rIsHu009/github-issues-updated huggingface dataset:
Title: Add FAISS .range_search() method for retrieving all texts from dataset above similarity threshold
Author: MoritzLaurer (NONE)
State: closed
Created: 2022-03-25T17:31:33Z
Labels: enhancement

**Is your feature request related to a problem? Please describe.**
I would like to retrieve all texts from a dataset, which are semantically similar to a specific input text (query), above a certain (cosine) similarity threshold. My dataset is very large (Wikipedia), so I need to use Datasets and FAISS for this. I would like to be able to repeat many different queries on the dataset quickly. 

**Describe the solution you'd like**
dataset objects currently have the .get_nearest_examples() method for text retrieval via FAISS. But this only allows retrieving a specific number of K texts instead of everything above a specified similarity threshold. 
It would be great if HF Datasets would also support the FAISS method .range_search() for retrieving texts above a certain similarity threshold. 
see details here: https://github.com/facebookresearch/faiss/issues/1273

**Describe alternatives you've considered**
I've considered using native FAISS, but doing this via HF datasets would be better. My assumption is that Dataset features like dataset streaming make it easier to work with large datasets


**Additional context**
The concrete use-case is: I have a large dataset (wikipedia) and I would like to retrieve all paragraphs which are similar to a query. I will use sentence-transformers for encoding the texts.

Comments:
Hi ! You can access the faiss index with
```python
faiss_index = my_dataset.get_index("my_index_name").faiss_index
```
and then do whatever you want with it, e.g. query it using range_search:
```python
threshold = 0.95
limits, distances, indices = faiss_index.range_search(x=xq, thresh=threshold)

texts = dataset[indices]
```

wow, that's great, thank you for the explanation. (if that's not already in the documentation, could be worth adding it)

which type of faiss index is Datasets using? I looked into faiss recently and I understand that there are several different types of indexes and the choice is important, e.g. regarding which distance metric you use (euclidian vs. cosine/dot product), the size of my dataset etc. can I chose the type of index somehow as well?

`Dataset.add_faiss_index` has a `string_factory` parameter, used to set the type of index (see the faiss documentation about [index factory](https://github.com/facebookresearch/faiss/wiki/The-index-factory)). Alternatively, you can pass an index you've defined yourself using faiss with the `custom_index` parameter of `Dataset.add_faiss_index` 

Here is the full documentation of `Dataset.add_faiss_index`: https://huggingface.co/docs/datasets/v2.0.0/en/package_reference/main_classes#datasets.Dataset.add_faiss_index

great thanks, I will try it out
Title: Fix docs on audio feature installation
Author: albertvillanova (MEMBER)
State: closed
Created: 2022-03-25T16:55:11Z

This PR:
- Removes the explicit installation of `librosa` (this is installed with `pip install datasets[audio]`
- Adds the warning for Linux users to install manually the non-Python package `libsndfile`
- Explains that the installation of `torchaudio` is only necessary to support loading audio datasets containing MP3 audio files

Related to #4000.

Comments:
_The documentation is not available anymore as the PR was closed or merged._
Title: ElasticSearch Indexing example: TypeError: __init__() missing 1 required positional argument: 'scheme'
Author: MoritzLaurer (NONE)
State: closed
Created: 2022-03-25T16:22:28Z
Labels: bug

duplicate

## Describe the bug
I am following the example in the documentation for elastic search step by step (on google colab): https://huggingface.co/docs/datasets/faiss_es#elasticsearch

```
from datasets import load_dataset
squad = load_dataset('crime_and_punish', split='train[:1000]')
```

When I run the line: 
`squad.add_elasticsearch_index("context", host="localhost", port="9200")`

I get the error: 
`TypeError: __init__() missing 1 required positional argument: 'scheme'`


## Expected results
No error message

## Actual results

```
TypeError                                 Traceback (most recent call last)

[<ipython-input-23-9205593edef3>](https://localhost:8080/#) in <module>()
      1 import elasticsearch
----> 2 squad.add_elasticsearch_index("text", host="localhost", port="9200")


6 frames

[/usr/local/lib/python3.7/dist-packages/elasticsearch/_sync/client/utils.py](https://localhost:8080/#) in host_mapping_to_node_config(host)
    209         options["path_prefix"] = options.pop("url_prefix")
    210 
--> 211     return NodeConfig(**options)  # type: ignore
    212 
    213 

TypeError: __init__() missing 1 required positional argument: 'scheme'
```

## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 2.2.0
- Platform: Linux, Google Colab
- Python version: Google Colab (probably 3.7)
- PyArrow version: ?

Comments:
Hi, @MoritzLaurer, thanks for reporting.

Normally this is due to a mismatch between the versions of your Elasticsearch client and server:
- your ES client is passing only keyword arguments to your ES server
- whereas your ES server expects a positional argument called 'scheme'

In order to fix this, you should align the major versions of both Elasticsearch client and server.

You can have more info:
- on this other issue page: https://github.com/huggingface/datasets/issues/3956#issuecomment-1072115173
- Elasticsearch client docs: https://www.elastic.co/guide/en/elasticsearch/client/python-api/current/overview.html#_compatibility

Feel free to re-open this issue if the problem persists.

Duplicate of:
- #3956

1. Check elasticsearch version
```
import elasticsearch
print(elasticsearch.__version__)
```
Ex: 7.9.1
2. Uninstall current elasticsearch package
`pip uninstall elasticsearch`
3. Install elasticsearch 7.9.1 package
`pip install elasticsearch==7.9.1`
Title: Missing argument in precision/recall
Author: Dref360 (CONTRIBUTOR)
State: closed
Created: 2022-03-25T15:55:52Z
Labels: enhancement

**Is your feature request related to a problem? Please describe.**
[`sklearn.metrics.precision_score`](https://scikit-learn.org/stable/modules/generated/sklearn.metrics.precision_score.html) accepts an argument `zero_division`, but it is not available in [precision Metric](https://github.com/huggingface/datasets/blob/master/metrics/precision/precision.py#L117)

Same issue is present for Recall.

**Describe the solution you'd like**
Support for **kwargs or adding a new field for `zero_division`.

**Describe alternatives you've considered**
I could filter the warnings myself, but that is not ideal.

**Additional context**
I can make the requested changes if this is approved.

Comments:
Thanks for the suggestion, @Dref360.

We are adding that argument.
Title: Doc: image_process small tip
Author: FrancescoSaverioZuppichini (NONE)
State: closed
Created: 2022-03-25T15:44:32Z

I've added a small tip in the `image_process` doc

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

This tip is unnecessary, i.e., Pillow will already be installed since the `Image` feature requires it for encoding and decoding. Thanks anyway.

cc @stevhliu I've noticed we are missing the installation section in the doc (`pip install datasets[vision]`). I can add it myself.
Title: Replace yahoo_answers_topics data url
Author: lhoestq (MEMBER)
State: closed
Created: 2022-03-25T14:08:57Z

I replaced the Google Drive URL of the dataset by the FastAI one, since we've had some issues with Google Drive.

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

The CI is failing because of issues in the dataset cards that are unrelated to this PR - merging
Title: Fix `map` remove_columns on empty dataset
Author: lhoestq (MEMBER)
State: closed
Created: 2022-03-25T13:36:29Z

On an empty dataset, the `remove_columns` parameter of `map` currently doesn't actually remove the columns:
```python
>>> ds = datasets.load_dataset("glue", "rte")
>>> ds_filtered = ds.filter(lambda x: x["label"] != -1)
>>> ds_mapped = ds_filtered.map(lambda x: x, remove_columns=["label"])
>>> print(repr(ds_mapped.column_names))
{
    'train': ['sentence1', 'sentence2', 'idx'],
    'validation': ['sentence1', 'sentence2', 'idx'],
    'test': ['sentence1', 'sentence2', 'label', 'idx']
}
```

I fixed this error and updated the tests

Comments:
_The documentation is not available anymore as the PR was closed or merged._
Title: Make yelp_polarity streamable
Author: lhoestq (MEMBER)
State: closed
Created: 2022-03-25T10:42:51Z

It was using `dl_manager.download_and_extract` on a TAR archive, which is not supported in streaming mode. I replaced this by `dl_manager.iter_archive`

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

The CI is failing because of the incomplete dataset card - this is unrelated to the goal of this PR so we can ignore it
Title: Replace yelp_review_full data url
Author: lhoestq (MEMBER)
State: closed
Created: 2022-03-25T10:37:18Z

I replaced the Google Drive URL of the Yelp review dataset by the FastAI one, since we've had some issues with Google Drive.

Close https://github.com/huggingface/datasets/issues/4005

Comments:
_The documentation is not available anymore as the PR was closed or merged._
Title: Can not correctly parse the classes with imagefolder
Author: YiSyuanChen (NONE)
State: closed
Created: 2022-03-25T08:51:17Z
Labels: bug

## Describe the bug
I try to load my own image dataset with imagefolder, but the parsing of classes is incorrect.

## Steps to reproduce the bug
I organized my dataset (ImageNet) in the following structure:
```
  - imagenet/
      - train/
          - n01440764/
              - ILSVRC2012_val_00000293.jpg
              - ...... 
          - n01695060/
          - ......
      - val/ 
          - n01440764/
          - n01695060/
          - ......
```

At first, I followed the instructions from the Huggingface [example](https://github.com/huggingface/transformers/tree/main/examples/pytorch/image-classification#using-your-own-data) to load my data as:
```
from datasets import load_dataset
data_files = {'train': 'imagenet/train', 'val': 'imagenet/val'}
ds = load_dataset("nateraw/image-folder", data_files=data_files, task="image-classification")
```
but it resulted following error (I mask my personal path as <PERSONAL_PATH>):
```
FileNotFoundError: Unable to find 'https://huggingface.co/datasets/nateraw/image-folder/resolve/main/imagenet/train' at <PERSONAL_PATH>/ImageNet/https:/huggingface.co/datasets/nateraw/image-folder/resolve/main
```

Next, I followed a recent issue #3960 to load data as:
```
from datasets import load_dataset
data_files = {'train': ['imagenet/train/**'], 'val': ['imagenet/val/**']}
ds = load_dataset("imagefolder", data_files=data_files, task="image-classification")
```
and the data can be loaded without error as: (I copy val folder to train folder for illustration)
```
>>> ds
DatasetDict({
    train: Dataset({
        features: ['image', 'labels'],
        num_rows: 50000
    })
    val: Dataset({
        features: ['image', 'labels'],
        num_rows: 50000
    })
})
```
However, the parsed classes is wrong (should be 1000 classes):
```
>>> ds["train"].features
{'image': Image(decode=True, id=None), 'labels': ClassLabel(num_classes=1, names=['val'], id=None)}
```

## Expected results
I expect that the "labels" in ds["train"].features should contain 1000 classes.

## Actual results
The "labels" in ds["train"].features contains only 1 wrong class.

## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 2.0.0
- Platform: Ubuntu 18.04
- Python version: Python 3.7.12
- PyArrow version: 7.0.0

Comments:
I found that the problem arises because the image files in my folder are actually symbolic links (for my own reasons).  After modifications, the classes can now be correctly parsed. Therefore, I close this issue.

HI, I have a question. How much time did you load the ImageNet data files?
Title: Cannot preview "hazal/Turkish-Biomedical-corpus-trM"
Author: hazalturkmen (NONE)
State: closed
Created: 2022-03-25T07:12:02Z

## Dataset viewer issue for '*hazal/Turkish-Biomedical-corpus-trM'

**Link:** *https://huggingface.co/datasets/hazal/Turkish-Biomedical-corpus-trM*

*I cannot see the dataset preview.*

```
Server Error

Status code:   400
Exception:     HTTPError
Message:       403 Client Error: Forbidden for url: https://huggingface.co/api/datasets/hazal/Turkish-Biomedical-corpus-trM?full=true
```


Am I the one who added this dataset ? Yes

Comments:
Hi @hazalturkmen, thanks for reporting.

Note that your dataset repository does not contain any loading script; it only contains a data file named `tr_article_2`.

When there is no loading script but only data files, the `datasets` library tries to infer how to load the data by looking at the data file extensions. However, your data file does not have any extension.

Note that current supported data file extensions are: 'csv', 'tsv', 'json', 'jsonl', 'parquet', 'txt', 'blp', 'bmp', 'dib', 'bufr', 'cur', 'pcx', 'dcx', 'dds', 'ps', 'eps', 'fit', 'fits', 'fli', 'flc', 'ftc', 'ftu', 'gbr', 'gif', 'grib', 'h5', 'hdf', 'png', 'apng', 'jp2', 'j2k', 'jpc', 'jpf', 'jpx', 'j2c', 'icns', 'ico', 'im', 'iim', 'tif', 'tiff', 'jfif', 'jpe', 'jpg', 'jpeg', 'mpg', 'mpeg', 'msp', 'pcd', 'pxr', 'pbm', 'pgm', 'ppm', 'pnm', 'psd', 'bw', 'rgb', 'rgba', 'sgi', 'ras', 'tga', 'icb', 'vda', 'vst', 'webp', 'wmf', 'emf', 'xbm', 'xpm', 'zip'.

You have more info on our docs: [How to share a dataset](https://huggingface.co/docs/datasets/share).

thanks for reply :)
Title: Fix SQuAD v2 metric docs on `references` format
Author: bryant1410 (CONTRIBUTOR)
State: closed
Created: 2022-03-24T18:27:10Z
Labels: transfer-to-evaluate

`references` it's not a list of dictionaries but a dictionary that has a list in its values.

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

Metrics are deprecated in `datasets` and `evaluate` should be used instead: https://github.com/huggingface/evaluate
Title: Fix None issue with Sequence of dict
Author: lhoestq (MEMBER)
State: closed
Created: 2022-03-24T17:58:59Z

`Features.encode_example` currently fails if it contains a sequence if dict like `Sequence({"subcolumn": Value("int32")})` and if `None` is passed instead of the dict.

```python
  File "/Users/quentinlhoest/Desktop/hf/datasets/src/datasets/features/features.py", line 1310, in encode_example
    return encode_nested_example(self, example)
  File "/Users/quentinlhoest/Desktop/hf/datasets/src/datasets/features/features.py", line 973, in encode_nested_example
    return {k: encode_nested_example(sub_schema, sub_obj) for k, (sub_schema, sub_obj) in zip_dict(schema, obj)}
  File "/Users/quentinlhoest/Desktop/hf/datasets/src/datasets/features/features.py", line 973, in <dictcomp>
    return {k: encode_nested_example(sub_schema, sub_obj) for k, (sub_schema, sub_obj) in zip_dict(schema, obj)}
  File "/Users/quentinlhoest/Desktop/hf/datasets/src/datasets/features/features.py", line 998, in encode_nested_example
    for k, (sub_schema, sub_objs) in zip_dict(schema.feature, obj):
  File "/Users/quentinlhoest/Desktop/hf/datasets/src/datasets/utils/py_utils.py", line 207, in zip_dict
    yield key, tuple(d[key] for d in dicts)
  File "/Users/quentinlhoest/Desktop/hf/datasets/src/datasets/utils/py_utils.py", line 207, in <genexpr>
    yield key, tuple(d[key] for d in dicts)
TypeError: 'NoneType' object is not subscriptable
```

I fixed this issue and updated the tests (this case was missing in the tests)

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

Merging since I'd like do do a patch release soon for this one
Title: AMI load_dataset error: sndfile library not found
Author: i-am-neo (NONE)
State: closed
Created: 2022-03-24T15:13:38Z
Labels: bug

## Describe the bug
Getting error message when loading AMI dataset.

## Steps to reproduce the bug
`python3 -c "from datasets import load_dataset; print(load_dataset('ami', 'headset-single', split='validation')[0])"

`

## Expected results
A clear and concise description of the expected results.

## Actual results
Traceback (most recent call last):
  File "<string>", line 1, in <module>
  File "/home/neo/.virtualenvs/hubert/lib/python3.7/site-packages/datasets/load.py", line 1707, in load_dataset
    use_auth_token=use_auth_token,
  File "/home/neo/.virtualenvs/hubert/lib/python3.7/site-packages/datasets/builder.py", line 595, in download_and_prepare
    dl_manager=dl_manager, verify_infos=verify_infos, **download_and_prepare_kwargs
  File "/home/neo/.virtualenvs/hubert/lib/python3.7/site-packages/datasets/builder.py", line 690, in _download_and_prepare
    ) from None
OSError: Cannot find data file. 
Original error:
sndfile library not found

## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.18.3
- Platform: Linux-4.19.0-18-cloud-amd64-x86_64-with-debian-10.11
- Python version: 3.7.3
- PyArrow version: 7.0.0

Comments:
Issue unresolved, see [4000](https://github.com/huggingface/datasets/issues/4009#issue-1179658611)
Title: set_format does not work with multi dimension tensor
Author: phihung (NONE)
State: closed
Created: 2022-03-24T11:27:43Z
Labels: bug

## Describe the bug
set_format only transforms the last dimension of a multi-dimension list to tensor

## Steps to reproduce the bug
```python
import torch
from datasets import Dataset

ds = Dataset.from_dict({"A": [torch.rand((2, 2))]})
# ds = Dataset.from_dict({"A": [np.random.rand(2, 2)]})  # => same result
ds = ds.with_format("torch")
print(ds[0])
```

## Expected results
```
{'A': [tensor([[0.6689, 0.1516], [0.1403, 0.5567]])]}
```

## Actual results
```
{'A': [tensor([0.6689, 0.1516]), tensor([0.1403, 0.5567])]}
```

## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- datasets version: 2.0.0
- Platform: Mac OSX
- Python version: 3.8.12
- PyArrow version: 7.0.0

Comments:
Hi! Use the `ArrayXD` feature type (where X is the number of dimensions) to get correctly formated tensors. So in your case, define the dataset as follows :
```python
ds = Dataset.from_dict({"A": [torch.rand((2, 2))]}, features=Features({"A": Array2D(shape=(2, 2), dtype="float32")}))
```


Hi @mariosasko I'm facing the same issue and the only work around I've found so far is to convert my `DatasetDict` to a dictionary and then create new objects with `Dataset.from_dict`.
```
dataset = load_dataset("my_dataset.py")
dataset = dataset.map(lambda example: blabla(example))
dict_dataset_test = dataset["test"].to_dict()
...
dataset_test = Dataset.from_dict(dict_dataset_test, features=Features(features))
```
However, converting a `Dataset` object to a dict takes quite a lot of time and memory... Is there a way to directly create an `Array2D` without having to transform the original `Dataset` to a dict?

Hi! Yes, you can directly pass the `Features` dictionary as `features` in `map` to cast the column to `Array2D`:
```python
dataset = dataset.map(lambda example: blabla(example), features=Features(features))
```
Or you can use `cast` after `map` to do that:
```python
dataset = dataset.map(lambda example: blabla(example))
dataset = dataset.cast(Features(features))
```

Fantastic thank you @mariosasko
The first option you suggested is indeed way faster 😃
Title: Use audio feature in ASR task template
Author: lhoestq (MEMBER)
State: closed
Created: 2022-03-24T11:15:22Z

The AutomaticSpeechRecognition task template is outdated: it still uses the file path column as input instead of the audio column.

I changed that and updated all the datasets as well as the tests.

The only community dataset that will need to be updated is `facebook/multilingual_librispeech`. It has almost zero usage unfortunately (probably because users load the duplicate `multilingual_librispeech` directly instead), but it means we can update it.

(this makes me think that we should deprecate `multilingual_librispeech` it and redirect users to `facebook/multilingual_librispeech`).

This PR is also useful for the AudioFolder in https://github.com/huggingface/datasets/pull/3963

Comments:
_The documentation is not available anymore as the PR was closed or merged._
Title: ASSIN 2 dataset: replace broken Google Drive _URLS by links on github
Author: ruanchaves (CONTRIBUTOR)
State: closed
Created: 2022-03-24T10:37:39Z

Closes #4003 .

Fixes checksum error. Replaces Google Drive urls by the files hosted here: [Multilingual Transformer Ensembles for Portuguese Natural Language Tasks](https://github.com/ruanchaves/assin)

Comments:
_The documentation is not available anymore as the PR was closed or merged._
Title: How to use generate this multitask dataset for SQUAD? I am getting a value error. 
Author: gsk1692 (NONE)
State: closed
Created: 2022-03-24T09:21:51Z

## Dataset viewer issue for 'squad_multitask*'

**Link:** https://huggingface.co/datasets/vershasaxena91/squad_multitask

*short description of the issue*

I am trying to generate the multitask dataset for squad dataset. However, gives the error in dataset explorer as well as my local machine. 
I tried the command: dataset = load_dataset("vershasaxena91/squad_multitask", 'highlight_qg_format')
Error:
Status code:   400
Exception:     TypeError
Message:       argument of type 'Value' is not iterable

Kindly advice.

Comments:
Hi! Replacing `nlp.<obj>` with `datasets.<obj>` in the script should fix the problem. `nlp` has been renamed to `datasets` more than a year ago, so please use `datasets` instead to avoid weird issues.

Thank You! Was able to solve with the help of this.

But I request you to please fix the same in the dataset hub explorer as well...

May I ask how to get this dataset?
Title: Fix Audio.encode_example() when writing an array
Author: polinaeterna (CONTRIBUTOR)
State: closed
Created: 2022-03-23T20:32:13Z

Closes  #3996

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

@albertvillanova do you think [this line](https://github.com/huggingface/datasets/pull/3998/files#diff-58e348f6e4deaa5f3119e420a5d48ebb82875a78c28628831748fb54f59b2c78R67) is enough? that's why we missed this bug, we didn't check this case
Title: Sync Features dictionaries
Author: mariosasko (COLLABORATOR)
State: closed
Created: 2022-03-23T19:23:51Z

This PR adds a wrapper to the `Features` class to keep the secondary dict, `_column_requires_decoding`, aligned with the main dict (as discussed in https://github.com/huggingface/datasets/pull/3723#discussion_r806912731).

A more elegant approach would be to subclass `UserDict` and override `__setitem__` and `__delitem__`, but this PR doesn't implement it for the following reasons:
* it requires replacing all occurrences of `isinstance(obj, dict)` with `isinstance(obj, Mapping)`, which is five times slower than `isinstance(obj, dict)` on my machine, in `features.py`
* is a breaking change, i.e., `isinstance(Features(...), dict)` would return `False` after it
* IMO, it makes sense to be consistent in the user-facing API and subclass either `dict` or `UserDict`. The problem with the latter is that it can't be used for `DatasetDict` because `DatasetDict` exposes the `data` property, which is also used by `UserDict`, so this would result in a collision.

Comments:
_The documentation is not available anymore as the PR was closed or merged._
Title: Close `PIL.Image` file handler in `Image.decode_example`
Author: mariosasko (COLLABORATOR)
State: closed
Created: 2022-03-23T14:51:48Z

Closes the file handler of the PIL image object in `Image.decode_example` to avoid the `Too many open files` error.

To pass [the image equality checks](https://app.circleci.com/pipelines/github/huggingface/datasets/10774/workflows/d56670e6-16bb-4c64-b601-a152c5acf5ed/jobs/65825) in CI, `Image.decode_example` calls `image.load()` regardless of how the image object is created (not only for the `PIL.Image.open(local_path)` case). This is needed because `load()` sets the `readonly` attribute of a `PIL.Image` object to 0 (it's 1 after `PIL.Image.open(file_like)`), and in the older PIL versions (only fixed on main), that attribute is considered in `PIL.Image.__eq__`. More info can be found here: https://github.com/python-pillow/Pillow/issues/5926.

Fix #3985

Comments:
_The documentation is not available anymore as the PR was closed or merged._
Title: Streaming dataset + interleave + DataLoader hangs with multiple workers
Author: jpilaul (NONE)
State: open
Created: 2022-03-23T14:27:29Z
Labels: bug

## Describe the bug
Interleaving multiple iterable datasets that use `load_dataset` on streaming mode hangs when passed to `torch.utils.data.DataLoader` with multiple workers.

## Steps to reproduce the bug
```python
from datasets import interleave_datasets, load_dataset
from torch.utils.data import DataLoader

en_dataset = load_dataset('oscar', "unshuffled_deduplicated_en", split='train', streaming=True)
fr_dataset = load_dataset('oscar', "unshuffled_deduplicated_fr", split='train', streaming=True)
it_dataset = load_dataset('oscar', "unshuffled_deduplicated_it", split='train', streaming=True)
de_dataset = load_dataset('oscar', "unshuffled_deduplicated_de", split='train', streaming=True)
multilingual_dataset = interleave_datasets([en_dataset, fr_dataset, de_dataset, it_dataset])
multilingual_dataset = multilingual_dataset.with_format('torch')

next(iter(multilingual_dataset))  # works fairly fast

dataloader = DataLoader(multilingual_dataset, batch_size=8, num_workers=4)
for batch in dataloader:
    print(len(batch))  # prints nothing after 30 min of waiting

dataloader = DataLoader(multilingual_dataset, batch_size=8, num_workers=0)
for batch in dataloader:
    print(len(batch))  # prints right away

```

## Expected results
It should be able to iterate the dataset with multiple workers.

## Actual results
Prints with results with `next(iter(multilingual_dataset)) ` and `num_workers=0`  but it prints nothing with `num_workers=4` or any number above 0.

## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 2.0.1.dev0
- `pytorch` version: 1.10.0+cu113
- Python version: 3.7
- PyArrow version: 6.0.1

Comments:
Same thing occurs when streaming files loaded from disk.

Hi ! Thanks for reporting, could this be related to https://github.com/huggingface/datasets/issues/3950 ?

Currently streaming datasets only works in single process, but we're working on having in work in distributed setups as well :) (EDIT: done)

Hi, thanks for your reply. It seems related :)

+1

Please update `datasets` if you're having this issue. What version are you using ?
Title: Image column is not decoded in map when using with with_transform
Author: phihung (NONE)
State: closed
Created: 2022-03-23T10:51:13Z
Labels: bug

## Describe the bug
Image column is not _decoded_ in **map** when using with `with_transform`

## Steps to reproduce the bug
```python
from datasets import Image, Dataset

def add_C(batch):
    batch["C"] = batch["A"]
    return batch

ds = Dataset.from_dict({"A": ["image.png"]}).cast_column("A",  Image())
ds = ds.with_transform(lambda x: x)  # <= This line causes the problem
ds = ds.map(add_C, batched=True)
print(ds[0])
```

## Expected results
```
{'C': <PIL.PngImagePlugin.PngImageFile>,  ...}
```

## Actual results
```
{'C': {'bytes': None, 'path': 'image.png'}, ...}
```

If we remove the `with_transform` line, we get the expected result.

## Environment info
- `datasets` version: 2.0.0
- Platform: Mac OSX
- Python version: 3.8.12
- PyArrow version: 7.0.0

Comments:
Hi! This behavior stems from this line: https://github.com/huggingface/datasets/blob/799b817d97590ddc97cbd38d07469403e030de8c/src/datasets/arrow_dataset.py#L1919
Basically, the `Image`/`Audio` columns are decoded only if the `format_type` attribute is `None` (`set_format`/`with_format` and `set_transform`/`with_transform` assign a non-`None` value to it) and the  `input_columns` param is not specified (see https://github.com/huggingface/datasets/issues/3756). We will remove these limitations soon.
Title: Add Lung Image Database Consortium image collection (LIDC-IDRI) dataset
Author: omarespejel (NONE)
State: open
Created: 2022-03-22T22:16:05Z
Labels: dataset request

vision

## Adding a Dataset

- **Name:** *Lung Image Database Consortium image collection (LIDC-IDRI)*
- **Description:** *Consists of diagnostic and lung cancer screening thoracic computed tomography (CT) scans with marked-up annotated lesions. It is a web-accessible international resource for development, training, and evaluation of computer-assisted diagnostic (CAD) methods for lung cancer detection and diagnosis. Initiated by the National Cancer Institute (NCI), further advanced by the Foundation for the National Institutes of Health (FNIH), and accompanied by the Food and Drug Administration (FDA) through active participation, this public-private partnership demonstrates the success of a consortium founded on a consensus-based process.*
- **Data:** *[link to the Github repository or current dataset location](https://wiki.cancerimagingarchive.net/display/Public/LIDC-IDRI)*
- **Motivation:** *Key dataset in the healthcare community*

Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).

FYI @osanseviero @abidlabs

Comments:
Title: Improve AutomaticSpeechRecognition task template
Author: polinaeterna (CONTRIBUTOR)
State: closed
Created: 2022-03-22T15:41:08Z
Labels: enhancement

**Is your feature request related to a problem? Please describe.**
[AutomaticSpeechRecognition task template](https://github.com/huggingface/datasets/blob/master/src/datasets/tasks/automatic_speech_recognition.py) is outdated as it uses path to audiofile as an audio column instead of a Audio feature itself (I guess it's because Audio feature didn't exist at the time this template was created).

**Describe the solution you'd like**
Change audio columns from string path to Audio feature.

Comments:
There is an open PR to do that: #3364. I just haven't had time to finish it... 

> There is an open PR to do that: #3364. I just haven't had time to finish it...

😬 thanks...
Title: Remove old wikipedia leftovers
Author: albertvillanova (MEMBER)
State: closed
Created: 2022-03-22T15:25:46Z

After updating Wikipedia dataset, remove old wikipedia leftovers from doc.

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

> This makes me think we shouldn't advise the use of load_dataset in dataset scripts, since it doesn't guarantee that the cache will work as expected (the cache directory is not set correctly, and the required disk space for downloaded files is not recorded)

@lhoestq, do you think it could be a good idea to add a comment in this script WARNING that using load_dataset in a script is not good practice and that people should avoid using that script as a template to create other scripts? 

good idea ! :)
Title: More consistent references in docs
Author: mariosasko (COLLABORATOR)
State: closed
Created: 2022-03-22T14:18:41Z

Aligns the internal references with style discussed in https://github.com/huggingface/datasets/pull/3980.

cc @stevhliu

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

Looks good, thanks for working on this!
Title: Fix Faiss custom_index device
Author: albertvillanova (MEMBER)
State: closed
Created: 2022-03-22T09:11:24Z

Currently, if both `custom_index` and `device` are passed to `FaissIndex`, `device` is silently ignored.

This PR fixes this by raising a ValueError if both arguments are passed.

Alternatively, the `custom_index` could be transferred to the target `device`.

Comments:
_The documentation is not available anymore as the PR was closed or merged._
Title: [image feature] Too many files open error when image feature is returned as a path
Author: apsdehal (CONTRIBUTOR)
State: closed
Created: 2022-03-21T21:54:05Z
Labels: bug

## Describe the bug

PR in context: #3967. If I load the dataset in this PR (TextVQA), and do a simple list comprehension on the dataset, I get `Too many open files error`. This is happening due to the way we are loading the image feature when a str path is returned from the `_generate_examples`. Specifically at https://github.com/huggingface/datasets/blob/508eb4ab5d52f590baa677b4f64b1cc069139f7b/src/datasets/features/image.py#L110, we are open the file handle to the image but never closing it. This in my understanding is causing the issue.

## Steps to reproduce the bug
Pull the PR locally and run the following code
```python
from datasets import load_dataset

dataset = load_dataset("./datasets/textvqa")["train"]
data = [item for item in dataset]

# Error happens
```

## Expected results

List comprehension should work smoothly

## Actual results

`Too many open files error`

## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 2.0.1.dev0
- Platform: macOS-12.2-arm64-arm-64bit
- Python version: 3.10.0
- PyArrow version: 7.0.0
- Pandas version: 1.4.1

Comments:
Title: Exclude Google Drive tests of the CI
Author: lhoestq (MEMBER)
State: closed
Created: 2022-03-21T14:34:16Z

These tests make the CI spam the Google Drive API, the CI now gets banned by Google Drive very often.

I think we can just skip these tests from the CI for now.

In the future we could have a CI job that runs only once a day or once a week for such cases

cc @albertvillanova @mariosasko @severo 

Close #3415

![image](https://user-images.githubusercontent.com/42851186/159283608-fdeca1ac-b57f-4fa3-bf09-6fa5361c494f.png)

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

I was thinking exactly the same: running unit tests that request continuously a third-party API is not a good idea.
Title: Add TER metric card
Author: emibaylor (CONTRIBUTOR)
State: closed
Created: 2022-03-21T13:54:36Z

Add TER metric card

This card is still missing content for the following sections:
- **Limitations & Biases**
- **Values from Papers**
If anyone has any ideas for either of the above, feel free to either add them or point me to them and I'll add them!

Comments:
_The documentation is not available anymore as the PR was closed or merged._
Title: Add tip on how to speed up loading with ImageFolder
Author: mariosasko (COLLABORATOR)
State: closed
Created: 2022-03-21T13:45:58Z

This PR does two things:
* adds a tip on how to speed up loading of a large number of files with ImageFolder (motivated by [this issue](https://github.com/huggingface/datasets/issues/3960))
* replaces the current references to the `Dataset` methods in the Image Processing doc with their fully qualified counterparts (to align it with the Audio Processing doc)

cc @stevhliu

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

Thanks for adding that tip! 👍 

For the docs syntax, it might be better if we hide the package name/full path to the class or function and only show the name of it. I think it's easier for users to read the function name (eg,`cast_column`) instead of the full path which can be a bit lengthy for some functions like `datasets.IterableDataset.remove_columns` (and if we like this idea, we can align the rest of the docs on it). 

> For the docs syntax, it might be better if we hide the package name/full path to the class or function and only show the name of it. I think it's easier for users to read the function name (eg,cast_column) instead of the full path which can be a bit lengthy for some functions like datasets.IterableDataset.remove_columns (and if we like this idea, we can align the rest of the docs on it).

That's also OK, as long as we are consistent.

@lhoestq @albertvillanova @polinaeterna Which one of these two styles do you prefer?

Agree on hiding `datasets` name. Not sure about hiding class name as it's anyway not visible for users if they use `Dataset.cast_column` or  `IterableDataset.cast_column` when working with their datasets. But I agree that the most important thing is to be consistent :)

Good points! :)

I think it'll be good to show the class name since some functions have different parameters. For example, if users click on `IterableDataset.map` and then `Dataset.map`, they'll see different parameters and have to figure out why (which isn't too difficult I guess lol). But showing the class name avoids any confusion upfront.
Title: Fix google drive streaming for small files
Author: lhoestq (MEMBER)
State: closed
Created: 2022-03-21T11:38:46Z

Google drive did another change recently, following #3787 #3843 .

In particular Google Drive now returns 403 for GET requests with `confirm=t` when a files doesn't have a virus warning message. I fixed this by passing `confirm=t` if and only if when there is one (i.e. when status code is 200 for HEAD)

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

Actually the CI fails because of this
![image](https://user-images.githubusercontent.com/42851186/159281771-78e611b1-6b04-4a87-8324-b6ba2d8c6a6a.png)

It looks like we can't have a proper way to test google drive in the CI right now. Though it seems to work locally if you're not banned. I think I'll just disable those tests for now

this fix will not be included?

No we can't do anything except stop using google drive when possible
Title: Adapt `docs/README.md` for datasets
Author: qqaatw (CONTRIBUTOR)
State: closed
Created: 2022-03-21T08:26:49Z
Labels: documentation

## Describe the bug

Currently `docs/README.md` is a direct copy from `transformers`, we should probably adapt this file for `datasets`.

Comments:
Thanks for reporting @qqaatw.

Yes, we should definitely adapt that file for `datasets`.
Title: Fix main classes reference in docs
Author: qqaatw (CONTRIBUTOR)
State: closed
Created: 2022-03-21T08:19:46Z

Currently the section index (on the page's right side) of the [main classes reference](https://huggingface.co/docs/datasets/master/en/package_reference/main_classes) incorrectly displays `Tensor returned:`, this PR fixes this issue by wrapping code examples in this page with markdown code block.

There are other examples in datasets library having this issue.

Comments:
The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3976). All of your documentation changes will be reflected on that endpoint.

Not sure why some section titles end with `[[datasets.xxx]]`, like this: https://moon-ci-docs.huggingface.co/docs/datasets/pr_3976/en/package_reference/main_classes#datasetdict[[datasets.datasetdict]]

Thanks ! I think this has been fixed already in https://github.com/huggingface/datasets/pull/3925 though

I'm closing this one then if it's fine for you
Title: Update many missing tags to dataset README's
Author: MarkusSagen (NONE)
State: closed
Created: 2022-03-20T20:42:27Z

I've started to go through the datasets available and noticed that there are 127 datasets that does not have all the tags so I started filling them in; starting with some of the most common and QA datasets

Not 100% certain that the task_id is correct for SuperGLUE

If anyone is browsing the issues and would like to help make Hugging face datasets even more feature complete and awesome, feel free to use this tool I wrote to find the missing tags in the [datacards](https://github.com/Hugging-Face-Supporter/datacards)

Comments:
Title: Add XFUN dataset
Author: qqaatw (CONTRIBUTOR)
State: closed
Created: 2022-03-20T09:24:54Z
Labels: dataset contribution

This PR adds XFUN dataset.

Home page and repository: https://github.com/doc-analysis/XFUND

Source code: https://github.com/microsoft/unilm/blob/master/layoutlmft/layoutlmft/data/datasets/xfun.py

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

Not sure how to generate dummy data.

The downloaded file structure is 

- document file paths
    - (a json file containing all documents info, document images folder)
    - (a json file containing all documents info, document images folder)
    - ...

Hey @mariosasko, thanks for the review. I'm not sure how to suggest these changes to the owner @ranpox, and I did spend some time to write the model card and hope to get it on the official repo. Is that possible?

Since the author is not responding, maybe we can go ahead with this PR ?

Go for it!

On Tue, Apr 12, 2022 at 10:24 AM Quentin Lhoest ***@***.***>
wrote:

> Since the author is not responding, maybe we can go ahead with this PR ?
>
> —
> Reply to this email directly, view it on GitHub
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@qqaatw Do you plan to finish this PR? I can give you some pointers and help you with the code if needed.

@mariosasko Yes, I'll apply all of the suggestions when I have some time.

Thanks for your contribution, @qqaatw.

We are removing the dataset scripts from this GitHub repo and moving them to the Hugging Face Hub: https://huggingface.co/datasets

We would suggest you propose this changes there to the original repo. Please, feel free to tell us if you need some help.
Title: Adding Roman Urdu Hate Speech dataset
Author: bp-high (CONTRIBUTOR)
State: closed
Created: 2022-03-20T00:19:26Z

This Pull request will add the Roman Urdu Hate speech Dataset.

Comments:
@lhoestq can you review when you have some time? Also were the previous CI fails due to the Google Drive tests which were excluded by #3982 ?

> were the previous CI fails due to the Google Drive tests which were excluded by https://github.com/huggingface/datasets/pull/3982 ?

Yes exactly, merging `master` into your branch fixed the CI ;)

_The documentation is not available anymore as the PR was closed or merged._
Title: Applied index-filters on scores in search.py.
Author: vishalsrao (CONTRIBUTOR)
State: closed
Created: 2022-03-19T18:43:42Z

Updated search.py to resolve the issue mentioned in https://github.com/huggingface/datasets/issues/3961.

Applied index-filters on scores in get_nearest_examples and get_nearest_examples_batch methods of search.py.

Comments:
_The documentation is not available anymore as the PR was closed or merged._
Title: Apply index-filters on scores in get_nearest_examples and get_nearest…
Author: vishalsrao (CONTRIBUTOR)
State: closed
Created: 2022-03-19T18:32:31Z

Updated search.py to resolve the issue mentioned in https://github.com/huggingface/datasets/issues/3961.

Applied index-filters on scores in get_nearest_examples and get_nearest_examples_batch methods of search.py.

Comments:
Title: Cannot preview cnn_dailymail dataset
Author: hasan-besh (NONE)
State: closed
Created: 2022-03-19T14:08:57Z

## Dataset viewer issue for '*cnn_dailymail*'

**Link:** https://huggingface.co/datasets/cnn_dailymail

*short description of the issue*

Am I the one who added this dataset ? Yes-No

Comments:
I guess the cache got corrupted due to a previous issue with Google Drive service.

The cache should be regenerated, e.g. by passing `download_mode="force_redownload"`.

CC: @severo 

Note that the dataset preview uses its own cache, not `datasets`' cache. So `download_mode="force_redownload"` doesn't help. But yes indeed the cache must be refreshed.

The CNN Dailymail dataste is currently hosted on Google Drive, which is an unreliable host and we've had many issues with it. Unless we found another most reliable host for the data, we will keep running into issues from time to time.

At Hugging Face we're not allowed to host the CNN Dailymail data by ourselves AFAIK

Yes @lhoestq, I didn't explain myself well: my previous message was addressed to @severo. 

I remove the tag dataset-viewer, since it's more an issue with the hosting on Google Drive

Sounds good. I was looking for another host of this dataset but couldn't find any (yet)

It seems like the issue is with the streaming mode, not with the hosting:

```python
>>> import datasets
>>> dataset = datasets.load_dataset('cnn_dailymail', name="3.0.0", split="train", streaming=True, download_mode="force_redownload")
Downloading builder script: 9.35kB [00:00, 10.2MB/s]
Downloading metadata: 9.50kB [00:00, 12.2MB/s]
>>> len(list(dataset))
0
>>> dataset = datasets.load_dataset('cnn_dailymail', name="3.0.0", split="train", streaming=False)
Reusing dataset cnn_dailymail (/home/slesage/.cache/huggingface/datasets/cnn_dailymail/3.0.0/3.0.0/3cb851bf7cf5826e45d49db2863f627cba583cbc32342df7349dfe6c38060234)
>>> len(dataset)
287113
```

Note, in particular, that the streaming mode is failing silently, returning 0 row while I would have expected an exception instead. The result is that the dataset viewer shows `No data` instead of a detailed error.

<img width="1511" alt="Capture d’écran 2022-04-12 à 11 50 46" src="https://user-images.githubusercontent.com/1676121/162935341-d50f1e73-d053-41d4-917f-e79708a0ca23.png">


Well this is because the host (Google Drive) returns a document that is not the actual data, but an error page

Do you think that `datasets` should detect this anyway and throw an exception?

Yes it definitely should ! I don't have the bandwidth to work on this right now though

Indeed, streaming was not supported: tgz archives were not properly iterated.

I've opened a PR to support streaming.

However, keep in mind that Google Drive will keep generating issues from time to time, like 403,...