ahmedfarazsyk/datasets-github-issues huggingface dataset:
ExpectedMoreSplits error on load_dataset when upgrading to 2.19.0
Author: ebsmothers
State: open

### Describe the bug

Hi there, thanks for the great library! We have been using it a lot in torchtune and it's been a huge help for us. 

Regarding the bug: the same call to `load_dataset` errors with `ExpectedMoreSplits` in 2.19.0 after working fine in 2.18.0. Full details given in the repro below.

### Steps to reproduce the bug

On 2.18.0, things work fine:
```
# First clear the locally cached dataset
rm -r ~/.cache/huggingface/datasets/lvwerra___stack-exchange-paired
pip install "datasets==2.18.0"
python3
>>> from datasets import load_dataset
>>> dataset = load_dataset('lvwerra/stack-exchange-paired', split='train', data_dir='data/rl')
```

On 2.19.0, they do not:
```
# First clear the locally cached dataset
rm -r ~/.cache/huggingface/datasets/lvwerra___stack-exchange-paired
pip install "datasets==2.19.0"
python3
>>> from datasets import load_dataset
>>> dataset = load_dataset('lvwerra/stack-exchange-paired', split='train', data_dir='data/rl')
```

The stack trace I see from the 2.19.0 version of load_dataset can be seen [here](https://gist.github.com/ebsmothers/f9b1f1949bee7030a8d7bb8a491550d2).

(Maybe unsurprising but) notably if I do not delete the cache first I am able to load the dataset successfully. So based on this I suspect the cause is somewhere in the download logic.

### Expected behavior

Download the dataset successfully :)

### Environment info

- `datasets` version: 2.19.0
- Platform: Linux-5.12.0-0_fbk16_zion_7661_geb00762ce6d2-x86_64-with-glibc2.34
- Python version: 3.11.9
- `huggingface_hub` version: 0.22.2
- PyArrow version: 16.0.0
- Pandas version: 2.2.2
- `fsspec` version: 2024.3.1

Comments: Get same error on same datasets too.

+1

same error
largelisttype not supported (.from_polars())
Author: Modexus
State: closed

### Describe the bug

The following code fails because LargeListType is not supported.
This is especially a problem for .from_polars since polars uses LargeListType.


### Steps to reproduce the bug

```python
import datasets
import polars as pl

df = pl.DataFrame({"list": [[]]})
datasets.Dataset.from_polars(df)
```

### Expected behavior

Convert LargeListType to list.

### Environment info

- `datasets` version: 2.19.1.dev0
- Platform: Linux-6.8.7-200.fc39.x86_64-x86_64-with-glibc2.38
- Python version: 3.12.2
- `huggingface_hub` version: 0.22.2
- PyArrow version: 16.0.0
- Pandas version: 2.1.4
- `fsspec` version: 2024.3.1
Load and save from/to disk no longer accept pathlib.Path
Author: albertvillanova
State: open
Labels: name: bug

Reported by @vttrifonov at https://github.com/huggingface/datasets/pull/6704#issuecomment-2071168296:
> This change is breaking in 
> https://github.com/huggingface/datasets/blob/f96e74d5c633cd5435dd526adb4a74631eb05c43/src/datasets/arrow_dataset.py#L1515
> when the input is `pathlib.Path`. The issue is that `url_to_fs` expects a `str` and cannot deal with `Path`. `get_fs_token_paths` converts to `str` so it is not a problem

This change was introduced in:
- #6704
Loading a remote dataset fails in the last release (v2.19.0)
Author: zrthxn
State: open

While loading a dataset with multiple splits I get an error saying `Couldn't find file at <URL>`

I am loading the dataset like so, nothing out of the ordinary.
This dataset needs a token to access it.
```
token="hf_myhftoken-sdhbdsjgkhbd"
load_dataset("speechcolab/gigaspeech", "test", cache_dir=f"gigaspeech/test", token=token)
```

I get the following error
![Screenshot 2024-04-19 at 11 03 07 PM](https://github.com/huggingface/datasets/assets/35369637/8dce757f-08ff-45dd-85b5-890fced7c5bc)

Now you can see that the URL that it is trying to reach has the JSON object of the dataset split appended to the base URL. I think this may be due to a newly introduced issue.

I did not have this issue with the previous version of the datasets. Everything was fine for me yesterday and after the release 12 hours ago, this seems to have broken. Also, the dataset in question runs custom code and I checked and there have been no commits to the dataset on Huggingface in 6 months.

### Steps to reproduce the bug

Since this happened with one particular dataset for me, I am listing steps to use that dataset.
1. Open https://huggingface.co/datasets/speechcolab/gigaspeech and fill the form to get access.
2. Create a token on your huggingface account with read access.
3. Run the following line, substituing `<your_token_here>` with your token.
```
load_dataset("speechcolab/gigaspeech", "test", cache_dir=f"gigaspeech/test", token="<your_token_here>")
```

### Expected behavior

Be able to load the dataset in question.

### Environment info

datasets == 2.19.0
python == 3.10
kernel == Linux 6.1.58+
Give more details in `DataFilesNotFoundError` when getting the config names
Author: severo
State: open
Labels: name: enhancement

### Feature request

After https://huggingface.co/datasets/cis-lmu/Glot500/commit/39060e01272ff228cc0ce1d31ae53789cacae8c3, the dataset viewer gives the following error:

```
{
  "error": "Cannot get the config names for the dataset.",
  "cause_exception": "DataFilesNotFoundError",
  "cause_message": "No (supported) data files found in cis-lmu/Glot500",
  "cause_traceback": [
    "Traceback (most recent call last):\n",
    " File \"/src/services/worker/src/worker/job_runners/dataset/config_names.py\", line 73, in compute_config_names_response\n config_names = get_dataset_config_names(\n",
    " File \"/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py\", line 347, in get_dataset_config_names\n dataset_module = dataset_module_factory(\n",
    " File \"/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py\", line 1873, in dataset_module_factory\n raise e1 from None\n",
    " File \"/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py\", line 1854, in dataset_module_factory\n return HubDatasetModuleFactoryWithoutScript(\n",
    " File \"/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py\", line 1245, in get_module\n module_name, default_builder_kwargs = infer_module_for_data_files(\n",
    " File \"/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py\", line 595, in infer_module_for_data_files\n raise DataFilesNotFoundError(\"No (supported) data files found\" + (f\" in {path}\" if path else \"\"))\n",
    "datasets.exceptions.DataFilesNotFoundError: No (supported) data files found in cis-lmu/Glot500\n"
  ]
}
```

because the deleted files were still listed in the README, see https://huggingface.co/datasets/cis-lmu/Glot500/discussions/4

Ideally, the error message would include the name of the first configuration with missing files, to help the user understand how to fix it. Here, it would tell that configuration `aze_Ethi` has no supported data files, instead of telling that the `cis-lmu/Glot500` *dataset* has no supported data files (which is not true).

### Motivation

Giving more detail in the error would help the Datasets Hub users to debug why the dataset viewer does not work.

### Your contribution

Not sure how to best fix this, as there are a lot of loops on the dataset configs in the traceback methods. "maybe" it would be easier to handle if the code was completely isolating each config.
`map` with `num_proc` > 1 leads to OOM
Author: bhavitvyamalik
State: open

### Describe the bug

When running `map` on parquet dataset loaded from local machine, the RAM usage increases linearly eventually leading to OOM. I was wondering if I should I save the `cache_file` after every n steps in order to prevent this?

### Steps to reproduce the bug



```
ds = load_dataset("parquet", data_files=dataset_path, split="train")
ds = ds.shard(num_shards=4, index=0)

ds = ds.cast_column("audio", datasets.features.Audio(sampling_rate=16_000))
ds = ds.map(prepare_dataset,
            num_proc=32,
            writer_batch_size=1000,
            keep_in_memory=False,
            desc="preprocess dataset")
```

```
def prepare_dataset(batch):
    # load audio
    sample = batch["audio"]

    inputs = feature_extractor(sample["array"], sampling_rate=16000)
    batch["input_values"] = inputs.input_values[0]
    batch["input_length"] = len(sample["array"].squeeze())

    return batch
```

### Expected behavior

It shouldn't run into OOM problem.

### Environment info

- `datasets` version: 2.18.0
- Platform: Linux-5.4.0-91-generic-x86_64-with-glibc2.17
- Python version: 3.8.19
- `huggingface_hub` version: 0.22.2
- PyArrow version: 15.0.2
- Pandas version: 2.0.3
- `fsspec` version: 2024.2.0

Comments: Hi ! You can try to reduce `writer_batch_size`. It corresponds to the number of samples that stay in RAM before being flushed to disk
Allow deleting a subset/config from a no-script dataset
Author: albertvillanova
State: closed
Labels: name: enhancement

As proposed by @BramVanroy, it would be neat to have this functionality through the API.

Comments: Probably best to implement this as a CLI command?

Thanks for your comment, @mariosasko. Or maybe both (in Python and as CLI command)? The Python command would be just the reverse of `push_to_hub`...

I am working on a draft implementation, so we can discuss about the API and UX.

2nd time I've come here in the past few days so for reference this doesn't work for me at the moment (token auth error despite successful `whoami` and all auths applied) so I resorted to [reverting](https://discuss.huggingface.co/t/how-to-revert-to-an-earlier-commit-on-a-repo/65735/2) to a previous commit (after installing git lfs)

```
# git lfs install
GIT_LFS_SKIP_SMUDGE=1 git clone https://huggingface.co/datasets/USER/REPO
cd REPO
git reset --hard HASH
git push --force
```
Make convert_to_parquet CLI command create script branch
Author: albertvillanova
State: closed
Labels: name: enhancement

As proposed by @severo, maybe we should add this functionality as well to the CLI command to convert a script-dataset to Parquet. See: https://github.com/huggingface/datasets/pull/6795#discussion_r1562819168
> When providing support, we sometimes suggest that users store their script in a script branch. What do you think of this alternative to deleting the files?
got fileNotFound
Author: laoniandisko
State: closed

### Describe the bug

When I use load_dataset to load the nyanko7/danbooru2023 data set, the cache is read in the form of a symlink. There may be a problem with the arrow_dataset initialization process and I get FileNotFoundError: [Errno 2] No such file or directory: '2945000.jpg'

### Steps to reproduce the bug

#code show as below
from datasets import load_dataset
data = load_dataset("nyanko7/danbooru2023",cache_dir=<symlink>)
data["train"][0]

### Expected behavior

I should get this result:
{'image': <PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=365x256 at 0x7FB730CB4070>, 'label': 0}

### Environment info

datasets==2.12.0
python==3.10.14


Comments: Hi! I'll open a PR on the Hub to fix this, but please use the Hub's [Community tab](https://huggingface.co/datasets/nyanko7/danbooru2023/discussions) to report such issues in the future.

I've opened a [PR](https://huggingface.co/datasets/nyanko7/danbooru2023/discussions/8) in the repo, so let's continue the discussion there
`DatasetBuilder._split_generators` incomplete type annotation
Author: JonasLoos
State: closed

### Describe the bug

The [`DatasetBuilder._split_generators`](https://github.com/huggingface/datasets/blob/0f27d7b77c73412cfc50b24354bfd7a3e838202f/src/datasets/builder.py#L1449) function has currently the following signature:

```python
class DatasetBuilder:
    def _split_generators(self, dl_manager: DownloadManager):
        ...
```

However, the `dl_manager` argument can also be of type [`StreamingDownloadManager`](https://github.com/huggingface/datasets/blob/0f27d7b77c73412cfc50b24354bfd7a3e838202f/src/datasets/download/streaming_download_manager.py#L962), which has different functionality. For example, the `download` function doesn't download, but rather just returns the given url(s). 

I suggest changing the function signature to:

```python
class DatasetBuilder:
    def _split_generators(self, dl_manager: Union[DownloadManager, StreamingDownloadManager]):
        ...
```

and also adjust the docstring accordingly.

I would like to create a Pull Request to fix this, and have the following questions:
* Are there also other options than `DownloadManager`, and `StreamingDownloadManager`?
* Should this also be changed in other functions?

### Steps to reproduce the bug

Minimal example to print the different class names:

```python
import tempfile
from datasets import load_dataset

example = b'''
from datasets import GeneratorBasedBuilder, DatasetInfo, Features, Value, SplitGenerator

class Test(GeneratorBasedBuilder):
    def _info(self):
        return DatasetInfo(features=Features({"x": Value("int64")}))
    def _split_generators(self, dl_manager):
        print(type(dl_manager))
        return [SplitGenerator('test')]
    def _generate_examples(self):
        yield 0, {'x': 42}
'''

with tempfile.NamedTemporaryFile(suffix='.py') as f:
    f.write(example)
    f.flush()
    load_dataset(f.name, streaming=False)
    load_dataset(f.name, streaming=True)
```

### Expected behavior

complete type annotations

### Environment info

/

Comments: Good catch! Feel free to open a PR with the suggested fix :).

There is also the [`MockDownloadManager`](https://github.com/JonasLoos/datasets/blob/main/src/datasets/download/mock_download_manager.py#L33), which seems like it might get passed here too. However, to me, it doesn't really seem relevant to the users of the datasets library, so I would just ignore it. What do you think, @mariosasko?

The API (`dummy_data` CLI command ) that uses the `MockDownloadManager` has been deprecated, so ignoring it sounds good!
CI is broken due to hf-internal-testing/dataset_with_script
Author: albertvillanova
State: closed
Labels: name: bug

CI is broken for test_load_dataset_distributed_with_script. See: https://github.com/huggingface/datasets/actions/runs/8614926216/job/23609378127
```
FAILED tests/test_load.py::test_load_dataset_distributed_with_script[None] - assert False
 +  where False = all(<generator object test_load_dataset_distributed_with_script.<locals>.<genexpr> at 0x7f0c741de3b0>)
FAILED tests/test_load.py::test_load_dataset_distributed_with_script[force_redownload] - assert False
 +  where False = all(<generator object test_load_dataset_distributed_with_script.<locals>.<genexpr> at 0x7f0be45f6ea0>)
```

Comments: Finally:
- the initial issue seems it was temporary
- there is a different issue now: https://github.com/huggingface/datasets/actions/runs/8627153993/job/23646584590?pr=6797
```
FAILED tests/test_load.py::ModuleFactoryTest::test_HubDatasetModuleFactoryWithParquetExport - datasets.utils._dataset_viewer.DatasetViewerError: No exported Parquet files available.
FAILED tests/test_load.py::ModuleFactoryTest::test_HubDatasetModuleFactoryWithParquetExport_errors_on_wrong_sha - datasets.utils._dataset_viewer.DatasetViewerError: No exported Parquet files available.
FAILED tests/test_load.py::test_load_dataset_builder_for_community_dataset_with_script - AssertionError: assert 'dataset_with_script' == 'parquet'
  
  - parquet
  + dataset_with_script
```

Maybe related to `hf-internal-testing/dataset_with_script` dataset: https://huggingface.co/datasets/hf-internal-testing/dataset_with_script

This URL: https://datasets-server.huggingface.co/parquet?dataset=hf-internal-testing/dataset_with_script
raises:
> {"error":"The dataset viewer doesn't support this dataset because it runs arbitrary python code. Please open a discussion in the discussion tab if you think this is an error and tag @lhoestq and @severo."}

Was there a recent change on the Hub enforcing this behavior?

OK, I just saw this PR:
- https://github.com/huggingface/dataset-viewer/pull/2689

Once merged and deployed, it should fix the issue.

Once the script-dataset has been allowed in the dataset-viewer, we should fix our test to make the CI pass.

I am addressing this.
Loading just one particular split is not possible for imagenet-1k
Author: PaulPSta
State: open

### Describe the bug

I'd expect the following code to download just the validation split but instead I get all data on my disk (train, test and validation splits)

`
from datasets import load_dataset

dataset = load_dataset("imagenet-1k", split="validation", trust_remote_code=True)
`

Is it expected to work like that? 

### Steps to reproduce the bug

1. Install the required libraries (python, datasets, huggingface_hub)
2. Login using huggingface cli
2. Run the code in the description

### Expected behavior

Just a single (validation) split should be downloaded.

### Environment info

python: 3.12.2
datasets: 2.18.0
huggingface_hub: 0.22.2

Comments: +1

+1
`add_faiss_index` raises ValueError: not enough values to unpack (expected 2, got 1)
Author: NeuralFlux
State: closed

### Describe the bug

Calling `add_faiss_index` on a `Dataset` with a column argument raises a ValueError. The following is the trace

```python
    214 def replacement_add(self, x):
    215     """Adds vectors to the index.
    216     The index must be trained before vectors can be added to it.
    217     The vectors are implicitly numbered in sequence. When `n` vectors are
   (...)
    224         `dtype` must be float32.
    225     """
--> 227     n, d = x.shape
    228     assert d == self.d
    229     x = np.ascontiguousarray(x, dtype='float32')

ValueError: not enough values to unpack (expected 2, got 1)
```

### Steps to reproduce the bug

1. Load any dataset like `ds = datasets.load_dataset("wikimedia/wikipedia", "20231101.en")["train"]`
2. Add an FAISS index on any column `ds.add_faiss_index('title')`

### Expected behavior

The index should be created

### Environment info

- `datasets` version: 2.18.0
- Platform: Linux-6.5.0-26-generic-x86_64-with-glibc2.35
- Python version: 3.9.19
- `huggingface_hub` version: 0.22.2
- PyArrow version: 15.0.2
- Pandas version: 2.2.1
- `fsspec` version: 2024.2.0
- `faiss-cpu` version: 1.8.0

Comments: I realized I was passing a string column to this instead of float. Is it possible to add a warning or error to prevent users from falsely believing there's a bug?

Hello!

I agree that we could add some safeguards around the type of `ds[column]`. At least for FAISS, we need the column to be made of embeddings as FAISS doesn't perform the embeddings itself.

I can propose a PR sometime this week.

@Dref360 thanks for the initiative!
A Question About the Map Function
Author: yslanprime
State: closed

### Describe the bug

Hello,

I have a question regarding the map function in the Hugging Face datasets.

The situation is as follows: when I load a jsonl file using load_dataset(..., streaming=False), and then utilize the map function to process it, I specify that the returned example should be of type Torch.tensor. However, I noticed that after applying the map function, the datatype automatically changes to List, which leads to errors in my program.

I attempted to use load_dataset(..., streaming=True), and this issue no longer occurs. I'm not entirely clear on why this happens. Could you please provide some insights into this?

### Steps to reproduce the bug

1.dataset =  load_dataset(xxx, streaming = False)
2. dataset.map(function), function will return torch.Tensor.
3. you will find the format of data in dataset is List.

### Expected behavior

I expected to receieve the format of data is torch.Tensor.

### Environment info

2.18.0

Comments: All data is saved in the arrow format on disk.
If you return a tensor it gets converted to arrow before saving to disk when using map.

To get a tensor when you access data elements you can use `dataset.set_format("pt")`.
Note that this just changes how the data is loaded, not how it is stored.

> All data is saved in the arrow format on disk. If you return a tensor it gets converted to arrow before saving to disk when using map.
> 
> To get a tensor when you access data elements you can use `dataset.set_format("pt")`. Note that this just changes how the data is loaded, not how it is stored.

Thank you very much for your explanation, I understand what you mean now. So you're saying that when streaming=True, there's no need to convert it to the arrow format and save it to disk. But if we directly load all formats and then convert them into the arrow format after passing through the map function, it will convert torch.Tensor into a List. I see.
Dataset.to_csv() missing commas in columns with lists
Author: mpickard-dataprof
State: open

### Describe the bug

The `to_csv()` method does not output commas in lists.  So when the Dataset is loaded back in the data structure of the column with a list is not correct.

Here's an example:

Obviously, it's not as trivial as inserting commas in the list, since its a comma-separated file.  But hopefully there's a way to export the list in a way that it'll be imported by `load_dataset()` correctly.

### Steps to reproduce the bug

Here's some code to reproduce the bug:


```python
from datasets import Dataset

ds = Dataset.from_dict(
    {
        "pokemon": ["bulbasaur", "squirtle"],
        "type": ["grass", "water"]
    }
)

def ascii_to_hex(text):
    return [ord(c) for c in text]

ds = ds.map(lambda x: {"int": ascii_to_hex(x['pokemon'])})

ds.to_csv('../output/temp.csv')
```

temp.csv then contains:
```

### Expected behavior

ACTUAL OUTPUT:
```
pokemon,type,int
bulbasaur,grass,[ 98 117 108  98  97 115  97 117 114]
squirtle,water,[115 113 117 105 114 116 108 101]
```

EXPECTED OUTPUT:
```
pokemon,type,int
bulbasaur,grass,[98, 117, 108,  98,  97, 115,  97, 117, 114]
squirtle,water,[115, 113, 117, 105, 114, 116, 108, 101]
```

or probably something more like this since it's a CSV file:
```
pokemon,type,int
bulbasaur,grass,"[98, 117, 108,  98,  97, 115,  97, 117, 114]"
squirtle,water,"[115, 113, 117, 105, 114, 116, 108, 101]"
```

### Environment info

### Package Version
Name: datasets
Version: 2.16.1

### Python
version: 3.10.12


### OS Info
PRETTY_NAME="Ubuntu 22.04.4 LTS"
NAME="Ubuntu"
VERSION_ID="22.04"
VERSION="22.04.4 LTS (Jammy Jellyfish)"
VERSION_CODENAME=jammy
ID=ubuntu
ID_LIKE=debian
...
UBUNTU_CODENAME=jammy

Comments: Hello!

This is due to how pandas write numpy arrays to csv. [Source](https://stackoverflow.com/questions/54753179/to-csv-saves-np-array-as-string-instead-of-as-a-list)
To fix this, you can convert them to list yourselves.

```python
df = ds.to_pandas()
df['int'] = df['int'].apply(lambda arr: list(arr))
df.to_csv(index=False, '../output/temp.csv')
```

I think it would be good if `datasets` would do the conversion itself, but it's a breaking change and I would wait for the greenlight from someone from HF.