id int64 599M 3.29B | url stringlengths 58 61 | html_url stringlengths 46 51 | number int64 1 7.72k | title stringlengths 1 290 | state stringclasses 2 values | comments int64 0 70 | created_at timestamp[s]date 2020-04-14 10:18:02 2025-08-05 09:28:51 | updated_at timestamp[s]date 2020-04-27 16:04:17 2025-08-05 11:39:56 | closed_at timestamp[s]date 2020-04-14 12:01:40 2025-08-01 05:15:45 β | user_login stringlengths 3 26 | labels listlengths 0 4 | body stringlengths 0 228k β | is_pull_request bool 2 classes |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
2,291,118,869 | https://api.github.com/repos/huggingface/datasets/issues/6891 | https://github.com/huggingface/datasets/issues/6891 | 6,891 | Unable to load JSON saved using `to_json` | closed | 2 | 2024-05-12T01:02:51 | 2024-05-16T14:32:55 | 2024-05-12T07:02:02 | DarshanDeshpande | [] | ### 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 | false |
2,288,699,041 | https://api.github.com/repos/huggingface/datasets/issues/6890 | https://github.com/huggingface/datasets/issues/6890 | 6,890 | add `with_transform` and/or `set_transform` to IterableDataset | open | 0 | 2024-05-10T01:00:12 | 2024-05-10T01:00:46 | null | not-lain | [
"enhancement"
] | ### Feature request
when working with a really large dataset it would save us a lot of time (and compute resources) to use either with_transform or the set_transform from the Dataset class instead of waiting for the entire dataset to map
### Motivation
don't want to wait for a really long dataset to map, this would give IterableDataset an extra advantage over the Dataset class.
reducing time and resources
### Your contribution
I am a little busy with my job search lately, but would post about this feature in my social media.
Apologies again (dad going to kick me out soon), if I ever have some free time I will contribute to making this a reality, but that's going to be hard
Β Β Β / (β¬β¬οΉβ¬β¬)\ | false |
2,287,720,539 | https://api.github.com/repos/huggingface/datasets/issues/6889 | https://github.com/huggingface/datasets/pull/6889 | 6,889 | fix bug #6877 | closed | 9 | 2024-05-09T13:38:40 | 2024-05-13T13:35:32 | 2024-05-13T13:35:32 | arthasking123 | [] | fix bug #6877 due to maybe f becomes invaild after yield process
the results are below:
Resolving data files: 100%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 828/828 [00:01<00:00, 420.41it/s]
Resolving data files: 100%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 828/828 [00:00<00:00, 26148.48it/s]
Resolving data files: 100%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 828/828 [00:00<00:00, 409731.44it/s]
Resolving data files: 100%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 828/828 [00:00<00:00, 289720.84it/s]
Resolving data files: 100%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 828/828 [00:00<00:00, 26663.42it/s]
Resolving data files: 100%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 828/828 [00:00<00:00, 434056.21it/s]
Downloading data: 100%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 828/828 [00:00<00:00, 13222.33files/s]
Downloading data: 100%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 828/828 [00:04<00:00, 180.67files/s]
Downloading data: 100%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 828/828 [01:35<00:00, 8.70files/s]
Generating train split: 1571592 examples [00:08, 176736.09 examples/s]
Generating test split: 85533 examples [00:01, 48224.56 examples/s]
Generating validation split: 86246 examples [00:01, 50164.16 examples/s]
Fix https://github.com/huggingface/datasets/issues/6877.
CC: @natolambert
| true |
2,287,169,676 | https://api.github.com/repos/huggingface/datasets/issues/6888 | https://github.com/huggingface/datasets/pull/6888 | 6,888 | Support WebDataset containing file basenames with dots | closed | 5 | 2024-05-09T08:25:30 | 2024-05-10T13:54:06 | 2024-05-10T13:54:06 | albertvillanova | [] | Support WebDataset containing file basenames with dots.
Fix #6880. | true |
2,286,786,396 | https://api.github.com/repos/huggingface/datasets/issues/6887 | https://github.com/huggingface/datasets/issues/6887 | 6,887 | FAISS load to None | open | 1 | 2024-05-09T02:43:50 | 2024-05-16T20:44:23 | null | brainer3220 | [] | ### Describe the bug
I've use FAISS with Datasets and save to FAISS.
Then load to save FAISS then no error, then ds to None
```python
ds.load_faiss_index('embeddings', 'my_index.faiss')
```
### Steps to reproduce the bug
# 1.
```python
ds_with_embeddings = ds.map(lambda example: {'embeddings': model(transforms(example['image']).unsqueeze(0)).squeeze()}, batch_size=64)
ds_with_embeddings.add_faiss_index(column='embeddings')
ds_with_embeddings.save_faiss_index('embeddings', 'index.faiss')
```
# 2.
```python
ds.load_faiss_index('embeddings', 'my_index.faiss')
```
### Expected behavior
Add column in Datasets.
### Environment info
Google Colab, SageMaker Notebook | false |
2,286,328,984 | https://api.github.com/repos/huggingface/datasets/issues/6886 | https://github.com/huggingface/datasets/issues/6886 | 6,886 | load_dataset with data_dir and cache_dir set fail with not supported | open | 0 | 2024-05-08T19:52:35 | 2024-05-08T19:58:11 | null | fah | [] | ### Describe the bug
with python 3.11 I execute:
```py
from transformers import Wav2Vec2Processor, Data2VecAudioModel
import torch
from torch import nn
from datasets import load_dataset, concatenate_datasets
# load demo audio and set processor
dataset_clean = load_dataset("librispeech_asr", "clean", split="validation", data_dir="data", cache_dir="cache")
```
This fails in the last line with
```log
Found cached dataset librispeech_asr (file:///Users/as/Documents/Project/git/audio2vec/cache/librispeech_asr/clean-data_dir=data/2.1.0/cff5df6e7955c80a67f80e27e7e655de71c689e2d2364bece785b972acb37fe7)
Traceback (most recent call last):
File "/Users/as/Documents/Project/git/audio2vec/src/music2vec-v1.py", line 7, in <module>
dataset_clean = load_dataset("librispeech_asr", "clean", split="validation", data_dir="data", cache_dir="cache")
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/as/anaconda3/lib/python3.11/site-packages/datasets/load.py", line 1810, in load_dataset
ds = builder_instance.as_dataset(split=split, verification_mode=verification_mode, in_memory=keep_in_memory)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/as/anaconda3/lib/python3.11/site-packages/datasets/builder.py", line 1113, in as_dataset
raise NotImplementedError(f"Loading a dataset cached in a {type(self._fs).__name__} is not supported.")
NotImplementedError: Loading a dataset cached in a LocalFileSystem is not supported.
```
### Steps to reproduce the bug
I setup an venv with requirements.txt
```txt
transformers==4.40.2
torch==2.2.2
datasets==2.16.0
fsspec==2023.9.2
```
pip freeze is:
```
aiohttp==3.9.5
aiosignal==1.3.1
attrs==23.2.0
certifi==2024.2.2
charset-normalizer==3.3.2
datasets==2.16.0
dill==0.3.7
filelock==3.14.0
frozenlist==1.4.1
fsspec==2023.9.2
huggingface-hub==0.23.0
idna==3.7
Jinja2==3.1.4
MarkupSafe==2.1.5
mpmath==1.3.0
multidict==6.0.5
multiprocess==0.70.15
networkx==3.3
numpy==1.26.4
packaging==24.0
pandas==2.2.2
pyarrow==16.0.0
pyarrow-hotfix==0.6
python-dateutil==2.9.0.post0
pytz==2024.1
PyYAML==6.0.1
regex==2024.4.28
requests==2.31.0
safetensors==0.4.3
six==1.16.0
sympy==1.12
tokenizers==0.19.1
torch==2.2.2
tqdm==4.66.4
transformers==4.40.2
typing_extensions==4.11.0
tzdata==2024.1
urllib3==2.2.1
xxhash==3.4.1
yarl==1.9.4
```
I execute this on a M1 Mac.
### Expected behavior
I don't understand the error message. Why is "local" caching not supported. Would it possible to give some additional hint with the error message how to solve this issue?
### Environment info
source ....
python -u example.py | false |
2,285,115,400 | https://api.github.com/repos/huggingface/datasets/issues/6885 | https://github.com/huggingface/datasets/pull/6885 | 6,885 | Support jax 0.4.27 in CI tests | closed | 2 | 2024-05-08T09:19:37 | 2024-05-08T09:43:19 | 2024-05-08T09:35:16 | albertvillanova | [] | Support jax 0.4.27 in CI tests by using jax Array `devices` method instead of `device` (which no longer exists).
Fix #6884. | true |
2,284,839,687 | https://api.github.com/repos/huggingface/datasets/issues/6884 | https://github.com/huggingface/datasets/issues/6884 | 6,884 | CI is broken after jax-0.4.27 release: AttributeError: 'jaxlib.xla_extension.DeviceList' object has no attribute 'device' | closed | 0 | 2024-05-08T07:01:47 | 2024-05-08T09:35:17 | 2024-05-08T09:35:17 | albertvillanova | [
"bug"
] | After jax-0.4.27 release (https://github.com/google/jax/releases/tag/jax-v0.4.27), our CI is broken with the error:
```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
``` | false |
2,284,808,399 | https://api.github.com/repos/huggingface/datasets/issues/6883 | https://github.com/huggingface/datasets/pull/6883 | 6,883 | Require Pillow >= 9.4.0 to avoid AttributeError when loading image dataset | closed | 10 | 2024-05-08T06:43:29 | 2024-08-28T13:13:57 | 2024-05-16T14:34:02 | albertvillanova | [] | Require Pillow >= 9.4.0 to avoid AttributeError when loading image dataset.
The `PIL.Image.ExifTags` that we use in our code was implemented in Pillow-9.4.0: https://github.com/python-pillow/Pillow/commit/24a5405a9f7ea22f28f9c98b3e407292ea5ee1d3
The bug #6881 was introduced in datasets-2.19.0 by this PR:
- #6739
Fix #6881. | true |
2,284,803,158 | https://api.github.com/repos/huggingface/datasets/issues/6882 | https://github.com/huggingface/datasets/issues/6882 | 6,882 | Connection Error When Using By-pass Proxies | open | 1 | 2024-05-08T06:40:14 | 2024-05-17T06:38:30 | null | MRNOBODY-ZST | [] | ### Describe the bug
I'm currently using Clash for Windows as my proxy tunnel, after exporting HTTP_PROXY and HTTPS_PROXY to the port that clash providesπ€, it runs into a connection error saying "Couldn't reach https://raw.githubusercontent.com/huggingface/datasets/2.19.1/metrics/seqeval/seqeval.py (ConnectionError(MaxRetryError("HTTPSConnectionPool(host='raw.githubusercontent.com', port=443): Max retries exceeded with url: /huggingface/datasets/2.19.1/metrics/seqeval/seqeval.py (Caused by NewConnectionError('<urllib3.connection.HTTPSConnection object at 0x7f969d391870>: Failed to establish a new connection: [Errno 111] Connection refused'))")))"
I have already read the documentation provided on the hugginface, but I think I didn't see the detailed instruction on how to set up proxies for this library.
### Steps to reproduce the bug
1. Turn on any proxy software like Clash / ShadosocksR etc.
2. export system varibles to the port provided by your proxy software in wsl (It's ok for other applications to use proxy expect dataset-library)
3. load any dataset from hugginface online
### Expected behavior
---------------------------------------------------------------------------
ConnectionError Traceback (most recent call last)
Cell In[33], [line 3](vscode-notebook-cell:?execution_count=33&line=3)
[1](vscode-notebook-cell:?execution_count=33&line=1) from datasets import load_metric
----> [3](vscode-notebook-cell:?execution_count=33&line=3) metric = load_metric("seqeval")
File ~/.local/lib/python3.10/site-packages/datasets/utils/deprecation_utils.py:46, in deprecated.<locals>.decorator.<locals>.wrapper(*args, **kwargs)
[44](https://vscode-remote+wsl-002bubuntu-002d22-002e04.vscode-resource.vscode-cdn.net/home/noodle/Transformers-Tutorials/LayoutLMv3/~/.local/lib/python3.10/site-packages/datasets/utils/deprecation_utils.py:44) warnings.warn(warning_msg, category=FutureWarning, stacklevel=2)
[45](https://vscode-remote+wsl-002bubuntu-002d22-002e04.vscode-resource.vscode-cdn.net/home/noodle/Transformers-Tutorials/LayoutLMv3/~/.local/lib/python3.10/site-packages/datasets/utils/deprecation_utils.py:45) _emitted_deprecation_warnings.add(func_hash)
---> [46](https://vscode-remote+wsl-002bubuntu-002d22-002e04.vscode-resource.vscode-cdn.net/home/noodle/Transformers-Tutorials/LayoutLMv3/~/.local/lib/python3.10/site-packages/datasets/utils/deprecation_utils.py:46) return deprecated_function(*args, **kwargs)
File ~/.local/lib/python3.10/site-packages/datasets/load.py:2104, in load_metric(path, config_name, process_id, num_process, cache_dir, experiment_id, keep_in_memory, download_config, download_mode, revision, trust_remote_code, **metric_init_kwargs)
[2101](https://vscode-remote+wsl-002bubuntu-002d22-002e04.vscode-resource.vscode-cdn.net/home/noodle/Transformers-Tutorials/LayoutLMv3/~/.local/lib/python3.10/site-packages/datasets/load.py:2101) warnings.filterwarnings("ignore", message=".*https://huggingface.co/docs/evaluate$", category=FutureWarning)
[2103](https://vscode-remote+wsl-002bubuntu-002d22-002e04.vscode-resource.vscode-cdn.net/home/noodle/Transformers-Tutorials/LayoutLMv3/~/.local/lib/python3.10/site-packages/datasets/load.py:2103) download_mode = DownloadMode(download_mode or DownloadMode.REUSE_DATASET_IF_EXISTS)
-> [2104](https://vscode-remote+wsl-002bubuntu-002d22-002e04.vscode-resource.vscode-cdn.net/home/noodle/Transformers-Tutorials/LayoutLMv3/~/.local/lib/python3.10/site-packages/datasets/load.py:2104) metric_module = metric_module_factory(
[2105](https://vscode-remote+wsl-002bubuntu-002d22-002e04.vscode-resource.vscode-cdn.net/home/noodle/Transformers-Tutorials/LayoutLMv3/~/.local/lib/python3.10/site-packages/datasets/load.py:2105) path,
[2106](https://vscode-remote+wsl-002bubuntu-002d22-002e04.vscode-resource.vscode-cdn.net/home/noodle/Transformers-Tutorials/LayoutLMv3/~/.local/lib/python3.10/site-packages/datasets/load.py:2106) revision=revision,
[2107](https://vscode-remote+wsl-002bubuntu-002d22-002e04.vscode-resource.vscode-cdn.net/home/noodle/Transformers-Tutorials/LayoutLMv3/~/.local/lib/python3.10/site-packages/datasets/load.py:2107) download_config=download_config,
[2108](https://vscode-remote+wsl-002bubuntu-002d22-002e04.vscode-resource.vscode-cdn.net/home/noodle/Transformers-Tutorials/LayoutLMv3/~/.local/lib/python3.10/site-packages/datasets/load.py:2108) download_mode=download_mode,
[2109](https://vscode-remote+wsl-002bubuntu-002d22-002e04.vscode-resource.vscode-cdn.net/home/noodle/Transformers-Tutorials/LayoutLMv3/~/.local/lib/python3.10/site-packages/datasets/load.py:2109) trust_remote_code=trust_remote_code,
[2110](https://vscode-remote+wsl-002bubuntu-002d22-002e04.vscode-resource.vscode-cdn.net/home/noodle/Transformers-Tutorials/LayoutLMv3/~/.local/lib/python3.10/site-packages/datasets/load.py:2110) ).module_path
[2111](https://vscode-remote+wsl-002bubuntu-002d22-002e04.vscode-resource.vscode-cdn.net/home/noodle/Transformers-Tutorials/LayoutLMv3/~/.local/lib/python3.10/site-packages/datasets/load.py:2111) metric_cls = import_main_class(metric_module, dataset=False)
[2112](https://vscode-remote+wsl-002bubuntu-002d22-002e04.vscode-resource.vscode-cdn.net/home/noodle/Transformers-Tutorials/LayoutLMv3/~/.local/lib/python3.10/site-packages/datasets/load.py:2112) metric = metric_cls(
[2113](https://vscode-remote+wsl-002bubuntu-002d22-002e04.vscode-resource.vscode-cdn.net/home/noodle/Transformers-Tutorials/LayoutLMv3/~/.local/lib/python3.10/site-packages/datasets/load.py:2113) config_name=config_name,
[2114](https://vscode-remote+wsl-002bubuntu-002d22-002e04.vscode-resource.vscode-cdn.net/home/noodle/Transformers-Tutorials/LayoutLMv3/~/.local/lib/python3.10/site-packages/datasets/load.py:2114) process_id=process_id,
...
--> [633](https://vscode-remote+wsl-002bubuntu-002d22-002e04.vscode-resource.vscode-cdn.net/home/noodle/Transformers-Tutorials/LayoutLMv3/~/.local/lib/python3.10/site-packages/datasets/utils/file_utils.py:633) raise ConnectionError(f"Couldn't reach {url} ({repr(head_error)})")
[634](https://vscode-remote+wsl-002bubuntu-002d22-002e04.vscode-resource.vscode-cdn.net/home/noodle/Transformers-Tutorials/LayoutLMv3/~/.local/lib/python3.10/site-packages/datasets/utils/file_utils.py:634) elif response is not None:
[635](https://vscode-remote+wsl-002bubuntu-002d22-002e04.vscode-resource.vscode-cdn.net/home/noodle/Transformers-Tutorials/LayoutLMv3/~/.local/lib/python3.10/site-packages/datasets/utils/file_utils.py:635) raise ConnectionError(f"Couldn't reach {url} (error {response.status_code})")
ConnectionError: Couldn't reach https://raw.githubusercontent.com/huggingface/datasets/2.19.1/metrics/seqeval/seqeval.py (SSLError(MaxRetryError("HTTPSConnectionPool(host='raw.githubusercontent.com', port=443): Max retries exceeded with url: /huggingface/datasets/2.19.1/metrics/seqeval/seqeval.py (Caused by SSLError(SSLEOFError(8, '[SSL: UNEXPECTED_EOF_WHILE_READING] EOF occurred in violation of protocol (_ssl.c:1007)')))")))
### Environment info
- `datasets` version: 2.19.1
- Platform: Linux-5.10.102.1-microsoft-standard-WSL2-x86_64-with-glibc2.35
- Python version: 3.10.12
- `huggingface_hub` version: 0.23.0
- PyArrow version: 16.0.0
- Pandas version: 2.2.2
- `fsspec` version: 2024.2.0 | false |
2,284,794,009 | https://api.github.com/repos/huggingface/datasets/issues/6881 | https://github.com/huggingface/datasets/issues/6881 | 6,881 | AttributeError: module 'PIL.Image' has no attribute 'ExifTags' | closed | 3 | 2024-05-08T06:33:57 | 2024-07-18T06:49:30 | 2024-05-16T14:34:03 | albertvillanova | [
"bug"
] | 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 | false |
2,283,278,337 | https://api.github.com/repos/huggingface/datasets/issues/6880 | https://github.com/huggingface/datasets/issues/6880 | 6,880 | Webdataset: KeyError: 'png' on some datasets when streaming | open | 5 | 2024-05-07T13:09:02 | 2024-05-14T20:34:05 | null | lhoestq | [] | reported at https://huggingface.co/datasets/tbone5563/tar_images/discussions/1
```python
>>> from datasets import load_dataset
>>> ds = load_dataset("tbone5563/tar_images")
Downloadingβdata:β100%
β1.41G/1.41Gβ[00:48<00:00,β17.2MB/s]
Downloadingβdata:β100%
β619M/619Mβ[00:11<00:00,β57.4MB/s]
Generatingβtrainβsplit:β
β970/0β[00:02<00:00,β534.94βexamples/s]
---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
[/usr/local/lib/python3.10/dist-packages/datasets/builder.py](https://localhost:8080/#) in _prepare_split_single(self, gen_kwargs, fpath, file_format, max_shard_size, split_info, check_duplicate_keys, job_id)
1747 _time = time.time()
-> 1748 for key, record in generator:
1749 if max_shard_size is not None and writer._num_bytes > max_shard_size:
7 frames
[/usr/local/lib/python3.10/dist-packages/datasets/packaged_modules/webdataset/webdataset.py](https://localhost:8080/#) in _generate_examples(self, tar_paths, tar_iterators)
108 for field_name in image_field_names + audio_field_names:
--> 109 example[field_name] = {"path": example["__key__"] + "." + field_name, "bytes": example[field_name]}
110 yield f"{tar_idx}_{example_idx}", example
KeyError: 'png'
The above exception was the direct cause of the following exception:
DatasetGenerationError Traceback (most recent call last)
[<ipython-input-2-8e0fbb7badc9>](https://localhost:8080/#) in <cell line: 3>()
1 from datasets import load_dataset
2
----> 3 ds = load_dataset("tbone5563/tar_images")
[/usr/local/lib/python3.10/dist-packages/datasets/load.py](https://localhost:8080/#) 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)
2607
2608 # Download and prepare data
-> 2609 builder_instance.download_and_prepare(
2610 download_config=download_config,
2611 download_mode=download_mode,
[/usr/local/lib/python3.10/dist-packages/datasets/builder.py](https://localhost:8080/#) in 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)
1025 if num_proc is not None:
1026 prepare_split_kwargs["num_proc"] = num_proc
-> 1027 self._download_and_prepare(
1028 dl_manager=dl_manager,
1029 verification_mode=verification_mode,
[/usr/local/lib/python3.10/dist-packages/datasets/builder.py](https://localhost:8080/#) in _download_and_prepare(self, dl_manager, verification_mode, **prepare_splits_kwargs)
1787
1788 def _download_and_prepare(self, dl_manager, verification_mode, **prepare_splits_kwargs):
-> 1789 super()._download_and_prepare(
1790 dl_manager,
1791 verification_mode,
[/usr/local/lib/python3.10/dist-packages/datasets/builder.py](https://localhost:8080/#) in _download_and_prepare(self, dl_manager, verification_mode, **prepare_split_kwargs)
1120 try:
1121 # Prepare split will record examples associated to the split
-> 1122 self._prepare_split(split_generator, **prepare_split_kwargs)
1123 except OSError as e:
1124 raise OSError(
[/usr/local/lib/python3.10/dist-packages/datasets/builder.py](https://localhost:8080/#) in _prepare_split(self, split_generator, check_duplicate_keys, file_format, num_proc, max_shard_size)
1625 job_id = 0
1626 with pbar:
-> 1627 for job_id, done, content in self._prepare_split_single(
1628 gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
1629 ):
[/usr/local/lib/python3.10/dist-packages/datasets/builder.py](https://localhost:8080/#) in _prepare_split_single(self, gen_kwargs, fpath, file_format, max_shard_size, split_info, check_duplicate_keys, job_id)
1782 if isinstance(e, SchemaInferenceError) and e.__context__ is not None:
1783 e = e.__context__
-> 1784 raise DatasetGenerationError("An error occurred while generating the dataset") from e
1785
1786 yield job_id, True, (total_num_examples, total_num_bytes, writer._features, num_shards, shard_lengths)
DatasetGenerationError: An error occurred while generating the dataset
``` | false |
2,282,968,259 | https://api.github.com/repos/huggingface/datasets/issues/6879 | https://github.com/huggingface/datasets/issues/6879 | 6,879 | Batched mapping does not raise an error if values for an existing column are empty | open | 0 | 2024-05-07T11:02:40 | 2024-05-07T11:02:40 | null | felix-schneider | [] | ### Describe the bug
Using `Dataset.map(fn, batched=True)` allows resizing the dataset by returning a dict of lists, all of which must be the same size. If they are not the same size, an error like `pyarrow.lib.ArrowInvalid: Column 1 named x expected length 1 but got length 0` is raised.
This is not the case if the function returns an empty list for an existing column in the dataset. In that case, the dataset is silently resized to 0 rows.
### Steps to reproduce the bug
MWE:
```
import datasets
data = datasets.Dataset.from_dict({"test": [1]})
def mapping_fn(examples):
return {"test": [], "y": [1]}
data = data.map(mapping_fn, batched=True)
print(len(data))
```
Note that when returning `"x": []`, the error is raised correctly, also when returning `"test": [1,2]`.
### Expected behavior
Expected an exception: `pyarrow.lib.ArrowInvalid: Column 1 named test expected length 1 but got length 0` or `pyarrow.lib.ArrowInvalid: Column 2 named y expected length 0 but got length 1`.
Any exception would be acceptable.
### Environment info
- `datasets` version: 2.19.1
- Platform: Linux-5.4.0-153-generic-x86_64-with-glibc2.31
- Python version: 3.11.8
- `huggingface_hub` version: 0.22.2
- PyArrow version: 15.0.2
- Pandas version: 2.2.1
- `fsspec` version: 2024.2.0 | false |
2,282,879,491 | https://api.github.com/repos/huggingface/datasets/issues/6878 | https://github.com/huggingface/datasets/pull/6878 | 6,878 | Create function to convert to parquet | closed | 2 | 2024-05-07T10:27:07 | 2024-05-16T14:46:44 | 2024-05-16T14:38:23 | albertvillanova | [] | Analogously with `delete_from_hub`, this PR:
- creates the Python function `convert_to_parquet`
- makes the corresponding CLI command use that function.
This way, the functionality can be used both from a terminal and from a Python console.
This PR also implements a test for convert_to_parquet function. | true |
2,282,068,337 | https://api.github.com/repos/huggingface/datasets/issues/6877 | https://github.com/huggingface/datasets/issues/6877 | 6,877 | OSError: [Errno 24] Too many open files | closed | 5 | 2024-05-07T01:15:09 | 2024-06-02T14:22:23 | 2024-05-13T13:01:55 | loicmagne | [
"bug"
] | ### 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%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 201k/201k [00:00<00:00, 1.07MB/s]
Resolving data files: 100%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 828/828 [00:00<00:00, 1069.15it/s]
Resolving data files: 100%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 828/828 [00:00<00:00, 436182.33it/s]
Resolving data files: 100%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 828/828 [00:00<00:00, 2228.75it/s]
Resolving data files: 100%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 828/828 [00:00<00:00, 646478.73it/s]
Resolving data files: 100%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 828/828 [00:00<00:00, 831032.24it/s]
Resolving data files: 100%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 828/828 [00:00<00:00, 517645.51it/s]
Downloading data: 100%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 828/828 [00:33<00:00, 24.87files/s]
Downloading data: 100%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 828/828 [00:30<00:00, 27.48files/s]
Downloading data: 100%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 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
| false |
2,281,450,743 | https://api.github.com/repos/huggingface/datasets/issues/6876 | https://github.com/huggingface/datasets/pull/6876 | 6,876 | Unpin hfh | closed | 12 | 2024-05-06T18:10:49 | 2024-05-27T10:20:42 | 2024-05-27T10:14:40 | lhoestq | [] | Needed to use those in dataset-viewer:
- dev version of hfh https://github.com/huggingface/dataset-viewer/pull/2781: don't span the hub with /paths-info requests
- dev version of datasets at https://github.com/huggingface/datasets/pull/6875: don't write too big logs in the viewer
close https://github.com/huggingface/datasets/issues/6863 | true |
2,281,428,826 | https://api.github.com/repos/huggingface/datasets/issues/6875 | https://github.com/huggingface/datasets/pull/6875 | 6,875 | Shorten long logs | closed | 2 | 2024-05-06T17:57:07 | 2024-05-07T12:31:46 | 2024-05-07T12:25:45 | lhoestq | [] | Some datasets may have unexpectedly long features/types (e.g. if the files are not formatted correctly).
In that case we should still be able to log something readable | true |
2,280,717,233 | https://api.github.com/repos/huggingface/datasets/issues/6874 | https://github.com/huggingface/datasets/pull/6874 | 6,874 | Use pandas ujson in JSON loader to improve performance | closed | 4 | 2024-05-06T12:01:27 | 2024-05-17T16:28:29 | 2024-05-17T16:22:27 | albertvillanova | [] | Use pandas ujson in JSON loader to improve performance.
Note that `datasets` has `pandas` as required dependency. And `pandas` includes `ujson` in `pd.io.json.ujson_loads`.
Fix #6867.
CC: @natolambert | true |
2,280,463,182 | https://api.github.com/repos/huggingface/datasets/issues/6873 | https://github.com/huggingface/datasets/pull/6873 | 6,873 | Set dev version | closed | 2 | 2024-05-06T09:43:18 | 2024-05-06T10:03:19 | 2024-05-06T09:57:12 | albertvillanova | [] | null | true |
2,280,438,432 | https://api.github.com/repos/huggingface/datasets/issues/6872 | https://github.com/huggingface/datasets/pull/6872 | 6,872 | Release 2.19.1 | closed | 0 | 2024-05-06T09:29:15 | 2024-05-06T09:35:33 | 2024-05-06T09:35:32 | albertvillanova | [] | null | true |
2,280,102,869 | https://api.github.com/repos/huggingface/datasets/issues/6871 | https://github.com/huggingface/datasets/pull/6871 | 6,871 | Fix download for dict of dicts of URLs | closed | 4 | 2024-05-06T06:06:52 | 2024-05-06T09:32:03 | 2024-05-06T09:25:52 | albertvillanova | [] | Fix download for a dict of dicts of URLs when batched (default), introduced by:
- #6794
This PR also implements regression tests.
Fix #6869, fix #6850. | true |
2,280,084,008 | https://api.github.com/repos/huggingface/datasets/issues/6870 | https://github.com/huggingface/datasets/pull/6870 | 6,870 | Update tqdm >= 4.66.3 to fix vulnerability | closed | 2 | 2024-05-06T05:49:36 | 2024-05-06T06:08:06 | 2024-05-06T06:02:00 | albertvillanova | [] | Update tqdm >= 4.66.3 to fix vulnerability, | true |
2,280,048,297 | https://api.github.com/repos/huggingface/datasets/issues/6869 | https://github.com/huggingface/datasets/issues/6869 | 6,869 | Download is broken for dict of dicts: FileNotFoundError | closed | 0 | 2024-05-06T05:13:36 | 2024-05-06T09:25:53 | 2024-05-06T09:25:53 | albertvillanova | [
"bug"
] | 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
| false |
2,279,385,159 | https://api.github.com/repos/huggingface/datasets/issues/6868 | https://github.com/huggingface/datasets/issues/6868 | 6,868 | datasets.BuilderConfig does not work. | closed | 1 | 2024-05-05T08:08:55 | 2024-05-05T12:15:02 | 2024-05-05T12:15:01 | jdm4pku | [] | ### 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 | false |
2,279,059,787 | https://api.github.com/repos/huggingface/datasets/issues/6867 | https://github.com/huggingface/datasets/issues/6867 | 6,867 | Improve performance of JSON loader | closed | 5 | 2024-05-04T15:04:16 | 2024-05-17T16:22:28 | 2024-05-17T16:22:28 | albertvillanova | [
"enhancement"
] | 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 | false |
2,278,736,221 | https://api.github.com/repos/huggingface/datasets/issues/6866 | https://github.com/huggingface/datasets/issues/6866 | 6,866 | DataFilesNotFoundError for datasets in the open-llm-leaderboard | closed | 3 | 2024-05-04T04:59:00 | 2024-05-14T08:09:56 | 2024-05-14T08:09:56 | jerome-white | [] | ### 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 | false |
2,277,304,832 | https://api.github.com/repos/huggingface/datasets/issues/6865 | https://github.com/huggingface/datasets/issues/6865 | 6,865 | Example on Semantic segmentation contains bug | open | 0 | 2024-05-03T09:40:12 | 2024-05-03T09:40:12 | null | ducha-aiki | [] | ### Describe the bug
https://huggingface.co/docs/datasets/en/semantic_segmentation shows wrong example with torchvision transforms.
Specifically, as one can see in screenshot below, the object boundaries have weird colors.
<img width="689" alt="image" src="https://github.com/huggingface/datasets/assets/4803565/59aa0e2c-2e3e-415b-9d42-2314044c5aee">
Original example with `albumentations` is correct
<img width="705" alt="image" src="https://github.com/huggingface/datasets/assets/4803565/27dbd725-cea5-4e48-ba59-7050c3ce17b3">
That is because `torch vision.transforms.Resize` interpolates with bilinear everything which is wrong when used for segmentation labels - you just cannot mix them. Overall, `torchvision.transforms` is designed for classification only and cannot be used to images and masks together, unless you write two separate branches of augmentations.
The correct way would be to use `v2` version of transforms and convert the segmentation labels to https://pytorch.org/vision/main/generated/torchvision.tv_tensors.Mask.html#torchvision.tv_tensors.Mask object
### Steps to reproduce the bug
Go to the website.
<img width="689" alt="image" src="https://github.com/huggingface/datasets/assets/4803565/ea1276d0-d69a-48cf-b9c2-cd61217815ef">
https://huggingface.co/docs/datasets/en/semantic_segmentation
### Expected behavior
Results, similar to `albumentation`. Or remove the torch vision part altogether. Or use `kornia` instead.
### Environment info
Irrelevant | false |
2,276,986,981 | https://api.github.com/repos/huggingface/datasets/issues/6864 | https://github.com/huggingface/datasets/issues/6864 | 6,864 | Dataset 'rewardsignal/reddit_writing_prompts' doesn't exist on the Hub | closed | 1 | 2024-05-03T06:03:30 | 2024-05-06T06:36:42 | 2024-05-06T06:36:41 | vinodrajendran001 | [] | ### 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 | false |
2,276,977,534 | https://api.github.com/repos/huggingface/datasets/issues/6863 | https://github.com/huggingface/datasets/issues/6863 | 6,863 | Revert temporary pin huggingface-hub < 0.23.0 | closed | 0 | 2024-05-03T05:53:55 | 2024-05-27T10:14:41 | 2024-05-27T10:14:41 | albertvillanova | [] | Revert temporary pin huggingface-hub < 0.23.0 introduced by
- #6861
once the following issue is fixed and released:
- huggingface/transformers#30618 | false |
2,276,763,745 | https://api.github.com/repos/huggingface/datasets/issues/6862 | https://github.com/huggingface/datasets/pull/6862 | 6,862 | Fix load_dataset for data_files with protocols other than HF | closed | 2 | 2024-05-03T01:43:47 | 2024-07-23T14:37:08 | 2024-07-23T14:30:09 | matstrand | [] | Fixes huggingface/datasets/issues/6598
I've added a new test case and a solution. Before applying the solution the test case was failing with the same error described in the linked issue.
MRE:
```
pip install "datasets[s3]"
python -c "from datasets import load_dataset; load_dataset('csv', data_files={'train': 's3://noaa-gsod-pds/2024/A5125600451.csv'})"
``` | true |
2,275,988,990 | https://api.github.com/repos/huggingface/datasets/issues/6861 | https://github.com/huggingface/datasets/pull/6861 | 6,861 | Fix CI by temporarily pinning huggingface-hub < 0.23.0 | closed | 2 | 2024-05-02T16:40:04 | 2024-05-02T16:59:42 | 2024-05-02T16:53:42 | albertvillanova | [] | As a hotfix for CI, temporarily pin `huggingface-hub` upper version
Fix #6860.
Revert once root cause is fixed, see:
- https://github.com/huggingface/transformers/issues/30618 | true |
2,275,537,137 | https://api.github.com/repos/huggingface/datasets/issues/6860 | https://github.com/huggingface/datasets/issues/6860 | 6,860 | CI fails after huggingface_hub-0.23.0 release: FutureWarning: "resume_download" | closed | 3 | 2024-05-02T13:24:17 | 2024-05-02T16:53:45 | 2024-05-02T16:53:45 | albertvillanova | [
"bug"
] | 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`.
``` | false |
2,274,996,774 | https://api.github.com/repos/huggingface/datasets/issues/6859 | https://github.com/huggingface/datasets/pull/6859 | 6,859 | Support folder-based datasets with large metadata.jsonl | open | 0 | 2024-05-02T09:07:26 | 2024-05-02T09:07:26 | null | gbenson | [] | I tried creating an `imagefolder` dataset with a 714MB `metadata.jsonl` but got the error below. This pull request fixes the problem by increasing the block size like the message suggests.
```
>>> from datasets import load_dataset
>>> dataset = load_dataset("imagefolder", data_dir="data-for-upload")
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/path/to/datasets/load.py", line 2609, in load_dataset
builder_instance.download_and_prepare(
...
File "/path/to/datasets/packaged_modules/folder_based_builder/folder_based_builder.py", line 245, in _read_metadata
return paj.read_json(f)
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: straddling object straddles two block boundaries (try to increase block size?)
``` | true |
2,274,917,185 | https://api.github.com/repos/huggingface/datasets/issues/6858 | https://github.com/huggingface/datasets/issues/6858 | 6,858 | Segmentation fault | closed | 2 | 2024-05-02T08:28:49 | 2024-05-03T08:43:21 | 2024-05-03T08:42:36 | scampion | [] | ### 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 | false |
2,274,849,730 | https://api.github.com/repos/huggingface/datasets/issues/6857 | https://github.com/huggingface/datasets/pull/6857 | 6,857 | Fix line-endings in tests on Windows | closed | 2 | 2024-05-02T07:49:15 | 2024-05-02T11:49:35 | 2024-05-02T11:43:00 | albertvillanova | [] | EDIT:
~~Fix test_delete_from_hub on Windows by passing explicit encoding.~~
Fix test_delete_from_hub and test_xgetsize_private by uploading the README file content directly (encoding the string), instead of writing a local file and uploading it.
Note that local files created on Windows will have "\r\n" line endings, instead of "\n".
These are no longer transformed to "\n" by the Hub.
Fix #6856. | true |
2,274,828,933 | https://api.github.com/repos/huggingface/datasets/issues/6856 | https://github.com/huggingface/datasets/issues/6856 | 6,856 | CI fails on Windows for test_delete_from_hub and test_xgetsize_private due to new-line character | closed | 1 | 2024-05-02T07:37:03 | 2024-05-02T11:43:01 | 2024-05-02T11:43:01 | albertvillanova | [
"bug"
] | 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',
),
]
``` | false |
2,274,777,812 | https://api.github.com/repos/huggingface/datasets/issues/6855 | https://github.com/huggingface/datasets/pull/6855 | 6,855 | Fix dataset name for community Hub script-datasets | closed | 6 | 2024-05-02T07:05:44 | 2024-05-03T15:58:00 | 2024-05-03T15:51:57 | albertvillanova | [] | Fix dataset name for community Hub script-datasets by passing explicit dataset_name to HubDatasetModuleFactoryWithScript.
Fix #6854.
CC: @Wauplin | true |
2,274,767,686 | https://api.github.com/repos/huggingface/datasets/issues/6854 | https://github.com/huggingface/datasets/issues/6854 | 6,854 | Wrong example of usage when config name is missing for community script-datasets | closed | 0 | 2024-05-02T06:59:39 | 2024-05-03T15:51:59 | 2024-05-03T15:51:58 | albertvillanova | [
"bug"
] | 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". | false |
2,272,570,000 | https://api.github.com/repos/huggingface/datasets/issues/6853 | https://github.com/huggingface/datasets/issues/6853 | 6,853 | Support soft links for load_datasets imagefolder | open | 0 | 2024-04-30T22:14:29 | 2024-04-30T22:14:29 | null | billytcl | [
"enhancement"
] | ### Feature request
Load_dataset from a folder of images doesn't seem to support soft links. It would be nice if it did, especially during methods development where image folders are being curated.
### Motivation
Images are coming from a complex variety of sources and we'd like to be able to soft link directly from the originating folders as opposed to copying. Having a copy of the file ensures that there may be issues with image versioning as well as having double the amount of required disk space.
### Your contribution
N/A | false |
2,272,465,011 | https://api.github.com/repos/huggingface/datasets/issues/6852 | https://github.com/huggingface/datasets/issues/6852 | 6,852 | Write token isn't working while pushing to datasets | closed | 0 | 2024-04-30T21:18:20 | 2024-05-02T00:55:46 | 2024-05-02T00:55:46 | realzai | [] | ### 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) | false |
2,270,965,503 | https://api.github.com/repos/huggingface/datasets/issues/6851 | https://github.com/huggingface/datasets/issues/6851 | 6,851 | load_dataset('emotion') UnicodeDecodeError | open | 2 | 2024-04-30T09:25:01 | 2024-09-05T03:11:04 | null | L-Block-C | [] | ### Describe the bug
**emotions = load_dataset('emotion')**
_UnicodeDecodeError: 'utf-8' codec can't decode byte 0x8b in position 1: invalid start byte_
### Steps to reproduce the bug
load_dataset('emotion')
### Expected behavior
succese
### Environment info
py3.10
transformers 4.41.0.dev0
datasets 2.19.0 | false |
2,269,500,624 | https://api.github.com/repos/huggingface/datasets/issues/6850 | https://github.com/huggingface/datasets/issues/6850 | 6,850 | Problem loading voxpopuli dataset | closed | 3 | 2024-04-29T16:46:51 | 2024-05-06T09:25:54 | 2024-05-06T09:25:54 | Namangarg110 | [] | ### 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 | false |
2,268,718,355 | https://api.github.com/repos/huggingface/datasets/issues/6849 | https://github.com/huggingface/datasets/pull/6849 | 6,849 | fix webdataset filename split | closed | 1 | 2024-04-29T10:57:18 | 2024-06-04T12:54:04 | 2024-06-04T12:54:04 | Bowser1704 | [] | use `os.path.splitext` to parse field_name.
fix filename which has dot. like:
```
a.b.jpeg
a.b.txt
``` | true |
2,268,622,609 | https://api.github.com/repos/huggingface/datasets/issues/6848 | https://github.com/huggingface/datasets/issues/6848 | 6,848 | Cant Downlaod Common Voice 17.0 hy-AM | open | 3 | 2024-04-29T10:06:02 | 2025-04-01T20:48:09 | null | mheryerznkanyan | [] | ### Describe the bug
I want to download Common Voice 17.0 hy-AM but it returns an error.
```
The version_base parameter is not specified.
Please specify a compatability version level, or None.
Will assume defaults for version 1.1
@hydra.main(config_name='hfds_config', config_path=None)
/usr/local/lib/python3.10/dist-packages/hydra/_internal/hydra.py:119: UserWarning: Future Hydra versions will no longer change working directory at job runtime by default.
See https://hydra.cc/docs/1.2/upgrades/1.1_to_1.2/changes_to_job_working_dir/ for more information.
ret = run_job(
/usr/local/lib/python3.10/dist-packages/datasets/load.py:1429: FutureWarning: The repository for mozilla-foundation/common_voice_17_0 contains custom code which must be executed to correctly load the dataset. You can inspect the repository content at https://hf.co/datasets/mozilla-foundation/common_voice_17_0
You can avoid this message in future by passing the argument `trust_remote_code=True`.
Passing `trust_remote_code=True` will be mandatory to load this dataset from the next major release of `datasets`.
warnings.warn(
Reading metadata...: 6180it [00:00, 133224.37it/s]les/s]
Generating train split: 0 examples [00:00, ? examples/s]
HuggingFace datasets failed due to some reason (stack trace below).
For certain datasets (eg: MCV), it may be necessary to login to the huggingface-cli (via `huggingface-cli login`).
Once logged in, you need to set `use_auth_token=True` when calling this script.
Traceback error for reference :
Traceback (most recent call last):
File "/usr/local/lib/python3.10/dist-packages/datasets/builder.py", line 1743, in _prepare_split_single
example = self.info.features.encode_example(record) if self.info.features is not None else record
File "/usr/local/lib/python3.10/dist-packages/datasets/features/features.py", line 1878, in encode_example
return encode_nested_example(self, example)
File "/usr/local/lib/python3.10/dist-packages/datasets/features/features.py", line 1243, in encode_nested_example
{
File "/usr/local/lib/python3.10/dist-packages/datasets/features/features.py", line 1243, in <dictcomp>
{
File "/usr/local/lib/python3.10/dist-packages/datasets/utils/py_utils.py", line 326, in zip_dict
yield key, tuple(d[key] for d in dicts)
File "/usr/local/lib/python3.10/dist-packages/datasets/utils/py_utils.py", line 326, in <genexpr>
yield key, tuple(d[key] for d in dicts)
KeyError: 'sentence_id'
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/workspace/nemo/scripts/speech_recognition/convert_hf_dataset_to_nemo.py", line 358, in main
dataset = load_dataset(
File "/usr/local/lib/python3.10/dist-packages/datasets/load.py", line 2549, in load_dataset
builder_instance.download_and_prepare(
File "/usr/local/lib/python3.10/dist-packages/datasets/builder.py", line 1005, in download_and_prepare
self._download_and_prepare(
File "/usr/local/lib/python3.10/dist-packages/datasets/builder.py", line 1767, in _download_and_prepare
super()._download_and_prepare(
File "/usr/local/lib/python3.10/dist-packages/datasets/builder.py", line 1100, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/usr/local/lib/python3.10/dist-packages/datasets/builder.py", line 1605, 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 1762, 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
```
### Steps to reproduce the bug
```
from datasets import load_dataset
cv_17 = load_dataset("mozilla-foundation/common_voice_17_0", "hy-AM")
```
### Expected behavior
It works fine with common_voice_16_1
### Environment info
- `datasets` version: 2.18.0
- Platform: Linux-5.15.0-1042-nvidia-x86_64-with-glibc2.35
- Python version: 3.11.6
- `huggingface_hub` version: 0.22.2
- PyArrow version: 15.0.2
- Pandas version: 2.2.2
- `fsspec` version: 2024.2.0 | false |
2,268,589,177 | https://api.github.com/repos/huggingface/datasets/issues/6847 | https://github.com/huggingface/datasets/issues/6847 | 6,847 | [Streaming] Only load requested splits without resolving files for the other splits | open | 2 | 2024-04-29T09:49:32 | 2024-05-07T04:43:59 | null | lhoestq | [] | e.g. [thangvip](https://huggingface.co/thangvip)/[cosmopedia_vi_math](https://huggingface.co/datasets/thangvip/cosmopedia_vi_math) has 300 splits and it takes a very long time to load only one split.
This is due to `load_dataset()` resolving the files of all the splits even if only one is needed.
In `dataset-viewer` the splits are loaded in different jobs so it results in 300 jobs that resolve 300 splits -> 90k calls to `/paths-info` | false |
2,267,352,120 | https://api.github.com/repos/huggingface/datasets/issues/6846 | https://github.com/huggingface/datasets/issues/6846 | 6,846 | Unimaginable super slow iteration | closed | 1 | 2024-04-28T05:24:14 | 2024-05-06T08:30:03 | 2024-05-06T08:30:03 | rangehow | [] | ### 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 datasetβ¦β¦οΌIs 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
- `fsspec` version: 2024.2.0 | false |
2,265,876,551 | https://api.github.com/repos/huggingface/datasets/issues/6845 | https://github.com/huggingface/datasets/issues/6845 | 6,845 | load_dataset doesn't support list column | open | 1 | 2024-04-26T14:11:44 | 2024-05-15T12:06:59 | null | arthasking123 | [] | ### Describe the bug
dataset = load_dataset("Doraemon-AI/text-to-neo4j-cypher-chinese")
got exception:
Generating train split: 1834 examples [00:00, 5227.98 examples/s]
Traceback (most recent call last):
File "/usr/local/lib/python3.11/dist-packages/datasets/builder.py", line 2011, in _prepare_split_single
writer.write_table(table)
File "/usr/local/lib/python3.11/dist-packages/datasets/arrow_writer.py", line 585, in write_table
pa_table = table_cast(pa_table, self._schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/dist-packages/datasets/table.py", line 2295, in table_cast
return cast_table_to_schema(table, schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/dist-packages/datasets/table.py", line 2254, in cast_table_to_schema
arrays = [cast_array_to_feature(table[name], feature) for name, feature in features.items()]
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/dist-packages/datasets/table.py", line 2254, in <listcomp>
arrays = [cast_array_to_feature(table[name], feature) for name, feature in features.items()]
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/dist-packages/datasets/table.py", line 1802, in wrapper
return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/dist-packages/datasets/table.py", line 1802, in <listcomp>
return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/dist-packages/datasets/table.py", line 2018, in cast_array_to_feature
casted_array_values = _c(array.values, feature[0])
^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/dist-packages/datasets/table.py", line 1804, in wrapper
return func(array, *args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/dist-packages/datasets/table.py", line 2115, in cast_array_to_feature
raise TypeError(f"Couldn't cast array of type\n{array.type}\nto\n{feature}")
TypeError: Couldn't cast array of type
struct<m.name: string, x.name: string, p.name: string, n.name: string, h.name: string, name: string, c: int64, collect(r.name): list<item: string>, q.name: string, rel.name: string, count(p): int64, 1: int64, p.location: string, max(n.name): null, mn.name: string, p.time: int64, min(q.name): string>
to
{'q.name': Value(dtype='string', id=None), 'mn.name': Value(dtype='string', id=None), 'x.name': Value(dtype='string', id=None), 'p.name': Value(dtype='string', id=None), 'n.name': Value(dtype='string', id=None), 'name': Value(dtype='string', id=None), 'm.name': Value(dtype='string', id=None), 'h.name': Value(dtype='string', id=None), 'count(p)': Value(dtype='int64', id=None), 'rel.name': Value(dtype='string', id=None), 'c': Value(dtype='int64', id=None), 'collect(r.name)': Sequence(feature=Value(dtype='string', id=None), length=-1, id=None), '1': Value(dtype='int64', id=None), 'p.location': Value(dtype='string', id=None), 'substring(h.name,0,5)': Value(dtype='string', id=None), 'p.time': Value(dtype='int64', id=None)}
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/home/ubuntu/llm/train-2.py", line 150, in <module>
dataset = load_dataset("Doraemon-AI/text-to-neo4j-cypher-chinese")
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/dist-packages/datasets/load.py", line 2609, in load_dataset
builder_instance.download_and_prepare(
File "/usr/local/lib/python3.11/dist-packages/datasets/builder.py", line 1027, in download_and_prepare
self._download_and_prepare(
File "/usr/local/lib/python3.11/dist-packages/datasets/builder.py", line 1122, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/usr/local/lib/python3.11/dist-packages/datasets/builder.py", line 1882, in _prepare_split
for job_id, done, content in self._prepare_split_single(
File "/usr/local/lib/python3.11/dist-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
### Steps to reproduce the bug
dataset = load_dataset("Doraemon-AI/text-to-neo4j-cypher-chinese")
### Expected behavior
no exception
### Environment info
python 3.11
datasets 2.19.0 | false |
2,265,870,546 | https://api.github.com/repos/huggingface/datasets/issues/6844 | https://github.com/huggingface/datasets/pull/6844 | 6,844 | Retry on HF Hub error when streaming | closed | 2 | 2024-04-26T14:09:04 | 2024-04-26T15:37:42 | 2024-04-26T15:37:42 | mariosasko | [] | Retry on the `huggingface_hub`'s `HfHubHTTPError` in the streaming mode.
Fix #6843 | true |
2,265,432,897 | https://api.github.com/repos/huggingface/datasets/issues/6843 | https://github.com/huggingface/datasets/issues/6843 | 6,843 | IterableDataset raises exception instead of retrying | open | 7 | 2024-04-26T10:00:43 | 2024-10-28T14:57:07 | null | bauwenst | [] | ### Describe the bug
In light of the recent server outages, I decided to look into whether I could somehow wrap my IterableDataset streams to retry rather than error out immediately. To my surprise, `datasets` [already supports retries](https://github.com/huggingface/datasets/issues/6172#issuecomment-1794876229). Since a commit by @lhoestq [last week](https://github.com/huggingface/datasets/commit/a188022dc43a76a119d90c03832d51d6e4a94d91), that code lives here:
https://github.com/huggingface/datasets/blob/fe2bea6a4b09b180bd23b88fe96dfd1a11191a4f/src/datasets/utils/file_utils.py#L1097C1-L1111C19
If GitHub code snippets still aren't working, here's a copy:
```python
def read_with_retries(*args, **kwargs):
disconnect_err = None
for retry in range(1, max_retries + 1):
try:
out = read(*args, **kwargs)
break
except (ClientError, TimeoutError) as err:
disconnect_err = err
logger.warning(
f"Got disconnected from remote data host. Retrying in {config.STREAMING_READ_RETRY_INTERVAL}sec [{retry}/{max_retries}]"
)
time.sleep(config.STREAMING_READ_RETRY_INTERVAL)
else:
raise ConnectionError("Server Disconnected") from disconnect_err
return out
```
With the latest outage, the end of my stack trace looked like this:
```
...
File "/miniconda3/envs/draft/lib/python3.11/site-packages/datasets/download/streaming_download_manager.py", line 342, in read_with_retries
out = read(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "/miniconda3/envs/draft/lib/python3.11/gzip.py", line 301, in read
return self._buffer.read(size)
^^^^^^^^^^^^^^^^^^^^^^^
File "/miniconda3/envs/draft/lib/python3.11/_compression.py", line 68, in readinto
data = self.read(len(byte_view))
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/miniconda3/envs/draft/lib/python3.11/gzip.py", line 505, in read
buf = self._fp.read(io.DEFAULT_BUFFER_SIZE)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/miniconda3/envs/draft/lib/python3.11/gzip.py", line 88, in read
return self.file.read(size)
^^^^^^^^^^^^^^^^^^^^
File "/miniconda3/envs/draft/lib/python3.11/site-packages/fsspec/spec.py", line 1856, in read
out = self.cache._fetch(self.loc, self.loc + length)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/miniconda3/envs/draft/lib/python3.11/site-packages/fsspec/caching.py", line 189, in _fetch
self.cache = self.fetcher(start, end) # new block replaces old
^^^^^^^^^^^^^^^^^^^^^^^^
File "/miniconda3/envs/draft/lib/python3.11/site-packages/huggingface_hub/hf_file_system.py", line 626, in _fetch_range
hf_raise_for_status(r)
File "/miniconda3/envs/draft/lib/python3.11/site-packages/huggingface_hub/utils/_errors.py", line 333, in hf_raise_for_status
raise HfHubHTTPError(str(e), response=response) from e
huggingface_hub.utils._errors.HfHubHTTPError: 504 Server Error: Gateway Time-out for url: https://huggingface.co/datasets/allenai/c4/resolve/1588ec454efa1a09f29cd18ddd04fe05fc8653a2/en/c4-train.00346-of-01024.json.gz
```
Indeed, the code for retries only catches `ClientError`s and `TimeoutError`s, and all other exceptions, *including HuggingFace's own custom HTTP error class*, **are not caught. Nothing is retried,** and instead the exception is propagated upwards immediately.
### Steps to reproduce the bug
Not sure how you reproduce this. Maybe unplug your Ethernet cable while streaming a dataset; the issue is pretty clear from the stack trace.
### Expected behavior
All HTTP errors while iterating a streamable dataset should cause retries.
### Environment info
Output from `datasets-cli env`:
- `datasets` version: 2.18.0
- Platform: Linux-4.18.0-513.24.1.el8_9.x86_64-x86_64-with-glibc2.28
- Python version: 3.11.7
- `huggingface_hub` version: 0.20.3
- PyArrow version: 15.0.0
- Pandas version: 2.2.0
- `fsspec` version: 2023.10.0 | false |
2,264,692,159 | https://api.github.com/repos/huggingface/datasets/issues/6842 | https://github.com/huggingface/datasets/issues/6842 | 6,842 | Datasets with files with colon : in filenames cannot be used on Windows | open | 0 | 2024-04-26T00:14:16 | 2024-04-26T00:14:16 | null | jacobjennings | [] | ### Describe the bug
Datasets (such as https://huggingface.co/datasets/MLCommons/peoples_speech) cannot be used on Windows due to the fact that windows does not allow colons ":" in filenames. These should be converted into alternative strings.
### Steps to reproduce the bug
1. Attempt to run load_dataset on MLCommons/peoples_speech
### Expected behavior
Does not crash during extraction
### Environment info
Windows 11, NTFS filesystem, Python 3.12
| false |
2,264,687,683 | https://api.github.com/repos/huggingface/datasets/issues/6841 | https://github.com/huggingface/datasets/issues/6841 | 6,841 | Unable to load wiki_auto_asset_turk from GEM | closed | 8 | 2024-04-26T00:08:47 | 2024-05-29T13:54:03 | 2024-04-26T16:12:29 | abhinavsethy | [] | ### 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%|β| 483801/483801 [00:03<00:00, 127164.26 examples/s
Generating validation split: 100%|β| 20000/20000 [00:00<00:00, 116052.94 example
Generating test_asset split: 100%|ββ| 359/359 [00:00<00:00, 76155.93 examples/s]
Generating test_turk split: 100%|βββ| 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 | false |
2,264,604,766 | https://api.github.com/repos/huggingface/datasets/issues/6840 | https://github.com/huggingface/datasets/issues/6840 | 6,840 | Delete uploaded files from the UI | open | 1 | 2024-04-25T22:33:57 | 2025-01-21T09:44:22 | null | saicharan2804 | [
"enhancement"
] | ### Feature request
Once a file is uploaded and the commit is made, I am unable to delete individual files without completely deleting the whole dataset via the website UI.
### Motivation
Would be a useful addition
### Your contribution
Would love to help out with some guidance | false |
2,263,761,062 | https://api.github.com/repos/huggingface/datasets/issues/6839 | https://github.com/huggingface/datasets/pull/6839 | 6,839 | Remove token arg from CLI examples | closed | 2 | 2024-04-25T14:36:58 | 2024-04-26T17:03:51 | 2024-04-26T16:57:40 | albertvillanova | [] | Remove token arg from CLI examples.
Fix #6838.
CC: @Wauplin | true |
2,263,674,843 | https://api.github.com/repos/huggingface/datasets/issues/6838 | https://github.com/huggingface/datasets/issues/6838 | 6,838 | Remove token arg from CLI examples | closed | 0 | 2024-04-25T14:00:38 | 2024-04-26T16:57:41 | 2024-04-26T16:57:41 | albertvillanova | [] | 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) | false |
2,263,273,983 | https://api.github.com/repos/huggingface/datasets/issues/6837 | https://github.com/huggingface/datasets/issues/6837 | 6,837 | Cannot use cached dataset without Internet connection (or when servers are down) | open | 6 | 2024-04-25T10:48:20 | 2025-01-25T16:36:41 | null | DionisMuzenitov | [] | ### Describe the bug
I want to be able to use cached dataset from HuggingFace even when I have no Internet connection (or when HuggingFace servers are down, or my company has network issues).
The problem why I can't use it:
`data_files` argument from `datasets.load_dataset()` function get it updates from the server before calculating hash for caching. As a result, when I run the same code with and without Internet I get different dataset configuration directory name.
### Steps to reproduce the bug
```
import datasets
c4_dataset = datasets.load_dataset(
path="allenai/c4",
data_files={"train": "en/c4-train.00000-of-01024.json.gz"},
split="train",
cache_dir="/datesets/cache",
download_mode="reuse_cache_if_exists",
token=False,
)
```
1. Run this code with the Internet.
2. Run the same code without the Internet.
### Expected behavior
When running without the Internet connection, the loader should be able to get dataset from cache
### Environment info
- `datasets` version: 2.19.0
- Platform: Windows-10-10.0.19044-SP0
- Python version: 3.10.13
- `huggingface_hub` version: 0.22.2
- PyArrow version: 16.0.0
- Pandas version: 1.5.3
- `fsspec` version: 2023.12.2 | false |
2,262,249,919 | https://api.github.com/repos/huggingface/datasets/issues/6836 | https://github.com/huggingface/datasets/issues/6836 | 6,836 | ExpectedMoreSplits error on load_dataset when upgrading to 2.19.0 | open | 3 | 2024-04-24T21:52:35 | 2024-05-14T04:08:19 | null | ebsmothers | [] | ### Describe the bug
Hi there, thanks for the great library! We have been using it a lot in torchtune and it's been a huge help for us.
Regarding the bug: the same call to `load_dataset` errors with `ExpectedMoreSplits` in 2.19.0 after working fine in 2.18.0. Full details given in the repro below.
### Steps to reproduce the bug
On 2.18.0, things work fine:
```
# First clear the locally cached dataset
rm -r ~/.cache/huggingface/datasets/lvwerra___stack-exchange-paired
pip install "datasets==2.18.0"
python3
>>> from datasets import load_dataset
>>> dataset = load_dataset('lvwerra/stack-exchange-paired', split='train', data_dir='data/rl')
```
On 2.19.0, they do not:
```
# First clear the locally cached dataset
rm -r ~/.cache/huggingface/datasets/lvwerra___stack-exchange-paired
pip install "datasets==2.19.0"
python3
>>> from datasets import load_dataset
>>> dataset = load_dataset('lvwerra/stack-exchange-paired', split='train', data_dir='data/rl')
```
The stack trace I see from the 2.19.0 version of load_dataset can be seen [here](https://gist.github.com/ebsmothers/f9b1f1949bee7030a8d7bb8a491550d2).
(Maybe unsurprising but) notably if I do not delete the cache first I am able to load the dataset successfully. So based on this I suspect the cause is somewhere in the download logic.
### Expected behavior
Download the dataset successfully :)
### Environment info
- `datasets` version: 2.19.0
- Platform: Linux-5.12.0-0_fbk16_zion_7661_geb00762ce6d2-x86_64-with-glibc2.34
- Python version: 3.11.9
- `huggingface_hub` version: 0.22.2
- PyArrow version: 16.0.0
- Pandas version: 2.2.2
- `fsspec` version: 2024.3.1 | false |
2,261,079,263 | https://api.github.com/repos/huggingface/datasets/issues/6835 | https://github.com/huggingface/datasets/pull/6835 | 6,835 | Support pyarrow LargeListType | closed | 3 | 2024-04-24T11:34:24 | 2024-08-12T14:43:47 | 2024-08-12T14:43:47 | Modexus | [] | Fixes #6834 | true |
2,261,078,104 | https://api.github.com/repos/huggingface/datasets/issues/6834 | https://github.com/huggingface/datasets/issues/6834 | 6,834 | largelisttype not supported (.from_polars()) | closed | 0 | 2024-04-24T11:33:43 | 2024-08-12T14:43:46 | 2024-08-12T14:43:46 | Modexus | [] | ### Describe the bug
The following code fails because LargeListType is not supported.
This is especially a problem for .from_polars since polars uses LargeListType.
### Steps to reproduce the bug
```python
import datasets
import polars as pl
df = pl.DataFrame({"list": [[]]})
datasets.Dataset.from_polars(df)
```
### Expected behavior
Convert LargeListType to list.
### Environment info
- `datasets` version: 2.19.1.dev0
- Platform: Linux-6.8.7-200.fc39.x86_64-x86_64-with-glibc2.38
- Python version: 3.12.2
- `huggingface_hub` version: 0.22.2
- PyArrow version: 16.0.0
- Pandas version: 2.1.4
- `fsspec` version: 2024.3.1 | false |
2,259,731,274 | https://api.github.com/repos/huggingface/datasets/issues/6833 | https://github.com/huggingface/datasets/issues/6833 | 6,833 | Super slow iteration with trivial custom transform | open | 7 | 2024-04-23T20:40:59 | 2024-10-08T15:41:18 | null | xslittlegrass | [] | ### Describe the bug
Dataset is 10X slower when applying trivial transforms:
```
import time
import numpy as np
from datasets import Dataset, Features, Array2D
a = np.zeros((800, 800))
a = np.stack([a] * 1000)
features = Features({"a": Array2D(shape=(800, 800), dtype="uint8")})
ds1 = Dataset.from_dict({"a": a}, features=features).with_format('numpy')
def transform(batch):
return batch
ds2 = ds1.with_transform(transform)
%time sum(1 for _ in ds1)
%time sum(1 for _ in ds2)
```
```
CPU times: user 472 ms, sys: 319 ms, total: 791 ms
Wall time: 794 ms
CPU times: user 9.32 s, sys: 443 ms, total: 9.76 s
Wall time: 9.78 s
```
In my real code I'm using set_transform to apply some post-processing on-the-fly for the 2d array, but it significantly slows down the dataset even if the transform itself is trivial.
Related issue: https://github.com/huggingface/datasets/issues/5841
### Steps to reproduce the bug
Use code in the description to reproduce.
### Expected behavior
Trivial custom transform in the example should not slowdown the dataset iteration.
### Environment info
- `datasets` version: 2.18.0
- Platform: Linux-5.15.0-79-generic-x86_64-with-glibc2.35
- Python version: 3.11.4
- `huggingface_hub` version: 0.20.2
- PyArrow version: 15.0.0
- Pandas version: 1.5.3
- `fsspec` version: 2023.12.2 | false |
2,258,761,447 | https://api.github.com/repos/huggingface/datasets/issues/6832 | https://github.com/huggingface/datasets/pull/6832 | 6,832 | Support downloading specific splits in `load_dataset` | open | 5 | 2024-04-23T12:32:27 | 2025-07-28T18:30:25 | null | mariosasko | [] | This PR builds on https://github.com/huggingface/datasets/pull/6639 to support downloading only the specified splits in `load_dataset`. For this to work, a builder's `_split_generators` need to be able to accept the requested splits (as a list) via a `splits` argument to avoid processing the non-requested ones. Also, the builder has to define a `_available_splits` method that lists all the possible `splits` values.
Close https://github.com/huggingface/datasets/issues/4101, close https://github.com/huggingface/datasets/issues/2538 (I'm probably missing some)
Should also make it possible to address https://github.com/huggingface/datasets/issues/6793 | true |
2,258,537,405 | https://api.github.com/repos/huggingface/datasets/issues/6831 | https://github.com/huggingface/datasets/pull/6831 | 6,831 | Add docs about the CLI | closed | 3 | 2024-04-23T10:41:03 | 2024-04-26T16:51:09 | 2024-04-25T10:44:10 | albertvillanova | [] | Add docs about the CLI.
Close #6830.
CC: @severo | true |
2,258,433,178 | https://api.github.com/repos/huggingface/datasets/issues/6830 | https://github.com/huggingface/datasets/issues/6830 | 6,830 | Add a doc page for the convert_to_parquet CLI | closed | 0 | 2024-04-23T09:49:04 | 2024-04-25T10:44:11 | 2024-04-25T10:44:11 | severo | [
"documentation"
] | Follow-up to https://github.com/huggingface/datasets/pull/6795. Useful for https://github.com/huggingface/dataset-viewer/issues/2742. cc @albertvillanova | false |
2,258,424,577 | https://api.github.com/repos/huggingface/datasets/issues/6829 | https://github.com/huggingface/datasets/issues/6829 | 6,829 | Load and save from/to disk no longer accept pathlib.Path | open | 0 | 2024-04-23T09:44:45 | 2024-04-23T09:44:46 | null | albertvillanova | [
"bug"
] | Reported by @vttrifonov at https://github.com/huggingface/datasets/pull/6704#issuecomment-2071168296:
> This change is breaking in
> https://github.com/huggingface/datasets/blob/f96e74d5c633cd5435dd526adb4a74631eb05c43/src/datasets/arrow_dataset.py#L1515
> when the input is `pathlib.Path`. The issue is that `url_to_fs` expects a `str` and cannot deal with `Path`. `get_fs_token_paths` converts to `str` so it is not a problem
This change was introduced in:
- #6704 | false |
2,258,420,421 | https://api.github.com/repos/huggingface/datasets/issues/6828 | https://github.com/huggingface/datasets/pull/6828 | 6,828 | Support PathLike input in save_to_disk / load_from_disk | open | 1 | 2024-04-23T09:42:38 | 2024-04-23T11:05:52 | null | lhoestq | [] | null | true |
2,254,011,833 | https://api.github.com/repos/huggingface/datasets/issues/6827 | https://github.com/huggingface/datasets/issues/6827 | 6,827 | Loading a remote dataset fails in the last release (v2.19.0) | open | 0 | 2024-04-19T21:11:58 | 2024-04-19T21:13:42 | null | zrthxn | [] | While loading a dataset with multiple splits I get an error saying `Couldn't find file at <URL>`
I am loading the dataset like so, nothing out of the ordinary.
This dataset needs a token to access it.
```
token="hf_myhftoken-sdhbdsjgkhbd"
load_dataset("speechcolab/gigaspeech", "test", cache_dir=f"gigaspeech/test", token=token)
```
I get the following error
Now you can see that the URL that it is trying to reach has the JSON object of the dataset split appended to the base URL. I think this may be due to a newly introduced issue.
I did not have this issue with the previous version of the datasets. Everything was fine for me yesterday and after the release 12 hours ago, this seems to have broken. Also, the dataset in question runs custom code and I checked and there have been no commits to the dataset on Huggingface in 6 months.
### Steps to reproduce the bug
Since this happened with one particular dataset for me, I am listing steps to use that dataset.
1. Open https://huggingface.co/datasets/speechcolab/gigaspeech and fill the form to get access.
2. Create a token on your huggingface account with read access.
3. Run the following line, substituing `<your_token_here>` with your token.
```
load_dataset("speechcolab/gigaspeech", "test", cache_dir=f"gigaspeech/test", token="<your_token_here>")
```
### Expected behavior
Be able to load the dataset in question.
### Environment info
datasets == 2.19.0
python == 3.10
kernel == Linux 6.1.58+ | false |
2,252,445,242 | https://api.github.com/repos/huggingface/datasets/issues/6826 | https://github.com/huggingface/datasets/pull/6826 | 6,826 | Set dev version | closed | 2 | 2024-04-19T08:51:42 | 2024-04-19T09:05:25 | 2024-04-19T08:52:14 | albertvillanova | [] | null | true |
2,252,404,599 | https://api.github.com/repos/huggingface/datasets/issues/6825 | https://github.com/huggingface/datasets/pull/6825 | 6,825 | Release: 2.19.0 | closed | 2 | 2024-04-19T08:29:02 | 2024-05-04T12:23:26 | 2024-04-19T08:44:57 | albertvillanova | [] | null | true |
2,251,076,197 | https://api.github.com/repos/huggingface/datasets/issues/6824 | https://github.com/huggingface/datasets/issues/6824 | 6,824 | Winogrande does not seem to be compatible with datasets version of 1.18.0 | closed | 2 | 2024-04-18T16:11:04 | 2024-04-19T09:53:15 | 2024-04-19T09:52:33 | spliew | [] | ### 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%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 2.06M/2.06M [00:00<00:00, 5.16MB/s]
Downloading data: 100%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 118k/118k [00:00<00:00, 360kB/s]
Downloading data: 100%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 85.9k/85.9k [00:00<00:00, 242kB/s]
Generating train split: 100%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 40398/40398 [00:00<00:00, 845491.12 examples/s]
Generating test split: 100%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 1767/1767 [00:00<00:00, 362501.11 examples/s]
Generating validation split: 100%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 1267/1267 [00:00<00:00, 318768.11 examples/s]```
### Environment info
datasets version: 1.18.0
| false |
2,250,775,569 | https://api.github.com/repos/huggingface/datasets/issues/6823 | https://github.com/huggingface/datasets/issues/6823 | 6,823 | Loading problems of Datasets with a single shard | open | 2 | 2024-04-18T13:59:00 | 2024-11-25T05:40:09 | null | andjoer | [] | ### Describe the bug
When saving a dataset on disk and it has a single shard it is not loaded as when it is saved in multiple shards. I installed the latest version of datasets via pip.
### Steps to reproduce the bug
The code below reproduces the behavior. All works well when the range of the loop is 10000 but it fails when it is 1000.
```
from PIL import Image
import numpy as np
from datasets import Dataset, DatasetDict, load_dataset
def load_image():
# Generate random noise image
noise = np.random.randint(0, 256, (256, 256, 3), dtype=np.uint8)
return Image.fromarray(noise)
def create_dataset():
input_images = []
output_images = []
text_prompts = []
for _ in range(10000): # this is the problematic parameter
input_images.append(load_image())
output_images.append(load_image())
text_prompts.append('test prompt')
data = {'input_image': input_images, 'output_image': output_images, 'text_prompt': text_prompts}
dataset = Dataset.from_dict(data)
return DatasetDict({'train': dataset})
dataset = create_dataset()
print('dataset before saving')
print(dataset)
print(dataset['train'].column_names)
dataset.save_to_disk('test_ds')
print('dataset after loading')
dataset_loaded = load_dataset('test_ds')
print(dataset_loaded)
print(dataset_loaded['train'].column_names)
```
The output for 1000 iterations is:
```
dataset before saving
DatasetDict({
train: Dataset({
features: ['input_image', 'output_image', 'text_prompt'],
num_rows: 1000
})
})
['input_image', 'output_image', 'text_prompt']
Saving the dataset (1/1 shards): 100%|β| 1000/1000 [00:00<00:00, 5156.00 example
dataset after loading
Generating train split: 1 examples [00:00, 230.52 examples/s]
DatasetDict({
train: Dataset({
features: ['_data_files', '_fingerprint', '_format_columns', '_format_kwargs', '_format_type', '_output_all_columns', '_split'],
num_rows: 1
})
})
['_data_files', '_fingerprint', '_format_columns', '_format_kwargs', '_format_type', '_output_all_columns', '_split']
```
For 10000 iteration (8 shards) it is correct:
```
dataset before saving
DatasetDict({
train: Dataset({
features: ['input_image', 'output_image', 'text_prompt'],
num_rows: 10000
})
})
['input_image', 'output_image', 'text_prompt']
Saving the dataset (8/8 shards): 100%|β| 10000/10000 [00:01<00:00, 6237.68 examp
dataset after loading
Generating train split: 10000 examples [00:00, 10773.16 examples/s]
DatasetDict({
train: Dataset({
features: ['input_image', 'output_image', 'text_prompt'],
num_rows: 10000
})
})
['input_image', 'output_image', 'text_prompt']
```
### Expected behavior
The procedure should work for a dataset with one shrad the same as for one with multiple shards
### Environment info
- `datasets` version: 2.18.0
- Platform: macOS-14.1-arm64-arm-64bit
- Python version: 3.11.8
- `huggingface_hub` version: 0.22.2
- PyArrow version: 15.0.2
- Pandas version: 2.2.2
- `fsspec` version: 2024.2.0
Edit: I looked in the source code of load.py in datasets. I should have used "load_from_disk" and it indeed works that way. But ideally load_dataset would have raisen an error the same way as if I call a path:
```
if Path(path, config.DATASET_STATE_JSON_FILENAME).exists():
raise ValueError(
"You are trying to load a dataset that was saved using `save_to_disk`. "
"Please use `load_from_disk` instead."
)
```
nevertheless I find it interesting that it works just well and without a warning if there are multiple shards. | false |
2,250,316,258 | https://api.github.com/repos/huggingface/datasets/issues/6822 | https://github.com/huggingface/datasets/pull/6822 | 6,822 | Fix parquet export infos | closed | 2 | 2024-04-18T10:21:41 | 2024-04-18T11:15:41 | 2024-04-18T11:09:13 | lhoestq | [] | Don't use the parquet export infos when USE_PARQUET_EXPORT is False.
Otherwise the `datasets-server` might reuse erroneous data when re-running a job
this follows https://github.com/huggingface/datasets/pull/6714 | true |
2,248,471,673 | https://api.github.com/repos/huggingface/datasets/issues/6820 | https://github.com/huggingface/datasets/pull/6820 | 6,820 | Allow deleting a subset/config from a no-script dataset | closed | 6 | 2024-04-17T14:41:12 | 2024-05-02T07:31:03 | 2024-04-30T09:44:24 | albertvillanova | [] | TODO:
- [x] Add docs
- [x] Delete token arg from CLI example
- See: #6839
Close #6810. | true |
2,248,043,797 | https://api.github.com/repos/huggingface/datasets/issues/6819 | https://github.com/huggingface/datasets/issues/6819 | 6,819 | Give more details in `DataFilesNotFoundError` when getting the config names | open | 0 | 2024-04-17T11:19:47 | 2024-04-17T11:19:47 | null | severo | [
"enhancement"
] | ### Feature request
After https://huggingface.co/datasets/cis-lmu/Glot500/commit/39060e01272ff228cc0ce1d31ae53789cacae8c3, the dataset viewer gives the following error:
```
{
"error": "Cannot get the config names for the dataset.",
"cause_exception": "DataFilesNotFoundError",
"cause_message": "No (supported) data files found in cis-lmu/Glot500",
"cause_traceback": [
"Traceback (most recent call last):\n",
" File \"/src/services/worker/src/worker/job_runners/dataset/config_names.py\", line 73, in compute_config_names_response\n config_names = get_dataset_config_names(\n",
" File \"/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py\", line 347, in get_dataset_config_names\n dataset_module = dataset_module_factory(\n",
" File \"/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py\", line 1873, in dataset_module_factory\n raise e1 from None\n",
" File \"/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py\", line 1854, in dataset_module_factory\n return HubDatasetModuleFactoryWithoutScript(\n",
" File \"/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py\", line 1245, in get_module\n module_name, default_builder_kwargs = infer_module_for_data_files(\n",
" File \"/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py\", line 595, in infer_module_for_data_files\n raise DataFilesNotFoundError(\"No (supported) data files found\" + (f\" in {path}\" if path else \"\"))\n",
"datasets.exceptions.DataFilesNotFoundError: No (supported) data files found in cis-lmu/Glot500\n"
]
}
```
because the deleted files were still listed in the README, see https://huggingface.co/datasets/cis-lmu/Glot500/discussions/4
Ideally, the error message would include the name of the first configuration with missing files, to help the user understand how to fix it. Here, it would tell that configuration `aze_Ethi` has no supported data files, instead of telling that the `cis-lmu/Glot500` *dataset* has no supported data files (which is not true).
### Motivation
Giving more detail in the error would help the Datasets Hub users to debug why the dataset viewer does not work.
### Your contribution
Not sure how to best fix this, as there are a lot of loops on the dataset configs in the traceback methods. "maybe" it would be easier to handle if the code was completely isolating each config. | false |
2,246,578,480 | https://api.github.com/repos/huggingface/datasets/issues/6817 | https://github.com/huggingface/datasets/pull/6817 | 6,817 | Support indexable objects in `Dataset.__getitem__` | closed | 2 | 2024-04-16T17:41:27 | 2024-04-16T18:27:44 | 2024-04-16T18:17:29 | mariosasko | [] | As discussed in https://github.com/huggingface/datasets/pull/6816, this is needed to support objects that implement `__index__` such as `np.int64` in `Dataset.__getitem__`. | true |
2,246,264,911 | https://api.github.com/repos/huggingface/datasets/issues/6816 | https://github.com/huggingface/datasets/pull/6816 | 6,816 | Improve typing of Dataset.search, matching definition | closed | 3 | 2024-04-16T14:53:39 | 2024-04-16T15:54:10 | 2024-04-16T15:54:10 | Dref360 | [] | Previously, the output of `score, indices = Dataset.search(...)` would be numpy arrays.
The definition in `SearchResult` is a `List[int]` so this PR now matched the expected type.
The previous behavior is a bit annoying as `Dataset.__getitem__` doesn't support `numpy.int64` which forced me to convert `indices` to int eg:
```python
score, indices = ds.search(...)
item = ds[int(indices[0])]
``` | true |
2,246,197,070 | https://api.github.com/repos/huggingface/datasets/issues/6815 | https://github.com/huggingface/datasets/pull/6815 | 6,815 | Remove `os.path.relpath` in `resolve_patterns` | closed | 2 | 2024-04-16T14:23:13 | 2024-04-16T16:06:48 | 2024-04-16T15:58:22 | mariosasko | [] | ... to save a few seconds when resolving repos with many data files. | true |
2,245,857,902 | https://api.github.com/repos/huggingface/datasets/issues/6814 | https://github.com/huggingface/datasets/issues/6814 | 6,814 | `map` with `num_proc` > 1 leads to OOM | open | 1 | 2024-04-16T11:56:03 | 2024-04-19T11:53:41 | null | bhavitvyamalik | [] | ### Describe the bug
When running `map` on parquet dataset loaded from local machine, the RAM usage increases linearly eventually leading to OOM. I was wondering if I should I save the `cache_file` after every n steps in order to prevent this?
### Steps to reproduce the bug
```
ds = load_dataset("parquet", data_files=dataset_path, split="train")
ds = ds.shard(num_shards=4, index=0)
ds = ds.cast_column("audio", datasets.features.Audio(sampling_rate=16_000))
ds = ds.map(prepare_dataset,
num_proc=32,
writer_batch_size=1000,
keep_in_memory=False,
desc="preprocess dataset")
```
```
def prepare_dataset(batch):
# load audio
sample = batch["audio"]
inputs = feature_extractor(sample["array"], sampling_rate=16000)
batch["input_values"] = inputs.input_values[0]
batch["input_length"] = len(sample["array"].squeeze())
return batch
```
### Expected behavior
It shouldn't run into OOM problem.
### Environment info
- `datasets` version: 2.18.0
- Platform: Linux-5.4.0-91-generic-x86_64-with-glibc2.17
- Python version: 3.8.19
- `huggingface_hub` version: 0.22.2
- PyArrow version: 15.0.2
- Pandas version: 2.0.3
- `fsspec` version: 2024.2.0 | false |
2,245,626,870 | https://api.github.com/repos/huggingface/datasets/issues/6813 | https://github.com/huggingface/datasets/pull/6813 | 6,813 | Add Dataset.take and Dataset.skip | closed | 2 | 2024-04-16T09:53:42 | 2024-04-16T14:12:14 | 2024-04-16T14:06:07 | lhoestq | [] | ...to be aligned with IterableDataset.take and IterableDataset.skip | true |
2,244,898,824 | https://api.github.com/repos/huggingface/datasets/issues/6812 | https://github.com/huggingface/datasets/pull/6812 | 6,812 | Run CI | closed | 1 | 2024-04-16T01:12:36 | 2024-04-16T01:14:16 | 2024-04-16T01:12:41 | charliermarsh | [] | null | true |
2,243,656,096 | https://api.github.com/repos/huggingface/datasets/issues/6811 | https://github.com/huggingface/datasets/pull/6811 | 6,811 | add allow_primitive_to_str and allow_decimal_to_str instead of allow_number_to_str | closed | 6 | 2024-04-15T13:14:38 | 2024-07-03T14:59:42 | 2024-04-16T17:03:17 | Modexus | [] | Fix #6805 | true |
2,242,968,745 | https://api.github.com/repos/huggingface/datasets/issues/6810 | https://github.com/huggingface/datasets/issues/6810 | 6,810 | Allow deleting a subset/config from a no-script dataset | closed | 3 | 2024-04-15T07:53:26 | 2025-01-11T18:40:40 | 2024-04-30T09:44:25 | albertvillanova | [
"enhancement"
] | As proposed by @BramVanroy, it would be neat to have this functionality through the API. | false |
2,242,956,297 | https://api.github.com/repos/huggingface/datasets/issues/6809 | https://github.com/huggingface/datasets/pull/6809 | 6,809 | Make convert_to_parquet CLI command create script branch | closed | 3 | 2024-04-15T07:47:26 | 2024-04-17T08:44:26 | 2024-04-17T08:38:18 | albertvillanova | [] | Make convert_to_parquet CLI command create a "script" branch and keep the script file on it.
This PR proposes the simplest UX approach: whenever `--revision` is not explicitly passed (i.e., when the script is in the main branch), try to create a "script" branch from the "main" branch; if the "script" branch exists already, then do nothing.
Follow-up of:
- #6795
Close #6808.
CC: @severo | true |
2,242,843,611 | https://api.github.com/repos/huggingface/datasets/issues/6808 | https://github.com/huggingface/datasets/issues/6808 | 6,808 | Make convert_to_parquet CLI command create script branch | closed | 0 | 2024-04-15T06:46:07 | 2024-04-17T08:38:19 | 2024-04-17T08:38:19 | albertvillanova | [
"enhancement"
] | As proposed by @severo, maybe we should add this functionality as well to the CLI command to convert a script-dataset to Parquet. See: https://github.com/huggingface/datasets/pull/6795#discussion_r1562819168
> When providing support, we sometimes suggest that users store their script in a script branch. What do you think of this alternative to deleting the files? | false |
2,239,435,074 | https://api.github.com/repos/huggingface/datasets/issues/6806 | https://github.com/huggingface/datasets/pull/6806 | 6,806 | Fix hf-internal-testing/dataset_with_script commit SHA in CI test | closed | 2 | 2024-04-12T08:47:50 | 2024-04-12T09:08:23 | 2024-04-12T09:02:12 | albertvillanova | [] | Fix test using latest commit SHA in hf-internal-testing/dataset_with_script dataset: https://huggingface.co/datasets/hf-internal-testing/dataset_with_script/commits/refs%2Fconvert%2Fparquet
Fix #6796. | true |
2,239,034,951 | https://api.github.com/repos/huggingface/datasets/issues/6805 | https://github.com/huggingface/datasets/issues/6805 | 6,805 | Batched mapping of existing string column casts boolean to string | closed | 7 | 2024-04-12T04:21:41 | 2024-07-03T15:00:07 | 2024-07-03T15:00:07 | starmpcc | [] | ### 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 | false |
2,238,035,124 | https://api.github.com/repos/huggingface/datasets/issues/6804 | https://github.com/huggingface/datasets/pull/6804 | 6,804 | Fix --repo-type order in cli upload docs | closed | 2 | 2024-04-11T15:39:09 | 2024-04-11T16:24:57 | 2024-04-11T16:18:47 | lhoestq | [] | null | true |
2,237,933,090 | https://api.github.com/repos/huggingface/datasets/issues/6803 | https://github.com/huggingface/datasets/pull/6803 | 6,803 | #6791 Improve type checking around FAISS | closed | 3 | 2024-04-11T14:54:30 | 2024-04-11T15:44:09 | 2024-04-11T15:38:04 | Dref360 | [] | Fixes #6791
Small PR to raise a better error when a dataset is not embedded properly. | true |
2,237,365,489 | https://api.github.com/repos/huggingface/datasets/issues/6802 | https://github.com/huggingface/datasets/pull/6802 | 6,802 | Fix typo in docs (upload CLI) | closed | 4 | 2024-04-11T10:05:05 | 2024-04-11T16:19:00 | 2024-04-11T13:19:43 | Wauplin | [] | Related to https://huggingface.slack.com/archives/C04RG8YRVB8/p1712643948574129 (interal)
Positional args must be placed before optional args.
Feel free to merge whenever it's ready. | true |
2,236,911,556 | https://api.github.com/repos/huggingface/datasets/issues/6801 | https://github.com/huggingface/datasets/issues/6801 | 6,801 | got fileNotFound | closed | 2 | 2024-04-11T04:57:41 | 2024-04-12T16:47:43 | 2024-04-12T16:47:43 | laoniandisko | [] | ### 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
| false |
2,236,431,288 | https://api.github.com/repos/huggingface/datasets/issues/6800 | https://github.com/huggingface/datasets/issues/6800 | 6,800 | High overhead when loading lots of subsets from the same dataset | open | 6 | 2024-04-10T21:08:57 | 2024-04-24T13:48:05 | null | loicmagne | [] | ### Describe the bug
I have a multilingual dataset that contains a lot of subsets. Each subset corresponds to a pair of languages, you can see here an example with 250 subsets: [https://hf.co/datasets/loicmagne/open-subtitles-250-bitext-mining](). As part of the MTEB benchmark, we may need to load all the subsets of the dataset. The dataset is relatively small and contains only ~45MB of data, but when I try to load every subset, it takes 15 minutes from the HF hub and 13 minutes from the cache
This issue https://github.com/huggingface/datasets/issues/5499 also referenced this overhead, but I'm wondering if there is anything I can do to speedup loading different subsets of the same dataset, both when loading from disk and from the HF hub? Currently each subset is stored in a jsonl file
### Steps to reproduce the bug
```
from datasets import load_dataset
for subset in ['ka-ml', 'br-sr', 'bg-br', 'kk-lv', 'br-sk', 'br-fi', 'eu-ze_zh', 'kk-nl', 'kk-vi', 'ja-kk', 'br-sv', 'kk-zh_cn', 'kk-ms', 'br-et', 'br-hu', 'eo-kk', 'br-tr', 'ko-tl', 'te-zh_tw', 'br-hr', 'br-nl', 'ka-si', 'br-cs', 'br-is', 'br-ro', 'br-de', 'et-kk', 'fr-hy', 'br-no', 'is-ko', 'br-da', 'br-en', 'eo-lt', 'is-ze_zh', 'eu-ko', 'br-it', 'br-id', 'eu-zh_cn', 'is-ja', 'br-sl', 'br-gl', 'br-pt_br', 'br-es', 'br-pt', 'is-th', 'fa-is', 'br-ca', 'eu-ka', 'is-zh_cn', 'eu-ur', 'id-kk', 'br-sq', 'eu-ja', 'uk-ur', 'is-zh_tw', 'ka-ko', 'eu-zh_tw', 'eu-th', 'eu-is', 'is-tl', 'br-eo', 'eo-ze_zh', 'eu-te', 'ar-kk', 'eo-lv', 'ko-ze_zh', 'ml-ze_zh', 'is-lt', 'br-fr', 'ko-te', 'kk-sl', 'eu-fa', 'eo-ko', 'ka-ze_en', 'eo-eu', 'ta-zh_tw', 'eu-lv', 'ko-lv', 'lt-tl', 'eu-si', 'hy-ru', 'ar-is', 'eu-lt', 'eu-tl', 'eu-uk', 'ka-ze_zh', 'si-ze_zh', 'el-is', 'bn-is', 'ko-ze_en', 'eo-si', 'cs-kk', 'is-uk', 'eu-ze_en', 'ta-ze_zh', 'is-pl', 'is-mk', 'eu-ta', 'ko-lt', 'is-lv', 'fa-ko', 'bn-ko', 'hi-is', 'bn-ze_zh', 'bn-eu', 'bn-ja', 'is-ml', 'eu-ru', 'ko-ta', 'is-vi', 'ja-tl', 'eu-mk', 'eu-he', 'ka-zh_tw', 'ka-zh_cn', 'si-tl', 'is-kk', 'eu-fi', 'fi-ko', 'is-ur', 'ka-th', 'ko-ur', 'eo-ja', 'he-is', 'is-tr', 'ka-ur', 'et-ko', 'eu-vi', 'is-sk', 'gl-is', 'fr-is', 'is-sq', 'hu-is', 'fr-kk', 'eu-sq', 'is-ru', 'ja-ka', 'fi-tl', 'ka-lv', 'fi-is', 'is-si', 'ar-ko', 'ko-sl', 'ar-eu', 'ko-si', 'bg-is', 'eu-hu', 'ko-sv', 'bn-hu', 'kk-ro', 'eu-hi', 'ka-ms', 'ko-th', 'ko-sr', 'ko-mk', 'fi-kk', 'ka-vi', 'eu-ml', 'ko-ml', 'de-ko', 'fa-ze_zh', 'eu-sk', 'is-sl', 'et-is', 'eo-is', 'is-sr', 'is-ze_en', 'kk-pt_br', 'hr-hy', 'kk-pl', 'ja-ta', 'is-ms', 'hi-ze_en', 'is-ro', 'ko-zh_cn', 'el-eu', 'ka-pl', 'ka-sq', 'eu-sl', 'fa-ka', 'ko-no', 'si-ze_en', 'ko-uk', 'ja-ze_zh', 'hu-ko', 'kk-no', 'eu-pl', 'is-pt_br', 'bn-lv', 'tl-zh_cn', 'is-nl', 'he-ko', 'ko-sq', 'ta-th', 'lt-ta', 'da-ko', 'ca-is', 'is-ta', 'bn-fi', 'ja-ml', 'lv-si', 'eu-sv', 'ja-te', 'bn-ur', 'bn-ca', 'bs-ko', 'bs-is', 'eu-sr', 'ko-vi', 'ko-zh_tw', 'et-tl', 'kk-tr', 'eo-vi', 'is-it', 'ja-ko', 'eo-et', 'id-is', 'bn-et', 'bs-eu', 'bn-lt', 'tl-uk', 'bn-zh_tw', 'da-eu', 'el-ko', 'no-tl', 'ko-sk', 'is-pt', 'hu-kk', 'si-zh_tw', 'si-te', 'ka-ru', 'lt-ml', 'af-ja', 'bg-eu', 'eo-th', 'cs-is', 'pl-ze_zh', 'el-kk', 'kk-sv', 'ka-nl', 'ko-pl', 'bg-ko', 'ka-pt_br', 'et-eu', 'tl-zh_tw', 'ka-pt', 'id-ko', 'fi-ze_zh', 'he-kk', 'ka-tr']:
load_dataset('loicmagne/open-subtitles-250-bitext-mining', subset)
```
### Expected behavior
Faster loading?
### Environment info
Copy-and-paste the text below in your GitHub issue.
- `datasets` version: 2.18.0
- Platform: Linux-6.5.0-27-generic-x86_64-with-glibc2.35
- Python version: 3.10.12
- `huggingface_hub` version: 0.22.2
- PyArrow version: 15.0.2
- Pandas version: 2.2.2
- `fsspec` version: 2023.5.0
| false |
2,236,124,531 | https://api.github.com/repos/huggingface/datasets/issues/6799 | https://github.com/huggingface/datasets/pull/6799 | 6,799 | fix `DatasetBuilder._split_generators` incomplete type annotation | closed | 3 | 2024-04-10T17:46:08 | 2024-04-11T15:41:06 | 2024-04-11T15:34:58 | JonasLoos | [] | solve #6798:
add missing `StreamingDownloadManager` type annotation to the `dl_manager` argument of the `DatasetBuilder._split_generators` function | true |
2,235,768,891 | https://api.github.com/repos/huggingface/datasets/issues/6798 | https://github.com/huggingface/datasets/issues/6798 | 6,798 | `DatasetBuilder._split_generators` incomplete type annotation | closed | 3 | 2024-04-10T14:38:50 | 2024-04-11T15:34:59 | 2024-04-11T15:34:59 | JonasLoos | [] | ### 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
/ | false |
2,234,890,097 | https://api.github.com/repos/huggingface/datasets/issues/6797 | https://github.com/huggingface/datasets/pull/6797 | 6,797 | Fix CI test_load_dataset_distributed_with_script | closed | 2 | 2024-04-10T06:57:48 | 2024-04-10T08:25:00 | 2024-04-10T08:18:01 | albertvillanova | [] | Fix #6796. | true |
2,234,887,618 | https://api.github.com/repos/huggingface/datasets/issues/6796 | https://github.com/huggingface/datasets/issues/6796 | 6,796 | CI is broken due to hf-internal-testing/dataset_with_script | closed | 4 | 2024-04-10T06:56:02 | 2024-04-12T09:02:13 | 2024-04-12T09:02:13 | albertvillanova | [
"bug"
] | CI is broken for test_load_dataset_distributed_with_script. See: https://github.com/huggingface/datasets/actions/runs/8614926216/job/23609378127
```
FAILED tests/test_load.py::test_load_dataset_distributed_with_script[None] - assert False
+ where False = all(<generator object test_load_dataset_distributed_with_script.<locals>.<genexpr> at 0x7f0c741de3b0>)
FAILED tests/test_load.py::test_load_dataset_distributed_with_script[force_redownload] - assert False
+ where False = all(<generator object test_load_dataset_distributed_with_script.<locals>.<genexpr> at 0x7f0be45f6ea0>)
``` | false |
2,233,618,719 | https://api.github.com/repos/huggingface/datasets/issues/6795 | https://github.com/huggingface/datasets/pull/6795 | 6,795 | Add CLI function to convert script-dataset to Parquet | closed | 3 | 2024-04-09T14:45:12 | 2024-04-17T08:41:23 | 2024-04-12T15:27:04 | albertvillanova | [] | Close #6690. | true |
2,233,202,088 | https://api.github.com/repos/huggingface/datasets/issues/6794 | https://github.com/huggingface/datasets/pull/6794 | 6,794 | Multithreaded downloads | closed | 4 | 2024-04-09T11:13:19 | 2024-04-15T21:24:13 | 2024-04-15T21:18:08 | lhoestq | [] | ...for faster dataset download when there are many many small files (e.g. imagefolder, audiofolder)
### Behcnmark
for example on [lhoestq/tmp-images-writer_batch_size](https://hf.co/datasets/lhoestq/tmp-images-writer_batch_size) (128 images)
| | duration of the download step in `load_dataset()` |
|--| ----------------------------------------------------------------------|
| Before | 58s |
| Now | 3s |
This should fix issues with the Dataset Viewer taking too much time to show up for imagefolder/audiofolder datasets.
### Implementation details
The main change is in the `DownloadManager`:
```diff
- download_func = partial(self._download, download_config=download_config)
+ download_func = partial(self._download_batched, download_config=download_config)
downloaded_path_or_paths = map_nested(
download_func,
url_or_urls,
map_tuple=True,
num_proc=download_config.num_proc,
desc="Downloading data files",
+ batched=True,
+ batch_size=-1,
)
```
and `_download_batched` is a multithreaded function.
I only enable multithreading if there are more than 16 files and files are small though, otherwise the progress bar that counts the number of downloaded files is not fluid (updating when a big batch of big files are done downloading). To do so I simply check if the first file is smaller than 20MB.
I also had to tweak `map_nested` to support batching. In particular it slices the data correctly if the user also enables multiprocessing. | true |
2,231,400,200 | https://api.github.com/repos/huggingface/datasets/issues/6793 | https://github.com/huggingface/datasets/issues/6793 | 6,793 | Loading just one particular split is not possible for imagenet-1k | open | 2 | 2024-04-08T14:39:14 | 2025-06-23T09:55:08 | null | PaulPSta | [] | ### Describe the bug
I'd expect the following code to download just the validation split but instead I get all data on my disk (train, test and validation splits)
`
from datasets import load_dataset
dataset = load_dataset("imagenet-1k", split="validation", trust_remote_code=True)
`
Is it expected to work like that?
### Steps to reproduce the bug
1. Install the required libraries (python, datasets, huggingface_hub)
2. Login using huggingface cli
2. Run the code in the description
### Expected behavior
Just a single (validation) split should be downloaded.
### Environment info
python: 3.12.2
datasets: 2.18.0
huggingface_hub: 0.22.2 | false |
2,231,318,682 | https://api.github.com/repos/huggingface/datasets/issues/6792 | https://github.com/huggingface/datasets/pull/6792 | 6,792 | Fix cache conflict in `_check_legacy_cache2` | closed | 2 | 2024-04-08T14:05:42 | 2024-04-09T11:34:08 | 2024-04-09T11:27:58 | lhoestq | [] | It was reloading from the wrong cache dir because of a bug in `_check_legacy_cache2`. This function should not trigger if there are config_kwars like `sample_by=`
fix https://github.com/huggingface/datasets/issues/6758 | true |
2,230,102,332 | https://api.github.com/repos/huggingface/datasets/issues/6791 | https://github.com/huggingface/datasets/issues/6791 | 6,791 | `add_faiss_index` raises ValueError: not enough values to unpack (expected 2, got 1) | closed | 3 | 2024-04-08T01:57:03 | 2024-04-11T15:38:05 | 2024-04-11T15:38:05 | NeuralFlux | [] | ### 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 | false |
2,229,915,236 | https://api.github.com/repos/huggingface/datasets/issues/6790 | https://github.com/huggingface/datasets/issues/6790 | 6,790 | PyArrow 'Memory mapping file failed: Cannot allocate memory' bug | open | 3 | 2024-04-07T19:25:39 | 2025-06-12T07:31:44 | null | lasuomela | [] | ### Describe the bug
Hello,
I've been struggling with a problem using Huggingface datasets caused by PyArrow memory allocation. I finally managed to solve it, and thought to document it since similar issues have been raised here before (https://github.com/huggingface/datasets/issues/5710, https://github.com/huggingface/datasets/issues/6176).
In my case, I was trying to load ~70k dataset files from disk using `datasets.load_from_disk(data_path)` (meaning 70k repeated calls to load_from_disk). This triggered an (uninformative) exception around 64k loaded files:
```
File "pyarrow/io.pxi", line 1053, in pyarrow.lib.memory_map
File "pyarrow/io.pxi", line 1000, in pyarrow.lib.MemoryMappedFile._open
File "pyarrow/error.pxi", line 154, in pyarrow.lib.pyarrow_internal_check_status
File "pyarrow/error.pxi", line 91, in pyarrow.lib.check_status
OSError: Memory mapping file failed: Cannot allocate memory
```
Despite system RAM usage being very low. After a lot of digging around, I discovered that my Ubuntu machine had a limit on the maximum number of memory mapped files in `/proc/sys/vm/max_map_count` set to 65530, which was causing my data loader to crash. Increasing the limit in the file (`echo <new_mmap_size> | sudo tee /proc/sys/vm/max_map_count`) made the issue go away.
While this isn't a bug as such in either Datasets or PyArrow, this behavior can be very confusing to users. Maybe this should be mentioned in documentation? I suspect the other issues raised here about memory mapping OOM errors could actually be consequence of system configuration.
Br,
Lauri
### Steps to reproduce the bug
```
import numpy as np
import pyarrow as pa
import tqdm
# Write some data to disk
arr = pa.array(np.arange(100))
schema = pa.schema([
pa.field('nums', arr.type)
])
with pa.OSFile('arraydata.arrow', 'wb') as sink:
with pa.ipc.new_file(sink, schema=schema) as writer:
batch = pa.record_batch([arr], schema=schema)
writer.write(batch)
# Number of times to open the memory map
nums = 70000
# Read the data back
arrays = [pa.memory_map('arraydata.arrow', 'r') for _ in tqdm.tqdm(range(nums))]
```
### Expected behavior
No errors.
### Environment info
datasets: 2.18.0
pyarrow: 15.0.0 | false |
2,229,527,001 | https://api.github.com/repos/huggingface/datasets/issues/6789 | https://github.com/huggingface/datasets/issues/6789 | 6,789 | Issue with map | open | 8 | 2024-04-07T02:52:06 | 2024-07-23T12:41:38 | null | Nsohko | [] | ### Describe the bug
Map has been taking extremely long to preprocess my data.
It seems to process 1000 examples (which it does really fast in about 10 seconds), then it hangs for a good 1-2 minutes, before it moves on to the next batch of 1000 examples.
It also keeps eating up my hard drive space for some reason by creating a file named tmp1335llua that is over 300GB.
Trying to set num_proc to be >1 also gives me the following error: NameError: name 'processor' is not defined
Please advise on how I could optimise this?
### Steps to reproduce the bug
In general, I have been using map as per normal. Here is a snippet of my code:
````
########################### DATASET LOADING AND PREP #########################
def load_custom_dataset(split):
ds = []
if split == 'train':
for dset in args.train_datasets:
ds.append(load_from_disk(dset))
if split == 'test':
for dset in args.test_datasets:
ds.append(load_from_disk(dset))
ds_to_return = concatenate_datasets(ds)
ds_to_return = ds_to_return.shuffle(seed=22)
return ds_to_return
def prepare_dataset(batch):
# load and (possibly) resample audio data to 16kHz
audio = batch["audio"]
# compute log-Mel input features from input audio array
batch["input_features"] = processor.feature_extractor(audio["array"], sampling_rate=audio["sampling_rate"]).input_features[0]
# compute input length of audio sample in seconds
batch["input_length"] = len(audio["array"]) / audio["sampling_rate"]
# optional pre-processing steps
transcription = batch["sentence"]
if do_lower_case:
transcription = transcription.lower()
if do_remove_punctuation:
transcription = normalizer(transcription).strip()
# encode target text to label ids
batch["labels"] = processor.tokenizer(transcription).input_ids
return batch
print('DATASET PREPARATION IN PROGRESS...')
# case 3: combine_and_shuffle is true, only train provided
# load train datasets
train_set = load_custom_dataset('train')
# split dataset
raw_dataset = DatasetDict()
raw_dataset = train_set.train_test_split(test_size = args.test_size, shuffle=True, seed=42)
raw_dataset = raw_dataset.cast_column("audio", Audio(sampling_rate=args.sampling_rate))
print("Before Map:")
print(raw_dataset)
raw_dataset = raw_dataset.map(prepare_dataset, num_proc=1)
print("After Map:")
print(raw_dataset)
````
### Expected behavior
Based on the speed at which map is processing examples, I would expect a 5-6 hours completion for all mapping
However, because it hangs every 1000 examples, I instead roughly estimate it would take about 40 hours!
Moreover, i cant even finish the map because it keeps exponentially eating up my hard drive space
### Environment info
- `datasets` version: 2.18.0
- Platform: Windows-10-10.0.22631-SP0
- Python version: 3.10.14
- `huggingface_hub` version: 0.22.2
- PyArrow version: 15.0.2
- Pandas version: 2.2.1
- `fsspec` version: 2024.2.0 | false |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.