html_url stringlengths 51 51 | title stringlengths 9 280 | comments stringlengths 63 24.7k | body stringlengths 51 58.6k | comments length int64 16 1.45k | text stringlengths 186 59.1k |
|---|---|---|---|---|---|
https://github.com/huggingface/datasets/issues/4163 | Optional Content Warning for Datasets | ```
---
annotations_creators:
- expert
language_creators:
- expert-generated
languages:
- en
license:
- cc-by-4.0
multilinguality:
- monolingual
pretty_name: HatemojiBuild
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- hate-speech-detection... | **Is your feature request related to a problem? Please describe.**
A clear and concise description of what the problem is.
We now have hate speech datasets on the hub, like this one: https://huggingface.co/datasets/HannahRoseKirk/HatemojiBuild
I'm wondering if there is an option to select a content warning messa... | 107 | Optional Content Warning for Datasets
**Is your feature request related to a problem? Please describe.**
A clear and concise description of what the problem is.
We now have hate speech datasets on the hub, like this one: https://huggingface.co/datasets/HannahRoseKirk/HatemojiBuild
I'm wondering if there is an op... |
https://github.com/huggingface/datasets/issues/4163 | Optional Content Warning for Datasets | -- is there a way to gate content anonymously, i.e. without registering which users access it? | **Is your feature request related to a problem? Please describe.**
A clear and concise description of what the problem is.
We now have hate speech datasets on the hub, like this one: https://huggingface.co/datasets/HannahRoseKirk/HatemojiBuild
I'm wondering if there is an option to select a content warning messa... | 16 | Optional Content Warning for Datasets
**Is your feature request related to a problem? Please describe.**
A clear and concise description of what the problem is.
We now have hate speech datasets on the hub, like this one: https://huggingface.co/datasets/HannahRoseKirk/HatemojiBuild
I'm wondering if there is an op... |
https://github.com/huggingface/datasets/issues/4163 | Optional Content Warning for Datasets | +1 to @leondz's question. One scenario is if you don't want the dataset to be indexed by search engines or viewed in browser b/c of upstream conditions on data, but don't want to collect emails. Some ability to turn off the dataset viewer or add a gating mechanism without emails would be fantastic. | **Is your feature request related to a problem? Please describe.**
A clear and concise description of what the problem is.
We now have hate speech datasets on the hub, like this one: https://huggingface.co/datasets/HannahRoseKirk/HatemojiBuild
I'm wondering if there is an option to select a content warning messa... | 53 | Optional Content Warning for Datasets
**Is your feature request related to a problem? Please describe.**
A clear and concise description of what the problem is.
We now have hate speech datasets on the hub, like this one: https://huggingface.co/datasets/HannahRoseKirk/HatemojiBuild
I'm wondering if there is an op... |
https://github.com/huggingface/datasets/issues/4407 | Dataset Viewer issue for conll2012_ontonotesv5 | Thanks for reporting, @jiangwy99.
I guess this could be addressed only once we fix our issue with irresponsive backend endpoint.
CC: @severo | ### Link
https://huggingface.co/datasets/conll2012_ontonotesv5
### Description
Dataset viewer outage.
### Owner
No | 22 | Dataset Viewer issue for conll2012_ontonotesv5
### Link
https://huggingface.co/datasets/conll2012_ontonotesv5
### Description
Dataset viewer outage.
### Owner
No
Thanks for reporting, @jiangwy99.
I guess this could be addressed only once we fix our issue with irresponsive backend endpoint.
CC: @severo |
https://github.com/huggingface/datasets/issues/4407 | Dataset Viewer issue for conll2012_ontonotesv5 | Fixed, thanks for the patience. The issue was the amount of RAM allowed to extract the first rows of the dataset was not sufficient. | ### Link
https://huggingface.co/datasets/conll2012_ontonotesv5
### Description
Dataset viewer outage.
### Owner
No | 24 | Dataset Viewer issue for conll2012_ontonotesv5
### Link
https://huggingface.co/datasets/conll2012_ontonotesv5
### Description
Dataset viewer outage.
### Owner
No
Fixed, thanks for the patience. The issue was the amount of RAM allowed to extract the first rows of the dataset was not sufficient. |
https://github.com/huggingface/datasets/issues/6600 | Loading CSV exported dataset has unexpected format | Hi! Parquet is the only format that supports complex/nested features such as `Translation`. So, this should work:
```python
test_dataset = load_dataset("opus100", name="en-fr", split="test")
# Save with .to_parquet()
test_parquet_path = "try_testset_save.parquet"
test_dataset.to_parquet(test_parquet_path)
# L... | ### Describe the bug
I wanted to be able to save a HF dataset for translations and load it again in another script, but I'm a bit confused with the documentation and the result I've got so I'm opening this issue to ask if this behavior is as expected.
### Steps to reproduce the bug
The documentation I've mainly cons... | 44 | Loading CSV exported dataset has unexpected format
### Describe the bug
I wanted to be able to save a HF dataset for translations and load it again in another script, but I'm a bit confused with the documentation and the result I've got so I'm opening this issue to ask if this behavior is as expected.
### Steps to re... |
https://github.com/huggingface/datasets/issues/6126 | Private datasets do not load when passing token | Our CI did not catch this issue because with current implementation, stored token in `HfFolder` (which always exists) is used by default. | ### Describe the bug
Since the release of `datasets` 2.14, private/gated datasets do not load when passing `token`: they raise `EmptyDatasetError`.
This is a non-planned backward incompatible breaking change.
Note that private datasets do load if instead `download_config` is passed:
```python
from datasets i... | 22 | Private datasets do not load when passing token
### Describe the bug
Since the release of `datasets` 2.14, private/gated datasets do not load when passing `token`: they raise `EmptyDatasetError`.
This is a non-planned backward incompatible breaking change.
Note that private datasets do load if instead `downloa... |
https://github.com/huggingface/datasets/issues/6126 | Private datasets do not load when passing token | I can confirm this and have the same problem (and just went almost crazy because I couldn't figure out the source of this problem because on another computer everything worked well even with `DownloadMode.FORCE_REDOWNLOAD`). | ### Describe the bug
Since the release of `datasets` 2.14, private/gated datasets do not load when passing `token`: they raise `EmptyDatasetError`.
This is a non-planned backward incompatible breaking change.
Note that private datasets do load if instead `download_config` is passed:
```python
from datasets i... | 34 | Private datasets do not load when passing token
### Describe the bug
Since the release of `datasets` 2.14, private/gated datasets do not load when passing `token`: they raise `EmptyDatasetError`.
This is a non-planned backward incompatible breaking change.
Note that private datasets do load if instead `downloa... |
https://github.com/huggingface/datasets/issues/6126 | Private datasets do not load when passing token | We are planning to do a patch release today, after the merge of the fix:
- #6127
In the meantime, the problem can be circumvented by passing `download_config` instead:
```python
from datasets import DownloadConfig, load_dataset
load_dataset("<DATASET-NAME>", split="train", download_config=DownloadConfig(token=... | ### Describe the bug
Since the release of `datasets` 2.14, private/gated datasets do not load when passing `token`: they raise `EmptyDatasetError`.
This is a non-planned backward incompatible breaking change.
Note that private datasets do load if instead `download_config` is passed:
```python
from datasets i... | 39 | Private datasets do not load when passing token
### Describe the bug
Since the release of `datasets` 2.14, private/gated datasets do not load when passing `token`: they raise `EmptyDatasetError`.
This is a non-planned backward incompatible breaking change.
Note that private datasets do load if instead `downloa... |
https://github.com/huggingface/datasets/issues/6126 | Private datasets do not load when passing token | > We are planning to do a patch release today, after the merge of the fix:
>
> * [Fix authentication issues #6127](https://github.com/huggingface/datasets/pull/6127)
>
>
> In the meantime, the problem can be circumvented by passing `download_config` instead:
>
> ```python
> from datasets import Download... | ### Describe the bug
Since the release of `datasets` 2.14, private/gated datasets do not load when passing `token`: they raise `EmptyDatasetError`.
This is a non-planned backward incompatible breaking change.
Note that private datasets do load if instead `download_config` is passed:
```python
from datasets i... | 78 | Private datasets do not load when passing token
### Describe the bug
Since the release of `datasets` 2.14, private/gated datasets do not load when passing `token`: they raise `EmptyDatasetError`.
This is a non-planned backward incompatible breaking change.
Note that private datasets do load if instead `downloa... |
https://github.com/huggingface/datasets/issues/6139 | Offline dataset viewer | Hi, thanks for the suggestion. It's not possible at the moment. The viewer is part of the Hub codebase and only works on public datasets. Also, it relies on [Datasets Server](https://github.com/huggingface/datasets-server/), which prepares the data and provides an API to access the rows, size, etc.
If you're interes... | ### Feature request
The dataset viewer feature is very nice. It enables to the user to easily view the dataset. However, when working for private companies we cannot always upload the dataset to the hub. Is there a way to create dataset viewer offline? I.e. to run a code that will open some kind of html or something t... | 66 | Offline dataset viewer
### Feature request
The dataset viewer feature is very nice. It enables to the user to easily view the dataset. However, when working for private companies we cannot always upload the dataset to the hub. Is there a way to create dataset viewer offline? I.e. to run a code that will open some kind... |
https://github.com/huggingface/datasets/issues/6139 | Offline dataset viewer | Hi, we are building an offline dataset viewer: https://github.com/Renumics/spotlight
It supports many HF datasets, but currently you have to use it via Pandas:
df=ds.to_pandas()
spotlight.show(df)
Would love to hear from you if that works for your use case. If not, feel free to open an issue on the repo: https://... | ### Feature request
The dataset viewer feature is very nice. It enables to the user to easily view the dataset. However, when working for private companies we cannot always upload the dataset to the hub. Is there a way to create dataset viewer offline? I.e. to run a code that will open some kind of html or something t... | 50 | Offline dataset viewer
### Feature request
The dataset viewer feature is very nice. It enables to the user to easily view the dataset. However, when working for private companies we cannot always upload the dataset to the hub. Is there a way to create dataset viewer offline? I.e. to run a code that will open some kind... |
https://github.com/huggingface/datasets/issues/6139 | Offline dataset viewer | @yuvalkirstain the dataset viewer is now available on private datasets for [PRO users](https://huggingface.co/pricing#pro) and [Enterprise Hub orgs](https://huggingface.co/enterprise). Would it fit your needs? | ### Feature request
The dataset viewer feature is very nice. It enables to the user to easily view the dataset. However, when working for private companies we cannot always upload the dataset to the hub. Is there a way to create dataset viewer offline? I.e. to run a code that will open some kind of html or something t... | 22 | Offline dataset viewer
### Feature request
The dataset viewer feature is very nice. It enables to the user to easily view the dataset. However, when working for private companies we cannot always upload the dataset to the hub. Is there a way to create dataset viewer offline? I.e. to run a code that will open some kind... |
https://github.com/huggingface/datasets/issues/6139 | Offline dataset viewer | Hi @ssuwelack I tried loading a HF dataset with your viewer but got this error https://github.com/Renumics/spotlight/issues/461 hope the team can help me on this. Thanks! | ### Feature request
The dataset viewer feature is very nice. It enables to the user to easily view the dataset. However, when working for private companies we cannot always upload the dataset to the hub. Is there a way to create dataset viewer offline? I.e. to run a code that will open some kind of html or something t... | 25 | Offline dataset viewer
### Feature request
The dataset viewer feature is very nice. It enables to the user to easily view the dataset. However, when working for private companies we cannot always upload the dataset to the hub. Is there a way to create dataset viewer offline? I.e. to run a code that will open some kind... |
https://github.com/huggingface/datasets/issues/8197 | Feature Request / Discussion: Skip origin_metadata fetch when streaming=True? | I think it's great that it checks that every file does exist by default. It's relatively cheap since it uses fsspec which caches file info at folder level.
On the other hand why not add skip_origin_metadata=False from @TheDerbiedOne by default to DatasetBuilder and document what it does (load_dataset passes kwargs to ... | Hi team!
I've been looking into the initialization process of the `DatasetBuilder` and noticed that the ETag/origin metadata caching path is executed unconditionally.
While fetching the `origin_metadata` and calculating the ETag is necessary for safely managing a local disk cache when using `as_dataset()`, it seems t... | 52 | Feature Request / Discussion: Skip origin_metadata fetch when streaming=True?
Hi team!
I've been looking into the initialization process of the `DatasetBuilder` and noticed that the ETag/origin metadata caching path is executed unconditionally.
While fetching the `origin_metadata` and calculating the ETag is necessar... |
https://github.com/huggingface/datasets/issues/8197 | Feature Request / Discussion: Skip origin_metadata fetch when streaming=True? | Hi @lhoestq Thanks for taking a look at this!
Regarding the file existence check: skipping _get_origin_metadata actually doesn't remove that safeguard. I think th verification that files exist happens earlier during pattern resolution (around L372-L384 in data_files.py (https://github.com/huggingface/datasets/blob/mai... | Hi team!
I've been looking into the initialization process of the `DatasetBuilder` and noticed that the ETag/origin metadata caching path is executed unconditionally.
While fetching the `origin_metadata` and calculating the ETag is necessary for safely managing a local disk cache when using `as_dataset()`, it seems t... | 97 | Feature Request / Discussion: Skip origin_metadata fetch when streaming=True?
Hi team!
I've been looking into the initialization process of the `DatasetBuilder` and noticed that the ETag/origin metadata caching path is executed unconditionally.
While fetching the `origin_metadata` and calculating the ETag is necessar... |
https://github.com/huggingface/datasets/issues/6405 | ConfigNamesError on a simple CSV file | The viewer is working now.
Based on the repo commit history, the bug was due to the incorrect format of the `features` field in the README YAML (`Value` requires `dtype`, e.g., `Value("string")`, but it was not specified) | See https://huggingface.co/datasets/Nguyendo1999/mmath/discussions/1
```
Error code: ConfigNamesError
Exception: TypeError
Message: __init__() missing 1 required positional argument: 'dtype'
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runn... | 37 | ConfigNamesError on a simple CSV file
See https://huggingface.co/datasets/Nguyendo1999/mmath/discussions/1
```
Error code: ConfigNamesError
Exception: TypeError
Message: __init__() missing 1 required positional argument: 'dtype'
Traceback: Traceback (most recent call last):
File "/s... |
https://github.com/huggingface/datasets/issues/4746 | Dataset Viewer issue for yanekyuk/wikikey | The dataset is empty, as far as I can tell: there are no files in the repository at https://huggingface.co/datasets/yanekyuk/wikikey/tree/main
Maybe the viewer can display a better message for empty datasets | ### Link
_No response_
### Description
_No response_
### Owner
_No response_ | 30 | Dataset Viewer issue for yanekyuk/wikikey
### Link
_No response_
### Description
_No response_
### Owner
_No response_
The dataset is empty, as far as I can tell: there are no files in the repository at https://huggingface.co/datasets/yanekyuk/wikikey/tree/main
Maybe the viewer can display a better message for ... |
https://github.com/huggingface/datasets/issues/4746 | Dataset Viewer issue for yanekyuk/wikikey | OK. Closing as it's not an error. We will work on making the error message a lot clearer. | ### Link
_No response_
### Description
_No response_
### Owner
_No response_ | 18 | Dataset Viewer issue for yanekyuk/wikikey
### Link
_No response_
### Description
_No response_
### Owner
_No response_
OK. Closing as it's not an error. We will work on making the error message a lot clearer. |
https://github.com/huggingface/datasets/issues/6773 | Dataset on Hub re-downloads every time? | hi @mariosasko , Thank you for checking. I also tried running this again just now, and it seems like the `load_dataset()` caches properly (though I'll double check later).
I think the issue might be in the caching of the function output for `territories.map(lambda row: {'Claimants': row['Claimants'].split(';')})`. M... | ### Describe the bug
Hi, I have a dataset on the hub [here](https://huggingface.co/datasets/manestay/borderlines). It has 1k+ downloads, which I sure is mostly just me and my colleagues working with it. It should have far fewer, since I'm using the same machine with a properly set up HF_HOME variable. However, whene... | 108 | Dataset on Hub re-downloads every time?
### Describe the bug
Hi, I have a dataset on the hub [here](https://huggingface.co/datasets/manestay/borderlines). It has 1k+ downloads, which I sure is mostly just me and my colleagues working with it. It should have far fewer, since I'm using the same machine with a properly... |
https://github.com/huggingface/datasets/issues/6773 | Dataset on Hub re-downloads every time? | This issue seems similar to https://github.com/huggingface/datasets/issues/6184 (`dill` serializes objects defined outside the `__main__` module by reference). You should be able to work around this limitation by defining the lambdas outside of `load_borderlines_hf` (as module variables) and then setting their `__modul... | ### Describe the bug
Hi, I have a dataset on the hub [here](https://huggingface.co/datasets/manestay/borderlines). It has 1k+ downloads, which I sure is mostly just me and my colleagues working with it. It should have far fewer, since I'm using the same machine with a properly set up HF_HOME variable. However, whene... | 64 | Dataset on Hub re-downloads every time?
### Describe the bug
Hi, I have a dataset on the hub [here](https://huggingface.co/datasets/manestay/borderlines). It has 1k+ downloads, which I sure is mostly just me and my colleagues working with it. It should have far fewer, since I'm using the same machine with a properly... |
https://github.com/huggingface/datasets/issues/6773 | Dataset on Hub re-downloads every time? | Thank you, I'll give this a try. Your fix makes sense to me, so this issue can be closed for now.
Unrelated comment -- for "Downloads last month" on the hub page, I'm assuming for this project that each downloaded CSV is 1 download? The dataset consists of 51 CSVs, so I'm trying to see why it's incrementing so quick... | ### Describe the bug
Hi, I have a dataset on the hub [here](https://huggingface.co/datasets/manestay/borderlines). It has 1k+ downloads, which I sure is mostly just me and my colleagues working with it. It should have far fewer, since I'm using the same machine with a properly set up HF_HOME variable. However, whene... | 67 | Dataset on Hub re-downloads every time?
### Describe the bug
Hi, I have a dataset on the hub [here](https://huggingface.co/datasets/manestay/borderlines). It has 1k+ downloads, which I sure is mostly just me and my colleagues working with it. It should have far fewer, since I'm using the same machine with a properly... |
https://github.com/huggingface/datasets/issues/5085 | Filtering on an empty dataset returns a corrupted dataset. | ~~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
`ds_filter_1._indices.column(0)`~~
**UPDATE:**
Empty datasets are returned without ... | ## 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) # ... | 103 | Filtering on an empty dataset returns a corrupted dataset.
## 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']... |
https://github.com/huggingface/datasets/issues/7502 | `load_dataset` of size 40GB creates a cache of >720GB | Hi ! Parquet is a compressed format. When you load a dataset, it uncompresses the Parquet data into Arrow data on your disk. That's why you can indeed end up with 720GB of uncompressed data on disk. The uncompression is needed to enable performant dataset objects (especially for random access).
To save some storage yo... | Hi there,
I am trying to load a dataset from the Hugging Face Hub and split it into train and validation splits. Somehow, when I try to do it with `load_dataset`, it exhausts my disk quota. So, I tried manually downloading the parquet files from the hub and loading them as follows:
```python
ds = DatasetDict(
... | 98 | `load_dataset` of size 40GB creates a cache of >720GB
Hi there,
I am trying to load a dataset from the Hugging Face Hub and split it into train and validation splits. Somehow, when I try to do it with `load_dataset`, it exhausts my disk quota. So, I tried manually downloading the parquet files from the hub and loading... |
https://github.com/huggingface/datasets/issues/7502 | `load_dataset` of size 40GB creates a cache of >720GB | Hi @lhoestq, thanks a lot for your answer. This makes perfect sense. I will try using the streaming mode. Closing the issue. | Hi there,
I am trying to load a dataset from the Hugging Face Hub and split it into train and validation splits. Somehow, when I try to do it with `load_dataset`, it exhausts my disk quota. So, I tried manually downloading the parquet files from the hub and loading them as follows:
```python
ds = DatasetDict(
... | 22 | `load_dataset` of size 40GB creates a cache of >720GB
Hi there,
I am trying to load a dataset from the Hugging Face Hub and split it into train and validation splits. Somehow, when I try to do it with `load_dataset`, it exhausts my disk quota. So, I tried manually downloading the parquet files from the hub and loading... |
https://github.com/huggingface/datasets/issues/4804 | streaming dataset with concatenating splits raises an error | Hi! Only the name of a particular split ("train", "test", ...) is supported as a split pattern if `streaming=True`. We plan to address this limitation soon. | ## Describe the bug
streaming dataset with concatenating splits raises an error
## Steps to reproduce the bug
```python
from datasets import load_dataset
# no error
repo = "nateraw/ade20k-tiny"
dataset = load_dataset(repo, split="train+validation")
```
```python
from datasets import load_dataset
# er... | 26 | streaming dataset with concatenating splits raises an error
## Describe the bug
streaming dataset with concatenating splits raises an error
## Steps to reproduce the bug
```python
from datasets import load_dataset
# no error
repo = "nateraw/ade20k-tiny"
dataset = load_dataset(repo, split="train+validation")
... |
https://github.com/huggingface/datasets/issues/4804 | streaming dataset with concatenating splits raises an error | yes, same error occurs.
```python
from datasets import load_dataset
# error
repo = "nateraw/ade20k-tiny"
dataset = load_dataset(repo, split="train+validation", streaming=True)
```
```python
---------------------------------------------------------------------------
ValueError ... | ## Describe the bug
streaming dataset with concatenating splits raises an error
## Steps to reproduce the bug
```python
from datasets import load_dataset
# no error
repo = "nateraw/ade20k-tiny"
dataset = load_dataset(repo, split="train+validation")
```
```python
from datasets import load_dataset
# er... | 201 | streaming dataset with concatenating splits raises an error
## Describe the bug
streaming dataset with concatenating splits raises an error
## Steps to reproduce the bug
```python
from datasets import load_dataset
# no error
repo = "nateraw/ade20k-tiny"
dataset = load_dataset(repo, split="train+validation")
... |
https://github.com/huggingface/datasets/issues/4804 | streaming dataset with concatenating splits raises an error | Hi!, still not fixed this, the truth is that it is an important update for what we want to train the entire dataset because we want to train fast, also should be enabled the function "[train:18%]" for streaming | ## Describe the bug
streaming dataset with concatenating splits raises an error
## Steps to reproduce the bug
```python
from datasets import load_dataset
# no error
repo = "nateraw/ade20k-tiny"
dataset = load_dataset(repo, split="train+validation")
```
```python
from datasets import load_dataset
# er... | 38 | streaming dataset with concatenating splits raises an error
## Describe the bug
streaming dataset with concatenating splits raises an error
## Steps to reproduce the bug
```python
from datasets import load_dataset
# no error
repo = "nateraw/ade20k-tiny"
dataset = load_dataset(repo, split="train+validation")
... |
https://github.com/huggingface/datasets/issues/7080 | Generating train split takes a long time | @alexanderswerdlow
When no specific split is mentioned, the load_dataset library will load all available splits of the dataset. For example, if a dataset has "train" and "test" splits, the load_dataset function will load both into the DatasetDict object.
![image](https://github.com/user-attachments/assets/379e6f57... | ### Describe the bug
Loading a simple webdataset takes ~45 minutes.
### Steps to reproduce the bug
```
from datasets import load_dataset
dataset = load_dataset("PixArt-alpha/SAM-LLaVA-Captions10M")
```
### Expected behavior
The dataset should load immediately as it does when loaded through a normal indexed WebD... | 120 | Generating train split takes a long time
### Describe the bug
Loading a simple webdataset takes ~45 minutes.
### Steps to reproduce the bug
```
from datasets import load_dataset
dataset = load_dataset("PixArt-alpha/SAM-LLaVA-Captions10M")
```
### Expected behavior
The dataset should load immediately as it does ... |
https://github.com/huggingface/datasets/issues/7080 | Generating train split takes a long time | @alexanderswerdlow, I will now work on this..
## Idea:
Whenever this code has ran:
```python
from datasets import load_dataset
dataset = load_dataset("PixArt-alpha/SAM-LLaVA-Captions10M")
```
It should show all the splits of the datasets, and user has to choose which one should be loaded before generating a ... | ### Describe the bug
Loading a simple webdataset takes ~45 minutes.
### Steps to reproduce the bug
```
from datasets import load_dataset
dataset = load_dataset("PixArt-alpha/SAM-LLaVA-Captions10M")
```
### Expected behavior
The dataset should load immediately as it does when loaded through a normal indexed WebD... | 49 | Generating train split takes a long time
### Describe the bug
Loading a simple webdataset takes ~45 minutes.
### Steps to reproduce the bug
```
from datasets import load_dataset
dataset = load_dataset("PixArt-alpha/SAM-LLaVA-Captions10M")
```
### Expected behavior
The dataset should load immediately as it does ... |
https://github.com/huggingface/datasets/issues/4210 | TypeError: Cannot cast array data from dtype('O') to dtype('int64') according to the rule 'safe' | Hi! Casting class labels from strings is currently not supported in the CSV loader, but you can get the same result with an additional map as follows:
```python
from datasets import load_dataset,Features,Value,ClassLabel
class_names = ["cmn","deu","rus","fra","eng","jpn","spa","ita","kor","vie","nld","epo","por","tu... | ### System Info
```shell
- `transformers` version: 4.18.0
- Platform: Linux-5.4.144+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.7.13
- Huggingface_hub version: 0.5.1
- PyTorch version (GPU?): 1.10.0+cu111 (True)
- Tensorflow version (GPU?): 2.8.0 (True)
- Flax version (CPU?/GPU?/TPU?): not installed ... | 134 | TypeError: Cannot cast array data from dtype('O') to dtype('int64') according to the rule 'safe'
### System Info
```shell
- `transformers` version: 4.18.0
- Platform: Linux-5.4.144+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.7.13
- Huggingface_hub version: 0.5.1
- PyTorch version (GPU?): 1.10.0+cu111 (... |
https://github.com/huggingface/datasets/issues/4210 | TypeError: Cannot cast array data from dtype('O') to dtype('int64') according to the rule 'safe' | @albertvillanova @mariosasko thank you, with that change now I get
```
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
[<ipython-input-9-eeb68eeb9bec>](https://localhost:8080/#) in <module>()
11 )
12 ... | ### System Info
```shell
- `transformers` version: 4.18.0
- Platform: Linux-5.4.144+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.7.13
- Huggingface_hub version: 0.5.1
- PyTorch version (GPU?): 1.10.0+cu111 (True)
- Tensorflow version (GPU?): 2.8.0 (True)
- Flax version (CPU?/GPU?/TPU?): not installed ... | 187 | TypeError: Cannot cast array data from dtype('O') to dtype('int64') according to the rule 'safe'
### System Info
```shell
- `transformers` version: 4.18.0
- Platform: Linux-5.4.144+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.7.13
- Huggingface_hub version: 0.5.1
- PyTorch version (GPU?): 1.10.0+cu111 (... |
https://github.com/huggingface/datasets/issues/4210 | TypeError: Cannot cast array data from dtype('O') to dtype('int64') according to the rule 'safe' | @mariosasko changed it like
```python
sentences = sentences.map(lambda ex: {"label" : features["label"].str2int(ex["label"]) if ex["label"] is not None else None}, features=features)
```
to avoid the above errorr. | ### System Info
```shell
- `transformers` version: 4.18.0
- Platform: Linux-5.4.144+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.7.13
- Huggingface_hub version: 0.5.1
- PyTorch version (GPU?): 1.10.0+cu111 (True)
- Tensorflow version (GPU?): 2.8.0 (True)
- Flax version (CPU?/GPU?/TPU?): not installed ... | 26 | TypeError: Cannot cast array data from dtype('O') to dtype('int64') according to the rule 'safe'
### System Info
```shell
- `transformers` version: 4.18.0
- Platform: Linux-5.4.144+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.7.13
- Huggingface_hub version: 0.5.1
- PyTorch version (GPU?): 1.10.0+cu111 (... |
https://github.com/huggingface/datasets/issues/4210 | TypeError: Cannot cast array data from dtype('O') to dtype('int64') according to the rule 'safe' | Any update on this? Is this correct ?
> @mariosasko changed it like
>
> ```python
> sentences = sentences.map(lambda ex: {"label" : features["label"].str2int(ex["label"]) if ex["label"] is not None else None}, features=features)
> ```
>
> to avoid the above errorr.
| ### System Info
```shell
- `transformers` version: 4.18.0
- Platform: Linux-5.4.144+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.7.13
- Huggingface_hub version: 0.5.1
- PyTorch version (GPU?): 1.10.0+cu111 (True)
- Tensorflow version (GPU?): 2.8.0 (True)
- Flax version (CPU?/GPU?/TPU?): not installed ... | 41 | TypeError: Cannot cast array data from dtype('O') to dtype('int64') according to the rule 'safe'
### System Info
```shell
- `transformers` version: 4.18.0
- Platform: Linux-5.4.144+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.7.13
- Huggingface_hub version: 0.5.1
- PyTorch version (GPU?): 1.10.0+cu111 (... |
https://github.com/huggingface/datasets/issues/7577 | arrow_schema is not compatible with list | Actually it looks like you just forgot parenthesis:
```diff
- f = datasets.Features({'x': list[datasets.Value(dtype='int32')]})
+ f = datasets.Features({'x': list([datasets.Value(dtype='int32')])})
```
or simply using the `[ ]` syntax:
```python
f = datasets.Features({'x':[datasets.Value(dtype='int32')]})
```
I'm c... | ### Describe the bug
```
import datasets
f = datasets.Features({'x': list[datasets.Value(dtype='int32')]})
f.arrow_schema
Traceback (most recent call last):
File "datasets/features/features.py", line 1826, in arrow_schema
return pa.schema(self.type).with_metadata({"huggingface": json.dumps(hf_metadata)})
... | 40 | arrow_schema is not compatible with list
### Describe the bug
```
import datasets
f = datasets.Features({'x': list[datasets.Value(dtype='int32')]})
f.arrow_schema
Traceback (most recent call last):
File "datasets/features/features.py", line 1826, in arrow_schema
return pa.schema(self.type).with_metadata({"huggi... |
https://github.com/huggingface/datasets/issues/7577 | arrow_schema is not compatible with list | Ah is that what the syntax is? I don't think I was able to find an actual example of it so I assumed it was in the same way that you specify types eg. `list[int]`. This is good to know, thanks. | ### Describe the bug
```
import datasets
f = datasets.Features({'x': list[datasets.Value(dtype='int32')]})
f.arrow_schema
Traceback (most recent call last):
File "datasets/features/features.py", line 1826, in arrow_schema
return pa.schema(self.type).with_metadata({"huggingface": json.dumps(hf_metadata)})
... | 41 | arrow_schema is not compatible with list
### Describe the bug
```
import datasets
f = datasets.Features({'x': list[datasets.Value(dtype='int32')]})
f.arrow_schema
Traceback (most recent call last):
File "datasets/features/features.py", line 1826, in arrow_schema
return pa.schema(self.type).with_metadata({"huggi... |
https://github.com/huggingface/datasets/issues/3450 | Unexpected behavior doing Split + Filter | Hi ! This is an issue with `datasets` 1.12. Sorry for the inconvenience. Can you update to `>=1.13` ?
see https://github.com/huggingface/datasets/issues/3190
Maybe we should also backport the bug fix to `1.12` (in a new version `1.12.2`) | ## Describe the bug
I observed unexpected behavior when applying 'train_test_split' followed by 'filter' on dataset. Elements of the training dataset eventually end up in the test dataset (after applying the 'filter')
## Steps to reproduce the bug
```
from datasets import Dataset
import pandas as pd
dic = {'x'... | 36 | Unexpected behavior doing Split + Filter
## Describe the bug
I observed unexpected behavior when applying 'train_test_split' followed by 'filter' on dataset. Elements of the training dataset eventually end up in the test dataset (after applying the 'filter')
## Steps to reproduce the bug
```
from datasets import... |
https://github.com/huggingface/datasets/issues/6697 | Unable to Load Dataset in Kaggle | FWIW, I run `load_dataset("llm-blender/mix-instruct")` and it ran successfully.
Can you clear your cache and try again?
### Environment Info
- `datasets` version: 2.17.0
- Platform: Linux-6.2.6-76060206-generic-x86_64-with-glibc2.35
- Python version: 3.9.13
- `huggingface_hub` version: 0.20.3
- PyArrow ver... | ### Describe the bug
Having installed the latest versions of transformers==4.38.1 and datasets==2.17.1 Unable to load the dataset in a kaggle notebook.
Get this Error:
```
---------------------------------------------------------------------------
ValueError Traceback (most recen... | 46 | Unable to Load Dataset in Kaggle
### Describe the bug
Having installed the latest versions of transformers==4.38.1 and datasets==2.17.1 Unable to load the dataset in a kaggle notebook.
Get this Error:
```
---------------------------------------------------------------------------
ValueError ... |
https://github.com/huggingface/datasets/issues/6697 | Unable to Load Dataset in Kaggle | It is working on the Kaggle GPU instance but gives this same error when running on the CPU instance. Still to run it on Kaggle you require to install the latest versions of datasets and transformers. | ### Describe the bug
Having installed the latest versions of transformers==4.38.1 and datasets==2.17.1 Unable to load the dataset in a kaggle notebook.
Get this Error:
```
---------------------------------------------------------------------------
ValueError Traceback (most recen... | 36 | Unable to Load Dataset in Kaggle
### Describe the bug
Having installed the latest versions of transformers==4.38.1 and datasets==2.17.1 Unable to load the dataset in a kaggle notebook.
Get this Error:
```
---------------------------------------------------------------------------
ValueError ... |
https://github.com/huggingface/datasets/issues/6697 | Unable to Load Dataset in Kaggle | This error means that `fsspec>=2023.12.0` is installed, which is incompatible with the current releases (the next `datasets` release will be the first to support it). In the meantime, downgrading `fsspec` (`pip install fsspec<=2023.12.0`) should fix the issue. | ### Describe the bug
Having installed the latest versions of transformers==4.38.1 and datasets==2.17.1 Unable to load the dataset in a kaggle notebook.
Get this Error:
```
---------------------------------------------------------------------------
ValueError Traceback (most recen... | 37 | Unable to Load Dataset in Kaggle
### Describe the bug
Having installed the latest versions of transformers==4.38.1 and datasets==2.17.1 Unable to load the dataset in a kaggle notebook.
Get this Error:
```
---------------------------------------------------------------------------
ValueError ... |
https://github.com/huggingface/datasets/issues/8178 | The full dataset viewer is not available (click to read why). Only showing a preview of the rows. Job manager crashed while running this job (missing heartbeats). Error code: JobManagerCrashedError | Oh yeah, we hit something pretty similar when running a dataset viewer on a large collection (~3M rows) a few months back. The JobManagerCrashedError with missing heartbeats usually showed up for us when the server process ran out of memory or couldn’t keep up with the load spikes during dataset streaming. Turns out, t... | ### Describe the bug
The full dataset viewer is not available (click to read why). Only showing a preview of the rows.
Job manager crashed while running this job (missing heartbeats).
Error code: JobManagerCrashedError
see: https://huggingface.co/datasets/Genius-Society/tt100k/viewer
### Steps to reproduce the bug... | 154 | The full dataset viewer is not available (click to read why). Only showing a preview of the rows. Job manager crashed while running this job (missing heartbeats). Error code: JobManagerCrashedError
### Describe the bug
The full dataset viewer is not available (click to read why). Only showing a preview of the rows.
... |
https://github.com/huggingface/datasets/issues/8178 | The full dataset viewer is not available (click to read why). Only showing a preview of the rows. Job manager crashed while running this job (missing heartbeats). Error code: JobManagerCrashedError | > Oh yeah, we hit something pretty similar when running a dataset viewer on a large collection (~3M rows) a few months back. The JobManagerCrashedError with missing heartbeats usually showed up for us when the server process ran out of memory or couldn’t keep up with the load spikes during dataset streaming. Turns out,... | ### Describe the bug
The full dataset viewer is not available (click to read why). Only showing a preview of the rows.
Job manager crashed while running this job (missing heartbeats).
Error code: JobManagerCrashedError
see: https://huggingface.co/datasets/Genius-Society/tt100k/viewer
### Steps to reproduce the bug... | 206 | The full dataset viewer is not available (click to read why). Only showing a preview of the rows. Job manager crashed while running this job (missing heartbeats). Error code: JobManagerCrashedError
### Describe the bug
The full dataset viewer is not available (click to read why). Only showing a preview of the rows.
... |
https://github.com/huggingface/datasets/issues/8178 | The full dataset viewer is not available (click to read why). Only showing a preview of the rows. Job manager crashed while running this job (missing heartbeats). Error code: JobManagerCrashedError | > Oh yeah, we hit something pretty similar when running a dataset viewer on a large collection (~3M rows) a few months back. The JobManagerCrashedError with missing heartbeats usually showed up for us when the server process ran out of memory or couldn’t keep up with the load spikes during dataset streaming. Turns out,... | ### Describe the bug
The full dataset viewer is not available (click to read why). Only showing a preview of the rows.
Job manager crashed while running this job (missing heartbeats).
Error code: JobManagerCrashedError
see: https://huggingface.co/datasets/Genius-Society/tt100k/viewer
### Steps to reproduce the bug... | 168 | The full dataset viewer is not available (click to read why). Only showing a preview of the rows. Job manager crashed while running this job (missing heartbeats). Error code: JobManagerCrashedError
### Describe the bug
The full dataset viewer is not available (click to read why). Only showing a preview of the rows.
... |
https://github.com/huggingface/datasets/issues/3756 | Images get decoded when using `map()` with `input_columns` argument on a dataset | Hi! If I'm not mistaken, this behavior is intentional, but I agree it could be more intuitive.
@albertvillanova Do you remember why you decided not to decode columns in the `Audio` feature PR when `input_columns` is not `None`? IMO we should decode those columns, and we don't even have to use lazy structures here be... | ## Describe the bug
The `datasets.features.Image` feature class decodes image data by default. Expectedly, when indexing a dataset or using the `map()` method, images are returned as PIL Image instances.
However, when calling `map()` and setting a specific data column with the `input_columns` argument, the image ... | 68 | Images get decoded when using `map()` with `input_columns` argument on a dataset
## Describe the bug
The `datasets.features.Image` feature class decodes image data by default. Expectedly, when indexing a dataset or using the `map()` method, images are returned as PIL Image instances.
However, when calling `map()`... |
https://github.com/huggingface/datasets/issues/3756 | Images get decoded when using `map()` with `input_columns` argument on a dataset | I think I excluded to decorate the function when `input_columns` were passed as a quick fix for some non-passing tests:
- https://github.com/huggingface/datasets/pull/2324/commits/9d7c3e8fa53e23ec636859b4407eeec904b1b3f9
That PR was quite complex and I decided to focus on the main feature requests, leaving refinem... | ## Describe the bug
The `datasets.features.Image` feature class decodes image data by default. Expectedly, when indexing a dataset or using the `map()` method, images are returned as PIL Image instances.
However, when calling `map()` and setting a specific data column with the `input_columns` argument, the image ... | 92 | Images get decoded when using `map()` with `input_columns` argument on a dataset
## Describe the bug
The `datasets.features.Image` feature class decodes image data by default. Expectedly, when indexing a dataset or using the `map()` method, images are returned as PIL Image instances.
However, when calling `map()`... |
https://github.com/huggingface/datasets/issues/5360 | IterableDataset returns duplicated data using PyTorch DDP | If you use huggingface trainer, you will find the trainer has wrapped a `IterableDatasetShard` to avoid duplication.
See:
https://github.com/huggingface/transformers/blob/dfd818420dcbad68e05a502495cf666d338b2bfb/src/transformers/trainer.py#L835
| As mentioned in https://github.com/huggingface/datasets/issues/3423, when using PyTorch DDP the dataset ends up with duplicated data. We already check for the PyTorch `worker_info` for single node, but we should also check for `torch.distributed.get_world_size()` and `torch.distributed.get_rank()` | 19 | IterableDataset returns duplicated data using PyTorch DDP
As mentioned in https://github.com/huggingface/datasets/issues/3423, when using PyTorch DDP the dataset ends up with duplicated data. We already check for the PyTorch `worker_info` for single node, but we should also check for `torch.distributed.get_world_size()... |
https://github.com/huggingface/datasets/issues/5360 | IterableDataset returns duplicated data using PyTorch DDP | If you want to support it by datasets natively, maybe we also need to change the code in `transformers` ? | As mentioned in https://github.com/huggingface/datasets/issues/3423, when using PyTorch DDP the dataset ends up with duplicated data. We already check for the PyTorch `worker_info` for single node, but we should also check for `torch.distributed.get_world_size()` and `torch.distributed.get_rank()` | 20 | IterableDataset returns duplicated data using PyTorch DDP
As mentioned in https://github.com/huggingface/datasets/issues/3423, when using PyTorch DDP the dataset ends up with duplicated data. We already check for the PyTorch `worker_info` for single node, but we should also check for `torch.distributed.get_world_size()... |
https://github.com/huggingface/datasets/issues/5360 | IterableDataset returns duplicated data using PyTorch DDP | Maybe something like this then ?
```python
from datasets.distributed import split_dataset_by_node
ds = split_dataset_by_node(ds, rank=rank, world_size=world_size)
```
For map-style datasets the implementation is trivial (it can simply use `.shard()`).
For iterable datasets we would need to implement a new Exa... | As mentioned in https://github.com/huggingface/datasets/issues/3423, when using PyTorch DDP the dataset ends up with duplicated data. We already check for the PyTorch `worker_info` for single node, but we should also check for `torch.distributed.get_world_size()` and `torch.distributed.get_rank()` | 66 | IterableDataset returns duplicated data using PyTorch DDP
As mentioned in https://github.com/huggingface/datasets/issues/3423, when using PyTorch DDP the dataset ends up with duplicated data. We already check for the PyTorch `worker_info` for single node, but we should also check for `torch.distributed.get_world_size()... |
https://github.com/huggingface/datasets/issues/5360 | IterableDataset returns duplicated data using PyTorch DDP | My plan is to skip examples by default to not end up with duplicates.
And if a dataset has a number of shards that is a factor of the world size, then I'd make it more optimized by distributing the shards evenly across nodes instead. | As mentioned in https://github.com/huggingface/datasets/issues/3423, when using PyTorch DDP the dataset ends up with duplicated data. We already check for the PyTorch `worker_info` for single node, but we should also check for `torch.distributed.get_world_size()` and `torch.distributed.get_rank()` | 45 | IterableDataset returns duplicated data using PyTorch DDP
As mentioned in https://github.com/huggingface/datasets/issues/3423, when using PyTorch DDP the dataset ends up with duplicated data. We already check for the PyTorch `worker_info` for single node, but we should also check for `torch.distributed.get_world_size()... |
https://github.com/huggingface/datasets/issues/5360 | IterableDataset returns duplicated data using PyTorch DDP | Opened a PR here: https://github.com/huggingface/datasets/pull/5369
feel free to play with it and share your feedbacks :) | As mentioned in https://github.com/huggingface/datasets/issues/3423, when using PyTorch DDP the dataset ends up with duplicated data. We already check for the PyTorch `worker_info` for single node, but we should also check for `torch.distributed.get_world_size()` and `torch.distributed.get_rank()` | 16 | IterableDataset returns duplicated data using PyTorch DDP
As mentioned in https://github.com/huggingface/datasets/issues/3423, when using PyTorch DDP the dataset ends up with duplicated data. We already check for the PyTorch `worker_info` for single node, but we should also check for `torch.distributed.get_world_size()... |
https://github.com/huggingface/datasets/issues/5360 | IterableDataset returns duplicated data using PyTorch DDP | @lhoestq I add shuffle after split_dataset_by_node, duplicated data still exist.
For example, we have a directory named `mock_pretraining_data`, which has three files, `part-00000`, `part-00002`,`part-00002`.
Text in `part-00000` is like this:
{"id": 0}
{"id": 1}
{"id": 2}
{"id": 3}
{"id": 4}
{"id": 5}
{"id... | As mentioned in https://github.com/huggingface/datasets/issues/3423, when using PyTorch DDP the dataset ends up with duplicated data. We already check for the PyTorch `worker_info` for single node, but we should also check for `torch.distributed.get_world_size()` and `torch.distributed.get_rank()` | 403 | IterableDataset returns duplicated data using PyTorch DDP
As mentioned in https://github.com/huggingface/datasets/issues/3423, when using PyTorch DDP the dataset ends up with duplicated data. We already check for the PyTorch `worker_info` for single node, but we should also check for `torch.distributed.get_world_size()... |
https://github.com/huggingface/datasets/issues/5360 | IterableDataset returns duplicated data using PyTorch DDP | Hi ! Thanks for reporting, you need to pass `seed=` to `shuffle()` or the processes won't use the same seed to shuffle the shards order before assigning each shard to a node.
The issue is that the workers are not using the same seed to shuffle the shards before splitting the shards list by node. | As mentioned in https://github.com/huggingface/datasets/issues/3423, when using PyTorch DDP the dataset ends up with duplicated data. We already check for the PyTorch `worker_info` for single node, but we should also check for `torch.distributed.get_world_size()` and `torch.distributed.get_rank()` | 55 | IterableDataset returns duplicated data using PyTorch DDP
As mentioned in https://github.com/huggingface/datasets/issues/3423, when using PyTorch DDP the dataset ends up with duplicated data. We already check for the PyTorch `worker_info` for single node, but we should also check for `torch.distributed.get_world_size()... |
https://github.com/huggingface/datasets/issues/5360 | IterableDataset returns duplicated data using PyTorch DDP | I have the same issue
```
ds['train'] = load_dataset(streaming=True)
ds['train'] = split_dataset_by_node(ds['train'], rank=int(os.environ["RANK"]), world_size=int(os.environ["WORLD_SIZE"]))
vectorized_datasets = ds.map(
prepare_dataset,
remove_columns=raw_datasets_features,
).with_format("torch")
vect... | As mentioned in https://github.com/huggingface/datasets/issues/3423, when using PyTorch DDP the dataset ends up with duplicated data. We already check for the PyTorch `worker_info` for single node, but we should also check for `torch.distributed.get_world_size()` and `torch.distributed.get_rank()` | 118 | IterableDataset returns duplicated data using PyTorch DDP
As mentioned in https://github.com/huggingface/datasets/issues/3423, when using PyTorch DDP the dataset ends up with duplicated data. We already check for the PyTorch `worker_info` for single node, but we should also check for `torch.distributed.get_world_size()... |
https://github.com/huggingface/datasets/issues/5360 | IterableDataset returns duplicated data using PyTorch DDP | There are two ways an iterable dataset can be split by node:
1. if the number of shards is a factor of number of GPUs: in that case the shards are evenly distributed per GPU
2. otherwise, each GPU iterate on the data and at the end keeps 1 sample out of n(GPUs) - skipping the others.
In case 2. it's therefore poss... | As mentioned in https://github.com/huggingface/datasets/issues/3423, when using PyTorch DDP the dataset ends up with duplicated data. We already check for the PyTorch `worker_info` for single node, but we should also check for `torch.distributed.get_world_size()` and `torch.distributed.get_rank()` | 111 | IterableDataset returns duplicated data using PyTorch DDP
As mentioned in https://github.com/huggingface/datasets/issues/3423, when using PyTorch DDP the dataset ends up with duplicated data. We already check for the PyTorch `worker_info` for single node, but we should also check for `torch.distributed.get_world_size()... |
https://github.com/huggingface/datasets/issues/6618 | While importing load_dataset from datasets | Hi! Can you please share the error's stack trace so we can see where it comes from? | ### Describe the bug
cannot import name 'DEFAULT_CIPHERS' from 'urllib3.util.ssl_' this is the error i received
### Steps to reproduce the bug
from datasets import load_dataset
### Expected behavior
No errors
### Environment info
python 3.11.5 | 17 | While importing load_dataset from datasets
### Describe the bug
cannot import name 'DEFAULT_CIPHERS' from 'urllib3.util.ssl_' this is the error i received
### Steps to reproduce the bug
from datasets import load_dataset
### Expected behavior
No errors
### Environment info
python 3.11.5
Hi! Can you please share ... |
https://github.com/huggingface/datasets/issues/6618 | While importing load_dataset from datasets | We cannot reproduce the issue and we do not have enough information: environment info (need to run `datasets-cli env`), stack trace,...
I am closing the issue. Feel free to reopen it (with additional information) if the problem persists. | ### Describe the bug
cannot import name 'DEFAULT_CIPHERS' from 'urllib3.util.ssl_' this is the error i received
### Steps to reproduce the bug
from datasets import load_dataset
### Expected behavior
No errors
### Environment info
python 3.11.5 | 38 | While importing load_dataset from datasets
### Describe the bug
cannot import name 'DEFAULT_CIPHERS' from 'urllib3.util.ssl_' this is the error i received
### Steps to reproduce the bug
from datasets import load_dataset
### Expected behavior
No errors
### Environment info
python 3.11.5
We cannot reproduce the i... |
https://github.com/huggingface/datasets/issues/6618 | While importing load_dataset from datasets | Yeah 👍
On Tue, 6 Feb 2024 at 2:56 PM, Albert Villanova del Moral <
***@***.***> wrote:
> We cannot reproduce the issue and we do not have enough information:
> environment info (need to run datasets-cli env), stack trace,...
>
> I am closing the issue. Feel free to reopen it (with additional
> information) ... | ### Describe the bug
cannot import name 'DEFAULT_CIPHERS' from 'urllib3.util.ssl_' this is the error i received
### Steps to reproduce the bug
from datasets import load_dataset
### Expected behavior
No errors
### Environment info
python 3.11.5 | 96 | While importing load_dataset from datasets
### Describe the bug
cannot import name 'DEFAULT_CIPHERS' from 'urllib3.util.ssl_' this is the error i received
### Steps to reproduce the bug
from datasets import load_dataset
### Expected behavior
No errors
### Environment info
python 3.11.5
Yeah 👍
On Tue, 6 Feb ... |
https://github.com/huggingface/datasets/issues/6618 | While importing load_dataset from datasets | > Please downgrade the version of urllib3 if you have the same issue:
>
> !pip install urllib3==1.25.11
This worked for me. Thanks.
I use python 3.11 and datasets==2.20.0. Downgrading urllib3 to 1.25.11 worked in my case. | ### Describe the bug
cannot import name 'DEFAULT_CIPHERS' from 'urllib3.util.ssl_' this is the error i received
### Steps to reproduce the bug
from datasets import load_dataset
### Expected behavior
No errors
### Environment info
python 3.11.5 | 37 | While importing load_dataset from datasets
### Describe the bug
cannot import name 'DEFAULT_CIPHERS' from 'urllib3.util.ssl_' this is the error i received
### Steps to reproduce the bug
from datasets import load_dataset
### Expected behavior
No errors
### Environment info
python 3.11.5
> Please downgrade the ve... |
https://github.com/huggingface/datasets/issues/4435 | Load a local cached dataset that has been modified | Hi! `datasets` caches every modification/loading, so you can either rerun the pipeline up to the `map` call or use `Dataset.from_file(modified_dataset)` to load the dataset directly from the cache file. | ## Describe the bug
I have loaded a dataset as follows:
```
d = load_dataset("emotion", split="validation")
```
Afterwards I make some modifications to the dataset via a `map` call:
```
d.map(some_update_func, cache_file_name=modified_dataset)
```
This generates a cached version of the dataset on my local syst... | 29 | Load a local cached dataset that has been modified
## Describe the bug
I have loaded a dataset as follows:
```
d = load_dataset("emotion", split="validation")
```
Afterwards I make some modifications to the dataset via a `map` call:
```
d.map(some_update_func, cache_file_name=modified_dataset)
```
This generat... |
https://github.com/huggingface/datasets/issues/4893 | Oversampling strategy for iterable datasets in `interleave_datasets` | Hi @lhoestq,
I plunged into the code and it should be manageable for me to work on it!
#take
Also, setting `d1`, `d2` and `d3` as you did raised a `SyntaxError: 'yield' inside list comprehension` for me, on Python 3.8.10.
The following snippet works for me though:
```
d1 = IterableDataset(ExamplesIterable((lamb... | In https://github.com/huggingface/datasets/pull/4831 @ylacombe added an oversampling strategy for `interleave_datasets`. However right now it doesn't work for datasets loaded using `load_dataset(..., streaming=True)`, which are `IterableDataset` objects.
It would be nice to expand `interleave_datasets` for iterable ... | 97 | Oversampling strategy for iterable datasets in `interleave_datasets`
In https://github.com/huggingface/datasets/pull/4831 @ylacombe added an oversampling strategy for `interleave_datasets`. However right now it doesn't work for datasets loaded using `load_dataset(..., streaming=True)`, which are `IterableDataset` objec... |
https://github.com/huggingface/datasets/issues/4893 | Oversampling strategy for iterable datasets in `interleave_datasets` | Hi @ylacombe :) Is there anything I can do to help ? Feel free to ping me if you have any question :) | In https://github.com/huggingface/datasets/pull/4831 @ylacombe added an oversampling strategy for `interleave_datasets`. However right now it doesn't work for datasets loaded using `load_dataset(..., streaming=True)`, which are `IterableDataset` objects.
It would be nice to expand `interleave_datasets` for iterable ... | 23 | Oversampling strategy for iterable datasets in `interleave_datasets`
In https://github.com/huggingface/datasets/pull/4831 @ylacombe added an oversampling strategy for `interleave_datasets`. However right now it doesn't work for datasets loaded using `load_dataset(..., streaming=True)`, which are `IterableDataset` objec... |
https://github.com/huggingface/datasets/issues/4893 | Oversampling strategy for iterable datasets in `interleave_datasets` | Hi @lhoestq,
I actually have already wrote the code last time [on this commit](https://github.com/ylacombe/datasets/commit/84769db97facc78a33ec53f7b1b395951e1804df) but I still have to change the docs and write some tests though. I'm working on it.
However, I still your advice on one matter.
In #4831, when usin... | In https://github.com/huggingface/datasets/pull/4831 @ylacombe added an oversampling strategy for `interleave_datasets`. However right now it doesn't work for datasets loaded using `load_dataset(..., streaming=True)`, which are `IterableDataset` objects.
It would be nice to expand `interleave_datasets` for iterable ... | 314 | Oversampling strategy for iterable datasets in `interleave_datasets`
In https://github.com/huggingface/datasets/pull/4831 @ylacombe added an oversampling strategy for `interleave_datasets`. However right now it doesn't work for datasets loaded using `load_dataset(..., streaming=True)`, which are `IterableDataset` objec... |
https://github.com/huggingface/datasets/issues/4893 | Oversampling strategy for iterable datasets in `interleave_datasets` | Hi ! Awesome :)
Maybe you can pre-load the next sample to know if the dataset is empty or not ?
This way it should be possible to have the same behavior for `IterableDataset` | In https://github.com/huggingface/datasets/pull/4831 @ylacombe added an oversampling strategy for `interleave_datasets`. However right now it doesn't work for datasets loaded using `load_dataset(..., streaming=True)`, which are `IterableDataset` objects.
It would be nice to expand `interleave_datasets` for iterable ... | 34 | Oversampling strategy for iterable datasets in `interleave_datasets`
In https://github.com/huggingface/datasets/pull/4831 @ylacombe added an oversampling strategy for `interleave_datasets`. However right now it doesn't work for datasets loaded using `load_dataset(..., streaming=True)`, which are `IterableDataset` objec... |
https://github.com/huggingface/datasets/issues/4893 | Oversampling strategy for iterable datasets in `interleave_datasets` | Hi @lhoestq, I've finally made some advances in the matter. I've modified the `IterableDataset` behavior so that it aligns with the `Dataset` behavior as we have discussed. The documentation has been dealt with too.
It works as expected on my examples. However I'm having trouble figuring out how to test `interleave_d... | In https://github.com/huggingface/datasets/pull/4831 @ylacombe added an oversampling strategy for `interleave_datasets`. However right now it doesn't work for datasets loaded using `load_dataset(..., streaming=True)`, which are `IterableDataset` objects.
It would be nice to expand `interleave_datasets` for iterable ... | 71 | Oversampling strategy for iterable datasets in `interleave_datasets`
In https://github.com/huggingface/datasets/pull/4831 @ylacombe added an oversampling strategy for `interleave_datasets`. However right now it doesn't work for datasets loaded using `load_dataset(..., streaming=True)`, which are `IterableDataset` objec... |
https://github.com/huggingface/datasets/issues/4893 | Oversampling strategy for iterable datasets in `interleave_datasets` | Thanks @ylacombe :)
Using the `pytest` command, you can run all the functions in a python file that start with "test_*" and make sure they return not errors:
```
pytest tests/test_iterable_dataset.py
```
In our case it can be nice to define a `test_interleave_datasets_with_oversampling` function. This function... | In https://github.com/huggingface/datasets/pull/4831 @ylacombe added an oversampling strategy for `interleave_datasets`. However right now it doesn't work for datasets loaded using `load_dataset(..., streaming=True)`, which are `IterableDataset` objects.
It would be nice to expand `interleave_datasets` for iterable ... | 66 | Oversampling strategy for iterable datasets in `interleave_datasets`
In https://github.com/huggingface/datasets/pull/4831 @ylacombe added an oversampling strategy for `interleave_datasets`. However right now it doesn't work for datasets loaded using `load_dataset(..., streaming=True)`, which are `IterableDataset` objec... |
https://github.com/huggingface/datasets/issues/3449 | Add `__add__()`, `__iadd__()` and similar to `Dataset` class | I was going through the codebase, and I believe the implementation of __add__() and __iadd__() will be similar to concatenate_datasets() after the elimination of code for arguments other than the list of datasets (info, split, axis).
(Assuming elimination of axis means concatenating over axis 1.) | **Is your feature request related to a problem? Please describe.**
No.
**Describe the solution you'd like**
I would like to be able to concatenate datasets as follows:
```python
>>> dataset["train"] += dataset["validation"]
```
... instead of using `concatenate_datasets()`:
```python
>>> raw_datasets["trai... | 45 | Add `__add__()`, `__iadd__()` and similar to `Dataset` class
**Is your feature request related to a problem? Please describe.**
No.
**Describe the solution you'd like**
I would like to be able to concatenate datasets as follows:
```python
>>> dataset["train"] += dataset["validation"]
```
... instead of using... |
https://github.com/huggingface/datasets/issues/3449 | Add `__add__()`, `__iadd__()` and similar to `Dataset` class | Most data frame libraries (Polars, Pandas, etc.) override `__add__` to perform (mathematical) summation, so having different behavior could lead to confusion. | **Is your feature request related to a problem? Please describe.**
No.
**Describe the solution you'd like**
I would like to be able to concatenate datasets as follows:
```python
>>> dataset["train"] += dataset["validation"]
```
... instead of using `concatenate_datasets()`:
```python
>>> raw_datasets["trai... | 21 | Add `__add__()`, `__iadd__()` and similar to `Dataset` class
**Is your feature request related to a problem? Please describe.**
No.
**Describe the solution you'd like**
I would like to be able to concatenate datasets as follows:
```python
>>> dataset["train"] += dataset["validation"]
```
... instead of using... |
https://github.com/huggingface/datasets/issues/5756 | Calling shuffle on a IterableDataset with streaming=True, gives "ValueError: cannot reshape array" | Thanks, this appears to have fixed the issue.
I've created a PR for the same change in the mnist dataset: https://huggingface.co/datasets/mnist/discussions/3/files | ### Describe the bug
When calling shuffle on a IterableDataset with streaming=True, I get the following error:
```
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/administrator/Documents/Projects/huggingface/jax-diffusers-sprint-consistency-models/virtualenv/lib/python3.1... | 21 | Calling shuffle on a IterableDataset with streaming=True, gives "ValueError: cannot reshape array"
### Describe the bug
When calling shuffle on a IterableDataset with streaming=True, I get the following error:
```
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/administra... |
https://github.com/huggingface/datasets/issues/6695 | Support JSON file with an array of strings | https://huggingface.co/datasets/CausalLM/Refined-Anime-Text/discussions/1 has been fixed, but how can we check if there are other datasets with the same error, in datasets-server's database? I don't know how to get the list of erroneous cache entries, since we only copied `Error code: JobManagerCrashedError`, but not... | Support loading a dataset from a JSON file with an array of strings.
See: https://huggingface.co/datasets/CausalLM/Refined-Anime-Text/discussions/1 | 58 | Support JSON file with an array of strings
Support loading a dataset from a JSON file with an array of strings.
See: https://huggingface.co/datasets/CausalLM/Refined-Anime-Text/discussions/1
https://huggingface.co/datasets/CausalLM/Refined-Anime-Text/discussions/1 has been fixed, but how can we check if there are ot... |
https://github.com/huggingface/datasets/issues/7863 | Support hosting lance / vortex / iceberg / zarr datasets on huggingface hub | @lhoestq thanks for your support! Any suggestions across `datasets` or `huggingface_hub` projects to make this happen?
I just noticed this blog post: https://huggingface.co/blog/streaming-datasets
Do you know if `hfFileSystem` from `huggingface_hub` is flexible enough to accommodate lance? I don't want to `open` and ... | ### Feature request
Huggingface datasets has great support for large tabular datasets in parquet with large partitions. I would love to see two things in the future:
- equivalent support for `lance`, `vortex`, `iceberg`, `zarr` (in that order) in a way that I can stream them using the datasets library
- more fine-gr... | 122 | Support hosting lance / vortex / iceberg / zarr datasets on huggingface hub
### Feature request
Huggingface datasets has great support for large tabular datasets in parquet with large partitions. I would love to see two things in the future:
- equivalent support for `lance`, `vortex`, `iceberg`, `zarr` (in that orde... |
https://github.com/huggingface/datasets/issues/7863 | Support hosting lance / vortex / iceberg / zarr datasets on huggingface hub | > Do you know if HfFileSystem from huggingface_hub is flexible enough to accommodate lance?
it provides file-like objects for files on HF, and works using range requests. PyArrow uses HfFileSystem for HF files already
Though in the Parquet / PyArrow case the data is read generally row group per row group (using range... | ### Feature request
Huggingface datasets has great support for large tabular datasets in parquet with large partitions. I would love to see two things in the future:
- equivalent support for `lance`, `vortex`, `iceberg`, `zarr` (in that order) in a way that I can stream them using the datasets library
- more fine-gr... | 131 | Support hosting lance / vortex / iceberg / zarr datasets on huggingface hub
### Feature request
Huggingface datasets has great support for large tabular datasets in parquet with large partitions. I would love to see two things in the future:
- equivalent support for `lance`, `vortex`, `iceberg`, `zarr` (in that orde... |
https://github.com/huggingface/datasets/issues/7863 | Support hosting lance / vortex / iceberg / zarr datasets on huggingface hub | Hi, I work on the Lance project. We'd be happy to see the format supported on huggingface hub.
It's not clear to me from this thread what is required for that. Could we clarify that? Are there examples we can point to?
> I think we might need a PR into `pyarrow` to create a `LanceFragmentScanOptions` class that subcl... | ### Feature request
Huggingface datasets has great support for large tabular datasets in parquet with large partitions. I would love to see two things in the future:
- equivalent support for `lance`, `vortex`, `iceberg`, `zarr` (in that order) in a way that I can stream them using the datasets library
- more fine-gr... | 124 | Support hosting lance / vortex / iceberg / zarr datasets on huggingface hub
### Feature request
Huggingface datasets has great support for large tabular datasets in parquet with large partitions. I would love to see two things in the future:
- equivalent support for `lance`, `vortex`, `iceberg`, `zarr` (in that orde... |
https://github.com/huggingface/datasets/issues/7863 | Support hosting lance / vortex / iceberg / zarr datasets on huggingface hub | > PS: there is an equivalent to HfFileSystem in rust in OpenDAL, but it only supports read from HF, not write (yet ?)
Hi, I’m willing to add full-fledged support for the HF file system. This shouldn’t be considered a blocker. 🤟 | ### Feature request
Huggingface datasets has great support for large tabular datasets in parquet with large partitions. I would love to see two things in the future:
- equivalent support for `lance`, `vortex`, `iceberg`, `zarr` (in that order) in a way that I can stream them using the datasets library
- more fine-gr... | 42 | Support hosting lance / vortex / iceberg / zarr datasets on huggingface hub
### Feature request
Huggingface datasets has great support for large tabular datasets in parquet with large partitions. I would love to see two things in the future:
- equivalent support for `lance`, `vortex`, `iceberg`, `zarr` (in that orde... |
https://github.com/huggingface/datasets/issues/7863 | Support hosting lance / vortex / iceberg / zarr datasets on huggingface hub | Exposing the existing HF filesystem from OpenDAL in pylance would be great ! and a good first step
Excited for write operations too | ### Feature request
Huggingface datasets has great support for large tabular datasets in parquet with large partitions. I would love to see two things in the future:
- equivalent support for `lance`, `vortex`, `iceberg`, `zarr` (in that order) in a way that I can stream them using the datasets library
- more fine-gr... | 23 | Support hosting lance / vortex / iceberg / zarr datasets on huggingface hub
### Feature request
Huggingface datasets has great support for large tabular datasets in parquet with large partitions. I would love to see two things in the future:
- equivalent support for `lance`, `vortex`, `iceberg`, `zarr` (in that orde... |
https://github.com/huggingface/datasets/issues/7863 | Support hosting lance / vortex / iceberg / zarr datasets on huggingface hub | Thanks @lhoestq @wjones127 @Xuanwo ! I think we have all the necessary people on this thread now to make it happen :)
> Could you elaborate why a FragmentScanOptions subclass is required? Also, if it is, we could just define that as a subclass within the pylance module, unless I'm missing something.
@wjones127 I'm no... | ### Feature request
Huggingface datasets has great support for large tabular datasets in parquet with large partitions. I would love to see two things in the future:
- equivalent support for `lance`, `vortex`, `iceberg`, `zarr` (in that order) in a way that I can stream them using the datasets library
- more fine-gr... | 259 | Support hosting lance / vortex / iceberg / zarr datasets on huggingface hub
### Feature request
Huggingface datasets has great support for large tabular datasets in parquet with large partitions. I would love to see two things in the future:
- equivalent support for `lance`, `vortex`, `iceberg`, `zarr` (in that orde... |
https://github.com/huggingface/datasets/issues/7863 | Support hosting lance / vortex / iceberg / zarr datasets on huggingface hub | Here's a public dataset which could be a working example to work backwards from:
https://huggingface.co/datasets/pavan-ramkumar/test-slaf
pylance currently looks for default object store backends and returns this `ValueError`
```
>>> import lance
>>> hf_path = "hf://datasets/pavan-ramkumar/test-slaf/tree/main/synthe... | ### Feature request
Huggingface datasets has great support for large tabular datasets in parquet with large partitions. I would love to see two things in the future:
- equivalent support for `lance`, `vortex`, `iceberg`, `zarr` (in that order) in a way that I can stream them using the datasets library
- more fine-gr... | 94 | Support hosting lance / vortex / iceberg / zarr datasets on huggingface hub
### Feature request
Huggingface datasets has great support for large tabular datasets in parquet with large partitions. I would love to see two things in the future:
- equivalent support for `lance`, `vortex`, `iceberg`, `zarr` (in that orde... |
https://github.com/huggingface/datasets/issues/7863 | Support hosting lance / vortex / iceberg / zarr datasets on huggingface hub | @Xuanwo @wjones127 just checking in to see if you had a chance to add a huggingface provider via opendal to pylance. I'm assuming we need a new `huggingface.rs` provider [here](https://github.com/lance-format/lance/tree/4d9c1a4d459ea486556de0ee90828a442d0425b0/rust/lance-io/src/object_store/providers).
Do let me know ... | ### Feature request
Huggingface datasets has great support for large tabular datasets in parquet with large partitions. I would love to see two things in the future:
- equivalent support for `lance`, `vortex`, `iceberg`, `zarr` (in that order) in a way that I can stream them using the datasets library
- more fine-gr... | 51 | Support hosting lance / vortex / iceberg / zarr datasets on huggingface hub
### Feature request
Huggingface datasets has great support for large tabular datasets in parquet with large partitions. I would love to see two things in the future:
- equivalent support for `lance`, `vortex`, `iceberg`, `zarr` (in that orde... |
https://github.com/huggingface/datasets/issues/7863 | Support hosting lance / vortex / iceberg / zarr datasets on huggingface hub | > @Xuanwo @wjones127 just checking in to see if you had a chance to add a huggingface provider via opendal to pylance. I'm assuming we need a new `huggingface.rs` provider [here](https://github.com/lance-format/lance/tree/4d9c1a4d459ea486556de0ee90828a442d0425b0/rust/lance-io/src/object_store/providers).
>
> Do let me... | ### Feature request
Huggingface datasets has great support for large tabular datasets in parquet with large partitions. I would love to see two things in the future:
- equivalent support for `lance`, `vortex`, `iceberg`, `zarr` (in that order) in a way that I can stream them using the datasets library
- more fine-gr... | 74 | Support hosting lance / vortex / iceberg / zarr datasets on huggingface hub
### Feature request
Huggingface datasets has great support for large tabular datasets in parquet with large partitions. I would love to see two things in the future:
- equivalent support for `lance`, `vortex`, `iceberg`, `zarr` (in that orde... |
https://github.com/huggingface/datasets/issues/7863 | Support hosting lance / vortex / iceberg / zarr datasets on huggingface hub | > I'm willing to work on this! Would you like to create an issue on lance side and ping me there?
Done! [Link](https://github.com/lance-format/lance/issues/5346)
| ### Feature request
Huggingface datasets has great support for large tabular datasets in parquet with large partitions. I would love to see two things in the future:
- equivalent support for `lance`, `vortex`, `iceberg`, `zarr` (in that order) in a way that I can stream them using the datasets library
- more fine-gr... | 23 | Support hosting lance / vortex / iceberg / zarr datasets on huggingface hub
### Feature request
Huggingface datasets has great support for large tabular datasets in parquet with large partitions. I would love to see two things in the future:
- equivalent support for `lance`, `vortex`, `iceberg`, `zarr` (in that orde... |
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... |
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... |
https://github.com/huggingface/datasets/issues/4525 | Out of memory error on workers while running Beam+Dataflow | Some naive ideas to cope with this:
- enable more RAM on each worker
- force the spanning of more workers
- others? | ## Describe the bug
While running the preprocessing of the natural_question dataset (see PR #4368), there is an issue for the "default" config (train+dev files).
Previously we ran the preprocessing for the "dev" config (only dev files) with success.
Train data files are larger than dev ones and apparently worker... | 23 | Out of memory error on workers while running Beam+Dataflow
## Describe the bug
While running the preprocessing of the natural_question dataset (see PR #4368), there is an issue for the "default" config (train+dev files).
Previously we ran the preprocessing for the "dev" config (only dev files) with success.
Trai... |
https://github.com/huggingface/datasets/issues/4525 | Out of memory error on workers while running Beam+Dataflow | @albertvillanova We were finally able to process the full NQ dataset on our machines using 600 gb with 5 workers. Maybe these numbers will work for you as well. | ## Describe the bug
While running the preprocessing of the natural_question dataset (see PR #4368), there is an issue for the "default" config (train+dev files).
Previously we ran the preprocessing for the "dev" config (only dev files) with success.
Train data files are larger than dev ones and apparently worker... | 29 | Out of memory error on workers while running Beam+Dataflow
## Describe the bug
While running the preprocessing of the natural_question dataset (see PR #4368), there is an issue for the "default" config (train+dev files).
Previously we ran the preprocessing for the "dev" config (only dev files) with success.
Trai... |
https://github.com/huggingface/datasets/issues/4525 | Out of memory error on workers while running Beam+Dataflow | Thanks a lot for the hint, @seirasto.
I have one question: what runner did you use? Direct, Apache Flink/Nemo/Samza/Spark, Google Dataflow...? Thank you. | ## Describe the bug
While running the preprocessing of the natural_question dataset (see PR #4368), there is an issue for the "default" config (train+dev files).
Previously we ran the preprocessing for the "dev" config (only dev files) with success.
Train data files are larger than dev ones and apparently worker... | 23 | Out of memory error on workers while running Beam+Dataflow
## Describe the bug
While running the preprocessing of the natural_question dataset (see PR #4368), there is an issue for the "default" config (train+dev files).
Previously we ran the preprocessing for the "dev" config (only dev files) with success.
Trai... |
https://github.com/huggingface/datasets/issues/4525 | Out of memory error on workers while running Beam+Dataflow | @albertvillanova Since we have already processed the NQ dataset on our machines can we upload it to datasets so the NQ PR can be merged? | ## Describe the bug
While running the preprocessing of the natural_question dataset (see PR #4368), there is an issue for the "default" config (train+dev files).
Previously we ran the preprocessing for the "dev" config (only dev files) with success.
Train data files are larger than dev ones and apparently worker... | 25 | Out of memory error on workers while running Beam+Dataflow
## Describe the bug
While running the preprocessing of the natural_question dataset (see PR #4368), there is an issue for the "default" config (train+dev files).
Previously we ran the preprocessing for the "dev" config (only dev files) with success.
Trai... |
https://github.com/huggingface/datasets/issues/4525 | Out of memory error on workers while running Beam+Dataflow | Maybe @lhoestq can give a more accurate answer as I am not sure about the authentication requirements to upload those files to our cloud bucket.
Anyway I propose to continue this discussion on the dedicated PR for Natural questions dataset:
- #4368 | ## Describe the bug
While running the preprocessing of the natural_question dataset (see PR #4368), there is an issue for the "default" config (train+dev files).
Previously we ran the preprocessing for the "dev" config (only dev files) with success.
Train data files are larger than dev ones and apparently worker... | 42 | Out of memory error on workers while running Beam+Dataflow
## Describe the bug
While running the preprocessing of the natural_question dataset (see PR #4368), there is an issue for the "default" config (train+dev files).
Previously we ran the preprocessing for the "dev" config (only dev files) with success.
Trai... |
https://github.com/huggingface/datasets/issues/4525 | Out of memory error on workers while running Beam+Dataflow | > I asked my colleague who ran the code and he said apache beam.
He looked into it further and he just used DirectRunner. @albertvillanova | ## Describe the bug
While running the preprocessing of the natural_question dataset (see PR #4368), there is an issue for the "default" config (train+dev files).
Previously we ran the preprocessing for the "dev" config (only dev files) with success.
Train data files are larger than dev ones and apparently worker... | 25 | Out of memory error on workers while running Beam+Dataflow
## Describe the bug
While running the preprocessing of the natural_question dataset (see PR #4368), there is an issue for the "default" config (train+dev files).
Previously we ran the preprocessing for the "dev" config (only dev files) with success.
Trai... |
https://github.com/huggingface/datasets/issues/4525 | Out of memory error on workers while running Beam+Dataflow | OK, thank you @seirasto for your hint.
That explains why you did not encounter the out of memory error: this only appears when the processing is distributed (on workers memory) and DirectRunner does not distribute the processing (all is done in a single machine). | ## Describe the bug
While running the preprocessing of the natural_question dataset (see PR #4368), there is an issue for the "default" config (train+dev files).
Previously we ran the preprocessing for the "dev" config (only dev files) with success.
Train data files are larger than dev ones and apparently worker... | 44 | Out of memory error on workers while running Beam+Dataflow
## Describe the bug
While running the preprocessing of the natural_question dataset (see PR #4368), there is an issue for the "default" config (train+dev files).
Previously we ran the preprocessing for the "dev" config (only dev files) with success.
Trai... |
https://github.com/huggingface/datasets/issues/4525 | Out of memory error on workers while running Beam+Dataflow | @albertvillanova Doesn't DirectRunner offer distributed processing through?
https://beam.apache.org/documentation/runners/direct/
```
Setting parallelism
Number of threads or subprocesses is defined by setting the direct_num_workers pipeline option. From 2.22.0, direct_num_workers = 0 is supported. When direc... | ## Describe the bug
While running the preprocessing of the natural_question dataset (see PR #4368), there is an issue for the "default" config (train+dev files).
Previously we ran the preprocessing for the "dev" config (only dev files) with success.
Train data files are larger than dev ones and apparently worker... | 130 | Out of memory error on workers while running Beam+Dataflow
## Describe the bug
While running the preprocessing of the natural_question dataset (see PR #4368), there is an issue for the "default" config (train+dev files).
Previously we ran the preprocessing for the "dev" config (only dev files) with success.
Trai... |
https://github.com/huggingface/datasets/issues/4525 | Out of memory error on workers while running Beam+Dataflow | Unrelated to the OOM issue, but we deprecated datasets with Beam scripts in #6474. I think we can close this issue | ## Describe the bug
While running the preprocessing of the natural_question dataset (see PR #4368), there is an issue for the "default" config (train+dev files).
Previously we ran the preprocessing for the "dev" config (only dev files) with success.
Train data files are larger than dev ones and apparently worker... | 21 | Out of memory error on workers while running Beam+Dataflow
## Describe the bug
While running the preprocessing of the natural_question dataset (see PR #4368), there is an issue for the "default" config (train+dev files).
Previously we ran the preprocessing for the "dev" config (only dev files) with success.
Trai... |
https://github.com/huggingface/datasets/issues/6670 | ValueError | Hi @prashanth19bolukonda,
You have to restart the notebook runtime session after the installation of `datasets`.
Duplicate of:
- #5923 | ### Describe the bug
ValueError Traceback (most recent call last)
[<ipython-input-11-9b99bc80ec23>](https://localhost:8080/#) in <cell line: 11>()
9 import numpy as np
10 import matplotlib.pyplot as plt
---> 11 from datasets import DatasetDict, Dataset
12 from transf... | 19 | ValueError
### Describe the bug
ValueError Traceback (most recent call last)
[<ipython-input-11-9b99bc80ec23>](https://localhost:8080/#) in <cell line: 11>()
9 import numpy as np
10 import matplotlib.pyplot as plt
---> 11 from datasets import DatasetDict, Dataset
12 ... |
https://github.com/huggingface/datasets/issues/6670 | ValueError | Thank you soo much
On Fri, Feb 16, 2024 at 8:14 PM Albert Villanova del Moral <
***@***.***> wrote:
> Closed #6670 <https://github.com/huggingface/datasets/issues/6670> as
> completed.
>
> —
> Reply to this email directly, view it on GitHub
> <https://github.com/huggingface/datasets/issues/6670#event-118297... | ### Describe the bug
ValueError Traceback (most recent call last)
[<ipython-input-11-9b99bc80ec23>](https://localhost:8080/#) in <cell line: 11>()
9 import numpy as np
10 import matplotlib.pyplot as plt
---> 11 from datasets import DatasetDict, Dataset
12 from transf... | 61 | ValueError
### Describe the bug
ValueError Traceback (most recent call last)
[<ipython-input-11-9b99bc80ec23>](https://localhost:8080/#) in <cell line: 11>()
9 import numpy as np
10 import matplotlib.pyplot as plt
---> 11 from datasets import DatasetDict, Dataset
12 ... |
https://github.com/huggingface/datasets/issues/5601 | Authorization error | Hi!
It's better to report this kind of issue in the `huggingface_hub` repo, so if you still haven't resolved it, I suggest you open an issue there. | ### Describe the bug
Get `Authorization error` when try to push data into hugginface datasets hub.
### Steps to reproduce the bug
I did all steps in the [tutorial](https://huggingface.co/docs/datasets/share),
1. `huggingface-cli login` with WRITE token
2. `git lfs install`
3. `git clone https://huggingfa... | 27 | Authorization error
### Describe the bug
Get `Authorization error` when try to push data into hugginface datasets hub.
### Steps to reproduce the bug
I did all steps in the [tutorial](https://huggingface.co/docs/datasets/share),
1. `huggingface-cli login` with WRITE token
2. `git lfs install`
3. `git clo... |
https://github.com/huggingface/datasets/issues/5601 | Authorization error | Yeah, I solved it. Problem was in osxkeychain. When I do `hugginface-cli login` it's add token with default account (username)`hg_user` but my repo contain other username. When I changed username in keychain - it works now. | ### Describe the bug
Get `Authorization error` when try to push data into hugginface datasets hub.
### Steps to reproduce the bug
I did all steps in the [tutorial](https://huggingface.co/docs/datasets/share),
1. `huggingface-cli login` with WRITE token
2. `git lfs install`
3. `git clone https://huggingfa... | 36 | Authorization error
### Describe the bug
Get `Authorization error` when try to push data into hugginface datasets hub.
### Steps to reproduce the bug
I did all steps in the [tutorial](https://huggingface.co/docs/datasets/share),
1. `huggingface-cli login` with WRITE token
2. `git lfs install`
3. `git clo... |
https://github.com/huggingface/datasets/issues/5671 | How to use `load_dataset('glue', 'cola')` | Sounds like an issue with incompatible `transformers` dependencies versions.
Can you try to update `transformers` ?
EDIT: I checked the `transformers` dependencies and it seems like you need `tokenizers>=0.10.1,<0.11` with `transformers==4.5.1`
EDIT2: this old version of `datasets` seems to import `transformer... | ### Describe the bug
I'm new to use HuggingFace datasets but I cannot use `load_dataset('glue', 'cola')`.
- I was stacked by the following problem:
```python
from datasets import load_dataset
cola_dataset = load_dataset('glue', 'cola')
------------------------------------------------------------------------... | 59 | How to use `load_dataset('glue', 'cola')`
### Describe the bug
I'm new to use HuggingFace datasets but I cannot use `load_dataset('glue', 'cola')`.
- I was stacked by the following problem:
```python
from datasets import load_dataset
cola_dataset = load_dataset('glue', 'cola')
------------------------------... |
https://github.com/huggingface/datasets/issues/5671 | How to use `load_dataset('glue', 'cola')` | Thank you for advising me to update these libraries versions.
I can implement codes using `datasets==2.10.1` and `transformers==4.27.3` | ### Describe the bug
I'm new to use HuggingFace datasets but I cannot use `load_dataset('glue', 'cola')`.
- I was stacked by the following problem:
```python
from datasets import load_dataset
cola_dataset = load_dataset('glue', 'cola')
------------------------------------------------------------------------... | 18 | How to use `load_dataset('glue', 'cola')`
### Describe the bug
I'm new to use HuggingFace datasets but I cannot use `load_dataset('glue', 'cola')`.
- I was stacked by the following problem:
```python
from datasets import load_dataset
cola_dataset = load_dataset('glue', 'cola')
------------------------------... |
https://github.com/huggingface/datasets/issues/7528 | Data Studio Error: Convert JSONL incorrectly | Hi ! Your JSONL file is incompatible with Arrow / Parquet. Indeed in Arrow / Parquet every dict should have the same keys, while in your dataset the bboxes have varying keys.
This causes the Data Studio to treat the bboxes as if each row was missing the keys from other rows.
Feel free to take a look at the docs on ob... | ### Describe the bug
Hi there,
I uploaded a dataset here https://huggingface.co/datasets/V-STaR-Bench/V-STaR, but I found that Data Studio incorrectly convert the "bboxes" value for the whole dataset. Therefore, anyone who downloaded the dataset via the API would get the wrong "bboxes" value in the data file.
Could ... | 74 | Data Studio Error: Convert JSONL incorrectly
### Describe the bug
Hi there,
I uploaded a dataset here https://huggingface.co/datasets/V-STaR-Bench/V-STaR, but I found that Data Studio incorrectly convert the "bboxes" value for the whole dataset. Therefore, anyone who downloaded the dataset via the API would get the w... |
https://github.com/huggingface/datasets/issues/6891 | Unable to load JSON saved using `to_json` | Hi @DarshanDeshpande,
Please note that the default format of the method `Dataset.to_json` is [JSON-Lines](https://jsonlines.org/): it passes `orient="records", lines=True` to `pandas.DataFrame.to_json`. This format is specially useful for large datasets, since unlike regular JSON files, it does not require loading a... | ### Describe the bug
Datasets stored in the JSON format cannot be loaded using `json.load()`
### Steps to reproduce the bug
```
import json
from datasets import load_dataset
dataset = load_dataset("squad")
train_dataset, test_dataset = dataset["train"], dataset["validation"]
test_dataset.to_json("full_dataset... | 92 | Unable to load JSON saved using `to_json`
### Describe the bug
Datasets stored in the JSON format cannot be loaded using `json.load()`
### Steps to reproduce the bug
```
import json
from datasets import load_dataset
dataset = load_dataset("squad")
train_dataset, test_dataset = dataset["train"], dataset["valida... |
https://github.com/huggingface/datasets/issues/6565 | `drop_last_batch=True` for IterableDataset map function is ignored with multiprocessing DataLoader | My current workaround this issue is to return `None` in the second element and then filter out samples which have `None` in them.
```python
def merge_samples(batch):
if len(batch['a']) == 1:
batch['c'] = [batch['a'][0]]
batch['d'] = [None]
else:
batch['c'] = [batch['a'][0]]
... | ### Describe the bug
Scenario:
- Interleaving two iterable datasets of unequal lengths (`all_exhausted`), followed by a batch mapping with batch size 2 to effectively merge the two datasets and get a sample from each dataset in a single batch, with `drop_last_batch=True` to skip the last batch in case it doesn't ha... | 59 | `drop_last_batch=True` for IterableDataset map function is ignored with multiprocessing DataLoader
### Describe the bug
Scenario:
- Interleaving two iterable datasets of unequal lengths (`all_exhausted`), followed by a batch mapping with batch size 2 to effectively merge the two datasets and get a sample from eac... |
https://github.com/huggingface/datasets/issues/6565 | `drop_last_batch=True` for IterableDataset map function is ignored with multiprocessing DataLoader | Hi @lhoestq , I found that this script no longer works due to this [line](https://github.com/huggingface/datasets/blob/f693f4e93aabafa878470c80fd42ddb10ec550d6/src/datasets/iterable_dataset.py#L1141), where it checks the validity before the column `a` is removed. Is this expected? | ### Describe the bug
Scenario:
- Interleaving two iterable datasets of unequal lengths (`all_exhausted`), followed by a batch mapping with batch size 2 to effectively merge the two datasets and get a sample from each dataset in a single batch, with `drop_last_batch=True` to skip the last batch in case it doesn't ha... | 29 | `drop_last_batch=True` for IterableDataset map function is ignored with multiprocessing DataLoader
### Describe the bug
Scenario:
- Interleaving two iterable datasets of unequal lengths (`all_exhausted`), followed by a batch mapping with batch size 2 to effectively merge the two datasets and get a sample from eac... |
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