Kokolipa/github-issues huggingface dataset:
Issue: Image column is not decoded in map when using with with_transform
State: closed
Labels: name: bug

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


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

name: vision

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

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


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

> There is an open PR to do that: #3364. I just haven't had time to finish it...

😬 thanks...
Issue: [image feature] Too many files open error when image feature is returned as a path
State: closed
Labels: name: bug

## Describe the bug

PR in context: #3967. If I load the dataset in this PR (TextVQA), and do a simple list comprehension on the dataset, I get `Too many open files error`. This is happening due to the way we are loading the image feature when a str path is returned from the `_generate_examples`. Specifically at https://github.com/huggingface/datasets/blob/508eb4ab5d52f590baa677b4f64b1cc069139f7b/src/datasets/features/image.py#L110, we are open the file handle to the image but never closing it. This in my understanding is causing the issue.

## Steps to reproduce the bug
Pull the PR locally and run the following code
```python
from datasets import load_dataset

dataset = load_dataset("./datasets/textvqa")["train"]
data = [item for item in dataset]

# Error happens
```

## Expected results

List comprehension should work smoothly

## Actual results

`Too many open files error`

## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 2.0.1.dev0
- Platform: macOS-12.2-arm64-arm-64bit
- Python version: 3.10.0
- PyArrow version: 7.0.0
- Pandas version: 1.4.1
Issue: Cannot preview cnn_dailymail dataset
State: closed

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


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

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

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

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

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

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


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

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

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

Indeed, streaming was not supported: tgz archives were not properly iterated.

I've opened a PR to support streaming.

However, keep in mind that Google Drive will keep generating issues from time to time, like 403,...
Issue: Cannot preview 'indonesian-nlp/eli5_id' dataset
State: closed
Labels: name: dataset-viewer

## Dataset viewer issue for '*indonesian-nlp/eli5_id*'

**Link:** https://huggingface.co/datasets/indonesian-nlp/eli5_id

I can not see the dataset preview.
```
Server Error
Status code:   400
Exception:     Status400Error
Message:       Not found. Maybe the cache is missing, or maybe the dataset does not exist.
```
Am I the one who added this dataset ? Yes


Hi @cahya-wirawan, thanks for reporting.

Your dataset is working OK in streaming mode:
```python
In [1]: from datasets import load_dataset
   ...: ds = load_dataset("indonesian-nlp/eli5_id", split="train", streaming=True)
   ...: item = next(iter(ds))
   ...: item
Using custom data configuration indonesian-nlp--eli5_id-9fe728a7e760fb7b

Out[1]: 
{'q_id': '1oy5tc',
 'title': 'dalam sepak bola apa gunanya menyia-nyiakan dua permainan pertama dengan terburu-buru - di tengah - bukan permainan terburu-buru biasa saya mendapatkannya',
 'selftext': '',
 'document': '',
 'subreddit': 'explainlikeimfive',
 'answers': {'a_id': ['ccwtgnz', 'ccwtmho', 'ccwt946', 'ccwvj0u'],
  'text': ['Jaga pertahanan tetap jujur, rasakan operan terburu-buru, buka permainan yang lewat. Pelanggaran yang terlalu satu dimensi akan gagal. Dan mereka yang bergegas ke tengah kadang-kadang dapat dibuka lebar-lebar untuk ukuran yard yang besar.',
   'Jika Anda melempar bola sepanjang waktu, maka pertahanan akan beradaptasi untuk selalu menutupi umpan. Dengan melakukan permainan lari sederhana sesekali, Anda memaksa pertahanan untuk tetap dekat dan menjaga dari lari. Terkadang, pelanggaran dapat membuat pertahanan lengah dengan berpura-pura berlari dan membebaskan penerima mereka. Selain itu, Anda tidak perlu mendapatkan yard besar di setiap permainan. Terkadang, paling baik mendapatkan beberapa yard sekaligus. Selama Anda mendapatkan yang pertama, Anda dalam kondisi yang baik.',
   'Dalam kebanyakan kasus, O-Line seharusnya membuat lubang untuk dilalui kembali. Jika Anda menjalankan terlalu banyak permainan ke luar / melempar, pertahanan akan mengejar. Juga, 2 permainan 5 yard memberi Anda satu set down baru.',
   'Saya Anda tidak suka jenis drama itu, tonton CFL. Kami hanya mendapatkan 3 down sehingga Anda tidak bisa menyia-nyiakannya. Lebih banyak lagi yang lewat.'],
  'score': [3, 2, 2, 2]},
 'title_urls': {'url': []},
 'selftext_urls': {'url': []},
 'answers_urls': {'url': []}}
```
Therefore, it should be properly rendered in the previewer. Let me ping @severo to have a look at it.

Thanks @albertvillanova for checking it. Btw, I have another dataset indonesian-nlp/lfqa_id which has the same issue. However, this dataset is still private, is it the reason why the preview doesn't work?

Yes, preview is not supported on private datasets yet. We are working on that though...

Thanks for the confirmation 

Fixed. Thanks for your feedback.
Issue: Scores from Index at extra positions are not filtered out
State: closed
Labels: name: bug

If a FAISS index has fewer records than the requested number of top results (k), then it returns -1 in indices for the additional positions. The get_nearest_examples method only filters out the extra results from the dataset samples. It would be better to filter out extra scores too.

Reference: https://github.com/huggingface/datasets/blob/2.0.0/src/datasets/search.py#L693


Hi! Yes, that makes sense! Would you like to submit a PR to fix this?

Created PR https://github.com/huggingface/datasets/pull/3971
Issue: The dataset preview is not available for tdklab/Hebrew_Squad_v1.1 dataset
State: closed

## Dataset viewer issue for 'tdklab/Hebrew_Squad_v1.1'

**Link:**  https://huggingface.co/api/datasets/tdklab/Hebrew_Squad_v1.1?full=true

The dataset preview is not available for this dataset.

Am I the one who added this dataset ? Yes

Hi @MatanBenChorin, thanks for reporting.

Please, take into account that the preview may take some time until it properly renders (we are working to reduce this time).

Maybe @severo can give more details on this.

Hi, 
Thank you

Thanks for reporting. We are looking at it and will give updates here.

I imagine the dataset has been moved to https://huggingface.co/datasets/tdklab/Hebrew_Squad_v1, which still has an issue:

```
Server Error

Status code:   400
Exception:     NameError
Message:       name 'HebrewSquad' is not defined
```

The issue is not related to the dataset viewer but to the loading script (cc @albertvillanova @lhoestq @mariosasko)

```python
>>> import datasets as ds
>>> hf_token = "hf_..." # <- required because the dataset is gated
>>> d = ds.load_dataset('tdklab/Hebrew_Squad_v1', use_auth_token=hf_token)
...
NameError: name 'HebrewSquad' is not defined
```

Yes indeed there is an error in [Hebrew_Squad_v1.py:L40](https://huggingface.co/datasets/tdklab/Hebrew_Squad_v1/blob/main/Hebrew_Squad_v1.py#L40)

Here is the fix @MatanBenChorin :

```diff
-         HebrewSquad(
+         HebrewSquadConfig(
```
Issue: Add ImageNet Sketch
State: closed
Labels: name: dataset request

name: vision

## Adding a Dataset
- **Name:** ImageNet Sketch
- **Description:** ImageNet-Sketch is a dataset consisting of sketch-like images, that matches the ImageNet classification validation set in categories and scale.
- **Paper:** [Learning Robust Global Representations by Penalizing Local Predictive Power](https://arxiv.org/abs/1905.13549)
- **Data:** https://github.com/HaohanWang/ImageNet-Sketch
- **Motivation:** Allows for evaluating the robustness of vision models.

Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).


Can you assign this task to me? @nreimers @mariosasko 

Hi! Sure! Let us know if you need any pointers.
Issue: reddit_tifu dataset: Checksums didn't match for dataset source files
State: closed
Labels: name: bug

name: duplicate

## Describe the bug
When loading the reddit_tifu dataset, it throws the exception "Checksums didn't match for dataset source files"


## Steps to reproduce the bug
```python
import datasets
from datasets import load_dataset

print(datasets.__version__)

# load_dataset('billsum')

load_dataset('reddit_tifu', 'short')
```


## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.17.0
- Platform: mac os
- Python version: Python 3.7.6
- PyArrow version: 3.0.0


Hi @XingxingZhang, 

We have already fixed this. You should update `datasets` version to at least 1.18.4:
```shell
pip install -U datasets
```
And then force the redownload:
```python
load_dataset("...", download_mode="force_redownload")
```

Duplicate of:
- #3773

thanks @albertvillanova . by upgrading to 1.18.4 and using `load_dataset("...", download_mode="force_redownload")` fixed 
 the bug.

using the following as you suggested in another thread can also fixed the bug
```
pip install git+https://github.com/huggingface/datasets#egg=datasets
```


The latter solution (installing from GitHub) was proposed because the fix was not released yet. But last week we made the 1.18.4 patch release (with the fix), so no longer necessary to install from GitHub.

You can now install from PyPI, as usual:
```shell
pip install -U datasets
```
Issue: billsum dataset: Checksums didn't match for dataset source files:
State: closed
Labels: name: bug

## Describe the bug

When loading the `billsum` dataset, it throws the exception "Checksums didn't match for dataset source files"

```
  File "virtualenv_projects/codex/lib/python3.7/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://drive.google.com/uc?export=download&id=1g89WgFHMRbr4QrvA0ngh26PY081Nv3lx']
```

## Steps to reproduce the bug
```python
import datasets
from datasets import load_dataset

print(datasets.__version__)

load_dataset('billsum')
```


## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.17.0

- Platform: mac os
- Python version: Python 3.7.6
- PyArrow version: 3.0.0






Hi @XingxingZhang, thanks for reporting.

This was due to a change in Google Drive service:
- #3786 

We have already fixed it:
- #3787

You should update `datasets` version to at least 1.18.4:
```shell
pip install -U datasets
```
And then force the redownload:
```python
load_dataset("...", download_mode="force_redownload")
```

thanks @albertvillanova 

@albertvillanova 
YOU Said: pip install git+ https://github.com/huggingface/datasets.git Then set: dataset=load_dataset ("multinews", download_mode="force-redownload"). I changed the ’datautils‘ file according to this setting: traindata=load_dataset (path='wikitext ', name='wikitext-2-raw v1', split='train ', download_mode="force-redownload")
Testdata=load_dataset (path='wikitext ', name='wikitext-2-raw v1', split='test ', download_mode="force-redownload")
then the bug is
![image](https://github.com/huggingface/datasets/assets/149936473/ee956e8f-e6f1-46bf-b514-0a7a0a0e0e37)
![image](https://github.com/huggingface/datasets/assets/149936473/f1318686-942c-4341-a61d-9be7a4b5747a)
I have tried both versions
![image](https://github.com/huggingface/datasets/assets/149936473/d3f0d786-304b-4596-83c6-49c3cac58aad)
Issue: Missing languages in lvwerra/github-code dataset
State: closed
Labels: name: Dataset discussion

Hi,

I'm working with the github-code dataset. First of all, thank you for creating this amazing dataset!
I've noticed that two languages are missing from the dataset: TypeScript and Scala. 
Looks like they're also omitted from the query you used to get the original code.
Are there any plans to add them in the future?

Thanks!

Thanks for contacting @Eytan-S.

I think @lvwerra could better answer this. 

That seems to be an oversight - I originally planned to include them in the dataset and for some reason they were in the list of languages but not in the query. Since there is an issue with the deduplication step I'll rerun the pipeline anyway and will double check the query.

Thanks for reporting this @Eytan-S!

Can confirm that the two languages are indeed missing from the dataset. Here are the file counts per language:
```Python
{'Assembly': 82847,
 'Batchfile': 236755,
 'C': 14127969,
 'C#': 6793439,
 'C++': 7368473,
 'CMake': 175076,
 'CSS': 1733625,
 'Dockerfile': 331966,
 'FORTRAN': 141963,
 'GO': 2259363,
 'Haskell': 340521,
 'HTML': 11165464,
 'Java': 19515696,
 'JavaScript': 11829024,
 'Julia': 58177,
 'Lua': 576279,
 'Makefile': 679338,
 'Markdown': 8454049,
 'PHP': 11181930,
 'Perl': 497490,
 'PowerShell': 136827,
 'Python': 7203553,
 'Ruby': 4479767,
 'Rust': 321765,
 'SQL': 655657,
 'Scala': 0,
 'Shell': 1382786,
 'TypeScript': 0,
 'TeX': 250764,
 'Visual Basic': 155371}
 ```

@Eytan-S check out v1.1 of the `github-code` dataset where issue should be fixed:

|    | Language     |File Count| Size (GB)|
|---:|:-------------|---------:|-------:|
|  0 | Java         | 19548190 | 107.7  |
|  1 | C            | 14143113 | 183.83 |
|  2 | JavaScript   | 11839883 |  87.82 |
|  3 | HTML         | 11178557 | 118.12 |
|  4 | PHP          | 11177610 |  61.41 |
|  5 | Markdown     |  8464626 |  23.09 |
|  6 | C++          |  7380520 |  87.73 |
|  7 | Python       |  7226626 |  52.03 |
|  8 | C#           |  6811652 |  36.83 |
|  9 | Ruby         |  4473331 |  10.95 |
| 10 | GO           |  2265436 |  19.28 |
| 11 | TypeScript   |  1940406 |  24.59 |
| 12 | CSS          |  1734406 |  22.67 |
| 13 | Shell        |  1385648 |   3.01 |
| 14 | Scala        |   835755 |   3.87 |
| 15 | Makefile     |   679430 |   2.92 |
| 16 | SQL          |   656671 |   5.67 |
| 17 | Lua          |   578554 |   2.81 |
| 18 | Perl         |   497949 |   4.7  |
| 19 | Dockerfile   |   366505 |   0.71 |
| 20 | Haskell      |   340623 |   1.85 |
| 21 | Rust         |   322431 |   2.68 |
| 22 | TeX          |   251015 |   2.15 |
| 23 | Batchfile    |   236945 |   0.7  |
| 24 | CMake        |   175282 |   0.54 |
| 25 | Visual Basic |   155652 |   1.91 |
| 26 | FORTRAN      |   142038 |   1.62 |
| 27 | PowerShell   |   136846 |   0.69 |
| 28 | Assembly     |    82905 |   0.78 |
| 29 | Julia        |    58317 |   0.29 |

Thanks @lvwerra.
Issue: Load a local dataset twice
State: closed
Labels: name: bug

## Describe the bug
Load a local "dataset" composed of two csv files twice.

## Steps to reproduce the bug
Put the two joined files in a repository named "Data".
Then in python:

import datasets as ds
ds.load_dataset('Data', data_files = {'file1.csv', 'file2.csv'})

## Expected results
Should give something like (because files have only one data row):
Title, clicks
Truc et astuce, 123
Machin, 12

## Actual results
Gives 
Title, clicks
Truc et astuce, 123
Machin, 12
Truc et astuce, 123
Machin, 12

## Environment info
[file1.csv](https://github.com/huggingface/datasets/files/8256322/file1.csv)
[file2.csv](https://github.com/huggingface/datasets/files/8256323/file2.csv)
- `datasets` version: 2.0.0
- Platform: Linux-5.4.0-65-generic-x86_64-with-glibc2.10
- Python version: 3.8.12
- PyArrow version: 7.0.0
- Pandas version: 1.4.1

Hi @caush, thanks for reporting:

In order to load local CSV files, you can use our "csv" loading script: https://huggingface.co/docs/datasets/loading#csv
```python
dataset = load_dataset("csv", data_files=["data/file1.csv", "data/file2.csv"])
```
OR:
```python
dataset = load_dataset("csv", data_dir="data")
```

Alternatively, you may also use:
```python
dataset = load_dataset("data")
Issue: Frugal score deprecations
State: closed
Labels: name: bug

## Describe the bug
The frugal score returns a really verbose output with warnings that can be easily changed. 

## Steps to reproduce the bug
```python
# Sample code to reproduce the bug
from datasets.load import load_metric

frugal = load_metric("frugalscore")
frugal.compute(predictions=["Do you like spinachis"], references=["Do you like spinach"])
```

## Expected results
A clear and concise description of the expected results.
```
{'scores': [0.9946]}
```

## Actual results
Specify the actual results or traceback.
```
PyTorch: setting up devices
The default value for the training argument `--report_to` will change in v5 (from all installed integrations to none). In v5, you will need to use `--report_to all` to get the same behavior as now. You should start updating your code and make this info disappear :-).
100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00, 864.09ba/s]
Using amp half precision backend
The following columns in the test set  don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: sentence2, sentence1. If sentence2, sentence1 are not expected by `BertForSequenceClassification.forward`,  you can safely ignore this message.
***** Running Prediction *****
  Num examples = 1
  Batch size = 64
100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00, 4644.85it/s]
 {'scores': [0.9946]}
```

## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.17.0
- Platform: Linux-5.13.0-30-generic-x86_64-with-glibc2.29
- Python version: 3.8.10
- PyArrow version: 7.0.0


Hi @Ierezell, thanks for reporting.

I'm making a PR to suppress those logs from the terminal.
Issue: 'datasets.features' is not a package
State: closed

@albertvillanova 
python 3.9
os: ubuntu 20.04

In conda environment

torch installed by


```/env/bin/pip install torch==1.9.0+cu111 torchvision==0.10.0+cu111 torchaudio==0.9.0 -f https://download.pytorch.org/whl/torch_stable.html```
datasets package is installed by 
```
/env/bin/pip  install datasets==1.8.0

```
During runing the code I have this error 


```
[6]<stderr>:  File "/home/arij/Memory-transformer-with-hierarchical-attention_MLM/env/lib/python3.9/site-packages/torch/serialization.py", line 875, in find_class
[6]<stderr>:    return super().find_class(mod_name, name)
[6]<stderr>:ModuleNotFoundError: No module named 'datasets.features.features'; 'datasets.features' is not a package

```
precisely this error appears when 

torch.load('data_file.pt')
```

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/home/arij/Memory-transformer-with-hierarchical-attention_MLM/env/lib/python3.9/site-packages/torch/serialization.py", line 607, in load
    return _load(opened_zipfile, map_location, pickle_module, **pickle_load_args)
  File "/home/arij/Memory-transformer-with-hierarchical-attention_MLM/env/lib/python3.9/site-packages/torch/serialization.py", line 882, in _load
    result = unpickler.load()
  File "/home/arij/Memory-transformer-with-hierarchical-attention_MLM/env/lib/python3.9/site-packages/torch/serialization.py", line 875, in find_class
    return super().find_class(mod_name, name)
ModuleNotFoundError: No module named 'datasets.features.features'; 'datasets.features' is not a package
```

Why I am getting this error?


Hi @Arij-Aladel,

You are using a very old version of our library `datasets`: 1.8.0
Current version is 2.0.0 (and the previous one was 1.18.4)

Please, try to update `datasets` library and check if the problem persists:
```shell
/env/bin/pip install -U datasets

The problem I can no I have build my project on this version and old version on transformers. I have preprocessed the data again to use it. Thank for your reply
Issue: AttributeError: 'DatasetDict' object has no attribute 'features'
State: closed
Labels: name: bug

## Describe the bug
Receiving the error when trying to check for Dataset features

## Steps to reproduce the bug
from datasets import Dataset
dataset = Dataset.from_pandas(df[['id', 'words', 'bboxes', 'ner_tags', 'image_path']])

dataset.features

## Expected results
A clear and concise description of the expected results.

## Actual results
Getting the following errror

AttributeError: 'DatasetDict' object has no attribute 'features'

## Environment info
Copy-and-paste the text below in your GitHub issue.

- `datasets` version: 1.18.4
- Platform: Linux-4.14.252-131.483.amzn1.x86_64-x86_64-with-glibc2.9
- Python version: 3.6.13
- PyArrow version: 6.0.1


You are likely trying to get the `features` from a `DatasetDict`, a dictionary containing `Datasets`. You probably first want to index into a particular split from your `DatasetDict` i.e. `dataset['train'].features`. 

For example 

```python 
ds = load_dataset('mnist')
ds.features
```
Returns 
```python
---------------------------------------------------------------------------

AttributeError                            Traceback (most recent call last)

[<ipython-input-39-791c1f9df6c2>](https://localhost:8080/#) in <module>()
----> 1 ds.features

AttributeError: 'DatasetDict' object has no attribute 'features'
```

If we look at the dataset variable, we see it is a `DatasetDict`:

```python 
print(ds)
DatasetDict({
    train: Dataset({
        features: ['image', 'label'],
        num_rows: 60000
    })
    test: Dataset({
        features: ['image', 'label'],
        num_rows: 10000
    })
})
```

We can grab the features from a split by indexing into `train`:
```python
ds['train'].features
{'image': Image(decode=True, id=None),
 'label': ClassLabel(num_classes=10, names=['0', '1', '2', '3', '4', '5', '6', '7', '8', '9'], id=None)}
```

Hope that helps 

Yes, Thanks for that clarification,
Issue: datasets.utils.info_utils.NonMatchingChecksumError: Checksums didn't match for dataset source files
State: closed
Labels: name: bug

name: duplicate

## Describe the bug
Can't load the dataset

## Steps to reproduce the bug
```python
# Sample code to reproduce the bug
```
from datasets import load_dataset

dataset = load_dataset('multi_news')
dataset_2=load_dataset("reddit_tifu", "long")


## Actual results
 raise NonMatchingChecksumError(error_msg + str(bad_urls))
datasets.utils.info_utils.NonMatchingChecksumError: Checksums didn't match for dataset source files:
['https://drive.google.com/uc?export=download&id=1ffWfITKFMJeqjT8loC8aiCLRNJpc_XnF']

## Environment info
- `datasets` version: 1.18.4
- Platform: macOS-10.16-x86_64-i386-64bit
- Python version: 3.8.0
- PyArrow version: 6.0.1


Hi @willowdong! These issues were fixed on master. We will have a new release of `datasets` later today. In the meantime, you can avoid these issues by installing `datasets` from master as follows:
```bash
pip install git+https://github.com/huggingface/datasets.git
```

You should force redownload:
```python
dataset = load_dataset("multi_news", download_mode="force_redownload")
dataset_2 = load_dataset("reddit_tifu", "long", download_mode="force_redownload")

Fixed by:
- #3787 
- #3843
Issue: NonMatchingChecksumError on Spider dataset 
State: closed
Labels: name: bug

## Describe the bug
Failure to generate dataset ```spider``` because of checksums error for dataset source files.

## Steps to reproduce the bug
```
from datasets import load_dataset
spider = load_dataset("spider")
```


## Expected results
Checksums should match for files from url ['https://drive.google.com/uc?export=download&id=1_AckYkinAnhqmRQtGsQgUKAnTHxxX5J0']

## Actual results
```
>>> load_dataset("spider")
load_dataset("spider")
Downloading and preparing dataset spider/spider (download: 95.12 MiB, generated: 5.17 MiB, post-processed: Unknown size, total: 100.29 MiB) to /home/user/.cache/huggingface/datasets/spider/spider/1.0.0/79778ebea87c59b19411f1eb3eda317e9dd5f7788a556d837ef25c3ae6e5e8b7...
Traceback (most recent call last):
  File "/home/user/py3_env/lib/python3.8/site-packages/IPython/core/interactiveshell.py", line 3441, in run_code
    exec(code_obj, self.user_global_ns, self.user_ns)
  File "<ipython-input-5-d4cb54197348>", line 1, in <module>
    load_dataset("spider")
  File "/home/user/py3_env/lib/python3.8/site-packages/datasets/load.py", line 1702, in load_dataset
    builder_instance.download_and_prepare(
  File "/home/user/py3_env/lib/python3.8/site-packages/datasets/builder.py", line 594, in download_and_prepare
    self._download_and_prepare(
  File "/home/user/py3_env/lib/python3.8/site-packages/datasets/builder.py", line 665, in _download_and_prepare
    verify_checksums(
  File "/home/user/py3_env/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:
['https://drive.google.com/uc?export=download&id=1_AckYkinAnhqmRQtGsQgUKAnTHxxX5J0']
```


## Environment info
datasets version: 1.18.3
Platform: Ubuntu 20 LTS
Python version: 3.8.10
PyArrow version: 6.0.1 





Hi @kolk, thanks for reporting.

Indeed, Google Drive service recently changed their service and we had to add a fix to our library to cope with that change:
- #3787 

We just made patch release last week: 1.18.4 https://github.com/huggingface/datasets/releases/tag/1.18.4

Please, feel free to update your local `datasets` version, so that you get the fix:
```shell
pip install -U datasets
```
Issue: Dataset viewer issue for IndicParaphrase- the preview doesn't show
State: closed
Labels: name: dataset-viewer

## Dataset viewer issue for '*IndicParaphrase*'

**Link:** *[IndicParaphrase](https://huggingface.co/datasets/ai4bharat/IndicParaphrase/viewer/hi/validation)*

*The preview of the dataset doesn't come up. 
The error on the console is:
Status code:   400
Exception:     FileNotFoundError
Message:       [Errno 2] No such file or directory: '/home/hf/datasets-preview-backend/hi_IndicParaphrase_v1.0.tar'*

Am I the one who added this dataset ? Yes


It seems to have been fixed:

<img width="1534" alt="Capture d’écran 2022-04-12 à 14 10 07" src="https://user-images.githubusercontent.com/1676121/162959599-6b7fef7c-8411-4e03-8f00-90040a658079.png">
Issue: Missing google file for `multi_news` dataset
State: closed
Labels: name: dataset-viewer

## Dataset viewer issue for '*multi_news*'

**Link:** https://huggingface.co/datasets/multi_news

```
Server error

Status code:   400
Exception:     FileNotFoundError
Message:       https://drive.google.com/uc?export=download&id=1vRY2wM6rlOZrf9exGTm5pXj5ExlVwJ0C/multi-news-original/train.src
```

Am I the one who added this dataset ? No


reported by @abidlabs 

related to https://github.com/huggingface/datasets/pull/3843?

`datasets` 1.18.4 fixes the issue when you load the dataset with `load_dataset`.

When loading in streaming mode, the fix is indeed on https://github.com/huggingface/datasets/pull/3843 which will be merged soon :)

That is. The PR #3843 was just opened a bit later we had made our 1.18.4 patch release...
Once merged, that will fix this issue. 

OK. Should fix the viewer for 50 datasets

<img width="148" alt="Capture d’écran 2022-03-14 à 11 51 02" src="https://user-images.githubusercontent.com/1676121/158157853-6c544a47-2d6d-4ac4-964a-6f10951ec36b.png">
Issue: Cannot load beans dataset (Couldn't reach the dataset)
State: closed
Labels: name: dataset bug

## Describe the bug
The beans dataset is unavailable to download.

## Steps to reproduce the bug
```python
from datasets import load_dataset
ds = load_dataset('beans')
```

## Expected results
The dataset would be downloaded with no issue.

## Actual results

```
ConnectionError: Couldn't reach https://storage.googleapis.com/ibeans/train.zip (error 403)
```

[It looks like the billing of this project has been disabled because it is associated with a delinquent account.](https://storage.googleapis.com/ibeans/train.zip )

## Environment info
Google Colab


Hi ! A pull request is open to fix the dataset, we'll release a patch soon with a new release of `datasets` :)
Issue: IterableDataset columns and feature types
State: open
Labels: name: generic discussion

name: streaming

Right now, an IterableDataset (e.g. when streaming a dataset) doesn't require to know the list of columns it contains, nor their types: `my_iterable_dataset.features` may be `None`

However it's often interesting to know the column types and types. This helps knowing what's inside your dataset without having to manually check a few examples, and this is useful to prepare a processing pipeline or to train models.

Here are a few cases that lead to `features` being `None`:

1. when loading a dataset with `load_dataset` on CSV, JSON Lines, etc. files: type inference is only done when iterating over the dataset
2. when calling `map`, because we don't know in advance what's the output of the user's function passed to `map`
3. when calling `rename_columns`, `remove_columns`, etc. because they rely on `map`

Things we can consider, for each point above:

1.a infer the type automatically from the first samples on the dataset using prefetching, when the dataset builder doesn't provide the `features`
2.a allow the user to specify the `features` as an argument to `map` (this would be consistent with the non-streaming API)
2.b prefetch the first output value to infer the type
3.a don't rely on `map` directly and reuse the previous `features` and rename/remove the corresponding ones

The thing is that prefetching can take a few seconds, while the operations above are instantaneous since no data are downloaded. Therefore I'm not sure whether this solution may be worth it. Maybe prefetching could also be done when explicitly asked by the user

cc @mariosasko @albertvillanova 

#self-assign

@alvarobartt I've assigned you the issue since I'm not actively working on it.

Cool thanks @mariosasko I'll try to fix it in the upcoming days, thanks!

@lhoestq so in order to address what’s not completed in this issue, do you think it makes sense to add a param `features` to `IterableDataset.map` so that the output features right after the `map` are defined there? 

Yes that would be ideal IMO, thanks again for the help :)

@lhoestq cool then if you agree I can work on that! I’ll also update the docs accordingly once done, thanks!

I've already started with a PR as a draft @lhoestq, should we also try to look for a way to explicitly request pre-fetching right after a map operation is applied, so that the features are inferred if the user says explicitly so? Thanks!

> should we also try to look for a way to explicitly request pre-fetching right after a map operation is applied, so that the features are inferred if the user says explicitly so?

Right now one can use `ds = ds._resolve_features()` do to so. It can be used after `map` or `load_dataset` if the features are not known. Maybe we can make this method public ?
Issue: The metric Meteor doesn't work for nltk ==3.6.4
State: closed
Labels: name: bug

## Describe the bug
Using the metric Meteor with nltk == 3.6.4 gives a TypeError:
TypeError: descriptor 'lower' for 'str' objects doesn't apply to a 'list' object

## Steps to reproduce the bug
```python
import datasets
metric = datasets.load_metric("meteor")
predictions = ["hello world"]
references = ["hello world"]
metric.compute(predictions=predictions, references=references)
```

## Expected results
TypeError: descriptor 'lower' for 'str' objects doesn't apply to a 'list' object

I think this TypeError exists because input sentences are tokenized into lists of tokens and the str.lower() is applied to this list of tokens.

## Actual results
No error but a meteor score

## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.18.3
- Platform: linux
- Python version: 3.8.12
- PyArrow version: 7.0.0


Hi @zhaowei-wang98, thanks for reporting.

We are fixing it...
Issue: Align metadata to DCAT/DCAT-AP
State: open
Labels: name: enhancement

**Is your feature request related to a problem? Please describe.**
Align to DCAT metadata to describe datasets

**Describe the solution you'd like**
Reuse terms and structure from DCAT in the metadata file, ideally generate a json-ld file dcat compliant

**Describe alternatives you've considered**


**Additional context**
DCAT is a W3C standard extended in Europe with DCAT-AP, an example is data.europa.eu publishing datasets metadata in DCAT-AP
Issue: HTTP error 504 Server Error: Gateway Time-out
State: closed

I am trying to push a large dataset(450000+) records with the help of `push_to_hub()`
While pushing, it gives some error like this.

```
Traceback (most recent call last):
  File "data_split_speech.py", line 159, in <module>
    data_new_2.push_to_hub("user-name/dataset-name",private=True)
  File "/opt/conda/lib/python3.8/site-packages/datasets/dataset_dict.py", line 951, in push_to_hub
    repo_id, split, uploaded_size, dataset_nbytes = self[split]._push_parquet_shards_to_hub(
  File "/opt/conda/lib/python3.8/site-packages/datasets/arrow_dataset.py", line 3556, in _push_parquet_shards_to_hub
    api.upload_file(
  File "/opt/conda/lib/python3.8/site-packages/huggingface_hub/hf_api.py", line 1017, in upload_file
    raise err
  File "/opt/conda/lib/python3.8/site-packages/huggingface_hub/hf_api.py", line 1008, in upload_file
    r.raise_for_status()
  File "/opt/conda/lib/python3.8/site-packages/requests/models.py", line 953, in raise_for_status
    raise HTTPError(http_error_msg, response=self)
requests.exceptions.HTTPError: 504 Server Error: Gateway Time-out for url: https://huggingface.co/api/datasets/user-name/dataset-name/upload/main/data/train2-00041-of-00064.parquet

```
Can anyone help me to resolve this issue.


is pushing directly with git (and git-lfs) an option for you?

I have installed git-lfs and doing this push with that


yes but is there any way you could try pushing with `git` command line directly instead of `push_to_hub`?

Okay. I didnt saved the dataset to my local machine. So, I processed the dataset and pushed it directly to the hub. I think I should try saving those dataset to my local machine by `save_to_disk` and then push it with git command line

cc @lhoestq @albertvillanova @LysandreJik because maybe I'm giving dumb advice here 😅 

`push_to_hub` is the preferred way of uploading a dataset to the Hub, which can then be reloaded with `load_dataset`. Feel free to try again and see if the server is working as expected now. Maybe we can add a retry mechanism in the meantime to workaround 504 errors.

Regarding `save_to_disk`, this must only be used for local serialization (because it's uncompressed and compatible with memory-mapping). If you upload a dataset saved with `save_to_disk` to the Hub, then to reload it you will have to download/clone the repository locally by yourself and use `load_from_disk`.
Issue: Making the Hub the place for datasets in Portuguese 
State: open
Labels: name: dataset request

Let's make Hugging Face Datasets the central hub for datasets in Portuguese :)

**Motivation**. Datasets are currently quite scattered and an open-source central point such as the Hugging Face Hub would be ideal to support the growth of the Portuguese speaking community.

What are some datasets in Portuguese worth integrating into the Hugging Face hub?

Special thanks to @augusnunes for his collaboration on identifying the first ones:

-  [NILC - USP](http://www.nilc.icmc.usp.br/nilc/index.php/tools-and-resources).

Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).

cc @osanseviero




Hi @omarespejel! I think the philosophy for `datasets` issues is to create concrete issues with proposals to add a specific, individual dataset rather than umbrella issues for things such as datasets for a language, since we could end up with hundreds of issues (one per language). I see NILC - USP has many datasets, I would suggest to either create an issue for their datasets, or even better, we are trying to push to upload datasets as community datasets instead of adding them to the core library as guided in https://huggingface.co/docs/datasets/share. That would have the additional benefit that the dataset would live under the NILC organization.

@lhoestq correct me if I'm wrong please 😄
Issue: big_patent cased version
State: closed
Labels: name: dataset request

Hi! I am interested in working with the big_patent dataset.

In Tensorflow, there are a number of versions of the dataset:

- 1.0.0 : lower cased tokenized words
- 2.0.0 : Update to use cased raw strings
- 2.1.2 (default): Fix update to cased raw strings.

The version in the huggingface `datasets` library is the 1.0.0. I would be very interested in using the 2.1.2 cased version (used more, recently, for example in the Pegasus paper), but it does not seem to be supported (I tried using the `revision` parameter in `load_datasets`). Is there a way to already load it, or would it be possible to add that version? 

To follow up on this: the cased and uncased versions actually contain different content, and the cased one is easier since it contains a Summary of the Invention in the input.

See the paper describing the issue here:
https://aclanthology.org/2022.gem-1.34/

Thanks for proposing the addition of the cased version of this dataset and for pinging again recently.

I have just merged a PR that adds the cased version: https://huggingface.co/datasets/big_patent/discussions/3

The cased version (2.1.2) is the default one:
```python
ds = load_dataset("big_patent", "all")
```

To use the 1.0.0 version (lower cased tokenized words), pass both parameters `codes` and `version`:
```python
ds = load_dataset("big_patent", codes="all", version="1.0.0")
```

Closed by: https://huggingface.co/datasets/big_patent/discussions/3
Issue: Order of dataset changes due to glob.glob.
State: open
Labels: name: generic discussion

## Describe the bug

After discussion with @lhoestq, just want to mention here that `glob.glob(...)` should always be used in combination with `sorted(...)` to make sure the list of files returned by `glob.glob(...)` doesn't change depending on the OS system. 

There are currently multiple datasets that use `glob.glob()` without making use of `sorted(...)` even the streaming download manager (if I'm not mistaken): 
https://github.com/huggingface/datasets/blob/c14bfeb4af89da14f870de5ddaa584b08aa08eeb/src/datasets/utils/streaming_download_manager.py#L483

I agree using `glob.glob` alone is bad practice because it's not deterministic. Using `sorted` is a nice solution.

Note that the `xglob` function you are referring to in the `streaming_download_manager.py` code just extends `glob.glob` for URLs - we don't change its behavior. That's why it has no `sorted()`
Issue: Bad error message when loading private dataset
State: closed
Labels: name: bug

## Describe the bug

A pretty common behavior of an interaction between the Hub and datasets is the following.
An organization adds a dataset in private mode and wants to load it afterward.


```python
from transformers import load_dataset

ds = load_dataset("NewT5/dummy_data", "dummy")
```

This command then fails with:

```bash
FileNotFoundError: Couldn't find a dataset script at /home/patrick/NewT5/dummy_data/dummy_data.py or any data file in the same directory. Couldn't find 'NewT5/dummy_data' on the Hugging Face Hub either: FileNotFoundError: Dataset 'NewT5/dummy_data' doesn't exist on the Hub
```

**even though** the user has access to the website `NewT5/dummy_data` since she/he is part of the org. 

We need to improve the error message here similar to how @sgugger, @LysandreJik and @julien-c have done it for transformers IMO.

## Steps to reproduce the bug

E.g. execute the following code to see the different error messages between `transformes` and `datasets`.

1. Transformers
```python
from transformers import BertModel

BertModel.from_pretrained("NewT5/dummy_model")
```

The error message is clearer here - it gives:

```
OSError: patrickvonplaten/gpt2-xl is not a local folder and is not a valid model identifier listed on 'https://huggingface.co/models'
If this is a private repository, make sure to pass a token having permission to this repo with `use_auth_token` or log in with `huggingface-cli login` and pass `use_auth_token=True`.
```

Let's maybe do the same for datasets? The PR was introduced to `transformers` here:
https://github.com/huggingface/transformers/pull/15261

## Expected results

Better error message

## 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: 1.18.4.dev0
- Platform: Linux-5.15.15-76051515-generic-x86_64-with-glibc2.34
- Python version: 3.9.7
- PyArrow version: 6.0.1



We raise the error “ FileNotFoundError: can’t find the dataset” mainly to follow best practice in security (otherwise users could be able to guess what private repositories users/orgs may have)

We can indeed reformulate this and add the "If this is a private repository,..." part !

Resolved via https://github.com/huggingface/datasets/pull/4536