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https://api.github.com/repos/huggingface/datasets/issues/7087 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7087/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7087/comments | https://api.github.com/repos/huggingface/datasets/issues/7087/events | https://github.com/huggingface/datasets/issues/7087 | 2,447,158,643 | I_kwDODunzps6R3K1z | 7,087 | Unable to create dataset card for Lushootseed language | {
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"Thanks for reporting.\r\n\r\nIt is weird, because the language entry is in the list. See: https://github.com/huggingface/huggingface.js/blob/98e32f0ed4ee057a596f66a1dec738e5db9643d5/packages/languages/src/languages_iso_639_3.ts#L15186-L15189\r\n\r\nI have reported the issue:\r\n- https://github.com/huggingface/hug... | 2024-08-04T14:27:04Z | 2024-08-06T06:59:23Z | 2024-08-06T06:59:22Z | NONE | null | null | {
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} | ### Feature request
While I was creating the dataset which contained all documents from the Lushootseed Wikipedia, the dataset card asked me to enter which language the dataset was in. Since Lushootseed is a critically endangered language, it was not available as one of the options. Is it possible to allow entering languages that aren't available in the options?
### Motivation
I'd like to add more information about my dataset in the dataset card, and the language is one of the most important pieces of information, since the entire dataset is primarily concerned collecting Lushootseed documents.
### Your contribution
I can submit a pull request | {
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"@lhoestq I detected this regression over on [DataDreamer](https://github.com/datadreamer-dev/DataDreamer)'s test suite. I put in these [monkey patches](https://github.com/datadreamer-dev/DataDreamer/blob/4cbaf9f39cf7bedde72bbaa68346e169788fbecb/src/_patches/datasets_reset_state_hack.py) in case that fixed it our t... | 2024-07-31T13:01:59Z | 2024-08-22T14:49:37Z | 2024-08-22T14:49:07Z | NONE | null | null | {
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} | ### Describe the bug
In the latest version of datasets there is a major regression, after creating an `IterableDataset` from a generator and applying a few operations (`map`, `select`), you can no longer iterate through the dataset multiple times.
The issue seems to stem from the recent addition of "resumable IterableDatasets" (#6658) (@lhoestq). It seems like it's keeping state when it shouldn't.
### Steps to reproduce the bug
Minimal Reproducible Example (comparing `datasets==2.17.0` and `datasets==2.20.0`)
```
#!/bin/bash
# List of dataset versions to test
versions=("2.17.0" "2.20.0")
# Loop through each version
for version in "${versions[@]}"; do
# Install the specific version of the datasets library
pip3 install -q datasets=="$version" 2>/dev/null
# Run the Python script
python3 - <<EOF
from datasets import IterableDataset
from datasets.features.features import Features, Value
def test_gen():
yield from [{"foo": i} for i in range(10)]
features = Features([("foo", Value("int64"))])
d = IterableDataset.from_generator(test_gen, features=features)
mapped = d.map(lambda row: {"foo": row["foo"] * 2})
column = mapped.select_columns(["foo"])
print("Version $version - Iterate Once:", list(column))
print("Version $version - Iterate Twice:", list(column))
EOF
done
```
The output looks like this:
```
Version 2.17.0 - Iterate Once: [{'foo': 0}, {'foo': 2}, {'foo': 4}, {'foo': 6}, {'foo': 8}, {'foo': 10}, {'foo': 12}, {'foo': 14}, {'foo': 16}, {'foo': 18}]
Version 2.17.0 - Iterate Twice: [{'foo': 0}, {'foo': 2}, {'foo': 4}, {'foo': 6}, {'foo': 8}, {'foo': 10}, {'foo': 12}, {'foo': 14}, {'foo': 16}, {'foo': 18}]
Version 2.20.0 - Iterate Once: [{'foo': 0}, {'foo': 2}, {'foo': 4}, {'foo': 6}, {'foo': 8}, {'foo': 10}, {'foo': 12}, {'foo': 14}, {'foo': 16}, {'foo': 18}]
Version 2.20.0 - Iterate Twice: []
```
### Expected behavior
The expected behavior is it version 2.20.0 should behave the same as 2.17.0.
### Environment info
`datasets==2.20.0` on any platform. | {
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"same issue here. @albertvillanova @lhoestq ",
"Also impacted by this issue in many of my datasets (though not all) - in my case, this also seems to affect datasets that have been updated recently. Git cloning and the web interface still work:\r\n- https://huggingface.co/api/datasets/acmc/cheat_reduced\r\n- https... | 2024-07-27T08:21:03Z | 2024-09-20T13:26:25Z | 2024-07-27T19:52:30Z | NONE | null | null | {
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} | ### Describe the bug
newly uploaded datasets, since yesterday, yields an error.
old datasets, works fine.
Seems like the datasets api server returns a 500
I'm getting the same error, when I invoke `load_dataset` with my dataset.
Long discussion about it here, but I'm not sure anyone from huggingface have seen it.
https://discuss.huggingface.co/t/hfhubhttperror-500-server-error-internal-server-error-for-url/99580/1
### Steps to reproduce the bug
this api url:
https://huggingface.co/api/datasets/neoneye/simon-arc-shape-v4-rev3
respond with:
```
{"error":"Internal Error - We're working hard to fix this as soon as possible!"}
```
### Expected behavior
return no error with newer datasets.
With older datasets I can load the datasets fine.
### Environment info
# Browser
When I access the api in the browser:
https://huggingface.co/api/datasets/neoneye/simon-arc-shape-v4-rev3
```
{"error":"Internal Error - We're working hard to fix this as soon as possible!"}
```
### Request headers
```
Accept text/html,application/xhtml+xml,application/xml;q=0.9,image/avif,image/webp,*/*;q=0.8
Accept-Encoding gzip, deflate, br, zstd
Accept-Language en-US,en;q=0.5
Connection keep-alive
Host huggingface.co
Priority u=1
Sec-Fetch-Dest document
Sec-Fetch-Mode navigate
Sec-Fetch-Site cross-site
Upgrade-Insecure-Requests 1
User-Agent Mozilla/5.0 (Macintosh; Intel Mac OS X 10.15; rv:127.0) Gecko/20100101 Firefox/127.0
```
### Response headers
```
X-Firefox-Spdy h2
access-control-allow-origin https://huggingface.co
access-control-expose-headers X-Repo-Commit,X-Request-Id,X-Error-Code,X-Error-Message,X-Total-Count,ETag,Link,Accept-Ranges,Content-Range
content-length 80
content-type application/json; charset=utf-8
cross-origin-opener-policy same-origin
date Fri, 26 Jul 2024 19:09:45 GMT
etag W/"50-9qrwU+BNI4SD0Fe32p/nofkmv0c"
referrer-policy strict-origin-when-cross-origin
vary Origin
via 1.1 1624c79cd07e6098196697a6a7907e4a.cloudfront.net (CloudFront)
x-amz-cf-id SP8E7n5qRaP6i9c9G83dNAiOzJBU4GXSrDRAcVNTomY895K35H0nJQ==
x-amz-cf-pop CPH50-C1
x-cache Error from cloudfront
x-error-message Internal Error - We're working hard to fix this as soon as possible!
x-powered-by huggingface-moon
x-request-id Root=1-66a3f479-026417465ef42f49349fdca1
``` | {
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"Any recent change in the API backend rejecting parameter `revision=\"refs/pr/1\"` to `HfApi.preupload_lfs_files`?\r\n```\r\nf\"{endpoint}/api/{repo_type}s/{repo_id}/preupload/{revision}\"\r\n\r\nhttps://hub-ci.huggingface.co/api/datasets/__DUMMY_TRANSFORMERS_USER__/test-dataset-5188a8-17219154347516/preupload/refs... | 2024-07-26T08:27:41Z | 2024-07-27T05:48:02Z | 2024-07-26T09:16:13Z | MEMBER | null | null | {
"completed": 0,
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```
FAILED tests/test_hub.py::test_convert_to_parquet - huggingface_hub.utils._errors.RevisionNotFoundError: 404 Client Error. (Request ID: Root=1-66a25839-31ce7b475e70e7db1e4d44c2;b0c8870f-d5ef-4bf2-a6ff-0191f3df0f64)
Revision Not Found for url: https://hub-ci.huggingface.co/api/datasets/__DUMMY_TRANSFORMERS_USER__/test-dataset-5188a8-17219154347516/preupload/refs%2Fpr%2F1.
Invalid rev id: refs/pr/1
```
```
/opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/datasets/hub.py:86: in convert_to_parquet
dataset.push_to_hub(
/opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/datasets/dataset_dict.py:1722: in push_to_hub
split_additions, uploaded_size, dataset_nbytes = self[split]._push_parquet_shards_to_hub(
/opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/datasets/arrow_dataset.py:5511: in _push_parquet_shards_to_hub
api.preupload_lfs_files(
/opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/huggingface_hub/hf_api.py:4231: in preupload_lfs_files
_fetch_upload_modes(
/opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/huggingface_hub/utils/_validators.py:118: in _inner_fn
return fn(*args, **kwargs)
/opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/huggingface_hub/_commit_api.py:507: in _fetch_upload_modes
hf_raise_for_status(resp)
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https://api.github.com/repos/huggingface/datasets/issues/7067 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7067/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7067/comments | https://api.github.com/repos/huggingface/datasets/issues/7067/events | https://github.com/huggingface/datasets/issues/7067 | 2,425,460,168 | I_kwDODunzps6QkZXI | 7,067 | Convert_to_parquet fails for datasets with multiple configs | {
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"Many users have encountered the same issue, which has caused inconvenience.\r\n\r\nhttps://discuss.huggingface.co/t/convert-to-parquet-fails-for-datasets-with-multiple-configs/86733\r\n",
"Thanks for reporting.\r\n\r\nI will make the code more robust.",
"I have opened an issue in the huggingface-hub repo:\r\n-... | 2024-07-23T15:09:33Z | 2024-07-30T10:51:02Z | 2024-07-30T10:51:02Z | NONE | null | null | {
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} | If the dataset has multiple configs, when using the `datasets-cli convert_to_parquet` command to avoid issues with the data viewer caused by loading scripts, the conversion process only successfully converts the data corresponding to the first config. When it starts converting the second config, it throws an error:
```
Traceback (most recent call last):
File "/opt/anaconda3/envs/dl/bin/datasets-cli", line 8, in <module>
sys.exit(main())
File "/opt/anaconda3/envs/dl/lib/python3.10/site-packages/datasets/commands/datasets_cli.py", line 41, in main
service.run()
File "/opt/anaconda3/envs/dl/lib/python3.10/site-packages/datasets/commands/convert_to_parquet.py", line 83, in run
dataset.push_to_hub(
File "/opt/anaconda3/envs/dl/lib/python3.10/site-packages/datasets/dataset_dict.py", line 1713, in push_to_hub
api.create_branch(repo_id, branch=revision, token=token, repo_type="dataset", exist_ok=True)
File "/opt/anaconda3/envs/dl/lib/python3.10/site-packages/huggingface_hub/utils/_validators.py", line 114, in _inner_fn
return fn(*args, **kwargs)
File "/opt/anaconda3/envs/dl/lib/python3.10/site-packages/huggingface_hub/hf_api.py", line 5503, in create_branch
hf_raise_for_status(response)
File "/opt/anaconda3/envs/dl/lib/python3.10/site-packages/huggingface_hub/utils/_errors.py", line 358, in hf_raise_for_status
raise BadRequestError(message, response=response) from e
huggingface_hub.utils._errors.BadRequestError: (Request ID: Root=1-669fc665-7c2e80d75f4337496ee95402;731fcdc7-0950-4eec-99cf-ce047b8d003f)
Bad request:
Invalid reference for a branch: refs/pr/1
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/7063 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7063/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7063/comments | https://api.github.com/repos/huggingface/datasets/issues/7063/events | https://github.com/huggingface/datasets/issues/7063 | 2,424,488,648 | I_kwDODunzps6QgsLI | 7,063 | Add `batch` method to `Dataset` | {
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] | closed | false | null | [] | null | [] | 2024-07-23T07:36:59Z | 2024-07-25T13:45:21Z | 2024-07-25T13:45:21Z | CONTRIBUTOR | null | null | {
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} | ### Feature request
Add a `batch` method to the Dataset class, similar to the one recently implemented for `IterableDataset` in PR #7054.
### Motivation
A batched iteration speeds up data loading significantly (see e.g. #6279)
### Your contribution
I plan to open a PR to implement this. | {
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https://api.github.com/repos/huggingface/datasets/issues/7055 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7055/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7055/comments | https://api.github.com/repos/huggingface/datasets/issues/7055/events | https://github.com/huggingface/datasets/issues/7055 | 2,421,708,891 | I_kwDODunzps6QWFhb | 7,055 | WebDataset with different prefixes are unsupported | {
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"Since `datasets` uses is built on Arrow to store the data, it requires each sample to have the same columns.\r\n\r\nThis can be fixed by specifyign in advance the name of all the possible columns in the `dataset_info` in YAML, and missing values will be `None`",
"Thanks. This currently doesn't work for WebDatase... | 2024-07-22T01:14:19Z | 2024-07-24T13:26:30Z | 2024-07-23T13:28:46Z | NONE | null | null | {
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} | ### Describe the bug
Consider a WebDataset with multiple images for each item where the number of images may vary: [example](https://huggingface.co/datasets/bigdata-pw/fashion-150k)
Due to this [code](https://github.com/huggingface/datasets/blob/87f4c2088854ff33e817e724e75179e9975c1b02/src/datasets/packaged_modules/webdataset/webdataset.py#L76-L80) an error is given.
```
The TAR archives of the dataset should be in WebDataset format, but the files in the archive don't share the same prefix or the same types.
```
The purpose of this check is unclear because PyArrow supports different keys.
Removing the check allows the dataset to be loaded and there's no issue when iterating through the dataset.
```
>>> from datasets import load_dataset
>>> path = "shards/*.tar"
>>> dataset = load_dataset("webdataset", data_files={"train": path}, split="train", streaming=True)
Resolving data files: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 152/152 [00:00<00:00, 56458.93it/s]
>>> dataset
IterableDataset({
features: ['__key__', '__url__', '1.jpg', '2.jpg', '3.jpg', '4.jpg', 'json'],
n_shards: 152
})
```
### Steps to reproduce the bug
```python
from datasets import load_dataset
load_dataset("bigdata-pw/fashion-150k")
```
### Expected behavior
Dataset loads without error
### Environment info
- `datasets` version: 2.20.0
- Platform: Linux-5.14.0-467.el9.x86_64-x86_64-with-glibc2.34
- Python version: 3.9.19
- `huggingface_hub` version: 0.23.4
- PyArrow version: 17.0.0
- Pandas version: 2.2.2
- `fsspec` version: 2024.5.0 | {
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https://api.github.com/repos/huggingface/datasets/issues/7053 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7053/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7053/comments | https://api.github.com/repos/huggingface/datasets/issues/7053/events | https://github.com/huggingface/datasets/issues/7053 | 2,416,423,791 | I_kwDODunzps6QB7Nv | 7,053 | Datasets.datafiles resolve_pattern `TypeError: can only concatenate tuple (not "str") to tuple` | {
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"Hi,\r\n\r\nThis issue was fixed in `datasets` 2.15.0:\r\n- #6105\r\n\r\nYou will need to update your `datasets`:\r\n```\r\npip install -U datasets\r\n```",
"Duplicate of:\r\n- #6100"
] | 2024-07-18T13:42:35Z | 2024-07-18T15:17:42Z | 2024-07-18T15:16:18Z | NONE | null | null | {
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} | ### Describe the bug
in data_files.py, line 332,
`fs, _, _ = get_fs_token_paths(pattern, storage_options=storage_options)`
If we run the code on AWS, as fs.protocol will be a tuple like: `('file', 'local')`
So, `isinstance(fs.protocol, str) == False` and
`protocol_prefix = fs.protocol + "://" if fs.protocol != "file" else ""` will raise
`TypeError: can only concatenate tuple (not "str") to tuple`.
### Steps to reproduce the bug
Steps to reproduce:
1. Run on a cloud server like AWS,
2. `import datasets.data_files as datafile`
3. datafile.resolve_pattern('path/to/dataset', '.')
4. `TypeError: can only concatenate tuple (not "str") to tuple`
### Expected behavior
Should return path of the dataset, with fs.protocol at the beginning
### Environment info
- `datasets` version: 2.14.0
- Platform: Linux-3.10.0-1160.119.1.el7.x86_64-x86_64-with-glibc2.17
- Python version: 3.8.19
- Huggingface_hub version: 0.23.5
- PyArrow version: 16.1.0
- Pandas version: 1.1.5 | {
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https://api.github.com/repos/huggingface/datasets/issues/7051 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7051/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7051/comments | https://api.github.com/repos/huggingface/datasets/issues/7051/events | https://github.com/huggingface/datasets/issues/7051 | 2,409,353,929 | I_kwDODunzps6Pm9LJ | 7,051 | How to set_epoch with interleave_datasets? | {
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"This is not possible right now afaik :/\r\n\r\nMaybe we could have something like this ? wdyt ?\r\n\r\n```python\r\nds = interleave_datasets(\r\n [shuffled_dataset_a, dataset_b],\r\n probabilities=probabilities,\r\n stopping_strategy='all_exhausted',\r\n reshuffle_each_iteration=True,\r\n)",
"That wo... | 2024-07-15T18:24:52Z | 2024-08-05T20:58:04Z | 2024-08-05T20:58:04Z | NONE | null | null | {
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} | Let's say I have dataset A which has 100k examples, and dataset B which has 100m examples.
I want to train on an interleaved dataset of A+B, with stopping_strategy='all_exhausted' so dataset B doesn't repeat any examples. But every time A is exhausted I want it to be reshuffled (eg. calling set_epoch)
Of course I want to interleave as IterableDatasets / streaming mode so B doesn't have to get tokenized completely at the start.
How could I achieve this? I was thinking something like, if I wrap dataset A in some new IterableDataset with from_generator() and manually call set_epoch before interleaving it? But I'm not sure how to keep the number of shards in that dataset...
Something like
```
dataset_a = load_dataset(...)
dataset_b = load_dataset(...)
def epoch_shuffled_dataset(ds):
# How to make this maintain the number of shards in ds??
for epoch in itertools.count():
ds.set_epoch(epoch)
yield from iter(ds)
shuffled_dataset_a = IterableDataset.from_generator(epoch_shuffled_dataset, gen_kwargs={'ds': dataset_a})
interleaved = interleave_datasets([shuffled_dataset_a, dataset_b], probs, stopping_strategy='all_exhausted')
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/7049 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7049/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7049/comments | https://api.github.com/repos/huggingface/datasets/issues/7049/events | https://github.com/huggingface/datasets/issues/7049 | 2,408,514,366 | I_kwDODunzps6PjwM- | 7,049 | Save nparray as list | {
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"In addition, when I use `set_format ` and index the ds, the following error occurs:\r\nthe code\r\n```python\r\nds.set_format(type=\"np\", colums=\"pixel_values\")\r\n```\r\nerror\r\n<img width=\"918\" alt=\"image\" src=\"https://github.com/user-attachments/assets/b28bbff2-20ea-4d28-ab62-b4ed2d944996\">\r\n",
">... | 2024-07-15T11:36:11Z | 2024-07-18T11:33:34Z | 2024-07-18T11:33:34Z | NONE | null | null | {
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} | ### Describe the bug
When I use the `map` function to convert images into features, datasets saves nparray as a list. Some people use the `set_format` function to convert the column back, but doesn't this lose precision?
### Steps to reproduce the bug
the map function
```python
def convert_image_to_features(inst, processor, image_dir):
image_file = inst["image_url"]
file = image_file.split("/")[-1]
image_path = os.path.join(image_dir, file)
image = Image.open(image_path)
image = image.convert("RGBA")
inst["pixel_values"] = processor(images=image, return_tensors="np")["pixel_values"]
return inst
```
main function
```python
map_fun = partial(
convert_image_to_features, processor=processor, image_dir=image_dir
)
ds = ds.map(map_fun, batched=False, num_proc=20)
print(type(ds[0]["pixel_values"])
```
### Expected behavior
(type < list>)
### Environment info
- `datasets` version: 2.16.1
- Platform: Linux-4.19.91-009.ali4000.alios7.x86_64-x86_64-with-glibc2.35
- Python version: 3.11.5
- `huggingface_hub` version: 0.23.4
- PyArrow version: 14.0.2
- Pandas version: 2.1.4
- `fsspec` version: 2023.10.0 | {
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https://api.github.com/repos/huggingface/datasets/issues/7048 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7048/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7048/comments | https://api.github.com/repos/huggingface/datasets/issues/7048/events | https://github.com/huggingface/datasets/issues/7048 | 2,408,487,547 | I_kwDODunzps6Pjpp7 | 7,048 | ImportError: numpy.core.multiarray when using `filter` | {
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"Could you please check your `numpy` version?",
"I got this issue while using numpy version 2.0. \r\n\r\nI solved it by switching back to numpy 1.26.0 :) ",
"We recently added support for numpy 2.0, but it is not released yet.",
"Ok I see, thanks! I think we can close this issue for now as switching back to v... | 2024-07-15T11:21:04Z | 2024-07-16T10:11:25Z | 2024-07-16T10:11:25Z | NONE | null | null | {
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} | ### Describe the bug
I can't apply the filter method on my dataset.
### Steps to reproduce the bug
The following snippet generates a bug:
```python
from datasets import load_dataset
ami = load_dataset('kamilakesbi/ami', 'ihm')
ami['train'].filter(
lambda example: example["file_name"] == 'EN2001a'
)
```
I get the following error:
`ImportError: numpy.core.multiarray failed to import (auto-generated because you didn't call 'numpy.import_array()' after cimporting numpy; use '<void>numpy._import_array' to disable if you are certain you don't need it).`
### Expected behavior
It should work properly!
### Environment info
- `datasets` version: 2.20.0
- Platform: Linux-5.15.0-67-generic-x86_64-with-glibc2.35
- Python version: 3.10.6
- `huggingface_hub` version: 0.23.4
- PyArrow version: 16.1.0
- Pandas version: 2.2.2
- `fsspec` version: 2024.5.0 | {
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https://api.github.com/repos/huggingface/datasets/issues/7041 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7041/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7041/comments | https://api.github.com/repos/huggingface/datasets/issues/7041/events | https://github.com/huggingface/datasets/issues/7041 | 2,404,576,038 | I_kwDODunzps6PUusm | 7,041 | `sort` after `filter` unreasonably slow | {
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"`filter` add an indices mapping on top of the dataset, so `sort` has to gather all the rows that are kept to form a new Arrow table and sort the table. Gathering all the rows can take some time, but is a necessary step. You can try calling `ds = ds.flatten_indices()` before sorting to remove the indices mapping.",... | 2024-07-12T03:29:27Z | 2025-04-29T09:49:25Z | 2025-04-29T09:49:25Z | NONE | null | null | {
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} | ### Describe the bug
as the tittle says ...
### Steps to reproduce the bug
`sort` seems to be normal.
```python
from datasets import Dataset
import random
nums = [{"k":random.choice(range(0,1000))} for _ in range(100000)]
ds = Dataset.from_list(nums)
print("start sort")
ds = ds.sort("k")
print("finish sort")
```
but `sort` after `filter` is extremely slow.
```python
from datasets import Dataset
import random
nums = [{"k":random.choice(range(0,1000))} for _ in range(100000)]
ds = Dataset.from_list(nums)
ds = ds.filter(lambda x:x > 100, input_columns="k")
print("start sort")
ds = ds.sort("k")
print("finish sort")
```
### Expected behavior
Is this a bug, or is it a misuse of the `sort` function?
### Environment info
- `datasets` version: 2.20.0
- Platform: Linux-3.10.0-1127.19.1.el7.x86_64-x86_64-with-glibc2.17
- Python version: 3.10.13
- `huggingface_hub` version: 0.23.4
- PyArrow version: 16.1.0
- Pandas version: 2.2.2
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https://api.github.com/repos/huggingface/datasets/issues/7035 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7035/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7035/comments | https://api.github.com/repos/huggingface/datasets/issues/7035/events | https://github.com/huggingface/datasets/issues/7035 | 2,400,021,225 | I_kwDODunzps6PDWrp | 7,035 | Docs are not generated when a parameter defaults to a NamedSplit value | {
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} | While generating the docs, we get an error when some parameter defaults to a `NamedSplit` value, like:
```python
def call_function(split=Split.TRAIN):
...
```
The error is: ValueError: Equality not supported between split train and <class 'inspect._empty'>
See: https://github.com/huggingface/datasets/actions/runs/9869660902/job/27254359863?pr=7015
```
Building the MDX files: 97%|█████████▋| 58/60 [00:00<00:00, 91.94it/s]
Traceback (most recent call last):
File "/home/runner/work/datasets/datasets/.venv/lib/python3.10/site-packages/doc_builder/build_doc.py", line 197, in build_mdx_files
content, new_anchors, source_files, errors = resolve_autodoc(
File "/home/runner/work/datasets/datasets/.venv/lib/python3.10/site-packages/doc_builder/build_doc.py", line 123, in resolve_autodoc
doc = autodoc(
File "/home/runner/work/datasets/datasets/.venv/lib/python3.10/site-packages/doc_builder/autodoc.py", line 499, in autodoc
method_doc, check = document_object(
File "/home/runner/work/datasets/datasets/.venv/lib/python3.10/site-packages/doc_builder/autodoc.py", line 395, in document_object
signature = format_signature(obj)
File "/home/runner/work/datasets/datasets/.venv/lib/python3.10/site-packages/doc_builder/autodoc.py", line 126, in format_signature
if param.default != inspect._empty:
File "/home/runner/work/datasets/datasets/.venv/lib/python3.10/site-packages/datasets/splits.py", line 136, in __ne__
return not self.__eq__(other)
File "/home/runner/work/datasets/datasets/.venv/lib/python3.10/site-packages/datasets/splits.py", line 379, in __eq__
raise ValueError(f"Equality not supported between split {self} and {other}")
ValueError: Equality not supported between split train and <class 'inspect._empty'>
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/home/runner/work/datasets/datasets/.venv/bin/doc-builder", line 8, in <module>
sys.exit(main())
File "/home/runner/work/datasets/datasets/.venv/lib/python3.10/site-packages/doc_builder/commands/doc_builder_cli.py", line 47, in main
args.func(args)
File "/home/runner/work/datasets/datasets/.venv/lib/python3.10/site-packages/doc_builder/commands/build.py", line 102, in build_command
build_doc(
File "/home/runner/work/datasets/datasets/.venv/lib/python3.10/site-packages/doc_builder/build_doc.py", line 367, in build_doc
anchors_mapping, source_files_mapping = build_mdx_files(
File "/home/runner/work/datasets/datasets/.venv/lib/python3.10/site-packages/doc_builder/build_doc.py", line 230, in build_mdx_files
raise type(e)(f"There was an error when converting {file} to the MDX format.\n" + e.args[0]) from e
ValueError: There was an error when converting ../datasets/docs/source/package_reference/main_classes.mdx to the MDX format.
Equality not supported between split train and <class 'inspect._empty'>
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/7033 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7033/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7033/comments | https://api.github.com/repos/huggingface/datasets/issues/7033/events | https://github.com/huggingface/datasets/issues/7033 | 2,397,419,768 | I_kwDODunzps6O5bj4 | 7,033 | `from_generator` does not allow to specify the split name | {
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"Thanks for reporting, @pminervini.\r\n\r\nI agree we should give the option to define the split name.\r\n\r\nIndeed, there is a PR that addresses precisely this issue:\r\n- #7015\r\n\r\nI am reviewing it.",
"Booom! thank you guys :)"
] | 2024-07-09T07:47:58Z | 2024-07-26T12:56:16Z | 2024-07-26T09:31:56Z | CONTRIBUTOR | null | null | {
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} | ### Describe the bug
I'm building train, dev, and test using `from_generator`; however, in all three cases, the logger prints `Generating train split:`
It's not possible to change the split name since it seems to be hardcoded: https://github.com/huggingface/datasets/blob/main/src/datasets/packaged_modules/generator/generator.py
### Steps to reproduce the bug
```
In [1]: from datasets import Dataset
In [2]: def gen():
...: yield {"pokemon": "bulbasaur", "type": "grass"}
...:
In [3]: ds = Dataset.from_generator(gen)
Generating train split: 1 examples [00:00, 133.89 examples/s]
```
### Expected behavior
It should be possible to specify any split name
### Environment info
- `datasets` version: 2.19.2
- Platform: macOS-10.16-x86_64-i386-64bit
- Python version: 3.8.5
- `huggingface_hub` version: 0.23.3
- PyArrow version: 15.0.0
- Pandas version: 2.0.3
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https://api.github.com/repos/huggingface/datasets/issues/7031 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7031/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7031/comments | https://api.github.com/repos/huggingface/datasets/issues/7031/events | https://github.com/huggingface/datasets/issues/7031 | 2,395,401,692 | I_kwDODunzps6Oxu3c | 7,031 | CI quality is broken: use ruff check instead | {
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```
error: `ruff <path>` has been removed. Use `ruff check <path>` instead.
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https://api.github.com/repos/huggingface/datasets/issues/7030 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7030/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7030/comments | https://api.github.com/repos/huggingface/datasets/issues/7030/events | https://github.com/huggingface/datasets/issues/7030 | 2,393,411,631 | I_kwDODunzps6OqJAv | 7,030 | Add option to disable progress bar when reading a dataset ("Loading dataset from disk") | {
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"You can disable progress bars for all of `datasets` with `disable_progress_bars`. [Link](https://huggingface.co/docs/datasets/en/package_reference/utilities#datasets.enable_progress_bars)\r\n\r\nSo you could do something like:\r\n\r\n```python\r\nfrom datasets import load_from_disk, enable_progress_bars, disable_p... | 2024-07-06T05:43:37Z | 2024-07-13T14:35:59Z | 2024-07-13T14:35:59Z | NONE | null | null | {
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} | ### Feature request
Add an option in load_from_disk to disable the progress bar even if the number of files is larger than 16.
### Motivation
I am reading a lot of datasets that it creates lots of logs.
<img width="1432" alt="image" src="https://github.com/huggingface/datasets/assets/57996478/8d4bbf03-6b89-44b6-937c-932f01b4eb2a">
### Your contribution
Seems like an easy fix to make. I can create a PR if necessary. | {
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https://api.github.com/repos/huggingface/datasets/issues/7022 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7022/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7022/comments | https://api.github.com/repos/huggingface/datasets/issues/7022/events | https://github.com/huggingface/datasets/issues/7022 | 2,388,064,650 | I_kwDODunzps6OVvmK | 7,022 | There is dead code after we require pyarrow >= 15.0.0 | {
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However, we require pyarrow >= 15.0.0 since the merge of PR:
- #6892
Those code lines are now dead code and should be removed. | {
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https://api.github.com/repos/huggingface/datasets/issues/7020 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7020/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7020/comments | https://api.github.com/repos/huggingface/datasets/issues/7020/events | https://github.com/huggingface/datasets/issues/7020 | 2,387,940,990 | I_kwDODunzps6OVRZ- | 7,020 | Casting list array to fixed size list raises error | {
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> AttributeError: 'pyarrow.lib.FixedSizeListType' object has no attribute 'length'
Steps to reproduce the bug:
```python
import pyarrow as pa
from datasets.table import array_cast
arr = pa.array([[0, 1]])
array_cast(arr, pa.list_(pa.int64(), 2))
```
Stack trace:
```
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-12-6cb90a1d8216> in <module>
3
4 arr = pa.array([[0, 1]])
----> 5 array_cast(arr, pa.list_(pa.int64(), 2))
~/huggingface/datasets/src/datasets/table.py in wrapper(array, *args, **kwargs)
1802 return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
1803 else:
-> 1804 return func(array, *args, **kwargs)
1805
1806 return wrapper
~/huggingface/datasets/src/datasets/table.py in array_cast(array, pa_type, allow_primitive_to_str, allow_decimal_to_str)
1920 else:
1921 array_values = array.values[
-> 1922 array.offset * pa_type.length : (array.offset + len(array)) * pa_type.length
1923 ]
1924 return pa.FixedSizeListArray.from_arrays(_c(array_values, pa_type.value_type), pa_type.list_size)
AttributeError: 'pyarrow.lib.FixedSizeListType' object has no attribute 'length'
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/7013 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7013/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7013/comments | https://api.github.com/repos/huggingface/datasets/issues/7013/events | https://github.com/huggingface/datasets/issues/7013 | 2,382,976,738 | I_kwDODunzps6OCVbi | 7,013 | CI is broken for faiss tests on Windows: node down: Not properly terminated | {
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See: https://github.com/huggingface/datasets/actions/runs/9712659783
```
test (integration, windows-latest, deps-minimum)
The job running on runner GitHub Actions 60 has exceeded the maximum execution time of 360 minutes.
test (integration, windows-latest, deps-latest)
The job running on runner GitHub Actions 238 has exceeded the maximum execution time of 360 minutes.
```
```
____________________________ tests/test_search.py _____________________________
[gw1] win32 -- Python 3.8.10 C:\hostedtoolcache\windows\Python\3.8.10\x64\python.exe
worker 'gw1' crashed while running 'tests/test_search.py::IndexableDatasetTest::test_add_faiss_index'
____________________________ tests/test_search.py _____________________________
[gw2] win32 -- Python 3.8.10 C:\hostedtoolcache\windows\Python\3.8.10\x64\python.exe
worker 'gw2' crashed while running 'tests/test_search.py::IndexableDatasetTest::test_add_faiss_index'
```
```
tests/test_search.py::IndexableDatasetTest::test_add_faiss_index
[gw0] node down: Not properly terminated
[gw0] FAILED tests/test_search.py::IndexableDatasetTest::test_add_faiss_index
replacing crashed worker gw0
tests/test_search.py::IndexableDatasetTest::test_add_faiss_index
[gw1] node down: Not properly terminated
[gw1] FAILED tests/test_search.py::IndexableDatasetTest::test_add_faiss_index
replacing crashed worker gw1
tests/test_search.py::IndexableDatasetTest::test_add_faiss_index
[gw2] node down: Not properly terminated
[gw2] FAILED tests/test_search.py::IndexableDatasetTest::test_add_faiss_index
replacing crashed worker gw2
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/7010 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7010/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7010/comments | https://api.github.com/repos/huggingface/datasets/issues/7010/events | https://github.com/huggingface/datasets/issues/7010 | 2,379,777,480 | I_kwDODunzps6N2IXI | 7,010 | Re-enable raising error from huggingface-hub FutureWarning in CI | {
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- #6876
Note that this can only be done once transformers releases the fix:
- https://github.com/huggingface/transformers/pull/31007 | {
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Also revert:
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See: https://github.com/huggingface/datasets/actions/runs/9707641618/job/26793170961?pr=6983
> src/datasets/features/features.py:844:12: E721 Use `is` and `is not` for type comparisons, or `isinstance()` for isinstance checks | {
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"Hi ! `data_dir=` is for directories, can you try using `data_files=` instead ?",
"If you are trying to load your image dataset from a local folder, you should replace \"data_dir=path/to/jsonl/metadata.jsonl\" with the real folder path in your computer.\r\n\r\nhttps://huggingface.co/docs/datasets/en/image_load#im... | 2024-06-27T15:08:26Z | 2024-06-28T09:56:19Z | 2024-06-28T09:56:19Z | NONE | null | null | {
"completed": 0,
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} | ### Describe the bug
while trying to load custom dataset from jsonl file, I get the error: "metadata.jsonl doesn't contain any data files"
### Steps to reproduce the bug
This is my [metadata_v2.jsonl](https://github.com/user-attachments/files/16016011/metadata_v2.json) file. I have this file in the folder with all images mentioned in that json(l) file.
Through below mentioned command I am trying to load_dataset so that I can upload it as mentioned here on the [official website](https://huggingface.co/docs/datasets/en/image_dataset#upload-dataset-to-the-hub).
````
from datasets import load_dataset
dataset = load_dataset("imagefolder", data_dir="path/to/jsonl/metadata.jsonl")
````
error:
````
EmptyDatasetError Traceback (most recent call last)
Cell In[18], line 3
1 from datasets import load_dataset
----> 3 dataset = load_dataset("imagefolder",
4 data_dir="path/to/jsonl/file/metadata.jsonl")
5 dataset[0]["objects"]
File ~/anaconda3/envs/lvis/lib/python3.11/site-packages/datasets/load.py:2594, in load_dataset(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, verification_mode, ignore_verifications, keep_in_memory, save_infos, revision, token, use_auth_token, task, streaming, num_proc, storage_options, trust_remote_code, **config_kwargs)
2589 verification_mode = VerificationMode(
2590 (verification_mode or VerificationMode.BASIC_CHECKS) if not save_infos else VerificationMode.ALL_CHECKS
2591 )
2593 # Create a dataset builder
-> 2594 builder_instance = load_dataset_builder(
2595 path=path,
2596 name=name,
2597 data_dir=data_dir,
2598 data_files=data_files,
2599 cache_dir=cache_dir,
2600 features=features,
2601 download_config=download_config,
2602 download_mode=download_mode,
2603 revision=revision,
2604 token=token,
2605 storage_options=storage_options,
2606 trust_remote_code=trust_remote_code,
2607 _require_default_config_name=name is None,
2608 **config_kwargs,
2609 )
2611 # Return iterable dataset in case of streaming
2612 if streaming:
File ~/anaconda3/envs/lvis/lib/python3.11/site-packages/datasets/load.py:2266, in load_dataset_builder(path, name, data_dir, data_files, cache_dir, features, download_config, download_mode, revision, token, use_auth_token, storage_options, trust_remote_code, _require_default_config_name, **config_kwargs)
2264 download_config = download_config.copy() if download_config else DownloadConfig()
2265 download_config.storage_options.update(storage_options)
-> 2266 dataset_module = dataset_module_factory(
2267 path,
2268 revision=revision,
2269 download_config=download_config,
2270 download_mode=download_mode,
2271 data_dir=data_dir,
2272 data_files=data_files,
2273 cache_dir=cache_dir,
2274 trust_remote_code=trust_remote_code,
2275 _require_default_config_name=_require_default_config_name,
2276 _require_custom_configs=bool(config_kwargs),
2277 )
2278 # Get dataset builder class from the processing script
2279 builder_kwargs = dataset_module.builder_kwargs
File ~/anaconda3/envs/lvis/lib/python3.11/site-packages/datasets/load.py:1805, in dataset_module_factory(path, revision, download_config, download_mode, dynamic_modules_path, data_dir, data_files, cache_dir, trust_remote_code, _require_default_config_name, _require_custom_configs, **download_kwargs)
1782 # We have several ways to get a dataset builder:
1783 #
1784 # - if path is the name of a packaged dataset module
(...)
1796
1797 # Try packaged
1798 if path in _PACKAGED_DATASETS_MODULES:
1799 return PackagedDatasetModuleFactory(
1800 path,
1801 data_dir=data_dir,
1802 data_files=data_files,
1803 download_config=download_config,
1804 download_mode=download_mode,
-> 1805 ).get_module()
1806 # Try locally
1807 elif path.endswith(filename):
File ~/anaconda3/envs/lvis/lib/python3.11/site-packages/datasets/load.py:1140, in PackagedDatasetModuleFactory.get_module(self)
1135 def get_module(self) -> DatasetModule:
1136 base_path = Path(self.data_dir or "").expanduser().resolve().as_posix()
1137 patterns = (
1138 sanitize_patterns(self.data_files)
1139 if self.data_files is not None
-> 1140 else get_data_patterns(base_path, download_config=self.download_config)
1141 )
1142 data_files = DataFilesDict.from_patterns(
1143 patterns,
1144 download_config=self.download_config,
1145 base_path=base_path,
1146 )
1147 supports_metadata = self.name in _MODULE_SUPPORTS_METADATA
File ~/anaconda3/envs/lvis/lib/python3.11/site-packages/datasets/data_files.py:503, in get_data_patterns(base_path, download_config)
501 return _get_data_files_patterns(resolver)
502 except FileNotFoundError:
--> 503 raise EmptyDatasetError(f"The directory at {base_path} doesn't contain any data files") from None
EmptyDatasetError: The directory at path/to/jsonl/file/metadata.jsonl doesn't contain any data files`
```
### Expected behavior
It should be able load the whole file in a format of "dataset" inside the dataset variable. But it gives error "The directory at "path/to/jsonl/metadata.jsonl" doesn't contain any data files."
### Environment info
I am using conda environment. | {
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https://api.github.com/repos/huggingface/datasets/issues/7000 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7000/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7000/comments | https://api.github.com/repos/huggingface/datasets/issues/7000/events | https://github.com/huggingface/datasets/issues/7000 | 2,372,887,585 | I_kwDODunzps6Nb2Qh | 7,000 | IterableDataset: Unsupported ScalarType BFloat16 | {
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"@lhoestq Thank you for merging #6607, but unfortunately the issue persists for `IterableDataset` :pensive: ",
"Hi ! I opened https://github.com/huggingface/datasets/pull/7002 to fix this bug",
"Amazing, thank you so much @lhoestq! :pray:"
] | 2024-06-25T14:43:26Z | 2024-06-25T16:04:00Z | 2024-06-25T15:51:53Z | NONE | null | null | {
"completed": 0,
"percent_completed": 0,
"total": 0
} | ### Describe the bug
`IterableDataset.from_generator` crashes when using BFloat16:
```
File "/usr/local/lib/python3.11/site-packages/datasets/utils/_dill.py", line 169, in _save_torchTensor
args = (obj.detach().cpu().numpy(),)
^^^^^^^^^^^^^^^^^^^^^^^^^^
TypeError: Got unsupported ScalarType BFloat16
```
### Steps to reproduce the bug
```python
import torch
from datasets import IterableDataset
def demo(x):
yield {"x": x}
x = torch.tensor([1.], dtype=torch.bfloat16)
dataset = IterableDataset.from_generator(
demo,
gen_kwargs=dict(x=x),
)
example = next(iter(dataset))
print(example)
```
### Expected behavior
Code sample should print:
```python
{'x': tensor([1.], dtype=torch.bfloat16)}
```
### Environment info
```
datasets==2.20.0
torch==2.2.2
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/6997 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6997/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6997/comments | https://api.github.com/repos/huggingface/datasets/issues/6997/events | https://github.com/huggingface/datasets/issues/6997 | 2,371,966,127 | I_kwDODunzps6NYVSv | 6,997 | CI is broken for tests using hf-internal-testing/librispeech_asr_dummy | {
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} | CI is broken: https://github.com/huggingface/datasets/actions/runs/9657882317/job/26637998686?pr=6996
```
FAILED tests/test_inspect.py::test_get_dataset_config_names[hf-internal-testing/librispeech_asr_dummy-expected4] - AssertionError: assert ['clean'] == ['clean', 'other']
Right contains one more item: 'other'
Full diff:
[
'clean',
- 'other',
]
FAILED tests/test_inspect.py::test_get_dataset_default_config_name[hf-internal-testing/librispeech_asr_dummy-None] - AssertionError: assert 'clean' is None
```
Note that repository was recently converted to Parquet: https://huggingface.co/datasets/hf-internal-testing/librispeech_asr_dummy/commit/5be91486e11a2d616f4ec5db8d3fd248585ac07a | {
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https://api.github.com/repos/huggingface/datasets/issues/6995 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6995/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6995/comments | https://api.github.com/repos/huggingface/datasets/issues/6995/events | https://github.com/huggingface/datasets/issues/6995 | 2,370,713,475 | I_kwDODunzps6NTjeD | 6,995 | ImportError when importing datasets.load_dataset | {
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"What is the version of your installed `huggingface-hub`:\r\n```python\r\nimport huggingface_hub\r\nprint(huggingface_hub.__version__)\r\n```\r\n\r\nIt seems you have a very old version of `huggingface-hub`, where `CommitInfo` was not still implemented. You need to update it:\r\n```\r\npip install -U huggingface-hu... | 2024-06-24T17:07:22Z | 2024-11-14T01:42:09Z | 2024-06-25T06:11:37Z | NONE | null | null | {
"completed": 0,
"percent_completed": 0,
"total": 0
} | ### Describe the bug
I encountered an ImportError while trying to import `load_dataset` from the `datasets` module in Hugging Face. The error message indicates a problem with importing 'CommitInfo' from 'huggingface_hub'.
### Steps to reproduce the bug
1. pip install git+https://github.com/huggingface/datasets
2. from datasets import load_dataset
### Expected behavior
ImportError Traceback (most recent call last)
Cell In[7], [line 1](vscode-notebook-cell:?execution_count=7&line=1)
----> [1](vscode-notebook-cell:?execution_count=7&line=1) from datasets import load_dataset
[3](vscode-notebook-cell:?execution_count=7&line=3) train_set = load_dataset("mispeech/speechocean762", split="train")
[4](vscode-notebook-cell:?execution_count=7&line=4) test_set = load_dataset("mispeech/speechocean762", split="test")
File d:\Anaconda3\envs\CS224S\Lib\site-packages\datasets\__init__.py:[1](file:///D:/Anaconda3/envs/CS224S/Lib/site-packages/datasets/__init__.py:1)7
1 # Copyright 2020 The HuggingFace Datasets Authors and the TensorFlow Datasets Authors.
[2](file:///D:/Anaconda3/envs/CS224S/Lib/site-packages/datasets/__init__.py:2) #
[3](file:///D:/Anaconda3/envs/CS224S/Lib/site-packages/datasets/__init__.py:3) # Licensed under the Apache License, Version 2.0 (the "License");
(...)
[12](file:///D:/Anaconda3/envs/CS224S/Lib/site-packages/datasets/__init__.py:12) # See the License for the specific language governing permissions and
[13](file:///D:/Anaconda3/envs/CS224S/Lib/site-packages/datasets/__init__.py:13) # limitations under the License.
[15](file:///D:/Anaconda3/envs/CS224S/Lib/site-packages/datasets/__init__.py:15) __version__ = "2.20.1.dev0"
---> [17](file:///D:/Anaconda3/envs/CS224S/Lib/site-packages/datasets/__init__.py:17) from .arrow_dataset import Dataset
[18](file:///D:/Anaconda3/envs/CS224S/Lib/site-packages/datasets/__init__.py:18) from .arrow_reader import ReadInstruction
[19](file:///D:/Anaconda3/envs/CS224S/Lib/site-packages/datasets/__init__.py:19) from .builder import ArrowBasedBuilder, BeamBasedBuilder, BuilderConfig, DatasetBuilder, GeneratorBasedBuilder
File d:\Anaconda3\envs\CS224S\Lib\site-packages\datasets\arrow_dataset.py:63
[61](file:///D:/Anaconda3/envs/CS224S/Lib/site-packages/datasets/arrow_dataset.py:61) import pyarrow.compute as pc
[62](file:///D:/Anaconda3/envs/CS224S/Lib/site-packages/datasets/arrow_dataset.py:62) from fsspec.core import url_to_fs
---> [63](file:///D:/Anaconda3/envs/CS224S/Lib/site-packages/datasets/arrow_dataset.py:63) from huggingface_hub import (
[64](file:///D:/Anaconda3/envs/CS224S/Lib/site-packages/datasets/arrow_dataset.py:64) CommitInfo,
[65](file:///D:/Anaconda3/envs/CS224S/Lib/site-packages/datasets/arrow_dataset.py:65) CommitOperationAdd,
...
[70](file:///D:/Anaconda3/envs/CS224S/Lib/site-packages/datasets/arrow_dataset.py:70) )
[71](file:///D:/Anaconda3/envs/CS224S/Lib/site-packages/datasets/arrow_dataset.py:71) from huggingface_hub.hf_api import RepoFile
[72](file:///D:/Anaconda3/envs/CS224S/Lib/site-packages/datasets/arrow_dataset.py:72) from multiprocess import Pool
ImportError: cannot import name 'CommitInfo' from 'huggingface_hub' (d:\Anaconda3\envs\CS224S\Lib\site-packages\huggingface_hub\__init__.py)
Output is truncated. View as a [scrollable element](command:cellOutput.enableScrolling?580889ab-0f61-4f37-9214-eaa2b3807f85) or open in a [text editor](command:workbench.action.openLargeOutput?580889ab-0f61-4f37-9214-eaa2b3807f85). Adjust cell output [settings](command:workbench.action.openSettings?%5B%22%40tag%3AnotebookOutputLayout%22%5D)...
### Environment info
Leo@DESKTOP-9NHUAMI MSYS /d/Anaconda3/envs/CS224S/Lib/site-packages/huggingface_hub
$ datasets-cli env
Traceback (most recent call last):
File "<frozen runpy>", line 198, in _run_module_as_main
File "<frozen runpy>", line 88, in _run_code
File "D:\Anaconda3\envs\CS224S\Scripts\datasets-cli.exe\__main__.py", line 4, in <module>
File "D:\Anaconda3\envs\CS224S\Lib\site-packages\datasets\__init__.py", line 17, in <module>
from .arrow_dataset import Dataset
File "D:\Anaconda3\envs\CS224S\Lib\site-packages\datasets\arrow_dataset.py", line 63, in <module>
from huggingface_hub import (
ImportError: cannot import name 'CommitInfo' from 'huggingface_hub' (D:\Anaconda3\envs\CS224S\Lib\site-packages\huggingface_hub\__init__.py)
(CS224S) | {
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https://api.github.com/repos/huggingface/datasets/issues/6990 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6990/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6990/comments | https://api.github.com/repos/huggingface/datasets/issues/6990/events | https://github.com/huggingface/datasets/issues/6990 | 2,366,660,785 | I_kwDODunzps6NEGCx | 6,990 | Problematic rank after calling `split_dataset_by_node` twice | {
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"ah yes good catch ! feel free to open a PR with your suggested fix"
] | 2024-06-21T14:25:26Z | 2024-06-25T16:19:19Z | 2024-06-25T16:19:19Z | CONTRIBUTOR | null | null | {
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} | ### Describe the bug
I'm trying to split `IterableDataset` by `split_dataset_by_node`.
But when doing split on a already split dataset, the resulting `rank` is greater than `world_size`.
### Steps to reproduce the bug
Here is the minimal code for reproduction:
```py
>>> from datasets import load_dataset
>>> from datasets.distributed import split_dataset_by_node
>>> dataset = load_dataset('fla-hub/slimpajama-test', split='train', streaming=True)
>>> dataset = split_dataset_by_node(dataset, 1, 32)
>>> dataset._distributed
DistributedConfig(rank=1, world_size=32)
>>> dataset = split_dataset_by_node(dataset, 1, 15)
>>> dataset._distributed
DistributedConfig(rank=481, world_size=480)
```
As you can see, the second rank 481 > 480, which is problematic.
### Expected behavior
I think this error comes from this line @lhoestq
https://github.com/huggingface/datasets/blob/a6ccf944e42c1a84de81bf326accab9999b86c90/src/datasets/iterable_dataset.py#L2943-L2944
We may need to obtain the rank first. Then the above code gives
```py
>>> dataset._distributed
DistributedConfig(rank=16, world_size=480)
```
### Environment info
datasets==2.20.0 | {
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https://api.github.com/repos/huggingface/datasets/issues/6985 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6985/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6985/comments | https://api.github.com/repos/huggingface/datasets/issues/6985/events | https://github.com/huggingface/datasets/issues/6985 | 2,362,378,276 | I_kwDODunzps6Mzwgk | 6,985 | AttributeError: module 'pyarrow.lib' has no attribute 'ListViewType' | {
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"Please note that the error is raised just at import:\r\n```python\r\nimport pyarrow.parquet as pq\r\n```\r\n\r\nTherefore it must be caused by some problem with your pyarrow installation. I would recommend you uninstall and install pyarrow again.\r\n\r\nI also see that it seems you use conda to install pyarrow. Pl... | 2024-06-19T13:22:28Z | 2025-03-14T18:47:53Z | 2024-06-25T05:40:51Z | NONE | null | null | {
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} | ### Describe the bug
I have been struggling with this for two days, any help would be appreciated. Python 3.10
```
from setfit import SetFitModel
from huggingface_hub import login
access_token_read = "cccxxxccc"
# Authenticate with the Hugging Face Hub
login(token=access_token_read)
# Load the models from the Hugging Face Hub
trainer_relv = SetFitModel.from_pretrained("snowdere/trainer_relevance")
trainer_trust = SetFitModel.from_pretrained("snowdere/trainer_trust")
trainer_sent = SetFitModel.from_pretrained("snowdere/trainer_sent")
trainer_topic = SetFitModel.from_pretrained("snowdere/trainer_topic")
```
```
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
Cell In[6], line 1
----> 1 from setfit import SetFitModel
2 from huggingface_hub import login
4 access_token_read = "ccsddsds"
File /opt/conda/lib/python3.10/site-packages/setfit/__init__.py:7
4 import os
5 import warnings
----> 7 from .data import get_templated_dataset, sample_dataset
8 from .model_card import SetFitModelCardData
9 from .modeling import SetFitHead, SetFitModel
File /opt/conda/lib/python3.10/site-packages/setfit/data.py:5
3 import pandas as pd
4 import torch
----> 5 from datasets import Dataset, DatasetDict, load_dataset
6 from torch.utils.data import Dataset as TorchDataset
8 from . import logging
File /opt/conda/lib/python3.10/site-packages/datasets/__init__.py:18
1 # ruff: noqa
2 # Copyright 2020 The HuggingFace Datasets Authors and the TensorFlow Datasets Authors.
3 #
(...)
13 # See the License for the specific language governing permissions and
14 # limitations under the License.
16 __version__ = "2.19.0"
---> 18 from .arrow_dataset import Dataset
19 from .arrow_reader import ReadInstruction
20 from .builder import ArrowBasedBuilder, BeamBasedBuilder, BuilderConfig, DatasetBuilder, GeneratorBasedBuilder
File /opt/conda/lib/python3.10/site-packages/datasets/arrow_dataset.py:76
73 from tqdm.contrib.concurrent import thread_map
75 from . import config
---> 76 from .arrow_reader import ArrowReader
77 from .arrow_writer import ArrowWriter, OptimizedTypedSequence
78 from .data_files import sanitize_patterns
File /opt/conda/lib/python3.10/site-packages/datasets/arrow_reader.py:29
26 from typing import TYPE_CHECKING, List, Optional, Union
28 import pyarrow as pa
---> 29 import pyarrow.parquet as pq
30 from tqdm.contrib.concurrent import thread_map
32 from .download.download_config import DownloadConfig
File /opt/conda/lib/python3.10/site-packages/pyarrow/parquet/__init__.py:20
1 # Licensed to the Apache Software Foundation (ASF) under one
2 # or more contributor license agreements. See the NOTICE file
3 # distributed with this work for additional information
(...)
17
18 # flake8: noqa
---> 20 from .core import *
File /opt/conda/lib/python3.10/site-packages/pyarrow/parquet/core.py:33
30 import pyarrow as pa
32 try:
---> 33 import pyarrow._parquet as _parquet
34 except ImportError as exc:
35 raise ImportError(
36 "The pyarrow installation is not built with support "
37 f"for the Parquet file format ({str(exc)})"
38 ) from None
File /opt/conda/lib/python3.10/site-packages/pyarrow/_parquet.pyx:1, in init pyarrow._parquet()
AttributeError: module 'pyarrow.lib' has no attribute 'ListViewType'
```
setfit: 1.0.3
transformers: 4.41.2
lingua-language-detector: 2.0.2
polars: 0.20.31
lightning: None
google-cloud-bigquery: 3.24.0
shapely: 2.0.4
pyarrow: 16.0.0
### Steps to reproduce the bug
I have tried all version combinations for Dataset and Pyarrow, the all have the same error since a few days ago. This is accross multiple scripts I have.
### Expected behavior
Just ron normally.
### Environment info
3.10 | {
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https://api.github.com/repos/huggingface/datasets/issues/6984 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6984/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6984/comments | https://api.github.com/repos/huggingface/datasets/issues/6984/events | https://github.com/huggingface/datasets/issues/6984 | 2,362,143,554 | I_kwDODunzps6My3NC | 6,984 | Convert polars DataFrame back to datasets | {
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"Hi ! Thanks for reporting :)\r\n\r\nWe don't support `large_list` yet, though it should be added to `Sequence` IMO (maybe with a parameter `large=True` ?)"
] | 2024-06-19T11:38:48Z | 2024-08-12T14:43:46Z | 2024-08-12T14:43:46Z | NONE | null | null | {
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} | ### Feature request
This returns error.
```python
from datasets import Dataset
dsdf = Dataset.from_dict({"x": [[1, 2], [3, 4, 5]], "y": ["a", "b"]})
Dataset.from_polars(dsdf.to_polars())
```
ValueError: Arrow type large_list<item: int64> does not have a datasets dtype equivalent.
### Motivation
When datasets contain Sequence data type, it will be converted to Arrow type large_list. However, the reverse (from large_list to Sequence) does not work.
### Your contribution
No | {
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"it seems the bug will happened in all windows system, I tried it in windows8.1, 10, 11 and all of them failed. But it won't happened in the Linux(Ubuntu and Centos7) and Mac (both my virtual and physical machine). I still don't know what the problem is. May be related to the path? I cannot run the split file in m... | 2024-06-19T08:07:16Z | 2024-07-08T06:20:16Z | 2024-07-08T06:20:16Z | NONE | null | null | {
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} | ### Describe the bug
when I use load_dataset methods to load mozilla-foundation/common_voice_7_0, it can successfully download and extracted the dataset but It cannot generating the arrow document,
This bug happened in my server, my laptop, so as #6906 , but it won't happen in the google colab. I work for it for days, even I load the datasets from local path, it can Generating train split and validation split but bug happen again in test split.
### Steps to reproduce the bug
from datasets import load_dataset, load_metric, Audio
common_voice_train = load_dataset("mozilla-foundation/common_voice_7_0", "ja", split="train", token=selftoken, trust_remote_code=True)
### Expected behavior
```
{
"name": "ValueError",
"message": "Instruction \"train\" corresponds to no data!",
"stack": "---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
Cell In[2], line 3
1 from datasets import load_dataset, load_metric, Audio
----> 3 common_voice_train = load_dataset(\"mozilla-foundation/common_voice_7_0\", \"ja\", split=\"train\",token='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')#,trust_remote_code=True)#,streaming=True)
4 common_voice_test = load_dataset(\"mozilla-foundation/common_voice_7_0\", \"ja\", split=\"test\",token='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')#,trust_remote_code=True)#,streaming=True)
File c:\\Users\\cybes\\.conda\\envs\\ECoG\\lib\\site-packages\\datasets\\load.py:2626, in load_dataset(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, verification_mode, ignore_verifications, keep_in_memory, save_infos, revision, token, use_auth_token, task, streaming, num_proc, storage_options, trust_remote_code, **config_kwargs)
2622 # Build dataset for splits
2623 keep_in_memory = (
2624 keep_in_memory if keep_in_memory is not None else is_small_dataset(builder_instance.info.dataset_size)
2625 )
-> 2626 ds = builder_instance.as_dataset(split=split, verification_mode=verification_mode, in_memory=keep_in_memory)
2627 # Rename and cast features to match task schema
2628 if task is not None:
2629 # To avoid issuing the same warning twice
File c:\\Users\\cybes\\.conda\\envs\\ECoG\\lib\\site-packages\\datasets\\builder.py:1266, in DatasetBuilder.as_dataset(self, split, run_post_process, verification_mode, ignore_verifications, in_memory)
1263 verification_mode = VerificationMode(verification_mode or VerificationMode.BASIC_CHECKS)
1265 # Create a dataset for each of the given splits
-> 1266 datasets = map_nested(
1267 partial(
1268 self._build_single_dataset,
1269 run_post_process=run_post_process,
1270 verification_mode=verification_mode,
1271 in_memory=in_memory,
1272 ),
1273 split,
1274 map_tuple=True,
1275 disable_tqdm=True,
1276 )
1277 if isinstance(datasets, dict):
1278 datasets = DatasetDict(datasets)
File c:\\Users\\cybes\\.conda\\envs\\ECoG\\lib\\site-packages\\datasets\\utils\\py_utils.py:484, in map_nested(function, data_struct, dict_only, map_list, map_tuple, map_numpy, num_proc, parallel_min_length, batched, batch_size, types, disable_tqdm, desc)
482 if batched:
483 data_struct = [data_struct]
--> 484 mapped = function(data_struct)
485 if batched:
486 mapped = mapped[0]
File c:\\Users\\cybes\\.conda\\envs\\ECoG\\lib\\site-packages\\datasets\\builder.py:1296, in DatasetBuilder._build_single_dataset(self, split, run_post_process, verification_mode, in_memory)
1293 split = Split(split)
1295 # Build base dataset
-> 1296 ds = self._as_dataset(
1297 split=split,
1298 in_memory=in_memory,
1299 )
1300 if run_post_process:
1301 for resource_file_name in self._post_processing_resources(split).values():
File c:\\Users\\cybes\\.conda\\envs\\ECoG\\lib\\site-packages\\datasets\\builder.py:1370, in DatasetBuilder._as_dataset(self, split, in_memory)
1368 if self._check_legacy_cache():
1369 dataset_name = self.name
-> 1370 dataset_kwargs = ArrowReader(cache_dir, self.info).read(
1371 name=dataset_name,
1372 instructions=split,
1373 split_infos=self.info.splits.values(),
1374 in_memory=in_memory,
1375 )
1376 fingerprint = self._get_dataset_fingerprint(split)
1377 return Dataset(fingerprint=fingerprint, **dataset_kwargs)
File c:\\Users\\cybes\\.conda\\envs\\ECoG\\lib\\site-packages\\datasets\\arrow_reader.py:256, in BaseReader.read(self, name, instructions, split_infos, in_memory)
254 msg = f'Instruction \"{instructions}\" corresponds to no data!'
255 #msg = f'Instruction \"{self._path}\",\"{name}\",\"{instructions}\",\"{split_infos}\" corresponds to no data!'
--> 256 raise ValueError(msg)
257 return self.read_files(files=files, original_instructions=instructions, in_memory=in_memory)
ValueError: Instruction \"train\" corresponds to no data!"
}
```
### Environment info
Environment:
python 3.9
windows 11 pro
VScode+jupyter | {
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] | closed | false | null | [] | null | [] | 2024-06-18T23:30:22Z | 2024-07-12T12:04:54Z | 2024-07-12T12:04:53Z | CONTRIBUTOR | null | null | {
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} | ### Feature request
Support NumPy 2.0.
### Motivation
NumPy introduces the Array API, which bridges the gap between machine learning libraries. Many clients of HuggingFace are eager to start using the Array API.
Besides that, NumPy 2 provides a cleaner interface than NumPy 1.
### Tasks
NumPy 2.0 was released for testing so that libraries could ensure compatibility [since mid-March](https://github.com/numpy/numpy/issues/24300#issuecomment-1986815755). What needs to be done for HuggingFace to support Numpy 2?
- [x] Fix use of `array`: https://github.com/huggingface/datasets/pull/6976
- [ ] Remove [NumPy version limit](https://github.com/huggingface/datasets/pull/6975): https://github.com/huggingface/datasets/pull/6991 | {
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https://api.github.com/repos/huggingface/datasets/issues/6979 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6979/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6979/comments | https://api.github.com/repos/huggingface/datasets/issues/6979/events | https://github.com/huggingface/datasets/issues/6979 | 2,360,175,363 | I_kwDODunzps6MrWsD | 6,979 | How can I load partial parquet files only? | {
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} | [] | closed | false | null | [] | null | [
"Hello,\r\n\r\nHave you tried loading the dataset in streaming mode? [Documentation](https://huggingface.co/docs/datasets/v2.20.0/stream)\r\n\r\nThis way you wouldn't have to load it all. Also, let's be nice to Parquet, it's a really nice technology and we don't need to be mean :)",
"I have downloaded part of it,... | 2024-06-18T15:44:16Z | 2024-06-21T17:09:32Z | 2024-06-21T13:32:50Z | NONE | null | null | {
"completed": 0,
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} | I have a HUGE dataset about 14TB, I unable to download all parquet all. I just take about 100 from it.
dataset = load_dataset("xx/", data_files="data/train-001*-of-00314.parquet")
How can I just using 000 - 100 from a 00314 from all partially?
I search whole net didn't found a solution, **this is stupid if they didn't support it, and I swear I wont using stupid parquet any more**
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https://api.github.com/repos/huggingface/datasets/issues/6977 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6977/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6977/comments | https://api.github.com/repos/huggingface/datasets/issues/6977/events | https://github.com/huggingface/datasets/issues/6977 | 2,359,295,045 | I_kwDODunzps6Mn_xF | 6,977 | load json file error with v2.20.0 | {
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"following_url": "https://api.github.com/users/albertvillanova/following{/o... | null | [
"Thanks for reporting, @xiaoyaolangzhi.\r\n\r\nIndeed, we are currently requiring `pandas` >= 2.0.0.\r\n\r\nYou will need to update pandas in your local environment:\r\n```\r\npip install -U pandas\r\n``` ",
"Thank you very much."
] | 2024-06-18T08:41:01Z | 2024-06-18T10:06:10Z | 2024-06-18T10:06:09Z | NONE | null | null | {
"completed": 0,
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} | ### Describe the bug
```
load_dataset(path="json", data_files="./test.json")
```
```
Generating train split: 0 examples [00:00, ? examples/s]
Traceback (most recent call last):
File "/usr/local/lib/python3.10/dist-packages/datasets/packaged_modules/json/json.py", line 132, in _generate_tables
pa_table = paj.read_json(
File "pyarrow/_json.pyx", line 308, in pyarrow._json.read_json
File "pyarrow/error.pxi", line 154, in pyarrow.lib.pyarrow_internal_check_status
File "pyarrow/error.pxi", line 91, in pyarrow.lib.check_status
pyarrow.lib.ArrowInvalid: JSON parse error: Column() changed from object to array in row 0
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/usr/local/lib/python3.10/dist-packages/datasets/builder.py", line 1997, in _prepare_split_single
for _, table in generator:
File "/usr/local/lib/python3.10/dist-packages/datasets/packaged_modules/json/json.py", line 155, in _generate_tables
df = pd.read_json(f, dtype_backend="pyarrow")
File "/usr/local/lib/python3.10/dist-packages/pandas/util/_decorators.py", line 211, in wrapper
return func(*args, **kwargs)
File "/usr/local/lib/python3.10/dist-packages/pandas/util/_decorators.py", line 331, in wrapper
return func(*args, **kwargs)
TypeError: read_json() got an unexpected keyword argument 'dtype_backend'
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/app/t1.py", line 11, in <module>
load_dataset(path=data_path, data_files="./t2.json")
File "/usr/local/lib/python3.10/dist-packages/datasets/load.py", line 2616, in load_dataset
builder_instance.download_and_prepare(
File "/usr/local/lib/python3.10/dist-packages/datasets/builder.py", line 1029, in download_and_prepare
self._download_and_prepare(
File "/usr/local/lib/python3.10/dist-packages/datasets/builder.py", line 1124, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/usr/local/lib/python3.10/dist-packages/datasets/builder.py", line 1884, in _prepare_split
for job_id, done, content in self._prepare_split_single(
File "/usr/local/lib/python3.10/dist-packages/datasets/builder.py", line 2040, in _prepare_split_single
raise DatasetGenerationError("An error occurred while generating the dataset") from e
datasets.exceptions.DatasetGenerationError: An error occurred while generating the dataset
```
```
import pandas as pd
with open("./test.json", "r") as f:
df = pd.read_json(f, dtype_backend="pyarrow")
```
```
Traceback (most recent call last):
File "/app/t3.py", line 3, in <module>
df = pd.read_json(f, dtype_backend="pyarrow")
File "/usr/local/lib/python3.10/dist-packages/pandas/util/_decorators.py", line 211, in wrapper
return func(*args, **kwargs)
File "/usr/local/lib/python3.10/dist-packages/pandas/util/_decorators.py", line 331, in wrapper
return func(*args, **kwargs)
TypeError: read_json() got an unexpected keyword argument 'dtype_backend'
```
### Steps to reproduce the bug
.
### Expected behavior
.
### Environment info
```
datasets 2.20.0
pandas 1.5.3
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"add remove_unused_columns=False to training_args\r\nhttps://github.com/huggingface/datasets/issues/6535#issuecomment-1874024704",
"Closing this issue because it was a reported and fixed in transformers."
] | 2024-06-16T07:53:54Z | 2024-07-01T11:25:40Z | 2024-07-01T11:25:40Z | NONE | null | null | {
"completed": 0,
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} | ### Describe the bug
I am encountering an IndexError while training a T5-small model on the Squad dataset using the transformers and datasets libraries. The error occurs even with a minimal reproducible example, suggesting a potential bug or incompatibility.
### Steps to reproduce the bug
1.Install the required libraries: !pip install transformers datasets
2.Run the following code:
!pip install transformers datasets
import torch
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, TrainingArguments, Trainer, DataCollatorWithPadding
# Load a small, publicly available dataset
from datasets import load_dataset
dataset = load_dataset("squad", split="train[:100]") # Use a small subset for testing
# Load a pre-trained model and tokenizer
model_name = "t5-small"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
# Define a basic data collator
data_collator = DataCollatorWithPadding(tokenizer=tokenizer)
# Define training arguments
training_args = TrainingArguments(
output_dir="./results",
per_device_train_batch_size=2,
num_train_epochs=1,
)
# Create a trainer
trainer = Trainer(
model=model,
args=training_args,
train_dataset=dataset,
data_collator=data_collator,
)
# Train the model
trainer.train()
### Expected behavior
---------------------------------------------------------------------------
IndexError Traceback (most recent call last)
[<ipython-input-23-f13a4b23c001>](https://localhost:8080/#) in <cell line: 34>()
32
33 # Train the model
---> 34 trainer.train()
10 frames
[/usr/local/lib/python3.10/dist-packages/datasets/formatting/formatting.py](https://localhost:8080/#) in _check_valid_index_key(key, size)
427 if isinstance(key, int):
428 if (key < 0 and key + size < 0) or (key >= size):
--> 429 raise IndexError(f"Invalid key: {key} is out of bounds for size {size}")
430 return
431 elif isinstance(key, slice):
IndexError: Invalid key: 42 is out of bounds for size 0
### Environment info
transformers version:4.41.2
datasets version:1.18.4
Python version:3.10.12
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https://api.github.com/repos/huggingface/datasets/issues/6958 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6958/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6958/comments | https://api.github.com/repos/huggingface/datasets/issues/6958/events | https://github.com/huggingface/datasets/issues/6958 | 2,337,476,383 | I_kwDODunzps6LUw8f | 6,958 | My Private Dataset doesn't exist on the Hub or cannot be accessed | {
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"I can load public dataset, but for my private dataset it fails",
"https://huggingface.co/docs/datasets/upload_dataset",
"I have checked the API HTTP link. Repository Not Found for url: https://huggingface.co/api/datasets/xxx/xxx.\r\n\r\n![image](https://github.com/huggingface/datasets/assets/39621324/4aceef59-... | 2024-06-06T06:52:19Z | 2024-07-01T11:27:46Z | 2024-07-01T11:27:46Z | NONE | null | null | {
"completed": 0,
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"total": 0
} | ### Describe the bug
```
File "/root/miniconda3/envs/gino_conda/lib/python3.9/site-packages/datasets/load.py", line 1852, in dataset_module_factory
raise DatasetNotFoundError(msg + f" at revision '{revision}'" if revision else msg)
datasets.exceptions.DatasetNotFoundError: Dataset 'xxx' doesn't exist on the Hub or cannot be accessed
>>> dataset = load_dataset("xxxx", token=True)
404 error 404 Client Error. (Request ID: Root=xxxx)
Repository Not Found for url: https://huggingface.co/api/datasets/xxx/xxx.
Please make sure you specified the correct `repo_id` and `repo_type`.
If you are trying to access a private or gated repo, make sure you are authenticated.
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/root/miniconda3/envs/gino_conda/lib/python3.9/site-packages/datasets/load.py", line 2593, in load_dataset
builder_instance = load_dataset_builder(
File "/root/miniconda3/envs/gino_conda/lib/python3.9/site-packages/datasets/load.py", line 2265, in load_dataset_builder
dataset_module = dataset_module_factory(
File "/root/miniconda3/envs/gino_conda/lib/python3.9/site-packages/datasets/load.py", line 1910, in dataset_module_factory
raise e1 from None
File "/root/miniconda3/envs/gino_conda/lib/python3.9/site-packages/datasets/load.py", line 1852, in dataset_module_factory
raise DatasetNotFoundError(msg + f" at revision '{revision}'" if revision else msg)
datasets.exceptions.DatasetNotFoundError: Dataset 'xxx' doesn't exist on the Hub or cannot be accessed
```
### Steps to reproduce the bug
123
### Expected behavior
123
### Environment info
123 | {
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https://api.github.com/repos/huggingface/datasets/issues/6953 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6953/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6953/comments | https://api.github.com/repos/huggingface/datasets/issues/6953/events | https://github.com/huggingface/datasets/issues/6953 | 2,333,366,120 | I_kwDODunzps6LFFdo | 6,953 | Remove canonical datasets from docs | {
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"Canonical datasets are no longer mentioned in the docs."
] | 2024-06-04T12:09:03Z | 2024-07-01T11:31:25Z | 2024-07-01T11:31:25Z | MEMBER | null | null | {
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https://api.github.com/repos/huggingface/datasets/issues/6951 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6951/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6951/comments | https://api.github.com/repos/huggingface/datasets/issues/6951/events | https://github.com/huggingface/datasets/issues/6951 | 2,333,231,042 | I_kwDODunzps6LEkfC | 6,951 | load_dataset() should load all subsets, if no specific subset is specified | {
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"@xianbaoqian ",
"Feel free to open a PR in `m-a-p/COIG-CQIA` to define a default subset. Currently there is no default.\r\n\r\nYou can find some documentation at https://huggingface.co/docs/hub/datasets-manual-configuration#multiple-configurations",
"@lhoestq \r\n\r\nWhilst having a default subset readily avai... | 2024-06-04T11:02:33Z | 2024-11-26T08:32:18Z | 2024-07-01T11:33:10Z | NONE | null | null | {
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} | ### Feature request
Currently load_dataset() is forcing users to specify a subset. Example
`from datasets import load_dataset
dataset = load_dataset("m-a-p/COIG-CQIA")`
```---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
[<ipython-input-10-c0cb49385da6>](https://localhost:8080/#) in <cell line: 2>()
1 from datasets import load_dataset
----> 2 dataset = load_dataset("m-a-p/COIG-CQIA")
3 frames
[/usr/local/lib/python3.10/dist-packages/datasets/builder.py](https://localhost:8080/#) in _create_builder_config(self, config_name, custom_features, **config_kwargs)
582 if not config_kwargs:
583 example_of_usage = f"load_dataset('{self.dataset_name}', '{self.BUILDER_CONFIGS[0].name}')"
--> 584 raise ValueError(
585 "Config name is missing."
586 f"\nPlease pick one among the available configs: {list(self.builder_configs.keys())}"
ValueError: Config name is missing.
Please pick one among the available configs: ['chinese_traditional', 'coig_pc', 'exam', 'finance', 'douban', 'human_value', 'logi_qa', 'ruozhiba', 'segmentfault', 'wiki', 'wikihow', 'xhs', 'zhihu']
Example of usage:
`load_dataset('coig-cqia', 'chinese_traditional')`
```
This means a dataset cannot contain all the subsets at the same time. I guess one workaround is to manually specify the subset files like in [here](https://huggingface.co/datasets/m-a-p/COIG-CQIA/discussions/1#658698b44bb41498f75c5622), which is clumsy.
### Motivation
Ideally, if not subset is specified, the API should just try to load all subsets. This makes it much easier to handle datasets w/ subsets.
### Your contribution
Not sure since I'm not familiar w/ the lib src. | {
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https://api.github.com/repos/huggingface/datasets/issues/6950 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6950/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6950/comments | https://api.github.com/repos/huggingface/datasets/issues/6950/events | https://github.com/huggingface/datasets/issues/6950 | 2,333,005,974 | I_kwDODunzps6LDtiW | 6,950 | `Dataset.with_format` behaves inconsistently with documentation | {
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"Hi ! It seems the documentation was outdated in this paragraph\r\n\r\nI fixed it here: https://github.com/huggingface/datasets/pull/6956",
"Fixed."
] | 2024-06-04T09:18:32Z | 2024-06-25T08:05:49Z | 2024-06-25T08:05:49Z | NONE | null | null | {
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} | ### Describe the bug
The actual behavior of the interface `Dataset.with_format` is inconsistent with the documentation.
https://huggingface.co/docs/datasets/use_with_pytorch#n-dimensional-arrays
https://huggingface.co/docs/datasets/v2.19.0/en/use_with_tensorflow#n-dimensional-arrays
> If your dataset consists of N-dimensional arrays, you will see that by default they are considered as nested lists.
> In particular, a PyTorch formatted dataset outputs nested lists instead of a single tensor.
> A TensorFlow formatted dataset outputs a RaggedTensor instead of a single tensor.
But I get a single tensor by default, which is inconsistent with the description.
Actually the current behavior seems more reasonable to me. Therefore, the document needs to be modified.
### Steps to reproduce the bug
```python
>>> from datasets import Dataset
>>> data = [[[1, 2],[3, 4]],[[5, 6],[7, 8]]]
>>> ds = Dataset.from_dict({"data": data})
>>> ds = ds.with_format("torch")
>>> ds[0]
{'data': tensor([[1, 2],
[3, 4]])}
>>> ds = ds.with_format("tf")
>>> ds[0]
{'data': <tf.Tensor: shape=(2, 2), dtype=int64, numpy=
array([[1, 2],
[3, 4]])>}
```
### Expected behavior
```python
>>> from datasets import Dataset
>>> data = [[[1, 2],[3, 4]],[[5, 6],[7, 8]]]
>>> ds = Dataset.from_dict({"data": data})
>>> ds = ds.with_format("torch")
>>> ds[0]
{'data': [tensor([1, 2]), tensor([3, 4])]}
>>> ds = ds.with_format("tf")
>>> ds[0]
{'data': <tf.RaggedTensor [[1, 2], [3, 4]]>}
```
### Environment info
datasets==2.19.1
torch==2.1.0
tensorflow==2.13.1 | {
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https://api.github.com/repos/huggingface/datasets/issues/6949 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6949/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6949/comments | https://api.github.com/repos/huggingface/datasets/issues/6949/events | https://github.com/huggingface/datasets/issues/6949 | 2,332,336,573 | I_kwDODunzps6LBKG9 | 6,949 | load_dataset error | {
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"Hi, @lion-ops.\r\n\r\nIn our Continuous Integration we have many tests on loading JSON files and all of them work properly.\r\n\r\nCould you please share your \"train.json\" file, so that we can try to reproduce the issue you have? ",
"> Hi, @lion-ops.\r\n> \r\n> In our Continuous Integration we have many tests ... | 2024-06-04T01:24:45Z | 2024-07-01T11:33:46Z | 2024-07-01T11:33:46Z | NONE | null | null | {
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} | ### Describe the bug
Why does the program get stuck when I use load_dataset method, and it still gets stuck after loading for several hours? In fact, my json file is only 21m, and I can load it in one go using open('', 'r').
### Steps to reproduce the bug
1. pip install datasets==2.19.2
2. from datasets import Dataset, DatasetDict, NamedSplit, Split, load_dataset
3. data = load_dataset('json', data_files='train.json')
### Expected behavior
It is able to load my json correctly
### Environment info
datasets==2.19.2 | {
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https://api.github.com/repos/huggingface/datasets/issues/6947 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6947/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6947/comments | https://api.github.com/repos/huggingface/datasets/issues/6947/events | https://github.com/huggingface/datasets/issues/6947 | 2,331,114,055 | I_kwDODunzps6K8fpH | 6,947 | FileNotFoundError：error when loading C4 dataset | {
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"same problem here",
"Hello,\r\n\r\nAre you sure you are really using datasets version 2.19.2? We just made the patch release yesterday specifically to fix this issue:\r\n- #6925\r\n\r\nI can't reproduce the error:\r\n```python\r\nIn [1]: from datasets import load_dataset\r\n\r\nIn [2]: ds = load_dataset('allenai... | 2024-06-03T13:06:33Z | 2024-06-25T06:21:28Z | 2024-06-25T06:21:28Z | NONE | null | null | {
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} | ### Describe the bug
can't load c4 datasets
When I replace the datasets package to 2.12.2 I get raise datasets.utils.info_utils.ExpectedMoreSplits: {'train'}
How can I fix this？
### Steps to reproduce the bug
1.from datasets import load_dataset
2.dataset = load_dataset('allenai/c4', data_files={'validation': 'en/c4-validation.00003-of-00008.json.gz'}, split='validation')
3. raise FileNotFoundError(
FileNotFoundError: Couldn't find a dataset script at local_path/c4_val/allenai/c4/c4.py or any data file in the same directory. Couldn't find 'allenai/c4' on the Hugging Face Hub either: FileNotFoundError: Unable to find 'hf://datasets/allenai/c4@1588ec454efa1a09f29cd18ddd04fe05fc8653a2/en/c4-validation.00003-of-00008.json.gz' with any supported extension ['.csv', '.tsv', '.json', '.jsonl', '.parquet', '.geoparquet', '.gpq', '.arrow', '.txt', '.tar', '.blp', '.bmp', '.dib', '.bufr', '.cur', '.pcx', '.dcx', '.dds', '.ps', '.eps', '.fit', '.fits', '.fli', '.flc', '.ftc', '.ftu', '.gbr', '.gif', '.grib', '.h5', '.hdf', '.png', '.apng', '.jp2', '.j2k', '.jpc', '.jpf', '.jpx', '.j2c', '.icns', '.ico', '.im', '.iim', '.tif', '.tiff', '.jfif', '.jpe', '.jpg', '.jpeg', '.mpg', '.mpeg', '.msp', '.pcd', '.pxr', '.pbm', '.pgm', '.ppm', '.pnm', '.psd', '.bw', '.rgb', '.rgba', '.sgi', '.ras', '.tga', '.icb', '.vda', '.vst', '.webp', '.wmf', '.emf', '.xbm', '.xpm', '.BLP', '.BMP', '.DIB', '.BUFR', '.CUR', '.PCX', '.DCX', '.DDS', '.PS', '.EPS', '.FIT', '.FITS', '.FLI', '.FLC', '.FTC', '.FTU', '.GBR', '.GIF', '.GRIB', '.H5', '.HDF', '.PNG', '.APNG', '.JP2', '.J2K', '.JPC', '.JPF', '.JPX', '.J2C', '.ICNS', '.ICO', '.IM', '.IIM', '.TIF', '.TIFF', '.JFIF', '.JPE', '.JPG', '.JPEG', '.MPG', '.MPEG', '.MSP', '.PCD', '.PXR', '.PBM', '.PGM', '.PPM', '.PNM', '.PSD', '.BW', '.RGB', '.RGBA', '.SGI', '.RAS', '.TGA', '.ICB', '.VDA', '.VST', '.WEBP', '.WMF', '.EMF', '.XBM', '.XPM', '.aiff', '.au', '.avr', '.caf', '.flac', '.htk', '.svx', '.mat4', '.mat5', '.mpc2k', '.ogg', '.paf', '.pvf', '.raw', '.rf64', '.sd2', '.sds', '.ircam', '.voc', '.w64', '.wav', '.nist', '.wavex', '.wve', '.xi', '.mp3', '.opus', '.AIFF', '.AU', '.AVR', '.CAF', '.FLAC', '.HTK', '.SVX', '.MAT4', '.MAT5', '.MPC2K', '.OGG', '.PAF', '.PVF', '.RAW', '.RF64', '.SD2', '.SDS', '.IRCAM', '.VOC', '.W64', '.WAV', '.NIST', '.WAVEX', '.WVE', '.XI', '.MP3', '.OPUS', '.zip']
### Expected behavior
The data was successfully imported
### Environment info
python version 3.9
datasets version 2.19.2 | {
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https://api.github.com/repos/huggingface/datasets/issues/6942 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6942/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6942/comments | https://api.github.com/repos/huggingface/datasets/issues/6942/events | https://github.com/huggingface/datasets/issues/6942 | 2,329,562,382 | I_kwDODunzps6K2k0O | 6,942 | Import sorting is disabled by flake8 noqa directive after switching to ruff linter | {
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} | When we switched to `ruff` linter in PR:
- #5519
import sorting was disabled in all files containing the `# flake8: noqa` directive
- https://github.com/astral-sh/ruff/issues/11679
We should re-enable import sorting on those files. | {
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https://api.github.com/repos/huggingface/datasets/issues/6939 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6939/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6939/comments | https://api.github.com/repos/huggingface/datasets/issues/6939/events | https://github.com/huggingface/datasets/issues/6939 | 2,328,059,386 | I_kwDODunzps6Kw136 | 6,939 | ExpectedMoreSplits error when using data_dir | {
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} | As reported by @regisss, an `ExpectedMoreSplits` error is raised when passing `data_dir`:
```python
from datasets import load_dataset
dataset = load_dataset(
"lvwerra/stack-exchange-paired",
split="train",
cache_dir=None,
data_dir="data/rl",
)
```
```
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/usr/local/lib/python3.10/dist-packages/datasets/load.py", line 2609, in load_dataset
builder_instance.download_and_prepare(
File "/usr/local/lib/python3.10/dist-packages/datasets/builder.py", line 1027, in download_and_prepare
self._download_and_prepare(
File "/usr/local/lib/python3.10/dist-packages/datasets/builder.py", line 1140, in _download_and_prepare
verify_splits(self.info.splits, split_dict)
File "/usr/local/lib/python3.10/dist-packages/datasets/utils/info_utils.py", line 92, in verify_splits
raise ExpectedMoreSplits(str(set(expected_splits) - set(recorded_splits)))
datasets.utils.info_utils.ExpectedMoreSplits: {'test'}
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/6918 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6918/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6918/comments | https://api.github.com/repos/huggingface/datasets/issues/6918/events | https://github.com/huggingface/datasets/issues/6918 | 2,315,322,738 | I_kwDODunzps6KAQVy | 6,918 | NonMatchingSplitsSizesError when using data_dir | {
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"Thanks for reporting, @srehaag.\r\n\r\nWe are investigating this issue.",
"I confirm there is a bug for data-based Hub datasets when the user passes `data_dir`, which was introduced by PR:\r\n- #6714"
] | 2024-05-24T12:43:39Z | 2024-05-31T17:10:38Z | 2024-05-31T17:10:38Z | NONE | null | null | {
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} | ### Describe the bug
Loading a dataset from with a data_dir argument generates a NonMatchingSplitsSizesError if there are multiple directories in the dataset.
This appears to happen because the expected split is calculated based on the data in all the directories whereas the recorded split is calculated based on the data in the directory specified using the data_dir argument.
This is recent behavior. Until the past few weeks loading using the data_dir argument worked without any issue.
### Steps to reproduce the bug
Simple test dataset available here: https://huggingface.co/datasets/srehaag/hf-bug-temp
The dataset contains two directories "data1" and "data2", each with a file called "train.parquet" with a 2 x 5 table.
from datasets import load_dataset
dataset = load_dataset("srehaag/hf-bug-temp", data_dir = "data1")
Generates:
---------------------------------------------------------------------------
NonMatchingSplitsSizesError Traceback (most recent call last)
Cell In[3], <a href='vscode-notebook-cell:?execution_count=3&line=2'>line 2</a>
<a href='vscode-notebook-cell:?execution_count=3&line=1'>1</a> from datasets import load_dataset
----> <a href='vscode-notebook-cell:?execution_count=3&line=2'>2</a> dataset = load_dataset("srehaag/hf-bug-temp", data_dir = "data1")
File ~/.python/current/lib/python3.10/site-packages/datasets/load.py:2609, in load_dataset(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, verification_mode, ignore_verifications, keep_in_memory, save_infos, revision, token, use_auth_token, task, streaming, num_proc, storage_options, trust_remote_code, **config_kwargs)
<a href='~/.python/current/lib/python3.10/site-packages/datasets/load.py:2606'>2606</a> return builder_instance.as_streaming_dataset(split=split)
<a href='~/.python/current/lib/python3.10/site-packages/datasets/load.py:2608'>2608</a> # Download and prepare data
-> <a href='~/.python/current/lib/python3.10/site-packages/datasets/load.py:2609'>2609</a> builder_instance.download_and_prepare(
<a href='~/.python/current/lib/python3.10/site-packages/datasets/load.py:2610'>2610</a> download_config=download_config,
<a href='~/.python/current/lib/python3.10/site-packages/datasets/load.py:2611'>2611</a> download_mode=download_mode,
<a href='~/.python/current/lib/python3.10/site-packages/datasets/load.py:2612'>2612</a> verification_mode=verification_mode,
<a href='~/.python/current/lib/python3.10/site-packages/datasets/load.py:2613'>2613</a> num_proc=num_proc,
<a href='~/.python/current/lib/python3.10/site-packages/datasets/load.py:2614'>2614</a> storage_options=storage_options,
<a href='~/.python/current/lib/python3.10/site-packages/datasets/load.py:2615'>2615</a> )
<a href='~/.python/current/lib/python3.10/site-packages/datasets/load.py:2617'>2617</a> # Build dataset for splits
<a href='~/.python/current/lib/python3.10/site-packages/datasets/load.py:2618'>2618</a> keep_in_memory = (
<a href='~/.python/current/lib/python3.10/site-packages/datasets/load.py:2619'>2619</a> keep_in_memory if keep_in_memory is not None else is_small_dataset(builder_instance.info.dataset_size)
<a href='~/.python/current/lib/python3.10/site-packages/datasets/load.py:2620'>2620</a> )
File ~/.python/current/lib/python3.10/site-packages/datasets/builder.py:1027, in DatasetBuilder.download_and_prepare(self, output_dir, download_config, download_mode, verification_mode, ignore_verifications, try_from_hf_gcs, dl_manager, base_path, use_auth_token, file_format, max_shard_size, num_proc, storage_options, **download_and_prepare_kwargs)
<a href='~/.python/current/lib/python3.10/site-packages/datasets/builder.py:1025'>1025</a> if num_proc is not None:
<a href='~/.python/current/lib/python3.10/site-packages/datasets/builder.py:1026'>1026</a> prepare_split_kwargs["num_proc"] = num_proc
-> <a href='~/.python/current/lib/python3.10/site-packages/datasets/builder.py:1027'>1027</a> self._download_and_prepare(
<a href='~/.python/current/lib/python3.10/site-packages/datasets/builder.py:1028'>1028</a> dl_manager=dl_manager,
<a href='~/.python/current/lib/python3.10/site-packages/datasets/builder.py:1029'>1029</a> verification_mode=verification_mode,
<a href='~/.python/current/lib/python3.10/site-packages/datasets/builder.py:1030'>1030</a> **prepare_split_kwargs,
<a href='~/.python/current/lib/python3.10/site-packages/datasets/builder.py:1031'>1031</a> **download_and_prepare_kwargs,
<a href='~/.python/current/lib/python3.10/site-packages/datasets/builder.py:1032'>1032</a> )
<a href='~/.python/current/lib/python3.10/site-packages/datasets/builder.py:1033'>1033</a> # Sync info
<a href='~/.python/current/lib/python3.10/site-packages/datasets/builder.py:1034'>1034</a> self.info.dataset_size = sum(split.num_bytes for split in self.info.splits.values())
File ~/.python/current/lib/python3.10/site-packages/datasets/builder.py:1140, in DatasetBuilder._download_and_prepare(self, dl_manager, verification_mode, **prepare_split_kwargs)
<a href='~/.python/current/lib/python3.10/site-packages/datasets/builder.py:1137'>1137</a> dl_manager.manage_extracted_files()
<a href='~/.python/current/lib/python3.10/site-packages/datasets/builder.py:1139'>1139</a> if verification_mode == VerificationMode.BASIC_CHECKS or verification_mode == VerificationMode.ALL_CHECKS:
-> <a href='~/.python/current/lib/python3.10/site-packages/datasets/builder.py:1140'>1140</a> verify_splits(self.info.splits, split_dict)
<a href='~/.python/current/lib/python3.10/site-packages/datasets/builder.py:1142'>1142</a> # Update the info object with the splits.
<a href='~/.python/current/lib/python3.10/site-packages/datasets/builder.py:1143'>1143</a> self.info.splits = split_dict
File ~/.python/current/lib/python3.10/site-packages/datasets/utils/info_utils.py:101, in verify_splits(expected_splits, recorded_splits)
<a href='~/.python/current/lib/python3.10/site-packages/datasets/utils/info_utils.py:95'>95</a> bad_splits = [
<a href='~/.python/current/lib/python3.10/site-packages/datasets/utils/info_utils.py:96'>96</a> {"expected": expected_splits[name], "recorded": recorded_splits[name]}
<a href='~/.python/current/lib/python3.10/site-packages/datasets/utils/info_utils.py:97'>97</a> for name in expected_splits
<a href='~/.python/current/lib/python3.10/site-packages/datasets/utils/info_utils.py:98'>98</a> if expected_splits[name].num_examples != recorded_splits[name].num_examples
<a href='~/.python/current/lib/python3.10/site-packages/datasets/utils/info_utils.py:99'>99</a> ]
<a href='~/.python/current/lib/python3.10/site-packages/datasets/utils/info_utils.py:100'>100</a> if len(bad_splits) > 0:
--> <a href='~/.python/current/lib/python3.10/site-packages/datasets/utils/info_utils.py:101'>101</a> raise NonMatchingSplitsSizesError(str(bad_splits))
<a href='~/.python/current/lib/python3.10/site-packages/datasets/utils/info_utils.py:102'>102</a> logger.info("All the splits matched successfully.")
NonMatchingSplitsSizesError: [{'expected': SplitInfo(name='train', num_bytes=212, num_examples=10, shard_lengths=None, dataset_name=None), 'recorded': SplitInfo(name='train', num_bytes=106, num_examples=5, shard_lengths=None, dataset_name='hf-bug-temp')}]
__________
By contrast, this loads the data from both data1/train.parquet and data2/train.parquet without any error message:
from datasets import load_dataset
dataset = load_dataset("srehaag/hf-bug-temp")
### Expected behavior
Should load the 5 x 2 table from data1/train.parquet without error message.
### Environment info
Used Codespaces to simplify environment (see details below), but bug is present across various configurations.
- `datasets` version: 2.19.1
- Platform: Linux-6.5.0-1021-azure-x86_64-with-glibc2.31
- Python version: 3.10.13
- `huggingface_hub` version: 0.23.1
- PyArrow version: 16.1.0
- Pandas version: 2.2.2
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https://api.github.com/repos/huggingface/datasets/issues/6916 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6916/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6916/comments | https://api.github.com/repos/huggingface/datasets/issues/6916/events | https://github.com/huggingface/datasets/issues/6916 | 2,311,675,564 | I_kwDODunzps6JyV6s | 6,916 | ```push_to_hub()``` - Prevent Automatic Generation of Splits | {
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} | ### Describe the bug
I currently have a dataset which has not been splited. When pushing the dataset to my hugging face dataset repository, it is split into a testing and training set. How can I prevent the split from happening?
### Steps to reproduce the bug
1. Have a unsplit dataset
```python
Dataset({ features: ['input', 'output', 'Attack', '__index_level_0__'], num_rows: 944685 })
```
2. Push it to huggingface
```python
dataset.push_to_hub(dataset_name)
```
3. On the hugging face dataset repo, the dataset then appears to be splited:
4. Indeed, when loading the dataset from this repo, the dataset is split in two testing and training set.
```python
from datasets import load_dataset, Dataset
dataset = load_dataset("Jetlime/NF-CSE-CIC-IDS2018-v2", streaming=True)
dataset
```
output:
```
IterableDatasetDict({
train: IterableDataset({
features: ['input', 'output', 'Attack', '__index_level_0__'],
n_shards: 2
})
test: IterableDataset({
features: ['input', 'output', 'Attack', '__index_level_0__'],
n_shards: 1
})
```
### Expected behavior
The dataset shall not be splited, as not requested.
### Environment info
- `datasets` version: 2.19.1
- Platform: Linux-6.2.0-35-generic-x86_64-with-glibc2.35
- Python version: 3.10.12
- `huggingface_hub` version: 0.23.0
- PyArrow version: 15.0.2
- Pandas version: 2.2.2
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https://api.github.com/repos/huggingface/datasets/issues/6913 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6913/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6913/comments | https://api.github.com/repos/huggingface/datasets/issues/6913/events | https://github.com/huggingface/datasets/issues/6913 | 2,309,605,889 | I_kwDODunzps6JqcoB | 6,913 | Column order is nondeterministic when loading from JSON | {
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} | As reported by @meg-huggingface, the order of the JSON object keys is not preserved while loading a dataset from a JSON file with a list of objects.
For example, when loading a JSON files with a list of objects, each with the following ordered keys:
- [ID, Language, Topic],
the resulting dataset may have columns:
- [ID, Topic, Language], or
- [Topic, Language, ID], or
- [Topic, ID, Language],...
This issue is caused by the use of a Python set (which does not preserve the order):
https://github.com/huggingface/datasets/blob/60d21efbc01e15d0b596ac1072750cbecd91548a/src/datasets/packaged_modules/json/json.py#L168
introduced in
- #5772 | {
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https://api.github.com/repos/huggingface/datasets/issues/6908 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6908/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6908/comments | https://api.github.com/repos/huggingface/datasets/issues/6908/events | https://github.com/huggingface/datasets/issues/6908 | 2,304,958,116 | I_kwDODunzps6JYt6k | 6,908 | Fail to load "stas/c4-en-10k" dataset since 2.16 version | {
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"I am not able to reproduce the error with datasets 2.19.1:\r\n```python\r\nIn [1]: from datasets import load_dataset; ds = load_dataset(\"stas/c4-en-10k\", streaming=True); item = next(iter(ds[\"train\"])); item\r\nOut[1]: {'text': 'Beginners BBQ Class Taking Place in Missoula!\\nDo you want to get better at makin... | 2024-05-20T02:43:59Z | 2024-05-24T10:58:09Z | 2024-05-24T10:58:09Z | NONE | null | null | {
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} | ### Describe the bug
When update datasets library to version 2.16+ ( I test it on 2.16, 2.19.0 and 2.19.1), using the following code to load stas/c4-en-10k dataset
```python
from datasets import load_dataset, Dataset
dataset = load_dataset('stas/c4-en-10k')
```
and then it raise UnicodeDecodeError like
```
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/*/conda3/envs/watermark/lib/python3.10/site-packages/datasets/load.py", line 2523, in load_dataset
builder_instance = load_dataset_builder(
File "/home/*/conda3/envs/watermark/lib/python3.10/site-packages/datasets/load.py", line 2195, in load_dataset_builder
dataset_module = dataset_module_factory(
File "/home/*/conda3/envs/watermark/lib/python3.10/site-packages/datasets/load.py", line 1846, in dataset_module_factory
raise e1 from None
File "/home/*/conda3/envs/watermark/lib/python3.10/site-packages/datasets/load.py", line 1798, in dataset_module_factory
can_load_config_from_parquet_export = "DEFAULT_CONFIG_NAME" not in f.read()
File "/home/*/conda3/envs/watermark/lib/python3.10/codecs.py", line 322, in decode
(result, consumed) = self._buffer_decode(data, self.errors, final)
UnicodeDecodeError: 'utf-8' codec can't decode byte 0x8b in position 1: invalid start byte
```
I found that fs.open loads a gzip file and parses it like plain text using utf-8 encoder.
```python
fs = HfFileSystem('https://huggingface.co')
fs.open("datasets/stas/c4-en-10k/c4-en-10k.py", "rb")
data = fs.read() # data is gzip bytes begin with b'\x1f\x8b\x08\x00\x00\tn\x88\x00...'
data2 = unzip_gzip_bytes(data) # data2 is what we want: '# coding=utf-8\n# Copyright 2020 The HuggingFace Datasets...'
```
### Steps to reproduce the bug
1. Install datasets between version 2.16 and 2.19
2. Use `datasets.load_dataset` method to load `stas/c4-en-10k` dataset.
### Expected behavior
Load dataset normally.
### Environment info
Platform = Linux-5.4.0-159-generic-x86_64-with-glibc2.35
Python = 3.10.14
Datasets = 2.19 | {
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https://api.github.com/repos/huggingface/datasets/issues/6906 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6906/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6906/comments | https://api.github.com/repos/huggingface/datasets/issues/6906/events | https://github.com/huggingface/datasets/issues/6906 | 2,303,679,119 | I_kwDODunzps6JT1qP | 6,906 | irc_disentangle - Issue with splitting data | {
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"Thank you I will try this out!\r\n\r\nOn Tue, Jun 11, 2024 at 3:55 AM Vincent Lau ***@***.***>\r\nwrote:\r\n\r\n> I add a \"streaming=True\" after the name of the dataset, and it\r\n> works.....hope it can help you\r\n>\r\n> And if you install the version datasets==2.15.0, this bug will not happen.\r\n> I don't kn... | 2024-05-17T23:19:37Z | 2024-07-16T00:21:56Z | 2024-07-08T06:18:08Z | NONE | null | null | {
"completed": 0,
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} | ### Describe the bug
I am trying to access your database through python using "datasets.load_dataset("irc_disentangle")" and I am getting this error message:
ValueError: Instruction "train" corresponds to no data!
### Steps to reproduce the bug
import datasets
ds = datasets.load_dataset('irc_disentangle')
ds
### Expected behavior
The data is supposed to load into ds and be accessable as such:
ds['train'][1050], ds['train'][1055]
### Environment info
I tired Python 3.12 and 3.10 | {
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https://api.github.com/repos/huggingface/datasets/issues/6905 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6905/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6905/comments | https://api.github.com/repos/huggingface/datasets/issues/6905/events | https://github.com/huggingface/datasets/issues/6905 | 2,303,098,587 | I_kwDODunzps6JRn7b | 6,905 | Extraction protocol for arrow files is not defined | {
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"Fixed in https://github.com/huggingface/datasets/pull/7083"
] | 2024-05-17T16:01:41Z | 2025-02-06T19:50:22Z | 2025-02-06T19:50:20Z | NONE | null | null | {
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} | ### Describe the bug
Passing files with `.arrow` extension into data_files argument, at least when `streaming=True` is very slow.
### Steps to reproduce the bug
Basically it goes through the `_get_extraction_protocol` method located [here](https://github.com/huggingface/datasets/blob/main/src/datasets/utils/file_utils.py#L820)
The method then looks at some base known extensions where `arrow` is not defined so it proceeds to determine the compression with the magic number method which is slow when dealing with a lot of files which are stored in s3 and by looking at this predefined list, I don't see `arrow` in there either so in the end it return None:
```
MAGIC_NUMBER_TO_COMPRESSION_PROTOCOL = {
bytes.fromhex("504B0304"): "zip",
bytes.fromhex("504B0506"): "zip", # empty archive
bytes.fromhex("504B0708"): "zip", # spanned archive
bytes.fromhex("425A68"): "bz2",
bytes.fromhex("1F8B"): "gzip",
bytes.fromhex("FD377A585A00"): "xz",
bytes.fromhex("04224D18"): "lz4",
bytes.fromhex("28B52FFD"): "zstd",
}
```
### Expected behavior
My expectation is that `arrow` would be in the known lists so it would return None without going through the magic number method.
### Environment info
datasets 2.19.0 | {
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} | CLI convert_to_parquet cannot create "script" branch on 3rd party repos.
It can only create it on repos where the user executing the script has write access.
Otherwise, a 403 Forbidden HTTPError is raised:
```
Traceback (most recent call last):
File "/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_errors.py", line 304, in hf_raise_for_status
response.raise_for_status()
File "/usr/local/lib/python3.10/dist-packages/requests/models.py", line 1021, in raise_for_status
raise HTTPError(http_error_msg, response=self)
requests.exceptions.HTTPError: 403 Client Error: Forbidden for url: https://huggingface.co/api/datasets/ORG/DATASET/branch/script
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/usr/local/bin/datasets-cli", line 8, in <module>
sys.exit(main())
File "/usr/local/lib/python3.10/dist-packages/datasets/commands/datasets_cli.py", line 41, in main
service.run()
File "/usr/local/lib/python3.10/dist-packages/datasets/commands/convert_to_parquet.py", line 92, in run
create_branch(dataset_id, branch="script", repo_type="dataset", token=token, exist_ok=True)
File "/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_validators.py", line 114, in _inner_fn
return fn(*args, **kwargs)
File "/usr/local/lib/python3.10/dist-packages/huggingface_hub/hf_api.py", line 5503, in create_branch
hf_raise_for_status(response)
File "/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_errors.py", line 367, in hf_raise_for_status
raise HfHubHTTPError(message, response=response) from e
huggingface_hub.utils._errors.HfHubHTTPError: (Request ID: Root=1-6645ee0d-4db1ed8a1fbe04956be15897;139a6e23-df7d-4f62-b5ba-adb6d8e6e696)
403 Forbidden: Forbidden: cannot write to script.
Cannot access content at: https://huggingface.co/api/datasets/ORG/DATASET/branch/script.
If you are trying to create or update content,make sure you have a token with the `write` role.
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https://api.github.com/repos/huggingface/datasets/issues/6900 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6900/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6900/comments | https://api.github.com/repos/huggingface/datasets/issues/6900/events | https://github.com/huggingface/datasets/issues/6900 | 2,298,489,733 | I_kwDODunzps6JACuF | 6,900 | [WebDataset] KeyError with user-defined `Features` when a field is missing in an example | {
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"@lhoestq How difficult of fix is this?",
"It shouldn't be difficult, I think it's just a matter of adding the missing fields from `self.config.features` in `example` here: before it iterates on image_field_names and audio_field_names. A missing field should have a value set to None\r\n\r\nhttps://github.com/hugg... | 2024-05-15T17:48:34Z | 2024-06-28T09:30:13Z | 2024-06-28T09:30:13Z | MEMBER | null | null | {
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} | reported at https://huggingface.co/datasets/ProGamerGov/synthetic-dataset-1m-dalle3-high-quality-captions/discussions/1
```
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 109, in _generate_examples
example[field_name] = {"path": example["__key__"] + "." + field_name, "bytes": example[field_name]}
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https://api.github.com/repos/huggingface/datasets/issues/6897 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6897/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6897/comments | https://api.github.com/repos/huggingface/datasets/issues/6897/events | https://github.com/huggingface/datasets/issues/6897 | 2,293,428,243 | I_kwDODunzps6IsvAT | 6,897 | datasets template guide :: issue in documentation YAML | {
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"Hello, @bghira.\r\n\r\nThanks for reporting. Please note that the text originating the error is not supposed to be valid YAML: it contains the instructions to generate the actual YAML content, that should replace the instructions comment.\r\n\r\nOn the other hand, I agree that it is not nice to have that YAML erro... | 2024-05-13T17:33:59Z | 2024-05-16T14:28:17Z | 2024-05-16T14:28:17Z | NONE | null | null | {
"completed": 0,
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} | ### Describe the bug
There is a YAML error at the top of the page, and I don't think it's supposed to be there
### Steps to reproduce the bug
1. Browse to [this tutorial document](https://github.com/huggingface/datasets/blob/main/templates/README_guide.md)
2. Observe a big red error at the top
3. The rest of the document remains functional
### Expected behavior
I think the YAML block should be displayed or ignored.
### Environment info
N/A | {
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https://api.github.com/repos/huggingface/datasets/issues/6894 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6894/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6894/comments | https://api.github.com/repos/huggingface/datasets/issues/6894/events | https://github.com/huggingface/datasets/issues/6894 | 2,292,840,226 | I_kwDODunzps6Iqfci | 6,894 | Better document defaults of to_json | {
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Related to:
- #6891 | {
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"Hi @DarshanDeshpande,\r\n\r\nPlease note that the default format of the method `Dataset.to_json` is [JSON-Lines](https://jsonlines.org/): it passes `orient=\"records\", lines=True` to `pandas.DataFrame.to_json`. This format is specially useful for large datasets, since unlike regular JSON files, it does not requir... | 2024-05-12T01:02:51Z | 2024-05-16T14:32:55Z | 2024-05-12T07:02:02Z | NONE | null | null | {
"completed": 0,
"percent_completed": 0,
"total": 0
} | ### Describe the bug
Datasets stored in the JSON format cannot be loaded using `json.load()`
### Steps to reproduce the bug
```
import json
from datasets import load_dataset
dataset = load_dataset("squad")
train_dataset, test_dataset = dataset["train"], dataset["validation"]
test_dataset.to_json("full_dataset.json")
# This works
loaded_test = load_dataset("json", data_files="full_dataset.json")
# This fails
loaded_test = json.load(open("full_dataset.json", "r"))
```
### Expected behavior
The JSON should be correctly formatted when writing so that it can be loaded using `json.load()`.
### Environment info
Colab: https://colab.research.google.com/drive/1st1iStFUVgu9ZPvnzSzL4vDeYWDwYpUm?usp=sharing | {
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https://api.github.com/repos/huggingface/datasets/issues/6884 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6884/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6884/comments | https://api.github.com/repos/huggingface/datasets/issues/6884/events | https://github.com/huggingface/datasets/issues/6884 | 2,284,839,687 | I_kwDODunzps6IL-MH | 6,884 | CI is broken after jax-0.4.27 release: AttributeError: 'jaxlib.xla_extension.DeviceList' object has no attribute 'device' | {
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```Python traceback
AttributeError: 'jaxlib.xla_extension.DeviceList' object has no attribute 'device'. Did you mean: 'devices'?
```
See: https://github.com/huggingface/datasets/actions/runs/8997488610/job/24715736153
```Python traceback
___________________ FormatterTest.test_jax_formatter_device ____________________
[gw1] linux -- Python 3.10.14 /opt/hostedtoolcache/Python/3.10.14/x64/bin/python
self = <tests.test_formatting.FormatterTest testMethod=test_jax_formatter_device>
@require_jax
def test_jax_formatter_device(self):
import jax
from datasets.formatting import JaxFormatter
pa_table = self._create_dummy_table()
device = jax.devices()[0]
formatter = JaxFormatter(device=str(device))
row = formatter.format_row(pa_table)
> assert row["a"].device() == device
E AttributeError: 'jaxlib.xla_extension.DeviceList' object has no attribute 'device'. Did you mean: 'devices'?
tests/test_formatting.py:630: AttributeError
``` | {
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"@albertvillanova @lhoestq just ran into it and requiring newer pillow isn't a solution as it breaks Pillow-SIMD which is behind Pillow quite a few versions but necessary for training with reasonable throughput. \r\n\r\nA couple things here... \r\n\r\n1. This can be done with a method that isn't an issue for any so... | 2024-05-08T06:33:57Z | 2024-07-18T06:49:30Z | 2024-05-16T14:34:03Z | MEMBER | null | null | {
"completed": 0,
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} | When trying to load an image dataset in an old Python environment (with Pillow-8.4.0), an error is raised:
```Python traceback
AttributeError: module 'PIL.Image' has no attribute 'ExifTags'
```
The error traceback:
```Python traceback
~/huggingface/datasets/src/datasets/iterable_dataset.py in __iter__(self)
1391 # `IterableDataset` automatically fills missing columns with None.
1392 # This is done with `_apply_feature_types_on_example`.
-> 1393 example = _apply_feature_types_on_example(
1394 example, self.features, token_per_repo_id=self._token_per_repo_id
1395 )
~/huggingface/datasets/src/datasets/iterable_dataset.py in _apply_feature_types_on_example(example, features, token_per_repo_id)
1080 encoded_example = features.encode_example(example)
1081 # Decode example for Audio feature, e.g.
-> 1082 decoded_example = features.decode_example(encoded_example, token_per_repo_id=token_per_repo_id)
1083 return decoded_example
1084
~/huggingface/datasets/src/datasets/features/features.py in decode_example(self, example, token_per_repo_id)
1974
-> 1975 return {
1976 column_name: decode_nested_example(feature, value, token_per_repo_id=token_per_repo_id)
1977 if self._column_requires_decoding[column_name]
~/huggingface/datasets/src/datasets/features/features.py in <dictcomp>(.0)
1974
1975 return {
-> 1976 column_name: decode_nested_example(feature, value, token_per_repo_id=token_per_repo_id)
1977 if self._column_requires_decoding[column_name]
1978 else value
~/huggingface/datasets/src/datasets/features/features.py in decode_nested_example(schema, obj, token_per_repo_id)
1339 # we pass the token to read and decode files from private repositories in streaming mode
1340 if obj is not None and schema.decode:
-> 1341 return schema.decode_example(obj, token_per_repo_id=token_per_repo_id)
1342 return obj
1343
~/huggingface/datasets/src/datasets/features/image.py in decode_example(self, value, token_per_repo_id)
187 image = PIL.Image.open(BytesIO(bytes_))
188 image.load() # to avoid "Too many open files" errors
--> 189 if image.getexif().get(PIL.Image.ExifTags.Base.Orientation) is not None:
190 image = PIL.ImageOps.exif_transpose(image)
191 if self.mode and self.mode != image.mode:
~/huggingface/datasets/venv/lib/python3.9/site-packages/PIL/Image.py in __getattr__(name)
75 )
76 return categories[name]
---> 77 raise AttributeError(f"module '{__name__}' has no attribute '{name}'")
78
79
AttributeError: module 'PIL.Image' has no attribute 'ExifTags'
```
### Environment info
Since datasets 2.19.0 | {
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"ulimit -n 8192 can solve this problem",
"> ulimit -n 8192 can solve this problem\r\n\r\nWould there be a systematic way to do this ? The data loading is part of the [MTEB](https://github.com/embeddings-benchmark/mteb) library",
"> > ulimit -n 8192 can solve this problem\r\n> \r\n> Would there be a systematic w... | 2024-05-07T01:15:09Z | 2024-06-02T14:22:23Z | 2024-05-13T13:01:55Z | NONE | null | null | {
"completed": 0,
"percent_completed": 0,
"total": 0
} | ### Describe the bug
I am trying to load the 'default' subset of the following dataset which contains lots of files (828 per split): [https://huggingface.co/datasets/mteb/biblenlp-corpus-mmteb](https://huggingface.co/datasets/mteb/biblenlp-corpus-mmteb)
When trying to load it using the `load_dataset` function I get the following error
```python
>>> from datasets import load_dataset
>>> d = load_dataset('mteb/biblenlp-corpus-mmteb')
Downloading readme: 100%|████████████████████████████████████████████████████████████████████████| 201k/201k [00:00<00:00, 1.07MB/s]
Resolving data files: 100%|█████████████████████████████████████████████████████████████████████| 828/828 [00:00<00:00, 1069.15it/s]
Resolving data files: 100%|███████████████████████████████████████████████████████████████████| 828/828 [00:00<00:00, 436182.33it/s]
Resolving data files: 100%|█████████████████████████████████████████████████████████████████████| 828/828 [00:00<00:00, 2228.75it/s]
Resolving data files: 100%|███████████████████████████████████████████████████████████████████| 828/828 [00:00<00:00, 646478.73it/s]
Resolving data files: 100%|███████████████████████████████████████████████████████████████████| 828/828 [00:00<00:00, 831032.24it/s]
Resolving data files: 100%|███████████████████████████████████████████████████████████████████| 828/828 [00:00<00:00, 517645.51it/s]
Downloading data: 100%|████████████████████████████████████████████████████████████████████████| 828/828 [00:33<00:00, 24.87files/s]
Downloading data: 100%|████████████████████████████████████████████████████████████████████████| 828/828 [00:30<00:00, 27.48files/s]
Downloading data: 100%|████████████████████████████████████████████████████████████████████████| 828/828 [00:30<00:00, 26.94files/s]
Generating train split: 1571592 examples [00:03, 461438.97 examples/s]
Generating test split: 11163 examples [00:00, 118190.72 examples/s]
Traceback (most recent call last):
File ".env/lib/python3.12/site-packages/datasets/builder.py", line 1995, in _prepare_split_single
for _, table in generator:
File ".env/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 99, in _generate_tables
with open(file, "rb") as f:
^^^^^^^^^^^^^^^^
File ".env/lib/python3.12/site-packages/datasets/streaming.py", line 75, in wrapper
return function(*args, download_config=download_config, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File ".env/lib/python3.12/site-packages/datasets/utils/file_utils.py", line 1224, in xopen
file_obj = fsspec.open(file, mode=mode, *args, **kwargs).open()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File ".env/lib/python3.12/site-packages/fsspec/core.py", line 135, in open
return self.__enter__()
^^^^^^^^^^^^^^^^
File ".env/lib/python3.12/site-packages/fsspec/core.py", line 103, in __enter__
f = self.fs.open(self.path, mode=mode)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File ".env/lib/python3.12/site-packages/fsspec/spec.py", line 1293, in open
f = self._open(
^^^^^^^^^^^
File ".env/lib/python3.12/site-packages/datasets/filesystems/compression.py", line 81, in _open
return self.file.open()
^^^^^^^^^^^^^^^^
File ".env/lib/python3.12/site-packages/fsspec/core.py", line 135, in open
return self.__enter__()
^^^^^^^^^^^^^^^^
File ".env/lib/python3.12/site-packages/fsspec/core.py", line 103, in __enter__
f = self.fs.open(self.path, mode=mode)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File ".env/lib/python3.12/site-packages/fsspec/spec.py", line 1293, in open
f = self._open(
^^^^^^^^^^^
File ".env/lib/python3.12/site-packages/fsspec/implementations/local.py", line 197, in _open
return LocalFileOpener(path, mode, fs=self, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File ".env/lib/python3.12/site-packages/fsspec/implementations/local.py", line 322, in __init__
self._open()
File ".env/lib/python3.12/site-packages/fsspec/implementations/local.py", line 327, in _open
self.f = open(self.path, mode=self.mode)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
OSError: [Errno 24] Too many open files: '.cache/huggingface/datasets/downloads/3a347186abfc0f9c924dde0221d246db758c7232c0101523f04a87c17d696618'
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File ".env/lib/python3.12/site-packages/datasets/builder.py", line 981, in incomplete_dir
yield tmp_dir
File ".env/lib/python3.12/site-packages/datasets/builder.py", line 1027, in download_and_prepare
self._download_and_prepare(
File ".env/lib/python3.12/site-packages/datasets/builder.py", line 1122, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File ".env/lib/python3.12/site-packages/datasets/builder.py", line 1882, in _prepare_split
for job_id, done, content in self._prepare_split_single(
File ".env/lib/python3.12/site-packages/datasets/builder.py", line 2038, in _prepare_split_single
raise DatasetGenerationError("An error occurred while generating the dataset") from e
datasets.exceptions.DatasetGenerationError: An error occurred while generating the dataset
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File ".env/lib/python3.12/site-packages/datasets/load.py", line 2609, in load_dataset
builder_instance.download_and_prepare(
File ".env/lib/python3.12/site-packages/datasets/builder.py", line 1007, in download_and_prepare
with incomplete_dir(self._output_dir) as tmp_output_dir:
File "/usr/lib/python3.12/contextlib.py", line 158, in __exit__
self.gen.throw(value)
File ".env/lib/python3.12/site-packages/datasets/builder.py", line 988, in incomplete_dir
shutil.rmtree(tmp_dir)
File "/usr/lib/python3.12/shutil.py", line 785, in rmtree
_rmtree_safe_fd(fd, path, onexc)
File "/usr/lib/python3.12/shutil.py", line 661, in _rmtree_safe_fd
onexc(os.scandir, path, err)
File "/usr/lib/python3.12/shutil.py", line 657, in _rmtree_safe_fd
with os.scandir(topfd) as scandir_it:
^^^^^^^^^^^^^^^^^
OSError: [Errno 24] Too many open files: '.cache/huggingface/datasets/mteb___biblenlp-corpus-mmteb/default/0.0.0/3912ed967b0834547f35b2da9470c4976b357c9a.incomplete'
```
I looked for the maximum number of open files on my machine (Ubuntu 24.04) and it seems to be 1024, but even when I try to load a single split (`load_dataset('mteb/biblenlp-corpus-mmteb', split='train')`) I get the same error
### Steps to reproduce the bug
```python
from datasets import load_dataset
d = load_dataset('mteb/biblenlp-corpus-mmteb')
```
### Expected behavior
Load the dataset without error
### Environment info
- `datasets` version: 2.19.0
- Platform: Linux-6.8.0-31-generic-x86_64-with-glibc2.39
- Python version: 3.12.3
- `huggingface_hub` version: 0.23.0
- PyArrow version: 16.0.0
- Pandas version: 2.2.2
- `fsspec` version: 2024.3.1
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https://api.github.com/repos/huggingface/datasets/issues/6869 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6869/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6869/comments | https://api.github.com/repos/huggingface/datasets/issues/6869/events | https://github.com/huggingface/datasets/issues/6869 | 2,280,048,297 | I_kwDODunzps6H5sap | 6,869 | Download is broken for dict of dicts: FileNotFoundError | {
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"following_url": "https://api.github.com/users/albertvillanova/following{/o... | null | [] | 2024-05-06T05:13:36Z | 2024-05-06T09:25:53Z | 2024-05-06T09:25:53Z | MEMBER | null | null | {
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} | It seems there is a bug when downloading a dict of dicts of URLs introduced by:
- #6794
## Steps to reproduce the bug:
```python
from datasets import DownloadManager
dl_manager = DownloadManager()
paths = dl_manager.download({"train": {"frr": "hf://datasets/wikimedia/wikipedia/20231101.frr/train-00000-of-00001.parquet"}})
```
Stack trace:
```
---------------------------------------------------------------------------
FileNotFoundError Traceback (most recent call last)
<ipython-input-7-0e0d76d25b09> in <module>
----> 1 paths = dl_manager.download({"train": {"frr": "hf://datasets/wikimedia/wikipedia/20231101.frr/train-00000-of-00001.parquet"}})
.../huggingface/datasets/src/datasets/download/download_manager.py in download(self, url_or_urls)
255 start_time = datetime.now()
256 with stack_multiprocessing_download_progress_bars():
--> 257 downloaded_path_or_paths = map_nested(
258 download_func,
259 url_or_urls,
.../huggingface/datasets/src/datasets/utils/py_utils.py in map_nested(function, data_struct, dict_only, map_list, map_tuple, map_numpy, num_proc, parallel_min_length, batched, batch_size, types, disable_tqdm, desc)
506 batch_size = max(len(iterable) // num_proc + int(len(iterable) % num_proc > 0), 1)
507 iterable = list(iter_batched(iterable, batch_size))
--> 508 mapped = [
509 _single_map_nested((function, obj, batched, batch_size, types, None, True, None))
510 for obj in hf_tqdm(iterable, disable=disable_tqdm, desc=desc)
.../huggingface/datasets/src/datasets/utils/py_utils.py in <listcomp>(.0)
507 iterable = list(iter_batched(iterable, batch_size))
508 mapped = [
--> 509 _single_map_nested((function, obj, batched, batch_size, types, None, True, None))
510 for obj in hf_tqdm(iterable, disable=disable_tqdm, desc=desc)
511 ]
.../huggingface/datasets/src/datasets/utils/py_utils.py in _single_map_nested(args)
375 and all(not isinstance(v, types) for v in data_struct)
376 ):
--> 377 return [mapped_item for batch in iter_batched(data_struct, batch_size) for mapped_item in function(batch)]
378
379 # Reduce logging to keep things readable in multiprocessing with tqdm
.../huggingface/datasets/src/datasets/utils/py_utils.py in <listcomp>(.0)
375 and all(not isinstance(v, types) for v in data_struct)
376 ):
--> 377 return [mapped_item for batch in iter_batched(data_struct, batch_size) for mapped_item in function(batch)]
378
379 # Reduce logging to keep things readable in multiprocessing with tqdm
.../huggingface/datasets/src/datasets/download/download_manager.py in _download_batched(self, url_or_filenames, download_config)
311 )
312 else:
--> 313 return [
314 self._download_single(url_or_filename, download_config=download_config)
315 for url_or_filename in url_or_filenames
.../huggingface/datasets/src/datasets/download/download_manager.py in <listcomp>(.0)
312 else:
313 return [
--> 314 self._download_single(url_or_filename, download_config=download_config)
315 for url_or_filename in url_or_filenames
316 ]
.../huggingface/datasets/src/datasets/download/download_manager.py in _download_single(self, url_or_filename, download_config)
321 # append the relative path to the base_path
322 url_or_filename = url_or_path_join(self._base_path, url_or_filename)
--> 323 out = cached_path(url_or_filename, download_config=download_config)
324 out = tracked_str(out)
325 out.set_origin(url_or_filename)
.../huggingface/datasets/src/datasets/utils/file_utils.py in cached_path(url_or_filename, download_config, **download_kwargs)
220 elif is_local_path(url_or_filename):
221 # File, but it doesn't exist.
--> 222 raise FileNotFoundError(f"Local file {url_or_filename} doesn't exist")
223 else:
224 # Something unknown
FileNotFoundError: Local file .../huggingface/datasets/{'frr': 'hf:/datasets/wikimedia/wikipedia/20231101.frr/train-00000-of-00001.parquet'} doesn't exist
```
Related to:
- #6850
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https://api.github.com/repos/huggingface/datasets/issues/6868 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6868/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6868/comments | https://api.github.com/repos/huggingface/datasets/issues/6868/events | https://github.com/huggingface/datasets/issues/6868 | 2,279,385,159 | I_kwDODunzps6H3KhH | 6,868 | datasets.BuilderConfig does not work. | {
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"I guess the issue is caused by the customization of BuilderConfig that you use from the repo [https://github.com/BeyonderXX/InstructUIE](https://github.com/BeyonderXX/InstructUIE/blob/master/src/uie_dataset.py). You should report to them.\r\n\r\nI see you already opened an issue in their repo:\r\n- https://github.... | 2024-05-05T08:08:55Z | 2024-05-05T12:15:02Z | 2024-05-05T12:15:01Z | NONE | null | null | {
"completed": 0,
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} | ### Describe the bug
I custom a BuilderConfig and GeneratorBasedBuilder.
Here is the code for BuilderConfig
```
class UIEConfig(datasets.BuilderConfig):
def __init__(
self,
*args,
data_dir=None,
instruction_file=None,
instruction_strategy=None,
task_config_dir=None,
num_examples=None,
max_num_instances_per_task=None,
max_num_instances_per_eval_task=None,
over_sampling=None,
**kwargs
):
super().__init__(*args, **kwargs)
self.data_dir = data_dir
self.num_examples = num_examples
self.over_sampling = over_sampling
self.instructions = self._parse_instruction(instruction_file)
self.task_configs = self._parse_task_config(task_config_dir)
self.instruction_strategy = instruction_strategy
self.max_num_instances_per_task = max_num_instances_per_task
self.max_num_instances_per_eval_task = max_num_instances_per_eval_task
```
Besides, here is the code for GeneratorBasedBuilder.
```
class UIEInstructions(datasets.GeneratorBasedBuilder):
VERSION = datasets.Version("2.0.0")
BUILDER_CONFIG_CLASS = UIEConfig
BUILDER_CONFIGS = [
UIEConfig(name="default", description="Default config for NaturalInstructions")
]
DEFAULT_CONFIG_NAME = "default"
```
Here is the load_dataset
```
raw_datasets = load_dataset(
os.path.join(CURRENT_DIR, "uie_dataset.py"),
data_dir=data_args.data_dir,
task_config_dir=data_args.task_config_dir,
instruction_file=data_args.instruction_file,
instruction_strategy=data_args.instruction_strategy,
cache_dir=data_cache_dir, # for debug, change dataset size, otherwise open it
max_num_instances_per_task=data_args.max_num_instances_per_task,
max_num_instances_per_eval_task=data_args.max_num_instances_per_eval_task,
num_examples=data_args.num_examples,
over_sampling=data_args.over_sampling
)
```
Finally, I met the error.
```
BuilderConfig UIEConfig(name='default', version=0.0.0, data_dir=None, data_files=None, description='Default config for NaturalInstructions') doesn't have a 'task_config_dir' key.
```
I debugged the code, but I find the parameters added by me may not work.
### Steps to reproduce the bug
https://github.com/BeyonderXX/InstructUIE/blob/master/src/uie_dataset.py
### Expected behavior
```
BuilderConfig UIEConfig(name='default', version=0.0.0, data_dir=None, data_files=None, description='Default config for NaturalInstructions') doesn't have a 'task_config_dir' key.
```
### Environment info
torch 2.3.0+cu118
transformers 4.40.1
python 3.8 | {
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https://api.github.com/repos/huggingface/datasets/issues/6867 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6867/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6867/comments | https://api.github.com/repos/huggingface/datasets/issues/6867/events | https://github.com/huggingface/datasets/issues/6867 | 2,279,059,787 | I_kwDODunzps6H17FL | 6,867 | Improve performance of JSON loader | {
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"Thanks! Feel free to ping me for examples. May not respond immediately because we're all busy but would like to help.",
"Hi @natolambert, could you please give some examples of JSON files to benchmark?\r\n\r\nPlease note that this JSON file (https://huggingface.co/datasets/allenai/reward-bench-results/blob/main/... | 2024-05-04T15:04:16Z | 2024-05-17T16:22:28Z | 2024-05-17T16:22:28Z | MEMBER | null | null | {
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} | As reported by @natolambert, loading regular JSON files with `datasets` shows poor performance.
The cause is that we use the `json` Python standard library instead of other faster libraries. See my old comment: https://github.com/huggingface/datasets/pull/2638#pullrequestreview-706983714
> There are benchmarks that compare different JSON packages, with the Standard Library one among the worst performant:
> - https://github.com/ultrajson/ultrajson#benchmarks
> - https://github.com/ijl/orjson#performance
I remember having a discussion about this and it was decided that it was better not to include an additional dependency on a 3rd-party library.
However:
- We already depend on `pandas` and `pandas` depends on `ujson`: so we have an indirect dependency on `ujson`
- Even if the above were not the case, we always could include `ujson` as an optional extra dependency, and check at runtime if it is installed to decide which library to use, either json or ujson | {
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https://api.github.com/repos/huggingface/datasets/issues/6866 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6866/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6866/comments | https://api.github.com/repos/huggingface/datasets/issues/6866/events | https://github.com/huggingface/datasets/issues/6866 | 2,278,736,221 | I_kwDODunzps6H0sFd | 6,866 | DataFilesNotFoundError for datasets in the open-llm-leaderboard | {
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"Potentially related:\r\n* #6864\r\n* #6850\r\n* #6848\r\n* #6819",
"Hi @jerome-white, thnaks for reporting.\r\n\r\nHowever, I cannot reproduce your issue:\r\n```python\r\n>>> from datasets import get_dataset_config_names\r\n\r\n>>> get_dataset_config_names(\"open-llm-leaderboard/details_davidkim205__Rhea-72b-v0.... | 2024-05-04T04:59:00Z | 2024-05-14T08:09:56Z | 2024-05-14T08:09:56Z | NONE | null | null | {
"completed": 0,
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} | ### Describe the bug
When trying to get config names or load any dataset within the open-llm-leaderboard ecosystem (`open-llm-leaderboard/details_`) I receive the DataFilesNotFoundError. For the last month or so I've been loading datasets from the leaderboard almost everyday; yesterday was the first time I started seeing this.
### Steps to reproduce the bug
This snippet has three cells:
1. Loads the modules
2. Tries to get config names
3. Tries to load the dataset
I've chosen "davidkim205"'s Rhea-72b-v0.5 model because it is one of the best performers on the leaderboard should likely have no dataset issues:
```python
In [1]: from datasets import load_dataset, get_dataset_config_names
In [2]: get_dataset_config_names("open-llm-leaderboard/details_davidkim205__Rhea
...: -72b-v0.5")
---------------------------------------------------------------------------
DataFilesNotFoundError Traceback (most recent call last)
Cell In[2], line 1
----> 1 get_dataset_config_names("open-llm-leaderboard/details_davidkim205__Rhea-72b-v0.5")
File ~/open-llm-bda/venv/lib/python3.11/site-packages/datasets/inspect.py:347, in get_dataset_config_names(path, revision, download_config, download_mode, dynamic_modules_path, data_files, **download_kwargs)
291 def get_dataset_config_names(
292 path: str,
293 revision: Optional[Union[str, Version]] = None,
(...)
298 **download_kwargs,
299 ):
300 """Get the list of available config names for a particular dataset.
301
302 Args:
(...)
345 ```
346 """
--> 347 dataset_module = dataset_module_factory(
348 path,
349 revision=revision,
350 download_config=download_config,
351 download_mode=download_mode,
352 dynamic_modules_path=dynamic_modules_path,
353 data_files=data_files,
354 **download_kwargs,
355 )
356 builder_cls = get_dataset_builder_class(dataset_module, dataset_name=os.path.basename(path))
357 return list(builder_cls.builder_configs.keys()) or [
358 dataset_module.builder_kwargs.get("config_name", builder_cls.DEFAULT_CONFIG_NAME or "default")
359 ]
File ~/open-llm-bda/venv/lib/python3.11/site-packages/datasets/load.py:1821, in dataset_module_factory(path, revision, download_config, download_mode, dynamic_modules_path, data_dir, data_files, cache_dir, trust_remote_code, _require_default_config_name, _require_custom_configs, **download_kwargs)
1812 return LocalDatasetModuleFactoryWithScript(
1813 combined_path,
1814 download_mode=download_mode,
1815 dynamic_modules_path=dynamic_modules_path,
1816 trust_remote_code=trust_remote_code,
1817 ).get_module()
1818 elif os.path.isdir(path):
1819 return LocalDatasetModuleFactoryWithoutScript(
1820 path, data_dir=data_dir, data_files=data_files, download_mode=download_mode
-> 1821 ).get_module()
1822 # Try remotely
1823 elif is_relative_path(path) and path.count("/") <= 1:
File ~/open-llm-bda/venv/lib/python3.11/site-packages/datasets/load.py:1039, in LocalDatasetModuleFactoryWithoutScript.get_module(self)
1033 patterns = get_data_patterns(base_path)
1034 data_files = DataFilesDict.from_patterns(
1035 patterns,
1036 base_path=base_path,
1037 allowed_extensions=ALL_ALLOWED_EXTENSIONS,
1038 )
-> 1039 module_name, default_builder_kwargs = infer_module_for_data_files(
1040 data_files=data_files,
1041 path=self.path,
1042 )
1043 data_files = data_files.filter_extensions(_MODULE_TO_EXTENSIONS[module_name])
1044 # Collect metadata files if the module supports them
File ~/open-llm-bda/venv/lib/python3.11/site-packages/datasets/load.py:597, in infer_module_for_data_files(data_files, path, download_config)
595 raise ValueError(f"Couldn't infer the same data file format for all splits. Got {split_modules}")
596 if not module_name:
--> 597 raise DataFilesNotFoundError("No (supported) data files found" + (f" in {path}" if path else ""))
598 return module_name, default_builder_kwargs
DataFilesNotFoundError: No (supported) data files found in open-llm-leaderboard/details_davidkim205__Rhea-72b-v0.5
In [3]: data = load_dataset("open-llm-leaderboard/details_davidkim205__Rhea-72b-
...: v0.5", "harness_winogrande_5")
---------------------------------------------------------------------------
DataFilesNotFoundError Traceback (most recent call last)
Cell In[3], line 1
----> 1 data = load_dataset("open-llm-leaderboard/details_davidkim205__Rhea-72b-v0.5", "harness_winogrande_5")
File ~/open-llm-bda/venv/lib/python3.11/site-packages/datasets/load.py:2587, in load_dataset(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, verification_mode, ignore_verifications, keep_in_memory, save_infos, revision, token, use_auth_token, task, streaming, num_proc, storage_options, trust_remote_code, **config_kwargs)
2582 verification_mode = VerificationMode(
2583 (verification_mode or VerificationMode.BASIC_CHECKS) if not save_infos else VerificationMode.ALL_CHECKS
2584 )
2586 # Create a dataset builder
-> 2587 builder_instance = load_dataset_builder(
2588 path=path,
2589 name=name,
2590 data_dir=data_dir,
2591 data_files=data_files,
2592 cache_dir=cache_dir,
2593 features=features,
2594 download_config=download_config,
2595 download_mode=download_mode,
2596 revision=revision,
2597 token=token,
2598 storage_options=storage_options,
2599 trust_remote_code=trust_remote_code,
2600 _require_default_config_name=name is None,
2601 **config_kwargs,
2602 )
2604 # Return iterable dataset in case of streaming
2605 if streaming:
File ~/open-llm-bda/venv/lib/python3.11/site-packages/datasets/load.py:2259, in load_dataset_builder(path, name, data_dir, data_files, cache_dir, features, download_config, download_mode, revision, token, use_auth_token, storage_options, trust_remote_code, _require_default_config_name, **config_kwargs)
2257 download_config = download_config.copy() if download_config else DownloadConfig()
2258 download_config.storage_options.update(storage_options)
-> 2259 dataset_module = dataset_module_factory(
2260 path,
2261 revision=revision,
2262 download_config=download_config,
2263 download_mode=download_mode,
2264 data_dir=data_dir,
2265 data_files=data_files,
2266 cache_dir=cache_dir,
2267 trust_remote_code=trust_remote_code,
2268 _require_default_config_name=_require_default_config_name,
2269 _require_custom_configs=bool(config_kwargs),
2270 )
2271 # Get dataset builder class from the processing script
2272 builder_kwargs = dataset_module.builder_kwargs
File ~/open-llm-bda/venv/lib/python3.11/site-packages/datasets/load.py:1821, in dataset_module_factory(path, revision, download_config, download_mode, dynamic_modules_path, data_dir, data_files, cache_dir, trust_remote_code, _require_default_config_name, _require_custom_configs, **download_kwargs)
1812 return LocalDatasetModuleFactoryWithScript(
1813 combined_path,
1814 download_mode=download_mode,
1815 dynamic_modules_path=dynamic_modules_path,
1816 trust_remote_code=trust_remote_code,
1817 ).get_module()
1818 elif os.path.isdir(path):
1819 return LocalDatasetModuleFactoryWithoutScript(
1820 path, data_dir=data_dir, data_files=data_files, download_mode=download_mode
-> 1821 ).get_module()
1822 # Try remotely
1823 elif is_relative_path(path) and path.count("/") <= 1:
File ~/open-llm-bda/venv/lib/python3.11/site-packages/datasets/load.py:1039, in LocalDatasetModuleFactoryWithoutScript.get_module(self)
1033 patterns = get_data_patterns(base_path)
1034 data_files = DataFilesDict.from_patterns(
1035 patterns,
1036 base_path=base_path,
1037 allowed_extensions=ALL_ALLOWED_EXTENSIONS,
1038 )
-> 1039 module_name, default_builder_kwargs = infer_module_for_data_files(
1040 data_files=data_files,
1041 path=self.path,
1042 )
1043 data_files = data_files.filter_extensions(_MODULE_TO_EXTENSIONS[module_name])
1044 # Collect metadata files if the module supports them
File ~/open-llm-bda/venv/lib/python3.11/site-packages/datasets/load.py:597, in infer_module_for_data_files(data_files, path, download_config)
595 raise ValueError(f"Couldn't infer the same data file format for all splits. Got {split_modules}")
596 if not module_name:
--> 597 raise DataFilesNotFoundError("No (supported) data files found" + (f" in {path}" if path else ""))
598 return module_name, default_builder_kwargs
DataFilesNotFoundError: No (supported) data files found in open-llm-leaderboard/details_davidkim205__Rhea-72b-v0.5
```
### Expected behavior
No exceptions from `get_dataset_config_names` or `load_dataset`
### Environment info
- `datasets` version: 2.19.0
- Platform: Linux-6.5.0-1018-aws-aarch64-with-glibc2.35
- Python version: 3.11.8
- `huggingface_hub` version: 0.23.0
- PyArrow version: 16.0.0
- Pandas version: 2.2.2
- `fsspec` version: 2024.3.1 | {
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https://api.github.com/repos/huggingface/datasets/issues/6864 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6864/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6864/comments | https://api.github.com/repos/huggingface/datasets/issues/6864/events | https://github.com/huggingface/datasets/issues/6864 | 2,276,986,981 | I_kwDODunzps6HuBBl | 6,864 | Dataset 'rewardsignal/reddit_writing_prompts' doesn't exist on the Hub | {
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"Hi @vinodrajendran001, thanks for reporting.\r\n\r\nIndeed the dataset no longer exists on the Hub. The URL https://huggingface.co/datasets/rewardsignal/reddit_writing_prompts gives 404 Not Found error."
] | 2024-05-03T06:03:30Z | 2024-05-06T06:36:42Z | 2024-05-06T06:36:41Z | NONE | null | null | {
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} | ### Describe the bug
The dataset `rewardsignal/reddit_writing_prompts` is missing in Huggingface Hub.
### Steps to reproduce the bug
```
from datasets import load_dataset
prompt_response_dataset = load_dataset("rewardsignal/reddit_writing_prompts", data_files="prompt_responses_full.csv", split='train[:80%]')
```
### Expected behavior
DatasetNotFoundError: Dataset 'rewardsignal/reddit_writing_prompts' doesn't exist on the Hub or cannot be accessed
### Environment info
Nothing to do with versions | {
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https://api.github.com/repos/huggingface/datasets/issues/6863 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6863/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6863/comments | https://api.github.com/repos/huggingface/datasets/issues/6863/events | https://github.com/huggingface/datasets/issues/6863 | 2,276,977,534 | I_kwDODunzps6Ht-t- | 6,863 | Revert temporary pin huggingface-hub < 0.23.0 | {
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} | Revert temporary pin huggingface-hub < 0.23.0 introduced by
- #6861
once the following issue is fixed and released:
- huggingface/transformers#30618 | {
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https://api.github.com/repos/huggingface/datasets/issues/6860 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6860/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6860/comments | https://api.github.com/repos/huggingface/datasets/issues/6860/events | https://github.com/huggingface/datasets/issues/6860 | 2,275,537,137 | I_kwDODunzps6HofDx | 6,860 | CI fails after huggingface_hub-0.23.0 release: FutureWarning: "resume_download" | {
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"I think this needs to be fixed on transformers.\r\n\r\nCC: @Wauplin ",
"See:\r\n- https://github.com/huggingface/transformers/issues/30618",
"Opened https://github.com/huggingface/transformers/pull/30620"
] | 2024-05-02T13:24:17Z | 2024-05-02T16:53:45Z | 2024-05-02T16:53:45Z | MEMBER | null | null | {
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} | CI fails after latest huggingface_hub-0.23.0 release: https://github.com/huggingface/huggingface_hub/releases/tag/v0.23.0
```
FAILED tests/test_metric_common.py::LocalMetricTest::test_load_metric_bertscore - FutureWarning: `resume_download` is deprecated and will be removed in version 1.0.0. Downloads always resume when possible. If you want to force a new download, use `force_download=True`.
FAILED tests/test_metric_common.py::LocalMetricTest::test_load_metric_frugalscore - FutureWarning: `resume_download` is deprecated and will be removed in version 1.0.0. Downloads always resume when possible. If you want to force a new download, use `force_download=True`.
FAILED tests/test_metric_common.py::LocalMetricTest::test_load_metric_perplexity - FutureWarning: `resume_download` is deprecated and will be removed in version 1.0.0. Downloads always resume when possible. If you want to force a new download, use `force_download=True`.
FAILED tests/test_fingerprint.py::TokenizersHashTest::test_hash_tokenizer - FutureWarning: `resume_download` is deprecated and will be removed in version 1.0.0. Downloads always resume when possible. If you want to force a new download, use `force_download=True`.
FAILED tests/test_fingerprint.py::TokenizersHashTest::test_hash_tokenizer_with_cache - FutureWarning: `resume_download` is deprecated and will be removed in version 1.0.0. Downloads always resume when possible. If you want to force a new download, use `force_download=True`.
FAILED tests/test_arrow_dataset.py::MiscellaneousDatasetTest::test_set_format_encode - FutureWarning: `resume_download` is deprecated and will be removed in version 1.0.0. Downloads always resume when possible. If you want to force a new download, use `force_download=True`.
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/6858 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6858/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6858/comments | https://api.github.com/repos/huggingface/datasets/issues/6858/events | https://github.com/huggingface/datasets/issues/6858 | 2,274,917,185 | I_kwDODunzps6HmHtB | 6,858 | Segmentation fault | {
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"I downloaded the jsonl file and extract it manually. \r\nThe issue seems to be related to pyarrow.json \r\n\r\n\r\n\r\npython3 -q -X faulthandler -c \"from datasets import load_dataset; load_dataset('json', data_files='/Users/scampion/Downloads/1998-09.jsonl')\"\r\nGenerating train split: 0 examples [00:00, ? exa... | 2024-05-02T08:28:49Z | 2024-05-03T08:43:21Z | 2024-05-03T08:42:36Z | NONE | null | null | {
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} | ### Describe the bug
Using various version for datasets, I'm no more longer able to load that dataset without a segmentation fault.
Several others files are also concerned.
### Steps to reproduce the bug
# Create a new venv
python3 -m venv venv_test
source venv_test/bin/activate
# Install the latest version
pip install datasets
# Load that dataset
python3 -q -X faulthandler -c "from datasets import load_dataset; load_dataset('EuropeanParliament/Eurovoc', '1998-09')"
### Expected behavior
Data must be loaded
### Environment info
datasets==2.19.0
Python 3.11.7
Darwin 22.5.0 Darwin Kernel Version 22.5.0: Mon Apr 24 20:51:50 PDT 2023; root:xnu-8796.121.2~5/RELEASE_X86_64 x86_64 | {
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https://api.github.com/repos/huggingface/datasets/issues/6856 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6856/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6856/comments | https://api.github.com/repos/huggingface/datasets/issues/6856/events | https://github.com/huggingface/datasets/issues/6856 | 2,274,828,933 | I_kwDODunzps6HlyKF | 6,856 | CI fails on Windows for test_delete_from_hub and test_xgetsize_private due to new-line character | {
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"After investigation, I have found that when a local file is uploaded to the Hub, the new line character is no longer transformed to \"\\n\": on Windows machine now it is kept as \"\\r\\n\".\r\n\r\nAny idea why this changed?\r\nCC: @lhoestq "
] | 2024-05-02T07:37:03Z | 2024-05-02T11:43:01Z | 2024-05-02T11:43:01Z | MEMBER | null | null | {
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} | CI fails on Windows for test_delete_from_hub after the merge of:
- #6820
This is weird because the CI was green in the PR branch before merging to main.
```
FAILED tests/test_hub.py::test_delete_from_hub - AssertionError: assert [CommitOperat...\r\n---\r\n')] == [CommitOperat...in/*\n---\n')]
At index 1 diff: CommitOperationAdd(path_in_repo='README.md', path_or_fileobj=b'---\r\nconfigs:\r\n- config_name: cats\r\n data_files:\r\n - split: train\r\n path: cats/train/*\r\n---\r\n') != CommitOperationAdd(path_in_repo='README.md', path_or_fileobj=b'---\nconfigs:\n- config_name: cats\n data_files:\n - split: train\n path: cats/train/*\n---\n')
Full diff:
[
CommitOperationDelete(
path_in_repo='dogs/train/0000.csv',
is_folder=False,
),
CommitOperationAdd(
path_in_repo='README.md',
- path_or_fileobj=b'---\nconfigs:\n- config_name: cats\n data_files:\n '
? --------
+ path_or_fileobj=b'---\r\nconfigs:\r\n- config_name: cats\r\n data_f'
? ++ ++ ++
- b' - split: train\n path: cats/train/*\n---\n',
? ^^^^^^ -
+ b'iles:\r\n - split: train\r\n path: cats/train/*\r'
? ++++++++++ ++ ^
+ b'\n---\r\n',
),
]
``` | {
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} | As reported by @Wauplin, when loading a community dataset with script, there is a bug in the example of usage of the error message if the dataset has multiple configs (and no default config) and the user does not pass any config. For example:
```python
>>> ds = load_dataset("google/fleurs")
ValueError: Config name is missing.
Please pick one among the available configs: ['af_za', 'am_et', 'ar_eg', 'as_in', 'ast_es', 'az_az', 'be_by', 'bg_bg', 'bn_in', 'bs_ba', 'ca_es', 'ceb_ph', 'ckb_iq', 'cmn_hans_cn', 'cs_cz', 'cy_gb', 'da_dk', 'de_de', 'el_gr', 'en_us', 'es_419', 'et_ee', 'fa_ir', 'ff_sn', 'fi_fi', 'fil_ph', 'fr_fr', 'ga_ie', 'gl_es', 'gu_in', 'ha_ng', 'he_il', 'hi_in', 'hr_hr', 'hu_hu', 'hy_am', 'id_id', 'ig_ng', 'is_is', 'it_it', 'ja_jp', 'jv_id', 'ka_ge', 'kam_ke', 'kea_cv', 'kk_kz', 'km_kh', 'kn_in', 'ko_kr', 'ky_kg', 'lb_lu', 'lg_ug', 'ln_cd', 'lo_la', 'lt_lt', 'luo_ke', 'lv_lv', 'mi_nz', 'mk_mk', 'ml_in', 'mn_mn', 'mr_in', 'ms_my', 'mt_mt', 'my_mm', 'nb_no', 'ne_np', 'nl_nl', 'nso_za', 'ny_mw', 'oc_fr', 'om_et', 'or_in', 'pa_in', 'pl_pl', 'ps_af', 'pt_br', 'ro_ro', 'ru_ru', 'sd_in', 'sk_sk', 'sl_si', 'sn_zw', 'so_so', 'sr_rs', 'sv_se', 'sw_ke', 'ta_in', 'te_in', 'tg_tj', 'th_th', 'tr_tr', 'uk_ua', 'umb_ao', 'ur_pk', 'uz_uz', 'vi_vn', 'wo_sn', 'xh_za', 'yo_ng', 'yue_hant_hk', 'zu_za', 'all']
Example of usage:
`load_dataset('fleurs', 'af_za')`
```
Note the example of usage in the error message suggests loading "fleurs" instead of "google/fleurs". | {
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} | ### Describe the bug
<img width="1001" alt="Screenshot 2024-05-01 at 3 37 06 AM" src="https://github.com/huggingface/datasets/assets/130903099/00fcf12c-fcc1-4749-8592-d263d4efcbcc">
As you can see I logged in to my account and the write token is valid.
But I can't upload on my main account and I am getting that error. It was okay on my test account at first try.
(I refreshed the token, tried a new token but still doesn't work)
### Steps to reproduce the bug
1. I loaded a dataset.
2. I logged in using both cli and huggingface_hub
3. I pushed to my down dataset
(It went well without any issues on my test account)
### Expected behavior
It should have gone smoothly and this is not even my first time uploading to huggingface datasets
### Environment info
colab, dataset (tried multiple versions) | {
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https://api.github.com/repos/huggingface/datasets/issues/6850 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6850/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6850/comments | https://api.github.com/repos/huggingface/datasets/issues/6850/events | https://github.com/huggingface/datasets/issues/6850 | 2,269,500,624 | I_kwDODunzps6HRdTQ | 6,850 | Problem loading voxpopuli dataset | {
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"Version 2.18 works without problem.",
"@Namangarg110 @mohsen-goodarzi The bug appears because the number of urls is less than 16 and the algorithm is meant to work on the previously created mode for a single url as stated on line 314: https://github.com/huggingface/datasets/blob/1bf8a46cc7b096d5c547ea3794f6a4b6... | 2024-04-29T16:46:51Z | 2024-05-06T09:25:54Z | 2024-05-06T09:25:54Z | NONE | null | null | {
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} | ### Describe the bug
```
Exception has occurred: FileNotFoundError
Couldn't find file at https://huggingface.co/datasets/facebook/voxpopuli/resolve/main/{'en': 'data/en/asr_train.tsv'}
```
Error in logic for link url creation. The link should be https://huggingface.co/datasets/facebook/voxpopuli/resolve/main/data/en/asr_train.tsv
Basically there should be links directly under ```metadata["train"]```, not under ```metadata["train"][self.config.languages[0]]```
same for audio urls
### Steps to reproduce the bug
```
from datasets import load_dataset
dataset = load_dataset("facebook/voxpopuli","en")
```
### Expected behavior
Dataset should be loaded successfully.
### Environment info
- `datasets` version: 2.19.0
- Platform: Linux-5.15.0-1041-aws-x86_64-with-glibc2.31
- Python version: 3.10.13
- `huggingface_hub` version: 0.22.2
- PyArrow version: 16.0.0
- Pandas version: 2.2.0
- `fsspec` version: 2023.12.2 | {
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https://api.github.com/repos/huggingface/datasets/issues/6846 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6846/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6846/comments | https://api.github.com/repos/huggingface/datasets/issues/6846/events | https://github.com/huggingface/datasets/issues/6846 | 2,267,352,120 | I_kwDODunzps6HJQw4 | 6,846 | Unimaginable super slow iteration | {
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"In every iteration you load the full \"random_input\" column in memory, only then to access it's i-th element.\r\n\r\nYou can try using this instead\r\n\r\na,b=dataset[i]['random_input'],dataset[i]['random_output']"
] | 2024-04-28T05:24:14Z | 2024-05-06T08:30:03Z | 2024-05-06T08:30:03Z | NONE | null | null | {
"completed": 0,
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} | ### Describe the bug
Assuming there is a dataset with 52000 sentences, each with a length of 500, it takes 20 seconds to extract a sentence from the dataset……？Is there something wrong with my iteration?
### Steps to reproduce the bug
```python
import datasets
import time
import random
num_rows = 52000
num_cols = 500
random_input = [[random.randint(1, 100) for _ in range(num_cols)] for _ in range(num_rows)]
random_output = [[random.randint(1, 100) for _ in range(num_cols)] for _ in range(num_rows)]
s=time.time()
d={'random_input':random_input,'random_output':random_output}
dataset=datasets.Dataset.from_dict(d)
print('from dict',time.time()-s)
print(dataset)
for i in range(len(dataset)):
aa=time.time()
a,b=dataset['random_input'][i],dataset['random_output'][i]
print(time.time()-aa)
```
corresponding output
```bash
from dict 9.215498685836792
Dataset({
features: ['random_input', 'random_output'],
num_rows: 52000
})
19.129778146743774
19.329464197158813
19.27668261528015
19.28557538986206
19.247620582580566
19.624247074127197
19.28673791885376
19.301053047180176
19.290496110916138
19.291821718215942
19.357765197753906
```
### Expected behavior
Under normal circumstances, iteration should be very rapid as it does not involve the main tasks other than getting items
### Environment info
- `datasets` version: 2.19.0
- Platform: Linux-3.10.0-1160.71.1.el7.x86_64-x86_64-with-glibc2.17
- Python version: 3.10.13
- `huggingface_hub` version: 0.21.4
- PyArrow version: 15.0.0
- Pandas version: 2.2.1
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https://api.github.com/repos/huggingface/datasets/issues/6841 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6841/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6841/comments | https://api.github.com/repos/huggingface/datasets/issues/6841/events | https://github.com/huggingface/datasets/issues/6841 | 2,264,687,683 | I_kwDODunzps6G_GRD | 6,841 | Unable to load wiki_auto_asset_turk from GEM | {
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"Hi! I've opened a [PR](https://huggingface.co/datasets/GEM/wiki_auto_asset_turk/discussions/5) with a fix. While waiting for it to be merged, you can load the dataset from the PR branch with `datasets.load_dataset(\"GEM/wiki_auto_asset_turk\", revision=\"refs/pr/5\")`",
"Thanks Mario. Still getting the same issu... | 2024-04-26T00:08:47Z | 2024-05-29T13:54:03Z | 2024-04-26T16:12:29Z | NONE | null | null | {
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} | ### Describe the bug
I am unable to load the wiki_auto_asset_turk dataset. I get a fatal error while trying to access wiki_auto_asset_turk and load it with datasets.load_dataset. The error (TypeError: expected str, bytes or os.PathLike object, not NoneType) is from filenames_for_dataset_split in a os.path.join call
>>import datasets
>>print (datasets.__version__)
>>dataset = datasets.load_dataset("GEM/wiki_auto_asset_turk")
System output:
Generating train split: 100%|█| 483801/483801 [00:03<00:00, 127164.26 examples/s
Generating validation split: 100%|█| 20000/20000 [00:00<00:00, 116052.94 example
Generating test_asset split: 100%|██| 359/359 [00:00<00:00, 76155.93 examples/s]
Generating test_turk split: 100%|███| 359/359 [00:00<00:00, 87691.76 examples/s]
Traceback (most recent call last):
File "/Users/abhinav.sethy/Code/openai_evals/evals/evals/grammarly_tasks/gem_sari.py", line 3, in <module>
dataset = datasets.load_dataset("GEM/wiki_auto_asset_turk")
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/datasets/load.py", line 2582, in load_dataset
builder_instance.download_and_prepare(
File "/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/datasets/builder.py", line 1005, in download_and_prepare
self._download_and_prepare(
File "/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/datasets/builder.py", line 1767, in _download_and_prepare
super()._download_and_prepare(
File "/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/datasets/builder.py", line 1100, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/datasets/builder.py", line 1565, in _prepare_split
split_info = self.info.splits[split_generator.name]
~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^
File "/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/datasets/splits.py", line 532, in __getitem__
instructions = make_file_instructions(
^^^^^^^^^^^^^^^^^^^^^^^
File "/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/datasets/arrow_reader.py", line 121, in make_file_instructions
info.name: filenames_for_dataset_split(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/datasets/naming.py", line 72, in filenames_for_dataset_split
prefix = os.path.join(path, prefix)
^^^^^^^^^^^^^^^^^^^^^^^^^^
File "<frozen posixpath>", line 76, in join
TypeError: expected str, bytes or os.PathLike object, not NoneType
### Steps to reproduce the bug
import datasets
print (datasets.__version__)
dataset = datasets.load_dataset("GEM/wiki_auto_asset_turk")
### Expected behavior
Should be able to load the dataset without any issues
### Environment info
datasets version 2.18.0 (was able to reproduce bug with older versions 2.16 and 2.14 also)
Python 3.12.0 | {
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} | As suggested by @Wauplin, see: https://github.com/huggingface/datasets/pull/6831#discussion_r1579492603
> I would not advertise the --token arg in the example as this shouldn't be the recommended way (best to login with env variable or huggingface-cli login) | {
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} | ### 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
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https://api.github.com/repos/huggingface/datasets/issues/6824 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6824/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6824/comments | https://api.github.com/repos/huggingface/datasets/issues/6824/events | https://github.com/huggingface/datasets/issues/6824 | 2,251,076,197 | I_kwDODunzps6GLLJl | 6,824 | Winogrande does not seem to be compatible with datasets version of 1.18.0 | {
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"Hi ! Do you mean 2.18 ? Can you try to update `fsspec` and `huggingface_hub` ?\r\n\r\n```\r\npip install -U fsspec huggingface_hub\r\n```",
"Yes I meant 2.18, and it works after updating `fsspec` and `huggingface_hub`. Thanks!"
] | 2024-04-18T16:11:04Z | 2024-04-19T09:53:15Z | 2024-04-19T09:52:33Z | NONE | null | null | {
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} | ### Describe the bug
I get the following error when simply running `load_dataset('winogrande','winogrande_xl')`.
I do not have such an issue in the 1.17.0 version.
```Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/usr/local/lib/python3.10/dist-packages/datasets/load.py", line 2556, in load_dataset
builder_instance = load_dataset_builder(
File "/usr/local/lib/python3.10/dist-packages/datasets/load.py", line 2265, in load_dataset_builder
builder_instance: DatasetBuilder = builder_cls(
File "/usr/local/lib/python3.10/dist-packages/datasets/builder.py", line 371, in __init__
self.config, self.config_id = self._create_builder_config(
File "/usr/local/lib/python3.10/dist-packages/datasets/builder.py", line 620, in _create_builder_config
builder_config._resolve_data_files(
File "/usr/local/lib/python3.10/dist-packages/datasets/builder.py", line 211, in _resolve_data_files
self.data_files = self.data_files.resolve(base_path, download_config)
File "/usr/local/lib/python3.10/dist-packages/datasets/data_files.py", line 799, in resolve
out[key] = data_files_patterns_list.resolve(base_path, download_config)
File "/usr/local/lib/python3.10/dist-packages/datasets/data_files.py", line 752, in resolve
resolve_pattern(
File "/usr/local/lib/python3.10/dist-packages/datasets/data_files.py", line 393, in resolve_pattern
raise FileNotFoundError(error_msg)
FileNotFoundError: Unable to find 'hf://datasets/winogrande@ebf71e3c7b5880d019ecf6099c0b09311b1084f5/winogrande_xl/train/0000.parquet' with any supported extension ['.csv', '.tsv', '.json', '.jsonl', '.parquet', '.geoparquet', '.gpq', '.arrow', '.txt', '.tar', '.blp', '.bmp', '.dib', '.bufr', '.cur', '.pcx', '.dcx', '.dds', '.ps', '.eps', '.fit', '.fits', '.fli', '.flc', '.ftc', '.ftu', '.gbr', '.gif', '.grib', '.h5', '.hdf', '.png', '.apng', '.jp2', '.j2k', '.jpc', '.jpf', '.jpx', '.j2c', '.icns', '.ico', '.im', '.iim', '.tif', '.tiff', '.jfif', '.jpe', '.jpg', '.jpeg', '.mpg', '.mpeg', '.msp', '.pcd', '.pxr', '.pbm', '.pgm', '.ppm', '.pnm', '.psd', '.bw', '.rgb', '.rgba', '.sgi', '.ras', '.tga', '.icb', '.vda', '.vst', '.webp', '.wmf', '.emf', '.xbm', '.xpm', '.BLP', '.BMP', '.DIB', '.BUFR', '.CUR', '.PCX', '.DCX', '.DDS', '.PS', '.EPS', '.FIT', '.FITS', '.FLI', '.FLC', '.FTC', '.FTU', '.GBR', '.GIF', '.GRIB', '.H5', '.HDF', '.PNG', '.APNG', '.JP2', '.J2K', '.JPC', '.JPF', '.JPX', '.J2C', '.ICNS', '.ICO', '.IM', '.IIM', '.TIF', '.TIFF', '.JFIF', '.JPE', '.JPG', '.JPEG', '.MPG', '.MPEG', '.MSP', '.PCD', '.PXR', '.PBM', '.PGM', '.PPM', '.PNM', '.PSD', '.BW', '.RGB', '.RGBA', '.SGI', '.RAS', '.TGA', '.ICB', '.VDA', '.VST', '.WEBP', '.WMF', '.EMF', '.XBM', '.XPM', '.aiff', '.au', '.avr', '.caf', '.flac', '.htk', '.svx', '.mat4', '.mat5', '.mpc2k', '.ogg', '.paf', '.pvf', '.raw', '.rf64', '.sd2', '.sds', '.ircam', '.voc', '.w64', '.wav', '.nist', '.wavex', '.wve', '.xi', '.mp3', '.opus', '.AIFF', '.AU', '.AVR', '.CAF', '.FLAC', '.HTK', '.SVX', '.MAT4', '.MAT5', '.MPC2K', '.OGG', '.PAF', '.PVF', '.RAW', '.RF64', '.SD2', '.SDS', '.IRCAM', '.VOC', '.W64', '.WAV', '.NIST', '.WAVEX', '.WVE', '.XI', '.MP3', '.OPUS', '.zip']```
### Steps to reproduce the bug
from datasets import load_dataset
datasets = load_dataset('winogrande','winogrande_xl')
### Expected behavior
```Downloading data: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 2.06M/2.06M [00:00<00:00, 5.16MB/s]
Downloading data: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 118k/118k [00:00<00:00, 360kB/s]
Downloading data: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 85.9k/85.9k [00:00<00:00, 242kB/s]
Generating train split: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████| 40398/40398 [00:00<00:00, 845491.12 examples/s]
Generating test split: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████| 1767/1767 [00:00<00:00, 362501.11 examples/s]
Generating validation split: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████| 1267/1267 [00:00<00:00, 318768.11 examples/s]```
### Environment info
datasets version: 1.18.0
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"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`...\r\n\r\nI am working on a draft implementation, so we can discuss about the API and UX.",
"2nd time I've come ... | 2024-04-15T07:53:26Z | 2025-01-11T18:40:40Z | 2024-04-30T09:44:25Z | MEMBER | null | null | {
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> 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? | {
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https://api.github.com/repos/huggingface/datasets/issues/6805 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6805/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6805/comments | https://api.github.com/repos/huggingface/datasets/issues/6805/events | https://github.com/huggingface/datasets/issues/6805 | 2,239,034,951 | I_kwDODunzps6FdPZH | 6,805 | Batched mapping of existing string column casts boolean to string | {
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"This seems to be hardcoded behavior in table.py `array_cast`.\r\n```python\r\nif (\r\n not allow_number_to_str\r\n and pa.types.is_string(pa_type)\r\n and (pa.types.is_floating(array.type) or pa.types.is_integer(array.type))\r\n ):\r\n raise TypeError(\r\n ... | 2024-04-12T04:21:41Z | 2024-07-03T15:00:07Z | 2024-07-03T15:00:07Z | NONE | null | null | {
"completed": 0,
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} | ### Describe the bug
Let the dataset contain a column named 'a', which is of the string type.
If 'a' is converted to a boolean using batched mapping, the mapper automatically casts the boolean to a string (e.g., True -> 'true').
It only happens when the original column and the mapped column name are identical.
Thank you!
### Steps to reproduce the bug
```python
from datasets import Dataset
dset = Dataset.from_dict({'a': ['11', '22']})
dset = dset.map(lambda x: {'a': [True for _ in x['a']]}, batched=True)
print(dset['a'])
```
```
> ['true', 'true']
```
### Expected behavior
[True, True]
### Environment info
- `datasets` version: 2.18.0
- Platform: Linux-5.4.0-148-generic-x86_64-with-glibc2.31
- Python version: 3.10.13
- `huggingface_hub` version: 0.21.4
- PyArrow version: 15.0.2
- Pandas version: 2.2.1
- `fsspec` version: 2023.12.2 | {
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https://api.github.com/repos/huggingface/datasets/issues/6801 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6801/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6801/comments | https://api.github.com/repos/huggingface/datasets/issues/6801/events | https://github.com/huggingface/datasets/issues/6801 | 2,236,911,556 | I_kwDODunzps6FVI_E | 6,801 | got fileNotFound | {
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"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 d... | 2024-04-11T04:57:41Z | 2024-04-12T16:47:43Z | 2024-04-12T16:47:43Z | NONE | null | null | {
"completed": 0,
"percent_completed": 0,
"total": 0
} | ### 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
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https://api.github.com/repos/huggingface/datasets/issues/6798 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6798/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6798/comments | https://api.github.com/repos/huggingface/datasets/issues/6798/events | https://github.com/huggingface/datasets/issues/6798 | 2,235,768,891 | I_kwDODunzps6FQyA7 | 6,798 | `DatasetBuilder._split_generators` incomplete type annotation | {
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"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 use... | 2024-04-10T14:38:50Z | 2024-04-11T15:34:59Z | 2024-04-11T15:34:59Z | CONTRIBUTOR | null | null | {
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} | ### 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
/ | {
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https://api.github.com/repos/huggingface/datasets/issues/6796 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6796/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6796/comments | https://api.github.com/repos/huggingface/datasets/issues/6796/events | https://github.com/huggingface/datasets/issues/6796 | 2,234,887,618 | I_kwDODunzps6FNa3C | 6,796 | CI is broken due to hf-internal-testing/dataset_with_script | {
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"Finally:\r\n- the initial issue seems it was temporary\r\n- there is a different issue now: https://github.com/huggingface/datasets/actions/runs/8627153993/job/23646584590?pr=6797\r\n```\r\nFAILED tests/test_load.py::ModuleFactoryTest::test_HubDatasetModuleFactoryWithParquetExport - datasets.utils._dataset_viewer.... | 2024-04-10T06:56:02Z | 2024-04-12T09:02:13Z | 2024-04-12T09:02:13Z | MEMBER | null | null | {
"completed": 0,
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} | 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>)
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/6791 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6791/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6791/comments | https://api.github.com/repos/huggingface/datasets/issues/6791/events | https://github.com/huggingface/datasets/issues/6791 | 2,230,102,332 | I_kwDODunzps6E7Kk8 | 6,791 | `add_faiss_index` raises ValueError: not enough values to unpack (expected 2, got 1) | {
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"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!\r\n\r\nI 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 embed... | 2024-04-08T01:57:03Z | 2024-04-11T15:38:05Z | 2024-04-11T15:38:05Z | NONE | null | null | {
"completed": 0,
"percent_completed": 0,
"total": 0
} | ### 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 | {
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https://api.github.com/repos/huggingface/datasets/issues/6788 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6788/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6788/comments | https://api.github.com/repos/huggingface/datasets/issues/6788/events | https://github.com/huggingface/datasets/issues/6788 | 2,229,207,521 | I_kwDODunzps6E3wHh | 6,788 | A Question About the Map Function | {
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"All data is saved in the arrow format on disk.\r\nIf you return a tensor it gets converted to arrow before saving to disk when using map.\r\n\r\nTo get a tensor when you access data elements you can use `dataset.set_format(\"pt\")`.\r\nNote that this just changes how the data is loaded, not how it is stored.",
"... | 2024-04-06T11:45:23Z | 2024-04-11T05:29:35Z | 2024-04-11T05:29:35Z | NONE | null | null | {
"completed": 0,
"percent_completed": 0,
"total": 0
} | ### 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 | {
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https://api.github.com/repos/huggingface/datasets/issues/6783 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6783/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6783/comments | https://api.github.com/repos/huggingface/datasets/issues/6783/events | https://github.com/huggingface/datasets/issues/6783 | 2,228,179,466 | I_kwDODunzps6Ez1IK | 6,783 | AttributeError: module 'numpy' has no attribute 'object'. in Kaggle Notebook | {
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} | [] | closed | false | null | [] | null | [
"Hi! You can fix this by updating the `datasets` package with `pip install -U datasets` and restarting the notebook.\r\n",
"Kaggle removed the problematic `datasets==2.1.0` pin last week, so I'm closing this issue (now it pre-installs the latest version)."
] | 2024-04-05T14:31:48Z | 2024-04-11T17:18:53Z | 2024-04-11T17:18:53Z | NONE | null | null | {
"completed": 0,
"percent_completed": 0,
"total": 0
} | ### Describe the bug
# problem
I can't resample audio dataset in Kaggle Notebook. It looks like some code in `datasets` library use aliases that were deprecated in NumPy 1.20.
## code for resampling
```
from datasets import load_dataset, Audio
from transformers import AutoFeatureExtractor
from transformers import AutoModelForAudioClassification, TrainingArguments, Trainer
minds = load_dataset("PolyAI/minds14", name="en-US", split="train")
feature_extractor = AutoFeatureExtractor.from_pretrained("facebook/wav2vec2-base")
def preprocess_function(examples):
audio_arrays = [x["array"] for x in examples["audio"]]
inputs = feature_extractor(
audio_arrays, sampling_rate=feature_extractor.sampling_rate, max_length=16000, truncation=True
)
return inputs
dataset = dataset.map(preprocess_function, remove_columns="audio", batched=True, batch_size=100)
```
## the error I got
<details>
<summary>Click to expand</summary>
```
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
Cell In[20], line 1
----> 1 dataset = dataset.map(preprocess_function, remove_columns="audio", batched=True, batch_size=100)
2 dataset
File /opt/conda/lib/python3.10/site-packages/datasets/arrow_dataset.py:1955, in Dataset.map(self, function, with_indices, with_rank, input_columns, batched, batch_size, drop_last_batch, remove_columns, keep_in_memory, load_from_cache_file, cache_file_name, writer_batch_size, features, disable_nullable, fn_kwargs, num_proc, suffix_template, new_fingerprint, desc)
1952 disable_tqdm = not logging.is_progress_bar_enabled()
1954 if num_proc is None or num_proc == 1:
-> 1955 return self._map_single(
1956 function=function,
1957 with_indices=with_indices,
1958 with_rank=with_rank,
1959 input_columns=input_columns,
1960 batched=batched,
1961 batch_size=batch_size,
1962 drop_last_batch=drop_last_batch,
1963 remove_columns=remove_columns,
1964 keep_in_memory=keep_in_memory,
1965 load_from_cache_file=load_from_cache_file,
1966 cache_file_name=cache_file_name,
1967 writer_batch_size=writer_batch_size,
1968 features=features,
1969 disable_nullable=disable_nullable,
1970 fn_kwargs=fn_kwargs,
1971 new_fingerprint=new_fingerprint,
1972 disable_tqdm=disable_tqdm,
1973 desc=desc,
1974 )
1975 else:
1977 def format_cache_file_name(cache_file_name, rank):
File /opt/conda/lib/python3.10/site-packages/datasets/arrow_dataset.py:520, in transmit_tasks.<locals>.wrapper(*args, **kwargs)
518 self: "Dataset" = kwargs.pop("self")
519 # apply actual function
--> 520 out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs)
521 datasets: List["Dataset"] = list(out.values()) if isinstance(out, dict) else [out]
522 for dataset in datasets:
523 # Remove task templates if a column mapping of the template is no longer valid
File /opt/conda/lib/python3.10/site-packages/datasets/arrow_dataset.py:487, in transmit_format.<locals>.wrapper(*args, **kwargs)
480 self_format = {
481 "type": self._format_type,
482 "format_kwargs": self._format_kwargs,
483 "columns": self._format_columns,
484 "output_all_columns": self._output_all_columns,
485 }
486 # apply actual function
--> 487 out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs)
488 datasets: List["Dataset"] = list(out.values()) if isinstance(out, dict) else [out]
489 # re-apply format to the output
File /opt/conda/lib/python3.10/site-packages/datasets/fingerprint.py:458, in fingerprint_transform.<locals>._fingerprint.<locals>.wrapper(*args, **kwargs)
452 kwargs[fingerprint_name] = update_fingerprint(
453 self._fingerprint, transform, kwargs_for_fingerprint
454 )
456 # Call actual function
--> 458 out = func(self, *args, **kwargs)
460 # Update fingerprint of in-place transforms + update in-place history of transforms
462 if inplace: # update after calling func so that the fingerprint doesn't change if the function fails
File /opt/conda/lib/python3.10/site-packages/datasets/arrow_dataset.py:2356, in Dataset._map_single(self, function, with_indices, with_rank, input_columns, batched, batch_size, drop_last_batch, remove_columns, keep_in_memory, load_from_cache_file, cache_file_name, writer_batch_size, features, disable_nullable, fn_kwargs, new_fingerprint, rank, offset, disable_tqdm, desc, cache_only)
2354 writer.write_table(batch)
2355 else:
-> 2356 writer.write_batch(batch)
2357 if update_data and writer is not None:
2358 writer.finalize() # close_stream=bool(buf_writer is None)) # We only close if we are writing in a file
File /opt/conda/lib/python3.10/site-packages/datasets/arrow_writer.py:507, in ArrowWriter.write_batch(self, batch_examples, writer_batch_size)
505 col_try_type = try_features[col] if try_features is not None and col in try_features else None
506 typed_sequence = OptimizedTypedSequence(batch_examples[col], type=col_type, try_type=col_try_type, col=col)
--> 507 arrays.append(pa.array(typed_sequence))
508 inferred_features[col] = typed_sequence.get_inferred_type()
509 schema = inferred_features.arrow_schema if self.pa_writer is None else self.schema
File /opt/conda/lib/python3.10/site-packages/pyarrow/array.pxi:236, in pyarrow.lib.array()
File /opt/conda/lib/python3.10/site-packages/pyarrow/array.pxi:110, in pyarrow.lib._handle_arrow_array_protocol()
File /opt/conda/lib/python3.10/site-packages/datasets/arrow_writer.py:184, in TypedSequence.__arrow_array__(self, type)
182 out = numpy_to_pyarrow_listarray(data)
183 elif isinstance(data, list) and data and isinstance(first_non_null_value(data)[1], np.ndarray):
--> 184 out = list_of_np_array_to_pyarrow_listarray(data)
185 else:
186 trying_cast_to_python_objects = True
File /opt/conda/lib/python3.10/site-packages/datasets/features/features.py:1174, in list_of_np_array_to_pyarrow_listarray(l_arr, type)
1172 """Build a PyArrow ListArray from a possibly nested list of NumPy arrays"""
1173 if len(l_arr) > 0:
-> 1174 return list_of_pa_arrays_to_pyarrow_listarray(
1175 [numpy_to_pyarrow_listarray(arr, type=type) if arr is not None else None for arr in l_arr]
1176 )
1177 else:
1178 return pa.array([], type=type)
File /opt/conda/lib/python3.10/site-packages/datasets/features/features.py:1163, in list_of_pa_arrays_to_pyarrow_listarray(l_arr)
1160 null_indices = [i for i, arr in enumerate(l_arr) if arr is None]
1161 l_arr = [arr for arr in l_arr if arr is not None]
1162 offsets = np.cumsum(
-> 1163 [0] + [len(arr) for arr in l_arr], dtype=np.object
1164 ) # convert to dtype object to allow None insertion
1165 offsets = np.insert(offsets, null_indices, None)
1166 offsets = pa.array(offsets, type=pa.int32())
File /opt/conda/lib/python3.10/site-packages/numpy/__init__.py:324, in __getattr__(attr)
319 warnings.warn(
320 f"In the future `np.{attr}` will be defined as the "
321 "corresponding NumPy scalar.", FutureWarning, stacklevel=2)
323 if attr in __former_attrs__:
--> 324 raise AttributeError(__former_attrs__[attr])
326 if attr == 'testing':
327 import numpy.testing as testing
AttributeError: module 'numpy' has no attribute 'object'.
`np.object` was a deprecated alias for the builtin `object`. To avoid this error in existing code, use `object` by itself. Doing this will not modify any behavior and is safe.
The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:
https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
```
</details>
### Steps to reproduce the bug
Run above code in Kaggle Notebook.
### Expected behavior
I can resample audio data without fail.
### Environment info
- `datasets` version: 2.1.0
- Platform: Linux-5.15.133+-x86_64-with-glibc2.31
- Python version: 3.10.13
- PyArrow version: 11.0.0
- Pandas version: 2.2.1 | {
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https://api.github.com/repos/huggingface/datasets/issues/6773 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6773/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6773/comments | https://api.github.com/repos/huggingface/datasets/issues/6773/events | https://github.com/huggingface/datasets/issues/6773 | 2,221,049,121 | I_kwDODunzps6EYoUh | 6,773 | Dataset on Hub re-downloads every time? | {
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"The caching works as expected when I try to reproduce this locally or on Colab...",
"hi @mariosasko , Thank you for checking. I also tried running this again just now, and it seems like the `load_dataset()` caches properly (though I'll double check later).\r\n\r\nI think the issue might be in the caching of the ... | 2024-04-02T17:23:22Z | 2024-04-08T18:43:45Z | 2024-04-08T18:43:45Z | NONE | null | null | {
"completed": 0,
"percent_completed": 0,
"total": 0
} | ### Describe the bug
Hi, I have a dataset on the hub [here](https://huggingface.co/datasets/manestay/borderlines). It has 1k+ downloads, which I sure is mostly just me and my colleagues working with it. It should have far fewer, since I'm using the same machine with a properly set up HF_HOME variable. However, whenever I run the below function `load_borderlines_hf`, it downloads the entire dataset from the hub and then does the other logic:
https://github.com/manestay/borderlines/blob/4e161f444661e2ebfe643f3fe149d9258d63a57d/run_gpt/lib.py#L80
Let me know what I'm doing wrong here, or if it's a bug with the `datasets` library itself. On the hub I have my data stored in CSVs, but several columns are lists, so that's why I have the code to map splitting on `;`. I looked into dataset loading scripts, but it seemed difficult to set up. I have verified that other `datasets` and `models` on my system are using the cache properly (e.g. I have a 13B parameter model and large datasets, but those are cached and don't redownload).
__EDIT: __ as pointed out in the discussion below, it may be the `map()` calls that aren't being cached properly. Supposing the `load_dataset()` retrieve from the cache, then it should be the case that the `map()` calls also retrieve from the cached output. But the `map()` commands re-execute sometimes.
### Steps to reproduce the bug
1. Copy and paste the function from [here](https://github.com/manestay/borderlines/blob/4e161f444661e2ebfe643f3fe149d9258d63a57d/run_gpt/lib.py#L80) (lines 80-100)
2. Run it in Python `load_borderlines_hf(None)`
3. It completes successfully, downloading from HF hub, then doing the mapping logic etc.
4. If you run it again after some time, it will re-download, ignoring the cache
### Expected behavior
Re-running the code, which calls `datasets.load_dataset('manestay/borderlines', 'territories')`, should use the cached version
### Environment info
- `datasets` version: 2.16.1
- Platform: Linux-5.14.21-150500.55.7-default-x86_64-with-glibc2.31
- Python version: 3.10.13
- `huggingface_hub` version: 0.20.3
- PyArrow version: 15.0.0
- Pandas version: 1.5.3
- `fsspec` version: 2023.10.0 | {
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https://api.github.com/repos/huggingface/datasets/issues/6771 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6771/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6771/comments | https://api.github.com/repos/huggingface/datasets/issues/6771/events | https://github.com/huggingface/datasets/issues/6771 | 2,220,131,457 | I_kwDODunzps6EVISB | 6,771 | Datasets FileNotFoundError when trying to generate examples. | {
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"Hi! I've opened a PR in the repo to fix this issue: https://huggingface.co/datasets/RitchieP/VerbaLex_voice/discussions/6",
"@mariosasko Thanks for the PR and help! Guess I could close the issue for now. Appreciate the help!"
] | 2024-04-02T10:24:57Z | 2024-04-04T14:22:03Z | 2024-04-04T14:22:03Z | NONE | null | null | {
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} | ### Discussed in https://github.com/huggingface/datasets/discussions/6768
<div type='discussions-op-text'>
<sup>Originally posted by **RitchieP** April 1, 2024</sup>
Currently, I have a dataset hosted on Huggingface with a custom script [here](https://huggingface.co/datasets/RitchieP/VerbaLex_voice).
I'm loading my dataset as below.
```py
from datasets import load_dataset, IterableDatasetDict
dataset = IterableDatasetDict()
dataset["train"] = load_dataset("RitchieP/VerbaLex_voice", "ar", split="train", use_auth_token=True, streaming=True)
dataset["test"] = load_dataset("RitchieP/VerbaLex_voice", "ar", split="test", use_auth_token=True, streaming=True)
```
And when I try to see the data I have loaded with
```py
list(dataset["train"].take(1))
```
And it gives me this stack trace
```
---------------------------------------------------------------------------
FileNotFoundError Traceback (most recent call last)
Cell In[2], line 1
----> 1 list(dataset["train"].take(1))
File /opt/conda/lib/python3.10/site-packages/datasets/iterable_dataset.py:1388, in IterableDataset.__iter__(self)
1385 yield formatter.format_row(pa_table)
1386 return
-> 1388 for key, example in ex_iterable:
1389 if self.features:
1390 # `IterableDataset` automatically fills missing columns with None.
1391 # This is done with `_apply_feature_types_on_example`.
1392 example = _apply_feature_types_on_example(
1393 example, self.features, token_per_repo_id=self._token_per_repo_id
1394 )
File /opt/conda/lib/python3.10/site-packages/datasets/iterable_dataset.py:1044, in TakeExamplesIterable.__iter__(self)
1043 def __iter__(self):
-> 1044 yield from islice(self.ex_iterable, self.n)
File /opt/conda/lib/python3.10/site-packages/datasets/iterable_dataset.py:234, in ExamplesIterable.__iter__(self)
233 def __iter__(self):
--> 234 yield from self.generate_examples_fn(**self.kwargs)
File ~/.cache/huggingface/modules/datasets_modules/datasets/RitchieP--VerbaLex_voice/9465eaee58383cf9d7c3e14111d7abaea56398185a641b646897d6df4e4732f7/VerbaLex_voice.py:127, in VerbaLexVoiceDataset._generate_examples(self, local_extracted_archive_paths, archives, meta_path)
125 for i, audio_archive in enumerate(archives):
126 print(audio_archive)
--> 127 for path, file in audio_archive:
128 _, filename = os.path.split(path)
129 if filename in metadata:
File /opt/conda/lib/python3.10/site-packages/datasets/download/streaming_download_manager.py:869, in _IterableFromGenerator.__iter__(self)
868 def __iter__(self):
--> 869 yield from self.generator(*self.args, **self.kwargs)
File /opt/conda/lib/python3.10/site-packages/datasets/download/streaming_download_manager.py:919, in ArchiveIterable._iter_from_urlpath(cls, urlpath, download_config)
915 @classmethod
916 def _iter_from_urlpath(
917 cls, urlpath: str, download_config: Optional[DownloadConfig] = None
918 ) -> Generator[Tuple, None, None]:
--> 919 compression = _get_extraction_protocol(urlpath, download_config=download_config)
920 # Set block_size=0 to get faster streaming
921 # (e.g. for hf:// and https:// it uses streaming Requests file-like instances)
922 with xopen(urlpath, "rb", download_config=download_config, block_size=0) as f:
File /opt/conda/lib/python3.10/site-packages/datasets/download/streaming_download_manager.py:400, in _get_extraction_protocol(urlpath, download_config)
398 urlpath, storage_options = _prepare_path_and_storage_options(urlpath, download_config=download_config)
399 try:
--> 400 with fsspec.open(urlpath, **(storage_options or {})) as f:
401 return _get_extraction_protocol_with_magic_number(f)
402 except FileNotFoundError:
File /opt/conda/lib/python3.10/site-packages/fsspec/core.py:100, in OpenFile.__enter__(self)
97 def __enter__(self):
98 mode = self.mode.replace("t", "").replace("b", "") + "b"
--> 100 f = self.fs.open(self.path, mode=mode)
102 self.fobjects = [f]
104 if self.compression is not None:
File /opt/conda/lib/python3.10/site-packages/fsspec/spec.py:1307, in AbstractFileSystem.open(self, path, mode, block_size, cache_options, compression, **kwargs)
1305 else:
1306 ac = kwargs.pop("autocommit", not self._intrans)
-> 1307 f = self._open(
1308 path,
1309 mode=mode,
1310 block_size=block_size,
1311 autocommit=ac,
1312 cache_options=cache_options,
1313 **kwargs,
1314 )
1315 if compression is not None:
1316 from fsspec.compression import compr
File /opt/conda/lib/python3.10/site-packages/fsspec/implementations/local.py:180, in LocalFileSystem._open(self, path, mode, block_size, **kwargs)
178 if self.auto_mkdir and "w" in mode:
179 self.makedirs(self._parent(path), exist_ok=True)
--> 180 return LocalFileOpener(path, mode, fs=self, **kwargs)
File /opt/conda/lib/python3.10/site-packages/fsspec/implementations/local.py:302, in LocalFileOpener.__init__(self, path, mode, autocommit, fs, compression, **kwargs)
300 self.compression = get_compression(path, compression)
301 self.blocksize = io.DEFAULT_BUFFER_SIZE
--> 302 self._open()
File /opt/conda/lib/python3.10/site-packages/fsspec/implementations/local.py:307, in LocalFileOpener._open(self)
305 if self.f is None or self.f.closed:
306 if self.autocommit or "w" not in self.mode:
--> 307 self.f = open(self.path, mode=self.mode)
308 if self.compression:
309 compress = compr[self.compression]
FileNotFoundError: [Errno 2] No such file or directory: '/kaggle/working/h'
```
After looking into the stack trace, and referring to the source codes, it looks like its trying to access a directory in the notebook's environment and I don't understand why.
Not sure if its a bug in Datasets library, so I'm opening a discussions first. Feel free to ask for more information if needed. Appreciate any help in advance!</div>
Hi, referring to the discussion title above, after further digging, I think it's an issue within the datasets library. But not quite sure where it is.
If you require any more info or actions from me, please let me know. Appreciate any help in advance! | {
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"You should be able to fix this by updating `huggingface_hub` with `pip install -U huggingface_hub`. We use this package under the hood to resolve the Hub's files."
] | 2024-04-01T20:17:48Z | 2024-04-11T17:31:44Z | 2024-04-11T17:31:44Z | NONE | null | null | {
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} | ### Describe the bug
`Datasets==2.18.0` is not compatible with `fsspec==2023.12.2`.
I have to downgrade fsspec to `fsspec==2023.10.0` to make `Datasets==2.18.0` work properly.
### Steps to reproduce the bug
To reproduce the bug:
1. Make sure that `Datasets==2.18.0` and `fsspec==2023.12.2`.
2. Run the following code:
```
from datasets import load_dataset
dataset = load_dataset("trec")
```
3. Then one will get the following error message:
```
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/opt/conda/lib/python3.10/site-packages/datasets/load.py", line 2556, in load_dataset
builder_instance = load_dataset_builder(
File "/opt/conda/lib/python3.10/site-packages/datasets/load.py", line 2265, in load_dataset_builder
builder_instance: DatasetBuilder = builder_cls(
File "/opt/conda/lib/python3.10/site-packages/datasets/builder.py", line 371, in __init__
self.config, self.config_id = self._create_builder_config(
File "/opt/conda/lib/python3.10/site-packages/datasets/builder.py", line 620, in _create_builder_config
builder_config._resolve_data_files(
File "/opt/conda/lib/python3.10/site-packages/datasets/builder.py", line 211, in _resolve_data_files
self.data_files = self.data_files.resolve(base_path, download_config)
File "/opt/conda/lib/python3.10/site-packages/datasets/data_files.py", line 799, in resolve
out[key] = data_files_patterns_list.resolve(base_path, download_config)
File "/opt/conda/lib/python3.10/site-packages/datasets/data_files.py", line 752, in resolve
resolve_pattern(
File "/opt/conda/lib/python3.10/site-packages/datasets/data_files.py", line 393, in resolve_pattern
raise FileNotFoundError(error_msg)
FileNotFoundError: Unable to find 'hf://datasets/trec@65752bf53af25bc935a0dce92fb5b6c930728450/default/train/0000.parquet' with any supported extension ['.csv', '.tsv', '.json', '.jsonl', '.parquet', '.geoparquet', '.gpq', '.arrow', '.txt', '.tar', '.blp', '.bmp', '.dib', '.bufr', '.cur', '.pcx', '.dcx', '.dds', '.ps', '.eps', '.fit', '.fits', '.fli', '.flc', '.ftc', '.ftu', '.gbr', '.gif', '.grib', '.h5', '.hdf', '.png', '.apng', '.jp2', '.j2k', '.jpc', '.jpf', '.jpx', '.j2c', '.icns', '.ico', '.im', '.iim', '.tif', '.tiff', '.jfif', '.jpe', '.jpg', '.jpeg', '.mpg', '.mpeg', '.msp', '.pcd', '.pxr', '.pbm', '.pgm', '.ppm', '.pnm', '.psd', '.bw', '.rgb', '.rgba', '.sgi', '.ras', '.tga', '.icb', '.vda', '.vst', '.webp', '.wmf', '.emf', '.xbm', '.xpm', '.BLP', '.BMP', '.DIB', '.BUFR', '.CUR', '.PCX', '.DCX', '.DDS', '.PS', '.EPS', '.FIT', '.FITS', '.FLI', '.FLC', '.FTC', '.FTU', '.GBR', '.GIF', '.GRIB', '.H5', '.HDF', '.PNG', '.APNG', '.JP2', '.J2K', '.JPC', '.JPF', '.JPX', '.J2C', '.ICNS', '.ICO', '.IM', '.IIM', '.TIF', '.TIFF', '.JFIF', '.JPE', '.JPG', '.JPEG', '.MPG', '.MPEG', '.MSP', '.PCD', '.PXR', '.PBM', '.PGM', '.PPM', '.PNM', '.PSD', '.BW', '.RGB', '.RGBA', '.SGI', '.RAS', '.TGA', '.ICB', '.VDA', '.VST', '.WEBP', '.WMF', '.EMF', '.XBM', '.XPM', '.aiff', '.au', '.avr', '.caf', '.flac', '.htk', '.svx', '.mat4', '.mat5', '.mpc2k', '.ogg', '.paf', '.pvf', '.raw', '.rf64', '.sd2', '.sds', '.ircam', '.voc', '.w64', '.wav', '.nist', '.wavex', '.wve', '.xi', '.mp3', '.opus', '.AIFF', '.AU', '.AVR', '.CAF', '.FLAC', '.HTK', '.SVX', '.MAT4', '.MAT5', '.MPC2K', '.OGG', '.PAF', '.PVF', '.RAW', '.RF64', '.SD2', '.SDS', '.IRCAM', '.VOC', '.W64', '.WAV', '.NIST', '.WAVEX', '.WVE', '.XI', '.MP3', '.OPUS', '.zip']
```
4. Similar issue also found for the following code:
```
dataset = load_dataset("sst", "default")
```
### Expected behavior
If the dataset is loaded correctly, one will have:
```
>>> print(dataset)
DatasetDict({
train: Dataset({
features: ['text', 'coarse_label', 'fine_label'],
num_rows: 5452
})
test: Dataset({
features: ['text', 'coarse_label', 'fine_label'],
num_rows: 500
})
})
>>>
```
### Environment info
- `datasets` version: 2.18.0
- Platform: Linux-6.2.0-35-generic-x86_64-with-glibc2.31
- Python version: 3.10.13
- `huggingface_hub` version: 0.20.3
- PyArrow version: 15.0.1
- Pandas version: 2.2.1
- `fsspec` version: 2023.12.2 | {
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"Hi! Instead of running `pip install` separately for each package, you should pass all the packages to a single `pip install` call (in this case, `pip install datasets s3fs`) to let `pip` properly resolve their versions.",
"> Hi! Instead of running `pip install` separately for each package, you should pass all th... | 2024-03-29T19:57:24Z | 2024-11-12T14:50:48Z | 2024-04-03T14:33:12Z | NONE | null | null | {
"completed": 0,
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} | ### Describe the bug
Here is the full error stack when installing:
```
ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.
datasets 2.18.0 requires fsspec[http]<=2024.2.0,>=2023.1.0, but you have fsspec 2024.3.1 which is incompatible.
Successfully installed aiobotocore-2.12.1 aioitertools-0.11.0 botocore-1.34.51 fsspec-2024.3.1 jmespath-1.0.1 s3fs-2024.3.1 urllib3-2.0.7 wrapt-1.16.0
```
When I install with pip, pip allows this error to exist while still installing s3fs, but this error breaks poetry, since poetry will refuse to install s3fs because of the dependency conflict.
Maybe I'm missing something so maybe it's not a bug but some mistake on my end? Any input would be helpful. Thanks!
### Steps to reproduce the bug
1. conda create -n tmp python=3.10 -y
2. conda activate tmp
3. pip install datasets
4. pip install s3fs
### Expected behavior
I would expect there to be no error.
### Environment info
MacOS (ARM), Python3.10, conda 23.11.0. | {
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"Thanks for reporting! We are working on a fix."
] | 2024-03-26T14:55:33Z | 2024-04-09T11:27:59Z | 2024-04-09T11:27:59Z | NONE | null | null | {
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} | ### Describe the bug
I have a dataset that consists of a bunch of text files, each representing an example. There is an undocumented `sample_by` argument for the `TextConfig` class that is used by `Text` to decide whether to split files into lines, paragraphs or take them whole. Passing `sample_by=“document”` to `load_dataset` results in files getting split into lines regardless. I have edited `src/datasets/packaged_modules/text/text.py` for myself to switch the default and it works fine.
As a side note, the `if-else` for `sample_by` will silently load an empty dataset if someone makes a typo in the argument, which is not ideal.
### Steps to reproduce the bug
1. Prepare data as a bunch of files in a directory.
2. Load that data via `load_dataset(“text”, data_files=<data_dir>/<files_glob>, …, sample_by=“document”)`.
3. Inspect the resultant dataset — every item should have the form of `{“text”: <a line from a file>}`.
### Expected behavior
`load_dataset(“text”, data_files=<data_dir>/<files_glob>, …, sample_by=“document”)` should result in a dataset with items of the form `{“text”: <one document>}`.
### Environment info
- `datasets` version: 2.18.0
- Platform: Linux-5.15.0-1046-nvidia-x86_64-with-glibc2.35
- Python version: 3.11.8
- `huggingface_hub` version: 0.21.4
- PyArrow version: 15.0.2
- Pandas version: 2.2.1
- `fsspec` version: 2024.2.0 | {
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"You can use `Dataset.from_sql(path_to_sql_file)` already. Though we haven't added the Sql dataset builder to the `_PACKAGED_DATASETS_MODULES` list or in `_EXTENSION_TO_MODULE` to map `.sqlite` to the Sql dataset builder\r\n\r\nThis would allow to load a dataset repository with a `.sqlite` file using `load_dataset`... | 2024-03-25T11:48:05Z | 2024-03-26T16:09:32Z | 2024-03-26T16:09:32Z | COLLABORATOR | null | null | {
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} | ### Feature request
Support loading a dataset from a SQLite file
https://huggingface.co/datasets/severo/test_iris_sqlite/tree/main
### Motivation
SQLite is a popular file format.
### Your contribution
See discussion on slack: https://huggingface.slack.com/archives/C04L6P8KNQ5/p1702481859117909 (internal)
In particular: a SQLite file can contain multiple tables, which might be matched to multiple configs. Maybe the detail of splits and configs should be defined in the README YAML, or use the same format as for ZIP files: `Iris.sqlite::Iris`.
See dataset here: https://huggingface.co/datasets/severo/test_iris_sqlite
Note: should we also support DuckDB files? | {
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"Thanks for reporting @fostiropoulos! I've edited your comment to fix the link to the problematic line.\r\n",
"@mariosasko can i take this up?",
"#self-assign"
] | 2024-03-24T21:47:52Z | 2024-04-02T14:01:19Z | 2024-04-02T14:01:19Z | NONE | null | null | {
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} | ### Describe the bug
There is a small typo on https://github.com/huggingface/datasets/blob/d5468836fe94e8be1ae093397dd43d4a2503b926/src/datasets/dataset_dict.py#L938
It should be `caching is enabled`.
### Steps to reproduce the bug
Please visit
https://github.com/huggingface/datasets/blob/d5468836fe94e8be1ae093397dd43d4a2503b926/src/datasets/dataset_dict.py#L938
### Expected behavior
`caching is enabled`
### Environment info
- `datasets` version: 2.17.1
- Platform: Linux-5.15.0-101-generic-x86_64-with-glibc2.35
- Python version: 3.11.7
- `huggingface_hub` version: 0.20.3
- PyArrow version: 15.0.0
- Pandas version: 2.2.1
- `fsspec` version: 2023.10.0 | {
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"I have the same problem \r\nIt seems that it only appears when you are using GPU \r\nIt seems to work fine with the 2.17 version though",
"Same here.",
"> I have the same problem\r\n> It seems that it only appears when you are using GPU\r\n> It seems to work fine with the 2.17 version though\r\n\r\nI downgrade... | 2024-03-24T03:01:30Z | 2024-10-02T11:49:35Z | 2024-03-30T00:23:49Z | NONE | null | null | {
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} | ### Describe the bug
When trying to run
```
import datasets
print(datasets.__version__)
```
It generates the following error
```
TypeError: expected string or bytes-like object
```
It looks like It cannot find the valid versions of `fsspec`
though fsspec version is fine when I checked Via command
```
import fsspec
print(fsspec.__version__)
# output: 2024.3.1
```
Detailed crash report
```
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
Cell In[1], line 1
----> 1 import datasets
2 print(datasets.__version__)
File /opt/conda/lib/python3.10/site-packages/datasets/__init__.py:18
1 # ruff: noqa
2 # Copyright 2020 The HuggingFace Datasets Authors and the TensorFlow Datasets Authors.
3 #
(...)
13 # See the License for the specific language governing permissions and
14 # limitations under the License.
16 __version__ = "2.18.0"
---> 18 from .arrow_dataset import Dataset
19 from .arrow_reader import ReadInstruction
20 from .builder import ArrowBasedBuilder, BeamBasedBuilder, BuilderConfig, DatasetBuilder, GeneratorBasedBuilder
File /opt/conda/lib/python3.10/site-packages/datasets/arrow_dataset.py:66
63 from multiprocess import Pool
64 from tqdm.contrib.concurrent import thread_map
---> 66 from . import config
67 from .arrow_reader import ArrowReader
68 from .arrow_writer import ArrowWriter, OptimizedTypedSequence
File /opt/conda/lib/python3.10/site-packages/datasets/config.py:41
39 # Imports
40 DILL_VERSION = version.parse(importlib.metadata.version("dill"))
---> 41 FSSPEC_VERSION = version.parse(importlib.metadata.version("fsspec"))
42 PANDAS_VERSION = version.parse(importlib.metadata.version("pandas"))
43 PYARROW_VERSION = version.parse(importlib.metadata.version("pyarrow"))
File /opt/conda/lib/python3.10/site-packages/packaging/version.py:49, in parse(version)
43 """
44 Parse the given version string and return either a :class:`Version` object
45 or a :class:`LegacyVersion` object depending on if the given version is
46 a valid PEP 440 version or a legacy version.
47 """
48 try:
---> 49 return Version(version)
50 except InvalidVersion:
51 return LegacyVersion(version)
File /opt/conda/lib/python3.10/site-packages/packaging/version.py:264, in Version.__init__(self, version)
261 def __init__(self, version: str) -> None:
262
263 # Validate the version and parse it into pieces
--> 264 match = self._regex.search(version)
265 if not match:
266 raise InvalidVersion(f"Invalid version: '{version}'")
TypeError: expected string or bytes-like object
```
### Steps to reproduce the bug
1. run `!pip install -U datasets` on kaggle
2. check datasets is installed via
```
import datasets
print(datasets.__version__)
```
### Expected behavior
Expected to print datasets version, like `2.18.0`
### Environment info
Running on Kaggle, latest enviornment , here is the notebook https://www.kaggle.com/code/jtv199/mistrial-7b-part2 | {
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https://api.github.com/repos/huggingface/datasets/issues/6750 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6750/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6750/comments | https://api.github.com/repos/huggingface/datasets/issues/6750/events | https://github.com/huggingface/datasets/issues/6750 | 2,203,590,658 | I_kwDODunzps6DWCAC | 6,750 | `load_dataset` requires a network connection for local download? | {
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"Are you using `HF_DATASETS_OFFLINE=1` ?",
"> Are you using `HF_DATASETS_OFFLINE=1` ?\r\n\r\nThis doesn't work for me. `datasets=2.18.0`\r\n\r\n`test.py`:\r\n```\r\nimport datasets\r\n\r\ndatasets.utils.logging.set_verbosity_info()\r\n\r\nds = datasets.load_dataset('C-MTEB/AFQMC', revision='b44c3b011063adb25877c1... | 2024-03-23T01:06:32Z | 2024-04-15T15:38:52Z | 2024-04-15T15:38:52Z | NONE | null | null | {
"completed": 0,
"percent_completed": 0,
"total": 0
} | ### Describe the bug
Hi all - I see that in the past a network dependency has been mistakenly introduced into `load_dataset` even for local loads. Is it possible this has happened again?
### Steps to reproduce the bug
```
>>> import datasets
>>> datasets.load_dataset("hh-rlhf")
Repo card metadata block was not found. Setting CardData to empty.
*hangs bc i'm firewalled*
````
stack trace from ctrl-c:
```
^CTraceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/jobuser/.local/lib/python3.10/site-packages/datasets/load.py", line 2582, in load_dataset
builder_instance.download_and_prepare(
output_path = get_from_cache( [0/122]
File "/home/jobuser/.local/lib/python3.10/site-packages/datasets/utils/file_utils.py", line 532, in get_from_cache
response = http_head(
File "/home/jobuser/.local/lib/python3.10/site-packages/datasets/utils/file_utils.py", line 419, in http_head
response = _request_with_retry(
File "/home/jobuser/.local/lib/python3.10/site-packages/datasets/utils/file_utils.py", line 304, in _request_with_retry
response = requests.request(method=method.upper(), url=url, timeout=timeout, **params)
File "/home/jobuser/build/lipy-flytekit-image/environments/satellites/python/lib/python3.10/site-packages/requests/api.py", line 59, in request
return session.request(method=method, url=url, **kwargs)
File "/home/jobuser/build/lipy-flytekit-image/environments/satellites/python/lib/python3.10/site-packages/requests/sessions.py", line 587, in request
resp = self.send(prep, **send_kwargs)
File "/home/jobuser/build/lipy-flytekit-image/environments/satellites/python/lib/python3.10/site-packages/requests/sessions.py", line 701, in send
r = adapter.send(request, **kwargs)
File "/home/jobuser/build/lipy-flytekit-image/environments/satellites/python/lib/python3.10/site-packages/requests/adapters.py", line 487, in send
resp = conn.urlopen(
File "/home/jobuser/build/lipy-flytekit-image/environments/satellites/python/lib/python3.10/site-packages/urllib3/connectionpool.py", line 703, in urlopen
httplib_response = self._make_request(
File "/home/jobuser/build/lipy-flytekit-image/environments/satellites/python/lib/python3.10/site-packages/urllib3/connectionpool.py", line 386, in _make_request
self._validate_conn(conn)
File "/home/jobuser/build/lipy-flytekit-image/environments/satellites/python/lib/python3.10/site-packages/urllib3/connectionpool.py", line 1042, in _validate_conn
conn.connect()
File "/home/jobuser/build/lipy-flytekit-image/environments/satellites/python/lib/python3.10/site-packages/urllib3/connection.py", line 363, in connect
self.sock = conn = self._new_conn()
File "/home/jobuser/build/lipy-flytekit-image/environments/satellites/python/lib/python3.10/site-packages/urllib3/connection.py", line 174, in _new_conn
conn = connection.create_connection(
File "/home/jobuser/build/lipy-flytekit-image/environments/satellites/python/lib/python3.10/site-packages/urllib3/util/connection.py", line 85, in create_connection
sock.connect(sa)
KeyboardInterrupt
```
### Expected behavior
loads the dataset
### Environment info
```
> pip show datasets
Name: datasets
Version: 2.18.0
```
Python 3.10.2 | {
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"Hi ! We updated the `allenai/c4` repository to allow people to specify which language to load easily (the the [c4 dataset page](https://huggingface.co/datasets/allenai/c4))\r\n\r\nTo fix this issue **you can update** `datasets` and remove the mention of the legacy configuration name \"allenai--c4\":\r\n\r\n```pyth... | 2024-03-21T02:53:04Z | 2024-09-18T19:57:14Z | 2024-07-29T07:21:08Z | NONE | null | null | {
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} | ### Describe the bug
I encounter bug when running the example command line
```python
python main.py \
--model decapoda-research/llama-7b-hf \
--prune_method wanda \
--sparsity_ratio 0.5 \
--sparsity_type unstructured \
--save out/llama_7b/unstructured/wanda/
```
The bug occurred at these lines of code (when loading c4 dataset)
```python
traindata = load_dataset('allenai/c4', 'allenai--c4', data_files={'train': 'en/c4-train.00000-of-01024.json.gz'}, split='train')
valdata = load_dataset('allenai/c4', 'allenai--c4', data_files={'validation': 'en/c4-validation.00000-of-00008.json.gz'}, split='validation')
```
The error message states:
```
raise ExpectedMoreSplits(str(set(expected_splits) - set(recorded_splits)))
datasets.utils.info_utils.ExpectedMoreSplits: {'validation'}
```
### Steps to reproduce the bug
1. I encounter bug when running the example command line
### Expected behavior
The error message states:
```
raise ExpectedMoreSplits(str(set(expected_splits) - set(recorded_splits)))
datasets.utils.info_utils.ExpectedMoreSplits: {'validation'}
```
### Environment info
I'm using cuda 12.4, so I use ```pip install pytorch``` instead of conda provided in install.md
Also, I've tried another environment using the same commands in install.md, but the same bug occured | {
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"It's not twitter here"
] | 2024-03-20T20:54:06Z | 2024-03-21T12:28:04Z | 2024-03-21T10:24:56Z | NONE | null | null | {
"completed": 0,
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} | ### Feature request
https://github.com/bigcode-project/opt-out-v2 - opt out is not consent. kindly quit this ridiculous nonsense.
### Motivation
[EDITED: insults not tolerated]
### Your contribution
[EDITED: insults not tolerated] | {
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} | ### Feature request
Request for adding rasterio support to load geotiff as a part of ImageFolder, instead of using PIL
### Motivation
As of now, there are many datasets in HuggingFace Hub which are predominantly focussed towards RemoteSensing or are from RemoteSensing. The current ImageFolder (if I have understood correctly) uses PIL. This is not really optimized because mostly these datasets have images with many channels and additional metadata. Using PIL makes one loose it unless we provide a custom script. Hence, maybe an API could be added to have this in common?
### Your contribution
If the issue is accepted - i can contribute the code, because I would like to have it automated and generalised. | {
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https://api.github.com/repos/huggingface/datasets/issues/6738 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6738/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6738/comments | https://api.github.com/repos/huggingface/datasets/issues/6738/events | https://github.com/huggingface/datasets/issues/6738 | 2,192,386,536 | I_kwDODunzps6CrSno | 6,738 | Dict feature is non-nullable while nested dict feature is | {
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"It looks like a bug, by default every feature should be nullable.",
"I've linked a PR with a fix :)",
"@mariosasko awesome thank you!"
] | 2024-03-18T14:31:47Z | 2024-03-20T10:24:15Z | 2024-03-19T20:05:20Z | CONTRIBUTOR | null | null | {
"completed": 0,
"percent_completed": 0,
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} | When i try to create a `Dataset` object with None values inside a dict column, like this:
```python
from datasets import Dataset, Features, Value
Dataset.from_dict(
{
"dict": [{"a": 0, "b": 0}, None],
}, features=Features(
{"dict": {"a": Value("int16"), "b": Value("int16")}}
)
)
```
i get `ValueError: Got None but expected a dictionary instead`.
At the same time, having None in _nested_ dict feature works, for example, this doesn't throw any errors:
```python
from datasets import Dataset, Features, Value, Sequence
dataset = Dataset.from_dict(
{
"list_dict": [[{"a": 0, "b": 0}], None],
"sequence_dict": [[{"a": 0, "b": 0}], None],
}, features=Features({
"list_dict": [{"a": Value("int16"), "b": Value("int16")}],
"sequence_dict": Sequence({"a": Value("int16"), "b": Value("int16")}),
})
)
```
Other types of features also seem to be nullable (but I haven't checked all of them).
Version of `datasets` is the latest atm (2.18.0)
Is this an expected behavior or a bug? | {
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https://api.github.com/repos/huggingface/datasets/issues/6737 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6737/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6737/comments | https://api.github.com/repos/huggingface/datasets/issues/6737/events | https://github.com/huggingface/datasets/issues/6737 | 2,190,198,425 | I_kwDODunzps6Ci8aZ | 6,737 | Invalid pattern: '**' can only be an entire path component | {
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"I couldn't reproduce the issue on my side on MacOS, I guess the issue comes from the recent `fsspec` on Windows.\r\n\r\nCan you try downgrading to `fsspec==2023.9.2` for now ? It would also be great to investigate this and see if we need a fix in `datasets` or `fsspec`",
"I had the same issue! \r\nDowngrading t... | 2024-03-16T19:28:46Z | 2024-07-23T14:23:28Z | 2024-05-13T11:32:57Z | NONE | null | null | {
"completed": 0,
"percent_completed": 0,
"total": 0
} | ### Describe the bug
ValueError: Invalid pattern: '**' can only be an entire path component
when loading any dataset
### Steps to reproduce the bug
import datasets
ds = datasets.load_dataset("TokenBender/code_instructions_122k_alpaca_style")
### Expected behavior
loading the dataset successfully
### Environment info
- `datasets` version: 2.18.0
- Platform: Windows-10-10.0.22631-SP0
- Python version: 3.11.7
- `huggingface_hub` version: 0.20.3
- PyArrow version: 15.0.0
- Pandas version: 2.2.1
- `fsspec` version: 2023.12.2 | {
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https://api.github.com/repos/huggingface/datasets/issues/6731 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6731/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6731/comments | https://api.github.com/repos/huggingface/datasets/issues/6731/events | https://github.com/huggingface/datasets/issues/6731 | 2,182,844,673 | I_kwDODunzps6CG5EB | 6,731 | Unexpected behavior when using load_dataset with streaming=True in a for loop | {
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} | [] | closed | false | null | [] | null | [
"This is normal behavior in python when using `lambda`: the `i` defined in your `lambda` refers to the global variable `i` in your loop, and `i` equals to `1` when you run your `for e in res[0]` line.\r\n\r\nYou should pass `fn_kwargs` that will be passed to your `lambda` instead of using the global variable:\r\n\r... | 2024-03-12T23:26:43Z | 2024-04-16T00:00:00Z | 2024-04-16T00:00:00Z | NONE | null | null | {
"completed": 0,
"percent_completed": 0,
"total": 0
} | ### Describe the bug
### My Code
```
from datasets import load_dataset
res=[]
for i in [0,1]:
di=load_dataset(
"json",
data_files='path_to.json',
split='train',
streaming=True,
).map(lambda x: {"source": i})
res.append(di)
for e in res[0]:
print(e)
```
### Unexpected Behavior
Data in `res[0]` has `source=1`. However the expected value is 0.
### FYI
I further switch `streaming` to `False`. And the output value is as expected (0). So there may exist bugs in setting `streaming=True` in a for loop.
### Environment
Python 3.8.0
datasets==2.18.0
transformers==4.28.1
### Steps to reproduce the bug
1. Create a Json file with any content.
2. Run the provided code.
3. Switch `streaming` to `False` and run again to see the expected behavior.
### Expected behavior
The expected behavior is the data are mapped with its corresponding value in the for loop.
### Environment info
Python 3.8.0
datasets==2.18.0
transformers==4.28.1
Ubuntu 20.04 | {
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https://api.github.com/repos/huggingface/datasets/issues/6729 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6729/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6729/comments | https://api.github.com/repos/huggingface/datasets/issues/6729/events | https://github.com/huggingface/datasets/issues/6729 | 2,180,237,159 | I_kwDODunzps6B88dn | 6,729 | Support zipfiles that span multiple disks? | {
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"default": true... | closed | false | null | [] | null | [
"@severo were you able to solve it?",
"No. cc @albertvillanova @lhoestq @polinaeterna for an evaluation of what it would take to support this feature.",
"The underlying issue issue is that the dataset repository has used split ZIP archive files: https://huggingface.co/datasets/PhilEO-community/PhilEO-downstream... | 2024-03-11T21:07:41Z | 2024-06-26T05:08:59Z | 2024-06-26T05:05:28Z | COLLABORATOR | null | null | {
"completed": 0,
"percent_completed": 0,
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} | See https://huggingface.co/datasets/PhilEO-community/PhilEO-downstream
The dataset viewer gives the following error:
```
Error code: ConfigNamesError
Exception: BadZipFile
Message: zipfiles that span multiple disks are not supported
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/dataset/config_names.py", line 67, in compute_config_names_response
get_dataset_config_names(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 347, in get_dataset_config_names
dataset_module = dataset_module_factory(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1871, in dataset_module_factory
raise e1 from None
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1846, in dataset_module_factory
return HubDatasetModuleFactoryWithoutScript(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1240, in get_module
module_name, default_builder_kwargs = infer_module_for_data_files(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 584, in infer_module_for_data_files
split_modules = {
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 585, in <dictcomp>
split: infer_module_for_data_files_list(data_files_list, download_config=download_config)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 526, in infer_module_for_data_files_list
return infer_module_for_data_files_list_in_archives(data_files_list, download_config=download_config)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 554, in infer_module_for_data_files_list_in_archives
for f in xglob(extracted, recursive=True, download_config=download_config)[
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/download/streaming_download_manager.py", line 576, in xglob
fs, *_ = fsspec.get_fs_token_paths(urlpath, storage_options=storage_options)
File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/core.py", line 622, in get_fs_token_paths
fs = filesystem(protocol, **inkwargs)
File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/registry.py", line 290, in filesystem
return cls(**storage_options)
File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/spec.py", line 79, in __call__
obj = super().__call__(*args, **kwargs)
File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/implementations/zip.py", line 57, in __init__
self.zip = zipfile.ZipFile(
File "/usr/local/lib/python3.9/zipfile.py", line 1266, in __init__
self._RealGetContents()
File "/usr/local/lib/python3.9/zipfile.py", line 1329, in _RealGetContents
endrec = _EndRecData(fp)
File "/usr/local/lib/python3.9/zipfile.py", line 286, in _EndRecData
return _EndRecData64(fpin, -sizeEndCentDir, endrec)
File "/usr/local/lib/python3.9/zipfile.py", line 232, in _EndRecData64
raise BadZipFile("zipfiles that span multiple disks are not supported")
zipfile.BadZipFile: zipfiles that span multiple disks are not supported
```
The files (https://huggingface.co/datasets/PhilEO-community/PhilEO-downstream/tree/main/data) are:
<img width="629" alt="Capture d’écran 2024-03-11 à 22 07 30" src="https://github.com/huggingface/datasets/assets/1676121/0bb15a51-d54f-4d73-8572-e427ea644b36">
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