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https://api.github.com/repos/huggingface/datasets/issues/3800 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3800/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3800/comments | https://api.github.com/repos/huggingface/datasets/issues/3800/events | https://github.com/huggingface/datasets/pull/3800 | 1,155,620,761 | PR_kwDODunzps4zvkjA | 3,800 | Added computer vision tasks | {
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https://api.github.com/repos/huggingface/datasets/issues/3799 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3799/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3799/comments | https://api.github.com/repos/huggingface/datasets/issues/3799/events | https://github.com/huggingface/datasets/pull/3799 | 1,155,356,102 | PR_kwDODunzps4zus9R | 3,799 | Xtreme-S Metrics | {
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- [x] MLS
- [x] Covost2
- [x] Minds-14
- [x] Voxpopuli
- [x] FLoRes (need data)
**Metrics**: Done | {
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https://api.github.com/repos/huggingface/datasets/issues/3798 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3798/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3798/comments | https://api.github.com/repos/huggingface/datasets/issues/3798/events | https://github.com/huggingface/datasets/pull/3798 | 1,154,411,066 | PR_kwDODunzps4zrl5Y | 3,798 | Fix error message in CSV loader for newer Pandas versions | {
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} | [] | closed | false | null | [] | null | [] | 2022-02-28T18:24:10 | 2022-02-28T18:51:39 | 2022-02-28T18:51:38 | CONTRIBUTOR | null | Fix the error message in the CSV loader for `Pandas >= 1.4`. To fix this, I directly print the current file name in the for-loop. An alternative would be to use a check similar to this:
```python
csv_file_reader.handle.handle if datasets.config.PANDAS_VERSION >= version.parse("1.4") else csv_file_reader.f
```
CC: @SBrandeis | {
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} | [] | closed | false | null | [] | null | [] | 2022-02-28T17:53:18 | 2023-03-09T22:08:58 | 2022-03-01T12:58:57 | CONTRIBUTOR | null | Description tags for webis-tldr-17 added. | {
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"same issue. downgrade it to a lower version.",
"Thanks for reporting, I'll take a look tomorrow :)"
] | 2022-02-27T13:57:40 | 2022-03-21T14:36:12 | 2022-03-21T14:36:12 | NONE | null | ## Describe the bug
after downloading the natural_questions dataset, can not flatten the dataset considering there are `long answer` and `short answer` in `annotations`.
## Steps to reproduce the bug
```python
from datasets import load_dataset
dataset = load_dataset('natural_questions',cache_dir = 'data/dataset_cache_dir')
dataset['train'].flatten()
```
## Expected results
a dataset with `long_answer` as features
## Actual results
Traceback (most recent call last):
File "temp.py", line 5, in <module>
dataset['train'].flatten()
File "/Users/hannibal046/anaconda3/lib/python3.8/site-packages/datasets/fingerprint.py", line 413, in wrapper
out = func(self, *args, **kwargs)
File "/Users/hannibal046/anaconda3/lib/python3.8/site-packages/datasets/arrow_dataset.py", line 1296, in flatten
dataset._data = update_metadata_with_features(dataset._data, dataset.features)
File "/Users/hannibal046/anaconda3/lib/python3.8/site-packages/datasets/arrow_dataset.py", line 536, in update_metadata_with_features
features = Features({col_name: features[col_name] for col_name in table.column_names})
File "/Users/hannibal046/anaconda3/lib/python3.8/site-packages/datasets/arrow_dataset.py", line 536, in <dictcomp>
features = Features({col_name: features[col_name] for col_name in table.column_names})
KeyError: 'annotations.long_answer'
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.8.13
- Platform: MBP
- Python version: 3.8
- PyArrow version: 6.0.1
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In this PR I implement the metric in a simple way with the help of numpy only.
Similar to the [MAUVE implementation](https://github.com/huggingface/datasets/blob/master/metrics/mauve/mauve.py), we can make this metric accept texts as input and encode them with a featurize model, if that is desirable. | {
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https://api.github.com/repos/huggingface/datasets/issues/3793 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3793/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3793/comments | https://api.github.com/repos/huggingface/datasets/issues/3793/events | https://github.com/huggingface/datasets/pull/3793 | 1,150,974,950 | PR_kwDODunzps4zfdL0 | 3,793 | Docs new UI actions no self hosted | {
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"Same issue with `dataset = load_dataset(\"dbpedia_14\")`\r\n```\r\nNonMatchingChecksumError: Checksums didn't match for dataset source files:\r\n['https://drive.google.com/uc?export=download&id=0Bz8a_Dbh9QhbQ2Vic1kxMmZZQ1k']",
"I think this is a side-effect of #3787. The checksums won't match because the URLs ha... | 2022-02-25T19:55:09 | 2022-10-12T13:33:26 | 2022-02-28T08:44:18 | NONE | null | ## Dataset viewer issue for 'wiki_lingua*'
**Link:** *link to the dataset viewer page*
`data = datasets.load_dataset("wiki_lingua", name=language, split="train[:2000]")
`
*short description of the issue*
```
[NonMatchingChecksumError: Checksums didn't match for dataset source files:
['https://drive.google.com/uc?export=download&id=11wMGqNVSwwk6zUnDaJEgm3qT71kAHeff']]()
```
Am I the one who added this dataset ? No
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} | [] | closed | false | null | [] | null | [] | 2022-02-25T16:38:47 | 2022-03-01T15:55:42 | 2022-03-01T15:55:41 | MEMBER | null | I added the three scripts:
- build_dev_documentation.yml
- build_documentation.yml
- delete_dev_documentation.yml
I got them from `transformers` and did a few changes:
- I removed the `transformers`-specific dependencies
- I changed all the paths to be "datasets" instead of "transformers"
- I passed the `--library_name datasets` arg to the `doc-builder build` command (according to https://github.com/huggingface/doc-builder/pull/94/files#diff-bcc33cf7c223511e498776684a9a433810b527a0a38f483b1487e8a42b6575d3R26)
cc @LysandreJik @mishig25 | {
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} | [] | closed | false | null | [] | null | [] | 2022-02-25T15:34:37 | 2022-03-04T08:24:24 | 2022-03-04T08:24:23 | MEMBER | null | This PR adds the URL field, so that we conform to proper attribution, required by their license: provide credit to the authors by including a hyperlink (where possible) or URL to the page or pages you are re-using.
About the conversion from title to URL, I found that apart from replacing blanks with underscores, some other special character must also be percent-encoded (e.g. `"` to `%22`): https://meta.wikimedia.org/wiki/Help:URL
Therefore, I have finally used `urllib.parse.quote` function. This additionally percent-encodes non-ASCII characters, but Wikimedia docs say these are equivalent:
> For the other characters either the code or the character can be used in internal and external links, they are equivalent. The system does a conversion when needed.
> [[%C3%80_propos_de_M%C3%A9ta]]
> is rendered as [À_propos_de_Méta](https://meta.wikimedia.org/wiki/%C3%80_propos_de_M%C3%A9ta), almost like [À propos de Méta](https://meta.wikimedia.org/wiki/%C3%80_propos_de_M%C3%A9ta), which leads to this page on Meta with in the address bar the URL
> [http://meta.wikipedia.org/wiki/%C3%80_propos_de_M%C3%A9ta](https://meta.wikipedia.org/wiki/%C3%80_propos_de_M%C3%A9ta)
> while [http://meta.wikipedia.org/wiki/À_propos_de_Méta](https://meta.wikipedia.org/wiki/%C3%80_propos_de_M%C3%A9ta) leads to the same.
Fix #3398.
CC: @geohci | {
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Fix #3786, fix #3784. | {
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"Once the PR merged into master and until our next `datasets` library release, you can get this fix by installing our library from the GitHub master branch:\r\n```shell\r\npip install git+https://github.com/huggingface/datasets#egg=datasets\r\n```\r\nThen, if you had previously tried to load the data and got the ch... | 2022-02-25T09:32:23 | 2022-03-03T09:25:59 | 2022-02-25T11:56:35 | MEMBER | null | ## Describe the bug
Recently, some issues were reported with URLs from Google Drive, where we were downloading the Virus scan warning page instead of the data file itself.
See:
- #3758
- #3773
- #3784
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} | [] | closed | false | null | [] | null | [] | 2022-02-25T05:48:57 | 2022-03-03T16:43:47 | 2022-03-03T14:03:37 | NONE | null | This commit fixes the issue described in #3784. By adding an extra parameter to the end of Google Drive links, we are able to bypass the virus check and download the datasets.
So, if the original link looked like https://drive.google.com/uc?export=download&id=0BwmD_VLjROrfTHk4NFg2SndKcjQ
The new link now looks like https://drive.google.com/uc?export=download&id=0BwmD_VLjROrfTHk4NFg2SndKcjQ&confirm=t
Fixes #3784 | {
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"#self-assign",
"@AngadSethi thanks for reporting and thanks for your PR!",
"Glad to help @albertvillanova! Just fine-tuning the PR, will comment once I am able to get it up and running 😀",
"Fixed by:\r\n- #3787"
] | 2022-02-25T05:24:47 | 2022-03-03T14:05:17 | 2022-03-03T14:05:17 | NONE | null | ## Describe the bug
I am unable to download the CNN-Dailymail dataset. Upon closer investigation, I realised why this was happening:
- The dataset sits in Google Drive, and both the CNN and DM datasets are large.
- Google is unable to scan the folder for viruses, **so the link which would originally download the dataset, now downloads the source code of this web page:**
- **This leads to the following error**:
```python
NotADirectoryError: [Errno 20] Not a directory: '/root/.cache/huggingface/datasets/downloads/1bc05d24fa6dda2468e83a73cf6dc207226e01e3c48a507ea716dc0421da583b/cnn/stories'
```
## Steps to reproduce the bug
```python
import datasets
dataset = datasets.load_dataset("cnn_dailymail", "3.0.0", split="train")
```
## Expected results
That the dataset is downloaded and processed just like other datasets.
## Actual results
Hit with this error:
```python
NotADirectoryError: [Errno 20] Not a directory: '/root/.cache/huggingface/datasets/downloads/1bc05d24fa6dda2468e83a73cf6dc207226e01e3c48a507ea716dc0421da583b/cnn/stories'
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.18.3
- Platform: Linux-5.4.144+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.7.12
- PyArrow version: 6.0.1
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https://api.github.com/repos/huggingface/datasets/issues/3782 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3782/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3782/comments | https://api.github.com/repos/huggingface/datasets/issues/3782/events | https://github.com/huggingface/datasets/pull/3782 | 1,148,994,022 | PR_kwDODunzps4zY-Xb | 3,782 | Error of writing with different schema, due to nonpreservation of nullability | {
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} | [] | closed | false | null | [] | null | [] | 2022-02-24T08:23:07 | 2022-03-03T14:54:39 | 2022-03-03T14:54:39 | CONTRIBUTOR | null | ## 1. Case
```
dataset.map(
batched=True,
disable_nullable=True,
)
```
will get the following error at here https://github.com/huggingface/datasets/blob/c9967f55626931f8059dc416526c791444cdfdf7/src/datasets/arrow_writer.py#L516
`pyarrow.lib.ArrowInvalid: Tried to write record batch with different schema`
## 2. Debugging
### 2.1 tracing
During `_map_single`, the following are called
https://github.com/huggingface/datasets/blob/c9967f55626931f8059dc416526c791444cdfdf7/src/datasets/arrow_dataset.py#L2523
https://github.com/huggingface/datasets/blob/c9967f55626931f8059dc416526c791444cdfdf7/src/datasets/arrow_writer.py#L511
### 2.2. Observation
The problem is, even after `table_cast`, `pa_table.schema != self._schema`
`pa_table.schema` (before/after `table_cast`)
```
input_ids: list<item: int32>
child 0, item: int32
```
`self._schema`
```
input_ids: list<item: int32> not null
child 0, item: int32
```
### 2.3. Reason
https://github.com/huggingface/datasets/blob/c9967f55626931f8059dc416526c791444cdfdf7/src/datasets/table.py#L1121
Here we lose nullability stored in `schema` because it seems that `Features` is always nullable and don't store nullability.
https://github.com/huggingface/datasets/blob/c9967f55626931f8059dc416526c791444cdfdf7/src/datasets/table.py#L1103
So, casting to schema from such `Features` loses nullability, and eventually causes error of writing with different schema
## 3. Solution
1. Let `Features` stores nullability.
2. Directly cast table with original schema but not schema from converted `Features`. (this PR)
3. Don't `cast_table` when `write_table` | {
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} | [] | closed | false | null | [] | null | [] | 2022-02-23T21:29:16 | 2022-02-28T18:00:40 | 2022-02-28T11:21:14 | CONTRIBUTOR | null | The changes proposed are based on the "TL;DR: Mining Reddit to Learn Automatic Summarization" paper & https://zenodo.org/record/1043504#.YhaKHpbQC38
It is a Reddit dataset indeed, but the name given to the dataset by the authors is Webis-TLDR-17 (corpus), so perhaps it should be modified as well.
The task at which the dataset is aimed is abstractive summarization.
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"Hi @Darshan2104, thanks for reporting.\r\n\r\nPlease note that at Hugging Face we do not host the data of this dataset, but just a loading script pointing to the host of the data owners.\r\n\r\nApparently the data owners changed their data host server. After googling it, I found their new website at: https://lil.n... | 2022-02-23T10:15:50 | 2022-02-23T17:05:04 | 2022-02-23T13:26:40 | NONE | null | Hello,
I tried to download the **newsroom** dataset but it didn't work out for me. it said me to **download it manually**!
For manually, Link is also didn't work! It is sawing some ad or something!
If anybody has solved this issue please help me out or if somebody has this dataset please share your google drive link, it would be a great help!
Thanks
Darshan Tank | {
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Indeed this makes the documentation confusing and we don't want this distinction anymore in the future. Ideally users should share their datasets on the Hub directly.
### Changes
- the documentation about dataset loading mentions the datasets on the Hub (no difference between canonical and community, since they all have their own repository now)
- the documentation about adding a dataset doesn't explain the technical differences between canonical and community anymore, and only presents how to add a community dataset. There is still a small section at the bottom that mentions the datasets that are still on GitHub and redirects to the `ADD_NEW_DATASET.md` guide on GitHub about how to contribute a dataset to the `datasets` library
- the code source doesn't mention "canonical" anymore anywhere. There is still a `GitHubDatasetModuleFactory` class that is left, but I updated the docstring to say that it will be eventually removed in favor of the `HubDatasetModuleFactory` classes that already exist
Would love to have your feedbacks on this !
cc @julien-c @thomwolf @SBrandeis | {
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"Thanks for reporting, @anna-kay. We are fixing it.",
"@albertvillanova Thank you for the fast response! However I am still getting the same error:\r\n\r\nDownloading: 2.23kB [00:00, ?B/s]\r\nTraceback (most recent call last):\r\n File \"C:\\Users\\Anna\\PycharmProjects\\summarization\\main.py\", line 17, in <mo... | 2022-02-22T10:57:07 | 2022-02-25T19:27:49 | 2022-02-22T12:38:44 | CONTRIBUTOR | null | ## Describe the bug
A checksum occurs when downloading the reddit_tifu data (both long & short).
## Steps to reproduce the bug
reddit_tifu_dataset = load_dataset('reddit_tifu', 'long')
## Expected results
The expected result is for the dataset to be downloaded and cached locally.
## Actual results
File "/.../lib/python3.9/site-packages/datasets/utils/info_utils.py", line 40, in verify_checksums
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
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.18.3
- Platform: Linux-5.13.0-30-generic-x86_64-with-glibc2.31
- Python version: 3.9.7
- PyArrow version: 7.0.0
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"Thanks for reporting, @kolk.\r\n\r\nWe are fixing it. "
] | 2022-02-22T00:43:33 | 2022-02-22T08:12:39 | 2022-02-22T08:12:39 | NONE | null | ### Describe the bug
Failure to generate dataset msr_sqa because of duplicate keys.
### Steps to reproduce the bug
```
from datasets import load_dataset
load_dataset("msr_sqa")
```
### Expected results
The examples keys should be unique.
**Actual results**
```
>>> load_dataset("msr_sqa")
Downloading:
6.72k/? [00:00<00:00, 148kB/s]
Downloading:
2.93k/? [00:00<00:00, 53.8kB/s]
Using custom data configuration default
Downloading and preparing dataset msr_sqa/default (download: 4.57 MiB, generated: 26.25 MiB, post-processed: Unknown size, total: 30.83 MiB) to /root/.cache/huggingface/datasets/msr_sqa/default/0.0.0/70b2a497bd3cc8fc960a3557d2bad1eac5edde824505e15c9c8ebe4c260fd4d1...
Downloading: 100%
4.80M/4.80M [00:00<00:00, 7.49MB/s]
---------------------------------------------------------------------------
DuplicatedKeysError Traceback (most recent call last)
[/usr/local/lib/python3.7/dist-packages/datasets/builder.py](https://localhost:8080/#) in _prepare_split(self, split_generator)
1080 example = self.info.features.encode_example(record)
-> 1081 writer.write(example, key)
1082 finally:
8 frames
DuplicatedKeysError: FAILURE TO GENERATE DATASET !
Found duplicate Key: nt-639
Keys should be unique and deterministic in nature
During handling of the above exception, another exception occurred:
DuplicatedKeysError Traceback (most recent call last)
[/usr/local/lib/python3.7/dist-packages/datasets/arrow_writer.py](https://localhost:8080/#) in check_duplicate_keys(self)
449 for hash, key in self.hkey_record:
450 if hash in tmp_record:
--> 451 raise DuplicatedKeysError(key)
452 else:
453 tmp_record.add(hash)
DuplicatedKeysError: FAILURE TO GENERATE DATASET !
Found duplicate Key: nt-639
Keys should be unique and deterministic in nature
```
### Environment info
datasets version: 1.18.3
Platform: Google colab notebook
Python version: 3.7
PyArrow version: 6.0.1
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**Link:** *link to the dataset viewer page*
*short description of the issue*
Am I the one who added this dataset ? Yes-No
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"Hi @jvanz, thanks for reporting.\r\n\r\nPlease note that Wikimedia website does not longer host Wikipedia dumps for so old dates.\r\n\r\nFor a list of accessible dump dates of `pt` Wikipedia, please see: https://dumps.wikimedia.org/ptwiki/\r\n\r\nYou can load for example `20220220` `pt` Wikipedia:\r\n```python\r\n... | 2022-02-20T18:34:58 | 2022-02-21T12:06:12 | 2022-02-21T09:25:06 | NONE | null | ## Describe the bug
The dataset `20200501.pt` is broken.
The available datasets: https://dumps.wikimedia.org/ptwiki/
## Steps to reproduce the bug
```python
from datasets import load_dataset
dataset = load_dataset("wikipedia", "20200501.pt", beam_runner='DirectRunner')
```
## Expected results
I expect to download the dataset locally.
## Actual results
```
>>> from datasets import load_dataset
>>> dataset = load_dataset("wikipedia", "20200501.pt", beam_runner='DirectRunner')
Downloading and preparing dataset wikipedia/20200501.pt to /home/jvanz/.cache/huggingface/datasets/wikipedia/20200501.pt/1.0.0/009f923d9b6dd00c00c8cdc7f408f2b47f45dd4f5fb7982a21f9448f4afbe475...
/home/jvanz/anaconda3/envs/tf-gpu/lib/python3.9/site-packages/apache_beam/__init__.py:79: UserWarning: This version of Apache Beam has not been sufficiently tested on Python 3.9. You may encounter bugs or missing features.
warnings.warn(
0%| | 0/1 [00:00<?, ?it/s]
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/jvanz/anaconda3/envs/tf-gpu/lib/python3.9/site-packages/datasets/load.py", line 1702, in load_dataset
builder_instance.download_and_prepare(
File "/home/jvanz/anaconda3/envs/tf-gpu/lib/python3.9/site-packages/datasets/builder.py", line 594, in download_and_prepare
self._download_and_prepare(
File "/home/jvanz/anaconda3/envs/tf-gpu/lib/python3.9/site-packages/datasets/builder.py", line 1245, in _download_and_prepare
super()._download_and_prepare(
File "/home/jvanz/anaconda3/envs/tf-gpu/lib/python3.9/site-packages/datasets/builder.py", line 661, in _download_and_prepare
split_generators = self._split_generators(dl_manager, **split_generators_kwargs)
File "/home/jvanz/.cache/huggingface/modules/datasets_modules/datasets/wikipedia/009f923d9b6dd00c00c8cdc7f408f2b47f45dd4f5fb7982a21f9448f4afbe475/wikipedia.py", line 420, in _split_generators
downloaded_files = dl_manager.download_and_extract({"info": info_url})
File "/home/jvanz/anaconda3/envs/tf-gpu/lib/python3.9/site-packages/datasets/utils/download_manager.py", line 307, in download_and_extract
return self.extract(self.download(url_or_urls))
File "/home/jvanz/anaconda3/envs/tf-gpu/lib/python3.9/site-packages/datasets/utils/download_manager.py", line 195, in download
downloaded_path_or_paths = map_nested(
File "/home/jvanz/anaconda3/envs/tf-gpu/lib/python3.9/site-packages/datasets/utils/py_utils.py", line 260, in map_nested
mapped = [
File "/home/jvanz/anaconda3/envs/tf-gpu/lib/python3.9/site-packages/datasets/utils/py_utils.py", line 261, in <listcomp>
_single_map_nested((function, obj, types, None, True))
File "/home/jvanz/anaconda3/envs/tf-gpu/lib/python3.9/site-packages/datasets/utils/py_utils.py", line 196, in _single_map_nested
return function(data_struct)
File "/home/jvanz/anaconda3/envs/tf-gpu/lib/python3.9/site-packages/datasets/utils/download_manager.py", line 216, in _download
return cached_path(url_or_filename, download_config=download_config)
File "/home/jvanz/anaconda3/envs/tf-gpu/lib/python3.9/site-packages/datasets/utils/file_utils.py", line 298, in cached_path
output_path = get_from_cache(
File "/home/jvanz/anaconda3/envs/tf-gpu/lib/python3.9/site-packages/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://dumps.wikimedia.org/ptwiki/20200501/dumpstatus.json
```
## Environment info
```
- `datasets` version: 1.18.3
- Platform: Linux-5.3.18-150300.59.49-default-x86_64-with-glibc2.31
- Python version: 3.9.7
- PyArrow version: 6.0.1
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/3762 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3762/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3762/comments | https://api.github.com/repos/huggingface/datasets/issues/3762/events | https://github.com/huggingface/datasets/issues/3762 | 1,144,849,557 | I_kwDODunzps5EPQSV | 3,762 | `Dataset.class_encode` should support custom class names | {
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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... | 2022-02-19T21:21:45 | 2022-02-21T12:16:35 | 2022-02-21T12:16:35 | CONTRIBUTOR | 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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https://api.github.com/repos/huggingface/datasets/issues/3761 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3761/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3761/comments | https://api.github.com/repos/huggingface/datasets/issues/3761/events | https://github.com/huggingface/datasets/issues/3761 | 1,144,830,702 | I_kwDODunzps5EPLru | 3,761 | Know your data for HF hub | {
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"Hi @Muhtasham you should take a look at https://huggingface.co/blog/data-measurements-tool and accompanying demo app at https://huggingface.co/spaces/huggingface/data-measurements-tool\r\n\r\nWe would be interested in your feedback. cc @meg-huggingface @sashavor @yjernite "
] | 2022-02-19T19:48:47 | 2022-02-21T14:15:23 | 2022-02-21T14:15:23 | NONE | null | **Is your feature request related to a problem? Please describe.**
Would be great to see be able to understand datasets with the goal of improving data quality, and helping mitigate fairness and bias issues.
**Describe the solution you'd like**
Something like https://knowyourdata.withgoogle.com/ for HF hub | {
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https://api.github.com/repos/huggingface/datasets/issues/3760 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3760/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3760/comments | https://api.github.com/repos/huggingface/datasets/issues/3760/events | https://github.com/huggingface/datasets/issues/3760 | 1,144,804,558 | I_kwDODunzps5EPFTO | 3,760 | Unable to view the Gradio flagged call back dataset | {
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"Hi @kingabzpro.\r\n\r\nI think you need to create a loading script that creates the dataset from the CSV file and the image paths.\r\n\r\nAs example, you could have a look at the Food-101 dataset: https://huggingface.co/datasets/food101\r\n- Loading script: https://huggingface.co/datasets/food101/blob/main/food101... | 2022-02-19T17:45:08 | 2022-03-22T07:12:11 | 2022-03-22T07:12:11 | NONE | null | ## Dataset viewer issue for '*savtadepth-flags*'
**Link:** *[savtadepth-flags](https://huggingface.co/datasets/kingabzpro/savtadepth-flags)*
*with the Gradio 2.8.1 the dataset viers stopped working. I tried to add values manually but its not working. The dataset is also not showing the link with the app https://huggingface.co/spaces/kingabzpro/savtadepth.*
Am I the one who added this dataset ? Yes
| {
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https://api.github.com/repos/huggingface/datasets/issues/3759 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3759/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3759/comments | https://api.github.com/repos/huggingface/datasets/issues/3759/events | https://github.com/huggingface/datasets/pull/3759 | 1,143,400,770 | PR_kwDODunzps4zGhQu | 3,759 | Rename GenerateMode to DownloadMode | {
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} | [] | closed | false | null | [] | null | [] | 2022-02-18T16:53:53 | 2022-02-22T13:57:24 | 2022-02-22T12:22:52 | MEMBER | null | This PR:
- Renames `GenerateMode` to `DownloadMode`
- Implements `DeprecatedEnum`
- Deprecates `GenerateMode`
Close #769. | {
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https://api.github.com/repos/huggingface/datasets/issues/3758 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3758/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3758/comments | https://api.github.com/repos/huggingface/datasets/issues/3758/events | https://github.com/huggingface/datasets/issues/3758 | 1,143,366,393 | I_kwDODunzps5EJmL5 | 3,758 | head_qa file missing | {
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"We usually find issues with files hosted at Google Drive...\r\n\r\nIn this case we download the Google Drive Virus scan warning instead of the data file.",
"Fixed: https://huggingface.co/datasets/head_qa/viewer/en/train. Thanks\r\n\r\n<img width=\"1551\" alt=\"Capture d’écran 2022-02-28 à 15 29 04\" src=\"http... | 2022-02-18T16:32:43 | 2022-02-28T14:29:18 | 2022-02-21T14:39:19 | CONTRIBUTOR | null | ## Describe the bug
A file for the `head_qa` dataset is missing (https://drive.google.com/u/0/uc?export=download&id=1a_95N5zQQoUCq8IBNVZgziHbeM-QxG2t/HEAD_EN/train_HEAD_EN.json)
## Steps to reproduce the bug
```python
>>> from datasets import load_dataset
>>> load_dataset("head_qa", name="en")
```
## Expected results
The dataset should be loaded
## Actual results
```
Downloading and preparing dataset head_qa/en (download: 75.69 MiB, generated: 2.69 MiB, post-processed: Unknown size, total: 78.38 MiB) to /home/slesage/.cache/huggingface/datasets/head_qa/en/1.1.0/583ab408e8baf54aab378c93715fadc4d8aa51b393e27c3484a877e2ac0278e9...
Downloading data: 2.21kB [00:00, 2.05MB/s]
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/datasets/load.py", line 1729, in load_dataset
builder_instance.download_and_prepare(
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/datasets/builder.py", line 594, in download_and_prepare
self._download_and_prepare(
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/datasets/builder.py", line 665, in _download_and_prepare
verify_checksums(
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/datasets/utils/info_utils.py", line 40, in verify_checksums
raise NonMatchingChecksumError(error_msg + str(bad_urls))
datasets.utils.info_utils.NonMatchingChecksumError: Checksums didn't match for dataset source files:
['https://drive.google.com/u/0/uc?export=download&id=1a_95N5zQQoUCq8IBNVZgziHbeM-QxG2t']
```
## Environment info
- `datasets` version: 1.18.4.dev0
- Platform: Linux-5.11.0-1028-aws-x86_64-with-glibc2.31
- Python version: 3.9.6
- PyArrow version: 6.0.1
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https://api.github.com/repos/huggingface/datasets/issues/3757 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3757/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3757/comments | https://api.github.com/repos/huggingface/datasets/issues/3757/events | https://github.com/huggingface/datasets/pull/3757 | 1,143,300,880 | PR_kwDODunzps4zGK7p | 3,757 | Add perplexity to metrics | {
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This code differs from the code in [this](https://huggingface.co/docs/transformers/perplexity) HF blog post because the blogpost code fails in at least the following circumstances:
- returns nans whenever the stride = 1
- hits a runtime error when the stride is significantly larger than the max model length (e.g. if max_model_length = 512 and stride = 1024)
Note that:
- As it is, it only works for causal models. Pseudoperplexity can be added later as another metric to work with masked language models.
- It takes in a list of strings so that it can be dataset independent. This does mean that it doesn't currently batch inputs, and is therefore relatively slow.
- It overwrites the metrics compute() function for a specific perplexity compute() function. This is because the current general metrics compute() function requires model-generated predictions, which doesn't make sense in the context of perplexity | {
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https://api.github.com/repos/huggingface/datasets/issues/3756 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3756/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3756/comments | https://api.github.com/repos/huggingface/datasets/issues/3756/events | https://github.com/huggingface/datasets/issues/3756 | 1,143,273,825 | I_kwDODunzps5EJPlh | 3,756 | Images get decoded when using `map()` with `input_columns` argument on a dataset | {
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"Hi! If I'm not mistaken, this behavior is intentional, but I agree it could be more intuitive.\r\n\r\n@albertvillanova Do you remember why you decided not to decode columns in the `Audio` feature PR when `input_columns` is not `None`? IMO we should decode those columns, and we don't even have to use lazy structure... | 2022-02-18T15:35:38 | 2022-12-13T16:59:06 | 2022-12-13T16:59:06 | NONE | null | ## Describe the bug
The `datasets.features.Image` feature class decodes image data by default. Expectedly, when indexing a dataset or using the `map()` method, images are returned as PIL Image instances.
However, when calling `map()` and setting a specific data column with the `input_columns` argument, the image data is passed as raw byte representation to the mapping function.
## Steps to reproduce the bug
```python
from datasets import load_dataset
from torchvision import transforms
from PIL.Image import Image
dataset = load_dataset('mnist', split='train')
def transform_all_columns(example):
# example['image'] is encoded as PIL Image
assert isinstance(example['image'], Image)
return example
def transform_image_column(image):
# image is decoded here and represented as raw bytes
assert isinstance(image, Image)
return image
# single-sample dataset for debugging purposes
dev = dataset.select([0])
dev.map(transform_all_columns)
dev.map(transform_image_column, input_columns='image')
```
## Expected results
Image data should be passed in decoded form, i.e. as PIL Image objects to the mapping function unless the `decode` attribute on the image feature is set to `False`.
## Actual results
The mapping function receives images as raw byte data.
## Environment info
- `datasets` version: 1.18.3
- Platform: Linux-5.11.0-49-generic-x86_64-with-glibc2.32
- Python version: 3.8.0b4
- PyArrow version: 7.0.0
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https://api.github.com/repos/huggingface/datasets/issues/3755 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3755/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3755/comments | https://api.github.com/repos/huggingface/datasets/issues/3755/events | https://github.com/huggingface/datasets/issues/3755 | 1,143,032,961 | I_kwDODunzps5EIUyB | 3,755 | Cannot preview dataset | {
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"Thanks for reporting. The dataset viewer depends on some backend treatments, and for now, they might take some hours to get processed. We're working on improving it.",
"It has finally been processed. Thanks for the patience.",
"Thanks for the info @severo !"
] | 2022-02-18T13:06:45 | 2022-02-19T14:30:28 | 2022-02-18T15:41:33 | NONE | null | ## Dataset viewer issue for '*rubrix/news*'
**Link:https://huggingface.co/datasets/rubrix/news** *link to the dataset viewer page*
Cannot see the dataset preview:
```
Status code: 400
Exception: Status400Error
Message: Not found. Cache is waiting to be refreshed.
```
Am I the one who added this dataset ? No
| {
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https://api.github.com/repos/huggingface/datasets/issues/3754 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3754/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3754/comments | https://api.github.com/repos/huggingface/datasets/issues/3754/events | https://github.com/huggingface/datasets/issues/3754 | 1,142,886,536 | I_kwDODunzps5EHxCI | 3,754 | Overflowing indices in `select` | {
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"Fixed on master (see https://github.com/huggingface/datasets/pull/3719).",
"Awesome, I did not find that one! Thanks."
] | 2022-02-18T11:30:52 | 2022-02-18T11:38:23 | 2022-02-18T11:38:23 | MEMBER | null | ## Describe the bug
The `Dataset.select` function seems to accept indices that are larger than the dataset size and seems to effectively use `index %len(ds)`.
## Steps to reproduce the bug
```python
from datasets import Dataset
ds = Dataset.from_dict({"test": [1,2,3]})
ds = ds.select(range(5))
print(ds)
print()
print(ds["test"])
```
Result:
```python
Dataset({
features: ['test'],
num_rows: 5
})
[1, 2, 3, 1, 2]
```
This behaviour is not documented and can lead to unexpected behaviour when for example taking a sample larger than the dataset and thus creating a lot of duplicates.
## Expected results
It think this should throw an error or at least a very big warning:
```python
IndexError: Invalid key: 5 is out of bounds for size 3
```
## Environment info
- `datasets` version: 1.18.3
- Platform: macOS-12.0.1-x86_64-i386-64bit
- Python version: 3.9.10
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https://api.github.com/repos/huggingface/datasets/issues/3752 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3752/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3752/comments | https://api.github.com/repos/huggingface/datasets/issues/3752/events | https://github.com/huggingface/datasets/pull/3752 | 1,142,627,889 | PR_kwDODunzps4zD1D9 | 3,752 | Update metadata JSON for cats_vs_dogs dataset | {
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Fix #3750. | {
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https://api.github.com/repos/huggingface/datasets/issues/3751 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3751/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3751/comments | https://api.github.com/repos/huggingface/datasets/issues/3751/events | https://github.com/huggingface/datasets/pull/3751 | 1,142,609,327 | PR_kwDODunzps4zDw9_ | 3,751 | Fix typo in train split name | {
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```
| Tain | Valid | Test |
```
This PR:
- fixes the typo in the train split name
- fixes the column alignment of the split tables
in the README guide and in all datasets. | {
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"Thnaks for reporting @jaketae. We are fixing it. "
] | 2022-02-18T05:46:39 | 2022-02-18T14:56:11 | 2022-02-18T14:56:11 | CONTRIBUTOR | null | ## Describe the bug
Cannot download cats_vs_dogs dataset due to `NonMatchingSplitsSizesError`.
## Steps to reproduce the bug
```python
from datasets import load_dataset
dataset = load_dataset("cats_vs_dogs")
```
## Expected results
Loading is successful.
## Actual results
```
NonMatchingSplitsSizesError: [{'expected': SplitInfo(name='train', num_bytes=7503250, num_examples=23422, dataset_name='cats_vs_dogs'), 'recorded': SplitInfo(name='train', num_bytes=7262410, num_examples=23410, dataset_name='cats_vs_dogs')}]
```
## Environment info
Reproduced on a fresh [Colab notebook](https://colab.research.google.com/drive/13GTvrSJbBGvL2ybDdXCBZwATd6FOkMub?usp=sharing).
## Additional Context
Originally reported in https://github.com/huggingface/transformers/issues/15698.
cc @mariosasko | {
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} | [] | closed | false | null | [] | null | [] | 2022-02-18T01:34:46 | 2022-03-08T09:38:48 | 2022-03-08T09:38:48 | NONE | null | In this PR, tqdm arguments can be passed to the map() function and such, in order to be more flexible. | {
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1. It is able to show the progress bar by adding the length of the iterator.
2. Pass in tqdm_kwargs so that can enable more feasibility for the control of tqdm library. | {
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} | [] | closed | false | null | [] | null | [] | 2022-02-17T17:06:31 | 2022-02-23T15:00:59 | 2022-02-23T15:00:58 | MEMBER | null | When shuffling in streaming mode, those two entangled lists are shuffled independently. In this PR I changed this to shuffle the lists of same length with the exact same seed, in order for the files and metadata to still be aligned.
```python
gen_kwargs = {
"files": [os.path.join(data_dir, filename) for filename in all_files],
"metadata_files": [all_metadata[filename] for filename in all_files],
}
```
IMO this is important to avoid big but silent issues.
Fix https://github.com/huggingface/datasets/issues/3744 | {
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} | [] | closed | false | null | [] | null | [] | 2022-02-17T15:52:17 | 2022-03-08T13:20:26 | 2022-03-08T13:20:26 | CONTRIBUTOR | null | This PR adds the mean Intersection-over-Union metric to the library, useful for tasks like semantic segmentation.
It is entirely based on mmseg's [implementation](https://github.com/open-mmlab/mmsegmentation/blob/master/mmseg/core/evaluation/metrics.py).
I've removed any PyTorch dependency, and rely on Numpy only. | {
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"node_id": "MDU6... | closed | false | null | [] | null | [] | 2022-02-17T15:07:21 | 2022-02-23T15:00:58 | 2022-02-23T15:00:58 | MEMBER | null | Sometimes a dataset script has a `_split_generators` that returns several files as well as the corresponding metadata of each file. It often happens that they end up in two separate lists in the `gen_kwargs`:
```python
gen_kwargs = {
"files": [os.path.join(data_dir, filename) for filename in all_files],
"metadata_files": [all_metadata[filename] for filename in all_files],
}
```
It happened for Multilingual Spoken Words for example in #3666
However currently **the two lists are shuffled independently** when shuffling the shards in streaming mode. This leads to `_generate_examples` not having the right metadata for each file.
To prevent this issue I suggest that we always shuffle lists of the same length the exact same way to avoid such a big but silent issue.
cc @polinaeterna | {
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I bumped into this particular `ValueError` during my work (because an instance of `np.int64` was passed instead of regular Python `int`), and so I had to `print(type(values))` myself. Apparently, it's just the missing `f` to make message an f-string.
It ain't much for a contribution, but it's honest work. Hope it spares someone else a few seconds in the future 😃 | {
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https://api.github.com/repos/huggingface/datasets/issues/3741 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3741/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3741/comments | https://api.github.com/repos/huggingface/datasets/issues/3741/events | https://github.com/huggingface/datasets/pull/3741 | 1,141,132,649 | PR_kwDODunzps4y-syt | 3,741 | Rm sphinx doc | {
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- [x] Update circle ci yaml
- [x] Delete sphinx static & python files in docs dir
- [x] Update readme in docs dir
- [ ] Update docs config in setup.py | {
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https://api.github.com/repos/huggingface/datasets/issues/3740 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3740/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3740/comments | https://api.github.com/repos/huggingface/datasets/issues/3740/events | https://github.com/huggingface/datasets/pull/3740 | 1,140,720,739 | PR_kwDODunzps4y9XAP | 3,740 | Support streaming for pubmed | {
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} | [] | closed | false | null | [] | null | [] | 2022-02-17T00:18:22 | 2022-02-18T14:42:13 | 2022-02-18T14:42:13 | CONTRIBUTOR | null | This PR makes some minor changes to the `pubmed` dataset to allow for `streaming=True`. Fixes #3739.
Basically, I followed the C4 dataset which works in streaming mode as an example, and made the following changes:
* Change URL prefix from `ftp://` to `https://`
* Explicilty `open` the filename and pass the XML contents to `etree.fromstring(xml_str)`
The Github diff tool makes it look like the changes are larger than they are, sorry about that.
I tested locally and the `pubmed` dataset now works in both normal and streaming modes. There is some overhead at the start of each shard in streaming mode as building the XML tree online is quite slow (each pubmed .xml.gz file is ~20MB), but the overhead gets amortized over all the samples in the shard. On my laptop with a single CPU worker I am able to stream at about ~600 samples/s. | {
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https://api.github.com/repos/huggingface/datasets/issues/3739 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3739/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3739/comments | https://api.github.com/repos/huggingface/datasets/issues/3739/events | https://github.com/huggingface/datasets/issues/3739 | 1,140,329,189 | I_kwDODunzps5D-Arl | 3,739 | Pubmed dataset does not work in streaming mode | {
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"Thanks for reporting, @abhi-mosaic (related to #3655).\r\n\r\nPlease note that `xml.etree.ElementTree.parse` already supports streaming:\r\n- #3476\r\n\r\nNo need to refactor to use `open`/`xopen`. Is is enough with importing the package `as ET` (instead of `as etree`)."
] | 2022-02-16T17:13:37 | 2022-02-18T14:42:13 | 2022-02-18T14:42:13 | CONTRIBUTOR | null | ## Describe the bug
Trying to use the `pubmed` dataset with `streaming=True` fails.
## Steps to reproduce the bug
```python
import datasets
pubmed_train = datasets.load_dataset('pubmed', split='train', streaming=True)
print (next(iter(pubmed_train)))
```
## Expected results
I would expect to see the first training sample from the pubmed dataset.
## Actual results
```
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/Users/abhinav/Documents/mosaicml/mosaicml_venv/lib/python3.8/site-packages/datasets/iterable_dataset.py", line 367, in __iter__
for key, example in self._iter():
File "/Users/abhinav/Documents/mosaicml/mosaicml_venv/lib/python3.8/site-packages/datasets/iterable_dataset.py", line 364, in _iter
yield from ex_iterable
File "/Users/abhinav/Documents/mosaicml/mosaicml_venv/lib/python3.8/site-packages/datasets/iterable_dataset.py", line 79, in __iter__
for key, example in self.generate_examples_fn(**self.kwargs):
File "/Users/abhinav/.cache/huggingface/modules/datasets_modules/datasets/pubmed/9715addf10c42a7877a2149ae0c5f2fddabefc775cd1bd9b03ac3f012b86ce46/pubmed.py", line 373, in _generate_examples
tree = etree.parse(filename)
File "/Library/Developer/CommandLineTools/Library/Frameworks/Python3.framework/Versions/3.8/lib/python3.8/xml/etree/ElementTree.py", line 1202, in parse
tree.parse(source, parser)
File "/Library/Developer/CommandLineTools/Library/Frameworks/Python3.framework/Versions/3.8/lib/python3.8/xml/etree/ElementTree.py", line 584, in parse
source = open(source, "rb")
FileNotFoundError: [Errno 2] No such file or directory: 'gzip://pubmed21n0001.xml::ftp://ftp.ncbi.nlm.nih.gov/pubmed/baseline/pubmed21n0001.xml.gz'
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.18.2
- Platform: macOS-11.4-x86_64-i386-64bit
- Python version: 3.8.2
- PyArrow version: 6.0.0
## Comments
The error looks like an issue with `open` vs. `xopen` inside the `xml` package. It looks like it's trying to open the remote source URL, which has been edited with prefix `gzip://...`.
Maybe there can be an explicit `xopen` before passing the raw data to `etree`, something like:
```python
# Before
tree = etree.parse(filename)
root = tree.getroot()
# After
with xopen(filename) as f:
data_str = f.read()
root = etree.fromstring(data_str)
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/3737 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3737/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3737/comments | https://api.github.com/repos/huggingface/datasets/issues/3737/events | https://github.com/huggingface/datasets/pull/3737 | 1,140,148,050 | PR_kwDODunzps4y7uFf | 3,737 | Make RedCaps streamable | {
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} | [] | closed | false | null | [] | null | [] | 2022-02-16T15:12:23 | 2022-02-16T15:28:38 | 2022-02-16T15:28:37 | CONTRIBUTOR | null | Make RedCaps streamable.
@lhoestq Using `data/redcaps_v1.0_annotations.zip` as a download URL gives an error locally when running `datasets-cli test` (will investigate this another time) | {
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} | [] | closed | false | null | [] | null | [] | 2022-02-16T15:01:29 | 2022-09-21T14:58:38 | 2022-02-22T09:13:43 | MEMBER | null | Continuation of https://github.com/huggingface/datasets/pull/3664:
- pass the `streaming` parameter to _split_generator
- update @anton-l's code to use this parameter for `common_voice`
- add a comment to explain why we use `download_and_extract` in non-streaming and `iter_archive` in streaming
Now the `common_voice` dataset has a local path back in `ds["path"]`, and this field is `None` in streaming mode.
cc @patrickvonplaten @anton-l @albertvillanova
Fix #3663. | {
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} | [] | closed | false | null | [] | null | [] | 2022-02-16T13:51:28 | 2022-02-17T07:54:26 | 2022-02-17T07:54:25 | MEMBER | null | Fix #3733. | {
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NewsQA dataset has the following bugs:
- the field `validated_answers` is an exact copy of the field `answers` but with the addition of `'count': [0]` to each dict
- the field `badQuestion` does not appear in `answers` nor `validated_answers`
## Steps to reproduce the bug
By inspecting the dataset script we can see that:
- the parsing of `validated_answers` is a copy-paste of the one for `answers`
- the `badQuestion` field is ignored in the parsing of both `answers` and `validated_answers`
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https://api.github.com/repos/huggingface/datasets/issues/3732 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3732/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3732/comments | https://api.github.com/repos/huggingface/datasets/issues/3732/events | https://github.com/huggingface/datasets/pull/3732 | 1,140,004,022 | PR_kwDODunzps4y7PTU | 3,732 | Support streaming in size estimation function in `push_to_hub` | {
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https://api.github.com/repos/huggingface/datasets/issues/3730 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3730/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3730/comments | https://api.github.com/repos/huggingface/datasets/issues/3730/events | https://github.com/huggingface/datasets/issues/3730 | 1,139,545,613 | I_kwDODunzps5D7BYN | 3,730 | Checksum Error when loading multi-news dataset | {
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"Thanks for reporting @byw2.\r\nWe are fixing it.\r\nIn the meantime, you can load the dataset by passing `ignore_verifications=True`:\r\n ```python\r\ndataset = load_dataset(\"multi_news\", ignore_verifications=True)"
] | 2022-02-16T05:11:08 | 2022-02-16T20:05:06 | 2022-02-16T08:48:46 | NONE | null | ## Describe the bug
When using the load_dataset function from datasets module to load the Multi-News dataset, does not load the dataset but throws Checksum Error instead.
## Steps to reproduce the bug
```python
from datasets import load_dataset
dataset = load_dataset("multi_news")
```
## Expected results
Should download and load Multi-News dataset.
## Actual results
Throws the following error and cannot load data successfully:
```
NonMatchingChecksumError: Checksums didn't match for dataset source files:
['https://drive.google.com/uc?export=download&id=1vRY2wM6rlOZrf9exGTm5pXj5ExlVwJ0C']
```
Could this issue please be looked at? Thanks! | {
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https://api.github.com/repos/huggingface/datasets/issues/3729 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3729/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3729/comments | https://api.github.com/repos/huggingface/datasets/issues/3729/events | https://github.com/huggingface/datasets/issues/3729 | 1,139,398,442 | I_kwDODunzps5D6dcq | 3,729 | Wrong number of examples when loading a text dataset | {
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"Hi @kg-nlp, thanks for reporting.\r\n\r\nThat is weird... I guess we would need some sample data file where this behavior appears to reproduce the bug for further investigation... ",
"ok, I found the reason why that two results are not same.\r\nthere is /u2029 in the text, the datasets will split sentence accord... | 2022-02-16T01:13:31 | 2022-03-15T16:16:09 | 2022-03-15T16:16:09 | NONE | null | ## Describe the bug
when I use load_dataset to read a txt file I find that the number of the samples is incorrect
## Steps to reproduce the bug
```
fr = open('train.txt','r',encoding='utf-8').readlines()
print(len(fr)) # 1199637
datasets = load_dataset('text', data_files={'train': ['train.txt']}, streaming=False)
print(len(datasets['train'])) # 1199649
```
I also use command line operation to verify it
```
$ wc -l train.txt
1199637 train.txt
```
## Expected results
please fix that issue
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.8.3
- Platform:windows&linux
- Python version:3.7
- PyArrow version:6.0.1
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https://api.github.com/repos/huggingface/datasets/issues/3728 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3728/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3728/comments | https://api.github.com/repos/huggingface/datasets/issues/3728/events | https://github.com/huggingface/datasets/issues/3728 | 1,139,303,614 | I_kwDODunzps5D6GS- | 3,728 | VoxPopuli | {
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"duplicate of https://github.com/huggingface/datasets/issues/2300"
] | 2022-02-15T23:04:55 | 2022-02-16T18:49:12 | 2022-02-16T18:49:12 | MEMBER | null | ## Adding a Dataset
- **Name:** VoxPopuli
- **Description:** A Large-Scale Multilingual Speech Corpus
- **Paper:** https://arxiv.org/pdf/2101.00390.pdf
- **Data:** https://github.com/facebookresearch/voxpopuli
- **Motivation:** one of the largest (if not the largest) multilingual speech corpus: 400K hours of multilingual unlabeled speech + 17k hours of labeled speech
Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
👀 @kahne @Molugan
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https://api.github.com/repos/huggingface/datasets/issues/3727 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3727/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3727/comments | https://api.github.com/repos/huggingface/datasets/issues/3727/events | https://github.com/huggingface/datasets/pull/3727 | 1,138,979,732 | PR_kwDODunzps4y34JN | 3,727 | Patch all module attributes in its namespace | {
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However those are only a subset of all the module attributes in its namespace (`__dict__` variable).
This PR fixes the problem of modules that have non-None `__all__` variable, but try to access an attribute present in `__dict__` (and not in `__all__`).
For example, `pandas` has attribute `__version__` only present in `__dict__`.
- Before version 1.4, pandas `__all__` was None, thus all attributes in `__dict__` were patched
- From version 1.4, pandas `__all__` is not None, thus attributes in `__dict__` not present in `__all__` are ignored
Fix #3724.
CC: @severo @lvwerra | {
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https://api.github.com/repos/huggingface/datasets/issues/3726 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3726/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3726/comments | https://api.github.com/repos/huggingface/datasets/issues/3726/events | https://github.com/huggingface/datasets/pull/3726 | 1,138,870,362 | PR_kwDODunzps4y3iSv | 3,726 | Use config pandas version in CSV dataset builder | {
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https://api.github.com/repos/huggingface/datasets/issues/3725 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3725/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3725/comments | https://api.github.com/repos/huggingface/datasets/issues/3725/events | https://github.com/huggingface/datasets/pull/3725 | 1,138,835,625 | PR_kwDODunzps4y3bOG | 3,725 | Pin pandas to avoid bug in streaming mode | {
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Related to #3724. | {
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https://api.github.com/repos/huggingface/datasets/issues/3724 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3724/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3724/comments | https://api.github.com/repos/huggingface/datasets/issues/3724/events | https://github.com/huggingface/datasets/issues/3724 | 1,138,827,681 | I_kwDODunzps5D4SGh | 3,724 | Bug while streaming CSV dataset with pandas 1.4 | {
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"followers_... | null | [] | 2022-02-15T15:16:19 | 2022-02-15T16:55:44 | 2022-02-15T16:55:44 | MEMBER | null | ## Describe the bug
If we upgrade to pandas `1.4`, the patching of the pandas module is no longer working
```
AttributeError: '_PatchedModuleObj' object has no attribute '__version__'
```
## Steps to reproduce the bug
```
pip install pandas==1.4
```
```python
from datasets import load_dataset
ds = load_dataset("lvwerra/red-wine", split="train", streaming=True)
item = next(iter(ds))
item
```
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https://api.github.com/repos/huggingface/datasets/issues/3723 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3723/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3723/comments | https://api.github.com/repos/huggingface/datasets/issues/3723/events | https://github.com/huggingface/datasets/pull/3723 | 1,138,789,493 | PR_kwDODunzps4y3RuI | 3,723 | Fix flatten of complex feature types | {
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} | [] | closed | false | null | [] | null | [] | 2022-02-15T14:45:33 | 2022-03-18T17:32:26 | 2022-03-18T17:28:14 | CONTRIBUTOR | null | Fix `flatten` for the following feature types: Image/Audio, Translation, and TranslationVariableLanguages.
Inspired by `cast`/`table_cast`, I've introduced a `table_flatten` function to handle the Image/Audio types.
CC: @SBrandeis
Fix #3686.
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https://api.github.com/repos/huggingface/datasets/issues/3722 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3722/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3722/comments | https://api.github.com/repos/huggingface/datasets/issues/3722/events | https://github.com/huggingface/datasets/pull/3722 | 1,138,770,211 | PR_kwDODunzps4y3NrP | 3,722 | added electricity load diagram dataset | {
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https://api.github.com/repos/huggingface/datasets/issues/3721 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3721/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3721/comments | https://api.github.com/repos/huggingface/datasets/issues/3721/events | https://github.com/huggingface/datasets/pull/3721 | 1,137,617,108 | PR_kwDODunzps4yzXCd | 3,721 | Multi-GPU support for `FaissIndex` | {
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} | [] | closed | false | null | [] | null | [] | 2022-02-14T17:26:51 | 2022-03-07T16:28:57 | 2022-03-07T16:28:56 | CONTRIBUTOR | null | Per #3716 , current implementation does not take into consideration that `faiss` can run on multiple GPUs.
In this commit, I provided multi-GPU support for `FaissIndex` by modifying the device management in `IndexableMixin.add_faiss_index` and `FaissIndex.load`.
Now users are able to pass in
1. a positive integer (as usual) to use 1 GPU
2. a negative integer `-1` to use all GPUs
3. a list of integers e.g. `[0, 1]` to run only on those GPUs
4. Of course, passing in nothing still runs on CPU.
This closes: #3716 | {
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Instead of reusing `_check_valid_index_key` from `datasets.formatting`, I defined a new function to provide a more meaningful error message.
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- fixes a bug in the script, by removing an unnamed column with the row index: fix KeyError
- fix the metadata JSON, by adding both configurations (1.1 and 2.0): fix ExpectedMoreDownloadedFiles
- updates the dataset card
Fix #3515. | {
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https://api.github.com/repos/huggingface/datasets/issues/3717 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3717/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3717/comments | https://api.github.com/repos/huggingface/datasets/issues/3717/events | https://github.com/huggingface/datasets/issues/3717 | 1,137,183,015 | I_kwDODunzps5DyAkn | 3,717 | wrong condition in `Features ClassLabel encode_example` | {
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"Hi @Tudyx, \r\n\r\nPlease note that in Python, the boolean NOT operator (`not`) has lower precedence than comparison operators (`<=`, `<`), thus the expression you mention is equivalent to:\r\n```python\r\n not (-1 <= example_data < self.num_classes)\r\n```\r\n\r\nAlso note that as expected, the exception is raise... | 2022-02-14T11:44:35 | 2022-02-14T15:09:36 | 2022-02-14T15:07:43 | NONE | null | ## Describe the bug
The `encode_example` function in *features.py* seems to have a wrong condition.
```python
if not -1 <= example_data < self.num_classes:
raise ValueError(f"Class label {example_data:d} greater than configured num_classes {self.num_classes}")
```
## Expected results
The `not - 1` condition change the result of the condition. For instance, if `example_data` equals 4 and ` self.num_classes` equals 4 too, `example_data < self.num_classes` will give `False` as expected . But if i add the `not - 1` condition, `not -1 <= example_data < self.num_classes` will give `True` and raise an exception.
## Environment info
- `datasets` version: 1.18.3
- Python version: 3.8.10
- PyArrow version: 7.00
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"Hi @rentruewang, thansk for reporting and for your PR!!! We should definitely support this. ",
"@albertvillanova Great! :)"
] | 2022-02-14T06:21:43 | 2022-03-07T16:28:56 | 2022-03-07T16:28:56 | CONTRIBUTOR | null | **Is your feature request related to a problem? Please describe.**
Currently, because `device` is of the type `int | None`, to leverage `faiss-gpu`'s multi-gpu support, you need to create a `custom_index`. However, if using a `custom_index` created by e.g. `faiss.index_cpu_to_all_gpus`, then `FaissIndex.save` does not work properly because it checks the device id (which is an int, so no multiple GPUs).
**Describe the solution you'd like**
I would like `FaissIndex` to support multiple GPUs, by passing in a list to `add_faiss_index`.
**Describe alternatives you've considered**
Alternatively, I would like it to at least provide a warning cause it wasn't the behavior that I expected.
**Additional context**
Relavent source code here:
https://github.com/huggingface/datasets/blob/6ed6ac9448311930557810383d2cfd4fe6aae269/src/datasets/search.py#L340-L349
Device management needs changing to support multiple GPUs, probably by `isinstance` calls.
I can provide a PR if you like :)
Thanks for reading!
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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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"Looks like I solved my problems ..."
] | 2022-02-13T16:35:45 | 2022-02-13T20:44:04 | 2022-02-13T20:44:04 | NONE | null | ## Dataset viewer issue for 'tatoeba_mt'
**Link:** https://huggingface.co/datasets/Helsinki-NLP/tatoeba_mt
My data loader script does not seem to work.
The files are part of the local repository but cannot be found. An example where it should work is the subset for "afr-eng".
Another problem is that I do not have validation data for all subsets and I don't know how to properly check whether validation exists in the configuration before I try to download it. An example is the subset for "afr-deu".
Am I the one who added this dataset ? Yes
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- [x] Update circle ci yaml
- [x] Delete sphinx static & python files in docs dir
- [x] Update readme in docs dir
- [ ] Update docs config in setup.py | {
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https://api.github.com/repos/huggingface/datasets/issues/3709 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3709/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3709/comments | https://api.github.com/repos/huggingface/datasets/issues/3709/events | https://github.com/huggingface/datasets/pull/3709 | 1,132,997,904 | PR_kwDODunzps4yi0J4 | 3,709 | Set base path to hub url for canonical datasets | {
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cc @polinaeterna this will be useful if we have audio datasets that are canonical and for which you'd like to host data files | {
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https://api.github.com/repos/huggingface/datasets/issues/3707 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3707/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3707/comments | https://api.github.com/repos/huggingface/datasets/issues/3707/events | https://github.com/huggingface/datasets/issues/3707 | 1,132,741,903 | I_kwDODunzps5DhEUP | 3,707 | `.select`: unexpected behavior with `indices` | {
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"Hi! Currently, we compute the final index as `index % len(dset)`. I agree this behavior is somewhat unexpected and that it would be more appropriate to raise an error instead (this is what `df.iloc` in Pandas does, for instance).\r\n\r\n@albertvillanova @lhoestq wdyt?",
"I agree. I think `index % len(dset)` was ... | 2022-02-11T15:20:01 | 2022-02-14T19:19:21 | 2022-02-14T19:19:21 | NONE | null | ## Describe the bug
The `.select` method will not throw when sending `indices` bigger than the dataset length; `indices` will be wrapped instead. This behavior is not documented anywhere, and is not intuitive.
## Steps to reproduce the bug
```python
from datasets import Dataset
ds = Dataset.from_dict({"text": ["d", "e", "f"], "label": [4, 5, 6]})
res1 = ds.select([1, 2, 3])['text']
res2 = ds.select([1000])['text']
```
## Expected results
Both results should throw an `Error`.
## Actual results
`res1` will give `['e', 'f', 'd']`
`res2` will give `['e']`
## Environment info
Bug found from this environment:
- `datasets` version: 1.16.1
- Platform: macOS-10.16-x86_64-i386-64bit
- Python version: 3.8.7
- PyArrow version: 6.0.1
It was also replicated on `master`.
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https://api.github.com/repos/huggingface/datasets/issues/3706 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3706/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3706/comments | https://api.github.com/repos/huggingface/datasets/issues/3706/events | https://github.com/huggingface/datasets/issues/3706 | 1,132,218,874 | I_kwDODunzps5DfEn6 | 3,706 | Unable to load dataset 'big_patent' | {
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"Hi @ankitk2109,\r\n\r\nHave you tried passing the split name with the keyword `split=`? See e.g. an example in our Quick Start docs: https://huggingface.co/docs/datasets/quickstart.html#load-the-dataset-and-model\r\n```python\r\n ds = load_dataset(\"big_patent\", \"d\", split=\"validation\")",
"Hi @albertvillano... | 2022-02-11T09:48:34 | 2022-02-14T15:26:03 | 2022-02-14T15:26:03 | NONE | null | ## Describe the bug
Unable to load the "big_patent" dataset
## Steps to reproduce the bug
```python
load_dataset('big_patent', 'd', 'validation')
```
## Expected results
Download big_patents' validation split from the 'd' subset
## Getting an error saying:
{FileNotFoundError}Local file ..\huggingface\datasets\downloads\6159313604f4f2c01e7d1cac52139343b6c07f73f6de348d09be6213478455c5\bigPatentData\train.tar.gz doesn't exist
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version:1.18.3
- Platform: Windows
- Python version:3.8
- PyArrow version:7.0.0
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https://api.github.com/repos/huggingface/datasets/issues/3705 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3705/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3705/comments | https://api.github.com/repos/huggingface/datasets/issues/3705/events | https://github.com/huggingface/datasets/pull/3705 | 1,132,053,226 | PR_kwDODunzps4yfhyj | 3,705 | Raise informative error when loading a save_to_disk dataset | {
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} | [] | closed | false | null | [] | null | [] | 2022-02-11T08:21:03 | 2022-02-11T22:56:40 | 2022-02-11T22:56:39 | MEMBER | null | People recurrently report error when trying to load a dataset (using `load_dataset`) that was previously saved using `save_to_disk`.
This PR raises an informative error message telling them they should use `load_from_disk` instead.
Close #3700. | {
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https://api.github.com/repos/huggingface/datasets/issues/3704 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3704/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3704/comments | https://api.github.com/repos/huggingface/datasets/issues/3704/events | https://github.com/huggingface/datasets/issues/3704 | 1,132,042,631 | I_kwDODunzps5DeZmH | 3,704 | OSCAR-2109 datasets are misaligned and truncated | {
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"Hi @adrianeboyd, thanks for reporting.\r\n\r\nThere is indeed a bug in that community dataset:\r\nLine:\r\n```python\r\nmetadata_and_text_files = list(zip(metadata_files, text_files))\r\n``` \r\nshould be replaced with\r\n```python\r\nmetadata_and_text_files = list(zip(sorted(metadata_files), sorted(text_files)))\... | 2022-02-11T08:14:59 | 2022-03-17T18:01:04 | 2022-03-16T16:21:28 | NONE | null | ## Describe the bug
The `oscar-corpus/OSCAR-2109` data appears to be misaligned and truncated by the dataset builder for subsets that contain more than one part and for cases where the texts contain non-unix newlines.
## Steps to reproduce the bug
A few examples, although I'm not sure how deterministic the particular (mis)alignment is in various configurations:
```python
from datasets import load_dataset
dataset = load_dataset("oscar-corpus/OSCAR-2109", "deduplicated_fi", split="train", use_auth_token=True)
entry = dataset[0]
# entry["text"] is from fi_part_3.txt.gz
# entry["meta"] is from fi_meta_part_2.jsonl.gz
dataset = load_dataset("oscar-corpus/OSCAR-2109", "deduplicated_no", split="train", use_auth_token=True)
entry = dataset[900000]
# entry["text"] is from no_part_3.txt.gz and contains a blank line
# entry["meta"] is from no_meta_part_1.jsonl.gz
dataset = load_dataset("oscar-corpus/OSCAR-2109", "deduplicated_mk", split="train", streaming=True, use_auth_token=True)
# 9088 texts in the dataset are empty
```
For `deduplicated_fi`, all exported raw texts from the dataset are 17GB rather than 20GB as reported in the data splits overview table. The token count with `wc -w` for the raw texts is 2,067,556,874 rather than the expected 2,357,264,196 from the data splits table.
For `deduplicated_no` all exported raw texts contain 624,040,887 rather than the expected 776,354,517 tokens.
For `deduplicated_mk` it is 122,236,936 rather than 134,544,934 tokens.
I'm not expecting the `wc -w` counts to line up exactly with the data splits table, but for comparison the `wc -w` count for `deduplicated_mk` on the raw texts is 134,545,424.
## Issues
* The meta / text files are not paired correctly when loading, so the extracted texts do not have the right offsets, the metadata is not associated with the correct text, and the text files may not be processed to the end or may be processed beyond the end (empty texts).
* The line count offset is not reset per file so the texts aren't aligned to the right offsets in any parts beyond the first part, leading to truncation when in effect blank lines are not skipped.
* Non-unix newline characters are treated as newlines when reading the text files while the metadata only counts unix newlines for its line offsets, leading to further misalignments between the metadata and the extracted texts, and which also results in truncation.
## Expected results
All texts from the OSCAR release are extracted according to the metadata and aligned with the correct metadata.
## Fixes
Not necessarily the exact fixes/checks you may want to use (I didn't test all languages or do any cross-platform testing, I'm not sure all the details are compatible with streaming), however to highlight the issues:
```diff
diff --git a/OSCAR-2109.py b/OSCAR-2109.py
index bbac1076..5eee8de7 100644
--- a/OSCAR-2109.py
+++ b/OSCAR-2109.py
@@ -20,6 +20,7 @@
import collections
import gzip
import json
+import os
import datasets
@@ -387,9 +388,20 @@ class Oscar2109(datasets.GeneratorBasedBuilder):
with open(checksum_file, encoding="utf-8") as f:
data_filenames = [line.split()[1] for line in f if line]
data_urls = [self.config.base_data_path + data_filename for data_filename in data_filenames]
- text_files = dl_manager.download([url for url in data_urls if url.endswith(".txt.gz")])
- metadata_files = dl_manager.download([url for url in data_urls if url.endswith(".jsonl.gz")])
+ # sort filenames so corresponding parts are aligned
+ text_files = sorted(dl_manager.download([url for url in data_urls if url.endswith(".txt.gz")]))
+ metadata_files = sorted(dl_manager.download([url for url in data_urls if url.endswith(".jsonl.gz")]))
+ assert len(text_files) == len(metadata_files)
metadata_and_text_files = list(zip(metadata_files, text_files))
+ for meta_path, text_path in metadata_and_text_files:
+ # check that meta/text part numbers are the same
+ if "part" in os.path.basename(text_path):
+ assert (
+ os.path.basename(text_path).replace(".txt.gz", "").split("_")[-1]
+ == os.path.basename(meta_path).replace(".jsonl.gz", "").split("_")[-1]
+ )
+ else:
+ assert len(metadata_and_text_files) == 1
return [
datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"metadata_and_text_files": metadata_and_text_files}),
]
@@ -397,10 +409,14 @@ class Oscar2109(datasets.GeneratorBasedBuilder):
def _generate_examples(self, metadata_and_text_files):
"""This function returns the examples in the raw (text) form by iterating on all the files."""
id_ = 0
- offset = 0
for meta_path, text_path in metadata_and_text_files:
+ # line offsets are per text file
+ offset = 0
logger.info("generating examples from = %s", text_path)
- with gzip.open(open(text_path, "rb"), "rt", encoding="utf-8") as text_f:
+ # some texts contain non-Unix newlines that should not be
+ # interpreted as line breaks for the line counts in the metadata
+ # with readline()
+ with gzip.open(open(text_path, "rb"), "rt", encoding="utf-8", newline="\n") as text_f:
with gzip.open(open(meta_path, "rb"), "rt", encoding="utf-8") as meta_f:
for line in meta_f:
# read meta
@@ -411,7 +427,12 @@ class Oscar2109(datasets.GeneratorBasedBuilder):
offset += 1
text_f.readline()
# read text
- text = "".join([text_f.readline() for _ in range(meta["nb_sentences"])]).rstrip()
+ text_lines = [text_f.readline() for _ in range(meta["nb_sentences"])]
+ # all lines contain text (no blank lines or EOF)
+ assert all(text_lines)
+ assert "\n" not in text_lines
offset += meta["nb_sentences"]
+ # only strip the trailing newline
+ text = "".join(text_lines).rstrip("\n")
yield id_, {"id": id_, "text": text, "meta": meta}
id_ += 1
```
I've tested this with a number of smaller deduplicated languages with 1-20 parts and the resulting datasets looked correct in terms of word count and size when compared to the data splits table and raw texts, and the text/metadata alignments were correct in all my spot checks. However, there are many many languages I didn't test and I'm not sure that there aren't any texts containing blank lines in the corpus, for instance. For the cases I tested, the assertions related to blank lines and EOF made it easier to verify that the text and metadata were aligned as intended, since there would be little chance of spurious alignments of variable-length texts across so much data. | {
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https://api.github.com/repos/huggingface/datasets/issues/3702 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3702/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3702/comments | https://api.github.com/repos/huggingface/datasets/issues/3702/events | https://github.com/huggingface/datasets/pull/3702 | 1,130,666,707 | PR_kwDODunzps4yahKc | 3,702 | Update data URL of lm1b dataset | {
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] | closed | false | null | [] | null | [] | 2022-02-10T18:46:30 | 2022-09-23T11:52:39 | 2022-09-23T11:52:39 | NONE | null | The http address doesn't work anymore | {
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https://api.github.com/repos/huggingface/datasets/issues/3701 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3701/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3701/comments | https://api.github.com/repos/huggingface/datasets/issues/3701/events | https://github.com/huggingface/datasets/pull/3701 | 1,130,498,738 | PR_kwDODunzps4yZ8Dw | 3,701 | Pin ElasticSearch | {
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} | [] | closed | false | null | [] | null | [] | 2022-02-10T17:15:26 | 2022-02-10T17:31:13 | 2022-02-10T17:31:12 | MEMBER | null | Until we manage to support ES 8.0, I'm setting the version to `<8.0.0`
Currently we're getting this error on 8.0:
```python
ValueError: Either 'hosts' or 'cloud_id' must be specified
```
When instantiating a `Elasticsearch()` object | {
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https://api.github.com/repos/huggingface/datasets/issues/3700 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3700/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3700/comments | https://api.github.com/repos/huggingface/datasets/issues/3700/events | https://github.com/huggingface/datasets/issues/3700 | 1,130,252,496 | I_kwDODunzps5DXkjQ | 3,700 | Unable to load a dataset | {
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"Hi! `load_dataset` is intended to be used to load a canonical dataset (`wikipedia`), a packaged dataset (`csv`, `json`, ...) or a dataset hosted on the Hub. For local datasets saved with `save_to_disk(\"path/to/dataset\")`, use `load_from_disk(\"path/to/dataset\")`.",
"Maybe we should raise an informative error ... | 2022-02-10T15:05:53 | 2022-02-11T22:56:39 | 2022-02-11T22:56:39 | NONE | null | ## Describe the bug
Unable to load a dataset from Huggingface that I have just saved.
## Steps to reproduce the bug
On Google colab
`! pip install datasets `
`from datasets import load_dataset`
`my_path = "wiki_dataset"`
`dataset = load_dataset('wikipedia', "20200501.fr")`
`dataset.save_to_disk(my_path)`
`dataset = load_dataset(my_path)`
## Expected results
Loading the dataset
## Actual results
ValueError: Couldn't cast
_data_files: list<item: struct<filename: string>>
child 0, item: struct<filename: string>
child 0, filename: string
_fingerprint: string
_format_columns: null
_format_kwargs: struct<>
_format_type: null
_indexes: struct<>
_output_all_columns: bool
_split: string
to
{'builder_name': Value(dtype='string', id=None), 'citation': Value(dtype='string', id=None), 'config_name': Value(dtype='string', id=None), 'dataset_size': Value(dtype='int64', id=None), 'description': Value(dtype='string', id=None), 'download_checksums': {}, 'download_size': Value(dtype='int64', id=None), 'features': {'title': {'dtype': Value(dtype='string', id=None), 'id': Value(dtype='null', id=None), '_type': Value(dtype='string', id=None)}, 'text': {'dtype': Value(dtype='string', id=None), 'id': Value(dtype='null', id=None), '_type': Value(dtype='string', id=None)}}, 'homepage': Value(dtype='string', id=None), 'license': Value(dtype='string', id=None), 'post_processed': Value(dtype='null', id=None), 'post_processing_size': Value(dtype='null', id=None), 'size_in_bytes': Value(dtype='int64', id=None), 'splits': {'train': {'name': Value(dtype='string', id=None), 'num_bytes': Value(dtype='int64', id=None), 'num_examples': Value(dtype='int64', id=None), 'dataset_name': Value(dtype='string', id=None)}}, 'supervised_keys': Value(dtype='null', id=None), 'task_templates': Value(dtype='null', id=None), 'version': {'version_str': Value(dtype='string', id=None), 'description': Value(dtype='string', id=None), 'major': Value(dtype='int64', id=None), 'minor': Value(dtype='int64', id=None), 'patch': Value(dtype='int64', id=None)}}
because column names don't match
## Environment info
- `datasets` version: 1.18.3
- Platform: Linux-5.4.144+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.7.12
- PyArrow version: 6.0.1
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https://api.github.com/repos/huggingface/datasets/issues/3699 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3699/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3699/comments | https://api.github.com/repos/huggingface/datasets/issues/3699/events | https://github.com/huggingface/datasets/pull/3699 | 1,130,200,593 | PR_kwDODunzps4yY49I | 3,699 | Add dev-only config to Natural Questions dataset | {
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} | [] | closed | false | null | [] | null | [] | 2022-02-10T14:42:24 | 2022-02-11T09:50:22 | 2022-02-11T09:50:21 | MEMBER | null | As suggested by @lhoestq and @thomwolf, a new config has been added to Natural Questions dataset, so that only dev split can be downloaded.
Fix #413. | {
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https://api.github.com/repos/huggingface/datasets/issues/3697 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3697/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3697/comments | https://api.github.com/repos/huggingface/datasets/issues/3697/events | https://github.com/huggingface/datasets/pull/3697 | 1,129,795,724 | PR_kwDODunzps4yXeXo | 3,697 | Add code-fill datasets for pretraining/finetuning/evaluating | {
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} | [] | closed | false | null | [] | null | [] | 2022-02-10T10:09:19 | 2022-02-14T08:37:20 | 2022-02-14T08:37:19 | MEMBER | null | Currently, it may raise `DuplicatedKeysError`.
Fix #3630. | {
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https://api.github.com/repos/huggingface/datasets/issues/3695 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3695/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3695/comments | https://api.github.com/repos/huggingface/datasets/issues/3695/events | https://github.com/huggingface/datasets/pull/3695 | 1,129,730,148 | PR_kwDODunzps4yXP44 | 3,695 | Fix ClassLabel to/from dict when passed names_file | {
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} | [] | closed | false | null | [] | null | [] | 2022-02-10T09:47:10 | 2022-02-11T23:02:32 | 2022-02-11T23:02:31 | MEMBER | null | Currently, `names_file` is a field of the data class `ClassLabel`, thus appearing when transforming it to dict (when saving infos). Afterwards, when trying to read it from infos, it conflicts with the other field `names`.
This PR, removes `names_file` as a field of the data class `ClassLabel`.
- it is only used at instantiation to generate the `labels` field
Fix #3631. | {
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https://api.github.com/repos/huggingface/datasets/issues/3693 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3693/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3693/comments | https://api.github.com/repos/huggingface/datasets/issues/3693/events | https://github.com/huggingface/datasets/pull/3693 | 1,128,554,365 | PR_kwDODunzps4yTTcQ | 3,693 | Standardize to `Example::` | {
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https://api.github.com/repos/huggingface/datasets/issues/3692 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3692/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3692/comments | https://api.github.com/repos/huggingface/datasets/issues/3692/events | https://github.com/huggingface/datasets/pull/3692 | 1,128,320,004 | PR_kwDODunzps4yShiu | 3,692 | Update data URL in pubmed dataset | {
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} | [] | closed | false | null | [] | null | [] | 2022-02-09T10:06:21 | 2022-02-14T14:15:42 | 2022-02-14T14:15:41 | MEMBER | null | Fix #3655. | {
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https://api.github.com/repos/huggingface/datasets/issues/3691 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3691/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3691/comments | https://api.github.com/repos/huggingface/datasets/issues/3691/events | https://github.com/huggingface/datasets/pull/3691 | 1,127,629,306 | PR_kwDODunzps4yQThV | 3,691 | Upgrade black to version ~=22.0 | {
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} | [] | closed | false | null | [] | null | [] | 2022-02-08T18:45:19 | 2022-02-08T19:56:40 | 2022-02-08T19:56:39 | MEMBER | null | Upgrades the `datasets` library quality tool `black` to use the first stable release of `black`, version 22.0. | {
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https://api.github.com/repos/huggingface/datasets/issues/3690 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3690/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3690/comments | https://api.github.com/repos/huggingface/datasets/issues/3690/events | https://github.com/huggingface/datasets/pull/3690 | 1,127,493,538 | PR_kwDODunzps4yP2p5 | 3,690 | Update docs to new frontend/UI | {
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} | [] | closed | false | null | [] | null | [] | 2022-02-08T16:38:09 | 2022-03-03T20:04:21 | 2022-03-03T20:04:20 | CONTRIBUTOR | null | ### TLDR: Update `datasets` `docs` to the new syntax (markdown and mdx files) & frontend (as how it looks on [hf.co/transformers](https://huggingface.co/docs/transformers/index))
| Light mode | Dark mode |
|-----------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------|
| <img width="400" alt="Screenshot 2022-02-17 at 14 15 34" src="https://user-images.githubusercontent.com/11827707/154489358-e2fb3708-8d72-4fb6-93f0-51d4880321c0.png"> | <img width="400" alt="Screenshot 2022-02-17 at 14 16 27" src="https://user-images.githubusercontent.com/11827707/154489596-c5a1311b-181c-4341-adb3-d60a7d3abe85.png"> |
## Checklist
- [x] update datasets docs to new syntax (should call `doc-builder convert`) (this PR)
- [x] discuss `@property` methods frontend https://github.com/huggingface/doc-builder/pull/87
- [x] discuss `inject_arrow_table_documentation` (this PR) https://github.com/huggingface/datasets/pull/3690#discussion_r801847860
- [x] update datasets docs path on moon-landing https://github.com/huggingface/moon-landing/pull/2089
- [x] convert pyarrow docstring from Numpydoc style to groups style https://github.com/huggingface/doc-builder/pull/89(https://stackoverflow.com/a/24385103/6558628)
- [x] handle `Raises` section on frontend and doc-builder https://github.com/huggingface/doc-builder/pull/86
- [x] check imgs path (this PR) (nothing to update here)
- [x] doc exaples block has to follow format `Examples::` https://github.com/huggingface/datasets/pull/3693
- [x] fix [this docstring](https://github.com/huggingface/datasets/blob/6ed6ac9448311930557810383d2cfd4fe6aae269/src/datasets/arrow_dataset.py#L3339) (causing svelte compilation error)
- [x] Delete sphinx related files
- [x] Delete sphinx CI
- [x] Update docs config in setup.py
- [x] add `versions.yml` in doc-build https://github.com/huggingface/doc-build/pull/1
- [x] add `versions.yml` in doc-build-dev https://github.com/huggingface/doc-build-dev/pull/1
- [x] https://github.com/huggingface/moon-landing/pull/2089
- [x] format docstrings for example `datasets.DatasetBuilder.download_and_prepare` args format look wrong
- [x] create new github actions. (can probably be in a separate PR) (see the transformers equivalents below)
1. [build_dev_documentation.yml](https://github.com/huggingface/transformers/blob/master/.github/workflows/build_dev_documentation.yml)
2. [build_documentation.yml](https://github.com/huggingface/transformers/blob/master/.github/workflows/build_documentation.yml)
3. [delete_dev_documentation.yml](https://github.com/huggingface/transformers/blob/master/.github/workflows/delete_dev_documentation.yml)
## Note to reviewers
The number of changed files is a lot (100+) because I've converted all `.rst` files to `.mdx` files & they are compiling fine on the svelte side (also, moved all the imgs to to [doc-imgs repo](https://huggingface.co/datasets/huggingface/documentation-images/tree/main/datasets)). Moreover, you should just review them on preprod and see if the rendering look fine.
_Therefore, I'd suggest to focus on the changed_ **`.py`** and **CI files** (github workflows, etc. you can use [this filter here](https://github.com/huggingface/datasets/pull/3690/files?file-filters%5B%5D=.py&file-filters%5B%5D=.yml&show-deleted-files=true&show-viewed-files=true)) during the review & ignore `.mdx` files. (if there's a bug in `.mdx` files, we can always handle it in a separate PR afterwards). | {
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