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I'm training the flux controlnet. The train_dataset.map() takes long time to finish. However, when I killed one training process and want to restart a new training with the same dataset. I can't reuse the mapped result even I defined the cache dir for the dataset.
with accelerator.main_process_... | null | {
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I tried following ways, the cache can't be disabled.
I got 2T data, but I also got more than 2T cache file. I got pressure on storage. I need to diable cache or cleaned immediately after processed. Following ways are all not working, please give some help!
```python
from datasets import ... | null | {
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this also affects push_to_hub which will just upload the local paths of the videos though | {
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https://api.github.com/repos/huggingface/datasets/issues/7254 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7254/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7254/comments | https://api.github.com/repos/huggingface/datasets/issues/7254/events | https://github.com/huggingface/datasets/issues/7254 | 2,616,174,996 | I_kwDODunzps6b76mU | 7,254 | mismatch for datatypes when providing `Features` with `Array2D` and user specified `dtype` and using with_format("numpy") | {
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If the user provides a `Features` type value to `datasets.Dataset` with members having `Array2D` with a value for `dtype`, it is not respected during `with_format("numpy")` which should return a `np.array` with `dtype` that the user provided for `Array2D`. It seems for floats, it will be set to `f... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7253 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7253/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7253/comments | https://api.github.com/repos/huggingface/datasets/issues/7253/events | https://github.com/huggingface/datasets/issues/7253 | 2,615,862,202 | I_kwDODunzps6b6uO6 | 7,253 | Unable to upload a large dataset zip either from command line or UI | {
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Unable to upload a large dataset zip from command line or UI. UI simply says error. I am trying to a upload a tar.gz file of 17GB.
<img width="550" alt="image" src="https://github.com/user-attachments/assets/f9d29024-06c8-49c4-a109-0492cff79d34">
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https://api.github.com/repos/huggingface/datasets/issues/7252 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7252/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7252/comments | https://api.github.com/repos/huggingface/datasets/issues/7252/events | https://github.com/huggingface/datasets/pull/7252 | 2,613,795,544 | PR_kwDODunzps5_41s7 | 7,252 | Add IterableDataset.shard() | {
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I also renamed `.n_shards` -> `.num_shards` for consistency and kept the old name for backward compatibility. And a few changes in internal functions for consistency as well (rank, world_size -> num_shards, index)
Breaking chang... | {
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https://api.github.com/repos/huggingface/datasets/issues/7250 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7250/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7250/comments | https://api.github.com/repos/huggingface/datasets/issues/7250/events | https://github.com/huggingface/datasets/pull/7250 | 2,612,041,969 | PR_kwDODunzps5_zDPS | 7,250 | Basic XML support (mostly copy pasted from text) | {
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https://api.github.com/repos/huggingface/datasets/issues/7249 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7249/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7249/comments | https://api.github.com/repos/huggingface/datasets/issues/7249/events | https://github.com/huggingface/datasets/issues/7249 | 2,610,136,636 | I_kwDODunzps6bk4Y8 | 7,249 | How to debugging | {
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I wanted to use my own script to handle the processing, and followed the tutorial documentation by rewriting the MyDatasetConfig and MyDatasetBuilder (which contains the _info,_split_generators and _generate_examples methods) classes. Testing with simple data was able to output the results of the ... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7248 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7248/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7248/comments | https://api.github.com/repos/huggingface/datasets/issues/7248/events | https://github.com/huggingface/datasets/issues/7248 | 2,609,926,089 | I_kwDODunzps6bkE_J | 7,248 | ModuleNotFoundError: No module named 'datasets.tasks' | {
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---------------------------------------------------------------------------
ModuleNotFoundError Traceback (most recent call last)
[<ipython-input-9-13b5f31bd391>](https://bcb6shpazyu-496ff2e9c6d22116-0-colab.googleusercontent.com/outputframe.html?vrz=colab_20241022-060119_R... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7247 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7247/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7247/comments | https://api.github.com/repos/huggingface/datasets/issues/7247/events | https://github.com/huggingface/datasets/issues/7247 | 2,606,230,029 | I_kwDODunzps6bV-oN | 7,247 | Adding column with dict struction when mapping lead to wrong order | {
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in `map()` function, I want to add a new column with a dict structure.
```
def map_fn(example):
example['text'] = {'user': ..., 'assistant': ...}
return example
```
However this leads to a wrong order `{'assistant':..., 'user':...}` in the dataset.
Thus I can't concatenate two datasets ... | null | {
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follow up to #7234 | {
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https://api.github.com/repos/huggingface/datasets/issues/7243 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7243/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7243/comments | https://api.github.com/repos/huggingface/datasets/issues/7243/events | https://github.com/huggingface/datasets/issues/7243 | 2,602,853,172 | I_kwDODunzps6bJGM0 | 7,243 | ArrayXD with None as leading dim incompatible with DatasetCardData | {
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Creating a dataset with ArrayXD features leads to errors when downloading from hub due to DatasetCardData removing the Nones
@lhoestq
### Steps to reproduce the bug
```python
import numpy as np
from datasets import Array2D, Dataset, Features, load_dataset
def examples_generator():... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7241 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7241/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7241/comments | https://api.github.com/repos/huggingface/datasets/issues/7241/events | https://github.com/huggingface/datasets/issues/7241 | 2,599,899,156 | I_kwDODunzps6a91AU | 7,241 | `push_to_hub` overwrite argument | {
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] | closed | false | null | [] | null | [] | 2024-10-20T03:23:26Z | 2024-10-24T17:39:08Z | 2024-10-24T17:39:08Z | NONE | null | null | null | null | ### Feature request
Add an `overwrite` argument to the `push_to_hub` method.
### Motivation
I want to overwrite a repo without deleting it on Hugging Face. Is this possible? I couldn't find anything in the documentation or tutorials.
### Your contribution
I can create a PR. | {
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https://api.github.com/repos/huggingface/datasets/issues/7240 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7240/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7240/comments | https://api.github.com/repos/huggingface/datasets/issues/7240/events | https://github.com/huggingface/datasets/pull/7240 | 2,598,980,027 | PR_kwDODunzps5_KxSL | 7,240 | Feature Request: Add functionality to pass split types like train, test in DatasetDict.map | {
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} | Hello datasets!
We often encounter situations where we need to preprocess data differently depending on split types such as train, valid, and test.
However, while DatasetDict.map has features to pass rank or index, there's no functionality to pass split types.
Therefore, I propose adding a 'with_splits' parame... | {
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https://api.github.com/repos/huggingface/datasets/issues/7238 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7238/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7238/comments | https://api.github.com/repos/huggingface/datasets/issues/7238/events | https://github.com/huggingface/datasets/issues/7238 | 2,598,409,993 | I_kwDODunzps6a4JcJ | 7,238 | incompatibily issue when using load_dataset with datasets==3.0.1 | {
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There is a bug when using load_dataset with dataset version at 3.0.1 .
Please see below in the "steps to reproduce the bug".
To resolve the bug, I had to downgrade to version 2.21.0
OS: Ubuntu 24 (AWS instance)
Python: same bug under 3.12 and 3.10
The error I had was:
Traceback (most rec... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7236 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7236/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7236/comments | https://api.github.com/repos/huggingface/datasets/issues/7236/events | https://github.com/huggingface/datasets/pull/7236 | 2,597,358,525 | PR_kwDODunzps5_GIvw | 7,236 | [MINOR:TYPO] Update arrow_dataset.py | {
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"url": "https://api.github.com/repos/huggingface/datasets/pulls/... | Fix wrong link.
csv kwargs docstring link was pointing to pandas json docs. | {
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https://api.github.com/repos/huggingface/datasets/issues/7234 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7234/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7234/comments | https://api.github.com/repos/huggingface/datasets/issues/7234/events | https://github.com/huggingface/datasets/pull/7234 | 2,594,220,624 | PR_kwDODunzps5-8Z_- | 7,234 | No need for dataset_info | {
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"url": "https://api.github.com/repos/huggingface/datasets/pulls/... | save a useless call to /api/datasets/repo_id | {
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https://api.github.com/repos/huggingface/datasets/issues/7233 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7233/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7233/comments | https://api.github.com/repos/huggingface/datasets/issues/7233/events | https://github.com/huggingface/datasets/issues/7233 | 2,593,903,113 | I_kwDODunzps6am9IJ | 7,233 | 数据集数量问题 | {
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这里我进行大模型微调，当数据集数量为718时，模型可以正常微调，但是当我添加一个在前718个数据集中的数据或者新增一个数据就会报错
### Steps to reproduce the bug
1.
这里我的数据集可以微调的最后两个数据集是：
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https://api.github.com/repos/huggingface/datasets/issues/7232 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7232/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7232/comments | https://api.github.com/repos/huggingface/datasets/issues/7232/events | https://github.com/huggingface/datasets/pull/7232 | 2,593,720,548 | PR_kwDODunzps5-62rY | 7,232 | (Super tiny doc update) Mention to_polars | {
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https://api.github.com/repos/huggingface/datasets/issues/7231 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7231/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7231/comments | https://api.github.com/repos/huggingface/datasets/issues/7231/events | https://github.com/huggingface/datasets/pull/7231 | 2,592,011,737 | PR_kwDODunzps5-1jP8 | 7,231 | Fix typo in image dataset docs | {
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Typo reported by @datavistics. | {
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https://api.github.com/repos/huggingface/datasets/issues/7230 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7230/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7230/comments | https://api.github.com/repos/huggingface/datasets/issues/7230/events | https://github.com/huggingface/datasets/pull/7230 | 2,589,531,942 | PR_kwDODunzps5-ttUV | 7,230 | Video support | {
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"url": "https://api.github.com/repos/huggingface/datasets/pulls/... | (wip and experimental)
adding the `Video` type based on `VideoReader` from `decord`
```python
>>>from datasets import load_dataset
>>> ds = load_dataset("path/to/videos", split="train").with_format("torch")
>>> print(ds[0]["video"])
<decord.video_reader.VideoReader object at 0x337a47910>
>>> print(ds[0]["vid... | {
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https://api.github.com/repos/huggingface/datasets/issues/7229 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7229/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7229/comments | https://api.github.com/repos/huggingface/datasets/issues/7229/events | https://github.com/huggingface/datasets/pull/7229 | 2,588,847,398 | PR_kwDODunzps5-rgrx | 7,229 | handle config_name=None in push_to_hub | {
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https://api.github.com/repos/huggingface/datasets/issues/7228 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7228/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7228/comments | https://api.github.com/repos/huggingface/datasets/issues/7228/events | https://github.com/huggingface/datasets/issues/7228 | 2,587,310,094 | I_kwDODunzps6aNzgO | 7,228 | Composite (multi-column) features | {
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] | open | false | null | [] | null | [] | 2024-10-14T23:59:19Z | 2024-10-15T11:17:15Z | null | CONTRIBUTOR | null | null | null | null | ### Feature request
Structured data types (graphs etc.) might often be most efficiently stored as multiple columns, which then need to be combined during feature decoding
Although it is currently possible to nest features as structs, my impression is that in particular when dealing with e.g. a feature composed of... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7227 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7227/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7227/comments | https://api.github.com/repos/huggingface/datasets/issues/7227/events | https://github.com/huggingface/datasets/pull/7227 | 2,587,048,312 | PR_kwDODunzps5-l-OE | 7,227 | fast array extraction | {
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} | Implements #7210 using method suggested in https://github.com/huggingface/datasets/pull/7207#issuecomment-2411789307
```python
import numpy as np
from datasets import Dataset, Features, Array3D
features=Features(**{"array0": Array3D((None, 10, 10), dtype="float32"), "array1": Array3D((None,10,10), dtype="float3... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7226 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7226/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7226/comments | https://api.github.com/repos/huggingface/datasets/issues/7226/events | https://github.com/huggingface/datasets/issues/7226 | 2,586,920,351 | I_kwDODunzps6aMUWf | 7,226 | Add R as a How to use from the Polars (R) Library as an option | {
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] | open | false | null | [] | null | [] | 2024-10-14T19:56:07Z | 2024-10-14T19:57:13Z | null | NONE | null | null | null | null | ### Feature request
The boiler plate code to access a dataset via the hugging face file system is very useful. Please addd
## Add Polars (R) option
The equivailent code works, because the [Polars-R](https://github.com/pola-rs/r-polars) wrapper has hugging faces funcitonaliy as well.
```r
library(polars)
... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7225 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7225/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7225/comments | https://api.github.com/repos/huggingface/datasets/issues/7225/events | https://github.com/huggingface/datasets/issues/7225 | 2,586,229,216 | I_kwDODunzps6aJrng | 7,225 | Huggingface GIT returns null as Content-Type instead of application/x-git-receive-pack-result | {
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"gists_url": "h... | [] | open | false | null | [] | null | [] | 2024-10-14T14:33:06Z | 2024-10-14T14:33:06Z | null | NONE | null | null | null | null | ### Describe the bug
We push changes to our datasets programmatically. Our git client jGit reports that the hf git server returns null as Content-Type after a push.
### Steps to reproduce the bug
A basic kotlin application:
```
val person = PersonIdent(
"padmalcom",
"padmalcom@sth.com"
)
... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7224 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7224/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7224/comments | https://api.github.com/repos/huggingface/datasets/issues/7224/events | https://github.com/huggingface/datasets/pull/7224 | 2,583,233,980 | PR_kwDODunzps5-bLNR | 7,224 | fallback to default feature casting in case custom features not available during dataset loading | {
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} | a fix for #7223 in case datasets is happy to support this kind of extensibility! seems cool / powerful for allowing sharing of datasets with potentially different feature types | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7223 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7223/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7223/comments | https://api.github.com/repos/huggingface/datasets/issues/7223/events | https://github.com/huggingface/datasets/issues/7223 | 2,583,231,590 | I_kwDODunzps6Z-Pxm | 7,223 | Fallback to arrow defaults when loading dataset with custom features that aren't registered locally | {
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Datasets allows users to create and register custom features.
However if datasets are then pushed to the hub, this means that anyone calling load_dataset without registering the custom Features in the same way as the dataset creator will get an error message.
It would be nice to offer a fall... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7222 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7222/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7222/comments | https://api.github.com/repos/huggingface/datasets/issues/7222/events | https://github.com/huggingface/datasets/issues/7222 | 2,582,678,033 | I_kwDODunzps6Z8IoR | 7,222 | TypeError: Couldn't cast array of type string to null in long json | {
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In general, changing the type from string to null is allowed within a dataset — there are even examples of this in the documentation.
However, if the dataset is large and unevenly distributed, this allowance stops working. The schema gets locked in after reading a chunk.
Consequently, if al... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7221 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7221/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7221/comments | https://api.github.com/repos/huggingface/datasets/issues/7221/events | https://github.com/huggingface/datasets/pull/7221 | 2,582,114,631 | PR_kwDODunzps5-YNI8 | 7,221 | add CustomFeature base class to support user-defined features with encoding/decoding logic | {
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} | intended as fix for #7220 if this kind of extensibility is something that datasets is willing to support!
```python
from datasets.features.features import CustomFeature
class ListOfStrs(CustomFeature):
requires_encoding = True
def _encode_example(self, value):
if isinstance(value, str):
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https://api.github.com/repos/huggingface/datasets/issues/7220 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7220/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7220/comments | https://api.github.com/repos/huggingface/datasets/issues/7220/events | https://github.com/huggingface/datasets/issues/7220 | 2,582,036,110 | I_kwDODunzps6Z5r6O | 7,220 | Custom features not compatible with special encoding/decoding logic | {
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It is possible to register custom features using datasets.features.features.register_feature (https://github.com/huggingface/datasets/pull/6727)
However such features are not compatible with Features.encode_example/decode_example if they require special encoding / decoding logic because encod... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7219 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7219/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7219/comments | https://api.github.com/repos/huggingface/datasets/issues/7219/events | https://github.com/huggingface/datasets/pull/7219 | 2,581,708,084 | PR_kwDODunzps5-XAQF | 7,219 | bump fsspec | {
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https://api.github.com/repos/huggingface/datasets/issues/7217 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7217/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7217/comments | https://api.github.com/repos/huggingface/datasets/issues/7217/events | https://github.com/huggingface/datasets/issues/7217 | 2,581,095,098 | I_kwDODunzps6Z2GK6 | 7,217 | ds.map(f, num_proc=10) is slower than df.apply | {
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pandas columns: song_id, song_name
ds = Dataset.from_pandas(df)
def has_cover(song_name):
if song_name is None or pd.isna(song_name):
return False
return 'cover' in song_name.lower()
df['has_cover'] = df.song_name.progress_apply(has_cover)
ds = ds.map(lambda x: {'has_cov... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7215 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7215/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7215/comments | https://api.github.com/repos/huggingface/datasets/issues/7215/events | https://github.com/huggingface/datasets/issues/7215 | 2,579,942,939 | I_kwDODunzps6Zxs4b | 7,215 | Iterable dataset map with explicit features causes slowdown for Sequence features | {
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When performing map, it's nice to be able to pass the new feature type, and indeed required by interleave and concatenate datasets.
However, this can cause a major slowdown for certain types of array features due to the features being re-encoded.
This is separate to the slowdown reported i... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7214 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7214/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7214/comments | https://api.github.com/repos/huggingface/datasets/issues/7214/events | https://github.com/huggingface/datasets/issues/7214 | 2,578,743,713 | I_kwDODunzps6ZtIGh | 7,214 | Formatted map + with_format(None) changes array dtype for iterable datasets | {
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When applying with_format -> map -> with_format(None), array dtypes seem to change, even if features are passed
### Steps to reproduce the bug
```python
features=Features(**{"array0": Array3D((None, 10, 10), dtype="float32")})
dataset = Dataset.from_dict({f"array0": [np.zeros((100,10,10... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7213 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7213/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7213/comments | https://api.github.com/repos/huggingface/datasets/issues/7213/events | https://github.com/huggingface/datasets/issues/7213 | 2,578,675,565 | I_kwDODunzps6Zs3dt | 7,213 | Add with_rank to Dataset.from_generator | {
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] | open | false | null | [] | null | [] | 2024-10-10T12:15:29Z | 2024-10-10T12:17:11Z | null | NONE | null | null | null | null | ### Feature request
Add `with_rank` to `Dataset.from_generator` similar to `Dataset.map` and `Dataset.filter`.
### Motivation
As for `Dataset.map` and `Dataset.filter`, this is useful when creating cache files using multi-GPU, where the rank can be used to select GPU IDs. For now, rank can be added in the `ge... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7212 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7212/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7212/comments | https://api.github.com/repos/huggingface/datasets/issues/7212/events | https://github.com/huggingface/datasets/issues/7212 | 2,578,641,259 | I_kwDODunzps6ZsvFr | 7,212 | Windows do not supprot signal.alarm and singal.signal | {
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signal.alarm and signal.signal are used in the load.py module, but these are not supported by Windows.
### Steps to reproduce the bug
lighteval accelerate --model_args "pretrained=gpt2,trust_remote_code=True" --tasks "community|kinit_sts" --custom_tasks "community_tasks/kinit_evals.py" --output... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7211 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7211/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7211/comments | https://api.github.com/repos/huggingface/datasets/issues/7211/events | https://github.com/huggingface/datasets/issues/7211 | 2,576,400,502 | I_kwDODunzps6ZkMB2 | 7,211 | Describe only selected fields in README | {
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] | open | false | null | [] | null | [] | 2024-10-09T16:25:47Z | 2024-10-09T16:25:47Z | null | NONE | null | null | null | null | ### Feature request
Hi Datasets team!
Is it possible to add the ability to describe only selected fields of the dataset files in `README.md`? For example, I have this open dataset ([open-llm-leaderboard/results](https://huggingface.co/datasets/open-llm-leaderboard/results?row=0)) and I want to describe only some f... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7210 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7210/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7210/comments | https://api.github.com/repos/huggingface/datasets/issues/7210/events | https://github.com/huggingface/datasets/issues/7210 | 2,575,883,939 | I_kwDODunzps6ZiN6j | 7,210 | Convert Array features to numpy arrays rather than lists by default | {
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] | open | false | null | [] | null | [] | 2024-10-09T13:05:21Z | 2024-10-09T13:05:21Z | null | CONTRIBUTOR | null | null | null | null | ### Feature request
It is currently quite easy to cause massive slowdowns when using datasets and not familiar with the underlying data conversions by e.g. making bad choices of formatting.
Would it be more user-friendly to set defaults that avoid this as much as possible? e.g. format Array features as numpy arrays... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7209 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7209/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7209/comments | https://api.github.com/repos/huggingface/datasets/issues/7209/events | https://github.com/huggingface/datasets/pull/7209 | 2,575,526,651 | PR_kwDODunzps5-D6_P | 7,209 | Preserve features in iterable dataset.filter | {
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"url": "https://api.github.com/repos/huggingface/datasets/pulls/... | Fixes example in #7208 - I'm not sure what other checks I should do? @lhoestq
I also haven't thought hard about the concatenate / interleaving example iterables but think this might work assuming that features are either all identical or None? | {
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https://api.github.com/repos/huggingface/datasets/issues/7208 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7208/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7208/comments | https://api.github.com/repos/huggingface/datasets/issues/7208/events | https://github.com/huggingface/datasets/issues/7208 | 2,575,484,256 | I_kwDODunzps6ZgsVg | 7,208 | Iterable dataset.filter should not override features | {
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When calling filter on an iterable dataset, the features get set to None
### Steps to reproduce the bug
import numpy as np
import time
from datasets import Dataset, Features, Array3D
```python
features=Features(**{"array0": Array3D((None, 10, 10), dtype="float32"), "array1": Array3D((None,... | {
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https://api.github.com/repos/huggingface/datasets/issues/7207 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7207/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7207/comments | https://api.github.com/repos/huggingface/datasets/issues/7207/events | https://github.com/huggingface/datasets/pull/7207 | 2,573,582,335 | PR_kwDODunzps59-Dms | 7,207 | apply formatting after iter_arrow to speed up format -> map, filter for iterable datasets | {
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"url": "https://api.github.com/repos/huggingface/datasets/pulls/... | I got to this by hacking around a bit but it seems to solve #7206
I have no idea if this approach makes sense or would break something else?
Could maybe work on a full pr if this looks reasonable @lhoestq ? I imagine the same issue might affect other iterable dataset methods? | {
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https://api.github.com/repos/huggingface/datasets/issues/7206 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7206/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7206/comments | https://api.github.com/repos/huggingface/datasets/issues/7206/events | https://github.com/huggingface/datasets/issues/7206 | 2,573,567,467 | I_kwDODunzps6ZZYXr | 7,206 | Slow iteration for iterable dataset with numpy formatting for array data | {
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When working with large arrays, setting with_format to e.g. numpy then applying map causes a significant slowdown for iterable datasets.
### Steps to reproduce the bug
```python
import numpy as np
import time
from datasets import Dataset, Features, Array3D
features=Features(**{"array... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7205 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7205/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7205/comments | https://api.github.com/repos/huggingface/datasets/issues/7205/events | https://github.com/huggingface/datasets/pull/7205 | 2,573,490,859 | PR_kwDODunzps599w0I | 7,205 | fix ci benchmark | {
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I keep the code in case we ever want to re-run the benchmark manually | {
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https://api.github.com/repos/huggingface/datasets/issues/7204 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7204/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7204/comments | https://api.github.com/repos/huggingface/datasets/issues/7204/events | https://github.com/huggingface/datasets/pull/7204 | 2,573,289,063 | PR_kwDODunzps599Hem | 7,204 | fix unbatched arrow map for iterable datasets | {
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"url": "https://api.github.com/repos/huggingface/datasets/pulls/... | Fixes the bug when applying map to an arrow-formatted iterable dataset described here:
https://github.com/huggingface/datasets/issues/6833#issuecomment-2399903885
```python
from datasets import load_dataset
ds = load_dataset("rotten_tomatoes", split="train", streaming=True)
ds = ds.with_format("arrow").map(l... | {
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https://api.github.com/repos/huggingface/datasets/issues/7203 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7203/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7203/comments | https://api.github.com/repos/huggingface/datasets/issues/7203/events | https://github.com/huggingface/datasets/pull/7203 | 2,573,154,222 | PR_kwDODunzps598skr | 7,203 | with_format docstring | {
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"url": "https://api.github.com/repos/huggingface/datasets/pulls/... | reported at https://github.com/huggingface/datasets/issues/3444 | {
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https://api.github.com/repos/huggingface/datasets/issues/7202 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7202/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7202/comments | https://api.github.com/repos/huggingface/datasets/issues/7202/events | https://github.com/huggingface/datasets/issues/7202 | 2,572,583,798 | I_kwDODunzps6ZVoN2 | 7,202 | `from_parquet` return type annotation | {
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As already posted in https://github.com/microsoft/pylance-release/issues/6534, the correct type hinting fails when building a dataset using the `from_parquet` constructor.
Their suggestion is to comprehensively annotate the method's return type to better align with the docstring information.
###... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7201 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7201/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7201/comments | https://api.github.com/repos/huggingface/datasets/issues/7201/events | https://github.com/huggingface/datasets/issues/7201 | 2,569,837,015 | I_kwDODunzps6ZLJnX | 7,201 | `load_dataset()` of images from a single directory where `train.png` image exists | {
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"gist... | [] | open | false | null | [] | null | [] | 2024-10-07T09:14:17Z | 2024-10-07T09:14:17Z | null | NONE | null | null | null | null | ### Describe the bug
Hey!
Firstly, thanks for maintaining such framework!
I had a small issue, where I wanted to load a custom dataset of image+text captioning. I had all of my images in a single directory, and one of the images had the name `train.png`. Then, the loaded dataset had only this image.
I guess it'... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7200 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7200/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7200/comments | https://api.github.com/repos/huggingface/datasets/issues/7200/events | https://github.com/huggingface/datasets/pull/7200 | 2,567,921,694 | PR_kwDODunzps59sgRd | 7,200 | Fix the environment variable for huggingface cache | {
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"url": "https://api.github.com/repos/huggingface/datasets/pulls/... | Resolve #6256. As far as I tested, `HF_DATASETS_CACHE` was ignored and I could not specify the cache directory at all except for the default one by this environment variable. `HF_HOME` has worked. Perhaps the recent change on file downloading by `huggingface_hub` could affect this bug.
In my testing, I could not sp... | {
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https://api.github.com/repos/huggingface/datasets/issues/7199 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7199/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7199/comments | https://api.github.com/repos/huggingface/datasets/issues/7199/events | https://github.com/huggingface/datasets/pull/7199 | 2,566,788,225 | PR_kwDODunzps59pN_M | 7,199 | Add with_rank to Dataset.from_generator | {
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} | Adds `with_rank` to `Dataset.from_generator`. As for `Dataset.map` and `Dataset.filter`, this is useful when creating cache files using multi-GPU. | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7198 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7198/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7198/comments | https://api.github.com/repos/huggingface/datasets/issues/7198/events | https://github.com/huggingface/datasets/pull/7198 | 2,566,064,849 | PR_kwDODunzps59mwgu | 7,198 | Add repeat method to datasets | {
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"url": "https://api.github.com/repos/huggingface/datasets/pulls/... | Following up on discussion in #6623 and #7198 I thought this would be pretty useful for my case so had a go at implementing.
My main motivation is to be able to call iterable_dataset.repeat(None).take(samples_per_epoch) to safely avoid timeout issues in a distributed training setting. This would provide a straightfo... | {
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https://api.github.com/repos/huggingface/datasets/issues/7197 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7197/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7197/comments | https://api.github.com/repos/huggingface/datasets/issues/7197/events | https://github.com/huggingface/datasets/issues/7197 | 2,565,924,788 | I_kwDODunzps6Y8Oe0 | 7,197 | ConnectionError: Couldn't reach 'allenai/c4' on the Hub (ConnectionError)数据集下不下来，怎么回事 | {
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from datasets import load_dataset
print("11")
traindata = load_dataset('ptb_text_only', 'penn_treebank', split='train')
print("22")
valdata = load_dataset('ptb_text_only',
'penn_treebank',
split='validation')
### Steps to reproduce the b... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7196 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7196/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7196/comments | https://api.github.com/repos/huggingface/datasets/issues/7196/events | https://github.com/huggingface/datasets/issues/7196 | 2,564,218,566 | I_kwDODunzps6Y1t7G | 7,196 | concatenate_datasets does not preserve shuffling state | {
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After concatenate datasets on an iterable dataset, the shuffling state is destroyed, similar to #7156
This means concatenation cant be used for resolving uneven numbers of samples across devices when using iterable datasets in a distributed setting as discussed in #6623
I also noticed th... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7195 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7195/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7195/comments | https://api.github.com/repos/huggingface/datasets/issues/7195/events | https://github.com/huggingface/datasets/issues/7195 | 2,564,070,809 | I_kwDODunzps6Y1J2Z | 7,195 | Add support for 3D datasets | {
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https://api.github.com/repos/huggingface/datasets/issues/7194 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7194/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7194/comments | https://api.github.com/repos/huggingface/datasets/issues/7194/events | https://github.com/huggingface/datasets/issues/7194 | 2,563,364,199 | I_kwDODunzps6YydVn | 7,194 | datasets.exceptions.DatasetNotFoundError for private dataset | {
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The following Python code tries to download a private dataset and fails with the error `datasets.exceptions.DatasetNotFoundError: Dataset 'ClimatePolicyRadar/all-document-text-data-weekly' doesn't exist on the Hub or cannot be accessed.`. Downloading a public dataset doesn't work.
``` py
fro... | {
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] | open | false | null | [] | null | [] | 2024-10-02T18:34:04Z | 2024-10-03T09:54:15Z | null | NONE | null | null | null | null | ### Feature request
Currently, IterableDataset doesn't support setting num_worker in .map(), which results in slow processing here. Could we add support for it? As .map() can be run in the batch fashion (e.g., batch_size is default to 1000 in datasets), it seems to be doable for IterableDataset as the regular Dataset.... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7192 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7192/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7192/comments | https://api.github.com/repos/huggingface/datasets/issues/7192/events | https://github.com/huggingface/datasets/issues/7192 | 2,562,289,642 | I_kwDODunzps6YuW_q | 7,192 | Add repeat() for iterable datasets | {
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] | closed | false | null | [] | null | [] | 2024-10-02T17:48:13Z | 2025-03-18T10:48:33Z | 2025-03-18T10:48:32Z | CONTRIBUTOR | null | null | null | null | ### Feature request
It would be useful to be able to straightforwardly repeat iterable datasets indefinitely, to provide complete control over starting and ending of iteration to the user.
An IterableDataset.repeat(n) function could do this automatically
### Motivation
This feature was discussed in this iss... | {
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} | # Feel free to give suggestions please..
### This PR is raised because of issue: https://github.com/huggingface/datasets/issues/7080
### This PR gives solution to https://github.com/huggingface/datasets/issues/7080
1. ... | {
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... | [] | open | false | null | [] | null | [] | 2024-10-02T16:43:46Z | 2024-10-10T07:33:18Z | null | NONE | null | null | null | null | ### Describe the bug
Installing both in latest versions are not possible
`pip install "datasets==3.0.1" "fsspec==2024.9.0"`
But using older version of datasets is ok
`pip install "datasets==1.24.4" "fsspec==2024.9.0"`
### Steps to reproduce the bug
`pip install "datasets==3.0.1" "fsspec==2024.9.0"`
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https://api.github.com/repos/huggingface/datasets/issues/7189 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7189/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7189/comments | https://api.github.com/repos/huggingface/datasets/issues/7189/events | https://github.com/huggingface/datasets/issues/7189 | 2,562,152,845 | I_kwDODunzps6Yt1mN | 7,189 | Audio preview in dataset viewer for audio array data without a path/filename | {
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] | open | false | null | [] | null | [] | 2024-10-02T16:38:38Z | 2024-10-02T17:01:40Z | null | NONE | null | null | null | null | ### Feature request
Huggingface has quite a comprehensive set of guides for [audio datasets](https://huggingface.co/docs/datasets/en/audio_dataset). It seems, however, all these guides assume the audio array data to be decoded/inserted into a HF dataset always originates from individual files. The [Audio-dataclass](... | null | {
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Note that multiprocess-0.70.1 requires dill-0.3.9: https://github.com/uqfoundation/multiprocess/releases/tag/0.70.17
Fix #7186. | {
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```
[rank0]: File "/home/qinghao/miniconda3/envs/doremi/lib/python3.10/site-packages/datasets/iterable_dataset.py", line 238, in __iter__
[rank0]: for key_example in islice(self.generate_examples_fn(**gen_kwags), shard_example_idx_start, None):
[rank0]: File "/home/qinghao/miniconda3/en... | null | {
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The [latest `multiprocess` release](https://github.com/uqfoundation/multiprocess/releases/tag/0.70.17) requires `dill>=0.3.9` which causes issues when installing `datasets` without backtracking during package version resolution. Is it possible to add a pin for multiprocess so something like `multi... | {
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```
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Note that dill-0.3.9 was released yesterday Sep 29, 2024:
- https://pypi.org/project/dill/0.3.9/
- https://github.com/uqfoundation/dill/releases/tag/0.3.9
Fix #7183. | {
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https://api.github.com/repos/huggingface/datasets/issues/7183 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7183/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7183/comments | https://api.github.com/repos/huggingface/datasets/issues/7183/events | https://github.com/huggingface/datasets/issues/7183 | 2,556,789,055 | I_kwDODunzps6YZYE_ | 7,183 | CI is broken for deps-latest | {
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```
=========================== short test summary info ============================
FAILED tests/test_arrow_dataset.py::BaseDatasetTest::test_filter_caching_on_disk - AssertionError: Lists differ: [{'fi[44 chars] {'filename': '/... | {
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https://api.github.com/repos/huggingface/datasets/issues/7182 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7182/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7182/comments | https://api.github.com/repos/huggingface/datasets/issues/7182/events | https://github.com/huggingface/datasets/pull/7182 | 2,556,333,671 | PR_kwDODunzps59GdLS | 7,182 | Support features in metadata configs | {
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"url": "https://api.github.com/repos/huggingface/datasets/pulls/... | Support features in metadata configs, like:
```
configs:
- config_name: default
features:
- name: id
dtype: int64
- name: name
dtype: string
- name: score
dtype: float64
```
This will allow to avoid inference of data types.
Currently, we allow passing th... | {
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https://api.github.com/repos/huggingface/datasets/issues/7180 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7180/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7180/comments | https://api.github.com/repos/huggingface/datasets/issues/7180/events | https://github.com/huggingface/datasets/issues/7180 | 2,554,244,750 | I_kwDODunzps6YPq6O | 7,180 | Memory leak when wrapping datasets into PyTorch Dataset without explicit deletion | {
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I've encountered a memory leak when wrapping the HuggingFace dataset into a PyTorch Dataset. The RAM usage constantly increases during iteration if items are not explicitly deleted after use.
### Steps to reproduce the bug
Steps to reproduce:
Create a PyTorch Dataset wrapper f... | {
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Fix #7178. | {
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During last release, I had to make this additional update. | {
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https://api.github.com/repos/huggingface/datasets/issues/7176 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7176/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7176/comments | https://api.github.com/repos/huggingface/datasets/issues/7176/events | https://github.com/huggingface/datasets/pull/7176 | 2,551,025,564 | PR_kwDODunzps580hTn | 7,176 | fix grammar in fingerprint.py | {
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https://api.github.com/repos/huggingface/datasets/issues/7175 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7175/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7175/comments | https://api.github.com/repos/huggingface/datasets/issues/7175/events | https://github.com/huggingface/datasets/issues/7175 | 2,550,957,337 | I_kwDODunzps6YDIUZ | 7,175 | [FSTimeoutError] load_dataset | {
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When using `load_dataset`to load [HuggingFaceM4/VQAv2](https://huggingface.co/datasets/HuggingFaceM4/VQAv2), I am getting `FSTimeoutError`.
### Error
```
TimeoutError:
The above exception was the direct cause of the following exception:
FSTimeoutError Trac... | {
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Note that previously, `torchdata` was installed from their repo and current main branch (0.10.0.dev) requires Python>=3.9.
Also note they made a recent release: 0.8.0 on Jul 31, 2024.
Fix #7171. | {
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```
Run uv pip install --system -r additional-tests-requirements.txt --no-deps
× No solution found when resolving dependencies:
╰─▶ Because the current Python version (3.8.18) does not satisfy Python>=3.9
and torchdata=... | {
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Fix #7169.
The implemented test raised:
```
datasets.table.CastError: Couldn't cast
age: int64
to
{'age': Value(dtype='int32', id=None), 'name': Value(dtype='string', id=None)}
because column names don't match
```
Related to:
- #7160
- #7162 | {
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> CastError: Couldn't cast ... to ... because column names don't match
Related to:
- #7159
- #7161 | {
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This will randomly pop up during training now
```
Traceback (most recent call last):
File "/workspace/diffusers/examples/controlnet/train_controlnet.py", line 1192, in <module>
main(args)
File "/workspace/diffusers/examples/controlnet/train_controlnet.py", line 1041, in main
... | {
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https://api.github.com/repos/huggingface/datasets/issues/7167 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7167/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7167/comments | https://api.github.com/repos/huggingface/datasets/issues/7167/events | https://github.com/huggingface/datasets/issues/7167 | 2,546,708,014 | I_kwDODunzps6Xy64u | 7,167 | Error Mapping on sd3, sdxl and upcoming flux controlnet training scripts in diffusers | {
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```
Map: 6%|██████ | 8000/138120 [19:27<5:16:36, 6.85 examples/s]
Traceback (most recent call last):
File "/workspace/diffusers/examples/controlnet/train_controlnet_sd3.py", line 1416, in <mod... | {
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I am trying to download the `librispeech_asr` `clean` dataset, which results in a `FSTimeoutError` exception after downloading around 61% of the data.
### Steps to reproduce the bug
```
import datasets
datasets.load_dataset("librispeech_asr", "clean")
```
The output is as follows:
> Dow... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7163 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7163/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7163/comments | https://api.github.com/repos/huggingface/datasets/issues/7163/events | https://github.com/huggingface/datasets/issues/7163 | 2,542,361,234 | I_kwDODunzps6XiVqS | 7,163 | Set explicit seed in iterable dataset ddp shuffling example | {
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In the examples section of the iterable dataset docs https://huggingface.co/docs/datasets/en/package_reference/main_classes#datasets.IterableDataset
the ddp example shuffles without seeding
```python
from datasets.distributed import split_dataset_by_node
ids = ds.to_iterable_dataset(num_sh... | {
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https://api.github.com/repos/huggingface/datasets/issues/7162 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7162/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7162/comments | https://api.github.com/repos/huggingface/datasets/issues/7162/events | https://github.com/huggingface/datasets/pull/7162 | 2,542,323,382 | PR_kwDODunzps58WlX5 | 7,162 | Support JSON lines with empty struct | {
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Fix #7161.
Related to:
- #7160 | {
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https://api.github.com/repos/huggingface/datasets/issues/7161 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7161/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7161/comments | https://api.github.com/repos/huggingface/datasets/issues/7161/events | https://github.com/huggingface/datasets/issues/7161 | 2,541,971,931 | I_kwDODunzps6Xg2nb | 7,161 | JSON lines with empty struct raise ArrowTypeError | {
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"following_url": "https://api.github.com/users/albertvillanova/following{/o... | null | [] | 2024-09-23T08:48:56Z | 2024-09-25T04:43:44Z | 2024-09-23T11:30:07Z | MEMBER | null | null | null | null | JSON lines with empty struct raise ArrowTypeError: struct fields don't match or are in the wrong order
See example: https://huggingface.co/datasets/wikimedia/structured-wikipedia/discussions/5
> ArrowTypeError: struct fields don't match or are in the wrong order: Input fields: struct<> output fields: struct<pov_c... | {
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https://api.github.com/repos/huggingface/datasets/issues/7160 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7160/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7160/comments | https://api.github.com/repos/huggingface/datasets/issues/7160/events | https://github.com/huggingface/datasets/pull/7160 | 2,541,877,813 | PR_kwDODunzps58VDhq | 7,160 | Support JSON lines with missing struct fields | {
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Fix #7159.
The implemented test raised:
```
TypeError: Couldn't cast array of type
struct<age: int64>
to
{'age': Value(dtype='int32', id=None), 'name': Value(dtype='string', id=None)}
``` | {
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