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https://api.github.com/repos/huggingface/datasets/issues/6080 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6080/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6080/comments | https://api.github.com/repos/huggingface/datasets/issues/6080/events | https://github.com/huggingface/datasets/pull/6080 | 1,822,667,554 | PR_kwDODunzps5WdL4K | 6,080 | Remove README link to deprecated Colab notebook | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | rea... | 2023-07-26T15:27:49 | 2023-07-26T16:24:43 | 2023-07-26T16:14:34 | CONTRIBUTOR | null | false | {
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https://api.github.com/repos/huggingface/datasets/issues/6079 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6079/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6079/comments | https://api.github.com/repos/huggingface/datasets/issues/6079/events | https://github.com/huggingface/datasets/issues/6079 | 1,822,597,471 | I_kwDODunzps5soqFf | 6,079 | Iterating over DataLoader based on HF datasets is stuck forever | {
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"When the process starts to hang, can you interrupt it with CTRL + C and paste the error stack trace here? ",
"Thanks @mariosasko for your prompt response, here's the stack trace:\r\n\r\n```\r\nKeyboardInterrupt Traceback (most recent call last)\r\nCell In[12], line 4\r\n 2 t = time.t... | 2023-07-26T14:52:37 | 2023-07-26T19:14:16 | null | NONE | null | null | null | ### Describe the bug
I am using Amazon Sagemaker notebook (Amazon Linux 2) with python 3.10 based Conda environment.
I have a dataset in parquet format locally. When I try to iterate over it, the loader is stuck forever. Note that the same code is working for python 3.6 based conda environment seamlessly. What should be my next steps here?
### Steps to reproduce the bug
```
train_dataset = load_dataset(
"parquet", data_files = {'train': tr_data_path + '*.parquet'},
split = 'train',
collate_fn = streaming_data_collate_fn,
streaming = True
).with_format('torch')
train_dataloader = DataLoader(train_dataset, batch_size = 2, num_workers = 0)
t = time.time()
iter_ = 0
for batch in train_dataloader:
iter_ += 1
if iter_ == 1000:
break
print (time.time() - t)
```
### Expected behavior
The snippet should work normally and load the next batch of data.
### Environment info
datasets: '2.14.0'
pyarrow: '12.0.0'
torch: '2.0.0'
Python: 3.10.10 | packaged by conda-forge | (main, Mar 24 2023, 20:08:06) [GCC 11.3.0]
!uname -r
5.10.178-162.673.amzn2.x86_64 | {
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https://api.github.com/repos/huggingface/datasets/issues/6078 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6078/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6078/comments | https://api.github.com/repos/huggingface/datasets/issues/6078/events | https://github.com/huggingface/datasets/issues/6078 | 1,822,501,472 | I_kwDODunzps5soSpg | 6,078 | resume_download with streaming=True | {
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"Currently, it's not possible to efficiently resume streaming after an error. Eventually, we plan to support this for Parquet (see https://github.com/huggingface/datasets/issues/5380). ",
"Ok thank you for your answer"
] | 2023-07-26T14:08:22 | 2023-07-26T21:10:40 | null | NONE | null | null | null | ### Describe the bug
I used:
```
dataset = load_dataset(
"oscar-corpus/OSCAR-2201",
token=True,
language="fr",
streaming=True,
split="train"
)
```
Unfortunately, the server had a problem during the training process. I saved the step my training stopped at.
But how can I resume download from step 1_000_´000 without re-streaming all the first 1 million docs of the dataset?
`download_config=DownloadConfig(resume_download=True)` seems to not work with streaming=True.
### Steps to reproduce the bug
```
from datasets import load_dataset, DownloadConfig
dataset = load_dataset(
"oscar-corpus/OSCAR-2201",
token=True,
language="fr",
streaming=True, # optional
split="train",
download_config=DownloadConfig(resume_download=True)
)
# interupt the run and try to relaunch it => this restart from scratch
```
### Expected behavior
I would expect a parameter to start streaming from a given index in the dataset.
### Environment info
- `datasets` version: 2.14.0
- Platform: Linux-5.19.0-45-generic-x86_64-with-glibc2.29
- Python version: 3.8.10
- Huggingface_hub version: 0.15.1
- PyArrow version: 12.0.1
- Pandas version: 2.0.0 | {
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https://api.github.com/repos/huggingface/datasets/issues/6077 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6077/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6077/comments | https://api.github.com/repos/huggingface/datasets/issues/6077/events | https://github.com/huggingface/datasets/issues/6077 | 1,822,486,810 | I_kwDODunzps5soPEa | 6,077 | Mapping gets stuck at 99% | {
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"The `MAX_MAP_BATCH_SIZE = 1_000_000_000` hack is bad as it loads the entire dataset into RAM when performing `.map`. Instead, it's best to use `.iter(batch_size)` to iterate over the data batches and compute `mean` for each column. (`stddev` can be computed in another pass).\r\n\r\nAlso, these arrays are big, so i... | 2023-07-26T14:00:40 | 2023-07-26T18:29:10 | null | CONTRIBUTOR | null | null | null | ### Describe the bug
Hi !
I'm currently working with a large (~150GB) unnormalized dataset at work.
The dataset is available on a read-only filesystem internally, and I use a [loading script](https://huggingface.co/docs/datasets/dataset_script) to retreive it.
I want to normalize the features of the dataset, meaning I need to compute the mean and standard deviation metric for each feature of the entire dataset. I cannot load the entire dataset to RAM as it is too big, so following [this discussion on the huggingface discourse](https://discuss.huggingface.co/t/copy-columns-in-a-dataset-and-compute-statistics-for-a-column/22157) I am using a [map operation](https://huggingface.co/docs/datasets/v2.14.0/en/package_reference/main_classes#datasets.Dataset.map) to first compute the metrics and a second map operation to apply them on the dataset.
The problem lies in the second mapping, as it gets stuck at ~99%. By checking what the process does (using `htop` and `strace`) it seems to be doing a lot of I/O operations, and I'm not sure why.
Obviously, I could always normalize the dataset externally and then load it using a loading script. However, since the internal dataset is updated fairly frequently, using the library to perform normalization automatically would make it much easier for me.
### Steps to reproduce the bug
I'm able to reproduce the problem using the following scripts:
```python
# random_data.py
import datasets
import torch
_VERSION = "1.0.0"
class RandomDataset(datasets.GeneratorBasedBuilder):
def _info(self):
return datasets.DatasetInfo(
version=_VERSION,
supervised_keys=None,
features=datasets.Features(
{
"positions": datasets.Array2D(
shape=(30000, 3),
dtype="float32",
),
"normals": datasets.Array2D(
shape=(30000, 3),
dtype="float32",
),
"features": datasets.Array2D(
shape=(30000, 6),
dtype="float32",
),
"scalars": datasets.Sequence(
feature=datasets.Value("float32"),
length=20,
),
},
),
)
def _split_generators(self, dl_manager):
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN, # type: ignore
gen_kwargs={"nb_samples": 1000},
),
datasets.SplitGenerator(
name=datasets.Split.TEST, # type: ignore
gen_kwargs={"nb_samples": 100},
),
]
def _generate_examples(self, nb_samples: int):
for idx in range(nb_samples):
yield idx, {
"positions": torch.rand(30000, 3),
"normals": torch.rand(30000, 3),
"features": torch.rand(30000, 6),
"scalars": torch.rand(20),
}
```
```python
# main.py
import datasets
import torch
def compute_mean_std(
dataset: datasets.Dataset,
) -> dict[str, torch.Tensor]:
"""Compute the mean and standard deviation of each feature of the dataset.
Args:
dataset (`Dataset`): A huggingface dataset.
Returns:
dict: A dictionary containing the mean and standard deviation of each feature.
"""
result = {}
for key in dataset:
# extract data from dataset
data: torch.Tensor = dataset[key] # type: ignore
# reshape data, from (a, ..., b, c) -> (*, c)
data = data.reshape(-1, data.shape[-1])
# compute mean and std
mean = data.mean(dim=0) # (c)
std = data.std(dim=0) # (c)
# store in result
result[key] = torch.stack((mean, std))
return result
def apply_mean_std(
dataset: datasets.Dataset,
mean_std: datasets.Dataset,
) -> dict[str, torch.Tensor]:
"""Normalize the dataset using the mean and standard deviation of each feature.
Args:
dataset (`Dataset`): A huggingface dataset.
mean_std (`Dataset`): A huggingface dataset containing the mean and standard deviation of each feature.
Returns:
dict: A dictionary containing the normalized dataset.
"""
result = {}
for key in mean_std.column_names:
# extract data from dataset
data: torch.Tensor = dataset[key] # type: ignore
# extract mean and std from dict
mean = mean_std[key][0] # type: ignore
std = mean_std[key][1] # type: ignore
# normalize data
normalized_data = (data - mean) / std
result[key] = normalized_data
return result
# hack to force the map function to use the entire dataset
MAX_MAP_BATCH_SIZE = 1_000_000_000
# get dataset
ds = datasets.load_dataset(
path="random_data.py",
split="train",
).with_format("torch")
# compute mean/std of each feature
mean_std = ds.map(
desc="Computing mean/std", # type: ignore
remove_columns=ds.column_names, # type: ignore
function=compute_mean_std,
batch_size=MAX_MAP_BATCH_SIZE,
batched=True,
)
# normalize each feature of the dataset
ds_normalized = ds.map(
desc="Applying mean/std", # type: ignore
function=apply_mean_std,
batched=False,
fn_kwargs={
"mean_std": mean_std,
},
)
```
### Expected behavior
Using the previous scripts, the `ds_normalized` mapping completes in ~5 minutes, but any subsequent use of `ds_normalized` is really really slow, for example reapplying `apply_mean_std` to `ds_normalized` takes forever. This is very strange, I'm sure I must be missing something, but I would still expect this to be faster.
### Environment info
- `datasets` version: 2.13.1
- Platform: Linux-3.10.0-1160.66.1.el7.x86_64-x86_64-with-glibc2.17
- Python version: 3.10.12
- Huggingface_hub version: 0.15.1
- PyArrow version: 12.0.0
- Pandas version: 2.0.2 | {
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https://api.github.com/repos/huggingface/datasets/issues/6076 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6076/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6076/comments | https://api.github.com/repos/huggingface/datasets/issues/6076/events | https://github.com/huggingface/datasets/pull/6076 | 1,822,345,597 | PR_kwDODunzps5WcGVR | 6,076 | No gzip encoding from github | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6076). All of your documentation changes will be reflected on that endpoint.",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchma... | 2023-07-26T12:46:07 | 2023-07-26T14:01:21 | null | MEMBER | null | false | {
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} | Don't accept gzip encoding from github, otherwise some files are not streamable + seekable.
fix https://huggingface.co/datasets/code_x_glue_cc_code_to_code_trans/discussions/2#64c0e0c1a04a514ba6303e84
and making sure https://github.com/huggingface/datasets/issues/2918 works as well | {
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https://api.github.com/repos/huggingface/datasets/issues/6075 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6075/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6075/comments | https://api.github.com/repos/huggingface/datasets/issues/6075/events | https://github.com/huggingface/datasets/issues/6075 | 1,822,341,398 | I_kwDODunzps5snrkW | 6,075 | Error loading music files using `load_dataset` | {
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"This code behaves as expected on my local machine or in Colab. Which version of `soundfile` do you have installed? MP3 requires `soundfile>=0.12.1`.",
"I upgraded the `soundfile` and it's working now! \r\nThanks @mariosasko for the help!"
] | 2023-07-26T12:44:05 | 2023-07-26T13:08:08 | 2023-07-26T13:08:08 | NONE | null | null | null | ### Describe the bug
I tried to load a music file using `datasets.load_dataset()` from the repository - https://huggingface.co/datasets/susnato/pop2piano_real_music_test
I got the following error -
```
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/susnato/anaconda3/envs/p2p/lib/python3.9/site-packages/datasets/arrow_dataset.py", line 2803, in __getitem__
return self._getitem(key)
File "/home/susnato/anaconda3/envs/p2p/lib/python3.9/site-packages/datasets/arrow_dataset.py", line 2788, in _getitem
formatted_output = format_table(
File "/home/susnato/anaconda3/envs/p2p/lib/python3.9/site-packages/datasets/formatting/formatting.py", line 629, in format_table
return formatter(pa_table, query_type=query_type)
File "/home/susnato/anaconda3/envs/p2p/lib/python3.9/site-packages/datasets/formatting/formatting.py", line 398, in __call__
return self.format_column(pa_table)
File "/home/susnato/anaconda3/envs/p2p/lib/python3.9/site-packages/datasets/formatting/formatting.py", line 442, in format_column
column = self.python_features_decoder.decode_column(column, pa_table.column_names[0])
File "/home/susnato/anaconda3/envs/p2p/lib/python3.9/site-packages/datasets/formatting/formatting.py", line 218, in decode_column
return self.features.decode_column(column, column_name) if self.features else column
File "/home/susnato/anaconda3/envs/p2p/lib/python3.9/site-packages/datasets/features/features.py", line 1924, in decode_column
[decode_nested_example(self[column_name], value) if value is not None else None for value in column]
File "/home/susnato/anaconda3/envs/p2p/lib/python3.9/site-packages/datasets/features/features.py", line 1924, in <listcomp>
[decode_nested_example(self[column_name], value) if value is not None else None for value in column]
File "/home/susnato/anaconda3/envs/p2p/lib/python3.9/site-packages/datasets/features/features.py", line 1325, in decode_nested_example
return schema.decode_example(obj, token_per_repo_id=token_per_repo_id)
File "/home/susnato/anaconda3/envs/p2p/lib/python3.9/site-packages/datasets/features/audio.py", line 184, in decode_example
array, sampling_rate = sf.read(f)
File "/home/susnato/anaconda3/envs/p2p/lib/python3.9/site-packages/soundfile.py", line 372, in read
with SoundFile(file, 'r', samplerate, channels,
File "/home/susnato/anaconda3/envs/p2p/lib/python3.9/site-packages/soundfile.py", line 740, in __init__
self._file = self._open(file, mode_int, closefd)
File "/home/susnato/anaconda3/envs/p2p/lib/python3.9/site-packages/soundfile.py", line 1264, in _open
_error_check(_snd.sf_error(file_ptr),
File "/home/susnato/anaconda3/envs/p2p/lib/python3.9/site-packages/soundfile.py", line 1455, in _error_check
raise RuntimeError(prefix + _ffi.string(err_str).decode('utf-8', 'replace'))
RuntimeError: Error opening <_io.BufferedReader name='/home/susnato/.cache/huggingface/datasets/downloads/d2b09cb974b967b13f91553297c40c0f02f3c0d4c8356350743598ff48d6f29e'>: Format not recognised.
```
### Steps to reproduce the bug
Code to reproduce the error -
```python
from datasets import load_dataset
ds = load_dataset("susnato/pop2piano_real_music_test", split="test")
print(ds[0])
```
### Expected behavior
I should be able to read the music file without any error.
### Environment info
- `datasets` version: 2.14.0
- Platform: Linux-5.19.0-50-generic-x86_64-with-glibc2.35
- Python version: 3.9.16
- Huggingface_hub version: 0.15.1
- PyArrow version: 11.0.0
- Pandas version: 1.5.3
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https://api.github.com/repos/huggingface/datasets/issues/6074 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6074/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6074/comments | https://api.github.com/repos/huggingface/datasets/issues/6074/events | https://github.com/huggingface/datasets/pull/6074 | 1,822,299,128 | PR_kwDODunzps5Wb8O_ | 6,074 | Misc doc improvements | {
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"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_a... | 2023-07-26T12:20:54 | 2023-07-26T14:42:56 | null | CONTRIBUTOR | null | false | {
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} | Removes the warning about requiring to write a dataset loading script to define multiple configurations, as the README YAML can be used instead (for simple cases). Also, deletes the section about using the `BatchSampler` in `torch<=1.12.1` to speed up loading, as `torch 1.12.1` is over a year old (and `torch 2.0` has been out for a while). | {
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https://api.github.com/repos/huggingface/datasets/issues/6073 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6073/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6073/comments | https://api.github.com/repos/huggingface/datasets/issues/6073/events | https://github.com/huggingface/datasets/issues/6073 | 1,822,167,804 | I_kwDODunzps5snBL8 | 6,073 | version2.3.2 load_dataset()data_files can't include .xxxx in path | {
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"Version 2.3.2 is over one year old, so please use the latest release (2.14.0) to get the expected behavior. Version 2.3.2 does not contain some fixes we made to fix resolving hidden files/directories (starting with a dot)."
] | 2023-07-26T11:09:31 | 2023-07-26T12:34:45 | null | NONE | null | null | null | ### Describe the bug
First, I cd workdir.
Then, I just use load_dataset("json", data_file={"train":"/a/b/c/.d/train/train.json", "test":"/a/b/c/.d/train/test.json"})
that couldn't work and
<FileNotFoundError: Unable to find
'/a/b/c/.d/train/train.jsonl' at
/a/b/c/.d/>
And I debug, it is fine in version2.1.2
So there maybe a bug in path join.
Here is the whole bug report:
/x/datasets/loa │
│ d.py:1656 in load_dataset │
│ │
│ 1653 │ ignore_verifications = ignore_verifications or save_infos │
│ 1654 │ │
│ 1655 │ # Create a dataset builder │
│ ❱ 1656 │ builder_instance = load_dataset_builder( │
│ 1657 │ │ path=path, │
│ 1658 │ │ name=name, │
│ 1659 │ │ data_dir=data_dir, │
│ │
│ x/datasets/loa │
│ d.py:1439 in load_dataset_builder │
│ │
│ 1436 │ if use_auth_token is not None: │
│ 1437 │ │ download_config = download_config.copy() if download_config e │
│ 1438 │ │ download_config.use_auth_token = use_auth_token │
│ ❱ 1439 │ dataset_module = dataset_module_factory( │
│ 1440 │ │ path, │
│ 1441 │ │ revision=revision, │
│ 1442 │ │ download_config=download_config, │
│ │
│ x/datasets/loa │
│ d.py:1097 in dataset_module_factory │
│ │
│ 1094 │ │
│ 1095 │ # Try packaged │
│ 1096 │ if path in _PACKAGED_DATASETS_MODULES: │
│ ❱ 1097 │ │ return PackagedDatasetModuleFactory( │
│ 1098 │ │ │ path, │
│ 1099 │ │ │ data_dir=data_dir, │
│ 1100 │ │ │ data_files=data_files, │
│ │
│x/datasets/loa │
│ d.py:743 in get_module │
│ │
│ 740 │ │ │ if self.data_dir is not None │
│ 741 │ │ │ else get_patterns_locally(str(Path().resolve())) │
│ 742 │ │ ) │
│ ❱ 743 │ │ data_files = DataFilesDict.from_local_or_remote( │
│ 744 │ │ │ patterns, │
│ 745 │ │ │ use_auth_token=self.download_config.use_auth_token, │
│ 746 │ │ │ base_path=str(Path(self.data_dir).resolve()) if self.data │
│ │
│ x/datasets/dat │
│ a_files.py:590 in from_local_or_remote │
│ │
│ 587 │ │ out = cls() │
│ 588 │ │ for key, patterns_for_key in patterns.items(): │
│ 589 │ │ │ out[key] = ( │
│ ❱ 590 │ │ │ │ DataFilesList.from_local_or_remote( │
│ 591 │ │ │ │ │ patterns_for_key, │
│ 592 │ │ │ │ │ base_path=base_path, │
│ 593 │ │ │ │ │ allowed_extensions=allowed_extensions, │
│ │
│ /x/datasets/dat │
│ a_files.py:558 in from_local_or_remote │
│ │
│ 555 │ │ use_auth_token: Optional[Union[bool, str]] = None, │
│ 556 │ ) -> "DataFilesList": │
│ 557 │ │ base_path = base_path if base_path is not None else str(Path() │
│ ❱ 558 │ │ data_files = resolve_patterns_locally_or_by_urls(base_path, pa │
│ 559 │ │ origin_metadata = _get_origin_metadata_locally_or_by_urls(data │
│ 560 │ │ return cls(data_files, origin_metadata) │
│ 561 │
│ │
│ /x/datasets/dat │
│ a_files.py:195 in resolve_patterns_locally_or_by_urls │
│ │
│ 192 │ │ if is_remote_url(pattern): │
│ 193 │ │ │ data_files.append(Url(pattern)) │
│ 194 │ │ else: │
│ ❱ 195 │ │ │ for path in _resolve_single_pattern_locally(base_path, pat │
│ 196 │ │ │ │ data_files.append(path) │
│ 197 │ │
│ 198 │ if not data_files: │
│ │
│ /x/datasets/dat │
│ a_files.py:145 in _resolve_single_pattern_locally │
│ │
│ 142 │ │ error_msg = f"Unable to find '{pattern}' at {Path(base_path).r │
│ 143 │ │ if allowed_extensions is not None: │
│ 144 │ │ │ error_msg += f" with any supported extension {list(allowed │
│ ❱ 145 │ │ raise FileNotFoundError(error_msg) │
│ 146 │ return sorted(out) │
│ 147
### Steps to reproduce the bug
1. Version=2.3.2
2. In shell, cd workdir.(cd /a/b/c/.d/)
3. load_dataset("json", data_file={"train":"/a/b/c/.d/train/train.json", "test":"/a/b/c/.d/train/test.json"})
### Expected behavior
fix it please~
### Environment info
2.3.2 | {
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https://api.github.com/repos/huggingface/datasets/issues/6072 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6072/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6072/comments | https://api.github.com/repos/huggingface/datasets/issues/6072/events | https://github.com/huggingface/datasets/pull/6072 | 1,822,123,560 | PR_kwDODunzps5WbWFN | 6,072 | Fix fsspec storage_options from load_dataset | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6072). All of your documentation changes will be reflected on that endpoint.",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchma... | 2023-07-26T10:44:23 | 2023-07-26T19:26:48 | null | MEMBER | null | false | {
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https://api.github.com/repos/huggingface/datasets/issues/6071 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6071/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6071/comments | https://api.github.com/repos/huggingface/datasets/issues/6071/events | https://github.com/huggingface/datasets/issues/6071 | 1,821,990,749 | I_kwDODunzps5smV9d | 6,071 | storage_options provided to load_dataset not fully piping through since datasets 2.14.0 | {
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"Hi ! Thanks for reporting, I opened a PR to fix this\r\n\r\nWhat filesystem are you using ?",
"Hi @lhoestq ! Thank you so much 🙌 \r\n\r\nIt's a bit of a custom setup, but in practice I am using a [pyarrow.fs.S3FileSystem](https://arrow.apache.org/docs/python/generated/pyarrow.fs.S3FileSystem.html) (wrapped in a... | 2023-07-26T09:37:20 | 2023-07-26T11:04:35 | null | NONE | null | null | null | ### Describe the bug
Since the latest release of `datasets` (`2.14.0`), custom filesystem `storage_options` passed to `load_dataset()` do not seem to propagate through all the way - leading to problems if loading data files that need those options to be set.
I think this is because of the new `_prepare_path_and_storage_options()` (https://github.com/huggingface/datasets/pull/6028), which returns the right `storage_options` to use given a path and a `DownloadConfig` - but which might not be taking into account the extra `storage_options` explicitly provided e.g. through `load_dataset()`
### Steps to reproduce the bug
```python
import fsspec
import pandas as pd
import datasets
# Generate mock parquet file
data_files = "demo.parquet"
pd.DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]}).to_parquet(data_files)
_storage_options = {"x": 1, "y": 2}
fs = fsspec.filesystem("file", **_storage_options)
dataset = datasets.load_dataset(
"parquet",
data_files=data_files,
storage_options=fs.storage_options
)
```
Looking at the `storage_options` resolved here:
https://github.com/huggingface/datasets/blob/b0177910b32712f28d147879395e511207e39958/src/datasets/data_files.py#L331
they end up being `{}`, instead of propagating through the `storage_options` that were provided to `load_dataset` (`fs.storage_options`). As these then get used for the filesystem operation a few lines below
https://github.com/huggingface/datasets/blob/b0177910b32712f28d147879395e511207e39958/src/datasets/data_files.py#L339
the call will fail if the user-provided `storage_options` were needed.
---
A temporary workaround that seemed to work locally to bypass the problem was to bundle a duplicate of the `storage_options` into the `download_config`, so that they make their way all the way to `_prepare_path_and_storage_options()` and get extracted correctly:
```python
dataset = datasets.load_dataset(
"parquet",
data_files=data_files,
storage_options=fs.storage_options,
download_config=datasets.DownloadConfig(storage_options={fs.protocol: fs.storage_options}),
)
```
### Expected behavior
`storage_options` provided to `load_dataset` take effect in all backend filesystem operations.
### Environment info
datasets==2.14.0 | {
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https://api.github.com/repos/huggingface/datasets/issues/6070 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6070/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6070/comments | https://api.github.com/repos/huggingface/datasets/issues/6070/events | https://github.com/huggingface/datasets/pull/6070 | 1,820,836,330 | PR_kwDODunzps5WXDLc | 6,070 | Fix Quickstart notebook link | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | rea... | 2023-07-25T17:48:37 | 2023-07-25T18:19:01 | 2023-07-25T18:10:16 | CONTRIBUTOR | null | false | {
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https://api.github.com/repos/huggingface/datasets/issues/6069 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6069/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6069/comments | https://api.github.com/repos/huggingface/datasets/issues/6069/events | https://github.com/huggingface/datasets/issues/6069 | 1,820,831,535 | I_kwDODunzps5sh68v | 6,069 | KeyError: dataset has no key "image" | {
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"You can list the dataset's columns with `ds.column_names` before `.map` to check whether the dataset has an `image` column. If it doesn't, then this is a bug. Otherwise, please paste the line with the `.map` call.\r\n\r\n\r\n",
"This is the piece of code I am running:\r\n```\r\ndata_transforms = utils.get_data_a... | 2023-07-25T17:45:50 | 2023-07-26T17:33:49 | null | NONE | null | null | null | ### Describe the bug
I've loaded a local image dataset with:
`ds = laod_dataset("imagefolder", data_dir=path-to-data)`
And defined a transform to process the data, following the Datasets docs.
However, I get a keyError error, indicating there's no "image" key in my dataset. When I printed out the example_batch sent to the transformation function, it shows only the labels are being sent to the function.
For some reason, the images are not in the example batches.
### Steps to reproduce the bug
I'm using the latest stable version of datasets
### Expected behavior
I expect the example_batches to contain both images and labels
### Environment info
I'm using the latest stable version of datasets | {
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https://api.github.com/repos/huggingface/datasets/issues/6068 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6068/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6068/comments | https://api.github.com/repos/huggingface/datasets/issues/6068/events | https://github.com/huggingface/datasets/pull/6068 | 1,820,106,952 | PR_kwDODunzps5WUkZi | 6,068 | fix tqdm lock deletion | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | rea... | 2023-07-25T11:17:25 | 2023-07-25T15:29:39 | 2023-07-25T15:17:50 | MEMBER | null | false | {
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} | related to https://github.com/huggingface/datasets/issues/6066 | {
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