Minimartzz/github-issues huggingface dataset:
Document link #load_dataset_enhancing_performance points to nowhere
State: closed
Labels: description: Something isn't working
name: bug

## Describe the bug
A clear and concise description of what the bug is.

![image](https://user-images.githubusercontent.com/11674033/175752806-5b066b92-9d28-4771-9112-5c8606f07741.png)


The [load_dataset_enhancing_performance](https://huggingface.co/docs/datasets/v2.3.2/en/package_reference/main_classes#load_dataset_enhancing_performance) link [here](https://huggingface.co/docs/datasets/v2.3.2/en/package_reference/main_classes#datasets.Dataset.load_from_disk.keep_in_memory) points to nowhere, I guess it should point to https://huggingface.co/docs/datasets/v2.3.2/en/cache#improve-performance?


Comments:
Hi! This is indeed the link the docstring should point to. Are you interested in submitting a PR to fix this?

https://github.com/huggingface/datasets/blame/master/docs/source/cache.mdx#L93

There seems already an anchor here. Somehow it doesn't work. I am not very familiar with how this online documentation works.
Add UFSC OCPap dataset
State: closed
Labels: description: Requesting to add a new dataset
name: dataset request

## Adding a Dataset
- **Name:** UFSC OCPap: Papanicolaou Stained Oral Cytology Dataset (v4)
- **Description:** The UFSC OCPap dataset comprises 9,797 labeled images of 1200x1600 pixels acquired from 5 slides of cancer diagnosed and 3 healthy of oral brush samples, from distinct patients.
- **Paper:** https://dx.doi.org/10.2139/ssrn.4119212
- **Data:**  https://data.mendeley.com/datasets/dr7ydy9xbk/1
- **Motivation:** real data of pap stained oral cytology samples

Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).


Comments:
I will add this directly on the hub (same as #4486)—in https://huggingface.co/lapix
Dataset Viewer issue for allocine
State: closed
Labels: description: Related to the dataset viewer on huggingface.co
name: dataset-viewer

### Link

https://huggingface.co/datasets/allocine

### Description

Not sure if this is a problem with `bz2` compression, but I thought these datasets could be streamed:

```
Status code:   400
Exception:     AttributeError
Message:       'TarContainedFile' object has no attribute 'readable'
```

### Owner

No

Comments:
I removed my assignment as @huggingface/datasets should be able to answer better than me


Let me have a look...

Thanks for the quick fix @albertvillanova 

Note that the underlying issue is that datasets containing TAR files are not streamable out of the box: they need being iterated with `dl_manager.iter_archive` to avoid performance issues because they access their file content *sequentially* (no random access).

> Note that the underlying issue is that datasets containing TAR files are not streamable out of the box: they need being iterated with `dl_manager.iter_archive` to avoid performance issues because they access their file content _sequentially_ (no random access).

Ah thanks for the clarification! I'll look out for this next time and implement the fix myself :)
Add evaluation metadata to wmt14
State: closed
Labels: description: Contribution to a dataset script
name: dataset contribution


Comments:
The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_4558). All of your documentation changes will be reflected on that endpoint.

As discussed with @lewtun, we are closing this PR, because it requires first the task names to be aligned between AutoTrain and datasets.
Add evaluation metadata to wmt16
State: closed
Labels: description: Contribution to a dataset script
name: dataset contribution

Just to confirm: we should add this metadata via GitHub and not Hub PRs for canonical datasets right?

Comments:
The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_4557). All of your documentation changes will be reflected on that endpoint.

> Just to confirm: we should add this metadata via GitHub and not Hub PRs for canonical datasets right?

yes :)

As discussed with @lewtun, we are closing this PR, because it requires first the task names to be aligned between AutoTrain and datasets.
Dataset Viewer issue for conll2003
State: closed
Labels: description: Related to the dataset viewer on huggingface.co
name: dataset-viewer

### Link

https://huggingface.co/datasets/conll2003/viewer/conll2003/test

### Description

Seems like a cache problem with this config / split:

```
Server error
Status code:   400
Exception:     FileNotFoundError
Message:       [Errno 2] No such file or directory: '/cache/modules/datasets_modules/datasets/conll2003/__init__.py'
```

### Owner

No

Comments:
Fixed, thanks.
Dataset Viewer issue for xtreme
State: closed
Labels: description: Related to the dataset viewer on huggingface.co
name: dataset-viewer

### Link

https://huggingface.co/datasets/xtreme/viewer/PAN-X.de/test

### Description

There seems to be a problem with the cache of this config / split:

```
Server error
Status code:   400
Exception:     FileNotFoundError
Message:       [Errno 2] No such file or directory: '/cache/modules/datasets_modules/datasets/xtreme/349258adc25bb45e47de193222f95e68a44f7a7ab53c4283b3f007208a11bf7e/xtreme.py'
```

### Owner

No

Comments:
Fixed, thanks.
Fix WMT dataset loading issue and docs update (Re-opened)
State: closed

This PR is a fix for #4354 

Changes are made for `wmt14`, `wmt15`, `wmt16`, `wmt17`, `wmt18`, `wmt19` and `wmt_t2t`. And READMEs are updated for the corresponding datasets.

Let me know, if any additional changes are required.

Thanks

Comments:
_The documentation is not available anymore as the PR was closed or merged._
Stop dropping columns in to_tf_dataset() before we load batches
State: closed

`to_tf_dataset()` dropped unnecessary columns before loading batches from the dataset, but this is causing problems when using a transform, because the dropped columns might be needed to compute the transform. Since there's no real way to check which columns the transform might need, we skip dropping columns and instead drop keys from the batch after we load it.

cc @amyeroberts and https://github.com/huggingface/notebooks/pull/202

Comments:
_The documentation is not available anymore as the PR was closed or merged._

@lhoestq Rebasing fixed the test failures, so this should be ready to review now! There's still a failure on Win but it seems unrelated.

Gentle ping @lhoestq ! This is a simple fix (dropping columns after loading a batch from the dataset rather than with `.remove_columns()` to make sure we don't break transforms), and tests are green so we're ready for review!

@lhoestq Test is in!
Tell users to upload on the hub directly
State: closed

As noted in https://github.com/huggingface/datasets/pull/4534, it is still not clear that it is recommended to add datasets on the Hugging Face Hub directly instead of GitHub, so I updated some docs.

Moreover since users won't be able to get reviews from us on the Hub, I added a paragraph to tell users that they can open a discussion and tag `datasets` maintainers for reviews.

Finally I removed the _previous good reasons_ to add a dataset on GitHub to only keep this one:

> In some rare cases it makes more sense to open a PR on GitHub. For example when you are not the author of the dataset and there is no clear organization / namespace that you can put the dataset under.

Does it sound good to you @albertvillanova @julien-c ?

Comments:
_The documentation is not available anymore as the PR was closed or merged._

Thanks ! I updated the two remaining files
Perform hidden file check on relative data file path
State: closed

Fix #4549 

Comments:
_The documentation is not available anymore as the PR was closed or merged._

I'm aware of this behavior, which is tricky to solve due to fsspec's hidden file handling (see https://github.com/huggingface/datasets/issues/4115#issuecomment-1108819538). I've tested some regex patterns to address this, and they seem to work (will push them on Monday; btw they don't break any of fsspec's tests, so maybe we can contribute this as an enhancement to them). Also, perhaps we should include the files starting with `__`  in the results again (we hadn't had issues with this pattern before). WDYT?

I see. Feel free to merge this one if it's good for you btw :)

> Also, perhaps we should include the files starting with __ in the results again (we hadn't had issues with this pattern before)

The point was mainly to ignore `__pycache__` directories for example. Also also for consistency with the iter_files/iter_archive which are already ignoring them

Very elegant solution! Feel free to merge if the CI is green after adding the tests.

CI failure is unrelated to this PR
imdb source error
State: closed
Labels: description: Something isn't working
name: bug

## Describe the bug
imdb dataset not loading

## Steps to reproduce the bug
```python
from datasets import load_dataset
dataset = load_dataset("imdb")
```


## Expected results


## Actual results
```bash
06/23/2022 14:45:18 - INFO - datasets.builder - Dataset not on Hf google storage. Downloading and preparing it from source
06/23/2022 14:46:34 - INFO - datasets.utils.file_utils - HEAD request to http://ai.stanford.edu/~amaas/data/sentiment/aclImdb_v1.tar.gz timed out, retrying... [1.0]
.....
ConnectionError: Couldn't reach http://ai.stanford.edu/~amaas/data/sentiment/aclImdb_v1.tar.gz (ConnectTimeout(MaxRetryError("HTTPConnectionPool(host='ai.stanford.edu', port=80): Max retries exceeded with url: /~amaas/data/sentiment/aclImdb_v1.tar.gz (Caused by ConnectTimeoutError(<urllib3.connection.HTTPConnection object at 0x7f2d750cf690>, 'Connection to ai.stanford.edu timed out. (connect timeout=100)'))")))
```
## Environment info
- `datasets` version: 2.3.2
- Platform: Linux-5.4.188+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.7.13
- PyArrow version: 6.0.1
- Pandas version: 1.3.5


Comments:
Thanks for reporting, @Muhtasham.

Indeed IMDB dataset is not accessible from yesterday, because the data is hosted on the data owners servers at Stanford (http://ai.stanford.edu/) and these are down due to a power outage originated by a fire: https://twitter.com/StanfordAILab/status/1539472302399623170?s=20&t=1HU1hrtaXprtn14U61P55w

As a temporary workaroud, you can load the IMDB dataset with this tweak:
```python
ds = load_dataset("imdb", revision="tmp-fix-imdb")
```
FileNotFoundError when passing a data_file inside a directory starting with double underscores
State: closed
Labels: description: Something isn't working
name: bug

Bug experienced in the `accelerate` CI: https://github.com/huggingface/accelerate/runs/7016055148?check_suite_focus=true

This is related to https://github.com/huggingface/datasets/pull/4505 and the changes from https://github.com/huggingface/datasets/pull/4412

Comments:
I have consistently experienced this bug on GitHub actions when bumping to `2.3.2`

We're working on a fix ;)
Metadata.jsonl for Imagefolder is ignored if it's in a parent directory to the splits directories/do not have "{split}_" prefix
State: closed

If data contains a single `metadata.jsonl` file for several splits, it won't be included in a dataset's `data_files` and therefore ignored. 
This happens when a directory is structured like as follows:
```
train/
  file_1.jpg
  file_2.jpg
test/
  file_3.jpg
  file_4.jpg
metadata.jsonl
```
or like as follows:
```
train_file_1.jpg
train_file_2.jpg
test_file_3.jpg
test_file_4.jpg
metadata.jsonl
```
The same for HF repos.

because it's ignored by the patterns [here](https://github.com/huggingface/datasets/blob/master/src/datasets/data_files.py#L29)

@lhoestq @mariosasko Do you think it's better to add this functionality in `data_files.py` or just specifically in imagefolder/audiofolder code? In `data_files.py` would me more general but I don't know if there are any other cases when that might be needed.
 

Comments:
I agree it would be nice to support this. It doesn't fit really well in the current data_files.py, where files of each splits are separated in different folder though, maybe we have to modify a bit the logic here. 

One idea would be to extend `get_patterns_in_dataset_repository` and `get_patterns_locally` to additionally check for `metadata.json`, but feel free to comment if you have better ideas (I feel like we're reaching the limits of what the current implementation IMO, so we could think of a different way of resolving the data files if necessary)
[CI] fixing seqeval install in ci by pinning setuptools-scm
State: closed

The latest setuptools-scm version supported on 3.6 is 6.4.2. However for some reason circleci has version 7, which doesn't work.

I fixed this by pinning the version of setuptools-scm in the circleci job

Fix https://github.com/huggingface/datasets/issues/4544

Comments:
_The documentation is not available anymore as the PR was closed or merged._
Make DuplicateKeysError more user friendly [For Issue #2556]
State: closed

# What does this PR do?

## Summary

*DuplicateKeysError error does not provide any information regarding the examples which have the same the key.*

*This information is very helpful for debugging the dataset generator script.*

## Additions
-

## Changes
- Changed `DuplicateKeysError Class` in `src/datasets/keyhash.py` to add current index and duplicate_key_indices to error message.
- Changed `check_duplicate_keys` function in `src/datasets/arrow_writer.py` to find indices of examples with duplicate hash if duplicate keys are found.

## Deletions
-

## To do  : 
- [x] Find way to find and print path `<Path to Dataset>` in Error message 

## Issues Addressed : 

Fixes #2556  

Comments:
> Nice thanks !
> 
> After your changes feel free to mark this PR as "ready for review" ;)

Marking PR ready for review.

@lhoestq Let me know if there is anything else required or if we are good to go ahead and merge.

_The documentation is not available anymore as the PR was closed or merged._
Fix timestamp conversion from Pandas to Python datetime in streaming mode
State: closed

Arrow accepts both pd.Timestamp and datetime.datetime objects to create timestamp arrays.
However a timestamp array is always converted to datetime.datetime objects.

This created an inconsistency between streaming in non-streaming. e.g. the `ett` dataset outputs datetime.datetime objects in non-streaming but pd.timestamp in streaming.

I fixed this by always converting pd.Timestamp to datetime.datetime during the example encoding step.
I fixed the same issue for pd.Timedelta as well. Finally I added an extra step of conversion for Series and DataFrame to take this into account in case such data are passed as Series or DataFrame.

Fix https://github.com/huggingface/datasets/issues/4533
Related to https://github.com/huggingface/datasets-server/issues/397

Comments:
_The documentation is not available anymore as the PR was closed or merged._

CI failures are unrelated to this PR, merging
Avoid splitting by` .py` for the file.
State: closed
Labels: description: Good for newcomers
name: good first issue

https://github.com/huggingface/datasets/blob/90b3a98065556fc66380cafd780af9b1814b9426/src/datasets/load.py#L272


Hello, 
Thanks you for this library . 

 I was using it and I had one edge case. my home folder name ends with `.py` it is `/home/espoir.py` so anytime I am running the code to load a local module this code here it is failing because after splitting it is trying to save the code to my home directory.


Step to reproduce.

- If you have a home folder which ends with `.py`

- load a module with a local folder 
`qa_dataset = load_dataset("src/data/build_qa_dataset.py")`
it is failed 
A possible workaround would be to use pathlib at the mentioned line

` meta_path = Path(importable_local_file).parent.joinpath("metadata.json")` this can alivate the issue .

Let me what are your thought on this and I can try to fix it by A PR.


Comments:
Hi @espoirMur, thanks for reporting.

You are right: that code line could be improved and made more generically valid.

On the other hand, I would suggest using `os.path.splitext` instead.

Are you willing to open a PR? :)

I will have a look.. 

This weekend .. 

@albertvillanova  , Can you have a look at #4590. 

Thanks 

#self-assign
Replace deprecated logging.warn with logging.warning
State: closed

Replace `logging.warn` (deprecated in [Python 2.7, 2011](https://github.com/python/cpython/commit/04d5bc00a219860c69ea17eaa633d3ab9917409f)) with `logging.warning` (added in [Python 2.3, 2003](https://github.com/python/cpython/commit/6fa635df7aa88ae9fd8b41ae42743341316c90f7)).

* https://docs.python.org/3/library/logging.html#logging.Logger.warning
* https://github.com/python/cpython/issues/57444


Comments:
Dataset Viewer issue for Pile of Law
State: closed
Labels: description: Related to the dataset viewer on huggingface.co
name: dataset-viewer

### Link

https://huggingface.co/datasets/pile-of-law/pile-of-law

### Description

Hi, I would like to turn off the dataset viewer for our dataset without enabling access requests. To comply with upstream dataset creator requests/licenses, we would like to make sure that the data is not indexed by search engines and so would like to turn off dataset previews. But we do not want to collect user emails because it would violate single blind review, allowing us to deduce potential reviewers' identities. Is there a way that we can turn off the dataset viewer without collecting identity information?

Thanks so much! 

### Owner

Yes

Comments:
Hi @Breakend, yes – we'll propose a solution today

Thanks so much, I appreciate it!

Thanks so much for adding the docs. I was able to successfully hide the viewer using the 
```
viewer: false
```
flag in the README.md of the dataset. I'm closing the issue because this is resolved. Thanks again!

Awesome! Thanks for confirming. cc @severo 

Just for the record:

- the doc
  
<img width="1430" alt="Capture d’écran 2022-06-27 à 09 29 27" src="https://user-images.githubusercontent.com/1676121/175884089-bca6c0d5-6387-473e-98ca-86a910ede4bd.png">

- the dataset main page

<img width="1134" alt="Capture d’écran 2022-06-27 à 09 29 05" src="https://user-images.githubusercontent.com/1676121/175884152-5f285bf0-3471-45de-927a-e141b00ebb33.png">

- the dataset viewer page

<img width="567" alt="Capture d’écran 2022-06-27 à 09 29 16" src="https://user-images.githubusercontent.com/1676121/175884191-ab6a297b-1c11-417e-bbde-0b7623278a79.png">
Fix WMT dataset loading issue and docs update
State: closed

This PR is a fix for #4354 

Changes are made for `wmt14`, `wmt15`, `wmt16`, `wmt17`, `wmt18`, `wmt19` and `wmt_t2t`. And READMEs are updated for the corresponding datasets.

As I am on a M1 Mac, I am not able to create a virtual `dev` environment using `pip install -e ".[dev]"`. Issue is with `tensorflow-text` not supported on M1s and there is no supporting repo by Apple or Google. So, if I was needed to perform local testing, I am not able to do that.

Let me know, if any additional changes are required.

Thanks

Comments:
The PR branch now has some commits unrelated to the changes, probably due to rebasing. Can you please close this PR and open a new one from a new branch? You can use  `git cherry-pick` to preserve the relevant changes:
```bash
git checkout master
git remote add upstream git@github.com:huggingface/datasets.git
git pull --ff-only upstream master
git checkout -b wmt-datasets-fix2
git cherry-pick f2d6c995d5153131168f64fc60fe33a7813739a4 a9fdead5f435aeb88c237600be28eb8d4fde4c55
```

Closing this PR due to unwanted commit changes. Will be opening new PR for the same issue.
Properly raise FileNotFound even if the dataset is private
State: closed

`tests/test_load.py::test_load_streaming_private_dataset` was failing because the hub now returns 401 when getting the HfApi.dataset_info of a dataset without authentication. `load_dataset` was raising ConnectionError, while it should be FileNoteFoundError since it first checks for local files before checking the Hub.

Moreover when use_auth_token is not set (default is False), we should not pass `token=None` to HfApi.dataset_info, or it will use the local token by default - instead it should use no token. It's currently not possible to ask for no token to be used, so as a workaround I simply set token="no-token"

Comments:
_The documentation is not available anymore as the PR was closed or merged._
Add `batch_size` parameter when calling `add_faiss_index` and `add_faiss_index_from_external_arrays`
State: closed

Currently, even though the `batch_size` when adding vectors to the FAISS index can be tweaked in `FaissIndex.add_vectors()`, the function `ArrowDataset.add_faiss_index` doesn't have either the parameter `batch_size` to be propagated to the nested `FaissIndex.add_vectors` function or `*args, **kwargs`, so on, this PR adds the `batch_size` parameter to both `ArrowDataset.add_faiss_index` and `ArrowDataset.add_faiss_index_from_external_arrays`.

This is useful so as to tweak the `batch_size` according to the VM specifications.

Comments:
Also, I had a doubt while checking the code related to the indices... 

@lhoestq, there's a value in `config.py` named `DATASET_INDICES_FILENAME` which has the arrow extension (which I assume it should be `indices.faiss`, as the Elastic Search indices are not stored in a file, but not sure), and it's just used before actually saving an `ArrowDataset` in disk, but since those indices are never stored AFAIK, is that actually required?

https://github.com/huggingface/datasets/blob/aec86ea4b790ccccc9b2e0376a496728b1c914cc/src/datasets/config.py#L183

https://github.com/huggingface/datasets/blob/aec86ea4b790ccccc9b2e0376a496728b1c914cc/src/datasets/arrow_dataset.py#L1079-L1092

So should I also remove that?

P.S. I also edited the following code comment which I found misleading as it's not actually storing the indices.

https://github.com/huggingface/datasets/blob/8ddc4bbeb1e2bd307b21f5d21f884649aa2bf640/src/datasets/arrow_dataset.py#L1122

_The documentation is not available anymore as the PR was closed or merged._

> @lhoestq, there's a value in config.py named DATASET_INDICES_FILENAME which has the arrow extension (which I assume it should be indices.faiss, as the Elastic Search indices are not stored in a file, but not sure), and it's just used before actually saving an ArrowDataset in disk, but since those indices are never stored AFAIK, is that actually required?

The arrow file is used to store an indices mapping (when you shuffle the dataset for example) - not for a faiss index ;)

Ok cool thanks a lot for the explanation @lhoestq I was not sure about that :+1: I'll also add it there as you suggested!

CI failures are unrelated to this PR and fixed on master, merging
Add `tldr_news` dataset
State: closed

This PR aims at adding support for a news dataset: `tldr news`.

This dataset is based on the daily [tldr tech newsletter](https://tldr.tech/newsletter) and contains a `headline` as well as a `content` for every piece of news contained in a newsletter.

Comments:
Hey @lhoestq, 
Sorry for opening a PR, I was following the guide [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md)! Thanks for the review anyway, I will follow the instructions you sent 😃 

Thanks, we will update the guide ;)
Timestamp not returned as datetime objects in streaming mode
State: closed
Labels: name: streaming

As reported in (internal) https://github.com/huggingface/datasets-server/issues/397

```python
>>> from datasets import load_dataset
>>> dataset = load_dataset("ett", name="h2", split="test", streaming=True)
>>> d = next(iter(dataset))
>>> d['start']
Timestamp('2016-07-01 00:00:00')
```

while loading in non-streaming mode it returns `datetime.datetime(2016, 7, 1, 0, 0)`

Comments: