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https://api.github.com/repos/huggingface/datasets/issues/5004 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5004/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5004/comments | https://api.github.com/repos/huggingface/datasets/issues/5004/events | https://github.com/huggingface/datasets/pull/5004 | 1,380,860,606 | PR_kwDODunzps4_WQck | 5,004 | Remove license tag file and validation | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-09-21T12:35:14Z | 2022-09-22T11:47:41Z | 2022-09-22T11:45:46Z | MEMBER | null | null | null | As requested, we are removing the validation of the licenses from `datasets` because this is done on the Hub.
Fix #4994.
Related to:
- #4926, which is removing all the validation from `datasets` | {
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https://api.github.com/repos/huggingface/datasets/issues/6475 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6475/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6475/comments | https://api.github.com/repos/huggingface/datasets/issues/6475/events | https://github.com/huggingface/datasets/issues/6475 | 2,027,373,734 | I_kwDODunzps5410Sm | 6,475 | laion2B-en failed to load on Windows with PrefetchVirtualMemory failed | {
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"~~You will see this error if the cache dir filepath contains relative `..` paths. Use `os.path.realpath(_CACHE_DIR)` before passing it to the `load_dataset` function.~~",
"This is a real issue and not related to paths.",
"Based on the StackOverflow answer, this causes the error to go away:\r\n```diff\r\ndiff -... | 2023-12-06T00:07:34Z | 2023-12-06T23:26:23Z | null | NONE | null | null | {
"completed": 0,
"percent_completed": 0,
"total": 0
} | ### Describe the bug
I have downloaded laion2B-en, and I'm receiving the following error trying to load it:
```
Resolving data files: 100%|ββββββββββ| 128/128 [00:00<00:00, 1173.79it/s]
Traceback (most recent call last):
File "D:\Art-Workspace\src\artworkspace\tokeneval\compute_frequencies.py", line 31, in <module>
count = compute_frequencies()
^^^^^^^^^^^^^^^^^^^^^
File "D:\Art-Workspace\src\artworkspace\tokeneval\compute_frequencies.py", line 17, in compute_frequencies
laion2b_dataset = load_dataset("laion/laion2B-en", split="train", cache_dir=_CACHE_DIR, keep_in_memory=False)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\bberman\Documents\Art-Workspace\venv\Lib\site-packages\datasets\load.py", line 2165, in load_dataset
ds = builder_instance.as_dataset(split=split, verification_mode=verification_mode, in_memory=keep_in_memory)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\bberman\Documents\Art-Workspace\venv\Lib\site-packages\datasets\builder.py", line 1187, in as_dataset
datasets = map_nested(
^^^^^^^^^^^
File "C:\Users\bberman\Documents\Art-Workspace\venv\Lib\site-packages\datasets\utils\py_utils.py", line 456, in map_nested
return function(data_struct)
^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\bberman\Documents\Art-Workspace\venv\Lib\site-packages\datasets\builder.py", line 1217, in _build_single_dataset
ds = self._as_dataset(
^^^^^^^^^^^^^^^^^
File "C:\Users\bberman\Documents\Art-Workspace\venv\Lib\site-packages\datasets\builder.py", line 1291, in _as_dataset
dataset_kwargs = ArrowReader(cache_dir, self.info).read(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\bberman\Documents\Art-Workspace\venv\Lib\site-packages\datasets\arrow_reader.py", line 244, in read
return self.read_files(files=files, original_instructions=instructions, in_memory=in_memory)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\bberman\Documents\Art-Workspace\venv\Lib\site-packages\datasets\arrow_reader.py", line 265, in read_files
pa_table = self._read_files(files, in_memory=in_memory)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\bberman\Documents\Art-Workspace\venv\Lib\site-packages\datasets\arrow_reader.py", line 200, in _read_files
pa_table: Table = self._get_table_from_filename(f_dict, in_memory=in_memory)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\bberman\Documents\Art-Workspace\venv\Lib\site-packages\datasets\arrow_reader.py", line 336, in _get_table_from_filename
table = ArrowReader.read_table(filename, in_memory=in_memory)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\bberman\Documents\Art-Workspace\venv\Lib\site-packages\datasets\arrow_reader.py", line 357, in read_table
return table_cls.from_file(filename)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\bberman\Documents\Art-Workspace\venv\Lib\site-packages\datasets\table.py", line 1059, in from_file
table = _memory_mapped_arrow_table_from_file(filename)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\bberman\Documents\Art-Workspace\venv\Lib\site-packages\datasets\table.py", line 66, in _memory_mapped_arrow_table_from_file
pa_table = opened_stream.read_all()
^^^^^^^^^^^^^^^^^^^^^^^^
File "pyarrow\ipc.pxi", line 757, in pyarrow.lib.RecordBatchReader.read_all
File "pyarrow\error.pxi", line 91, in pyarrow.lib.check_status
OSError: [WinError 8] PrefetchVirtualMemory failed. Detail: [Windows error 8] Not enough memory resources are available to process this command.
```
This error is probably a red herring: https://stackoverflow.com/questions/50263929/numpy-memmap-returns-not-enough-memory-while-there-are-plenty-available In other words, the issue is related to asking for a memory mapping of length N > M the length of the file on Windows. This gracefully succeeds on Linux.
I have 1024 arrow files in my cache instead of 128 like in the repository for it. Probably related. I don't know why `datasets` reorganized/rewrote the dataset in my cache to be 1024 slices instead of the original 128.
### Steps to reproduce the bug
```
# as a huggingface developer, you may already have laion2B-en somewhere
_CACHE_DIR = "."
from datasets import load_dataset
load_dataset("laion/laion2B-en", split="train", cache_dir=_CACHE_DIR, keep_in_memory=False)
```
### Expected behavior
This should correctly load as a memory mapped Arrow dataset.
### Environment info
- `datasets` version: 2.15.0
- Platform: Windows-10-10.0.20348-SP0 (this is windows 2022)
- Python version: 3.11.4
- `huggingface_hub` version: 0.19.4
- PyArrow version: 14.0.1
- Pandas version: 2.1.2
- `fsspec` version: 2023.10.0
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https://api.github.com/repos/huggingface/datasets/issues/6760 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6760/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6760/comments | https://api.github.com/repos/huggingface/datasets/issues/6760/events | https://github.com/huggingface/datasets/issues/6760 | 2,212,288,122 | I_kwDODunzps6D3NZ6 | 6,760 | Load codeparrot/apps raising UnicodeDecodeError in datasets-2.18.0 | {
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"The same error with mteb datasets.",
"Unfortunately, I'm unable to reproduce this error locally or on Colab.",
"Here is the requirements.txt from a clean virtual environment (managed by conda) where I only install `datasets` by \r\n`pip install datasets`. \r\nThe pip list:\r\n```\r\naiohttp==3.9.3\r\naiosignal... | 2024-03-28T03:44:26Z | 2024-06-19T07:06:40Z | null | NONE | null | null | {
"completed": 0,
"percent_completed": 0,
"total": 0
} | ### Describe the bug
This happens with datasets-2.18.0; I downgraded the version to 2.14.6 fixing this temporarily.
```
Traceback (most recent call last):
File "/home/xxx/miniconda3/envs/py310/lib/python3.10/site-packages/datasets/load.py", line 2556, in load_dataset
builder_instance = load_dataset_builder(
File "/home/xxx/miniconda3/envs/py310/lib/python3.10/site-packages/datasets/load.py", line 2228, in load_dataset_builder
dataset_module = dataset_module_factory(
File "/home/xxx/miniconda3/envs/py310/lib/python3.10/site-packages/datasets/load.py", line 1879, in dataset_module_factory
raise e1 from None
File "/home/xxx/miniconda3/envs/py310/lib/python3.10/site-packages/datasets/load.py", line 1831, in dataset_module_factory
can_load_config_from_parquet_export = "DEFAULT_CONFIG_NAME" not in f.read()
File "/home/xxx/miniconda3/envs/py310/lib/python3.10/codecs.py", line 322, in decode
(result, consumed) = self._buffer_decode(data, self.errors, final)
UnicodeDecodeError: 'utf-8' codec can't decode byte 0x8b in position 1: invalid start byte
```
### Steps to reproduce the bug
1. Using Python3.10/3.11
2. Install datasets-2.18.0
3. test with
```
from datasets import load_dataset
dataset = load_dataset("codeparrot/apps")
```
### Expected behavior
Normally it should manage to download and load the dataset without such error.
### Environment info
Ubuntu, Python3.10/3.11 | null | {
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https://api.github.com/repos/huggingface/datasets/issues/6260 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6260/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6260/comments | https://api.github.com/repos/huggingface/datasets/issues/6260/events | https://github.com/huggingface/datasets/issues/6260 | 1,912,593,466 | I_kwDODunzps5x_9w6 | 6,260 | REUSE_DATASET_IF_EXISTS don't work | {
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"Hi! Unfortunately, the current behavior is to delete the downloaded data when this error happens. So, I've opened a PR that removes the problematic import to avoid losing data due to `apache_beam` not being installed (we host the preprocessed version of `natual_questions` on the HF GCS, so requiring `apache_beam` ... | 2023-09-26T03:02:16Z | 2023-09-28T18:23:36Z | 2023-09-28T18:23:36Z | NONE | null | null | {
"completed": 0,
"percent_completed": 0,
"total": 0
} | ### Describe the bug
I use the following code to download natural_question dataset. Even though I have completely download it, the next time I run this code, the new download procedure will start and cover the original /data/lxy/NQ
config=datasets.DownloadConfig(resume_download=True,max_retries=100,cache_dir=r'/data/lxy/NQ',download_desc='NQ')
data=datasets.load_dataset('natural_questions',cache_dir=r'/data/lxy/NQ',download_config=config,download_mode=DownloadMode.REUSE_DATASET_IF_EXISTS)
---
Since I don't have apache_beam installed, it throw a exception. After I pip install apache_beam ,the download restart..
### Steps to reproduce the bug
run this two line code
config=datasets.DownloadConfig(resume_download=True,max_retries=100,cache_dir=r'/data/lxy/NQ',download_desc='NQ')
data=datasets.load_dataset('natural_questions',cache_dir=r'/data/lxy/NQ',download_config=config,download_mode=DownloadMode.REUSE_DATASET_IF_EXISTS)
### Expected behavior
Download behavior can be correctly follow DownloadMode
### Environment info
- `datasets` version: 2.14.4
- Platform: Linux-3.10.0-1160.88.1.el7.x86_64-x86_64-with-glibc2.17
- Python version: 3.9.17
- Huggingface_hub version: 0.16.4
- PyArrow version: 11.0.0
- Pandas version: 2.0.3 | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"I thought this issue was resolved in my parallel `to_tf_dataset` PR! I changed the default `num_test_batches` in `_get_output_signature` to 20 and used a test batch size of 1 to maximize variance to detect shorter samples. I think it... | 2023-01-26T18:09:40Z | 2023-01-27T18:16:45Z | 2023-01-27T18:08:36Z | CONTRIBUTOR | null | null | null | `to_tf_dataset` calls can be very costly because of the number of test batches drawn during `_get_output_signature`. The test batches are draw in order to estimate the shapes when creating the tensorflow dataset. This is necessary when the shapes can be irregular, but not in cases when the tensor shapes are the same across all samples. This PR adds an option to change the number of batches drawn, so the user can speed this conversion up.
Running the following, and modifying `num_test_batches`
```
import time
from datasets import load_dataset
from transformers import DefaultDataCollator
data_collator = DefaultDataCollator()
dataset = load_dataset("beans")
dataset = dataset["train"].with_format("np")
start = time.time()
dataset = dataset.to_tf_dataset(
columns=["image"],
label_cols=["label"],
batch_size=8,
collate_fn=data_collator,
num_test_batches=NUM_TEST_BATCHES,
)
end = time.time()
print(end - start)
```
NUM_TEST_BATCHES=200: 0.8197s
NUM_TEST_BATCHES=50: 0.3070s
NUM_TEST_BATCHES=2: 0.1417s
NUM_TEST_BATCHES=1: 0.1352s | {
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https://api.github.com/repos/huggingface/datasets/issues/6833 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6833/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6833/comments | https://api.github.com/repos/huggingface/datasets/issues/6833/events | https://github.com/huggingface/datasets/issues/6833 | 2,259,731,274 | I_kwDODunzps6GsMNK | 6,833 | Super slow iteration with trivial custom transform | {
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"Similar issue in text process \r\n\r\n```python\r\n\r\ntokenizer=AutoTokenizer.from_pretrained(model_dir[args.model])\r\ntrain_dataset=datasets.load_from_disk(dataset_dir[args.dataset],keep_in_memory=True)['train']\r\ntrain_dataset=train_dataset.map(partial(dname2func[args.dataset],tokenizer=tokenizer),batched=Tru... | 2024-04-23T20:40:59Z | 2024-10-08T15:41:18Z | null | NONE | null | null | {
"completed": 0,
"percent_completed": 0,
"total": 0
} | ### 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 | null | {
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https://api.github.com/repos/huggingface/datasets/issues/6965 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6965/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6965/comments | https://api.github.com/repos/huggingface/datasets/issues/6965/events | https://github.com/huggingface/datasets/pull/6965 | 2,348,653,895 | PR_kwDODunzps5yOyNG | 6,965 | Improve skip take shuffling and distributed | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6965). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>... | 2024-06-12T12:30:27Z | 2024-06-24T15:22:21Z | 2024-06-24T15:16:16Z | MEMBER | null | null | null | set the right behavior of skip/take depending on whether it's called after or before shuffle/split_by_node | {
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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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"<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... | 2023-07-25T17:48:37Z | 2023-07-25T18:19:01Z | 2023-07-25T18:10:16Z | COLLABORATOR | null | null | null | Reported in https://github.com/huggingface/datasets/pull/5902#issuecomment-1649885621 (cc @alvarobartt) | {
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https://api.github.com/repos/huggingface/datasets/issues/7454 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7454/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7454/comments | https://api.github.com/repos/huggingface/datasets/issues/7454/events | https://github.com/huggingface/datasets/pull/7454 | 2,920,760,793 | PR_kwDODunzps6Os6bx | 7,454 | set dev version | {
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] | 2025-03-14T16:48:19Z | 2025-03-14T16:50:31Z | 2025-03-14T16:48:28Z | MEMBER | null | null | null | null | {
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https://api.github.com/repos/huggingface/datasets/issues/6829 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6829/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6829/comments | https://api.github.com/repos/huggingface/datasets/issues/6829/events | https://github.com/huggingface/datasets/issues/6829 | 2,258,424,577 | I_kwDODunzps6GnNMB | 6,829 | Load and save from/to disk no longer accept pathlib.Path | {
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} | 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 | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7497 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7497/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7497/comments | https://api.github.com/repos/huggingface/datasets/issues/7497/events | https://github.com/huggingface/datasets/issues/7497 | 2,968,553,693 | I_kwDODunzps6w8Ijd | 7,497 | How to convert videos to images? | {
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"Hi ! there is some documentation here on how to read video frames: https://huggingface.co/docs/datasets/video_load"
] | 2025-04-03T07:08:39Z | 2025-04-15T12:35:15Z | null | NONE | null | null | {
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} | ### Feature request
Does someone know how to return the images from videos?
### Motivation
I am trying to use openpi(https://github.com/Physical-Intelligence/openpi) to finetune my Lerobot dataset(V2.0 and V2.1). I find that although the codedaset is v2.0, they are different. It seems like Lerobot V2.0 has two version, one is data include images infos and another one is separate to data and videos.
Does someone know how to return the images from videos?
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https://api.github.com/repos/huggingface/datasets/issues/5041 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5041/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5041/comments | https://api.github.com/repos/huggingface/datasets/issues/5041/events | https://github.com/huggingface/datasets/pull/5041 | 1,390,722,230 | PR_kwDODunzps4_2WES | 5,041 | Support streaming hendrycks_test dataset. | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-09-29T11:37:58Z | 2022-09-30T07:13:38Z | 2022-09-29T12:07:29Z | MEMBER | null | null | null | This PR:
- supports streaming
- fixes the description section of the dataset card | {
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https://api.github.com/repos/huggingface/datasets/issues/5159 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5159/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5159/comments | https://api.github.com/repos/huggingface/datasets/issues/5159/events | https://github.com/huggingface/datasets/pull/5159 | 1,422,172,080 | PR_kwDODunzps5BfBN9 | 5,159 | fsspec lock reset in multiprocessing | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-10-25T09:41:59Z | 2022-11-03T20:51:15Z | 2022-11-03T20:48:53Z | MEMBER | null | null | null | `fsspec` added a clean way of resetting its lock - instead of doing it manually | {
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https://api.github.com/repos/huggingface/datasets/issues/4696 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4696/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4696/comments | https://api.github.com/repos/huggingface/datasets/issues/4696/events | https://github.com/huggingface/datasets/issues/4696 | 1,307,183,099 | I_kwDODunzps5N6gf7 | 4,696 | Cannot load LinCE dataset | {
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"Hi @finiteautomata, thanks for reporting.\r\n\r\nUnfortunately, I'm not able to reproduce your issue:\r\n```python\r\nIn [1]: from datasets import load_dataset\r\n ...: dataset = load_dataset(\"lince\", \"ner_spaeng\")\r\nDownloading builder script: 20.8kB [00:00, 9.09MB/s] ... | 2022-07-17T19:01:54Z | 2022-07-18T09:20:40Z | 2022-07-18T07:24:22Z | NONE | null | null | {
"completed": 0,
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} | ## Describe the bug
Cannot load LinCE dataset due to a connection error
## Steps to reproduce the bug
```python
from datasets import load_dataset
dataset = load_dataset("lince", "ner_spaeng")
```
A notebook with this code and corresponding error can be found at https://colab.research.google.com/drive/1pgX3bNB9amuUwAVfPFm-XuMV5fEg-cD2
## Expected results
It should load the dataset
## Actual results
```python
---------------------------------------------------------------------------
ConnectionError Traceback (most recent call last)
<ipython-input-2-fc551ddcebef> in <module>()
1 from datasets import load_dataset
2
----> 3 dataset = load_dataset("lince", "ner_spaeng")
10 frames
/usr/local/lib/python3.7/dist-packages/datasets/load.py in load_dataset(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, ignore_verifications, keep_in_memory, save_infos, revision, use_auth_token, task, streaming, **config_kwargs)
1682 ignore_verifications=ignore_verifications,
1683 try_from_hf_gcs=try_from_hf_gcs,
-> 1684 use_auth_token=use_auth_token,
1685 )
1686
/usr/local/lib/python3.7/dist-packages/datasets/builder.py in download_and_prepare(self, download_config, download_mode, ignore_verifications, try_from_hf_gcs, dl_manager, base_path, use_auth_token, **download_and_prepare_kwargs)
703 if not downloaded_from_gcs:
704 self._download_and_prepare(
--> 705 dl_manager=dl_manager, verify_infos=verify_infos, **download_and_prepare_kwargs
706 )
707 # Sync info
/usr/local/lib/python3.7/dist-packages/datasets/builder.py in _download_and_prepare(self, dl_manager, verify_infos)
1219
1220 def _download_and_prepare(self, dl_manager, verify_infos):
-> 1221 super()._download_and_prepare(dl_manager, verify_infos, check_duplicate_keys=verify_infos)
1222
1223 def _get_examples_iterable_for_split(self, split_generator: SplitGenerator) -> ExamplesIterable:
/usr/local/lib/python3.7/dist-packages/datasets/builder.py in _download_and_prepare(self, dl_manager, verify_infos, **prepare_split_kwargs)
769 split_dict = SplitDict(dataset_name=self.name)
770 split_generators_kwargs = self._make_split_generators_kwargs(prepare_split_kwargs)
--> 771 split_generators = self._split_generators(dl_manager, **split_generators_kwargs)
772
773 # Checksums verification
/root/.cache/huggingface/modules/datasets_modules/datasets/lince/10d41747f55f0849fa84ac579ea1acfa7df49aa2015b60426bc459c111b3d589/lince.py in _split_generators(self, dl_manager)
481 def _split_generators(self, dl_manager):
482 """Returns SplitGenerators."""
--> 483 lince_dir = dl_manager.download_and_extract(f"{_LINCE_URL}/{self.config.name}.zip")
484 data_dir = os.path.join(lince_dir, self.config.data_dir)
485 return [
/usr/local/lib/python3.7/dist-packages/datasets/download/download_manager.py in download_and_extract(self, url_or_urls)
429 extracted_path(s): `str`, extracted paths of given URL(s).
430 """
--> 431 return self.extract(self.download(url_or_urls))
432
433 def get_recorded_sizes_checksums(self):
/usr/local/lib/python3.7/dist-packages/datasets/download/download_manager.py in download(self, url_or_urls)
313 num_proc=download_config.num_proc,
314 disable_tqdm=not is_progress_bar_enabled(),
--> 315 desc="Downloading data files",
316 )
317 duration = datetime.now() - start_time
/usr/local/lib/python3.7/dist-packages/datasets/utils/py_utils.py in map_nested(function, data_struct, dict_only, map_list, map_tuple, map_numpy, num_proc, types, disable_tqdm, desc)
346 # Singleton
347 if not isinstance(data_struct, dict) and not isinstance(data_struct, types):
--> 348 return function(data_struct)
349
350 disable_tqdm = disable_tqdm or not logging.is_progress_bar_enabled()
/usr/local/lib/python3.7/dist-packages/datasets/download/download_manager.py in _download(self, url_or_filename, download_config)
333 # append the relative path to the base_path
334 url_or_filename = url_or_path_join(self._base_path, url_or_filename)
--> 335 return cached_path(url_or_filename, download_config=download_config)
336
337 def iter_archive(self, path_or_buf: Union[str, io.BufferedReader]):
/usr/local/lib/python3.7/dist-packages/datasets/utils/file_utils.py in cached_path(url_or_filename, download_config, **download_kwargs)
195 use_auth_token=download_config.use_auth_token,
196 ignore_url_params=download_config.ignore_url_params,
--> 197 download_desc=download_config.download_desc,
198 )
199 elif os.path.exists(url_or_filename):
/usr/local/lib/python3.7/dist-packages/datasets/utils/file_utils.py in get_from_cache(url, cache_dir, force_download, proxies, etag_timeout, resume_download, user_agent, local_files_only, use_etag, max_retries, use_auth_token, ignore_url_params, download_desc)
531 _raise_if_offline_mode_is_enabled(f"Tried to reach {url}")
532 if head_error is not None:
--> 533 raise ConnectionError(f"Couldn't reach {url} ({repr(head_error)})")
534 elif response is not None:
535 raise ConnectionError(f"Couldn't reach {url} (error {response.status_code})")
ConnectionError: Couldn't reach https://ritual.uh.edu/lince/libaccess/eyJ1c2VybmFtZSI6ICJodWdnaW5nZmFjZSBubHAiLCAidXNlcl9pZCI6IDExMSwgImVtYWlsIjogImR1bW15QGVtYWlsLmNvbSJ9/ner_spaeng.zip (ConnectTimeout(MaxRetryError("HTTPSConnectionPool(host='ritual.uh.edu', port=443): Max retries exceeded with url: /lince/libaccess/eyJ1c2VybmFtZSI6ICJodWdnaW5nZmFjZSBubHAiLCAidXNlcl9pZCI6IDExMSwgImVtYWlsIjogImR1bW15QGVtYWlsLmNvbSJ9/ner_spaeng.zip (Caused by ConnectTimeoutError(<urllib3.connection.HTTPSConnection object at 0x7feb1c45a690>, 'Connection to ritual.uh.edu timed out. (connect timeout=100)'))")))
```
## Environment info
- `datasets` version: 2.3.2
- Platform: Linux-5.4.188+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.7.13
- PyArrow version: 6.0.1
- Pandas version: 1.3.5
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https://api.github.com/repos/huggingface/datasets/issues/5464 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5464/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5464/comments | https://api.github.com/repos/huggingface/datasets/issues/5464/events | https://github.com/huggingface/datasets/issues/5464 | 1,557,462,104 | I_kwDODunzps5c1PxY | 5,464 | NonMatchingChecksumError for hendrycks_test | {
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"Thanks for reporting, @sarahwie.\r\n\r\nPlease note this issue was already fixed in `datasets` 2.6.0 version:\r\n- #5040\r\n\r\nIf you update your `datasets` version, you will be able to load the dataset:\r\n```\r\npip install -U datasets\r\n```",
"Oops, missed that I needed to upgrade. Thanks!"
] | 2023-01-26T00:43:23Z | 2023-01-27T05:44:31Z | 2023-01-26T07:41:58Z | NONE | null | null | {
"completed": 0,
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} | ### Describe the bug
The checksum of the file has likely changed on the remote host.
### Steps to reproduce the bug
`dataset = nlp.load_dataset("hendrycks_test", "anatomy")`
### Expected behavior
no error thrown
### Environment info
- `datasets` version: 2.2.1
- Platform: macOS-13.1-arm64-arm-64bit
- Python version: 3.9.13
- PyArrow version: 9.0.0
- Pandas version: 1.5.1 | {
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https://api.github.com/repos/huggingface/datasets/issues/4675 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4675/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4675/comments | https://api.github.com/repos/huggingface/datasets/issues/4675/events | https://github.com/huggingface/datasets/issues/4675 | 1,302,193,649 | I_kwDODunzps5NneXx | 4,675 | Unable to use dataset with PyTorch dataloader | {
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"Hi! `para_crawl` has a single column of type `Translation`, which stores translation dictionaries. These dictionaries can be stored in a NumPy array but not in a PyTorch tensor since PyTorch only supports numeric types. In `datasets`, the conversion to `torch` works as follows: \r\n1. convert PyArrow table to NumP... | 2022-07-12T15:04:04Z | 2022-07-14T14:17:46Z | null | NONE | null | null | {
"completed": 0,
"percent_completed": 0,
"total": 0
} | ## Describe the bug
When using `.with_format("torch")`, an arrow table is returned and I am unable to use it by passing it to a PyTorch DataLoader: please see the code below.
## Steps to reproduce the bug
```python
from datasets import load_dataset
from torch.utils.data import DataLoader
ds = load_dataset(
"para_crawl",
name="enfr",
cache_dir="/tmp/test/",
split="train",
keep_in_memory=True,
)
dataloader = DataLoader(ds.with_format("torch"), num_workers=32)
print(next(iter(dataloader)))
```
Is there something I am doing wrong? The documentation does not say much about the behavior of `.with_format()` so I feel like I am a bit stuck here :-/
Thanks in advance for your help!
## Expected results
The code should run with no error
## Actual results
```
AttributeError: 'str' object has no attribute 'dtype'
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 2.3.2
- Platform: Linux-4.18.0-348.el8.x86_64-x86_64-with-glibc2.28
- Python version: 3.10.4
- PyArrow version: 8.0.0
- Pandas version: 1.4.3
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https://api.github.com/repos/huggingface/datasets/issues/7401 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7401/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7401/comments | https://api.github.com/repos/huggingface/datasets/issues/7401/events | https://github.com/huggingface/datasets/pull/7401 | 2,853,260,869 | PR_kwDODunzps6LOMSo | 7,401 | set dev version | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_7401). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update."
] | 2025-02-14T10:17:03Z | 2025-02-14T10:19:20Z | 2025-02-14T10:17:13Z | MEMBER | null | null | null | null | {
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https://api.github.com/repos/huggingface/datasets/issues/5192 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5192/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5192/comments | https://api.github.com/repos/huggingface/datasets/issues/5192/events | https://github.com/huggingface/datasets/pull/5192 | 1,433,199,790 | PR_kwDODunzps5CD2BQ | 5,192 | Drop labels in Image and Audio folders if files are on different levels in directory or if there is only one label | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_5192). All of your documentation changes will be reflected on that endpoint.",
"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_5192). All of your documentation changes will be reflected on... | 2022-11-02T14:01:41Z | 2022-11-15T16:32:53Z | 2022-11-15T16:31:07Z | CONTRIBUTOR | null | null | null | Will close https://github.com/huggingface/datasets/issues/5153
Drop labels by default (`drop_labels=None`) when:
* there are files on different levels of directory hierarchy by checking their path depth
* all files are in the same directory (=only one label was inferred)
First one fixes cases like this:
```
repo
image3.jpg
image4.jpg
data
image1.jpg
image2.jpg
```
Second one fixes cases like this:
```
repo
image1.jpg
image2.jpg
image3.jpg
```
This is mostly to fix the viewer for people who just drop images in the Hub interface into the root dir.
I added tests for both of the cases on local and remote files. **I also changed data files for old test on drop_labels** (`test_generate_examples_drop_labels`). The files I provide to `test_generate_examples_drop_labels` now has "canonical" classification structure (two dirs) in order not to change the logic of the test (=not to check these two cases addressed in the PR).
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"Hi, thanks for reporting! If there are no examples in ImageFolder, the `label` column is of type `ClassLabel(names=[])`, which leads to an error in [this line](https://github.com/huggingface/datasets/blob/c15b391942764152f6060b59921b09cacc5f22a6/src/datasets/arrow_writer.py#L387) as `asdict(info)` calls `Features(... | 2022-07-14T10:57:55Z | 2022-07-25T12:37:54Z | 2022-07-25T12:37:54Z | NONE | null | null | {
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} | ## Describe the bug
Loading an image dataset with `imagefolder` throws `IndexError: list index out of range` when the given folder contains a non-image file (like a csv).
## Steps to reproduce the bug
Put a csv file in a folder with images and load it:
```python
import datasets
datasets.load_dataset("imagefolder", data_dir=path/to/folder)
```
## Expected results
I would expect a better error message, like `Unsupported file` or even the dataset loader just ignoring every file that is not an image in that case.
## Actual results
Here is the whole traceback:
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 2.3.2
- Platform: Linux-5.11.0-051100-generic-x86_64-with-glibc2.27
- Python version: 3.9.9
- PyArrow version: 8.0.0
- Pandas version: 1.4.3
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https://api.github.com/repos/huggingface/datasets/issues/7493 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7493/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7493/comments | https://api.github.com/repos/huggingface/datasets/issues/7493/events | https://github.com/huggingface/datasets/issues/7493 | 2,964,025,179 | I_kwDODunzps6wq29b | 7,493 | push_to_hub does not upload videos | {
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"Hi ! the `Video` type is still experimental, and in particular `push_to_hub` doesn't upload videos at the moment (only the paths).\n\nThere is an open question to either upload the videos inside the Parquet files, or rather have them as separate files (which is great to enable remote seeking/streaming)"
] | 2025-04-01T17:00:20Z | 2025-04-15T12:34:23Z | null | NONE | null | null | {
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} | ### Describe the bug
Hello,
I would like to upload a video dataset (some .mp4 files and some segments within them), i.e. rows correspond to subsequences from videos. Videos might be referenced by several rows.
I created a dataset locally and it references the videos and the video readers can read them correctly. I use push_to_hub() to upload the dataset to the hub.
Expectation: A user uses `load_dataset` and can load the videos.
However, the videos seem to be just referenced via paths on the computer and not uploaded to the hub. Therefore a target user cannot load the videos in the dataset.
### Steps to reproduce the bug
1. create a video dataset with paths e.g. { ["videos"]: [path1, path2, ...]}
2. dataset.push_to_hub
3. on a different computer (or same pc if relative paths are used in a different folder):
```
dataset = load_dataset("siplab/egosim", split="train")
video = dataset[0]["video_head"]
```
3. will fail
### Expected behavior
Expectation: A user uses `load_dataset` and can load the videos.
### Environment info
datasets 3.1.0
Python 3.8.18 | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7393 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7393/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7393/comments | https://api.github.com/repos/huggingface/datasets/issues/7393/events | https://github.com/huggingface/datasets/pull/7393 | 2,846,446,674 | PR_kwDODunzps6K3DiZ | 7,393 | Optimized sequence encoding for scalars | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_7393). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update."
] | 2025-02-11T20:30:44Z | 2025-02-13T17:11:33Z | 2025-02-13T17:11:32Z | CONTRIBUTOR | null | null | null | The change in https://github.com/huggingface/datasets/pull/3197 introduced redundant list-comprehensions when `obj` is a long sequence of scalars. This becomes a noticeable overhead when loading data from an `IterableDataset` in the function `_apply_feature_types_on_example` and can be eliminated by adding a check for scalars in `encode_nested_example` proposed here.
In the following code example
```
import time
from datasets.features import Sequence, Value
from datasets.features.features import encode_nested_example
schema = Sequence(Value("int32"))
obj = list(range(100000))
start = time.perf_counter()
result = encode_nested_example(schema, obj)
stop = time.perf_counter()
print(f"Time spent is {stop-start} sec")
```
`encode_nested_example` becomes 492x faster (from 0.0769 to 0.0002 sec), respectively 322x (from 0.00814 to 0.00003 sec) for a list of length 10000, on a GH200 system, making it unnoticeable when loading data with tokenization.
Another change is made to avoid creating arrays from scalars and afterwards re-extracting them during casting to python (`obj == obj.__array__()[()]` in that case), which avoids a regression in the array write benchmarks. | {
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https://api.github.com/repos/huggingface/datasets/issues/4732 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4732/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4732/comments | https://api.github.com/repos/huggingface/datasets/issues/4732/events | https://github.com/huggingface/datasets/issues/4732 | 1,314,371,566 | I_kwDODunzps5OV7fu | 4,732 | Document better that loading a dataset passing its name does not use the local script | {
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"Thanks for the feedback!\r\n\r\nI think since this issue is closely related to loading, I can add a clearer explanation under [Load > local loading script](https://huggingface.co/docs/datasets/main/en/loading#local-loading-script).",
"That makes sense but I think having a line about it under https://huggingface.... | 2022-07-22T06:07:31Z | 2022-08-23T16:32:23Z | 2022-08-23T16:32:23Z | MEMBER | null | null | {
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} | As reported by @TrentBrick here https://github.com/huggingface/datasets/issues/4725#issuecomment-1191858596, it could be more clear that loading a dataset by passing its name does not use the (modified) local script of it.
What he did:
- he installed `datasets` from source
- he modified locally `datasets/the_pile/the_pile.py` loading script
- he tried to load it but using `load_dataset("the_pile")` instead of `load_dataset("datasets/the_pile")`
- as explained here https://github.com/huggingface/datasets/issues/4725#issuecomment-1191040245:
- the former does not use the local script, but instead it downloads a copy of `the_pile.py` from our GitHub, caches it locally (inside `~/.cache/huggingface/modules`) and uses that.
He suggests adding a more clear explanation about this. He suggests adding it maybe in [Installation > source](https://huggingface.co/docs/datasets/installation))
CC: @stevhliu | {
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https://api.github.com/repos/huggingface/datasets/issues/5917 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5917/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5917/comments | https://api.github.com/repos/huggingface/datasets/issues/5917/events | https://github.com/huggingface/datasets/pull/5917 | 1,733,661,588 | PR_kwDODunzps5RwoRU | 5,917 | Refactor extensions | {
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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... | 2023-05-31T08:33:02Z | 2023-05-31T13:34:35Z | 2023-05-31T13:25:57Z | MEMBER | null | null | null | Related to:
- #5850 | {
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https://api.github.com/repos/huggingface/datasets/issues/5450 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5450/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5450/comments | https://api.github.com/repos/huggingface/datasets/issues/5450/events | https://github.com/huggingface/datasets/issues/5450 | 1,551,109,365 | I_kwDODunzps5cdAz1 | 5,450 | to_tf_dataset with a TF collator causes bizarrely persistent slowdown | {
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"wtf",
"Couldn't find what's causing this, this will need more investigation",
"A possible hint: The function it seems to be spending a lot of time in (when iterating over the original dataset) is `_get_mp` in the PIL JPEG decoder: \r\n![image](https://user-images.githubusercontent.com/12866554/214057267-c889f0... | 2023-01-20T16:08:37Z | 2023-02-13T14:13:34Z | 2023-02-13T14:13:34Z | MEMBER | null | null | {
"completed": 0,
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"total": 0
} | ### Describe the bug
This will make more sense if you take a look at [a Colab notebook that reproduces this issue.](https://colab.research.google.com/drive/1rxyeciQFWJTI0WrZ5aojp4Ls1ut18fNH?usp=sharing)
Briefly, there are several datasets that, when you iterate over them with `to_tf_dataset` **and** a data collator that returns `tf` tensors, become very slow. We haven't been able to figure this one out - it can be intermittent, and we have no idea what could possibly cause it. The weirdest thing is that **the slowdown affects other attempts to access the underlying dataset**. If you try to iterate over the `tf.data.Dataset`, then interrupt execution, and then try to iterate over the original dataset, the original dataset is now also very slow! This is true even if the dataset format is not set to `tf` - the iteration is slow even though it's not calling TF at all!
There is a simple workaround for this - we can simply get our data collators to return `np` tensors. When we do this, the bug is never triggered and everything is fine. In general, `np` is preferred for this kind of preprocessing work anyway, when the preprocessing is not going to be compiled into a pure `tf.data` pipeline! However, the issue is fascinating, and the TF team were wondering if anyone in datasets (cc @lhoestq @mariosasko) might have an idea of what could cause this.
### Steps to reproduce the bug
Run the attached Colab.
### Expected behavior
The slowdown should go away, or at least not persist after we stop iterating over the `tf.data.Dataset`
### Environment info
The issue occurs on multiple versions of Python and TF, both on local machines and on Colab.
All testing was done using the latest versions of `transformers` and `datasets` from `main` | {
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"Some of the shard files now have 0 number of rows.\r\n\r\nWe have opened an issue in the Apache Beam repo:\r\n- https://github.com/apache/beam/issues/25041"
] | 2023-01-17T06:42:12Z | 2024-02-06T19:24:21Z | 2024-02-06T19:24:21Z | MEMBER | null | null | {
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} | Once we find out the root cause of:
- #5426
we should revert the temporary pin on apache-beam introduced by:
- #5429 | {
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"Addressed in https://github.com/huggingface/datasets/pull/5191 (torch.Tensor objects now produce deterministic hashes)"
] | 2022-10-25T12:19:00Z | 2022-11-03T16:12:52Z | 2022-11-03T16:12:51Z | NONE | null | null | {
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} | ### Describe the bug
Hi,
I try to cache some outputs of teacher model( Knowledge Distillation ) by using map function of Dataset library, while every time I run my code, I still recompute all the sequences. I tested Bert Model like this, I got different hash every single run, so any idea to deal with this?
### Steps to reproduce the bug
1. run below code
2. get different hash
```
from transformers import BertModel
from transformers import AutoTokenizer
import torch
token = ['hello']
model = BertModel.from_pretrained("bert-base-uncased").eval()
tok = AutoTokenizer.from_pretrained("bert-base-uncased")
def abcd():
with torch.no_grad():
out = model(**tok(token,return_tensors='pt'))[0]
# out = tok(token)
return out
from datasets.fingerprint import Hasher
my_func = abcd
print(Hasher.hash(my_func))
print(abcd())
```
### Expected behavior
I wanna cache all the model output
### Environment info
datasets:2.5.0 | {
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https://api.github.com/repos/huggingface/datasets/issues/6769 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6769/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6769/comments | https://api.github.com/repos/huggingface/datasets/issues/6769/events | https://github.com/huggingface/datasets/issues/6769 | 2,218,242,015 | I_kwDODunzps6EN6_f | 6,769 | (Willing to PR) Datasets with custom python objects | {
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} | ### Feature request
Hi thanks for the library! I would like to have a huggingface Dataset, and one of its column is custom (non-serializable) Python objects. For example, a minimal code:
```
class MyClass:
pass
dataset = datasets.Dataset.from_list([
dict(a=MyClass(), b='hello'),
])
```
It gives error:
```
ArrowInvalid: Could not convert <__main__.MyClass object at 0x7a852830d050> with type MyClass: did not recognize Python value type when inferring an Arrow data type
```
I guess it is because Dataset forces to convert everything into arrow format. However, is there any ways to make the scenario work? Thanks!
### Motivation
(see above)
### Your contribution
Yes, I am happy to PR!
Cross-posted: https://discuss.huggingface.co/t/datasets-with-custom-python-objects/79050?u=fzyzcjy
EDIT: possibly related https://github.com/huggingface/datasets/issues/5766 | null | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6632). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>... | 2024-01-30T18:52:23Z | 2024-02-06T17:27:35Z | 2024-02-06T17:21:24Z | MEMBER | null | null | null | The cache used to only check for the latest cache directory with a given config_name, but it was wrong (e.g. `default-data_dir=data%2Ffortran-data_dir=data%2Ffortran` instead of `default-data_dir=data%2Ffortran`)
I fixed this by not passing the `config_kwargs` to the parent Builder `__init__`, and passing the config_id forged from the `config_kwargs` directly
close https://github.com/huggingface/datasets/issues/6609 | {
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"Can you post a reproducible code snippet of what you tried to do?\r\n\r\n",
"> Can you post a reproducible code snippet of what you tried to do?\n> \n> \n\n```python\nfrom datasets import load_dataset\n\ndataset = load_dataset(\"my_folder_name\", split=\"train\")\n```",
"hi @WiNE-iNEFF ! can you please also te... | 2023-03-18T13:59:13Z | 2023-07-24T14:13:02Z | 2023-07-24T14:13:01Z | NONE | null | null | {
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} | I have about 20000 images in my folder which divided into 4 folders with class names.
When i use load_dataset("my_folder_name", split="train") this function create dataset in which there are only 4 images, the remaining 19000 images were not added there. What is the problem and did not understand. Tried converting images and the like but absolutely nothing worked | {
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https://api.github.com/repos/huggingface/datasets/issues/4948 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4948/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4948/comments | https://api.github.com/repos/huggingface/datasets/issues/4948/events | https://github.com/huggingface/datasets/pull/4948 | 1,364,973,778 | PR_kwDODunzps4-hwsl | 4,948 | Fix minor typo in error message for missing imports | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-09-07T17:20:51Z | 2022-09-08T14:59:31Z | 2022-09-08T14:57:15Z | COLLABORATOR | null | null | null | null | {
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https://api.github.com/repos/huggingface/datasets/issues/6302 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6302/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6302/comments | https://api.github.com/repos/huggingface/datasets/issues/6302/events | https://github.com/huggingface/datasets/issues/6302 | 1,942,096,078 | I_kwDODunzps5zwgjO | 6,302 | ArrowWriter/ParquetWriter `write` method does not increase `_num_bytes` and hence datasets not sharding at `max_shard_size` | {
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"`writer._num_bytes` is updated every `writer_batch_size`-th call to the `write` method (default `writer_batch_size` is 1000 (examples)). You should be able to see the update by passing a smaller `writer_batch_size` to the `load_dataset_builder`.\r\n\r\nWe could improve this by supporting the string `writer_batch_s... | 2023-10-13T14:43:36Z | 2023-10-17T06:52:12Z | 2023-10-17T06:52:11Z | NONE | null | null | {
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} | ### Describe the bug
An example from [1], does not work when limiting shards with `max_shard_size`.
Try the following example with low `max_shard_size`, such as:
```python
builder.download_and_prepare(output_dir, storage_options=storage_options, file_format="parquet", max_shard_size="10MB")
```
The reason for this is that, in line [2] `writer._num_bytes > max_shard_size` is never true, because the `write` method of `ArrowWriter` [3] does not increase `self._num_bytes`.
Such that respective Arrow/Parquet shards are only written to file based on the `writer_batch_size` or `config.DEFAULT_MAX_BATCH_SIZE`, but not based on `max_shard_size`.
[1] https://huggingface.co/docs/datasets/filesystems#download-and-prepare-a-dataset-into-a-cloud-storage
[2] https://github.com/huggingface/datasets/blob/3e8d420808718c9a1453a2e7ee3484ca12c9c70d/src/datasets/builder.py#L1677
[3] https://github.com/huggingface/datasets/blob/3e8d420808718c9a1453a2e7ee3484ca12c9c70d/src/datasets/arrow_writer.py#L459
### Steps to reproduce the bug
Get example from: https://huggingface.co/docs/datasets/filesystems#download-and-prepare-a-dataset-into-a-cloud-storage
Call `builder.download_and_prepare` with low `max_shard_size` such as `10MB`, e.g.:
```python
builder.download_and_prepare(output_dir, storage_options=storage_options, file_format="parquet", max_shard_size="10MB")
```
### Expected behavior
Shards should be written based on `max_shard_size` instead of batch size.
### Environment info
```
>>> import datasets
>>> datasets.__version__
'2.14.6.dev0
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/6900 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6900/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6900/comments | https://api.github.com/repos/huggingface/datasets/issues/6900/events | https://github.com/huggingface/datasets/issues/6900 | 2,298,489,733 | I_kwDODunzps6JACuF | 6,900 | [WebDataset] KeyError with user-defined `Features` when a field is missing in an example | {
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"@lhoestq How difficult of fix is this?",
"It shouldn't be difficult, I think it's just a matter of adding the missing fields from `self.config.features` in `example` here: before it iterates on image_field_names and audio_field_names. A missing field should have a value set to None\r\n\r\nhttps://github.com/hugg... | 2024-05-15T17:48:34Z | 2024-06-28T09:30:13Z | 2024-06-28T09:30:13Z | MEMBER | null | null | {
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} | reported at https://huggingface.co/datasets/ProGamerGov/synthetic-dataset-1m-dalle3-high-quality-captions/discussions/1
```
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 109, in _generate_examples
example[field_name] = {"path": example["__key__"] + "." + field_name, "bytes": example[field_name]}
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/5416 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5416/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5416/comments | https://api.github.com/repos/huggingface/datasets/issues/5416/events | https://github.com/huggingface/datasets/pull/5416 | 1,526,988,113 | PR_kwDODunzps5HDLmR | 5,416 | Fix RuntimeError: Sharding is ambiguous for this dataset | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"By the way, do we know how many datasets are impacted by this issue?\r\n\r\nMaybe we should do a patch release with this fix.",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==6.0.0\n\n<details>\n<summary>Show updated be... | 2023-01-10T08:43:19Z | 2023-01-18T17:12:17Z | 2023-01-18T14:09:02Z | MEMBER | null | null | null | This PR fixes the RuntimeError: Sharding is ambiguous for this dataset.
The error for ambiguous sharding will be raised only if num_proc > 1.
Fix #5415, fix #5414.
Fix https://huggingface.co/datasets/ami/discussions/3. | {
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https://api.github.com/repos/huggingface/datasets/issues/6193 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6193/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6193/comments | https://api.github.com/repos/huggingface/datasets/issues/6193/events | https://github.com/huggingface/datasets/issues/6193 | 1,872,285,153 | I_kwDODunzps5vmM3h | 6,193 | Dataset loading script method does not work with .pyc file | {
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"Before dynamically loading `.py` scripts with `importlib.import_module`, we also parse their contents to check imports, which is tricky to implement for binary `.pyc` files (requires parsing bytecode), so I don't think this is something we want to support (unless more users request it ofc) as this use case is a bi... | 2023-08-29T19:35:06Z | 2023-08-31T19:47:29Z | null | NONE | null | null | {
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} | ### Describe the bug
The huggingface dataset library specifically looks for β.pyβ file while loading the dataset using loading script approach and it does not work with β.pycβ file.
While deploying in production, it becomes an issue when we are restricted to use only .pyc files. Is there any work around for this ?
### Steps to reproduce the bug
1. Create a dataset loading script to read the custom data.
2. compile the code to make sure that .pyc file is created
3. Delete the loading script and re-run the code. Usually, python should make use of complied .pyc files. However, in this case, the dataset library errors out with the message that it's unable to find the data loader loading script.
### Expected behavior
The code should make use of .pyc file and run without any error.
### Environment info
NA | null | {
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https://api.github.com/repos/huggingface/datasets/issues/6772 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6772/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6772/comments | https://api.github.com/repos/huggingface/datasets/issues/6772/events | https://github.com/huggingface/datasets/pull/6772 | 2,220,851,533 | PR_kwDODunzps5rdKZ2 | 6,772 | `remove_columns`/`rename_columns` doc fixes | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6772). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>... | 2024-04-02T15:41:28Z | 2024-04-02T16:28:45Z | 2024-04-02T16:17:46Z | COLLABORATOR | null | null | null | Use more consistent wording in `remove_columns` to explain why it's faster than `map` and update `remove_columns`/`rename_columns` docstrings to fix in-place calls.
Reported in https://github.com/huggingface/datasets/issues/6700 | {
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https://api.github.com/repos/huggingface/datasets/issues/7113 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7113/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7113/comments | https://api.github.com/repos/huggingface/datasets/issues/7113/events | https://github.com/huggingface/datasets/issues/7113 | 2,475,029,640 | I_kwDODunzps6ThfSI | 7,113 | Stream dataset does not iterate if the batch size is larger than the dataset size (related to drop_last_batch) | {
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"That's expected behavior, it's also the same in `torch`:\r\n\r\n```python\r\n>>> list(DataLoader(list(range(5)), batch_size=10, drop_last=True))\r\n[]\r\n```"
] | 2024-08-20T08:26:40Z | 2024-08-26T04:24:11Z | 2024-08-26T04:24:10Z | NONE | null | null | {
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} | ### Describe the bug
Hi there,
I use streaming and interleaving to combine multiple datasets saved in jsonl files. The size of dataset can vary (from 100ish to 100k-ish). I use dataset.map() and a big batch size to reduce the IO cost. It was working fine with datasets-2.16.1 but this problem shows up after I upgraded to datasets-2.19.2. With 2.21.0 the problem remains.
Please see the code below to reproduce the problem.
The dataset can iterate correctly if we set either streaming=False or drop_last_batch=False.
I have to use drop_last_batch=True since it's for distributed training.
### Steps to reproduce the bug
```python
# datasets==2.21.0
import datasets
def data_prepare(examples):
print(examples["sentence1"][0])
return examples
batch_size = 101
# the size of the dataset is 100
# the dataset iterates correctly if we set either streaming=False or drop_last_batch=False
dataset = datasets.load_dataset("mteb/biosses-sts", split="test", streaming=True)
dataset = dataset.map(lambda x: data_prepare(x),
drop_last_batch=True,
batched=True, batch_size=batch_size)
for ex in dataset:
print(ex)
pass
```
### Expected behavior
The dataset iterates regardless of the batch size.
### Environment info
- `datasets` version: 2.21.0
- Platform: Linux-6.1.58+-x86_64-with-glibc2.35
- Python version: 3.10.14
- `huggingface_hub` version: 0.24.5
- PyArrow version: 17.0.0
- Pandas version: 2.2.2
- `fsspec` version: 2024.2.0
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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... | 2023-09-08T11:08:55Z | 2023-09-08T12:29:21Z | 2023-09-08T12:20:51Z | MEMBER | null | null | null | null | {
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"@mariosasko I'm getting a similar issue when creating a Dataset from a Pandas dataframe, like so:\r\n\r\n```\r\nfrom datasets import Dataset, Features, Image, Value\r\nimport pandas as pd\r\nimport requests\r\nimport PIL\r\n\r\n# we need to define the features ourselves\r\nfeatures = Features({\r\n 'a': Value(d... | 2022-08-05T12:41:19Z | 2024-11-29T16:35:17Z | null | CONTRIBUTOR | null | null | {
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} | ## Describe the bug
When adding a Pillow image to an existing Dataset on the hub, `add_item` fails due to the Pillow image not being automatically converted into the Image feature.
## Steps to reproduce the bug
```python
from datasets import load_dataset
from PIL import Image
dataset = load_dataset("hf-internal-testing/example-documents")
# load any random Pillow image
image = Image.open("/content/cord_example.png").convert("RGB")
new_image = {'image': image}
dataset['test'] = dataset['test'].add_item(new_image)
```
## Expected results
The image should be automatically casted to the Image feature when using `add_item`. For now, this can be fixed by using `encode_example`:
```
import datasets
feature = datasets.Image(decode=False)
new_image = {'image': feature.encode_example(image)}
dataset['test'] = dataset['test'].add_item(new_image)
```
## Actual results
```
ArrowInvalid: Could not convert <PIL.Image.Image image mode=RGB size=576x864 at 0x7F7CCC4589D0> with type Image: did not recognize Python value type when inferring an Arrow data type
```
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-10-17T08:45:08Z | 2022-10-19T09:12:17Z | 2022-10-19T09:10:06Z | MEMBER | null | null | null | Fix #5118. | {
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https://api.github.com/repos/huggingface/datasets/issues/6218 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6218/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6218/comments | https://api.github.com/repos/huggingface/datasets/issues/6218/events | https://github.com/huggingface/datasets/pull/6218 | 1,883,734,000 | PR_kwDODunzps5Zqw3Y | 6,218 | Rename old push_to_hub configs to "default" in dataset_infos | {
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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... | 2023-09-06T10:40:05Z | 2023-09-07T08:31:29Z | 2023-09-06T11:23:56Z | MEMBER | null | null | null | Fix
```python
from datasets import load_dataset_builder
b = load_dataset_builder("lambdalabs/pokemon-blip-captions", "default")
print(b.info)
```
which should return
```
DatasetInfo(
features={'image': Image(decode=True, id=None), 'text': Value(dtype='string', id=None)},
dataset_name='pokemon-blip-captions',
config_name='default',
version=0.0.0,
splits={'train': SplitInfo(name='train', num_bytes=119417410.0, num_examples=833, shard_lengths=None, dataset_name='pokemon-blip-captions')},
download_checksums=None,
download_size=99672355,
dataset_size=119417410.0,
size_in_bytes=219089765.0,
...
)
```
instead of and empty dataset info.
The dataset has a dataset_infos.json file with a deprecated config name "lambdalabs--pokemon-blip-captions". We switched those config names to "default" in 2.14, so the builder.info should take this into account. | {
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https://api.github.com/repos/huggingface/datasets/issues/5752 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5752/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5752/comments | https://api.github.com/repos/huggingface/datasets/issues/5752/events | https://github.com/huggingface/datasets/issues/5752 | 1,668,574,209 | I_kwDODunzps5jdGwB | 5,752 | Streaming dataset looses `.feature` method after `.add_column` | {
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"I believe the issue resides in this line:\r\nhttps://github.com/huggingface/datasets/blob/7c3a9b057c476c40d157bd7a5d57f49066239df0/src/datasets/iterable_dataset.py#L1415\r\n\r\nIf we pass the **new** features of the dataset to the `.map` method we can return the features after adding a column, e.g.:\r\n```python\r... | 2023-04-14T16:39:50Z | 2024-01-18T10:15:20Z | null | CONTRIBUTOR | null | null | {
"completed": 0,
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"total": 0
} | ### Describe the bug
After appending a new column to a streaming dataset using `.add_column`, we can no longer access the list of dataset features using the `.feature` method.
### Steps to reproduce the bug
```python
from datasets import load_dataset
original_dataset = load_dataset("librispeech_asr", "clean", split="validation", streaming=True)
print(original_dataset.features.keys())
# now add a new column to our streaming dataset
modified_dataset = original_dataset.add_column("new_column", ["some random text" for _ in range(50)])
print(modified_dataset.features.keys())
```
**Print Output:**
```
dict_keys(['file', 'audio', 'text', 'speaker_id', 'chapter_id', 'id'])
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
Cell In[1], line 8
6 # now add a new column to our streaming dataset
7 modified_dataset = original_dataset.add_column("new_column", ["some random text" for _ in range(50)])
----> 8 print(modified_dataset.features.keys())
AttributeError: 'NoneType' object has no attribute 'keys'
```
We see that we get the features for the original dataset, but not the modified one with the added column.
### Expected behavior
Features should be persevered after adding a new column, i.e. calling:
```python
print(modified_dataset.features.keys())
```
Should return:
```
dict_keys(['file', 'audio', 'text', 'speaker_id', 'chapter_id', 'id', 'new_column'])
```
### Environment info
- `datasets` version: 2.10.2.dev0
- Platform: Linux-4.19.0-23-cloud-amd64-x86_64-with-glibc2.28
- Python version: 3.9.16
- Huggingface_hub version: 0.13.3
- PyArrow version: 10.0.1
- Pandas version: 1.5.2 | null | {
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https://api.github.com/repos/huggingface/datasets/issues/4978 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4978/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4978/comments | https://api.github.com/repos/huggingface/datasets/issues/4978/events | https://github.com/huggingface/datasets/pull/4978 | 1,374,271,504 | PR_kwDODunzps4_Axnh | 4,978 | Update IndicGLUE download links | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-09-15T10:05:57Z | 2022-09-15T22:00:20Z | 2022-09-15T21:57:34Z | CONTRIBUTOR | null | null | null | null | {
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https://api.github.com/repos/huggingface/datasets/issues/4823 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4823/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4823/comments | https://api.github.com/repos/huggingface/datasets/issues/4823/events | https://github.com/huggingface/datasets/pull/4823 | 1,335,687,033 | PR_kwDODunzps49A0O_ | 4,823 | Update data URL in mkqa dataset | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-08-11T09:16:13Z | 2022-08-11T09:51:50Z | 2022-08-11T09:37:52Z | MEMBER | null | null | null | Update data URL in mkqa dataset.
Fix #4817. | {
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https://api.github.com/repos/huggingface/datasets/issues/7527 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7527/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7527/comments | https://api.github.com/repos/huggingface/datasets/issues/7527/events | https://github.com/huggingface/datasets/issues/7527 | 3,005,242,422 | I_kwDODunzps6zIFw2 | 7,527 | Auto-merge option for `convert-to-parquet` | {
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"Alternatively, there could be an option to switch from submitting PRs to just committing changes directly to `main`."
] | 2025-04-18T16:03:22Z | 2025-04-18T16:05:30Z | null | NONE | null | null | {
"completed": 0,
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} | ### Feature request
Add a command-line option, e.g. `--auto-merge-pull-request` that enables automatic merging of the commits created by the `convert-to-parquet` tool.
### Motivation
Large datasets may result in dozens of PRs due to the splitting mechanism. Each of these has to be manually accepted via the website.
### Your contribution
Happy to look into submitting a PR if this is of interest to maintainers. | null | {
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https://api.github.com/repos/huggingface/datasets/issues/6207 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6207/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6207/comments | https://api.github.com/repos/huggingface/datasets/issues/6207/events | https://github.com/huggingface/datasets/issues/6207 | 1,879,555,234 | I_kwDODunzps5wB7yi | 6,207 | No-script datasets with ZIP files do not load | {
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"following_url": "https://api.github.com/users/albertvillanova/following{/o... | null | [] | 2023-09-04T05:50:27Z | 2023-09-04T09:13:33Z | 2023-09-04T09:13:33Z | MEMBER | null | null | {
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} | While investigating an issue on a Hub dataset, I have discovered the no-script datasets containing ZIP files do not load.
For example, that no-script dataset containing ZIP files, raises NonMatchingSplitsSizesError:
```python
In [2]: ds = load_dataset("sidovic/LearningQ-qg")
NonMatchingSplitsSizesError: [
{
'expected': SplitInfo(name='train', num_bytes=0, num_examples=188660, shard_lengths=None, dataset_name=None),
'recorded': SplitInfo(name='train', num_bytes=0, num_examples=0, shard_lengths=None, dataset_name='learning_q-qg')
}, {
'expected': SplitInfo(name='validation', num_bytes=0, num_examples=20630, shard_lengths=None, dataset_name=None),
'recorded': SplitInfo(name='validation', num_bytes=0, num_examples=0, shard_lengths=None, dataset_name='learning_q-qg')
}, {
'expected': SplitInfo(name='test', num_bytes=0, num_examples=18227, shard_lengths=None, dataset_name=None),
'recorded': SplitInfo(name='test', num_bytes=0, num_examples=0, shard_lengths=None, dataset_name='learning_q-qg')
}
]
```
As another example, a no-script dataset containing just a (CSV)-ZIP file, raises a DatasetGenerationError:
```
> num_examples, num_bytes = writer.finalize()
src/datasets/builder.py:1949:
> raise SchemaInferenceError("Please pass `features` or at least one example when writing data")
E datasets.arrow_writer.SchemaInferenceError: Please pass `features` or at least one example when writing data
src/datasets/arrow_writer.py:598: SchemaInferenceError
The above exception was the direct cause of the following exception:
src/datasets/load.py:2143: in load_dataset
builder_instance.download_and_prepare(
src/datasets/builder.py:954: in download_and_prepare
self._download_and_prepare(
src/datasets/builder.py:1049: in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
src/datasets/builder.py:1813: in _prepare_split
for job_id, done, content in self._prepare_split_single(
> raise DatasetGenerationError("An error occurred while generating the dataset") from e
E datasets.builder.DatasetGenerationError: An error occurred while generating the dataset
src/datasets/builder.py:1958: DatasetGenerationError
```
After investigating, I think this bug was introduced in this PR:
- #5972
Related to:
- https://huggingface.co/datasets/sidovic/LearningQ-qg/discussions/1
CC: @lhoestq | {
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https://api.github.com/repos/huggingface/datasets/issues/6086 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6086/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6086/comments | https://api.github.com/repos/huggingface/datasets/issues/6086/events | https://github.com/huggingface/datasets/issues/6086 | 1,825,009,268 | I_kwDODunzps5sx250 | 6,086 | Support `fsspec` in `Dataset.to_<format>` methods | {
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"Hi @mariosasko unless someone's already working on it, I guess I can tackle it!",
"Hi! Sure, feel free to tackle this.",
"#self-assign",
"I'm assuming this should just cover `to_csv`, `to_parquet`, and `to_json`, right? As `to_list` and `to_dict` just return Python objects, `to_pandas` returns a `pandas.Data... | 2023-07-27T19:08:37Z | 2024-03-07T07:22:43Z | 2024-03-07T07:22:42Z | COLLABORATOR | null | null | {
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} | Supporting this should be fairly easy.
Requested on the forum [here](https://discuss.huggingface.co/t/how-can-i-convert-a-loaded-dataset-in-to-a-parquet-file-and-save-it-to-the-s3/48353). | {
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https://api.github.com/repos/huggingface/datasets/issues/6739 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6739/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6739/comments | https://api.github.com/repos/huggingface/datasets/issues/6739/events | https://github.com/huggingface/datasets/pull/6739 | 2,192,730,134 | PR_kwDODunzps5p-Bwe | 6,739 | Transpose images with EXIF Orientation tag | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6739). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>... | 2024-03-18T16:43:06Z | 2024-03-19T15:35:57Z | 2024-03-19T15:29:42Z | COLLABORATOR | null | null | null | Closes https://github.com/huggingface/datasets/issues/6252 | {
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https://api.github.com/repos/huggingface/datasets/issues/7514 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7514/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7514/comments | https://api.github.com/repos/huggingface/datasets/issues/7514/events | https://github.com/huggingface/datasets/pull/7514 | 2,994,714,923 | PR_kwDODunzps6Sk7Et | 7,514 | Do not hash `generator` in `BuilderConfig.create_config_id` | {
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} | [] | closed | false | null | [] | null | [] | 2025-04-15T01:26:43Z | 2025-04-23T11:55:55Z | 2025-04-15T16:27:51Z | NONE | null | null | null | `Dataset.from_generator` function passes all of its arguments to `BuilderConfig.create_config_id`, including generator function itself. `BuilderConfig.create_config_id` function tries to hash all the args, and hashing a `generator` can take a large amount of time or even cause MemoryError if the dataset processed in a generator function is large enough.
Maybe we should pop generator from `config_kwargs_to_add_to_suffix` before hashing to avoid it.
There is a more detailed description of the problem this PR solves in #7513 | {
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https://api.github.com/repos/huggingface/datasets/issues/5067 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5067/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5067/comments | https://api.github.com/repos/huggingface/datasets/issues/5067/events | https://github.com/huggingface/datasets/pull/5067 | 1,396,361,768 | PR_kwDODunzps5AI86d | 5,067 | Fix CONTRIBUTING once dataset scripts transferred to Hub | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-10-04T14:16:05Z | 2022-10-06T06:14:43Z | 2022-10-06T06:12:12Z | MEMBER | null | null | null | This PR updates the `CONTRIBUTING.md` guide, once the all dataset scripts have been removed from the GitHub repo and transferred to the HF Hub:
- #4974
See diff here: https://github.com/huggingface/datasets/commit/e3291ecff9e54f09fcee3f313f051a03fdc3d94b
Additionally, this PR fixes the line separator that by some previous mistake was CRLF instead of LF. | {
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https://api.github.com/repos/huggingface/datasets/issues/5864 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5864/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5864/comments | https://api.github.com/repos/huggingface/datasets/issues/5864/events | https://github.com/huggingface/datasets/issues/5864 | 1,710,450,047 | I_kwDODunzps5l82V_ | 5,864 | Slow iteration over Torch tensors | {
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"I am highly interested performance of dataset so I ran your example as a curious user.\r\n```python\r\ntrain_dataset.cast_column(\"x\", Array3D(shape=img_shape, dtype=\"float32\"))\r\n```\r\nhave return values and \"x\" is a new column, it shoulde be\r\n```python\r\nds=train_dataset.cast_column(\"img\", Array3D(sh... | 2023-05-15T16:43:58Z | 2024-10-08T10:21:48Z | null | NONE | null | null | {
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} | ### Describe the bug
I have a problem related to this [issue](https://github.com/huggingface/datasets/issues/5841): I get a way slower iteration when using a Torch dataloader if I use vanilla Numpy tensors or if I first apply a ToTensor transform to the input. In particular, it takes 5 seconds to iterate over the vanilla input and ~30s after the transformation.
### Steps to reproduce the bug
Here is the minimum code to reproduce the problem
```python
import numpy as np
from datasets import Dataset, DatasetDict, load_dataset, Array3D, Image, Features
from torch.utils.data import DataLoader
from tqdm import tqdm
import torchvision
from torchvision.transforms import ToTensor, Normalize
#################################
# Without transform
#################################
train_dataset = load_dataset(
'cifar100',
split='train',
use_auth_token=True,
)
train_dataset.set_format(type="numpy", columns=["img", "fine_label"])
train_loader= DataLoader(
train_dataset,
batch_size=100,
pin_memory=False,
shuffle=True,
num_workers=8,
)
for batch in tqdm(train_loader, desc="Loading data, no transform"):
pass
#################################
# With transform
#################################
transform_func = torchvision.transforms.Compose([
ToTensor(),
Normalize(mean=[0.485, 0.456, 0.406], std= [0.229, 0.224, 0.225]),]
)
train_dataset = train_dataset.map(
desc=f"Preprocessing samples",
function=lambda x: {"img": transform_func(x["img"])},
)
train_dataset.set_format(type="numpy", columns=["img", "fine_label"])
train_loader= DataLoader(
train_dataset,
batch_size=100,
pin_memory=False,
shuffle=True,
num_workers=8,
)
for batch in tqdm(train_loader, desc="Loading data after transform"):
pass
```
I have also tried converting the Image column to an Array3D
```python
img_shape = train_dataset[0]["img"].shape
features = train_dataset.features.copy()
features["x"] = Array3D(shape=img_shape, dtype="float32")
train_dataset = train_dataset.map(
desc=f"Preprocessing samples",
function=lambda x: {"x": np.array(x["img"], dtype=np.uint8)},
features=features,
)
train_dataset.cast_column("x", Array3D(shape=img_shape, dtype="float32"))
train_dataset.set_format(type="numpy", columns=["x", "fine_label"])
```
but to no avail. Any clue?
### Expected behavior
The iteration should take approximately the same time with or without the transformation, as it doesn't change the shape of the input. What may be the issue here?
### Environment info
```
- `datasets` version: 2.12.0
- Platform: Linux-5.4.0-137-generic-x86_64-with-glibc2.31
- Python version: 3.9.16
- Huggingface_hub version: 0.14.1
- PyArrow version: 12.0.0
- Pandas version: 2.0.1
``` | null | {
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https://api.github.com/repos/huggingface/datasets/issues/6083 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6083/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6083/comments | https://api.github.com/repos/huggingface/datasets/issues/6083/events | https://github.com/huggingface/datasets/pull/6083 | 1,824,832,348 | PR_kwDODunzps5WkgAI | 6,083 | set dev version | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6083). 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... | 2023-07-27T17:10:41Z | 2023-07-27T17:22:05Z | 2023-07-27T17:11:01Z | MEMBER | null | null | null | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7505 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7505/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7505/comments | https://api.github.com/repos/huggingface/datasets/issues/7505/events | https://github.com/huggingface/datasets/issues/7505 | 2,979,926,156 | I_kwDODunzps6xnhCM | 7,505 | HfHubHTTPError: 403 Forbidden: None. Cannot access content at: https://hf.co/api/s3proxy | {
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} | I have already logged in Huggingface using CLI with my valid token. Now trying to download the datasets using following code:
from transformers import WhisperProcessor, WhisperForConditionalGeneration, WhisperTokenizer, Trainer, TrainingArguments, DataCollatorForSeq2Seq
from datasets import load_dataset, DatasetDict, Audio
def load_and_preprocess_dataset():
dataset = load_dataset("mozilla-foundation/common_voice_17_0", "bn")
dataset = dataset.remove_columns(["accent", "age", "client_id", "down_votes", "gender", "locale", "segment", "up_votes"])
dataset = dataset.cast_column("audio", Audio(sampling_rate=16000))
dataset = dataset["train"].train_test_split(test_size=0.1)
dataset = DatasetDict({
"train": dataset["train"],
"test": dataset["test"]
})
return dataset
load_and_preprocess_dataset()
I am getting following error:
Downloadingβdata:β100%
β25/25β[00:01<00:00,β25.31files/s]
---------------------------------------------------------------------------
HTTPError Traceback (most recent call last)
File ~/github/bangla-asr/.venv/lib/python3.11/site-packages/huggingface_hub/utils/_http.py:409, in hf_raise_for_status(response, endpoint_name)
408 try:
--> 409 response.raise_for_status()
410 except HTTPError as e:
File ~/github/bangla-asr/.venv/lib/python3.11/site-packages/requests/models.py:1024, in Response.raise_for_status(self)
1023 if http_error_msg:
-> 1024 raise HTTPError(http_error_msg, response=self)
HTTPError: 403 Client Error: BlockSIEL for url: https://hf.co/api/s3proxy?GET=https%3A%2F%2Fhf-hub-lfs-us-east-1.s3.us-east-1.amazonaws.com%2Frepos%2Fa3%2F86%2Fa386bf65687d8a6928c1ea57c383aa3faade32f5171150e25af3fc1cfc273db8%2F67f1ac9cabd539bfbff3acbc549b60647833a250dc638866f22bf1b64e68806d%3FX-Amz-Algorithm%3DAWS4-HMAC-SHA256%26X-Amz-Content-Sha256%3DUNSIGNED-PAYLOAD%26X-Amz-Credential%3DAKIA2JU7TKAQLC2QXPN7%252F20250408%252Fus-east-1%252Fs3%252Faws4_request%26X-Amz-Date%3D20250408T134345Z%26X-Amz-Expires%3D3600%26X-Amz-Signature%3D621e731d4fd6d08afbf568379797746ab8e2b853b6728ff5e1122fef6e56880b%26X-Amz-SignedHeaders%3Dhost%26response-content-disposition%3Dinline%253B%2520filename%252A%253DUTF-8%2527%2527bn_validated_1.tar%253B%2520filename%253D%2522bn_validated_1.tar%2522%253B%26response-content-type%3Dapplication%252Fx-tar%26x-id%3DGetObject&HEAD=https%3A%2F%2Fhf-hub-lfs-us-east-1.s3.us-east-1.amazonaws.com%2Frepos%2Fa3%2F86%2Fa386bf65687d8a6928c1ea57c383aa3faade32f5171150e25af3fc1cfc273db8%2F67f1ac9cabd539bfbff3acbc549b60647833a250dc638866f22bf1b64e68806d%3FX-Amz-Algorithm%3DAWS4-HMAC-SHA256%26X-Amz-Content-Sha256%3DUNSIGNED-PAYLOAD%26X-Amz-Credential%3DAKIA2JU7TKAQLC2QXPN7%252F20250408%252Fus-east-1%252Fs3%252Faws4_request%26X-Amz-Date%3D20250408T134345Z%26X-Amz-Expires%3D3600%26X-Amz-Signature%3D15254fb79d30b0dc36b94a28138e675e0e00bb475b8a3ae774418500b095a661%26X-Amz-SignedHeaders%3Dhost&sign=eyJhbGciOiJIUzI1NiJ9.eyJyZWRpcmVjdF9kb21haW4iOiJoZi1odWItbGZzLXVzLWVhc3QtMS5zMy51cy1lYXN0LTEuYW1hem9uYXdzLmNvbSIsImlhdCI6MTc0NDExOTgyNSwiZXhwIjoxNzQ0MjA2MjI1LCJpc3MiOiJodHRwczovL2h1Z2dpbmdmYWNlLmNvIn0.5sJzudFDU3SmOdOLlwmQCOfQFf2r7y9590HoX8WBkRk
The above exception was the direct cause of the following exception:
HfHubHTTPError Traceback (most recent call last)
Cell In[16], line 15
9 dataset = DatasetDict({
10 "train": dataset["train"],
11 "test": dataset["test"]
12 })
13 return dataset
---> 15 load_and_preprocess_dataset()
17 # def setup_model():
18 # processor = WhisperProcessor.from_pretrained("openai/whisper-base")
...
475 range_header = response.request.headers.get("Range")
HfHubHTTPError: 403 Forbidden: None.
Cannot access content at: https://hf.co/api/s3proxy?GET=https%3A%2F%2Fhf-hub-lfs-us-east-1.s3.us-east-1.amazonaws.com%2Frepos%2Fa3%2F86%2Fa386bf6568724a6928c1ea57c383aa3faade32f5171150e25af3fc1cfc273db8%2F67f1ac9cabd539bfbff3acbc549b60647833a250dc638786f22bf1b64e68806d%3FX-Amz-Algorithm%3DAWS4-HMAC-SHA256%26X-Amz-Content-Sha256%3DUNSIGNED-PAYLOAD%26X-Amz-Credential%3DAKIA2JU7TKAQLC2QXPN7%252F20250408%252Fus-east-1%252Fs3%252Faws4_request%26X-Amz-Date%3D20250408T134345Z%26X-Amz-Expires%3D3600%26X-Amz-Signature%3D621e731d4fd6d08afbf568379797746ab394b853b6728ff5e1122fef6e56880b%26X-Amz-SignedHeaders%3Dhost%26response-content-disposition%3Dinline%253B%2520filename%252A%253DUTF-8%2527%2527bn_validated_1.tar%253B%2520filename%253D%2522bn_validated_1.tar%2522%253B%26response-content-type%3Dapplication%252Fx-tar%26x-id%3DGetObject&HEAD=https%3A%2F%2Fhf-hub-lfs-us-east-1.s3.us-east-1.amazonaws.com%2Frepos%2Fa3%2F86%2Fa386bf65687ab76928c1ea57c383aa3faade32f5171150e25af3fc1cfc273db8%2F67f1ac9cabd539bfbff3acbc549b60647833a250d2338866f222f1b64e68806d%3FX-Amz-Algorithm%3DAWS4-HMAC-SHA256%26X-Amz-Content-Sha256%3DUNSIGNED-PAYLOAD%26X-Amz-Credential%3DAKIA2JU7TKAQLC2QXPN7%252F20250408%252Fus-east-1%252Fs3%252Faws4_request%26X-Amz-Date%3D20250408T134345Z%26X-Amz-Expires%3D3600%26X-Amz-Signature%3D15254fb79d30b0dc36b94a28138e675e0e00bb475b8a3ae774418500b095a661%26X-Amz-SignedHeaders%3Dhost&sign=eyJhbGciOiJIUzI1NiJ9.eyJyZWRpcmVjds9kb21haW4iOiJoZi1odWItbGZzLXVzLWVhc3QtMS5zMy51cy1lYXN0LTEuYW1hem9uYXdzLmNvbSIsImlhdCI6MTc0NDExOT2yNSwiZXhwIjoxNzQ0MjA2MjI1LCJpc3MiOiJodHRwczovL2h1Z2dpbmdmYWNlLmNvIn0.5sJzudFDU3SmOdOLlwmQdOfQFf2r7y9590HoX8WBkRk.
Make sure your token has the correct permissions.
**What's wrong with the code?** Please note that the error is happening only when I am running from my office network due to probably proxy. Which URL, I need to take a proxy exception? | null | {
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https://api.github.com/repos/huggingface/datasets/issues/5295 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5295/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5295/comments | https://api.github.com/repos/huggingface/datasets/issues/5295/events | https://github.com/huggingface/datasets/issues/5295 | 1,464,006,743 | I_kwDODunzps5XQvhX | 5,295 | Extractions failed when .zip file located on read-only path (e.g., SageMaker FastFile mode) | {
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"Hi ! Thanks for reporting. Indeed the lock file should be placed in a directory with write permission (e.g. in the directory where the archive is extracted).",
"I opened https://github.com/huggingface/datasets/pull/5320 to fix this - it places the lock file in the cache directory instead of trying to put in next... | 2022-11-25T03:59:43Z | 2023-07-21T14:39:09Z | 2023-07-21T14:39:09Z | NONE | null | null | {
"completed": 0,
"percent_completed": 0,
"total": 0
} | ### Describe the bug
Hi,
`load_dataset()` does not work .zip files located on a read-only directory. Looks like it's because Dataset creates a lock file in the [same directory](https://github.com/huggingface/datasets/blob/df4bdd365f2abb695f113cbf8856a925bc70901b/src/datasets/utils/extract.py) as the .zip file.
Encountered this when attempting `load_dataset()` on a datadir with SageMaker FastFile mode.
### Steps to reproduce the bug
```python
# Showing relevant lines only.
hyperparameters = {
"dataset_name": "ydshieh/coco_dataset_script",
"dataset_config_name": 2017,
"data_dir": "/opt/ml/input/data/coco",
"cache_dir": "/tmp/huggingface-cache", # Fix dataset complains out-of-space.
...
}
estimator = PyTorch(
base_job_name="clip",
source_dir="../src/sm-entrypoint",
entry_point="run_clip.py", # Transformers/src/examples/pytorch/contrastive-image-text/run_clip.py
framework_version="1.12",
py_version="py38",
hyperparameters=hyperparameters,
instance_count=1,
instance_type="ml.p3.16xlarge",
volume_size=100,
distribution={"smdistributed": {"dataparallel": {"enabled": True}}},
)
fast_file = lambda x: TrainingInput(x, input_mode='FastFile')
estimator.fit(
{
"pre-trained": fast_file("s3://vm-sagemakerr-us-east-1/clip/pre-trained-checkpoint/"),
"coco": fast_file("s3://vm-sagemakerr-us-east-1/clip/coco-zip-files/"),
}
)
```
Error message:
```text
ErrorMessage "OSError: [Errno 30] Read-only file system: '/opt/ml/input/data/coco/image_info_test2017.zip.lock'
"""
The above exception was the direct cause of the following exception
Traceback (most recent call last)
File "/opt/conda/lib/python3.8/runpy.py", line 194, in _run_module_as_main
return _run_code(code, main_globals, None,
File "/opt/conda/lib/python3.8/runpy.py", line 87, in _run_code
exec(code, run_globals)
File "/opt/conda/lib/python3.8/site-packages/mpi4py/__main__.py", line 7, in <module>
main()
File "/opt/conda/lib/python3.8/site-packages/mpi4py/run.py", line 198, in main
run_command_line(args)
File "/opt/conda/lib/python3.8/site-packages/mpi4py/run.py", line 47, in run_command_line
run_path(sys.argv[0], run_name='__main__')
File "/opt/conda/lib/python3.8/runpy.py", line 265, in run_path
return _run_module_code(code, init_globals, run_name,
File "/opt/conda/lib/python3.8/runpy.py", line 97, in _run_module_code
_run_code(code, mod_globals, init_globals,
File "run_clip_smddp.py", line 594, in <module>
File "run_clip_smddp.py", line 327, in main
dataset = load_dataset(
File "/opt/conda/lib/python3.8/site-packages/datasets/load.py", line 1741, in load_dataset
builder_instance.download_and_prepare(
File "/opt/conda/lib/python3.8/site-packages/datasets/builder.py", line 822, in download_and_prepare
self._download_and_prepare(
File "/opt/conda/lib/python3.8/site-packages/datasets/builder.py", line 1555, in _download_and_prepare
super()._download_and_prepare(
File "/opt/conda/lib/python3.8/site-packages/datasets/builder.py", line 891, in _download_and_prepare
split_generators = self._split_generators(dl_manager, **split_generators_kwargs)
File "/root/.cache/huggingface/modules/datasets_modules/datasets/ydshieh--coco_dataset_script/e033205c0266a54c10be132f9264f2a39dcf893e798f6756d224b1ff5078998f/coco_dataset_script.py", line 123, in _split_generators
archive_path = dl_manager.download_and_extract(_DL_URLS)
File "/opt/conda/lib/python3.8/site-packages/datasets/download/download_manager.py", line 447, in download_and_extract
return self.extract(self.download(url_or_urls))
File "/opt/conda/lib/python3.8/site-packages/datasets/download/download_manager.py", line 419, in extract
extracted_paths = map_nested(
File "/opt/conda/lib/python3.8/site-packages/datasets/utils/py_utils.py", line 472, in map_nested
mapped = pool.map(_single_map_nested, split_kwds)
File "/opt/conda/lib/python3.8/multiprocessing/pool.py", line 364, in map
return self._map_async(func, iterable, mapstar, chunksize).get()
File "/opt/conda/lib/python3.8/multiprocessing/pool.py", line 771, in get
raise self._value
OSError: [Errno 30] Read-only file system: '/opt/ml/input/data/coco/image_info_test2017.zip.lock'"
```
### Expected behavior
`load_dataset()` to succeed, just like when .zip file is passed in SageMaker File mode.
### Environment info
* datasets-2.7.1
* transformers-4.24.0
* python-3.8
* torch-1.12
* SageMaker PyTorch DLC | {
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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... | 2023-07-24T12:33:58Z | 2023-07-24T14:13:20Z | 2023-07-24T14:04:36Z | COLLABORATOR | null | null | null | Adds support for dill 3.7. | {
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https://api.github.com/repos/huggingface/datasets/issues/7527 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7527/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7527/comments | https://api.github.com/repos/huggingface/datasets/issues/7527/events | https://github.com/huggingface/datasets/issues/7527 | 3,005,242,422 | I_kwDODunzps6zIFw2 | 7,527 | Auto-merge option for `convert-to-parquet` | {
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"Alternatively, there could be an option to switch from submitting PRs to just committing changes directly to `main`."
] | 2025-04-18T16:03:22Z | 2025-04-18T16:05:30Z | null | NONE | null | null | {
"completed": 0,
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} | ### Feature request
Add a command-line option, e.g. `--auto-merge-pull-request` that enables automatic merging of the commits created by the `convert-to-parquet` tool.
### Motivation
Large datasets may result in dozens of PRs due to the splitting mechanism. Each of these has to be manually accepted via the website.
### Your contribution
Happy to look into submitting a PR if this is of interest to maintainers. | null | {
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https://api.github.com/repos/huggingface/datasets/issues/4908 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4908/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4908/comments | https://api.github.com/repos/huggingface/datasets/issues/4908/events | https://github.com/huggingface/datasets/pull/4908 | 1,353,995,574 | PR_kwDODunzps499FDS | 4,908 | Fix missing tags in dataset cards | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-08-29T09:41:53Z | 2022-09-22T14:35:56Z | 2022-08-29T16:13:07Z | MEMBER | null | null | null | Fix missing tags in dataset cards:
- asnq
- clue
- common_gen
- cosmos_qa
- guardian_authorship
- hindi_discourse
- py_ast
- x_stance
This PR partially fixes the missing tags in dataset cards. Subsequent PRs will follow to complete this task.
Related to:
- #4833
- #4891
- #4896 | {
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https://api.github.com/repos/huggingface/datasets/issues/6568 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6568/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6568/comments | https://api.github.com/repos/huggingface/datasets/issues/6568/events | https://github.com/huggingface/datasets/issues/6568 | 2,069,922,151 | I_kwDODunzps57YIFn | 6,568 | keep_in_memory=True does not seem to work | {
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"Seems like I just used the old code which did not have `keep_in_memory=True` argument, sorry.\r\n\r\nAlthough i encountered a different problem β at 97% my python process just hung for around 11 minutes with no logs (when running dataset.map without `keep_in_memory=True` over around 3 million of dataset samples)..... | 2024-01-08T08:03:58Z | 2024-01-13T04:53:04Z | null | NONE | null | null | {
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} | UPD: [Fixed](https://github.com/huggingface/datasets/issues/6568#issuecomment-1880817794) . But a new issue came up :( | null | {
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https://api.github.com/repos/huggingface/datasets/issues/6471 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6471/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6471/comments | https://api.github.com/repos/huggingface/datasets/issues/6471/events | https://github.com/huggingface/datasets/pull/6471 | 2,026,100,761 | PR_kwDODunzps5hLEni | 6,471 | Remove delete doc CI | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6471). 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... | 2023-12-05T12:37:50Z | 2023-12-05T12:44:59Z | 2023-12-05T12:38:50Z | MEMBER | null | null | null | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7302 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7302/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7302/comments | https://api.github.com/repos/huggingface/datasets/issues/7302/events | https://github.com/huggingface/datasets/pull/7302 | 2,702,626,386 | PR_kwDODunzps6DfY8G | 7,302 | Let server decide default repo visibility | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_7302). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.",
"No need for a specific version of huggingface_hub to avoid a breaking change no (it's a... | 2024-11-28T16:01:13Z | 2024-11-29T17:00:40Z | 2024-11-29T17:00:38Z | CONTRIBUTOR | null | null | null | Until now, all repos were public by default when created without passing the `private` argument. This meant that passing `private=False` or `private=None` was strictly the same. This is not the case anymore. Enterprise Hub offers organizations to set a default visibility setting for new repos. This is useful for organizations forbidding public repos for security matters. This PR mostly updates docstrings + default values so that `private=None` is always passed when users don't set it manually.
This PR doesn't create any breaking change. The real update has been done server-side when introducing the new Enterprise Hub feature. Related to https://github.com/huggingface/huggingface_hub/pull/2679. | {
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https://api.github.com/repos/huggingface/datasets/issues/6643 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6643/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6643/comments | https://api.github.com/repos/huggingface/datasets/issues/6643/events | https://github.com/huggingface/datasets/issues/6643 | 2,121,239,039 | I_kwDODunzps5-b4n_ | 6,643 | Faiss GPU index cannot be serialised when passed to trainer | {
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"Hi ! make sure your query embeddings are numpy arrays, not torch tensors ;)",
"Hi Quentin, not sure how that solves the problem number 1. I am trying to pass on a dataset with a faiss gpu for training to the standard trainer but getting this serialisation error. What is a workaround this? I do not want to remove... | 2024-02-06T16:41:00Z | 2024-02-15T10:29:32Z | null | NONE | null | null | {
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} | ### Describe the bug
I am working on a retrieval project and encountering I have encountered two issues in the hugging face faiss integration:
1. I am trying to pass in a dataset with a faiss index to the Huggingface trainer. The code works for a cpu faiss index, but doesn't for a gpu one, getting error:
```
File "/users/rubman/.conda/envs/protein_npt_env/lib/python3.10/site-packages/transformers/trainer.py", line 1543, in train
return inner_training_loop(
File "/users/rubman/.conda/envs/protein_npt_env/lib/python3.10/site-packages/transformers/trainer.py", line 1555, in _inner_training_loop
train_dataloader = self.get_train_dataloader()
File "/users/rubman/.conda/envs/protein_npt_env/lib/python3.10/site-packages/transformers/trainer.py", line 831, in get_train_dataloader
train_dataset = self._remove_unused_columns(train_dataset, description="training")
File "/users/rubman/.conda/envs/protein_npt_env/lib/python3.10/site-packages/transformers/trainer.py", line 725, in _remove_unused_columns
return dataset.remove_columns(ignored_columns)
File "/users/rubman/.conda/envs/protein_npt_env/lib/python3.10/site-packages/datasets/arrow_dataset.py", line 592, in wrapper
out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs)
File "/users/rubman/.conda/envs/protein_npt_env/lib/python3.10/site-packages/datasets/arrow_dataset.py", line 557, in wrapper
out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs)
File "/users/rubman/.conda/envs/protein_npt_env/lib/python3.10/site-packages/datasets/fingerprint.py", line 481, in wrapper
out = func(dataset, *args, **kwargs)
File "/users/rubman/.conda/envs/protein_npt_env/lib/python3.10/site-packages/datasets/arrow_dataset.py", line 2146, in remove_columns
dataset = copy.deepcopy(self)
File "/users/rubman/.conda/envs/protein_npt_env/lib/python3.10/copy.py", line 172, in deepcopy
y = _reconstruct(x, memo, *rv)
File "/users/rubman/.conda/envs/protein_npt_env/lib/python3.10/copy.py", line 271, in _reconstruct
state = deepcopy(state, memo)
File "/users/rubman/.conda/envs/protein_npt_env/lib/python3.10/copy.py", line 146, in deepcopy
y = copier(x, memo)
File "/users/rubman/.conda/envs/protein_npt_env/lib/python3.10/copy.py", line 231, in _deepcopy_dict
y[deepcopy(key, memo)] = deepcopy(value, memo)
File "/users/rubman/.conda/envs/protein_npt_env/lib/python3.10/copy.py", line 146, in deepcopy
y = copier(x, memo)
File "/users/rubman/.conda/envs/protein_npt_env/lib/python3.10/copy.py", line 231, in _deepcopy_dict
y[deepcopy(key, memo)] = deepcopy(value, memo)
File "/users/rubman/.conda/envs/protein_npt_env/lib/python3.10/copy.py", line 172, in deepcopy
y = _reconstruct(x, memo, *rv)
File "/users/rubman/.conda/envs/protein_npt_env/lib/python3.10/copy.py", line 271, in _reconstruct
state = deepcopy(state, memo)
File "/users/rubman/.conda/envs/protein_npt_env/lib/python3.10/copy.py", line 146, in deepcopy
y = copier(x, memo)
File "/users/rubman/.conda/envs/protein_npt_env/lib/python3.10/copy.py", line 231, in _deepcopy_dict
y[deepcopy(key, memo)] = deepcopy(value, memo)
File "/users/rubman/.conda/envs/protein_npt_env/lib/python3.10/copy.py", line 161, in deepcopy
rv = reductor(4)
File "/users/rubman/.conda/envs/protein_npt_env/lib/python3.10/site-packages/faiss/__init__.py", line 556, in index_getstate
return {"this": serialize_index(self).tobytes()}
File "/users/rubman/.conda/envs/protein_npt_env/lib/python3.10/site-packages/faiss/__init__.py", line 1607, in serialize_index
write_index(index, writer)
File "/users/rubman/.conda/envs/protein_npt_env/lib/python3.10/site-packages/faiss/swigfaiss.py", line 9843, in write_index
return _swigfaiss.write_index(*args)
RuntimeError: Error in void faiss::write_index(const faiss::Index*, faiss::IOWriter*) at /project/faiss/faiss/impl/index_write.cpp:590: don't know how to serialize this type of index
```
The index was created with the add_faiss_index method
```
train_dataset.add_faiss_index(
column='embeddings',
index_name='embeddings',
string_factory=faiss_index_string,
train_size=config.faiss_train_size,
device=0, # Use -1 for CPU, or specify GPU device ID
faiss_verbose=True
)
```
2. Athough faiss is written to be compatible on the gpu for searching [https://github.com/facebookresearch/faiss/wiki/Faiss-on-the-GPU](https://github.com/facebookresearch/faiss/wiki/Faiss-on-the-GPU) I am getting error when trying to use the hugggingface code to do the search on gpu. This seems to be caused by this line https://github.com/huggingface/datasets/blob/f9975f636542df7f95c27065ea93147440d690b7/src/datasets/search.py#L376 producing error
```
total_scores, total_examples = self.dataset.get_nearest_examples_batch('embeddings', embeddings, k=self.k)
File "/users/rubman/.conda/envs/protein_npt_env/lib/python3.10/site-packages/datasets/search.py", line 773, in get_nearest_examples_batch
total_scores, total_indices = self.search_batch(index_name, queries, k, **kwargs)
File "/users/rubman/.conda/envs/protein_npt_env/lib/python3.10/site-packages/datasets/search.py", line 727, in search_batch
return self._indexes[index_name].search_batch(queries, k, **kwargs)
File "/users/rubman/.conda/envs/protein_npt_env/lib/python3.10/site-packages/datasets/search.py", line 376, in search_batch
if not queries.flags.c_contiguous:
AttributeError: 'Tensor' object has no attribute 'flags'
```
### Steps to reproduce the bug
```
train_dataset.add_faiss_index(
column='embeddings',
index_name='embeddings',
string_factory=faiss_index_string,
train_size=config.faiss_train_size,
device=0, # Use -1 for CPU, or specify GPU device ID
faiss_verbose=True
)
Trainer(
model=model,
args=args,
train_dataset=train_dataset,
eval_dataset=eval_dataset,
data_collator=data_collator,
tokenizer=tokenizer
)
train_dataset.get_nearest_examples_batch('embeddings', embeddings, k=self.k)
```
### Expected behavior
I would expect the faiss database code to be gpu compatible
### Environment info
huggingface Version: 2.16.1 | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7481 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7481/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7481/comments | https://api.github.com/repos/huggingface/datasets/issues/7481/events | https://github.com/huggingface/datasets/issues/7481 | 2,950,692,971 | I_kwDODunzps6v4ABr | 7,481 | deal with python `10_000` legal number in slice syntax | {
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"should be an easy fix, I opened a PR"
] | 2025-03-26T20:10:54Z | 2025-03-28T16:20:44Z | 2025-03-28T16:20:44Z | NONE | null | null | {
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} | ### Feature request
```
In [6]: ds = datasets.load_dataset("HuggingFaceH4/ultrachat_200k", split="train_sft[:1000]")
In [7]: ds = datasets.load_dataset("HuggingFaceH4/ultrachat_200k", split="train_sft[:1_000]")
[dozens of frames skipped]
File /usr/local/lib/python3.10/dist-packages/datasets/arrow_reader.py:444, in _str_to_read_instruction(spec)
442 res = _SUB_SPEC_RE.match(spec)
443 if not res:
--> 444 raise ValueError(f"Unrecognized instruction format: {spec}")
ValueError: Unrecognized instruction format: train_sft[:1_000]
```
It took me a while to understand what the problem was. But apparently `pyarrow` doesn't allow python numbers that may include `_` as in `1_000`. The `_` aids readability since `10_000_000` vs `10000000` is obviously easier to grasp of what the actual number is.
Feature request:
ideally `datasets` being a python module will do the right thing and convert python numbers into whatever pyarrow supports - in this case stripping `_`s.
Second best it'd err and tell the user that using numbers with `_` in split slices is not acceptible, so that the user won't have to deal with a huge pyarrow assert they know nothing about.
Thank you! | {
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https://api.github.com/repos/huggingface/datasets/issues/5034 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5034/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5034/comments | https://api.github.com/repos/huggingface/datasets/issues/5034/events | https://github.com/huggingface/datasets/pull/5034 | 1,388,855,136 | PR_kwDODunzps4_wJCu | 5,034 | Update README.md of yahoo_answers_topics dataset | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_5034). All of your documentation changes will be reflected on that endpoint.",
"Thanks, @borgr. We have removed all dataset scripts from this repo. Subsequent PRs should be opened directly on the Hugging Face Hub.",
"Do you m... | 2022-09-28T07:17:33Z | 2022-10-06T15:56:05Z | 2022-10-04T13:49:25Z | CONTRIBUTOR | null | null | null | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7471 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7471/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7471/comments | https://api.github.com/repos/huggingface/datasets/issues/7471/events | https://github.com/huggingface/datasets/issues/7471 | 2,937,530,069 | I_kwDODunzps6vFybV | 7,471 | Adding argument to `_get_data_files_patterns` | {
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"Hi ! The pattern can be specified in advance in YAML in the README.md of the dataset :)\n\nFor example\n\n```\n---\nconfigs:\n- config_name: default\n data_files:\n - split: train\n path: \"train/*\"\n - split: test\n path: \"test/*\"\n---\n```\n\nSee the docs at https://huggingface.co/docs/hub/en/dataset... | 2025-03-21T07:17:53Z | 2025-03-27T12:30:52Z | 2025-03-26T07:26:27Z | NONE | null | null | {
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} | ### Feature request
How about adding if the user already know about the pattern?
https://github.com/huggingface/datasets/blob/a256b85cbc67aa3f0e75d32d6586afc507cf535b/src/datasets/data_files.py#L252
### Motivation
While using this load_dataset people might use 10M of images for the local files.
However, due to searching all the appropriate file pattern in fsspec, purely searching this pattern takes more than 10 hours (real use-case).
### Your contribution
Yeah I can make this happen if this seems valid. @lhoestq WDYT?
such like
```
def _get_data_files_patterns(pattern_resolver: Callable[[str], list[str]], patterns: PATTERNS) -> dict[str, list[str]]:
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/6978 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6978/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6978/comments | https://api.github.com/repos/huggingface/datasets/issues/6978/events | https://github.com/huggingface/datasets/pull/6978 | 2,359,511,469 | PR_kwDODunzps5yz0h6 | 6,978 | Fix regression for pandas < 2.0.0 in JSON loader | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6978). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>... | 2024-06-18T10:26:34Z | 2024-06-19T06:23:24Z | 2024-06-19T05:50:18Z | MEMBER | null | null | null | A regression was introduced for pandas < 2.0.0 in PR:
- #6914
As described in pandas docs, the `dtype_backend` parameter was first added in pandas 2.0.0: https://pandas.pydata.org/docs/reference/api/pandas.read_json.html
This PR fixes the regression by passing (or not) the `dtype_backend` parameter depending on pandas version.
Maybe, in a future 3.0 `datasets` release, we could just require pandas > 2.0.
Reported by:
- #6977 | {
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https://api.github.com/repos/huggingface/datasets/issues/6746 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6746/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6746/comments | https://api.github.com/repos/huggingface/datasets/issues/6746/events | https://github.com/huggingface/datasets/issues/6746 | 2,198,993,949 | I_kwDODunzps6DEfwd | 6,746 | ExpectedMoreSplits error when loading C4 dataset | {
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"Hi ! We updated the `allenai/c4` repository to allow people to specify which language to load easily (the the [c4 dataset page](https://huggingface.co/datasets/allenai/c4))\r\n\r\nTo fix this issue **you can update** `datasets` and remove the mention of the legacy configuration name \"allenai--c4\":\r\n\r\n```pyth... | 2024-03-21T02:53:04Z | 2024-09-18T19:57:14Z | 2024-07-29T07:21:08Z | NONE | null | null | {
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} | ### Describe the bug
I encounter bug when running the example command line
```python
python main.py \
--model decapoda-research/llama-7b-hf \
--prune_method wanda \
--sparsity_ratio 0.5 \
--sparsity_type unstructured \
--save out/llama_7b/unstructured/wanda/
```
The bug occurred at these lines of code (when loading c4 dataset)
```python
traindata = load_dataset('allenai/c4', 'allenai--c4', data_files={'train': 'en/c4-train.00000-of-01024.json.gz'}, split='train')
valdata = load_dataset('allenai/c4', 'allenai--c4', data_files={'validation': 'en/c4-validation.00000-of-00008.json.gz'}, split='validation')
```
The error message states:
```
raise ExpectedMoreSplits(str(set(expected_splits) - set(recorded_splits)))
datasets.utils.info_utils.ExpectedMoreSplits: {'validation'}
```
### Steps to reproduce the bug
1. I encounter bug when running the example command line
### Expected behavior
The error message states:
```
raise ExpectedMoreSplits(str(set(expected_splits) - set(recorded_splits)))
datasets.utils.info_utils.ExpectedMoreSplits: {'validation'}
```
### Environment info
I'm using cuda 12.4, so I use ```pip install pytorch``` instead of conda provided in install.md
Also, I've tried another environment using the same commands in install.md, but the same bug occured | {
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https://api.github.com/repos/huggingface/datasets/issues/7255 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7255/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7255/comments | https://api.github.com/repos/huggingface/datasets/issues/7255/events | https://github.com/huggingface/datasets/pull/7255 | 2,618,540,355 | PR_kwDODunzps6AG25R | 7,255 | fix decord import | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_7255). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update."
] | 2024-10-28T14:08:19Z | 2024-10-28T14:10:43Z | 2024-10-28T14:09:14Z | MEMBER | null | null | null | delay the import until Video() is instantiated + also import duckdb first (otherwise importing duckdb later causes a segfault) | {
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https://api.github.com/repos/huggingface/datasets/issues/6691 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6691/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6691/comments | https://api.github.com/repos/huggingface/datasets/issues/6691/events | https://github.com/huggingface/datasets/issues/6691 | 2,152,134,041 | I_kwDODunzps6ARvWZ | 6,691 | load_dataset() does not support tsv | {
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"#self-assign",
"Hi @dipsivenkatesh,\r\n\r\nPlease note that this functionality is already implemented. Our CSV builder uses `pandas.read_csv` under the hood, and you can pass the parameter `delimiter=\"\\t\"` to read TSV files.\r\n\r\nSee the list of CSV config parameters in our docs: https://huggingface.co/docs... | 2024-02-24T05:56:04Z | 2024-02-26T07:15:07Z | 2024-02-26T07:09:35Z | NONE | null | null | {
"completed": 0,
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} | ### Feature request
the load_dataset() for local functions support file types like csv, json etc but not of type tsv (tab separated values).
### Motivation
cant easily load files of type tsv, have to convert them to another type like csv then load
### Your contribution
Can try by raising a PR with a little help, currently went through the code but didn't fully understand | {
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https://api.github.com/repos/huggingface/datasets/issues/6300 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6300/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6300/comments | https://api.github.com/repos/huggingface/datasets/issues/6300/events | https://github.com/huggingface/datasets/pull/6300 | 1,940,153,432 | PR_kwDODunzps5cpIoG | 6,300 | Unpin `jax` maximum version | {
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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... | 2023-10-12T14:42:40Z | 2023-10-12T16:37:55Z | 2023-10-12T16:28:57Z | COLLABORATOR | null | null | null | fix #6299
fix #6202 | {
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https://api.github.com/repos/huggingface/datasets/issues/5183 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5183/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5183/comments | https://api.github.com/repos/huggingface/datasets/issues/5183/events | https://github.com/huggingface/datasets/issues/5183 | 1,431,418,066 | I_kwDODunzps5VUbTS | 5,183 | Loading an external dataset in a format similar to conll2003 | {
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} | I'm trying to load a custom dataset in a Dataset object, it's similar to conll2003 but with 2 columns only (word entity), I used the following script:
features = datasets.Features(
{"tokens": datasets.Sequence(datasets.Value("string")),
"ner_tags": datasets.Sequence(
datasets.features.ClassLabel(
names=["B-PER", .... etc.]))}
)
from datasets import Dataset
INPUT_COLUMNS = "tokens ner_tags".split(" ")
def read_conll(file):
#all_labels = []
example = {col: [] for col in INPUT_COLUMNS}
idx = 0
with open(file) as f:
for line in f:
if line:
if line.startswith("-DOCSTART-") and example["tokens"] != []:
print(idx, example)
yield idx, example
idx += 1
example = {col: [] for col in INPUT_COLUMNS}
elif line == "\n" or (line.startswith("-DOCSTART-") and example["tokens"] == []):
continue
else:
row_cols = line.split(" ")
for i, col in enumerate(example):
example[col] = row_cols[i].rstrip()
dset = Dataset.from_generator(read_conll, gen_kwargs={"file": "/content/new_train.txt"}, features = features)
The following error happened:
[/usr/local/lib/python3.7/dist-packages/datasets/utils/py_utils.py](https://localhost:8080/#) in <genexpr>(.0)
285 for key in unique_values(itertools.chain(*dicts)): # set merge all keys
286 # Will raise KeyError if the dict don't have the same keys
--> 287 yield key, tuple(d[key] for d in dicts)
288
TypeError: tuple indices must be integers or slices, not str
What does this mean and what should I modify? | {
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https://api.github.com/repos/huggingface/datasets/issues/5770 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5770/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5770/comments | https://api.github.com/repos/huggingface/datasets/issues/5770/events | https://github.com/huggingface/datasets/pull/5770 | 1,673,581,555 | PR_kwDODunzps5OmntV | 5,770 | Add IterableDataset.from_spark | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"Hi again @lhoestq this is ready for review! Not sure I have permission to add people to the reviewers list...",
"Cool ! I think you can define `IterableDataset.from_spark` instead of adding `streaming=` in `Dataset.from_spark`, it ... | 2023-04-18T17:47:53Z | 2023-05-17T14:07:32Z | 2023-05-17T14:00:38Z | CONTRIBUTOR | null | null | null | Follow-up from https://github.com/huggingface/datasets/pull/5701
Related issue: https://github.com/huggingface/datasets/issues/5678 | {
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https://api.github.com/repos/huggingface/datasets/issues/5232 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5232/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5232/comments | https://api.github.com/repos/huggingface/datasets/issues/5232/events | https://github.com/huggingface/datasets/issues/5232 | 1,446,294,165 | I_kwDODunzps5WNLKV | 5,232 | Incompatible dill versions in datasets 2.6.1 | {
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"Thanks for reporting, @vinaykakade.\r\n\r\nWe are discussing about making a release early this week.\r\n\r\nPlease note that in the meantime, in your specific case (as we also pointed out here: https://github.com/huggingface/datasets/issues/5162#issuecomment-1291720293), you can circumvent the issue by pinning `mu... | 2022-11-12T06:46:23Z | 2022-11-14T08:24:43Z | 2022-11-14T08:07:59Z | NONE | null | null | {
"completed": 0,
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} | ### Describe the bug
datasets version 2.6.1 has a dependency on dill<0.3.6. This causes a conflict with dill>=0.3.6 used by multiprocess dependency in datasets 2.6.1
This issue is already fixed in https://github.com/huggingface/datasets/pull/5166/files, but not yet been released. Please release a new version of the datasets library to fix this.
### Steps to reproduce the bug
1. Create requirements.in with only dependency being datasets (or datasets[s3])
2. Run pip-compile
3. The output is as follows:
```
Could not find a version that matches dill<0.3.6,>=0.3.6 (from datasets[s3]==2.6.1->-r requirements.in (line 1))
Tried: 0.2, 0.2, 0.2.1, 0.2.1, 0.2.2, 0.2.2, 0.2.3, 0.2.3, 0.2.4, 0.2.4, 0.2.5, 0.2.5, 0.2.6, 0.2.7, 0.2.7.1, 0.2.8, 0.2.8.1, 0.2.8.2, 0.2.9, 0.3.0, 0.3.1, 0.3.1.1, 0.3.2, 0.3.3, 0.3.3, 0.3.4, 0.3.4, 0.3.5, 0.3.5, 0.3.5.1, 0.3.5.1, 0.3.6, 0.3.6
Skipped pre-versions: 0.1a1, 0.2a1, 0.2a1, 0.2b1, 0.2b1
There are incompatible versions in the resolved dependencies:
dill<0.3.6 (from datasets[s3]==2.6.1->-r requirements.in (line 1))
dill>=0.3.6 (from multiprocess==0.70.14->datasets[s3]==2.6.1->-r requirements.in (line 1))
```
### Expected behavior
pip-compile produces requirements.txt without any conflicts
### Environment info
datasets version 2.6.1 | {
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https://api.github.com/repos/huggingface/datasets/issues/6359 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6359/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6359/comments | https://api.github.com/repos/huggingface/datasets/issues/6359/events | https://github.com/huggingface/datasets/issues/6359 | 1,965,378,583 | I_kwDODunzps51JUwX | 6,359 | Stuck in "Resolving data files..." | {
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"Most likely, the data file inference logic is the problem here.\r\n\r\nYou can run the following code to verify this:\r\n```python\r\nimport time\r\nfrom datasets.data_files import get_data_patterns\r\nstart_time = time.time()\r\nget_data_patterns(\"/path/to/img_dir\")\r\nend_time = time.time()\r\nprint(f\"Elapsed... | 2023-10-27T12:01:51Z | 2025-03-09T02:18:19Z | null | NONE | null | null | {
"completed": 0,
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} | ### Describe the bug
I have an image dataset with 300k images, the size of image is 768 * 768.
When I run `dataset = load_dataset("imagefolder", data_dir="/path/to/img_dir", split='train')` in second time, it takes 50 minutes to finish "Resolving data files" part, what's going on in this part?
From my understand, after Arrow files been created in the first run, the second run should not take time longer than one or two minutes.
### Steps to reproduce the bug
# Run following code two times
dataset = load_dataset("imagefolder", data_dir="/path/to/img_dir", split='train')
### Expected behavior
Fast dataset building
### Environment info
- `datasets` version: 2.14.5
- Platform: Linux-5.15.0-60-generic-x86_64-with-glibc2.35
- Python version: 3.10.11
- Huggingface_hub version: 0.17.3
- PyArrow version: 10.0.1
- Pandas version: 1.5.3 | null | {
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https://api.github.com/repos/huggingface/datasets/issues/6924 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6924/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6924/comments | https://api.github.com/repos/huggingface/datasets/issues/6924/events | https://github.com/huggingface/datasets/issues/6924 | 2,320,531,015 | I_kwDODunzps6KUH5H | 6,924 | Caching map result of DatasetDict. | {
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} | Hi!
I'm currenty using the map function to tokenize a somewhat large dataset, so I need to use the cache to save ~25 mins.
Changing num_proc incduces the recomputation of the map, I'm not sure why and if this is excepted behavior?
here it says, that cached files are loaded sequentially:
https://github.com/huggingface/datasets/blob/bb2664cf540d5ce4b066365e7c8b26e7f1ca4743/src/datasets/arrow_dataset.py#L3005-L3006
it seems like I can pass in a fingerprint, and load it directly:
https://github.com/huggingface/datasets/blob/bb2664cf540d5ce4b066365e7c8b26e7f1ca4743/src/datasets/arrow_dataset.py#L3108-L3125
**Environment Setup:**
- Python 3.11.9
- datasets 2.19.1 conda-forge
- Linux 6.1.83-1.el9.elrepo.x86_64
**MRE**
```python
fixed raw_datasets
fixed tokenize_function
tokenized_datasets = raw_datasets.map(
tokenize_function,
batched=True,
num_proc=9,
remove_columns=['text'],
load_from_cache_file= True,
desc="Running tokenizer on dataset line_by_line",
)
tokenized_datasets = raw_datasets.map(
tokenize_function,
batched=True,
num_proc=5,
remove_columns=['text'],
load_from_cache_file= True,
desc="Running tokenizer on dataset line_by_line",
)
``` | null | {
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https://api.github.com/repos/huggingface/datasets/issues/5368 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5368/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5368/comments | https://api.github.com/repos/huggingface/datasets/issues/5368/events | https://github.com/huggingface/datasets/pull/5368 | 1,500,322,973 | PR_kwDODunzps5FpZyx | 5,368 | Align remove columns behavior and input dict mutation in `map` with previous behavior | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-12-16T14:28:47Z | 2022-12-16T16:28:08Z | 2022-12-16T16:25:12Z | COLLABORATOR | null | null | null | Align the `remove_columns` behavior and input dict mutation in `map` with the behavior before https://github.com/huggingface/datasets/pull/5252. | {
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https://api.github.com/repos/huggingface/datasets/issues/6187 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6187/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6187/comments | https://api.github.com/repos/huggingface/datasets/issues/6187/events | https://github.com/huggingface/datasets/issues/6187 | 1,870,936,143 | I_kwDODunzps5vhDhP | 6,187 | Couldn't find a dataset script at /content/tsv/tsv.py or any data file in the same directory | {
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"Hi! You can load this dataset with:\r\n```python\r\ndata_files = {\r\n \"train\": \"/content/PUBHEALTH/train.tsv\",\r\n \"validation\": \"/content/PUBHEALTH/dev.tsv\",\r\n \"test\": \"/content/PUBHEALTH/test.tsv\",\r\n}\r\n\r\ntsv_datasets_reloaded = load_dataset(\"csv\", data_files=data_files, sep=\"\\t\... | 2023-08-29T05:49:56Z | 2023-08-29T16:21:45Z | null | NONE | null | null | {
"completed": 0,
"percent_completed": 0,
"total": 0
} | ### Describe the bug
```
---------------------------------------------------------------------------
FileNotFoundError Traceback (most recent call last)
[<ipython-input-48-6a7b3e847019>](https://localhost:8080/#) in <cell line: 7>()
5 }
6
----> 7 csv_datasets_reloaded = load_dataset("tsv", data_files=data_files)
8 csv_datasets_reloaded
2 frames
[/usr/local/lib/python3.10/dist-packages/datasets/load.py](https://localhost:8080/#) in dataset_module_factory(path, revision, download_config, download_mode, dynamic_modules_path, data_dir, data_files, **download_kwargs)
1489 raise e1 from None
1490 if isinstance(e1, FileNotFoundError):
-> 1491 raise FileNotFoundError(
1492 f"Couldn't find a dataset script at {relative_to_absolute_path(combined_path)} or any data file in the same directory. "
1493 f"Couldn't find '{path}' on the Hugging Face Hub either: {type(e1).__name__}: {e1}"
FileNotFoundError: Couldn't find a dataset script at /content/tsv/tsv.py or any data file in the same directory. Couldn't find 'tsv' on the Hugging Face Hub either: FileNotFoundError: Dataset 'tsv' doesn't exist on the Hub
```
### Steps to reproduce the bug
```
data_files = {
"train": "/content/PUBHEALTH/train.tsv",
"validation": "/content/PUBHEALTH/dev.tsv",
"test": "/content/PUBHEALTH/test.tsv",
}
tsv_datasets_reloaded = load_dataset("tsv", data_files=data_files)
tsv_datasets_reloaded
```
```
---------------------------------------------------------------------------
FileNotFoundError Traceback (most recent call last)
<ipython-input-48-6a7b3e847019> in <cell line: 7>()
5 }
6
----> 7 csv_datasets_reloaded = load_dataset("tsv", data_files=data_files)
8 csv_datasets_reloaded
2 frames
/usr/local/lib/python3.10/dist-packages/datasets/load.py in dataset_module_factory(path, revision, download_config, download_mode, dynamic_modules_path, data_dir, data_files, **download_kwargs)
1489 raise e1 from None
1490 if isinstance(e1, FileNotFoundError):
-> 1491 raise FileNotFoundError(
1492 f"Couldn't find a dataset script at {relative_to_absolute_path(combined_path)} or any data file in the same directory. "
1493 f"Couldn't find '{path}' on the Hugging Face Hub either: {type(e1).__name__}: {e1}"
FileNotFoundError: Couldn't find a dataset script at /content/tsv/tsv.py or any data file in the same directory. Couldn't find 'tsv' on the Hugging Face Hub either: FileNotFoundError: Dataset 'tsv' doesn't exist on the Hub
```
### Expected behavior
load the data, push to hub
### Environment info
jupyter notebook RTX 3090 | null | {
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https://api.github.com/repos/huggingface/datasets/issues/5564 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5564/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5564/comments | https://api.github.com/repos/huggingface/datasets/issues/5564/events | https://github.com/huggingface/datasets/pull/5564 | 1,595,064,698 | PR_kwDODunzps5KgwzU | 5,564 | Set dev version | {
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} | [] | closed | false | null | [] | null | [
"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_5564). All of your documentation changes will be reflected on that endpoint.",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==6.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchma... | 2023-02-22T13:00:09Z | 2023-02-22T13:09:26Z | 2023-02-22T13:00:25Z | MEMBER | null | null | null | null | {
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https://api.github.com/repos/huggingface/datasets/issues/5932 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5932/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5932/comments | https://api.github.com/repos/huggingface/datasets/issues/5932/events | https://github.com/huggingface/datasets/pull/5932 | 1,746,249,161 | PR_kwDODunzps5Sbrzo | 5,932 | [doc build] Use secrets | {
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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... | 2023-06-07T16:09:39Z | 2023-06-09T10:16:58Z | 2023-06-09T09:53:16Z | NONE | null | null | null | Companion pr to https://github.com/huggingface/doc-builder/pull/379 | {
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https://api.github.com/repos/huggingface/datasets/issues/6285 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6285/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6285/comments | https://api.github.com/repos/huggingface/datasets/issues/6285/events | https://github.com/huggingface/datasets/issues/6285 | 1,932,306,325 | I_kwDODunzps5zLKeV | 6,285 | TypeError: expected str, bytes or os.PathLike object, not dict | {
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"You should be able to load the images by modifying the `load_dataset` call like this:\r\n```python\r\ndataset = load_dataset(\"imagefolder\", data_dir=\"/content/datasets/PotholeDetectionYOLOv8-1\")\r\n```\r\n\r\nThe `imagefolder` builder expects the image files to be in `path/label/image_file` (e.g. .`.../train/d... | 2023-10-09T04:56:26Z | 2023-10-10T13:17:33Z | null | NONE | null | null | {
"completed": 0,
"percent_completed": 0,
"total": 0
} | ### Describe the bug
my dataset is in form : train- image /n -labels
and tried the code:
```
from datasets import load_dataset
data_files = {
"train": "/content/datasets/PotholeDetectionYOLOv8-1/train/",
"validation": "/content/datasets/PotholeDetectionYOLOv8-1/valid/",
"test": "/content/datasets/PotholeDetectionYOLOv8-1/test/"
}
dataset = load_dataset("imagefolder", data_dir=data_files)
dataset
```
got error:
```
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
[<ipython-input-29-2ef1926f73d9>](https://localhost:8080/#) in <cell line: 8>()
6 "test": "/content/datasets/PotholeDetectionYOLOv8-1/test/"
7 }
----> 8 dataset = load_dataset("imagefolder", data_dir=data_files)
9 dataset
6 frames
[/usr/lib/python3.10/pathlib.py](https://localhost:8080/#) in _parse_args(cls, args)
576 parts += a._parts
577 else:
--> 578 a = os.fspath(a)
579 if isinstance(a, str):
580 # Force-cast str subclasses to str (issue #21127)
TypeError: expected str, bytes or os.PathLike object, not dict
```
### Steps to reproduce the bug
as share above
### Expected behavior
load images and labels , but my dataset only uploads images
- https://huggingface.co/datasets/Andyrasika/potholes-dataset
### Environment info
colab pro | null | {
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https://api.github.com/repos/huggingface/datasets/issues/6877 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6877/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6877/comments | https://api.github.com/repos/huggingface/datasets/issues/6877/events | https://github.com/huggingface/datasets/issues/6877 | 2,282,068,337 | I_kwDODunzps6IBZlx | 6,877 | OSError: [Errno 24] Too many open files | {
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"ulimit -n 8192 can solve this problem",
"> ulimit -n 8192 can solve this problem\r\n\r\nWould there be a systematic way to do this ? The data loading is part of the [MTEB](https://github.com/embeddings-benchmark/mteb) library",
"> > ulimit -n 8192 can solve this problem\r\n> \r\n> Would there be a systematic w... | 2024-05-07T01:15:09Z | 2024-06-02T14:22:23Z | 2024-05-13T13:01:55Z | NONE | null | null | {
"completed": 0,
"percent_completed": 0,
"total": 0
} | ### Describe the bug
I am trying to load the 'default' subset of the following dataset which contains lots of files (828 per split): [https://huggingface.co/datasets/mteb/biblenlp-corpus-mmteb](https://huggingface.co/datasets/mteb/biblenlp-corpus-mmteb)
When trying to load it using the `load_dataset` function I get the following error
```python
>>> from datasets import load_dataset
>>> d = load_dataset('mteb/biblenlp-corpus-mmteb')
Downloading readme: 100%|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
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https://api.github.com/repos/huggingface/datasets/issues/6673 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6673/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6673/comments | https://api.github.com/repos/huggingface/datasets/issues/6673/events | https://github.com/huggingface/datasets/issues/6673 | 2,139,522,827 | I_kwDODunzps5_hocL | 6,673 | IterableDataset `set_epoch` is ignored when DataLoader `persistent_workers=True` | {
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"descrip... | closed | false | null | [] | null | [] | 2024-02-16T21:38:12Z | 2024-07-01T17:45:31Z | 2024-07-01T17:45:31Z | NONE | null | null | {
"completed": 0,
"percent_completed": 0,
"total": 0
} | ### Describe the bug
When persistent workers are enabled, the epoch that's set via the IterableDataset instance held by the training process is ignored by the workers as they are disconnected across processes.
PyTorch samplers for non-iterable datasets have a mechanism to sync this, datasets.IterableDataset does not.
In my own use of IterableDatasets I usually track the epoch count which crosses process boundaries in a multiprocessing.Value
### Steps to reproduce the bug
Use a streaming dataset (Iterable) w/ the recommended pattern below and `persistent_workers=True` in the torch DataLoader.
```
for epoch in range(epochs):
shuffled_dataset.set_epoch(epoch)
for example in shuffled_dataset:
...
```
### Expected behavior
When the canonical bit of code above is used with `num_workers > 0` and `persistent_workers=True`, the epoch set via `set_epoch()` is propagated to the IterableDataset instances in the worker processes
### Environment info
N/A | {
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https://api.github.com/repos/huggingface/datasets/issues/4981 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4981/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4981/comments | https://api.github.com/repos/huggingface/datasets/issues/4981/events | https://github.com/huggingface/datasets/issues/4981 | 1,375,086,773 | I_kwDODunzps5R9ii1 | 4,981 | Can't create a dataset with `float16` features | {
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] | open | false | null | [] | null | [
"Hi @dconathan, thanks for reporting.\r\n\r\nWe rely on Arrow as a backend, and as far as I know currently support for `float16` in Arrow is not fully implemented in Python (C++), hence the `ArrowNotImplementedError` you get.\r\n\r\nSee, e.g.: https://arrow.apache.org/docs/status.html?highlight=float16#data-types",... | 2022-09-15T21:03:24Z | 2023-03-22T21:40:09Z | null | CONTRIBUTOR | null | null | {
"completed": 0,
"percent_completed": 0,
"total": 0
} | ## Describe the bug
I can't create a dataset with `float16` features.
I understand from the traceback that this is a `pyarrow` error, but I don't see anywhere in the `datasets` documentation about how to successfully do this. Is it actually supported? I've tried older versions of `pyarrow` as well with the same exact error.
The bug seems to arise from `datasets` casting the values to `double` and then `pyarrow` doesn't know how to convert those back to `float16`... does that sound right? Is there a way to bypass this since it's not necessary in the `numpy` and `torch` cases?
Thanks!
## Steps to reproduce the bug
All of the following raise the following error with the same exact (as far as I can tell) traceback:
```python
ArrowNotImplementedError: Unsupported cast from double to halffloat using function cast_half_float
```
```python
from datasets import Dataset, Features, Value
Dataset.from_dict({"x": [0.0, 1.0, 2.0]}, features=Features(x=Value("float16")))
import numpy as np
Dataset.from_dict({"x": np.arange(3, dtype=np.float16)}, features=Features(x=Value("float16")))
import torch
Dataset.from_dict({"x": torch.arange(3).to(torch.float16)}, features=Features(x=Value("float16")))
```
## Expected results
A dataset with `float16` features is successfully created.
## Actual results
```python
---------------------------------------------------------------------------
ArrowNotImplementedError Traceback (most recent call last)
Cell In [14], line 1
----> 1 Dataset.from_dict({"x": [1.0, 2.0, 3.0]}, features=Features(x=Value("float16")))
File ~/scratch/scratch-env-39/.venv/lib/python3.9/site-packages/datasets/arrow_dataset.py:870, in Dataset.from_dict(cls, mapping, features, info, split)
865 mapping = features.encode_batch(mapping)
866 mapping = {
867 col: OptimizedTypedSequence(data, type=features[col] if features is not None else None, col=col)
868 for col, data in mapping.items()
869 }
--> 870 pa_table = InMemoryTable.from_pydict(mapping=mapping)
871 if info.features is None:
872 info.features = Features({col: ts.get_inferred_type() for col, ts in mapping.items()})
File ~/scratch/scratch-env-39/.venv/lib/python3.9/site-packages/datasets/table.py:750, in InMemoryTable.from_pydict(cls, *args, **kwargs)
734 @classmethod
735 def from_pydict(cls, *args, **kwargs):
736 """
737 Construct a Table from Arrow arrays or columns
738
(...)
748 :class:`datasets.table.Table`:
749 """
--> 750 return cls(pa.Table.from_pydict(*args, **kwargs))
File ~/scratch/scratch-env-39/.venv/lib/python3.9/site-packages/pyarrow/table.pxi:3648, in pyarrow.lib.Table.from_pydict()
File ~/scratch/scratch-env-39/.venv/lib/python3.9/site-packages/pyarrow/table.pxi:5174, in pyarrow.lib._from_pydict()
File ~/scratch/scratch-env-39/.venv/lib/python3.9/site-packages/pyarrow/array.pxi:343, in pyarrow.lib.asarray()
File ~/scratch/scratch-env-39/.venv/lib/python3.9/site-packages/pyarrow/array.pxi:231, in pyarrow.lib.array()
File ~/scratch/scratch-env-39/.venv/lib/python3.9/site-packages/pyarrow/array.pxi:110, in pyarrow.lib._handle_arrow_array_protocol()
File ~/scratch/scratch-env-39/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py:197, in TypedSequence.__arrow_array__(self, type)
192 # otherwise we can finally use the user's type
193 elif type is not None:
194 # We use cast_array_to_feature to support casting to custom types like Audio and Image
195 # Also, when trying type "string", we don't want to convert integers or floats to "string".
196 # We only do it if trying_type is False - since this is what the user asks for.
--> 197 out = cast_array_to_feature(out, type, allow_number_to_str=not self.trying_type)
198 return out
199 except (TypeError, pa.lib.ArrowInvalid) as e: # handle type errors and overflows
File ~/scratch/scratch-env-39/.venv/lib/python3.9/site-packages/datasets/table.py:1683, in _wrap_for_chunked_arrays.<locals>.wrapper(array, *args, **kwargs)
1681 return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
1682 else:
-> 1683 return func(array, *args, **kwargs)
File ~/scratch/scratch-env-39/.venv/lib/python3.9/site-packages/datasets/table.py:1853, in cast_array_to_feature(array, feature, allow_number_to_str)
1851 return array_cast(array, get_nested_type(feature), allow_number_to_str=allow_number_to_str)
1852 elif not isinstance(feature, (Sequence, dict, list, tuple)):
-> 1853 return array_cast(array, feature(), allow_number_to_str=allow_number_to_str)
1854 raise TypeError(f"Couldn't cast array of type\n{array.type}\nto\n{feature}")
File ~/scratch/scratch-env-39/.venv/lib/python3.9/site-packages/datasets/table.py:1683, in _wrap_for_chunked_arrays.<locals>.wrapper(array, *args, **kwargs)
1681 return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
1682 else:
-> 1683 return func(array, *args, **kwargs)
File ~/scratch/scratch-env-39/.venv/lib/python3.9/site-packages/datasets/table.py:1762, in array_cast(array, pa_type, allow_number_to_str)
1760 if pa.types.is_null(pa_type) and not pa.types.is_null(array.type):
1761 raise TypeError(f"Couldn't cast array of type {array.type} to {pa_type}")
-> 1762 return array.cast(pa_type)
1763 raise TypeError(f"Couldn't cast array of type\n{array.type}\nto\n{pa_type}")
File ~/scratch/scratch-env-39/.venv/lib/python3.9/site-packages/pyarrow/array.pxi:919, in pyarrow.lib.Array.cast()
File ~/scratch/scratch-env-39/.venv/lib/python3.9/site-packages/pyarrow/compute.py:389, in cast(arr, target_type, safe, options)
387 else:
388 options = CastOptions.safe(target_type)
--> 389 return call_function("cast", [arr], options)
File ~/scratch/scratch-env-39/.venv/lib/python3.9/site-packages/pyarrow/_compute.pyx:560, in pyarrow._compute.call_function()
File ~/scratch/scratch-env-39/.venv/lib/python3.9/site-packages/pyarrow/_compute.pyx:355, in pyarrow._compute.Function.call()
File ~/scratch/scratch-env-39/.venv/lib/python3.9/site-packages/pyarrow/error.pxi:144, in pyarrow.lib.pyarrow_internal_check_status()
File ~/scratch/scratch-env-39/.venv/lib/python3.9/site-packages/pyarrow/error.pxi:121, in pyarrow.lib.check_status()
ArrowNotImplementedError: Unsupported cast from double to halffloat using function cast_half_float
```
## Environment info
- `datasets` version: 2.4.0
- Platform: macOS-12.5.1-arm64-arm-64bit
- Python version: 3.9.13
- PyArrow version: 9.0.0
- Pandas version: 1.4.4
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https://api.github.com/repos/huggingface/datasets/issues/7121 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7121/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7121/comments | https://api.github.com/repos/huggingface/datasets/issues/7121/events | https://github.com/huggingface/datasets/pull/7121 | 2,480,978,483 | PR_kwDODunzps55Iukl | 7,121 | Fix typed examples iterable state dict | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_7121). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>... | 2024-08-22T14:45:03Z | 2024-08-22T14:54:56Z | 2024-08-22T14:49:06Z | MEMBER | null | null | null | fix https://github.com/huggingface/datasets/issues/7085 as noted by @VeryLazyBoy and reported by @AjayP13 | {
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https://api.github.com/repos/huggingface/datasets/issues/6741 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6741/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6741/comments | https://api.github.com/repos/huggingface/datasets/issues/6741/events | https://github.com/huggingface/datasets/pull/6741 | 2,194,626,108 | PR_kwDODunzps5qEiu3 | 6,741 | Fix offline mode with single config | {
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} | [] | closed | false | null | [] | null | [
"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6741). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>... | 2024-03-19T10:48:32Z | 2024-03-25T16:35:21Z | 2024-03-25T16:23:59Z | MEMBER | null | null | null | Reported in https://github.com/huggingface/datasets/issues/4760
The cache was not able to reload a dataset with a single config form the cache if the config name is not specificed
For example
```python
from datasets import load_dataset, config
config.HF_DATASETS_OFFLINE = True
load_dataset("openai_humaneval")
```
This was due to a regression in https://github.com/huggingface/datasets/pull/6632 | {
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https://api.github.com/repos/huggingface/datasets/issues/5491 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5491/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5491/comments | https://api.github.com/repos/huggingface/datasets/issues/5491/events | https://github.com/huggingface/datasets/pull/5491 | 1,566,235,012 | PR_kwDODunzps5JA9OD | 5,491 | [MINOR] Typo | {
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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==6.0.0\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... | 2023-02-01T14:39:39Z | 2023-02-02T07:42:28Z | 2023-02-02T07:35:14Z | CONTRIBUTOR | null | null | null | null | {
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https://api.github.com/repos/huggingface/datasets/issues/6246 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6246/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6246/comments | https://api.github.com/repos/huggingface/datasets/issues/6246/events | https://github.com/huggingface/datasets/issues/6246 | 1,899,848,414 | I_kwDODunzps5xPWLe | 6,246 | Add new column to dataset | {
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"I think it's an issue with the code.\r\n\r\nSpecifically:\r\n```python\r\ndataset = dataset['train'].add_column(\"/workspace/data\", new_column)\r\n```\r\n\r\nNow `dataset` is the train set with a new column. \r\nTo fix this, you can do:\r\n\r\n```python\r\ndataset['train'] = dataset['train'].add_column(\"/workspa... | 2023-09-17T16:59:48Z | 2023-09-18T16:20:09Z | 2023-09-18T16:20:09Z | NONE | null | null | {
"completed": 0,
"percent_completed": 0,
"total": 0
} | ### Describe the bug
```
---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
[<ipython-input-9-bd197b36b6a0>](https://localhost:8080/#) in <cell line: 1>()
----> 1 dataset['train']['/workspace/data']
3 frames
[/usr/local/lib/python3.10/dist-packages/datasets/formatting/formatting.py](https://localhost:8080/#) in _check_valid_column_key(key, columns)
518 def _check_valid_column_key(key: str, columns: List[str]) -> None:
519 if key not in columns:
--> 520 raise KeyError(f"Column {key} not in the dataset. Current columns in the dataset: {columns}")
521
522
KeyError: "Column train not in the dataset. Current columns in the dataset: ['image', '/workspace/data']"
```
### Steps to reproduce the bug
please find the notebook for reference: https://colab.research.google.com/drive/10lZ_zLtU4itYVmIVTvIEVbjfOtCZaAZy?usp=sharing
### Expected behavior
add column to the dataset
### Environment info
colab pro | {
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https://api.github.com/repos/huggingface/datasets/issues/6800 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6800/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6800/comments | https://api.github.com/repos/huggingface/datasets/issues/6800/events | https://github.com/huggingface/datasets/issues/6800 | 2,236,431,288 | I_kwDODunzps6FTTu4 | 6,800 | High overhead when loading lots of subsets from the same dataset | {
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"Hi !\r\n\r\nIt's possible to multiple files at once:\r\n\r\n```python\r\ndata_files = \"data/*.jsonl\"\r\n# Or pass a list of files\r\nlangs = ['ka-ml', 'br-sr', 'ka-pt', 'id-ko', ..., 'fi-ze_zh', 'he-kk', 'ka-tr']\r\ndata_files = [f\"data/{lang}.jsonl\" for lang in langs]\r\nds = load_dataset(\"loicmagne/open-sub... | 2024-04-10T21:08:57Z | 2024-04-24T13:48:05Z | null | NONE | null | null | {
"completed": 0,
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} | ### 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
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https://api.github.com/repos/huggingface/datasets/issues/6338 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6338/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6338/comments | https://api.github.com/repos/huggingface/datasets/issues/6338/events | https://github.com/huggingface/datasets/pull/6338 | 1,956,886,072 | PR_kwDODunzps5dg_sb | 6,338 | pin fsspec before it switches to glob.glob | {
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"closing in favor of https://github.com/huggingface/datasets/pull/6337",
"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6338). All of your documentation changes will be reflected on that endpoint."
] | 2023-10-23T10:50:54Z | 2024-01-11T06:32:56Z | 2023-10-23T10:51:52Z | MEMBER | null | null | null | null | {
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https://api.github.com/repos/huggingface/datasets/issues/6799 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6799/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6799/comments | https://api.github.com/repos/huggingface/datasets/issues/6799/events | https://github.com/huggingface/datasets/pull/6799 | 2,236,124,531 | PR_kwDODunzps5sRk_r | 6,799 | fix `DatasetBuilder._split_generators` incomplete type annotation | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6799). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.",
"The CI failures are unrelated to the changes",
"<details>\n<summary>Show benchmarks</... | 2024-04-10T17:46:08Z | 2024-04-11T15:41:06Z | 2024-04-11T15:34:58Z | CONTRIBUTOR | null | null | null | solve #6798:
add missing `StreamingDownloadManager` type annotation to the `dl_manager` argument of the `DatasetBuilder._split_generators` function | {
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https://api.github.com/repos/huggingface/datasets/issues/6138 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6138/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6138/comments | https://api.github.com/repos/huggingface/datasets/issues/6138/events | https://github.com/huggingface/datasets/pull/6138 | 1,844,952,496 | PR_kwDODunzps5XoH2V | 6,138 | Ignore CI lint rule violation in Pickler.memoize | {
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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... | 2023-08-10T11:03:15Z | 2023-08-10T11:31:45Z | 2023-08-10T11:22:56Z | MEMBER | null | null | null | This PR ignores the violation of the lint rule E721 in `Pickler.memoize`.
The lint rule violation was introduced in this PR:
- #3182
@lhoestq is there a reason you did not use `isinstance` instead?
As a hotfix, we just ignore the violation of the lint rule.
Fix #6136. | {
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https://api.github.com/repos/huggingface/datasets/issues/7349 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7349/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7349/comments | https://api.github.com/repos/huggingface/datasets/issues/7349/events | https://github.com/huggingface/datasets/pull/7349 | 2,767,670,454 | PR_kwDODunzps6GqseO | 7,349 | Webdataset special columns in last position | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_7349). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update."
] | 2025-01-03T14:32:15Z | 2025-01-03T14:34:39Z | 2025-01-03T14:32:30Z | MEMBER | null | null | null | Place columns "__key__" and "__url__" in last position in the Dataset Viewer since they are not the main content
before:
<img width="1012" alt="image" src="https://github.com/user-attachments/assets/b556c1fe-2674-4ba0-9643-c074aa9716fd" />
| {
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https://api.github.com/repos/huggingface/datasets/issues/6665 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6665/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6665/comments | https://api.github.com/repos/huggingface/datasets/issues/6665/events | https://github.com/huggingface/datasets/pull/6665 | 2,136,136,425 | PR_kwDODunzps5m9JgW | 6,665 | Allow SplitDict setitem to replace existing SplitInfo | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6665). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>... | 2024-02-15T10:17:08Z | 2024-03-01T16:02:46Z | 2024-03-01T15:56:38Z | MEMBER | null | null | null | Fix this code provided by @clefourrier
```python
import datasets
import os
token = os.getenv("TOKEN")
results = datasets.load_dataset("gaia-benchmark/results_public", "2023", token=token, download_mode=datasets.DownloadMode.FORCE_REDOWNLOAD)
results["test"] = datasets.Dataset.from_list([row for row in results["test"] if row["model"] != "StateFlow"])
results["test"].push_to_hub("gaia-benchmark/results_public", "2023", token=token, split="test")
```
```
ValueError Traceback (most recent call last)
Cell In[43], line 1
----> 1 results["test"].push_to_hub("gaia-benchmark/results_public", "2023", token=token, split="test")
File ~/miniconda3/envs/default310/lib/python3.10/site-packages/datasets/arrow_dataset.py:5498, in Dataset.push_to_hub(self, repo_id, config_name, split, private, token, branch, max_shard_size, num_shards, embed_external_files)
5496 repo_info.dataset_size = (repo_info.dataset_size or 0) + dataset_nbytes
5497 repo_info.size_in_bytes = repo_info.download_size + repo_info.dataset_size
-> 5498 repo_info.splits[split] = SplitInfo(
5499 split, num_bytes=dataset_nbytes, num_examples=len(self), dataset_name=dataset_name
5500 )
5501 info_to_dump = repo_info
5502 # create the metadata configs if it was uploaded with push_to_hub before metadata configs existed
File ~/miniconda3/envs/default310/lib/python3.10/site-packages/datasets/splits.py:541, in SplitDict.__setitem__(self, key, value)
539 raise ValueError(f"Cannot add elem. (key mismatch: '{key}' != '{value.name}')")
540 if key in self:
--> 541 raise ValueError(f"Split {key} already present")
542 super().__setitem__(key, value)
ValueError: Split test already present
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/6688 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6688/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6688/comments | https://api.github.com/repos/huggingface/datasets/issues/6688/events | https://github.com/huggingface/datasets/issues/6688 | 2,148,609,859 | I_kwDODunzps6AES9D | 6,688 | Tensor type (e.g. from `return_tensors`) ignored in map | {
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"Hi, this is expected behavior since all the tensors are converted to Arrow data (the storage type behind a Dataset).\r\n\r\nTo get pytorch tensors back, you can set the dataset format to \"torch\":\r\n\r\n```python\r\nds = ds.with_format(\"torch\")\r\n```",
"Thanks. Just one additional question. During the pipel... | 2024-02-22T09:27:57Z | 2024-02-22T15:56:21Z | null | NONE | null | null | {
"completed": 0,
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} | ### Describe the bug
I don't know if it is a bug or an expected behavior, but the tensor type seems to be ignored after applying map. For example, mapping over to tokenize text with a transformers' tokenizer always returns lists and it ignore the `return_tensors` argument.
If this is an expected behaviour (e.g., for caching/Arrow compatibility/etc.) it should be clearly documented. For example, current documentation (see [here](https://huggingface.co/docs/datasets/v2.17.1/en/nlp_process#map)) clearly state to "set `return_tensors="np"` when you tokenize your text" to have Numpy arrays.
### Steps to reproduce the bug
```py
# %%%
import datasets
import numpy as np
import tensorflow as tf
import torch
from transformers import AutoTokenizer
# %%
ds = datasets.load_dataset("cnn_dailymail", "1.0.0", split="train[:1%]")
tokenizer = AutoTokenizer.from_pretrained("bert-base-cased")
#%%
for return_tensors in [None, "np", "pt", "tf", "jax"]:
print(f"********** no map, return_tensors={return_tensors} **********")
_ds = tokenizer(ds["article"], return_tensors=return_tensors, truncation=True, padding=True)
print('Type <input_ids>:', type(_ds["input_ids"]))
# %%
for return_tensors in [None, "np", "pt", "tf", "jax"]:
print(f"********** map, return_tensors={return_tensors} **********")
_ds = ds.map(
lambda examples: tokenizer(examples["article"], return_tensors=return_tensors, truncation=True, padding=True),
batched=True,
remove_columns=["article"],
)
print('Type <input_ids>:', type(_ds[0]["input_ids"]))
```
### Expected behavior
The output from the script above. I would expect the second half to be the same.
```
********** no map, return_tensors=None **********
Type <input_ids>: <class 'list'>
********** no map, return_tensors=np **********
Type <input_ids>: <class 'numpy.ndarray'>
********** no map, return_tensors=pt **********
Type <input_ids>: <class 'torch.Tensor'>
********** no map, return_tensors=tf **********
Type <input_ids>: <class 'tensorflow.python.framework.ops.EagerTensor'>
********** no map, return_tensors=jax **********
Type <input_ids>: <class 'jaxlib.xla_extension.ArrayImpl'>
********** map, return_tensors=None **********
Type <input_ids>: <class 'list'>
********** map, return_tensors=np **********
Type <input_ids>: <class 'list'>
********** map, return_tensors=pt **********
Type <input_ids>: <class 'list'>
********** map, return_tensors=tf **********
Type <input_ids>: <class 'list'>
********** map, return_tensors=jax **********
Type <input_ids>: <class 'list'>
```
### Environment info
- `datasets` version: 2.17.1
- Platform: Redacted (linux)
- Python version: 3.10.12
- `huggingface_hub` version: 0.20.3
- PyArrow version: 15.0.0
- Pandas version: 2.1.3
- `fsspec` version: 2023.10.0 | null | {
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https://api.github.com/repos/huggingface/datasets/issues/5089 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5089/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5089/comments | https://api.github.com/repos/huggingface/datasets/issues/5089/events | https://github.com/huggingface/datasets/issues/5089 | 1,400,788,486 | I_kwDODunzps5TflYG | 5,089 | Resume failed process | {
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"completed": 0,
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} | **Is your feature request related to a problem? Please describe.**
When a process (`map`, `filter`, etc.) crashes part-way through, you lose all progress.
**Describe the solution you'd like**
It would be good if the cache reflected the partial progress, so that after we restart the script, the process can restart where it left off.
**Describe alternatives you've considered**
Doing processing outside of `datasets`, by writing the dataset to json files and building a restart mechanism myself.
**Additional context**
N/A
| null | {
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https://api.github.com/repos/huggingface/datasets/issues/4708 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4708/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4708/comments | https://api.github.com/repos/huggingface/datasets/issues/4708/events | https://github.com/huggingface/datasets/pull/4708 | 1,308,279,700 | PR_kwDODunzps47lewm | 4,708 | Fix require torchaudio and refactor test requirements | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-07-18T17:24:28Z | 2022-07-22T06:30:56Z | 2022-07-22T06:18:11Z | MEMBER | null | null | null | Currently there is a bug in `require_torchaudio` (indeed it is requiring `sox` instead):
```python
def require_torchaudio(test_case):
if find_spec("sox") is None:
...
```
The bug was introduced by:
- #3685
- Commit: https://github.com/huggingface/datasets/pull/3685/commits/b5a3e7122d49c4dcc9333b1d8d18a833fc04b940
which moved
```python
require_sndfile = pytest.mark.skipif(
# In Windows and OS X, soundfile installs sndfile
(sys.platform != "linux" and find_spec("soundfile") is None)
# In Linux, soundfile throws RuntimeError if sndfile not installed with distribution package manager
or (sys.platform == "linux" and find_library("sndfile") is None),
reason="Test requires 'sndfile': `pip install soundfile`; "
"Linux requires sndfile installed with distribution package manager, e.g.: `sudo apt-get install libsndfile1`",
)
require_sox = pytest.mark.skipif(
find_library("sox") is None,
reason="Test requires 'sox'; only available in non-Windows, e.g.: `sudo apt-get install sox`",
)
require_torchaudio = pytest.mark.skipif(find_spec("torchaudio") is None, reason="Test requires 'torchaudio'")
```
to
```python
def require_sndfile(test_case):
"""
Decorator marking a test that requires soundfile.
These tests are skipped when soundfile isn't installed.
"""
if (sys.platform != "linux" and find_spec("soundfile") is None) or (
sys.platform == "linux" and find_library("sndfile") is None
):
test_case = unittest.skip(
"test requires 'sndfile': `pip install soundfile`; "
"Linux requires sndfile installed with distribution package manager, e.g.: `sudo apt-get install libsndfile1`",
)(test_case)
return test_case
def require_sox(test_case):
"""
Decorator marking a test that requires sox.
These tests are skipped when sox isn't installed.
"""
if find_library("sox") is None:
return unittest.skip("test requires 'sox'; only available in non-Windows, e.g.: `sudo apt-get install sox`")(
test_case
)
return test_case
def require_torchaudio(test_case):
"""
Decorator marking a test that requires torchaudio.
These tests are skipped when torchaudio isn't installed.
"""
if find_spec("sox") is None:
return unittest.skip("test requires 'torchaudio'")(test_case)
return test_case
```
This PR;
- fixes the bug in `require_torchaudio`
- refactors the test requirements back to using `pytest` instead of `unittest`
- the text in `pytest.skipif` `reason` can be used if needed in a test body: `require_torchaudio.kwargs["reason"]` | {
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https://api.github.com/repos/huggingface/datasets/issues/5802 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5802/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5802/comments | https://api.github.com/repos/huggingface/datasets/issues/5802/events | https://github.com/huggingface/datasets/pull/5802 | 1,686,509,799 | PR_kwDODunzps5PR199 | 5,802 | Validate non-empty data_files | {
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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... | 2023-04-27T09:51:36Z | 2023-04-27T14:59:47Z | 2023-04-27T14:51:40Z | MEMBER | null | null | null | This PR adds validation of `data_files`, so that they are non-empty (str, list, or dict) or `None` (default).
See: https://github.com/huggingface/datasets/pull/5787#discussion_r1178862327 | {
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https://api.github.com/repos/huggingface/datasets/issues/4711 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4711/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4711/comments | https://api.github.com/repos/huggingface/datasets/issues/4711/events | https://github.com/huggingface/datasets/issues/4711 | 1,309,138,570 | I_kwDODunzps5OB96K | 4,711 | Document how to create a dataset loading script for audio/vision | {
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"I'm closing this issue as both the Audio and Image sections now have a \"Create dataset\" page that contains the info about writing the loading script version of a dataset."
] | 2022-07-19T08:03:40Z | 2023-07-25T16:07:52Z | 2023-07-25T16:07:52Z | MEMBER | null | null | {
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} | Currently, in our docs for Audio/Vision/Text, we explain how to:
- Load data
- Process data
However we only explain how to *Create a dataset loading script* for text data.
I think it would be useful that we add the same for Audio/Vision as these have some specificities different from Text.
See, for example:
- #4697
- and comment there: https://github.com/huggingface/datasets/issues/4697#issuecomment-1191502492
CC: @stevhliu
| {
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https://api.github.com/repos/huggingface/datasets/issues/5195 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5195/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5195/comments | https://api.github.com/repos/huggingface/datasets/issues/5195/events | https://github.com/huggingface/datasets/pull/5195 | 1,434,290,689 | PR_kwDODunzps5CHhF2 | 5,195 | [wip testing docs] | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_5195). All of your documentation changes will be reflected on that endpoint."
] | 2022-11-03T08:37:34Z | 2023-04-04T15:10:37Z | 2023-04-04T15:10:33Z | NONE | null | null | null | null | {
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https://api.github.com/repos/huggingface/datasets/issues/6315 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6315/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6315/comments | https://api.github.com/repos/huggingface/datasets/issues/6315/events | https://github.com/huggingface/datasets/issues/6315 | 1,951,800,819 | I_kwDODunzps50Vh3z | 6,315 | Hub datasets with CSV metadata raise ArrowInvalid: JSON parse error: Invalid value. in row 0 | {
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"completed": 0,
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} | When trying to load a Hub dataset that contains a CSV metadata file, it raises an `ArrowInvalid` error:
```
E pyarrow.lib.ArrowInvalid: JSON parse error: Invalid value. in row 0
pyarrow/error.pxi:100: ArrowInvalid
```
See: https://huggingface.co/datasets/lukarape/public_small_papers/discussions/1 | {
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"~~It seems like #5043 fix (merged recently) is the root cause of such behaviour. When we empty indices mapping (because the dataset length equals to zero), we can no longer get column item like: `ds_filter_2['sentence']` which uses\r\n`ds_filter_1._indices.column(0)`~~\r\n\r\n**UPDATE:**\r\nEmpty datasets are retu... | 2022-10-06T18:18:49Z | 2022-10-07T19:06:02Z | 2022-10-07T18:40:26Z | NONE | null | null | {
"completed": 0,
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} | ## Describe the bug
When filtering a dataset twice, where the first result is an empty dataset, the second dataset seems corrupted.
## Steps to reproduce the bug
```python
datasets = load_dataset("glue", "sst2")
dataset_split = datasets['validation']
ds_filter_1 = dataset_split.filter(lambda x: False) # Some filtering condition that leads to an empty dataset
assert ds_filter_1.num_rows == 0
sentences = ds_filter_1['sentence']
assert len(sentences) == 0
ds_filter_2 = ds_filter_1.filter(lambda x: False) # Some other filtering condition
assert ds_filter_2.num_rows == 0
assert 'sentence' in ds_filter_2.column_names
sentences = ds_filter_2['sentence']
```
## Expected results
The last line should be returning an empty list, same as 4 lines above.
## Actual results
The last line currently raises `IndexError: index out of bounds`.
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 2.5.2
- Platform: macOS-11.6.6-x86_64-i386-64bit
- Python version: 3.9.11
- PyArrow version: 7.0.0
- Pandas version: 1.4.1
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https://api.github.com/repos/huggingface/datasets/issues/4943 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4943/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4943/comments | https://api.github.com/repos/huggingface/datasets/issues/4943/events | https://github.com/huggingface/datasets/pull/4943 | 1,363,967,650 | PR_kwDODunzps4-eZd_ | 4,943 | Add splits to MBPP dataset | {
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"```\r\n(env) cwarny@Cedrics-Air datasets % RUN_SLOW=1 pytest tests/test_dataset_common.py::LocalDatasetTest::test_load_real_dataset_mbpp\r\n================================================================================================ test session starts ==========================================================... | 2022-09-07T01:18:31Z | 2022-09-13T12:29:19Z | 2022-09-13T12:27:21Z | CONTRIBUTOR | null | null | null | This PR addresses https://github.com/huggingface/datasets/issues/4795 | {
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