helmo/github-issues huggingface dataset:
Error "in void don't know how to serialize this type of index" when saving index to disk when device=0 (GPU)
State: closed | Author: corticalstack (NONE)

Error serializing faiss index.  Error as follows:

`Error in void faiss::write_index(const faiss::Index*, faiss::IOWriter*) at /home/conda/feedstock_root/build_artifacts/faiss-split_1612472484670/work/faiss/impl/index_write.cpp:453: don't know how to serialize this type of index`


Note:

`torch.cuda.is_available()` reports:

```
Cuda is available
cuda:0

```

Adding index, device=0 for GPU.

`dataset.add_faiss_index(column='embeddings', index_name='idx_embeddings', device=0)`

However, during a quick debug, self.faiss_index has no attr "device" when checked in` search.py, method save`, so fails to transform gpu index to cpu index.  If I add index without device, index is saved OK.


```
def save(self, file: str):
        """Serialize the FaissIndex on disk"""
        import faiss  # noqa: F811

        if (
            hasattr(self.faiss_index, "device")
            and self.faiss_index.device is not None
            and self.faiss_index.device > -1
        ):
            index = faiss.index_gpu_to_cpu(self.faiss_index)
        else:
            index = self.faiss_index
        faiss.write_index(index, file)
```


Comments: Hi @corticalstack ! Thanks for reporting. Indeed in the recent versions of Faiss we must use `getDevice` to check if the index in on GPU.

I'm opening a PR

I fixed this issue. It should work fine now.
Feel free to try it out by installing `datasets` from source.
Otherwise you can wait for the next release of `datasets` (in a few days)

Thanks for such a quick fix and merge to master, pip installed git master, tested all OK
Unable to upload "community provided" dataset - 400 Client Error
State: closed | Author: mwrzalik (NONE)

Hi,
i'm trying to a upload a dataset as described [here](https://huggingface.co/docs/datasets/v1.2.0/share_dataset.html#sharing-a-community-provided-dataset). This is what happens:

``` 
$ datasets-cli login
$ datasets-cli upload_dataset my_dataset
About to upload file /path/to/my_dataset/dataset_infos.json to S3 under filename my_dataset/dataset_infos.json and namespace username
About to upload file /path/to/my_dataset/my_dataset.py to S3 under filename my_dataset/my_dataset.py and namespace username
Proceed? [Y/n] Y
Uploading... This might take a while if files are large
400 Client Error: Bad Request for url: https://huggingface.co/api/datasets/presign
huggingface.co migrated to a new model hosting system.
You need to upgrade to transformers v3.5+ to upload new models.
More info at https://discuss.hugginface.co or https://twitter.com/julien_c. Thank you! 
```
I'm using the latest releases of datasets and transformers.

Comments: Hi ! We're in the process of switching the community datasets to git repos, exactly like what we're doing for models.
You can find an example here:
https://huggingface.co/datasets/lhoestq/custom_squad/tree/main

We'll update the CLI in the coming days and do a new release :)

Also cc @julien-c maybe we can make improve the error message ?
Feature Request: Dataset.add_item
State: closed | Author: sshleifer (CONTRIBUTOR)
Labels: name: enhancement

I'm trying to integrate `huggingface/datasets` functionality into `fairseq`, which requires (afaict) being able to build a dataset through an `add_item` method, such as https://github.com/pytorch/fairseq/blob/master/fairseq/data/indexed_dataset.py#L318, as opposed to loading all the text into arrow, and then `dataset.map(binarizer)`.
Is this possible at the moment? Is there an example? I'm happy to use raw `pa.Table` but not sure whether it will support uneven length entries.

### Desired API

```python
import numpy as np
tokenized: List[np.NDArray[np.int64]] = [np.array([4,4,2]), np.array([8,6,5,5,2]), np.array([3,3,31,5])

def build_dataset_from_tokenized(tokenized: List[np.NDArray[int]]) -> Dataset:
   """FIXME"""
   dataset = EmptyDataset()
   for t in tokenized: dataset.append(t)
   return dataset
ds = build_dataset_from_tokenized(tokenized)
assert (ds[0] == np.array([4,4,2])).all()
```

### What I tried
grep, google for "add one entry at a time", "datasets.append"

### Current Code
This code achieves the same result but doesn't fit into the `add_item` abstraction.

```python
    dataset = load_dataset('text', data_files={'train': 'train.txt'})
    tokenizer = RobertaTokenizerFast.from_pretrained('roberta-base', max_length=4096)
    def tokenize_function(examples):
        ids = tokenizer(examples['text'], return_attention_mask=False)['input_ids']
        return {'input_ids': [x[1:] for x in ids]}
    ds = dataset.map(tokenize_function, batched=True, num_proc=4, remove_columns=['text'], load_from_cache_file=not overwrite_cache)
	print(ds['train'][0]) => np array
```

Thanks in advance!

Comments: Hi @sshleifer.

I am not sure of understanding the need of the `add_item` approach...

By just reading your "Desired API" section, I would say you could (nearly) get it with a 1-column Dataset:
```python
data = {"input_ids": [np.array([4,4,2]), np.array([8,6,5,5,2]), np.array([3,3,31,5])]}
ds = Dataset.from_dict(data)
assert (ds["input_ids"][0] == np.array([4,4,2])).all()
```

Hi @sshleifer :) 

We don't have methods like `Dataset.add_batch` or `Dataset.add_entry/add_item` yet.
But that's something we'll add pretty soon. Would an API that looks roughly like this help ? Do you have suggestions ?
```python
import numpy as np
from datasets import Dataset

tokenized = [np.array([4,4,2]), np.array([8,6,5,5,2]), np.array([3,3,31,5])

# API suggestion (not available yet)
d = Dataset()
for input_ids in tokenized:
    d.add_item({"input_ids": input_ids})

print(d[0]["input_ids"])
# [4, 4, 2]
```

Currently you can define a dataset with what @albertvillanova suggest, or via a generator using dataset builders. It's also possible to [concatenate datasets](https://huggingface.co/docs/datasets/package_reference/main_classes.html?highlight=concatenate#datasets.concatenate_datasets).

Your API looks perfect @lhoestq, thanks!
Add cord 19 dataset
State: closed | Author: ggdupont (CONTRIBUTOR)

Initial version only reading the metadata in CSV.

### Checklist:
- [x] Create the dataset script /datasets/my_dataset/my_dataset.py using the template
- [x] Fill the _DESCRIPTION and _CITATION variables
- [x] Implement _infos(), _split_generators() and _generate_examples()
- [x] Make sure that the BUILDER_CONFIGS class attribute is filled with the different configurations of the dataset and that the BUILDER_CONFIG_CLASS is specified if there is a custom config class.
- [x] Generate the metadata file dataset_infos.json for all configurations
- [x] Generate the dummy data dummy_data.zip files to have the dataset script tested and that they don't weigh too much (<50KB)
- [x] Add the dataset card README.md using the template and at least fill the tags
- [x] Both tests for the real data and the dummy data pass.

### Extras:
- [x] add more metadata
- [x] add full text
- [x] add pre-computed document embedding

Comments: Cleaned-up version of previous PR: https://github.com/huggingface/datasets/pull/1129

@lhoestq FYI

Before merging I might tweak a little bit the dummy data to avoid having to check if the `document_parses` and `embeddings` directories exist or not. I'll do that later today

Looks all good now ! Thanks a lot @ggdupont :)
Merging
Add TIMIT
State: closed | Author: patrickvonplaten (CONTRIBUTOR)
Labels: name: dataset request

name: speech

## Adding a Dataset
- **Name:** *TIMIT*
- **Description:** *The TIMIT corpus of read speech has been designed to provide speech data for the acquisition of acoustic-phonetic knowledge and for the development and evaluation of automatic speech recognition systems*

- **Paper:** *Homepage*: http://groups.inf.ed.ac.uk/ami/corpus/ / *Wikipedia*: https://en.wikipedia.org/wiki/TIMIT
- **Data:** *https://deepai.org/dataset/timit*
- **Motivation:** Important speech dataset


If interested in tackling this issue, feel free to tag @patrickvonplaten


Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).


Comments: @patrickvonplaten Could you please help me with how the output text has to be represented in the data? TIMIT has Words, Phonemes and texts. Also has lot on info on the speaker and the dialect. Could you please help me? An example of how to arrange it would be super helpful!



Hey @vrindaprabhu - sure I'll help you :-) Could you open a first PR for TIMIT where you copy-paste more or less the `librispeech_asr` script: https://github.com/huggingface/datasets/blob/28be129db862ec89a87ac9349c64df6b6118aff4/datasets/librispeech_asr/librispeech_asr.py#L93 (obviously replacing all the naming and links correctly...) and then you can list all possible outputs in the features dict: https://github.com/huggingface/datasets/blob/28be129db862ec89a87ac9349c64df6b6118aff4/datasets/librispeech_asr/librispeech_asr.py#L104 (words, phonemes should probably be of kind `datasets.Sequence(datasets.Value("string"))` and texts I think should be of type `"text": datasets.Value("string")`.

When you've opened a first PR, I think it'll be much easier for us to take a look together :-) 

I am sorry! I created the PR [#1903](https://github.com/huggingface/datasets/pull/1903#). Requesting your comments! CircleCI tests are failing, will address them along with your comments!
[Metrics] Add word error metric metric
State: closed | Author: patrickvonplaten (CONTRIBUTOR)

This PR adds the word error rate metric to datasets. 
WER: https://en.wikipedia.org/wiki/Word_error_rate
for speech recognition. WER is the main metric used in ASR. 

`jiwer` seems to be a solid library (see https://github.com/asteroid-team/asteroid/pull/329#discussion_r525158939)

Comments: Feel free to merge once the CI is all green ;)
Make DownloadManager downloaded/extracted paths accessible
State: closed | Author: albertvillanova (MEMBER)

Make accessible the file paths downloaded/extracted by DownloadManager.

Close #1831.

The approach:
- I set these paths as DownloadManager attributes: these are DownloadManager's concerns
- To access to these from DatasetBuilder, I set the DownloadManager instance as DatasetBuilder attribute: object composition

Comments: First I was thinking of the dict, which makes sense for .download, mapping URL to downloaded path. However does this make sense for .extract, mapping the downloaded path to the extracted path? I ask this because the user did not chose the downloaded path, so this is completely unknown for them...

There could be several situations:
- download a file with no extraction
- download a file and extract it
- download a file, extract it and then inside the output folder extract some more files
- extract a local file (for datasets with data that are manually downloaded for example)
- extract a local file, and then inside the output folder extract some more files

So I think it's ok to have `downloaded_paths` as a dict url -> downloaded_path and `extracted_paths` as a dict local_path -> extracted_path.

OK. I am refactoring this. I have opened #1879, as an intermediate step...
Enable logging propagation and remove logging handler
State: closed | Author: lhoestq (MEMBER)

We used to have logging propagation disabled because of this issue: https://github.com/tensorflow/tensorflow/issues/26691
But since it's now fixed we should re-enable it. This is important to keep the default logging behavior for users, and propagation is also needed for pytest fixtures as asked in #1826 

I also removed the handler that was added since, according to the logging [documentation](https://docs.python.org/3/howto/logging.html#configuring-logging-for-a-library):
> It is strongly advised that you do not add any handlers other than NullHandler to your library’s loggers. This is because the configuration of handlers is the prerogative of the application developer who uses your library. The application developer knows their target audience and what handlers are most appropriate for their application: if you add handlers ‘under the hood’, you might well interfere with their ability to carry out unit tests and deliver logs which suit their requirements.

It could have been useful if we wanted to have a custom formatter for the logging but I think it's more important to keep the logging as default to not interfere with the users' logging management.

Therefore I also removed the two methods `datasets.logging.enable_default_handler` and `datasets.logging.disable_default_handler`.

cc @albertvillanova this should let you use capsys/caplog in pytest
cc @LysandreJik @sgugger if you want to do the same in `transformers`

Comments: Thank you @lhoestq. This logging configuration makes more sense to me.

Once propagation is allowed, the end-user can customize logging behavior and add custom handlers to the proper top logger in the hierarchy.

And I also agree with following the best practices and removing any custom handlers:
- it is the end user who has to implement any custom handlers
- indeed, the previous logging problem with TensorFlow was due to the fact that absl did not follow best practices and had implemented a custom handler

Our errors/warnings will be displayed anyway, even if we do not implement any custom handler. Since Python 3.2, logging has a built-in "default" handler (logging.lastResort) with the expected default behavior (sending error/warning messages to sys.stderr), which is used only if the end user has not configured any custom handler.
Add AMI Corpus
State: closed | Author: patrickvonplaten (CONTRIBUTOR)
Labels: name: dataset request

name: speech

## Adding a Dataset
- **Name:** *AMI*
- **Description:** *The AMI Meeting Corpus is a multi-modal data set consisting of 100 hours of meeting recordings. For a gentle introduction to the corpus, see the corpus overview. To access the data, follow the directions given there. Around two-thirds of the data has been elicited using a scenario in which the participants play different roles in a design team, taking a design project from kick-off to completion over the course of a day. The rest consists of naturally occurring meetings in a range of domains. Detailed information can be found in the documentation section.*

- **Paper:** *Homepage*: http://groups.inf.ed.ac.uk/ami/corpus/
- **Data:** *http://groups.inf.ed.ac.uk/ami/download/* - Select all cases in 1) and select "Individual Headsets" & "Microphone array" for 2)
- **Motivation:** Important speech dataset


If interested in tackling this issue, feel free to tag @patrickvonplaten


Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).


Comments: Available here: ~https://huggingface.co/datasets/ami~ https://huggingface.co/datasets/edinburghcstr/ami

@mariosasko actually the "official" AMI dataset can be found here: https://huggingface.co/datasets/edinburghcstr/ami -> the old one under `datasets/ami` doesn't work and should be deleted. 

The new one was tested by fine-tuning a Wav2Vec2 model on it + we uploaded all the processed audio directly into it

@patrickvonplaten Thanks for correcting me! I've updated the link.
Add ljspeech
State: closed | Author: patrickvonplaten (CONTRIBUTOR)
Labels: name: dataset request

name: speech

## Adding a Dataset
- **Name:** *ljspeech*
- **Description:** *This is a public domain speech dataset consisting of 13,100 short audio clips of a single speaker reading passages from 7 non-fiction books. A transcription is provided for each clip. Clips vary in length from 1 to 10 seconds and have a total length of approximately 24 hours.

The texts were published between 1884 and 1964, and are in the public domain. The audio was recorded in 2016-17 by the LibriVox project and is also in the public domain.)*
- **Paper:** *Homepage*: https://keithito.com/LJ-Speech-Dataset/
- **Data:** *https://keithito.com/LJ-Speech-Dataset/*
- **Motivation:** Important speech dataset
- **TFDatasets Implementation**: https://www.tensorflow.org/datasets/catalog/ljspeech
If interested in tackling this issue, feel free to tag @patrickvonplaten


Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
Add common voice
State: closed | Author: patrickvonplaten (CONTRIBUTOR)
Labels: name: dataset request

name: speech

## Adding a Dataset
- **Name:** *common voice*
- **Description:** *Mozilla Common Voice Dataset*
- **Paper:** Homepage: https://voice.mozilla.org/en/datasets
- **Data:** https://voice.mozilla.org/en/datasets
- **Motivation:** Important speech dataset
- **TFDatasets Implementation**: https://www.tensorflow.org/datasets/catalog/common_voice
If interested in tackling this issue, feel free to tag @patrickvonplaten

Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).


Comments: I have started working on adding this dataset.

Hey @BirgerMoell - awesome that you started working on Common Voice. Common Voice is a bit special since, there is no direct download link to download the data. In these cases we usually consider two options:

1) Find a hacky solution to extract the download link somehow from the XLM tree of the website 
2) If this doesn't work we force the user to download the data himself and add a `"data_dir"` as an input parameter. E.g. you can take a look at how it is done for [this](https://github.com/huggingface/datasets/blob/66f2a7eece98d2778bd22bb5034cb7c2376032d4/datasets/arxiv_dataset/arxiv_dataset.py#L66) 

Also the documentation here: https://huggingface.co/docs/datasets/add_dataset.html?highlight=data_dir#downloading-data-files-and-organizing-splits (especially the "note") might be helpful.

Let me know if you have any other questions

I added a Work in Progress pull request (hope that is ok). I've made a card for the dataset and filled out the common_voice.py file with information about the datset (not completely).

I didn't manage to get the tagging tool working locally on my machine but will look into that later.

Left to do.

- Tag the dataset
- Add missing information and update common_voice.py

https://github.com/huggingface/datasets/pull/1886

Awesome! I left a longer comment on the PR :-)

I saw that this current datasets package holds common voice version 6.1, how to add the new version 7.0 that is already available?

Will me merged next week - we're working on it :-)

Common voice still appears to be a 6.1. Is the plan still to upgrade to 7.0?

We actually already have the code and everything ready to add Common Voice 7.0 to `datasets` but are still waiting for the common voice authors to give us the green light :-) 

Also gently pinging @phirework and @milupo here

Common Voice 7.0 is available here now: https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0

For anyone else stumbling upon this thread, the 8.0 version is also available now: https://huggingface.co/datasets/mozilla-foundation/common_voice_8_0
Add Voxforge
State: open | Author: patrickvonplaten (CONTRIBUTOR)
Labels: name: dataset request

name: speech

## Adding a Dataset
- **Name:** *voxforge* 
- **Description:** *VoxForge is a language classification dataset. It consists of user submitted audio clips submitted to the website. In this release, data from 6 languages is collected - English, Spanish, French, German, Russian, and Italian. Since the website is constantly updated, and for the sake of reproducibility, this release contains only recordings submitted prior to 2020-01-01. The samples are splitted between train, validation and testing so that samples from each speaker belongs to exactly one split.*
- **Paper:** *Homepage*: http://www.voxforge.org/
- **Data:** *http://www.voxforge.org/home/downloads*
- **Motivation:** Important speech dataset
- **TFDatasets Implementation**: https://www.tensorflow.org/datasets/catalog/voxforge
If interested in tackling this issue, feel free to tag @patrickvonplaten

Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
Add tedlium
State: closed | Author: patrickvonplaten (CONTRIBUTOR)
Labels: name: dataset request

name: speech

## Adding a Dataset
- **Name:** *tedlium*
- **Description:** *The TED-LIUM 1-3 corpus is English-language TED talks, with transcriptions, sampled at 16kHz. It contains about 118 hours of speech.*
- **Paper:** Homepage: http://www.openslr.org/7/, https://lium.univ-lemans.fr/en/ted-lium2/ &, https://www.openslr.org/51/
- **Data:** http://www.openslr.org/7/
- **Motivation:** Important speech dataset
- **TFDatasets Implementation**: https://www.tensorflow.org/datasets/catalog/tedlium
If interested in tackling this issue, feel free to tag @patrickvonplaten

Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).


Comments: Hi @patrickvonplaten 
I can have a look to this dataset later since I am trying to add the OpenSLR dataset https://github.com/huggingface/datasets/pull/2173
Hopefully I have enough space since the compressed file is 21GB. The release 3 is even bigger: 54GB :-0

Resolved via https://github.com/huggingface/datasets/pull/4309
Add VCTK
State: closed | Author: patrickvonplaten (CONTRIBUTOR)
Labels: name: dataset request

name: speech

## Adding a Dataset
- **Name:** *VCTK*
- **Description:** *This CSTR VCTK Corpus includes speech data uttered by 110 English speakers with various accents. Each speaker reads out about 400 sentences, which were selected from a newspaper, the rainbow passage and an elicitation paragraph used for the speech accent archive.*
- **Paper:** Homepage: https://datashare.ed.ac.uk/handle/10283/3443
- **Data:** https://datashare.ed.ac.uk/handle/10283/3443
- **Motivation:** Important speech dataset
- **TFDatasets Implementation**: https://www.tensorflow.org/datasets/catalog/vctk

If interested in tackling this issue, feel free to tag @patrickvonplaten

Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).


Comments: @patrickvonplaten I'd like to take this, if nobody has already done it. I have added datasets before through the datasets sprint, but I feel rusty on the details, so I'll look at the guide as well as similar audio PRs (#1878 in particular comes to mind). If there is any detail I should be aware of please, let me know! Otherwise, I'll try to write up a PR in the coming days.

That sounds great @jaketae - let me know if you need any help i.e. feel free to ping me on a first PR :-)
test.json has been removed from the limit dataset repo (breaks dataset)
State: closed | Author: Paethon (NONE)
Labels: name: dataset bug

https://github.com/huggingface/datasets/blob/16042b233dbff2a7585110134e969204c69322c3/datasets/limit/limit.py#L51

The URL is not valid anymore since test.json has been removed in master for some reason. Directly referencing the last commit works:

`https://raw.githubusercontent.com/ilmgut/limit_dataset/0707d3989cd8848f0f11527c77dcf168fefd2b23/data`

Comments: Thanks for the heads up ! I'm opening a PR to fix that