html_url stringlengths 51 51 | title stringlengths 10 280 | comments stringlengths 63 141k | body stringlengths 51 58.6k | comment_length int64 16 10.8k | text stringlengths 186 146k | embeddings listlengths 768 768 |
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https://github.com/huggingface/datasets/issues/8005 | Multi-channel audio is automatically cast to mono, num_channels is ignored | **Workaround**
Directly load audio using torchcodec, this is what datasets does under the hood (but doesn't maintain multi-channel)
```python
import torchcodec
decoder = torchcodec.decoders.AudioDecoder(audio["bytes"])
audio_samples = decoder.get_all_samples()
audio = audio_samples.data.numpy()
sample_rate = audio_s... | ### Describe the bug
The `num_channels` parameter in `datasets.Audio()` is documented to preserve stereo channels when set to `None` (preserve original) or `2` (explicit stereo), but it currently downmixes all audio to mono regardless of this setting.
### Steps to reproduce the bug
```python
import numpy as np
impor... | 34 | Multi-channel audio is automatically cast to mono, num_channels is ignored
### Describe the bug
The `num_channels` parameter in `datasets.Audio()` is documented to preserve stereo channels when set to `None` (preserve original) or `2` (explicit stereo), but it currently downmixes all audio to mono regardless of this s... | [
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https://github.com/huggingface/datasets/issues/7999 | Too many dataloader workers: 4 (max is dataset.num_shards=3). Stopping 1 dataloader workers. | Hi, thanks for the clear question and code snippet!
From my understanding, **hf_dataset.num_shards** represents the number of actual iterable partitions that the streaming dataset can be read from in parallel. This is not the same as the number of underlying Parquet files—many files can be grouped into a much smaller ... | Hi !
I’m working on training with a large-scale dataset (100+ Parquet files) using lazy loading, and I’m struggling to understand/optimize the num_shards setting— in the lerobot repo: streaming_datasets.py:
```
from datasets import load_dataset
self.hf_dataset: datasets.IterableDataset = load_dataset(
self.... | 174 | Too many dataloader workers: 4 (max is dataset.num_shards=3). Stopping 1 dataloader workers.
Hi !
I’m working on training with a large-scale dataset (100+ Parquet files) using lazy loading, and I’m struggling to understand/optimize the num_shards setting— in the lerobot repo: streaming_datasets.py:
```
from datasets im... | [
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0.0192980859... |
https://github.com/huggingface/datasets/issues/7986 | `Dataset.map()` causes cache miss/fingerprint change when closure captures self containing non-deterministic state. | I suggest metion this in docs specifically for attention with use, tell users explicitly to pass arguments with `fn_kwargs` param or using `functools.partial` to create a pure funcion. | ### Describe the bug
When using `.map()` with a function defined inside a **class (of which has any non-deterministic states)** method (a closure), if that function captures `self` to access a configuration variable (e.g., self.foo), the fingerprint mechanism serializes the entire class instance state.
If the class i... | 28 | `Dataset.map()` causes cache miss/fingerprint change when closure captures self containing non-deterministic state.
### Describe the bug
When using `.map()` with a function defined inside a **class (of which has any non-deterministic states)** method (a closure), if that function captures `self` to access a configurat... | [
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https://github.com/huggingface/datasets/issues/7970 | cast_column(..., Audio) fails with load_dataset("csv",) | The following code *does* work:
```py
from datasets import load_dataset,Audio,Features
dataset = load_dataset("csv",data_files="audio.csv",features=Features({"audio": Audio()}))
print(dataset["train"][0]["audio"])
``` | ### Describe the bug
Attempt to load a dataset from a csv with a single `audio` column with a single row with a path to an audio file fails when casting the column to Audio, but the exact same dataset created from a dictionary succeeds.
### Steps to reproduce the bug
1. Have any valid audio file `audio.wav`
2. Have ... | 16 | cast_column(..., Audio) fails with load_dataset("csv",)
### Describe the bug
Attempt to load a dataset from a csv with a single `audio` column with a single row with a path to an audio file fails when casting the column to Audio, but the exact same dataset created from a dictionary succeeds.
### Steps to reproduce th... | [
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https://github.com/huggingface/datasets/issues/7970 | cast_column(..., Audio) fails with load_dataset("csv",) | Thanks for reporing ! Are you using pandas v3 by any chance ? The CSV loader uses pandas and this release is brand new and might have caused a breaking change | ### Describe the bug
Attempt to load a dataset from a csv with a single `audio` column with a single row with a path to an audio file fails when casting the column to Audio, but the exact same dataset created from a dictionary succeeds.
### Steps to reproduce the bug
1. Have any valid audio file `audio.wav`
2. Have ... | 31 | cast_column(..., Audio) fails with load_dataset("csv",)
### Describe the bug
Attempt to load a dataset from a csv with a single `audio` column with a single row with a path to an audio file fails when casting the column to Audio, but the exact same dataset created from a dictionary succeeds.
### Steps to reproduce th... | [
-0.0855577141046524,
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0.2804476320743561,
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https://github.com/huggingface/datasets/issues/7965 | `huggingface_hub.errors.HfHubHTTPError: 404 Client Error: Not Found for url` when fetching a dataset with `datasets.load_dataset` | Hi ! Yes you should use `cornell-movie-review-data/rotten_tomatoes` instead of `rotten_tomatoes`, which is the legacy name. Those datasets have been moved under their actual owners accounts some time ago (but we were keeping the old names as aliases)
Some other impacted names are:
- `imdb` -> `stanfordnlp/imdb`
- `wik... | Not a bug but a question. We started getting the following error:
https://github.com/mlflow/mlflow/actions/runs/21368603305/job/61506951617
```
ests/data/test_huggingface_dataset_and_source.py::test_from_huggingface_dataset_constructs_expected_dataset_with_revision - huggingface_hub.errors.HfHubHTTPError: 404 Client ... | 91 | `huggingface_hub.errors.HfHubHTTPError: 404 Client Error: Not Found for url` when fetching a dataset with `datasets.load_dataset`
Not a bug but a question. We started getting the following error:
https://github.com/mlflow/mlflow/actions/runs/21368603305/job/61506951617
```
ests/data/test_huggingface_dataset_and_sourc... | [
0.1389400213956833,
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0.1081468015909195,
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0.10686794668436... |
https://github.com/huggingface/datasets/issues/7965 | `huggingface_hub.errors.HfHubHTTPError: 404 Client Error: Not Found for url` when fetching a dataset with `datasets.load_dataset` | Thanks for the heads up @lhoestq ! fyi, this change is likely breaking a lot of repos that have legacy names hardcoded ([example](https://github.com/allenai/olmes/pull/40)) Would be helpful to many to share this update in a more visible way if it is likely to persist for a while. | Not a bug but a question. We started getting the following error:
https://github.com/mlflow/mlflow/actions/runs/21368603305/job/61506951617
```
ests/data/test_huggingface_dataset_and_source.py::test_from_huggingface_dataset_constructs_expected_dataset_with_revision - huggingface_hub.errors.HfHubHTTPError: 404 Client ... | 46 | `huggingface_hub.errors.HfHubHTTPError: 404 Client Error: Not Found for url` when fetching a dataset with `datasets.load_dataset`
Not a bug but a question. We started getting the following error:
https://github.com/mlflow/mlflow/actions/runs/21368603305/job/61506951617
```
ests/data/test_huggingface_dataset_and_sourc... | [
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0.0871490... |
https://github.com/huggingface/datasets/issues/7958 | [CUDA Tensors Not working in ~v4.5.0] set_format(type="torch", device="cuda") returns cpu | I reverted this change which caused the issue #7961 , I'll do a new release soon but in the meantime feel free to install `datasets` from source | ### Describe the bug
The problem is that when calling:
```ds.set_format(type="torch", columns = ["input", "labels"], device="cuda")```
The device type of the individual datapoints is now: `cpu` as opposed to `cuda:0`.
With `v4.0.0` it still works. With `v4.5.0` it doesn't work anymore.
Related Issue:
https://github... | 27 | [CUDA Tensors Not working in ~v4.5.0] set_format(type="torch", device="cuda") returns cpu
### Describe the bug
The problem is that when calling:
```ds.set_format(type="torch", columns = ["input", "labels"], device="cuda")```
The device type of the individual datapoints is now: `cpu` as opposed to `cuda:0`.
With `v4.0... | [
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0.506611645221710... |
https://github.com/huggingface/datasets/issues/7958 | [CUDA Tensors Not working in ~v4.5.0] set_format(type="torch", device="cuda") returns cpu | @lhoestq thanks a lot. I am actually checking older versions of datasets and it seems that it doesn't work with 4.2.0 as well.
(hopefully that's relevant). | ### Describe the bug
The problem is that when calling:
```ds.set_format(type="torch", columns = ["input", "labels"], device="cuda")```
The device type of the individual datapoints is now: `cpu` as opposed to `cuda:0`.
With `v4.0.0` it still works. With `v4.5.0` it doesn't work anymore.
Related Issue:
https://github... | 26 | [CUDA Tensors Not working in ~v4.5.0] set_format(type="torch", device="cuda") returns cpu
### Describe the bug
The problem is that when calling:
```ds.set_format(type="torch", columns = ["input", "labels"], device="cuda")```
The device type of the individual datapoints is now: `cpu` as opposed to `cuda:0`.
With `v4.0... | [
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0.54283368587... |
https://github.com/huggingface/datasets/issues/7956 | Is the 10k files / folder limit a hard limit for a dataset repo? | "Yes, that's a hard limit. Can you split your files into different folders? Or we'll probably have a(...TRUNCATED) | "### Feature request\n\nCan the hard limit of 10k files per folder be extended with acceptable loss (...TRUNCATED) | 34 | "Is the 10k files / folder limit a hard limit for a dataset repo?\n### Feature request\n\nCan the ha(...TRUNCATED) | [-0.05702270194888115,-0.066613107919693,-0.07194454967975616,0.28664830327033997,0.1709624975919723(...TRUNCATED) |
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