kardwalker/my_dataset huggingface dataset:
GitHub issue #1703: Improvements regarding caching and fingerprinting
State: closed | Created: 2021-01-07T15:26:29Z

This PR adds these features:
- Enable/disable caching
    If disabled, the library will no longer reload cached datasets files when applying transforms to the datasets.
    It is equivalent to setting `load_from_cache` to `False` in dataset transforms.
```python
from datasets import set_caching_enabled

set_caching_enabled(False)
```
- Allow unpicklable functions in `map`
    If an unpicklable function is used, then it's not possible to hash it to update the dataset fingerprint that is used to name cache files. To workaround that, a random fingerprint is generated instead and a warning is raised.
```python
logger.warning(
    f"Transform {transform} couldn't be hashed properly, a random hash was used instead. "
    "Make sure your transforms and parameters are serializable with pickle or dill for the dataset fingerprinting and caching to work. "
    "If you reuse this transform, the caching mechanism will consider it to be different from the previous calls and recompute everything."
)
```

and also (open to discussion, EDIT: actually NOT included):
- Enable/disable fingerprinting
    Fingerprinting allows to have one deterministic fingerprint per dataset state.
    A dataset fingerprint is updated after each transform.
    Re-running the same transforms on a dataset in a different session results in the same fingerprint.
    Disabling the fingerprinting mechanism makes all the fingerprints random.
    Since the caching mechanism uses fingerprints to name the cache files, then cache file names will be different.
    Therefore disabling fingerprinting will prevent the caching mechanism from reloading datasets files that have already been computed.
    Disabling fingerprinting may speed up the lib for users that don't care about this feature and don't want to use caching.
```python
from datasets import set_fingerprinting_enabled

set_fingerprinting_enabled(False)
```

Other details:
- I renamed the `fingerprint` decorator to `fingerprint_transform` since the name was clearly not explicit. This decorator is used on dataset transform functions to allow them to update fingerprints.
- I added some `ignore_kwargs` when decorating transforms with `fingerprint_transform`, to make the fingerprint update not sensible to kwargs like `load_from_cache` or `cache_file_name`.

Todo: tests for set_fingerprinting_enabled + documentation for all the above features
GitHub issue #1701: Some datasets miss dataset_infos.json or dummy_data.zip
State: closed | Created: 2021-01-07T14:17:13Z

While working on dataset REAME generation script at https://github.com/madlag/datasets_readme_generator , I noticed that some datasets miss a dataset_infos.json : 

```
c4
lm1b
reclor
wikihow
```

And some does not have a dummy_data.zip : 

```
kor_nli
math_dataset
mlqa
ms_marco
newsgroup
qa4mre
qangaroo
reddit_tifu
super_glue
trivia_qa
web_of_science
wmt14
wmt15
wmt16
wmt17
wmt18
wmt19
xtreme
```

But it seems that some of those last do have a "dummy" directory .
GitHub issue #1699: Update DBRD dataset card and download URL
State: closed | Created: 2021-01-07T12:16:43Z

I've added the Dutch Bood Review Dataset (DBRD) during the recent sprint. This pull request makes two minor changes:

1.  I'm changing the download URL from Google Drive to the dataset's GitHub release package. This is now possible because of PR #1316.
2. I've updated the dataset card.

Cheers! 😄
GitHub issue #1694: Add OSCAR
State: closed | Created: 2021-01-06T10:21:08Z

Continuation of #348 
The files have been moved to S3 and only the unshuffled version is available.
Both original and deduplicated versions of each language are available.

Example of usage:
```python
from datasets import load_dataset

oscar_dedup_en = load_dataset("oscar", "unshuffled_deduplicated_en", split="train")
oscar_orig_fr = load_dataset("oscar", "unshuffled_original_fr", split="train")
```

cc @pjox @jonatasgrosman 

-------------

To make the metadata generation work in parallel I did a few changes in the `datasets-cli test` command to add the `num_proc` and `proc_rank` arguments. This way you can run multiple processes for the metadata computation.

```
datasets-cli test ./datasets/oscar --save_infos --all_configs --num_proc 4 --proc_rank 0 --clear_cache --cache_dir tmp0
```

-------------

ToDo: add the dummy_data
GitHub issue #1691: Updated HuggingFace Datasets README (fix typos)
State: closed | Created: 2021-01-06T02:14:38Z

Awesome work on 🤗 Datasets. I found a couple of small typos in the README. Hope this helps.



![](https://emojipedia-us.s3.dualstack.us-west-1.amazonaws.com/thumbs/160/google/56/hugging-face_1f917.png)
GitHub issue #1690: Fast start up
State: closed | Created: 2021-01-05T19:07:53Z

Currently if optional dependencies such as tensorflow, torch, apache_beam, faiss and elasticsearch are installed, then it takes a long time to do `import datasets` since it imports all of these heavy dependencies.

To make a fast start up for `datasets` I changed that so that they are not imported when `datasets` is being imported. On my side it changed the import time of `datasets` from 5sec to 0.5sec, which is enjoyable.

To be able to check if optional dependencies are available without importing them I'm using `importlib_metadata`, which is part of the standard lib in python>=3.8 and was backported. The difference with `importlib` is that it also enables to get the versions of the libraries without importing them.
I added this dependency in `setup.py`.
GitHub issue #1689: Fix ade_corpus_v2 config names
State: closed | Created: 2021-01-05T14:33:28Z

There are currently some typos in the config names of the `ade_corpus_v2` dataset, I fixed them:

- Ade_corpos_v2_classificaion -> Ade_corpus_v2_classification
- Ade_corpos_v2_drug_ade_relation -> Ade_corpus_v2_drug_ade_relation
- Ade_corpos_v2_drug_dosage_relation -> Ade_corpus_v2_drug_dosage_relation
GitHub issue #1687: Question: Shouldn't .info be a part of DatasetDict?
State: open | Created: 2021-01-05T13:08:41Z

Currently, only `Dataset` contains the .info or .features, but as many datasets contains standard splits (train, test) and thus the underlying information is the same (or at least should be) across the datasets. 

For instance:
```
>>> ds = datasets.load_dataset("conll2002", "es")
>>> ds.info
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
AttributeError: 'DatasetDict' object has no attribute 'info'
```

I could imagine that this wouldn't work for datasets dicts which hold entirely different datasets (multimodal datasets), but it seems odd that splits of the same dataset is treated the same as what is essentially different datasets. 

Intuitively it would also make sense that if a dataset is supplied via. the load_dataset that is have a common .info which covers the entire dataset.

It is entirely possible that I am missing another perspective
GitHub issue #1686: Dataset Error: DaNE contains empty samples at the end
State: closed | Created: 2021-01-05T11:54:26Z

The dataset DaNE, contains empty samples at the end. It is naturally easy to remove using a filter but should probably not be there, to begin with as it can cause errors.

```python
>>> import datasets
[...]
>>> dataset = datasets.load_dataset("dane")
[...]
>>> dataset["test"][-1]
{'dep_ids': [], 'dep_labels': [], 'lemmas': [], 'morph_tags': [], 'ner_tags': [], 'pos_tags': [], 'sent_id': '', 'text': '', 'tok_ids': [], 'tokens': []}
>>> dataset["train"][-1]
{'dep_ids': [], 'dep_labels': [], 'lemmas': [], 'morph_tags': [], 'ner_tags': [], 'pos_tags': [], 'sent_id': '', 'text': '', 'tok_ids': [], 'tokens': []}
```

Best,
Kenneth
GitHub issue #1685: Update README.md of covid-tweets-japanese
State: closed | Created: 2021-01-05T11:47:27Z

Update README.md of covid-tweets-japanese added by PR https://github.com/huggingface/datasets/pull/1367 and https://github.com/huggingface/datasets/pull/1402.

- Update "Data Splits" to be more precise that no information is provided for now.
  - old: [More Information Needed]
  - new: No information about data splits is provided for now.

- The automatic generation of links seemed not working properly, so I added a space before and after the URL to make the links work correctly.
GitHub issue #1682: Don't use xlrd for xlsx files
State: closed | Created: 2021-01-04T18:11:50Z

Since the latest release of `xlrd` (2.0), the support for xlsx files stopped.
Therefore we needed to use something else.
A good alternative is `openpyxl` which has also an integration with pandas si we can still call `pd.read_excel`.

I left the unused import of `openpyxl` in the dataset scripts to show users that this is a required dependency to use the scripts.

I tested the different datasets using `datasets-cli test` and the tests are successful (no missing examples).
GitHub issue #1681: Dataset "dane" missing
State: closed | Created: 2021-01-03T14:03:03Z

the `dane` dataset appear to be missing in the latest version (1.1.3).

```python
>>> import datasets
>>> datasets.__version__
'1.1.3'
>>> "dane" in datasets.list_datasets()
True
```

As we can see it should be present, but doesn't seem to be findable when using `load_dataset`.

```python
>>> datasets.load_dataset("dane")
Traceback (most recent call last):
  File "/home/kenneth/.Envs/EDP/lib/python3.8/site-packages/datasets/load.py", line 267, in prepare_module
    local_path = cached_path(file_path, download_config=download_config)
  File "/home/kenneth/.Envs/EDP/lib/python3.8/site-packages/datasets/utils/file_utils.py", line 300, in cached_path
    output_path = get_from_cache(
  File "/home/kenneth/.Envs/EDP/lib/python3.8/site-packages/datasets/utils/file_utils.py", line 486, in get_from_cache
    raise FileNotFoundError("Couldn't find file at {}".format(url))
FileNotFoundError: Couldn't find file at https://raw.githubusercontent.com/huggingface/datasets/1.1.3/datasets/dane/dane.py

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/home/kenneth/.Envs/EDP/lib/python3.8/site-packages/datasets/load.py", line 278, in prepare_module
    local_path = cached_path(file_path, download_config=download_config)
  File "/home/kenneth/.Envs/EDP/lib/python3.8/site-packages/datasets/utils/file_utils.py", line 300, in cached_path
    output_path = get_from_cache(
  File "/home/kenneth/.Envs/EDP/lib/python3.8/site-packages/datasets/utils/file_utils.py", line 486, in get_from_cache
    raise FileNotFoundError("Couldn't find file at {}".format(url))
FileNotFoundError: Couldn't find file at https://s3.amazonaws.com/datasets.huggingface.co/datasets/datasets/dane/dane.py

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/home/kenneth/.Envs/EDP/lib/python3.8/site-packages/datasets/load.py", line 588, in load_dataset
    module_path, hash = prepare_module(
  File "/home/kenneth/.Envs/EDP/lib/python3.8/site-packages/datasets/load.py", line 280, in prepare_module
    raise FileNotFoundError(
FileNotFoundError: Couldn't find file locally at dane/dane.py, or remotely at https://raw.githubusercontent.com/huggingface/datasets/1.1.3/datasets/dane/dane.py or https://s3.amazonaws.com/datasets.huggingface.co/datasets/datasets/dane/dane.py
```

This issue might be relevant to @ophelielacroix from the Alexandra Institut whom created the data.
GitHub issue #1680: added TurkishProductReviews dataset
State: closed | Created: 2021-01-03T11:52:59Z

This PR added **Turkish Product Reviews Dataset contains 235.165 product reviews collected online. There are 220.284 positive, 14881 negative reviews**.

- **Repository:** [turkish-text-data](https://github.com/fthbrmnby/turkish-text-data)
- **Point of Contact:** Fatih Barmanbay - @fthbrmnby
GitHub issue #1679: Can't import cc100 dataset
State: closed | Created: 2021-01-03T07:12:56Z

There is some issue to import cc100 dataset.

```
from datasets import load_dataset
dataset = load_dataset("cc100")
```

FileNotFoundError: Couldn't find file at https://raw.githubusercontent.com/huggingface/datasets/1.1.3/datasets/cc100/cc100.py

During handling of the above exception, another exception occurred:

FileNotFoundError                         Traceback (most recent call last)
FileNotFoundError: Couldn't find file at https://s3.amazonaws.com/datasets.huggingface.co/datasets/datasets/cc100/cc100.py

During handling of the above exception, another exception occurred:

FileNotFoundError                         Traceback (most recent call last)
/usr/local/lib/python3.6/dist-packages/datasets/load.py in prepare_module(path, script_version, download_config, download_mode, dataset, force_local_path, **download_kwargs)
    280                 raise FileNotFoundError(
    281                     "Couldn't find file locally at {}, or remotely at {} or {}".format(
--> 282                         combined_path, github_file_path, file_path
    283                     )
    284                 )

FileNotFoundError: Couldn't find file locally at cc100/cc100.py, or remotely at https://raw.githubusercontent.com/huggingface/datasets/1.1.3/datasets/cc100/cc100.py or https://s3.amazonaws.com/datasets.huggingface.co/datasets/datasets/cc100/cc100.py
GitHub issue #1678: Switchboard Dialog Act Corpus added under `datasets/swda`
State: closed | Created: 2021-01-03T03:53:41Z

Switchboard Dialog Act Corpus

Intro:
The Switchboard Dialog Act Corpus (SwDA) extends the Switchboard-1 Telephone Speech Corpus, Release 2,
with turn/utterance-level dialog-act tags. The tags summarize syntactic, semantic, and pragmatic information
about the associated turn. The SwDA project was undertaken at UC Boulder in the late 1990s.

Details:
[homepage](http://compprag.christopherpotts.net/swda.html)
[repo](https://github.com/NathanDuran/Switchboard-Corpus/raw/master/swda_data/)

I believe this is an important dataset to have since there is no dataset related to dialogue act added.

I didn't find any formatting for pull request. I hope all this information is enough.

For any support please contact me.
GitHub issue #1677: Switchboard Dialog Act Corpus added under `datasets/swda`
State: closed | Created: 2021-01-03T01:16:42Z

Pleased to announced that I added my first dataset **Switchboard Dialog Act Corpus**.


I think this is an important datasets to be added since it is the only one related to dialogue act classification. 

Hope the pull request is ok. Wasn't able to see any special formatting for the pull request form.


The Switchboard Dialog Act Corpus (SwDA) extends the Switchboard-1 Telephone Speech Corpus, Release 2,
with turn/utterance-level dialog-act tags. The tags summarize syntactic, semantic, and pragmatic information
about the associated turn. The SwDA project was undertaken at UC Boulder in the late 1990s.


[webpage](http://compprag.christopherpotts.net/swda.html)

[repo](https://github.com/NathanDuran/Switchboard-Corpus/raw/master/swda_data/)

Please contact me for any support!

All tests passed and followed all steps in the contribution guide!
GitHub issue #1676: new version of Ted Talks IWSLT (WIT3)
State: closed | Created: 2021-01-02T15:30:03Z

In the previous iteration #1608 I had used language pairs. Which created 21,582 configs (109*108) !!! 

Now, TED talks in _each language_ is a separate config. So it's more cleaner with _just 109 configs_  (one for each language). Dummy files were created manually. 

Locally  I was able to clear the `python datasets-cli test datasets/......` . Which created the `dataset_info.json`  file . The test for the dummy files was also cleared. However couldn't figure out how to specify the local data folder for the real dataset


**Note: that this requires manual download of the dataset.** 
**Note2: The high number of _Files changed (112)_ is because of the large number of dummy files/configs!**
GitHub issue #1675: Add the 800GB Pile dataset?
State: closed | Created: 2021-01-01T22:58:12Z

## Adding a Dataset
- **Name:** The Pile
- **Description:** The Pile is a 825 GiB diverse, open source language modelling data set that consists of 22 smaller, high-quality datasets combined together. See [here](https://twitter.com/nabla_theta/status/1345130408170541056?s=20) for the Twitter announcement
- **Paper:** https://pile.eleuther.ai/paper.pdf
- **Data:** https://pile.eleuther.ai/
- **Motivation:** Enables hardcore  (GPT-3 scale!) language modelling

## Remarks
Given the extreme size of this dataset, I'm not sure how feasible this will be to include in `datasets` 🤯  . I'm also unsure how many `datasets` users are pretraining LMs, so the usage of this dataset may not warrant the effort to integrate it.
GitHub issue #1674: dutch_social can't be loaded
State: closed | Created: 2021-01-01T17:37:08Z

Hi all,

I'm trying to import the `dutch_social` dataset described [here](https://huggingface.co/datasets/dutch_social).

However, the code that should load the data doesn't seem to be working, in particular because the corresponding files can't be found at the provided links.

```
(base) Koens-MacBook-Pro:~ koenvandenberge$ python
Python 3.7.4 (default, Aug 13 2019, 15:17:50) 
[Clang 4.0.1 (tags/RELEASE_401/final)] :: Anaconda, Inc. on darwin
Type "help", "copyright", "credits" or "license" for more information.
>>> from datasets import load_dataset
dataset = load_dataset(
   'dutch_social')
>>> dataset = load_dataset(
...    'dutch_social')
Traceback (most recent call last):
  File "/Users/koenvandenberge/opt/anaconda3/lib/python3.7/site-packages/datasets/load.py", line 267, in prepare_module
    local_path = cached_path(file_path, download_config=download_config)
  File "/Users/koenvandenberge/opt/anaconda3/lib/python3.7/site-packages/datasets/utils/file_utils.py", line 308, in cached_path
    use_etag=download_config.use_etag,
  File "/Users/koenvandenberge/opt/anaconda3/lib/python3.7/site-packages/datasets/utils/file_utils.py", line 486, in get_from_cache
    raise FileNotFoundError("Couldn't find file at {}".format(url))
FileNotFoundError: Couldn't find file at https://raw.githubusercontent.com/huggingface/datasets/1.1.3/datasets/dutch_social/dutch_social.py

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/Users/koenvandenberge/opt/anaconda3/lib/python3.7/site-packages/datasets/load.py", line 278, in prepare_module
    local_path = cached_path(file_path, download_config=download_config)
  File "/Users/koenvandenberge/opt/anaconda3/lib/python3.7/site-packages/datasets/utils/file_utils.py", line 308, in cached_path
    use_etag=download_config.use_etag,
  File "/Users/koenvandenberge/opt/anaconda3/lib/python3.7/site-packages/datasets/utils/file_utils.py", line 486, in get_from_cache
    raise FileNotFoundError("Couldn't find file at {}".format(url))
FileNotFoundError: Couldn't find file at https://s3.amazonaws.com/datasets.huggingface.co/datasets/datasets/dutch_social/dutch_social.py

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "<stdin>", line 2, in <module>
  File "/Users/koenvandenberge/opt/anaconda3/lib/python3.7/site-packages/datasets/load.py", line 589, in load_dataset
    path, script_version=script_version, download_config=download_config, download_mode=download_mode, dataset=True
  File "/Users/koenvandenberge/opt/anaconda3/lib/python3.7/site-packages/datasets/load.py", line 282, in prepare_module
    combined_path, github_file_path, file_path
FileNotFoundError: Couldn't find file locally at dutch_social/dutch_social.py, or remotely at https://raw.githubusercontent.com/huggingface/datasets/1.1.3/datasets/dutch_social/dutch_social.py or https://s3.amazonaws.com/datasets.huggingface.co/datasets/datasets/dutch_social/dutch_social.py
```
GitHub issue #1673: Unable to Download Hindi Wikipedia Dataset
State: closed | Created: 2021-01-01T10:52:53Z

I used the Dataset Library in Python to load the wikipedia dataset with the Hindi Config 20200501.hi along with something called beam_runner='DirectRunner' and it keeps giving me the error that the file is not found. I have attached the screenshot of the error and the code both. Please help me to understand how to resolve this issue.

![Code](https://user-images.githubusercontent.com/30871963/103437466-1f3a3300-4c4e-11eb-9d54-fc9601abfeec.png)

![Error](https://user-images.githubusercontent.com/30871963/103437407-7ee40e80-4c4d-11eb-8151-a86eb664e6be.png)
GitHub issue #1672: load_dataset hang on file_lock
State: closed | Created: 2021-01-01T10:25:07Z

I am trying to load the squad dataset. Fails on Windows 10 but succeeds in Colab.
Transformers:  3.3.1
Datasets:  1.0.2
Windows 10 (also tested in WSL)

```
datasets.logging.set_verbosity_debug()
datasets.
train_dataset = load_dataset('squad', split='train')
valid_dataset = load_dataset('squad', split='validation')

train_dataset.features
```

```
https://raw.githubusercontent.com/huggingface/datasets/1.0.2/datasets/squad/squad.py not found in cache or force_download set to True, downloading to C:\Users\simpl\.cache\huggingface\datasets\tmpzj_o_6u7
Downloading:
5.24k/? [00:00<00:00, 134kB/s]
storing https://raw.githubusercontent.com/huggingface/datasets/1.0.2/datasets/squad/squad.py in cache at C:\Users\simpl\.cache\huggingface\datasets\f6877c8d2e01e8fcb60dc101be28b54a7522feac756deb9ac5c39c6d8ebef1ce.85f43de978b9b25921cb78d7a2f2b350c04acdbaedb9ecb5f7101cd7c0950e68.py
creating metadata file for C:\Users\simpl\.cache\huggingface\datasets\f6877c8d2e01e8fcb60dc101be28b54a7522feac756deb9ac5c39c6d8ebef1ce.85f43de978b9b25921cb78d7a2f2b350c04acdbaedb9ecb5f7101cd7c0950e68.py

Checking C:\Users\simpl\.cache\huggingface\datasets\f6877c8d2e01e8fcb60dc101be28b54a7522feac756deb9ac5c39c6d8ebef1ce.85f43de978b9b25921cb78d7a2f2b350c04acdbaedb9ecb5f7101cd7c0950e68.py for additional imports.
Found main folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.0.2/datasets/squad/squad.py at C:\Users\simpl\.cache\huggingface\modules\datasets_modules\datasets\squad
Found specific version folder for dataset https://raw.githubusercontent.com/huggingface/datasets/1.0.2/datasets/squad/squad.py at C:\Users\simpl\.cache\huggingface\modules\datasets_modules\datasets\squad\1244d044b266a5e4dbd4174d23cb995eead372fbca31a03edc3f8a132787af41
Found script file from https://raw.githubusercontent.com/huggingface/datasets/1.0.2/datasets/squad/squad.py to C:\Users\simpl\.cache\huggingface\modules\datasets_modules\datasets\squad\1244d044b266a5e4dbd4174d23cb995eead372fbca31a03edc3f8a132787af41\squad.py
Couldn't find dataset infos file at https://raw.githubusercontent.com/huggingface/datasets/1.0.2/datasets/squad\dataset_infos.json
Found metadata file for dataset https://raw.githubusercontent.com/huggingface/datasets/1.0.2/datasets/squad/squad.py at C:\Users\simpl\.cache\huggingface\modules\datasets_modules\datasets\squad\1244d044b266a5e4dbd4174d23cb995eead372fbca31a03edc3f8a132787af41\squad.json
No config specified, defaulting to first: squad/plain_text
```

Interrupting the jupyter kernel we are in a file lock.

In Google Colab the download is ok. In contrast to a local run in colab dataset_infos.json is downloaded
```
https://raw.githubusercontent.com/huggingface/datasets/1.0.2/datasets/squad/dataset_infos.json not found in cache or force_download set to True, downloading to /root/.cache/huggingface/datasets/tmptl9ha_ad

Downloading:
2.19k/? [00:00<00:00, 26.2kB/s]
```
GitHub issue #1670: wiki_dpr pre-processing performance
State: open | Created: 2020-12-30T19:41:43Z

I've been working with wiki_dpr and noticed that the dataset processing is seriously impaired in performance [1]. It takes about 12h to process the entire dataset. Most of this time is simply loading and processing the data, but the actual indexing is also quite slow (3h).

I won't repeat the concerns around multiprocessing as they are addressed in other issues (#786), but this is the first obvious thing to do. Using cython to speed up the text manipulation may be also help. Loading and processing a dataset of this size in under 15 minutes does not seem unreasonable on a modern multi-core machine. I have hit such targets myself on similar tasks. Would love to see this improve.

The other issue is that it takes 3h to construct the FAISS index. If only we could use GPUs with HNSW, but we can't. My sharded GPU indexing code can build an IVF + PQ index in 10 minutes on 20 million vectors. Still, 3h seems slow even for the CPU.

It looks like HF is adding only 1000 vectors at a time by default [2], whereas the faiss benchmarks adds 1 million vectors at a time (effectively) [3]. It's possible the runtime could be reduced with a larger batch. Also, it looks like project dependencies ultimately use OpenBLAS, but this is known to have issues when combined with OpenMP, which HNSW does [3]. A workaround is to set the environment variable `OMP_WAIT_POLICY=PASSIVE` via `os.environ` or similar.

References:
[1] https://github.com/huggingface/datasets/blob/master/datasets/wiki_dpr/wiki_dpr.py
[2] https://github.com/huggingface/datasets/blob/master/src/datasets/search.py
[3] https://github.com/facebookresearch/faiss/blob/master/benchs/bench_hnsw.py
[4] https://github.com/facebookresearch/faiss/issues/422
GitHub issue #1669: wiki_dpr dataset pre-processesing performance
State: closed | Created: 2020-12-30T19:41:09Z

I've been working with wiki_dpr and noticed that the dataset processing is seriously impaired in performance [1]. It takes about 12h to process the entire dataset. Most of this time is simply loading and processing the data, but the actual indexing is also quite slow (3h).

I won't repeat the concerns around multiprocessing as they are addressed in other issues (#786), but this is the first obvious thing to do. Using cython to speed up the text manipulation may be also help. Loading and processing a dataset of this size in under 15 minutes does not seem unreasonable on a modern multi-core machine. I have hit such targets myself on similar tasks. Would love to see this improve.

The other issue is that it takes 3h to construct the FAISS index. If only we could use GPUs with HNSW, but we can't. My sharded GPU indexing code can build an IVF + PQ index in 10 minutes on 20 million vectors. Still, 3h seems slow even for the CPU.

It looks like HF is adding only 1000 vectors at a time by default [2], whereas the faiss benchmarks adds 1 million vectors at a time (effectively) [3]. It's possible the runtime could be reduced with a larger batch. Also, it looks like project dependencies ultimately use OpenBLAS, but this is known to have issues when combined with OpenMP, which HNSW does [3]. A workaround is to set the environment variable `OMP_WAIT_POLICY=PASSIVE` via `os.environ` or similar.

References:
[1] https://github.com/huggingface/datasets/blob/master/datasets/wiki_dpr/wiki_dpr.py
[2] https://github.com/huggingface/datasets/blob/master/src/datasets/search.py
[3] https://github.com/facebookresearch/faiss/blob/master/benchs/bench_hnsw.py
[4] https://github.com/facebookresearch/faiss/issues/422
GitHub issue #1667: Fix NER metric example in Overview notebook
State: closed | Created: 2020-12-30T13:05:19Z

Fix errors in `NER metric example` section in `Overview.ipynb`.

```
---------------------------------------------------------------------------
ImportError                               Traceback (most recent call last)
<ipython-input-37-ee559b166e25> in <module>()
----> 1 ner_metric = load_metric('seqeval')
      2 references = [['O', 'O', 'O', 'B-MISC', 'I-MISC', 'I-MISC', 'O'], ['B-PER', 'I-PER', 'O']]
      3 predictions =  [['O', 'O', 'B-MISC', 'I-MISC', 'I-MISC', 'I-MISC', 'O'], ['B-PER', 'I-PER', 'O']]
      4 ner_metric.compute(predictions, references)


/usr/local/lib/python3.6/dist-packages/datasets/load.py in prepare_module(path, script_version, download_config, download_mode, dataset, force_local_path, **download_kwargs)
    340     if needs_to_be_installed:
    341         raise ImportError(
--> 342             f"To be able to use this {module_type}, you need to install the following dependencies"
    343             f"{[lib_name for lib_name, lib_path in needs_to_be_installed]} using 'pip install "
    344             f"{' '.join([lib_path for lib_name, lib_path in needs_to_be_installed])}' for instance'"

ImportError: To be able to use this metric, you need to install the following dependencies['seqeval'] using 'pip install seqeval' for instance'
```

```
ValueError                                Traceback (most recent call last)
<ipython-input-39-ee559b166e25> in <module>()
      2 references = [['O', 'O', 'O', 'B-MISC', 'I-MISC', 'I-MISC', 'O'], ['B-PER', 'I-PER', 'O']]
      3 predictions =  [['O', 'O', 'B-MISC', 'I-MISC', 'I-MISC', 'I-MISC', 'O'], ['B-PER', 'I-PER', 'O']]
----> 4 ner_metric.compute(predictions, references)

/usr/local/lib/python3.6/dist-packages/datasets/metric.py in compute(self, *args, **kwargs)
    378         """
    379         if args:
--> 380             raise ValueError("Please call `compute` using keyword arguments.")
    381 
    382         predictions = kwargs.pop("predictions", None)

ValueError: Please call `compute` using keyword arguments.
```
GitHub issue #1663: update saving and loading methods for faiss index so to accept path l…
State: closed | Created: 2020-12-29T14:15:37Z

- Update saving and loading methods for faiss index so to accept path like objects from pathlib

The current code only supports using a string type to save and load a faiss index. This change makes it possible to use a string type OR a Path from [pathlib](https://docs.python.org/3/library/pathlib.html). The codes becomes a more intuitive this way I think.
GitHub issue #1662: Arrow file is too large when saving vector data
State: closed | Created: 2020-12-29T13:23:12Z

I computed the sentence embedding of each sentence of bookcorpus data using bert base and saved them to disk. I used 20M sentences and the obtained arrow file is about 59GB while the original text file is only about 1.3GB. Are there any ways to reduce the size of the arrow file?
GitHub issue #1647: NarrativeQA fails to load with `load_dataset`
State: closed | Created: 2020-12-28T18:16:09Z

When loading the NarrativeQA dataset with `load_dataset('narrativeqa')` as given in the documentation [here](https://huggingface.co/datasets/narrativeqa), I receive a cascade of exceptions, ending with

    FileNotFoundError: Couldn't find file locally at narrativeqa/narrativeqa.py, or remotely at 
        https://raw.githubusercontent.com/huggingface/datasets/1.1.3/datasets/narrativeqa/narrativeqa.py or 
        https://s3.amazonaws.com/datasets.huggingface.co/datasets/datasets/narrativeqa/narrativeqa.py

Workaround: manually copy the `narrativeqa.py` builder into my local directory with 

    curl https://raw.githubusercontent.com/huggingface/datasets/master/datasets/narrativeqa/narrativeqa.py -o narrativeqa.py

and load the dataset as `load_dataset('narrativeqa.py')` everything works fine. I'm on datasets v1.1.3 using Python 3.6.10.
GitHub issue #1644: HoVeR dataset fails to load
State: closed | Created: 2020-12-28T12:27:07Z

Hi! I'm getting an error when trying to load **HoVeR** dataset. Another one (**SQuAD**) does work for me. I'm using the latest (1.1.3) version of the library.

Steps to reproduce the error:

```python
>>> from datasets import load_dataset
>>> dataset = load_dataset("hover")
Traceback (most recent call last):
  File "/Users/urikz/anaconda/envs/mentionmemory/lib/python3.7/site-packages/datasets/load.py", line 267, in prepare_module
    local_path = cached_path(file_path, download_config=download_config)
  File "/Users/urikz/anaconda/envs/mentionmemory/lib/python3.7/site-packages/datasets/utils/file_utils.py", line 308, in cached_path
    use_etag=download_config.use_etag,
  File "/Users/urikz/anaconda/envs/mentionmemory/lib/python3.7/site-packages/datasets/utils/file_utils.py", line 486, in get_from_cache
    raise FileNotFoundError("Couldn't find file at {}".format(url))
FileNotFoundError: Couldn't find file at https://raw.githubusercontent.com/huggingface/datasets/1.1.3/datasets/hover/hover.py

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/Users/urikz/anaconda/envs/mentionmemory/lib/python3.7/site-packages/datasets/load.py", line 278, in prepare_module
    local_path = cached_path(file_path, download_config=download_config)
  File "/Users/urikz/anaconda/envs/mentionmemory/lib/python3.7/site-packages/datasets/utils/file_utils.py", line 308, in cached_path
    use_etag=download_config.use_etag,
  File "/Users/urikz/anaconda/envs/mentionmemory/lib/python3.7/site-packages/datasets/utils/file_utils.py", line 486, in get_from_cache
    raise FileNotFoundError("Couldn't find file at {}".format(url))
FileNotFoundError: Couldn't find file at https://s3.amazonaws.com/datasets.huggingface.co/datasets/datasets/hover/hover.py

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/Users/urikz/anaconda/envs/mentionmemory/lib/python3.7/site-packages/datasets/load.py", line 589, in load_dataset
    path, script_version=script_version, download_config=download_config, download_mode=download_mode, dataset=True
  File "/Users/urikz/anaconda/envs/mentionmemory/lib/python3.7/site-packages/datasets/load.py", line 282, in prepare_module
    combined_path, github_file_path, file_path
FileNotFoundError: Couldn't find file locally at hover/hover.py, or remotely at https://raw.githubusercontent.com/huggingface/datasets/1.1.3/datasets/hover/hover.py or https://s3.amazonaws.com/datasets.huggingface.co/datasets/datasets/hover/hover.py
```
GitHub issue #1643: Dataset social_bias_frames 404
State: closed | Created: 2020-12-28T08:35:34Z

```
>>> from datasets import load_dataset
>>> dataset = load_dataset("social_bias_frames")
...
Downloading and preparing dataset social_bias_frames/default
...
~/.pyenv/versions/3.7.6/lib/python3.7/site-packages/datasets/utils/file_utils.py in get_from_cache(url, cache_dir, force_download, proxies, etag_timeout, resume_download, user_agent, local_files_only, use_etag)
    484             )
    485         elif response is not None and response.status_code == 404:
--> 486             raise FileNotFoundError("Couldn't find file at {}".format(url))
    487         raise ConnectionError("Couldn't reach {}".format(url))
    488 

FileNotFoundError: Couldn't find file at https://homes.cs.washington.edu/~msap/social-bias-frames/SocialBiasFrames_v2.tgz
```
[Here](https://homes.cs.washington.edu/~msap/social-bias-frames/) we find button `Download data` with the correct URL for the data: https://homes.cs.washington.edu/~msap/social-bias-frames/SBIC.v2.tgz
GitHub issue #1641: muchocine dataset cannot be dowloaded
State: closed | Created: 2020-12-27T21:26:28Z

```python
---------------------------------------------------------------------------
FileNotFoundError                         Traceback (most recent call last)
/usr/local/lib/python3.6/dist-packages/datasets/load.py in prepare_module(path, script_version, download_config, download_mode, dataset, force_local_path, **download_kwargs)
    267         try:
--> 268             local_path = cached_path(file_path, download_config=download_config)
    269         except FileNotFoundError:

7 frames
FileNotFoundError: Couldn't find file at https://raw.githubusercontent.com/huggingface/datasets/1.0.2/datasets/muchocine/muchocine.py

During handling of the above exception, another exception occurred:

FileNotFoundError                         Traceback (most recent call last)
FileNotFoundError: Couldn't find file at https://s3.amazonaws.com/datasets.huggingface.co/datasets/datasets/muchocine/muchocine.py

During handling of the above exception, another exception occurred:

FileNotFoundError                         Traceback (most recent call last)
/usr/local/lib/python3.6/dist-packages/datasets/load.py in prepare_module(path, script_version, download_config, download_mode, dataset, force_local_path, **download_kwargs)
    281                 raise FileNotFoundError(
    282                     "Couldn't find file locally at {}, or remotely at {} or {}".format(
--> 283                         combined_path, github_file_path, file_path
    284                     )
    285                 )

FileNotFoundError: Couldn't find file locally at muchocine/muchocine.py, or remotely at https://raw.githubusercontent.com/huggingface/datasets/1.0.2/datasets/muchocine/muchocine.py or https://s3.amazonaws.com/datasets.huggingface.co/datasets/datasets/muchocine/muchocine.py
```
GitHub issue #1640: Fix "'BertTokenizerFast' object has no attribute 'max_len'"
State: closed | Created: 2020-12-26T19:25:41Z

Tensorflow 2.3.0 gives:
 FutureWarning: The `max_len` attribute has been deprecated and will be removed in a future version, use `model_max_length` instead.

Tensorflow 2.4.0 gives:
AttributeError 'BertTokenizerFast' object has no attribute 'max_len'
GitHub issue #1639: bug with sst2 in glue 
State: closed | Created: 2020-12-26T16:57:23Z

Hi
I am getting very low accuracy on SST2 I investigate this and observe that for this dataset sentences are tokenized, while this is correct for the other datasets in GLUE, please see below.
Is there any alternatives I could get untokenized sentences? I am unfortunately under time pressure to report some results on this dataset. thank you for your help. @lhoestq 
 
```
>>> a =  datasets.load_dataset('glue', 'sst2', split="validation", script_version="master")
Reusing dataset glue (/julia/datasets/glue/sst2/1.0.0/7c99657241149a24692c402a5c3f34d4c9f1df5ac2e4c3759fadea38f6cb29c4)
>>> a[:10]
{'idx': [0, 1, 2, 3, 4, 5, 6, 7, 8, 9], 'label': [1, 0, 1, 1, 0, 1, 0, 0, 1, 0], 'sentence': ["it 's a charming and often affecting journey . ", 'unflinchingly bleak and desperate ', 'allows us to hope that nolan is poised to embark a major career as a commercial yet inventive filmmaker . ', "the acting , costumes , music , cinematography and sound are all astounding given the production 's austere locales . ", "it 's slow -- very , very slow . ", 'although laced with humor and a few fanciful touches , the film is a refreshingly serious look at young women . ', 'a sometimes tedious film . ', "or doing last year 's taxes with your ex-wife . ", "you do n't have to know about music to appreciate the film 's easygoing blend of comedy and romance . ", "in exactly 89 minutes , most of which passed as slowly as if i 'd been sitting naked on an igloo , formula 51 sank from quirky to jerky to utter turkey . "]}

```
GitHub issue #1636: winogrande cannot be dowloaded 
State: closed | Created: 2020-12-24T22:28:22Z

Hi,
I am getting this error when trying to run the codes on the cloud.  Thank you for any suggestion and help on this @lhoestq 

```
 File "./finetune_trainer.py", line 318, in <module>
    main()
  File "./finetune_trainer.py", line 148, in main
    for task in data_args.tasks]
  File "./finetune_trainer.py", line 148, in <listcomp>
    for task in data_args.tasks]
  File "/workdir/seq2seq/data/tasks.py", line 65, in get_dataset
    dataset = self.load_dataset(split=split)
  File "/workdir/seq2seq/data/tasks.py", line 466, in load_dataset
    return datasets.load_dataset('winogrande', 'winogrande_l', split=split)
  File "/usr/local/lib/python3.6/dist-packages/datasets/load.py", line 589, in load_dataset
    path, script_version=script_version, download_config=download_config, download_mode=download_mode, dataset=True
  File "/usr/local/lib/python3.6/dist-packages/datasets/load.py", line 267, in prepare_module
    local_path = cached_path(file_path, download_config=download_config)
  File "/usr/local/lib/python3.6/dist-packages/datasets/utils/file_utils.py", line 308, in cached_path
    use_etag=download_config.use_etag,
  File "/usr/local/lib/python3.6/dist-packages/datasets/utils/file_utils.py", line 487, in get_from_cache
    raise ConnectionError("Couldn't reach {}".format(url))
ConnectionError: Couldn't reach https://raw.githubusercontent.com/huggingface/datasets/1.1.3/datasets/winogrande/winogrande.py
yo/0 I1224 14:17:46.419031 31226 main shadow.py:122 > Traceback (most recent call last):
  File "/usr/lib/python3.6/runpy.py", line 193, in _run_module_as_main
    "__main__", mod_spec)
  File "/usr/lib/python3.6/runpy.py", line 85, in _run_code
    exec(code, run_globals)
  File "/usr/local/lib/python3.6/dist-packages/torch/distributed/launch.py", line 260, in <module>
    main()
  File "/usr/local/lib/python3.6/dist-packages/torch/distributed/launch.py", line 256, in main
    cmd=cmd)
```
GitHub issue #1635: Persian Abstractive/Extractive Text Summarization
State: closed | Created: 2020-12-24T17:47:12Z

Assembling datasets tailored to different tasks and languages is a precious target. This would be great to have this dataset included.

## Adding a Dataset
- **Name:** *pn-summary*
- **Description:** *A well-structured summarization dataset for the Persian language consists of 93,207 records. It is prepared for Abstractive/Extractive tasks (like cnn_dailymail for English). It can also be used in other scopes like Text Generation, Title Generation, and News Category Classification.*
- **Paper:** *https://arxiv.org/abs/2012.11204*
- **Data:** *https://github.com/hooshvare/pn-summary/#download*
- **Motivation:** *It is the first Persian abstractive/extractive Text summarization dataset (like cnn_dailymail for English)!*

Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
GitHub issue #1633: social_i_qa wrong format of labels
State: closed | Created: 2020-12-24T13:11:54Z

Hi,
there is extra "\n" in labels of social_i_qa datasets, no big deal, but I was wondering if you could remove it to make it consistent.
so label is 'label': '1\n', not '1'
thanks

```
>>> import datasets 
>>> from datasets import load_dataset
>>> dataset = load_dataset(
...    'social_i_qa')
cahce dir  /julia/cache/datasets
Downloading: 4.72kB [00:00, 3.52MB/s]                                                                                                  
cahce dir /julia/cache/datasets
Downloading: 2.19kB [00:00, 1.81MB/s]                                                                                                  
Using custom data configuration default
Reusing dataset social_i_qa (/julia/datasets/social_i_qa/default/0.1.0/4a4190cc2d2482d43416c2167c0c5dccdd769d4482e84893614bd069e5c3ba06)
>>> dataset['train'][0]
{'answerA': 'like attending', 'answerB': 'like staying home', 'answerC': 'a good friend to have', 'context': 'Cameron decided to have a barbecue and gathered her friends together.', 'label': '1\n', 'question': 'How would Others feel as a result?'}

```
GitHub issue #1632: SICK dataset 
State: closed | Created: 2020-12-24T12:40:14Z

Hi, this would be great to have this dataset included. I might be missing something, but I could not find it in the list of already included datasets. Thank you. 

## Adding a Dataset
- **Name:** SICK
- **Description:**  SICK consists of about 10,000 English sentence pairs that include many examples of the lexical, syntactic, and semantic phenomena. 
- **Paper:** https://www.aclweb.org/anthology/L14-1314/
- **Data:** http://marcobaroni.org/composes/sick.html
- **Motivation:** This dataset is well-known in the NLP community used for recognizing entailment between sentences.

Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
GitHub issue #1630: Adding UKP Argument Aspect Similarity Corpus
State: closed | Created: 2020-12-24T11:01:31Z

Hi, this would be great to have this dataset included.

## Adding a Dataset
- **Name:** UKP Argument Aspect Similarity Corpus
- **Description:** The UKP Argument Aspect Similarity Corpus (UKP ASPECT) includes 3,595 sentence pairs over 28 controversial topics. Each sentence pair was annotated via crowdsourcing as either “high similarity”, “some similarity”, “no similarity” or “not related” with respect to the topic.
- **Paper:** https://www.aclweb.org/anthology/P19-1054/
- **Data:** https://tudatalib.ulb.tu-darmstadt.de/handle/tudatalib/1998
- **Motivation:** this is one of the datasets currently used frequently in recent adapter papers like https://arxiv.org/pdf/2005.00247.pdf 

Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).

Thank you
GitHub issue #1624: Cannot download ade_corpus_v2
State: closed | Created: 2020-12-23T10:58:14Z

I tried this to get the dataset following this url : https://huggingface.co/datasets/ade_corpus_v2

but received this error : 

`Traceback (most recent call last):
  File "/opt/anaconda3/lib/python3.7/site-packages/datasets/load.py", line 267, in prepare_module
    local_path = cached_path(file_path, download_config=download_config)
  File "/opt/anaconda3/lib/python3.7/site-packages/datasets/utils/file_utils.py", line 308, in cached_path
    use_etag=download_config.use_etag,
  File "/opt/anaconda3/lib/python3.7/site-packages/datasets/utils/file_utils.py", line 486, in get_from_cache
    raise FileNotFoundError("Couldn't find file at {}".format(url))
FileNotFoundError: Couldn't find file at https://raw.githubusercontent.com/huggingface/datasets/1.1.3/datasets/ade_corpus_v2/ade_corpus_v2.py

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/opt/anaconda3/lib/python3.7/site-packages/datasets/load.py", line 278, in prepare_module
    local_path = cached_path(file_path, download_config=download_config)
  File "/opt/anaconda3/lib/python3.7/site-packages/datasets/utils/file_utils.py", line 308, in cached_path
    use_etag=download_config.use_etag,
  File "/opt/anaconda3/lib/python3.7/site-packages/datasets/utils/file_utils.py", line 486, in get_from_cache
    raise FileNotFoundError("Couldn't find file at {}".format(url))
FileNotFoundError: Couldn't find file at https://s3.amazonaws.com/datasets.huggingface.co/datasets/datasets/ade_corpus_v2/ade_corpus_v2.py

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/opt/anaconda3/lib/python3.7/site-packages/datasets/load.py", line 589, in load_dataset
    path, script_version=script_version, download_config=download_config, download_mode=download_mode, dataset=True
  File "/opt/anaconda3/lib/python3.7/site-packages/datasets/load.py", line 282, in prepare_module
    combined_path, github_file_path, file_path
FileNotFoundError: Couldn't find file locally at ade_corpus_v2/ade_corpus_v2.py, or remotely at https://raw.githubusercontent.com/huggingface/datasets/1.1.3/datasets/ade_corpus_v2/ade_corpus_v2.py or https://s3.amazonaws.com/datasets.huggingface.co/datasets/datasets/ade_corpus_v2/ade_corpus_v2.py`
GitHub issue #1623: Add CLIMATE-FEVER dataset
State: closed | Created: 2020-12-22T13:34:05Z

As suggested by @SBrandeis , fresh PR that adds CLIMATE-FEVER. Replaces PR #1579.

---

A dataset adopting the FEVER methodology that consists of 1,535 real-world claims regarding climate-change collected on the internet. Each claim is accompanied by five manually annotated evidence sentences retrieved from the English Wikipedia that support, refute or do not give enough information to validate the claim totalling in 7,675 claim-evidence pairs. The dataset features challenging claims that relate multiple facets and disputed cases of claims where both supporting and refuting evidence are present.

More information can be found at:

* Homepage: http://climatefever.ai
* Paper: https://arxiv.org/abs/2012.00614