sunny2309/githug-issues huggingface dataset:
❓ Dataset loading script from Hugging Face Hub

Hi there,

I am trying to add my custom `ag_news` with its own loading script on the Hugging Face datasets hub. In particular, I would like to test the addition of a second configuration to the existing `ag_news` dataset. Once it works in my hub, I plan to make a PR to the original dataset. However, in trying to do so I have encountered certain problems as detailed below.

Issues I have encountered:
- Without a loading script, the train and test files are loaded together into a unique `dataset.Dataset` -> so I wrote a loading script. Also, I need a loading script otherwise I cannot specify multiple configurations
- Once my loading script is working locally, I do not manage to make it work on the hub. In particular, I would like to be able to load the dataset like this
```python
load_dataset("pietrolesci/ag_news", name="my_configuration")
```

Apparently, the `load_dataset` is able to pick up the loading script from the hub and run it. However, it errors because it is unable to find the files. The structure of my hub repo is the following
```
ag_news.py
train.csv
test.csv
```
and the loading script I specify  `data_dir=Path(__file__).parent` and `data_files=DataFilesDict({"train": "train.csv", "test": "test.csv"})`. In the documentation I could not find info regarding loading a dataset from the hub using a loading script present on the hub.

Any suggestion is very much appreciated.

Best,
Pietro

Link to the hub repo: https://huggingface.co/datasets/pietrolesci/ag_news

BONUS: how can I make the data viewer work in this specific case? :)
.map() cache is wrongfully reused - only happens when the mapping function is imported

## Describe the bug
When `.map` is used with a mapping function that is imported, the cache is reused even if the mapping function has been modified.
The reason for this is that `dill` that is used for creating the fingerprint [pickles imported functions by reference](https://stackoverflow.com/a/67851411).

I guess it is not a widespread case, but it can still lead to unwanted results unnoticeably. 

## Steps to reproduce the bug
Create files `a.py` and `b.py`:
```python
# a.py
from datasets import load_dataset

def main():
    squad = load_dataset("squad")
    squad.map(mapping_func, batched=True)

def mapping_func(examples):
    ID_LENGTH = 4
    examples["id"] = [id_[:ID_LENGTH] for id_ in examples["id"]]
    return examples

if __name__ == "__main__":
    main()
```
```python
# b.py
from datasets import load_dataset
from a import mapping_func

def main():
    squad = load_dataset("squad")
    squad.map(mapping_func, batched=True)

if __name__ == "__main__":
    main()
```
Run `python b.py` twice: In the first run you will see tqdm bars showing that the data is processed, and in the second run you will see "Loading cached processed dataset at...".
Now change `ID_LENGTH` to another number in order to change the mapping function, and run `python b.py` again. You'll see that `.map` loads from the cache the result of the previous mapping function.

## Expected results
Run `python a.py` twice: In the first run you will see tqdm bars showing that the data is processed, and in the second run you will see "Loading cached processed dataset at...".
Now change `ID_LENGTH` to another number in order to change the mapping function, and run `python a.py` again. You'll see that the dataset is being processed and that there's no reuse of the previous mapping function result.

## Workaround
Put the mapping function inside a dummy class as a static method:
```python
# a.py
class MappingFuncClass:
    @staticmethod
    def mapping_func(examples):
        ID_LENGTH = 4
        examples["id"] = [id_[:ID_LENGTH] for id_ in examples["id"]]
        return examples
```
```python
# b.py
from datasets import load_dataset
from a import MappingFuncClass

def main():
    squad = load_dataset("squad")
    squad.map(MappingFuncClass.mapping_func, batched=True)

if __name__ == "__main__":
    main()
```

## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.15.1
- Platform: Linux-4.4.0-19041-Microsoft-x86_64-with-glibc2.17
- Python version: 3.8.10
- PyArrow version: 4.0.1
Temporary dataset_path for remote fs URIs not built properly in arrow_dataset.py::load_from_disk

## Describe the bug
When trying to build a temporary dataset path from a remote URI in this block of code:

https://github.com/huggingface/datasets/blob/42f6b1d18a4a1b6009b6e62d115491be16dfca22/src/datasets/arrow_dataset.py#L1038-L1042

the result is not the expected when passing an absolute path in an URI like `hdfs:///absolute/path`.

## Steps to reproduce the bug
```python
dataset_path = "hdfs:///absolute/path"
src_dataset_path = extract_path_from_uri(dataset_path)
tmp_dir = get_temporary_cache_files_directory()
dataset_path = Path(tmp_dir, src_dataset_path)
print(dataset_path)
```

## Expected results
With the code above, we would expect a value in `dataset_path` similar to:
`/tmp/tmpnwxyvao5/absolute/path`

## Actual results
However, we get a `dataset_path` value like:
`/absolute/path`

This is because this line here: https://github.com/huggingface/datasets/blob/42f6b1d18a4a1b6009b6e62d115491be16dfca22/src/datasets/arrow_dataset.py#L1041
returns the last absolute path when two absolute paths (the one in `tmp_dir` and the one extracted from the URI in `src_dataset_path`) are passed as arguments.

## Environment info
- `datasets` version: 1.13.3
- Platform: Linux-3.10.0-1160.15.2.el7.x86_64-x86_64-with-glibc2.33
- Python version: 3.9.7
- PyArrow version: 5.0.0
Make several audio datasets streamable


Needs https://github.com/huggingface/datasets/pull/3129 to be merged first


Make those audio datasets streamable:
- [x] common_voice
- [x] openslr
- [x] vivos
- [x] librispeech_asr 
(still has some issues to read FLAC)
 *actually it's ok*
- [ ] 
multilingual_librispeech (yet to be converted)</S> *TODO in a separate PR*
Add IEMOCAP dataset

## Adding a Dataset
- **Name:** IEMOCAP
- **Description:** acted, multimodal and multispeaker database
- **Paper:** https://sail.usc.edu/iemocap/Busso_2008_iemocap.pdf
- **Data:** https://sail.usc.edu/iemocap/index.html
- **Motivation:** Useful multimodal dataset

cc @anton-l 

Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
Add VoxLingua107 dataset

## Adding a Dataset
- **Name:** VoxLingua107
- **Description:** VoxLingua107 is a speech dataset for training spoken language identification models. The dataset consists of short speech segments automatically extracted from YouTube videos and labeled according the language of the video title and description, with some post-processing steps to filter out false positives.
- **Paper:** https://arxiv.org/abs/2011.12998
- **Data:** http://bark.phon.ioc.ee/voxlingua107/
- **Motivation:** Nice audio classification dataset

cc @anton-l 

Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
Add Speech Commands dataset

## Adding a Dataset
- **Name:** Speech commands
- **Description:** A Dataset for Limited-Vocabulary Speech Recognition
- **Paper:** https://arxiv.org/abs/1804.03209
- **Data:** https://www.tensorflow.org/datasets/catalog/speech_commands,  Available:
http://download.tensorflow.org/data/speech_commands_v0.02.tar.gz
- **Motivation:** Nice dataset for audio classification training

cc @anton-l 

Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
ConnectionError: Couldn't reach https://huggingface.co/datasets/oscar-corpus/OSCAR-2109/resolve/main/OSCAR-2109.py

## Dataset viewer issue for '*oscar-corpus/OSCAR-2109*'

**Link:** *[link to the dataset viewer page](https://huggingface.co/datasets/oscar-corpus/OSCAR-2109)*

*The dataset library cannot download any language from the oscar-corpus/OSCAR-2109 dataset. By entering the URL in your browser I can access the file.*

```
    raise ConnectionError("Couldn't reach {}".format(url))
ConnectionError: Couldn't reach https://huggingface.co/datasets/oscar-corpus/OSCAR-2109/resolve/main/OSCAR-2109.py
```

Am I the one who added this dataset ? No

Using the older version of [OSCAR](https://huggingface.co/datasets/oscar) I don't have any issues downloading languages with the dataset library.
[Datasets] Improve Covost 2

It's currently quite confusing to understand the manual data download instruction of Covost and not very user-friendly.

Currenty the user has to:

1. Go on Common Voice website
2. Find the correct dataset which is **not** mentioned in the error message
3. Download it
4. Untar it
5. Create a language id folder (why? this folder does not exist in the `.tar` downloaded file)
6. pass the folder containing the created language id folder

This PR improves this to:

1. Go on Common Voice website
2. Find the correct dataset which **is** mentioned in the error message
3. Download it
4. Untar it
5. pass the untared folder

**Note**: This PR is not at all time-critical
f-string formatting

**Fix #3257**

Replaced _.format()_ and _%_ by f-strings in the following modules : 
- [x] **tests**
- [x] **metrics**
- [x] **benchmarks**
- [x] **utils**
- [x] **templates**
- [x] **src/Datasets/\*.py**

Modules in **_src/Datasets/_**: 
- [x] **commands**
- [x] **features**
- [x] **formatting**
- [x] **io**
- [x] **tasks**
- [x] **utils**


Module **datasets** will not be edited as asked by @mariosasko 

-A correction of the first PR (#3267)-
coqa NonMatchingChecksumError

```
>>> from datasets import load_dataset
>>> dataset = load_dataset("coqa")
Downloading: 3.82kB [00:00, 1.26MB/s]                                                                                                                                                                                                                       
Downloading: 1.79kB [00:00, 733kB/s]                                                                                                                                                                                                                        
Using custom data configuration default
Downloading and preparing dataset coqa/default (download: 55.40 MiB, generated: 18.35 MiB, post-processed: Unknown size, total: 73.75 MiB) to /Users/zhaofengw/.cache/huggingface/datasets/coqa/default/1.0.0/553ce70bfdcd15ff4b5f4abc4fc2f37137139cde1f58f4f60384a53a327716f0...
Downloading: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 222/222 [00:00<00:00, 1.38MB/s]
Downloading: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 222/222 [00:00<00:00, 1.32MB/s]
100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 2/2 [00:01<00:00,  1.91it/s]
100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 2/2 [00:00<00:00, 1117.44it/s]
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/Users/zhaofengw/miniconda3/lib/python3.9/site-packages/datasets/load.py", line 1632, in load_dataset
    builder_instance.download_and_prepare(
  File "/Users/zhaofengw/miniconda3/lib/python3.9/site-packages/datasets/builder.py", line 607, in download_and_prepare
    self._download_and_prepare(
  File "/Users/zhaofengw/miniconda3/lib/python3.9/site-packages/datasets/builder.py", line 679, in _download_and_prepare
    verify_checksums(
  File "/Users/zhaofengw/miniconda3/lib/python3.9/site-packages/datasets/utils/info_utils.py", line 40, in verify_checksums
    raise NonMatchingChecksumError(error_msg + str(bad_urls))
datasets.utils.info_utils.NonMatchingChecksumError: Checksums didn't match for dataset source files:
['https://nlp.stanford.edu/data/coqa/coqa-train-v1.0.json', 'https://nlp.stanford.edu/data/coqa/coqa-dev-v1.0.json']
```
Dataset viewer issue for 'liweili/c4_200m'

## Dataset viewer issue for '*liweili/c4_200m*'

**Link:** *[link to the dataset viewer page](https://huggingface.co/datasets/liweili/c4_200m)*

*Server Error*
```
Status code:   404
Exception:     Status404Error
Message:       Not found. Maybe the cache is missing, or maybe the ressource does not exist.
```

Am I the one who added this dataset ? Yes
Replacing .format() and % by f-strings

**Fix #3257**

Replaced _.format()_ and _%_ by f-strings in the following modules : 
- [x] **tests**
- [x] **metrics**
- [x] **benchmarks**
- [x] **utils**
- [x] **templates**

Will follow in the next PR the modules left : 
- [ ] **src**

Module **datasets** will not be edited as asked by @mariosasko 

PS : black and isort applied to files
Checksum error for kilt_task_wow

## Describe the bug
Checksum failed when downloads kilt_tasks_wow. See error output for details.

## Steps to reproduce the bug
```python
import datasets
datasets.load_datasets('kilt_tasks','wow')
```

## Expected results
Download successful

## Actual results
```
Downloading and preparing dataset kilt_tasks/wow (download: 72.07 MiB, generated: 61.82 MiB, post-processed: Unknown size, total: 133.89 MiB) to /root/.cache/huggingface/datasets/kilt_tasks/wow/1.0.0/57dc8b2431e76637e0c6ef79689ca4af61ed3a330e2e0cd62c8971465a35db3a...
100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<00:00, 5121.25it/s]
100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<00:00, 1527.42it/s]
Traceback (most recent call last):
  File "kilt_wow.py", line 30, in <module>
    main()
  File "kilt_wow.py", line 27, in main
    train, dev, test = dataset.generate_k_shot_data(k=32, seed=seed, path="../data/")
  File "/workspace/projects/CrossFit/tasks/fewshot_gym_dataset.py", line 79, in generate_k_shot_data
    dataset = self.load_dataset()
  File "kilt_wow.py", line 21, in load_dataset
    return datasets.load_dataset('kilt_tasks','wow')
  File "/opt/conda/lib/python3.8/site-packages/datasets/load.py", line 1632, in load_dataset
    builder_instance.download_and_prepare(
  File "/opt/conda/lib/python3.8/site-packages/datasets/builder.py", line 607, in download_and_prepare
    self._download_and_prepare(
  File "/opt/conda/lib/python3.8/site-packages/datasets/builder.py", line 679, in _download_and_prepare
    verify_checksums(
  File "/opt/conda/lib/python3.8/site-packages/datasets/utils/info_utils.py", line 40, in verify_checksums
    raise NonMatchingChecksumError(error_msg + str(bad_urls))
datasets.utils.info_utils.NonMatchingChecksumError: Checksums didn't match for dataset source files:
['http://dl.fbaipublicfiles.com/KILT/wow-train-kilt.jsonl', 'http://dl.fbaipublicfiles.com/KILT/wow-dev-kilt.jsonl']
```

## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.15.1
- Platform: Linux-4.15.0-161-generic-x86_64-with-glibc2.10
- Python version: 3.8.3
- PyArrow version: 4.0.1
Scifi_TV_Shows: Having trouble getting viewer to find appropriate files

## Dataset viewer issue for '*Science Fiction TV Show Plots Corpus  (Scifi_TV_Shows)*'

**Link:** [link](https://huggingface.co/datasets/lara-martin/Scifi_TV_Shows)

I tried adding both a script (https://huggingface.co/datasets/lara-martin/Scifi_TV_Shows/blob/main/Scifi_TV_Shows.py) and some dummy examples (https://huggingface.co/datasets/lara-martin/Scifi_TV_Shows/tree/main/dummy), but the viewer still has a 404 error ("Not found. Maybe the cache is missing, or maybe the ressource does not exist."). I'm not sure what to try next. Thanks in advance!

Am I the one who added this dataset? Yes
asserts replaced by exception for text classification task with test.

I have replaced only a single assert in text_classification.py along with a unit test to verify an exception is raised based on https://github.com/huggingface/datasets/issues/3171 . 

I would like to first understand the code contribution workflow. So keeping the change to a single file rather than making too many changes. Once this gets approved, I will look into the rest. 

Thanks.
`GeneratorBasedBuilder` does not support `None` values

## Describe the bug
`GeneratorBasedBuilder` does not support `None` values.

## Steps to reproduce the bug
See [this repository](https://github.com/pavel-lexyr/huggingface-datasets-bug-reproduction) for minimal reproduction.

## Expected results
Dataset is initialized with a `None` value in the `value` column.

## Actual results
```
Traceback (most recent call last):
  File "main.py", line 3, in <module>
    datasets.load_dataset("./bad-data")
  File ".../datasets/load.py", line 1632, in load_dataset
    builder_instance.download_and_prepare(
  File ".../datasets/builder.py", line 607, in download_and_prepare
    self._download_and_prepare(
  File ".../datasets/builder.py", line 697, in _download_and_prepare
    self._prepare_split(split_generator, **prepare_split_kwargs)
  File ".../datasets/builder.py", line 1103, in _prepare_split
    example = self.info.features.encode_example(record)
  File ".../datasets/features/features.py", line 1033, in encode_example
    return encode_nested_example(self, example)
  File ".../datasets/features/features.py", line 808, in encode_nested_example
    return {
  File ".../datasets/features/features.py", line 809, in <dictcomp>
    k: encode_nested_example(sub_schema, sub_obj) for k, (sub_schema, sub_obj) in utils.zip_dict(schema, obj)
  File ".../datasets/features/features.py", line 855, in encode_nested_example
    return schema.encode_example(obj)
  File ".../datasets/features/features.py", line 299, in encode_example
    return float(value)
TypeError: float() argument must be a string or a number, not 'NoneType'
```

## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.15.1
- Platform: Linux-5.4.0-81-generic-x86_64-with-glibc2.29
- Python version: 3.8.10
- PyArrow version: 6.0.0
Stream from Google Drive and other hosts

Streaming from Google Drive is a bit more challenging than the other host we've been supporting:
- the download URL must be updated to add the confirm token obtained by HEAD request
- it requires to use cookies to keep the connection alive
- the URL doesn't tell any information about whether the file is compressed or not

Therefore I did two things:
- I added a step for URL and headers/cookies preparation in the StreamingDownloadManager
- I added automatic compression type inference by reading the [magic number](https://en.wikipedia.org/wiki/List_of_file_signatures)

This allows to do do fancy things like
```python
from datasets.utils.streaming_download_manager import StreamingDownloadManager, xopen, xjoin, xglob

# zip file containing a train.tsv file
url = "https://drive.google.com/uc?export=download&id=1k92sUfpHxKq8PXWRr7Y5aNHXwOCNUmqh"

extracted = StreamingDownloadManager().download_and_extract(url)
for inner_file in xglob(xjoin(extracted, "*.tsv")):
    with xopen(inner_file) as f:
        # streaming starts here
        for line in f:
            print(line)
```

This should make around 80 datasets streamable. It concerns those hosted on Google Drive but also any dataset for which the URL doesn't give any information about compression. Here is the full list:

```
amazon_polarity, ami, arabic_billion_words, ascent_kb, asset, big_patent, billsum, capes, cmrc2018, cnn_dailymail,
code_x_glue_cc_code_completion_token, code_x_glue_cc_code_refinement, code_x_glue_cc_code_to_code_trans,
code_x_glue_tt_text_to_text, conll2002, craigslist_bargains, dbpedia_14, docred, ehealth_kd, emo, euronews, germeval_14,
gigaword, grail_qa, great_code, has_part, head_qa, health_fact, hope_edi, id_newspapers_2018,
igbo_english_machine_translation, irc_disentangle, jfleg, jnlpba, journalists_questions, kor_ner, linnaeus, med_hop, mrqa,
mt_eng_vietnamese, multi_news, norwegian_ner, offcombr, offenseval_dravidian, para_pat, peoples_daily_ner, pn_summary,
poleval2019_mt, pubmed_qa, qangaroo, reddit_tifu, refresd, ro_sts_parallel, russian_super_glue, samsum, sberquad, scielo,
search_qa, species_800, spider, squad_adversarial, tamilmixsentiment, tashkeela, ted_talks_iwslt, trec, turk, turkish_ner,
twi_text_c3, universal_morphologies, web_of_science, weibo_ner, wiki_bio, wiki_hop, wiki_lingua, wiki_summary, wili_2018,
wisesight1000, wnut_17, yahoo_answers_topics, yelp_review_full, yoruba_text_c3
```

Some of them may not work if the host doesn't support HTTP range requests for example

Fix https://github.com/huggingface/datasets/issues/2742
Fix https://github.com/huggingface/datasets/issues/3188
Couldn't reach data file for disaster_response_messages

## Describe the bug
Following command gives an ConnectionError.

## Steps to reproduce the bug
```python
disaster = load_dataset('disaster_response_messages')
```

## Error
```
ConnectionError: Couldn't reach https://datasets.appen.com/appen_datasets/disaster_response_data/disaster_response_messages_training.csv
```
## Expected results
It should load dataset without an error

## Actual results
Specify the actual results or traceback.

## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version:
- Platform: Google Colab
- Python version: 3.7
- PyArrow version:
Reuters21578 Couldn't reach 

``## Adding a Dataset
- **Name:** *Reuters21578*
- **Description:** *ConnectionError: Couldn't reach https://kdd.ics.uci.edu/databases/reuters21578/reuters21578.tar.gz*
- **Data:** *https://huggingface.co/datasets/reuters21578*

`from datasets import load_dataset`
`dataset = load_dataset("reuters21578", 'ModLewis')`

ConnectionError: Couldn't reach https://kdd.ics.uci.edu/databases/reuters21578/reuters21578.tar.gz

And I try to request the link as follow:
`import requests`
`requests.head('https://kdd.ics.uci.edu/databases/reuters21578/reuters21578.tar.gz')`

SSLError: HTTPSConnectionPool(host='kdd.ics.uci.edu', port=443): Max retries exceeded with url: /databases/reuters21578/reuters21578.tar.gz (Caused by SSLError(SSLError(1, '[SSL: CERTIFICATE_VERIFY_FAILED] certificate verify failed (_ssl.c:852)'),))

This problem likes #575
What should I do ?
wikitext description wrong

## Describe the bug
Descriptions of the wikitext datasests are wrong. 

## Steps to reproduce the bug
Please see: https://github.com/huggingface/datasets/blob/f6dcafce996f39b6a4bbe3a9833287346f4a4b68/datasets/wikitext/wikitext.py#L50

## Expected results
The descriptions for raw-v1 and v1 should be switched.