3399 | 1,073,593,861 | I_kwDODunzps4__b4F | 3,399 | Add Wikisource dataset | {
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"See notebook by @geohci: https://public.paws.wmcloud.org/User:Isaac_(WMF)/HuggingFace%20Wikisource%20Processing.ipynb"
] | 2021-12-07T17:21:31Z | 2021-12-10T17:26:26Z | null | MEMBER | null | null | null | ## Adding a Dataset
- **Name:** *wikisource*
- **Description:** *short description of the dataset (or link to social media or blog post)*
- **Paper:** *link to the dataset paper if available*
- **Data:** *link to the Github repository or current dataset location*
- **Motivation:** Additional high quality textual data, besides Wikipedia.
Add loading script as "canonical" dataset (as it is the case for ""wikipedia").
Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
CC: @geohci, @yjernite | {
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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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https://api.github.com/repos/huggingface/datasets/issues/4669 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4669/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4669/comments | https://api.github.com/repos/huggingface/datasets/issues/4669/events | https://github.com/huggingface/datasets/issues/4669 | 1,299,848,003 | I_kwDODunzps5NehtD | 4,669 | loading oscar-corpus/OSCAR-2201 raises an error | {
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"I had to use the appropriate token for use_auth_token. Thank you."
] | 2022-07-10T07:09:30Z | 2022-07-11T09:27:49Z | 2022-07-11T09:27:49Z | NONE | null | null | null | ## Describe the bug
load_dataset('oscar-2201', 'af')
raises an error:
Traceback (most recent call last):
File "/usr/lib/python3.8/code.py", line 90, in runcode
exec(code, self.locals)
File "<input>", line 1, in <module>
File "..python3.8/site-packages/datasets/load.py", line 1656, in load_dataset
builder_instance = load_dataset_builder(
File ".../lib/python3.8/site-packages/datasets/load.py", line 1439, in load_dataset_builder
dataset_module = dataset_module_factory(
File ".../lib/python3.8/site-packages/datasets/load.py", line 1189, in dataset_module_factory
raise FileNotFoundError(
FileNotFoundError: Couldn't find a dataset script at .../oscar-2201/oscar-2201.py or any data file in the same directory. Couldn't find 'oscar-2201' on the Hugging Face Hub either: FileNotFoundError: Couldn't find file at https://raw.githubusercontent.com/huggingface/datasets/master/datasets/oscar-2201/oscar-2201.py
I've tried other permutations such as :
oscar_22 = load_dataset('oscar-2201', 'af',use_auth_token=True)
oscar_22 = load_dataset('oscar-corpus/OSCAR-2201', 'af',use_auth_token=True)
oscar_22 = load_dataset('oscar-2201', 'af')
oscar_22 = load_dataset('oscar-corpus/OSCAR-2201')
with the same unfortunate result.
## Steps to reproduce the bug
oscar_22 = load_dataset('oscar-2201', 'af',use_auth_token=True)
oscar_22 = load_dataset('oscar-corpus/OSCAR-2201', 'af',use_auth_token=True)
oscar_22 = load_dataset('oscar-2201', 'af')
oscar_22 = load_dataset('oscar-corpus/OSCAR-2201')
# Sample code to reproduce the bug
```
## Expected results
loaded data
## Actual results
Traceback (most recent call last):
File "/usr/lib/python3.8/code.py", line 90, in runcode
exec(code, self.locals)
File "<input>", line 1, in <module>
File "..python3.8/site-packages/datasets/load.py", line 1656, in load_dataset
builder_instance = load_dataset_builder(
File ".../lib/python3.8/site-packages/datasets/load.py", line 1439, in load_dataset_builder
dataset_module = dataset_module_factory(
File ".../lib/python3.8/site-packages/datasets/load.py", line 1189, in dataset_module_factory
raise FileNotFoundError(
FileNotFoundError: Couldn't find a dataset script at .../oscar-2201/oscar-2201.py or any data file in the same directory. Couldn't find 'oscar-2201' on the Hugging Face Hub either: FileNotFoundError: Couldn't find file at https://raw.githubusercontent.com/huggingface/datasets/master/datasets/oscar-2201/oscar-2201.py
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 2.3.2
- Platform: Linux-5.13.0-37-generic-x86_64-with-glibc2.29
- Python version: 3.8.10
- PyArrow version: 8.0.0
- Pandas version: 1.4.3
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https://api.github.com/repos/huggingface/datasets/issues/1880 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1880/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1880/comments | https://api.github.com/repos/huggingface/datasets/issues/1880/events | https://github.com/huggingface/datasets/pull/1880 | 808,563,439 | MDExOlB1bGxSZXF1ZXN0NTczNTgzNjg0 | 1,880 | Update multi_woz_v22 checksums | {
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} | As noticed in #1876 the checksums of this dataset are outdated.
I updated them in this PR | {
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https://api.github.com/repos/huggingface/datasets/issues/2595 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2595/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2595/comments | https://api.github.com/repos/huggingface/datasets/issues/2595/events | https://github.com/huggingface/datasets/issues/2595 | 937,483,120 | MDU6SXNzdWU5Mzc0ODMxMjA= | 2,595 | ModuleNotFoundError: No module named 'datasets.tasks' while importing common voice datasets | {
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"Hi @profsatwinder.\r\n\r\nIt looks like you are using an old version of `datasets`. Please update it with `pip install -U datasets` and indicate if the problem persists.",
"@albertvillanova Thanks for the information. I updated it to 1.9.0 and the issue is resolved. Thanks again. "
] | 2021-07-06T03:20:55Z | 2021-07-06T05:59:49Z | 2021-07-06T05:59:49Z | NONE | null | null | null | Error traceback:
---------------------------------------------------------------------------
ModuleNotFoundError Traceback (most recent call last)
<ipython-input-8-a7b592d3bca0> in <module>()
1 from datasets import load_dataset, load_metric
2
----> 3 common_voice_train = load_dataset("common_voice", "pa-IN", split="train+validation")
4 common_voice_test = load_dataset("common_voice", "pa-IN", split="test")
9 frames
/root/.cache/huggingface/modules/datasets_modules/datasets/common_voice/078d412587e9efeb0ae2e574da99c31e18844c496008d53dc5c60f4159ed639b/common_voice.py in <module>()
19
20 import datasets
---> 21 from datasets.tasks import AutomaticSpeechRecognition
22
23
ModuleNotFoundError: No module named 'datasets.tasks' | {
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https://api.github.com/repos/huggingface/datasets/issues/1329 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1329/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1329/comments | https://api.github.com/repos/huggingface/datasets/issues/1329/events | https://github.com/huggingface/datasets/pull/1329 | 759,654,174 | MDExOlB1bGxSZXF1ZXN0NTM0NjIxNzg0 | 1,329 | Add yoruba ner corpus | {
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https://api.github.com/repos/huggingface/datasets/issues/3855 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3855/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3855/comments | https://api.github.com/repos/huggingface/datasets/issues/3855/events | https://github.com/huggingface/datasets/issues/3855 | 1,162,448,589 | I_kwDODunzps5FSY7N | 3,855 | Bad error message when loading private dataset | {
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"We raise the error “ FileNotFoundError: can’t find the dataset” mainly to follow best practice in security (otherwise users could be able to guess what private repositories users/orgs may have)\r\n\r\nWe can indeed reformulate this and add the \"If this is a private repository,...\" part !",
"Resolved via https:... | 2022-03-08T09:55:17Z | 2022-07-11T15:06:40Z | 2022-07-11T15:06:40Z | MEMBER | null | null | null | ## Describe the bug
A pretty common behavior of an interaction between the Hub and datasets is the following.
An organization adds a dataset in private mode and wants to load it afterward.
```python
from transformers import load_dataset
ds = load_dataset("NewT5/dummy_data", "dummy")
```
This command then fails with:
```bash
FileNotFoundError: Couldn't find a dataset script at /home/patrick/NewT5/dummy_data/dummy_data.py or any data file in the same directory. Couldn't find 'NewT5/dummy_data' on the Hugging Face Hub either: FileNotFoundError: Dataset 'NewT5/dummy_data' doesn't exist on the Hub
```
**even though** the user has access to the website `NewT5/dummy_data` since she/he is part of the org.
We need to improve the error message here similar to how @sgugger, @LysandreJik and @julien-c have done it for transformers IMO.
## Steps to reproduce the bug
E.g. execute the following code to see the different error messages between `transformes` and `datasets`.
1. Transformers
```python
from transformers import BertModel
BertModel.from_pretrained("NewT5/dummy_model")
```
The error message is clearer here - it gives:
```
OSError: patrickvonplaten/gpt2-xl is not a local folder and is not a valid model identifier listed on 'https://huggingface.co/models'
If this is a private repository, make sure to pass a token having permission to this repo with `use_auth_token` or log in with `huggingface-cli login` and pass `use_auth_token=True`.
```
Let's maybe do the same for datasets? The PR was introduced to `transformers` here:
https://github.com/huggingface/transformers/pull/15261
## Expected results
Better error message
## Actual results
Specify the actual results or traceback.
## Environment info
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- `datasets` version: 1.18.4.dev0
- Platform: Linux-5.15.15-76051515-generic-x86_64-with-glibc2.34
- Python version: 3.9.7
- PyArrow version: 6.0.1
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https://api.github.com/repos/huggingface/datasets/issues/1643 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1643/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1643/comments | https://api.github.com/repos/huggingface/datasets/issues/1643/events | https://github.com/huggingface/datasets/issues/1643 | 775,280,046 | MDU6SXNzdWU3NzUyODAwNDY= | 1,643 | Dataset social_bias_frames 404 | {
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"I see, master is already fixed in https://github.com/huggingface/datasets/commit/9e058f098a0919efd03a136b9b9c3dec5076f626"
] | 2020-12-28T08:35:34Z | 2020-12-28T08:38:07Z | 2020-12-28T08:38:07Z | NONE | null | null | null | ```
>>> from datasets import load_dataset
>>> dataset = load_dataset("social_bias_frames")
...
Downloading and preparing dataset social_bias_frames/default
...
~/.pyenv/versions/3.7.6/lib/python3.7/site-packages/datasets/utils/file_utils.py in get_from_cache(url, cache_dir, force_download, proxies, etag_timeout, resume_download, user_agent, local_files_only, use_etag)
484 )
485 elif response is not None and response.status_code == 404:
--> 486 raise FileNotFoundError("Couldn't find file at {}".format(url))
487 raise ConnectionError("Couldn't reach {}".format(url))
488
FileNotFoundError: Couldn't find file at https://homes.cs.washington.edu/~msap/social-bias-frames/SocialBiasFrames_v2.tgz
```
[Here](https://homes.cs.washington.edu/~msap/social-bias-frames/) we find button `Download data` with the correct URL for the data: https://homes.cs.washington.edu/~msap/social-bias-frames/SBIC.v2.tgz | {
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https://api.github.com/repos/huggingface/datasets/issues/3715 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3715/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3715/comments | https://api.github.com/repos/huggingface/datasets/issues/3715/events | https://github.com/huggingface/datasets/pull/3715 | 1,136,107,879 | PR_kwDODunzps4yuKJj | 3,715 | Fix bugs in msr_sqa dataset | {
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"It shows below when I run test:\r\n\r\nFAILED tests/test_dataset_common.py::LocalDatasetTest::test_load_dataset_all_configs_msr_sqa - ValueError: Unknown split \"validation\". Should be one of ['train', 'test'].\r\n\r\nIt make no sense for me😂. \r\n",
"@albertvillanova Does this PR has some additional fixes com... | 2022-02-13T16:37:30Z | 2022-10-03T09:10:02Z | 2022-10-03T09:08:06Z | CONTRIBUTOR | null | 0 | {
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} | The last version has many problems,
1) Errors in table load-in. Split by a single comma instead of using pandas is wrong.
2) id reduplicated in _generate_examples function.
3) Missing information of history questions which make it hard to use.
I fix it refer to https://github.com/HKUNLP/UnifiedSKG. And we test it to perform normally. | {
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https://api.github.com/repos/huggingface/datasets/issues/3144 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3144/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3144/comments | https://api.github.com/repos/huggingface/datasets/issues/3144/events | https://github.com/huggingface/datasets/issues/3144 | 1,033,573,760 | I_kwDODunzps49mxWA | 3,144 | Infer the features if missing | {
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"Done by @lhoestq here: https://github.com/huggingface/datasets/pull/4500 (https://github.com/huggingface/datasets/pull/4500/files#diff-02930e1d966f4b41f9ddf15d961f16f5466d9bee583138657018c7329f71aa43R1255 in particular)\r\n"
] | 2021-10-22T13:17:33Z | 2022-09-08T08:23:10Z | 2022-09-08T08:23:10Z | CONTRIBUTOR | null | null | null | **Is your feature request related to a problem? Please describe.**
Some datasets, in particular community datasets, have no info file, thus no features.
**Describe the solution you'd like**
If a dataset has no features, the first loaded data (5-10 rows) could be used to infer the type.
Related: `datasets` would provide a way to load the data, and get the rows AND the features as the result.
**Describe alternatives you've considered**
The HF hub could also provide some UI to help the dataset maintainers to explicit the types of their rows, or automatically infer them as an initial proposal. | {
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https://api.github.com/repos/huggingface/datasets/issues/4985 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4985/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4985/comments | https://api.github.com/repos/huggingface/datasets/issues/4985/events | https://github.com/huggingface/datasets/pull/4985 | 1,375,807,768 | PR_kwDODunzps4_F6kU | 4,985 | Prefer split patterns from directories over split patterns from filenames | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"Can we merge this one since the issue this PR fixes was reported for the second time? I also think we don't need a test for this simple change.",
"@mariosasko sure! could you please approve it? ",
"Hi there @polinaeterna @mariosa... | 2022-09-16T11:20:40Z | 2022-11-02T11:54:28Z | 2022-09-29T08:07:49Z | CONTRIBUTOR | null | 0 | {
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} | related to https://github.com/huggingface/datasets/issues/4895
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https://api.github.com/repos/huggingface/datasets/issues/5174 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5174/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5174/comments | https://api.github.com/repos/huggingface/datasets/issues/5174/events | https://github.com/huggingface/datasets/pull/5174 | 1,427,216,416 | PR_kwDODunzps5Bv3rh | 5,174 | Preserve None in list type cast in PyArrow 10 | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-10-28T12:48:30Z | 2022-10-28T13:15:33Z | 2022-10-28T13:13:18Z | CONTRIBUTOR | null | 0 | {
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} | The `ListArray` type in PyArrow 10.0.0 supports the `mask` parameter, which allows us to preserve Nones in nested lists in `cast` instead of replacing them with empty lists.
Fix https://github.com/huggingface/datasets/issues/3676 | {
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https://api.github.com/repos/huggingface/datasets/issues/1375 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1375/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1375/comments | https://api.github.com/repos/huggingface/datasets/issues/1375/events | https://github.com/huggingface/datasets/pull/1375 | 760,294,931 | MDExOlB1bGxSZXF1ZXN0NTM1MTUwOTk2 | 1,375 | Add OPUS EMEA Dataset | {
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https://api.github.com/repos/huggingface/datasets/issues/6073 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6073/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6073/comments | https://api.github.com/repos/huggingface/datasets/issues/6073/events | https://github.com/huggingface/datasets/issues/6073 | 1,822,167,804 | I_kwDODunzps5snBL8 | 6,073 | version2.3.2 load_dataset()data_files can't include .xxxx in path | {
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"Version 2.3.2 is over one year old, so please use the latest release (2.14.0) to get the expected behavior. Version 2.3.2 does not contain some fixes we made to fix resolving hidden files/directories (starting with a dot)."
] | 2023-07-26T11:09:31Z | 2023-08-29T15:53:59Z | 2023-08-29T15:53:59Z | NONE | null | null | null | ### Describe the bug
First, I cd workdir.
Then, I just use load_dataset("json", data_file={"train":"/a/b/c/.d/train/train.json", "test":"/a/b/c/.d/train/test.json"})
that couldn't work and
<FileNotFoundError: Unable to find
'/a/b/c/.d/train/train.jsonl' at
/a/b/c/.d/>
And I debug, it is fine in version2.1.2
So there maybe a bug in path join.
Here is the whole bug report:
/x/datasets/loa │
│ d.py:1656 in load_dataset │
│ │
│ 1653 │ ignore_verifications = ignore_verifications or save_infos │
│ 1654 │ │
│ 1655 │ # Create a dataset builder │
│ ❱ 1656 │ builder_instance = load_dataset_builder( │
│ 1657 │ │ path=path, │
│ 1658 │ │ name=name, │
│ 1659 │ │ data_dir=data_dir, │
│ │
│ x/datasets/loa │
│ d.py:1439 in load_dataset_builder │
│ │
│ 1436 │ if use_auth_token is not None: │
│ 1437 │ │ download_config = download_config.copy() if download_config e │
│ 1438 │ │ download_config.use_auth_token = use_auth_token │
│ ❱ 1439 │ dataset_module = dataset_module_factory( │
│ 1440 │ │ path, │
│ 1441 │ │ revision=revision, │
│ 1442 │ │ download_config=download_config, │
│ │
│ x/datasets/loa │
│ d.py:1097 in dataset_module_factory │
│ │
│ 1094 │ │
│ 1095 │ # Try packaged │
│ 1096 │ if path in _PACKAGED_DATASETS_MODULES: │
│ ❱ 1097 │ │ return PackagedDatasetModuleFactory( │
│ 1098 │ │ │ path, │
│ 1099 │ │ │ data_dir=data_dir, │
│ 1100 │ │ │ data_files=data_files, │
│ │
│x/datasets/loa │
│ d.py:743 in get_module │
│ │
│ 740 │ │ │ if self.data_dir is not None │
│ 741 │ │ │ else get_patterns_locally(str(Path().resolve())) │
│ 742 │ │ ) │
│ ❱ 743 │ │ data_files = DataFilesDict.from_local_or_remote( │
│ 744 │ │ │ patterns, │
│ 745 │ │ │ use_auth_token=self.download_config.use_auth_token, │
│ 746 │ │ │ base_path=str(Path(self.data_dir).resolve()) if self.data │
│ │
│ x/datasets/dat │
│ a_files.py:590 in from_local_or_remote │
│ │
│ 587 │ │ out = cls() │
│ 588 │ │ for key, patterns_for_key in patterns.items(): │
│ 589 │ │ │ out[key] = ( │
│ ❱ 590 │ │ │ │ DataFilesList.from_local_or_remote( │
│ 591 │ │ │ │ │ patterns_for_key, │
│ 592 │ │ │ │ │ base_path=base_path, │
│ 593 │ │ │ │ │ allowed_extensions=allowed_extensions, │
│ │
│ /x/datasets/dat │
│ a_files.py:558 in from_local_or_remote │
│ │
│ 555 │ │ use_auth_token: Optional[Union[bool, str]] = None, │
│ 556 │ ) -> "DataFilesList": │
│ 557 │ │ base_path = base_path if base_path is not None else str(Path() │
│ ❱ 558 │ │ data_files = resolve_patterns_locally_or_by_urls(base_path, pa │
│ 559 │ │ origin_metadata = _get_origin_metadata_locally_or_by_urls(data │
│ 560 │ │ return cls(data_files, origin_metadata) │
│ 561 │
│ │
│ /x/datasets/dat │
│ a_files.py:195 in resolve_patterns_locally_or_by_urls │
│ │
│ 192 │ │ if is_remote_url(pattern): │
│ 193 │ │ │ data_files.append(Url(pattern)) │
│ 194 │ │ else: │
│ ❱ 195 │ │ │ for path in _resolve_single_pattern_locally(base_path, pat │
│ 196 │ │ │ │ data_files.append(path) │
│ 197 │ │
│ 198 │ if not data_files: │
│ │
│ /x/datasets/dat │
│ a_files.py:145 in _resolve_single_pattern_locally │
│ │
│ 142 │ │ error_msg = f"Unable to find '{pattern}' at {Path(base_path).r │
│ 143 │ │ if allowed_extensions is not None: │
│ 144 │ │ │ error_msg += f" with any supported extension {list(allowed │
│ ❱ 145 │ │ raise FileNotFoundError(error_msg) │
│ 146 │ return sorted(out) │
│ 147
### Steps to reproduce the bug
1. Version=2.3.2
2. In shell, cd workdir.(cd /a/b/c/.d/)
3. load_dataset("json", data_file={"train":"/a/b/c/.d/train/train.json", "test":"/a/b/c/.d/train/test.json"})
### Expected behavior
fix it please~
### Environment info
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https://api.github.com/repos/huggingface/datasets/issues/1915 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1915/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1915/comments | https://api.github.com/repos/huggingface/datasets/issues/1915/events | https://github.com/huggingface/datasets/issues/1915 | 812,229,654 | MDU6SXNzdWU4MTIyMjk2NTQ= | 1,915 | Unable to download `wiki_dpr` | {
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"gists... | null | [
"Thanks for reporting ! This is a bug. For now feel free to set `ignore_verifications=False` in `load_dataset`.\r\nI'm working on a fix",
"I just merged a fix :)\r\n\r\nWe'll do a patch release soon. In the meantime feel free to try it from the master branch\r\nThanks again for reporting !",
"Closing since this... | 2021-02-19T18:11:32Z | 2021-03-03T17:40:48Z | 2021-03-03T17:40:48Z | NONE | null | null | null | I am trying to download the `wiki_dpr` dataset. Specifically, I want to download `psgs_w100.multiset.no_index` with no embeddings/no index. In order to do so, I ran:
`curr_dataset = load_dataset("wiki_dpr", embeddings_name="multiset", index_name="no_index")`
However, I got the following error:
`datasets.utils.info_utils.UnexpectedDownloadedFile: {'embeddings_index'}`
I tried adding in flags `with_embeddings=False` and `with_index=False`:
`curr_dataset = load_dataset("wiki_dpr", with_embeddings=False, with_index=False, embeddings_name="multiset", index_name="no_index")`
But I got the following error:
`raise ExpectedMoreDownloadedFiles(str(set(expected_checksums) - set(recorded_checksums)))
datasets.utils.info_utils.ExpectedMoreDownloadedFiles: {‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_5’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_15’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_30’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_36’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_18’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_41’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_13’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_48’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_10’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_23’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_14’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_34’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_43’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_40’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_47’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_3’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_24’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_7’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_33’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_46’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_42’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_27’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_29’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_26’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_22’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_4’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_20’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_39’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_6’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_16’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_8’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_35’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_49’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_17’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_25’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_0’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_38’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_12’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_44’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_1’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_32’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_19’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_31’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_37’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_9’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_11’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_21’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_28’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_45’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_2’}`
Is there anything else I need to set to download the dataset?
**UPDATE**: just running `curr_dataset = load_dataset("wiki_dpr", with_embeddings=False, with_index=False)` gives me the same error.
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https://api.github.com/repos/huggingface/datasets/issues/5115 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5115/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5115/comments | https://api.github.com/repos/huggingface/datasets/issues/5115/events | https://github.com/huggingface/datasets/pull/5115 | 1,409,250,020 | PR_kwDODunzps5Az9Pm | 5,115 | Fix iter_batches | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"I also ran the code in https://github.com/huggingface/datasets/issues/5111 and it works fine now :)",
"This is ready for review :)"
] | 2022-10-14T12:06:14Z | 2022-10-14T15:02:15Z | 2022-10-14T14:59:58Z | MEMBER | null | 0 | {
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} | The `pa.Table.to_reader()` method available in `pyarrow>=8.0.0` may return chunks of size < `max_chunksize`, therefore `iter_batches` can return batches smaller than the `batch_size` specified by the user
Therefore batched `map` couldn't always use batches of the right size, e.g. this fails because it runs only on one batch of one element:
```python
from datasets import Dataset, concatenate_datasets
ds = concatenate_datasets([Dataset.from_dict({"a": [i]}) for i in range(10)])
ds2 = ds.map(lambda _: {}, batched=True)
assert list(ds2) == list(ds)
```
This was introduced in https://github.com/huggingface/datasets/pull/5030
Close https://github.com/huggingface/datasets/issues/5111
This will require a patch release along with https://github.com/huggingface/datasets/pull/5113
TODO:
- [x] fix tests
- [x] add more tests | {
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https://api.github.com/repos/huggingface/datasets/issues/1864 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1864/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1864/comments | https://api.github.com/repos/huggingface/datasets/issues/1864/events | https://github.com/huggingface/datasets/issues/1864 | 806,172,843 | MDU6SXNzdWU4MDYxNzI4NDM= | 1,864 | Add Winogender Schemas | {
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"Nevermind, this one is already available on the hub under the name `'wino_bias'`: https://huggingface.co/datasets/wino_bias"
] | 2021-02-11T08:18:38Z | 2021-02-11T08:19:51Z | 2021-02-11T08:19:51Z | CONTRIBUTOR | null | null | null | ## Adding a Dataset
- **Name:** Winogender Schemas
- **Description:** Winogender Schemas (inspired by Winograd Schemas) are minimal pairs of sentences that differ only by the gender of one pronoun in the sentence, designed to test for the presence of gender bias in automated coreference resolution systems.
- **Paper:** https://arxiv.org/abs/1804.09301
- **Data:** https://github.com/rudinger/winogender-schemas (see data directory)
- **Motivation:** Testing gender bias in automated coreference resolution systems, improve coreference resolution in general.
Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
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https://api.github.com/repos/huggingface/datasets/issues/3589 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3589/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3589/comments | https://api.github.com/repos/huggingface/datasets/issues/3589/events | https://github.com/huggingface/datasets/pull/3589 | 1,106,766,114 | PR_kwDODunzps4xMhGp | 3,589 | Pin torchmetrics to fix the COMET test | {
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} | Torchmetrics 0.7.0 got released and has issues with `transformers` (see https://github.com/PyTorchLightning/metrics/issues/770)
I'm pinning it to 0.6.0 in the CI, since 0.7.0 makes the COMET metric test fail. COMET requires torchmetrics==0.6.0 anyway. | {
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"Hi @e-tornike, thanks a lot for adding this interesting dataset.\r\n\r\nRecently at Hugging Face, we have decided to give priority to adding datasets directly on the Hub. Would you mind to transfer your loading script to the Hub? You could create a dedicated org namespace, so that your dataset would be accessible ... | 2022-06-14T12:09:00Z | 2022-06-20T08:48:26Z | 2022-06-20T08:37:27Z | NONE | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/2535 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2535/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2535/comments | https://api.github.com/repos/huggingface/datasets/issues/2535/events | https://github.com/huggingface/datasets/pull/2535 | 927,334,349 | MDExOlB1bGxSZXF1ZXN0Njc1NTA3MTAw | 2,535 | Improve Features docs | {
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} | - Fix rendering and cross-references in Features docs
- Add docstrings to Features methods | {
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https://api.github.com/repos/huggingface/datasets/issues/2233 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2233/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2233/comments | https://api.github.com/repos/huggingface/datasets/issues/2233/events | https://github.com/huggingface/datasets/pull/2233 | 860,097,084 | MDExOlB1bGxSZXF1ZXN0NjE3MDYwMTkw | 2,233 | Fix `xnli` dataset tuple key | {
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The `xnli` dataset yields a tuple key in case of `ar` which is inconsistant with the acceptable key types (str/int).
The key was thus ported to `str` keeping the original information intact. | {
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https://api.github.com/repos/huggingface/datasets/issues/5608 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5608/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5608/comments | https://api.github.com/repos/huggingface/datasets/issues/5608/events | https://github.com/huggingface/datasets/issues/5608 | 1,609,996,563 | I_kwDODunzps5f9pkT | 5,608 | audiofolder only creates dataset of 13 rows (files) when the data folder it's reading from has 20,000 mp3 files. | {
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"Hi!\r\n\r\n> naming convention of mp3 files\r\n\r\nYes, this could be the problem. MP3 files should end with `.mp3`/`.MP3` to be recognized as audio files.\r\n\r\nIf the file names are not the culprit, can you paste the audio folder's directory structure to help us reproduce the error (e.g., by running the `tree ... | 2023-03-05T00:14:45Z | 2023-03-12T00:02:57Z | 2023-03-12T00:02:57Z | NONE | null | null | null | ### Describe the bug
x = load_dataset("audiofolder", data_dir="x")
When running this, x is a dataset of 13 rows (files) when it should be 20,000 rows (files) as the data_dir "x" has 20,000 mp3 files. Does anyone know what could possibly cause this (naming convention of mp3 files, etc.)
### Steps to reproduce the bug
x = load_dataset("audiofolder", data_dir="x")
### Expected behavior
x = load_dataset("audiofolder", data_dir="x") should create a dataset of 20,000 rows (files).
### Environment info
- `datasets` version: 2.9.0
- Platform: Linux-3.10.0-1160.80.1.el7.x86_64-x86_64-with-glibc2.17
- Python version: 3.9.16
- PyArrow version: 11.0.0
- Pandas version: 1.5.3 | {
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"_The documentation is not available anymore as the PR was closed or merged._"
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"Hi, it seems I am somewhat stuck here. The failed test `ci/circleci: run_dataset_script_tests_pyarrow_1_WIN` seems to be caused by some broken connection (`ConnectionResetError: [WinError 10054] An existing connection was forcibly closed by the remote host`). Any help on this is appreciated. \r\n\r\nEdit: Seems to... | 2021-02-23T08:11:57Z | 2021-03-01T10:01:03Z | 2021-03-01T10:01:03Z | CONTRIBUTOR | null | 0 | {
"diff_url": "https://github.com/huggingface/datasets/pull/1931.diff",
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} | Add a multilingual (machine translated and automatically generated) version of the LAMA benchmark. For details see the paper https://arxiv.org/pdf/2102.00894.pdf | {
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