html_url stringlengths 48 51 | title stringlengths 5 280 | comments stringlengths 63 51.8k | body stringlengths 0 36.2k ⌀ | comment_length int64 16 1.52k | text stringlengths 159 54.1k | embeddings listlengths 768 768 |
|---|---|---|---|---|---|---|
https://github.com/huggingface/datasets/issues/4632 | 'sort' method sorts one column only | Hi ! `ds.sort()` does sort the full dataset, not just one column:
```python
from datasets import *
ds = Dataset.from_dict({"foo": [3, 2, 1], "bar": ["c", "b", "a"]})
print(d.sort("foo").to_pandas()
# foo bar
# 0 1 a
# 1 2 b
# 2 3 c
```
What made you think it was not the case ? Did you ex... | The 'sort' method changes the order of one column only (the one defined by the argument 'column'), thus creating a mismatch between a sample fields. I would expect it to change the order of the samples as a whole, based on the 'column' order. | 67 | 'sort' method sorts one column only
The 'sort' method changes the order of one column only (the one defined by the argument 'column'), thus creating a mismatch between a sample fields. I would expect it to change the order of the samples as a whole, based on the 'column' order.
Hi ! `ds.sort()` does sort the full d... | [
0.28042128682136536,
-0.11438897997140884,
-0.09566597640514374,
0.1052810400724411,
0.24284778535366058,
-0.04496185481548309,
0.2915063202381134,
0.1874726563692093,
0.02114611119031906,
0.3759722113609314,
0.05880950391292572,
0.3416837155818939,
0.3120458126068115,
0.060936711728572845... |
https://github.com/huggingface/datasets/issues/4632 | 'sort' method sorts one column only | Hi! thank you for your quick reply!
I wanted to sort the `cnn_dailymail` dataset by the length of the labels (num of characters). I added a new column to the dataset (`ds.add_column`) with the lengths and then sorted by this new column. Only the new length column was sorted, the reset left in their original order. | The 'sort' method changes the order of one column only (the one defined by the argument 'column'), thus creating a mismatch between a sample fields. I would expect it to change the order of the samples as a whole, based on the 'column' order. | 56 | 'sort' method sorts one column only
The 'sort' method changes the order of one column only (the one defined by the argument 'column'), thus creating a mismatch between a sample fields. I would expect it to change the order of the samples as a whole, based on the 'column' order.
Hi! thank you for your quick reply!
... | [
0.3292351961135864,
-0.11990857869386673,
-0.042574502527713776,
0.08674963563680649,
0.1433679312467575,
-0.13137592375278473,
0.26586341857910156,
0.07707978785037994,
0.11549831926822662,
0.33633139729499817,
0.020844804123044014,
0.3247247338294983,
0.1618967354297638,
0.13079890608787... |
https://github.com/huggingface/datasets/issues/4623 | Loading MNIST as Pytorch Dataset | Hi ! We haven't implemented the conversion from images data to PyTorch tensors yet I think
cc @mariosasko | ## Describe the bug
Conversion of MNIST dataset to pytorch fails with bug
## Steps to reproduce the bug
```python
from datasets import load_dataset
dataset = load_dataset("mnist", split="train")
dataset.set_format('torch')
dataset[0]
print()
```
## Expected results
Expect to see torch tensors image and l... | 18 | Loading MNIST as Pytorch Dataset
## Describe the bug
Conversion of MNIST dataset to pytorch fails with bug
## Steps to reproduce the bug
```python
from datasets import load_dataset
dataset = load_dataset("mnist", split="train")
dataset.set_format('torch')
dataset[0]
print()
```
## Expected results
Expe... | [
-0.08833067119121552,
-0.09968702495098114,
0.01369825005531311,
0.1784951090812683,
0.29652881622314453,
-0.1651548445224762,
0.4545488953590393,
0.44875994324684143,
0.09683285653591156,
0.34280669689178467,
-0.03596876561641693,
0.7176253795623779,
-0.16904443502426147,
-0.1498889476060... |
https://github.com/huggingface/datasets/issues/4623 | Loading MNIST as Pytorch Dataset | So I understand:
set_format() does not properly do the conversion to pytorch tensors from PIL images.
So that someone who stumbles on this can use the package:
```python
dataset = load_dataset("mnist", split="train")
def transform_func(examples):
examples["image"] = [np.array(img) for img in examples["i... | ## Describe the bug
Conversion of MNIST dataset to pytorch fails with bug
## Steps to reproduce the bug
```python
from datasets import load_dataset
dataset = load_dataset("mnist", split="train")
dataset.set_format('torch')
dataset[0]
print()
```
## Expected results
Expect to see torch tensors image and l... | 48 | Loading MNIST as Pytorch Dataset
## Describe the bug
Conversion of MNIST dataset to pytorch fails with bug
## Steps to reproduce the bug
```python
from datasets import load_dataset
dataset = load_dataset("mnist", split="train")
dataset.set_format('torch')
dataset[0]
print()
```
## Expected results
Expe... | [
-0.08833067119121552,
-0.09968702495098114,
0.01369825005531311,
0.1784951090812683,
0.29652881622314453,
-0.1651548445224762,
0.4545488953590393,
0.44875994324684143,
0.09683285653591156,
0.34280669689178467,
-0.03596876561641693,
0.7176253795623779,
-0.16904443502426147,
-0.1498889476060... |
https://github.com/huggingface/datasets/issues/4623 | Loading MNIST as Pytorch Dataset | This then appears to work with pytorch dataloaders as:
```
dataloader=torch.utils.data.DataLoader(dataset,batch_size=1)
```
and tensorflow as:
```
dataset=dataset.to_tf_dataset(batch_size=1)
``` | ## Describe the bug
Conversion of MNIST dataset to pytorch fails with bug
## Steps to reproduce the bug
```python
from datasets import load_dataset
dataset = load_dataset("mnist", split="train")
dataset.set_format('torch')
dataset[0]
print()
```
## Expected results
Expect to see torch tensors image and l... | 18 | Loading MNIST as Pytorch Dataset
## Describe the bug
Conversion of MNIST dataset to pytorch fails with bug
## Steps to reproduce the bug
```python
from datasets import load_dataset
dataset = load_dataset("mnist", split="train")
dataset.set_format('torch')
dataset[0]
print()
```
## Expected results
Expe... | [
-0.08833067119121552,
-0.09968702495098114,
0.01369825005531311,
0.1784951090812683,
0.29652881622314453,
-0.1651548445224762,
0.4545488953590393,
0.44875994324684143,
0.09683285653591156,
0.34280669689178467,
-0.03596876561641693,
0.7176253795623779,
-0.16904443502426147,
-0.1498889476060... |
https://github.com/huggingface/datasets/issues/4623 | Loading MNIST as Pytorch Dataset | Hi! `set_transform`/`with_transform` is indeed the correct solution for the conversion. Improving this part of the API is one of the things I'm working on currently, so stay tuned! | ## Describe the bug
Conversion of MNIST dataset to pytorch fails with bug
## Steps to reproduce the bug
```python
from datasets import load_dataset
dataset = load_dataset("mnist", split="train")
dataset.set_format('torch')
dataset[0]
print()
```
## Expected results
Expect to see torch tensors image and l... | 28 | Loading MNIST as Pytorch Dataset
## Describe the bug
Conversion of MNIST dataset to pytorch fails with bug
## Steps to reproduce the bug
```python
from datasets import load_dataset
dataset = load_dataset("mnist", split="train")
dataset.set_format('torch')
dataset[0]
print()
```
## Expected results
Expe... | [
-0.08833067119121552,
-0.09968702495098114,
0.01369825005531311,
0.1784951090812683,
0.29652881622314453,
-0.1651548445224762,
0.4545488953590393,
0.44875994324684143,
0.09683285653591156,
0.34280669689178467,
-0.03596876561641693,
0.7176253795623779,
-0.16904443502426147,
-0.1498889476060... |
https://github.com/huggingface/datasets/issues/4619 | np arrays get turned into native lists | If you add the line `dataset2.set_format('np')` before calling `dataset2[0]['tmp']` it should return `np.ndarray`.
I believe internally it will not store it as a list, it is only returning a list when you index it.
```
In [1]: import datasets, numpy as np
In [2]: dataset = datasets.load_dataset("glue", "mrpc")["v... | ## Describe the bug
When attaching an `np.array` field, it seems that it automatically gets turned into a list (see below). Why is this happening? Could it lose precision? Is there a way to make sure this doesn't happen?
## Steps to reproduce the bug
```python
>>> import datasets, numpy as np
>>> dataset = datas... | 71 | np arrays get turned into native lists
## Describe the bug
When attaching an `np.array` field, it seems that it automatically gets turned into a list (see below). Why is this happening? Could it lose precision? Is there a way to make sure this doesn't happen?
## Steps to reproduce the bug
```python
>>> import d... | [
0.1432117521762848,
-0.08071322739124298,
-0.051935769617557526,
0.08374571800231934,
0.3818095326423645,
0.12156004458665848,
0.3182193338871002,
0.20185120403766632,
0.3359062969684601,
0.1461300551891327,
-0.0025853863917291164,
0.6777687668800354,
0.1720501333475113,
-0.083465047180652... |
https://github.com/huggingface/datasets/issues/4619 | np arrays get turned into native lists | I see, thanks! Any idea if the default numpy → list conversion might cause precision loss? | ## Describe the bug
When attaching an `np.array` field, it seems that it automatically gets turned into a list (see below). Why is this happening? Could it lose precision? Is there a way to make sure this doesn't happen?
## Steps to reproduce the bug
```python
>>> import datasets, numpy as np
>>> dataset = datas... | 16 | np arrays get turned into native lists
## Describe the bug
When attaching an `np.array` field, it seems that it automatically gets turned into a list (see below). Why is this happening? Could it lose precision? Is there a way to make sure this doesn't happen?
## Steps to reproduce the bug
```python
>>> import d... | [
0.0756758600473404,
-0.06403491646051407,
-0.04665675759315491,
0.016813814640045166,
0.369318425655365,
0.0984451100230217,
0.3085053563117981,
0.158713236451149,
0.2478821575641632,
0.1558501273393631,
0.03274393826723099,
0.6403751373291016,
0.18294264376163483,
-0.10110799968242645,
... |
https://github.com/huggingface/datasets/issues/4619 | np arrays get turned into native lists | I'm not super familiar with our datasets works internally, but I think your `np` array will be stored in a `pyarrow` format, and then you take a view of this as a python array. In which case, I think the precision should be preserved. | ## Describe the bug
When attaching an `np.array` field, it seems that it automatically gets turned into a list (see below). Why is this happening? Could it lose precision? Is there a way to make sure this doesn't happen?
## Steps to reproduce the bug
```python
>>> import datasets, numpy as np
>>> dataset = datas... | 44 | np arrays get turned into native lists
## Describe the bug
When attaching an `np.array` field, it seems that it automatically gets turned into a list (see below). Why is this happening? Could it lose precision? Is there a way to make sure this doesn't happen?
## Steps to reproduce the bug
```python
>>> import d... | [
0.08610011637210846,
-0.04592133313417435,
-0.05543023347854614,
0.03548063337802887,
0.3768509030342102,
0.09786156564950943,
0.27538272738456726,
0.1547374129295349,
0.1943834275007248,
0.1570320874452591,
0.01732492446899414,
0.6573179364204407,
0.1881696730852127,
-0.07049423456192017,... |
https://github.com/huggingface/datasets/issues/4618 | contribute data loading for object detection datasets with yolo data format | Hi! The `imagefolder` script is already quite complex, so a standalone script sounds better. Also, I suggest we create an org on the Hub (e.g. `hf-loaders`) and store such scripts there for easier maintenance rather than having them as packaged modules (IMO only very generic loaders should be packaged). WDYT @lhoestq @... | **Is your feature request related to a problem? Please describe.**
At the moment, HF datasets loads [image classification datasets](https://huggingface.co/docs/datasets/image_process) out-of-the-box. There could be a data loader for loading standard object detection datasets ([original discussion here](https://hugging... | 53 | contribute data loading for object detection datasets with yolo data format
**Is your feature request related to a problem? Please describe.**
At the moment, HF datasets loads [image classification datasets](https://huggingface.co/docs/datasets/image_process) out-of-the-box. There could be a data loader for loading ... | [
-0.19951283931732178,
-0.22327779233455658,
0.030088167637586594,
0.22801147401332855,
0.002493320032954216,
-0.1767904907464981,
0.3969922959804535,
0.3359566926956177,
0.7367866635322571,
0.016155928373336792,
-0.36364102363586426,
-0.009577297605574131,
-0.22434969246387482,
0.555282354... |
https://github.com/huggingface/datasets/issues/4618 | contribute data loading for object detection datasets with yolo data format | Thank you for the suggestion @mariosasko . I agree with the point, but I have a few doubts
1. How would the user access the script if it's not a part of the core codebase?
2. Could you direct me as to what will be the tasks I have to do to contribute to the code? As per my understanding, it would be like
1. Cr... | **Is your feature request related to a problem? Please describe.**
At the moment, HF datasets loads [image classification datasets](https://huggingface.co/docs/datasets/image_process) out-of-the-box. There could be a data loader for loading standard object detection datasets ([original discussion here](https://hugging... | 135 | contribute data loading for object detection datasets with yolo data format
**Is your feature request related to a problem? Please describe.**
At the moment, HF datasets loads [image classification datasets](https://huggingface.co/docs/datasets/image_process) out-of-the-box. There could be a data loader for loading ... | [
-0.08097722381353378,
-0.0058672428131103516,
0.01908848062157631,
0.14947840571403503,
-0.14927737414836884,
-0.057615093886852264,
0.4828805923461914,
0.22512643039226532,
0.6821538805961609,
0.06522554159164429,
-0.3322116434574127,
-0.11917440593242645,
-0.2263093888759613,
0.496855676... |
https://github.com/huggingface/datasets/issues/4618 | contribute data loading for object detection datasets with yolo data format | 1. Like this: `load_dataset("hf-loaders/yolo", data_files=...)`
2. The steps would be:
1. Create a new org `hf-community-loaders` (IMO a better name than "hf-loaders") and add me (as an admin)
2. Create a new dataset repo `yolo` and add the loading script to it (`yolo.py`)
3. Open a discussion to reques... | **Is your feature request related to a problem? Please describe.**
At the moment, HF datasets loads [image classification datasets](https://huggingface.co/docs/datasets/image_process) out-of-the-box. There could be a data loader for loading standard object detection datasets ([original discussion here](https://hugging... | 73 | contribute data loading for object detection datasets with yolo data format
**Is your feature request related to a problem? Please describe.**
At the moment, HF datasets loads [image classification datasets](https://huggingface.co/docs/datasets/image_process) out-of-the-box. There could be a data loader for loading ... | [
-0.18556027114391327,
-0.03586704283952713,
0.03169272840023041,
0.21702206134796143,
-0.050836190581321716,
-0.15607544779777527,
0.4227236807346344,
0.3171769976615906,
0.5954245924949646,
0.0406724289059639,
-0.3604072332382202,
-0.0022463675122708082,
-0.19751162827014923,
0.4584817588... |
https://github.com/huggingface/datasets/issues/4612 | Release 2.3.0 broke custom iterable datasets | Apparently, `fsspec` does not allow access to attribute-based modules anymore, such as `fsspec.async`.
However, this is a fairly simple fix:
- Change the import to: `from fsspec import asyn`;
- Change line 18 to: `asyn.iothread[0] = None`;
- Change line 19 to `asyn.loop[0] = None`. | ## Describe the bug
Trying to iterate examples from custom iterable dataset fails to bug introduced in `torch_iterable_dataset.py` since the release of 2.3.0.
## Steps to reproduce the bug
```python
next(iter(custom_iterable_dataset))
```
## Expected results
`next(iter(custom_iterable_dataset))` should retu... | 45 | Release 2.3.0 broke custom iterable datasets
## Describe the bug
Trying to iterate examples from custom iterable dataset fails to bug introduced in `torch_iterable_dataset.py` since the release of 2.3.0.
## Steps to reproduce the bug
```python
next(iter(custom_iterable_dataset))
```
## Expected results
`n... | [
-0.2921886742115021,
-0.13219138979911804,
-0.06178423762321472,
0.08947064727544785,
-0.027991287410259247,
-0.06942635774612427,
0.4363798201084137,
0.08186624944210052,
-0.10973890125751495,
0.03781239688396454,
0.07510139048099518,
0.42103448510169983,
-0.2893877327442169,
0.1537691503... |
https://github.com/huggingface/datasets/issues/4612 | Release 2.3.0 broke custom iterable datasets | Hi! I think it's easier to replace `import fsspec` with `import fsspec.asyn` and leave the rest unchanged. @gugarosa Are you interested in submitting a PR? | ## Describe the bug
Trying to iterate examples from custom iterable dataset fails to bug introduced in `torch_iterable_dataset.py` since the release of 2.3.0.
## Steps to reproduce the bug
```python
next(iter(custom_iterable_dataset))
```
## Expected results
`next(iter(custom_iterable_dataset))` should retu... | 25 | Release 2.3.0 broke custom iterable datasets
## Describe the bug
Trying to iterate examples from custom iterable dataset fails to bug introduced in `torch_iterable_dataset.py` since the release of 2.3.0.
## Steps to reproduce the bug
```python
next(iter(custom_iterable_dataset))
```
## Expected results
`n... | [
-0.29491984844207764,
-0.20614497363567352,
-0.09534762799739838,
0.046741463243961334,
-0.0868976041674614,
-0.041585780680179596,
0.4108291268348694,
0.09821152687072754,
-0.09093771874904633,
0.013974092900753021,
0.0952100083231926,
0.3712005317211151,
-0.28548166155815125,
0.191101893... |
https://github.com/huggingface/datasets/issues/4610 | codeparrot/github-code failing to load | I believe the issue is in `codeparrot/github-code`. `base_path` param is missing - https://huggingface.co/datasets/codeparrot/github-code/blob/main/github-code.py#L169
Function definition has changed.
https://github.com/huggingface/datasets/blob/0e1c629cfb9f9ba124537ba294a0ec451584da5f/src/datasets/data_files.py#L5... | ## Describe the bug
codeparrot/github-code fails to load with a `TypeError: get_patterns_in_dataset_repository() missing 1 required positional argument: 'base_path'`
## Steps to reproduce the bug
```python
from datasets import load_dataset
```
## Expected results
loaded dataset object
## Actual results
`... | 38 | codeparrot/github-code failing to load
## Describe the bug
codeparrot/github-code fails to load with a `TypeError: get_patterns_in_dataset_repository() missing 1 required positional argument: 'base_path'`
## Steps to reproduce the bug
```python
from datasets import load_dataset
```
## Expected results
loa... | [
-0.21699845790863037,
-0.06861083209514618,
-0.08182676136493683,
0.21229784190654755,
0.22685489058494568,
0.02494252473115921,
0.42694762349128723,
0.5157313346862793,
0.07178185880184174,
-0.03193691372871399,
0.2613385021686554,
0.543058454990387,
-0.08034840226173401,
0.21459496021270... |
https://github.com/huggingface/datasets/issues/4610 | codeparrot/github-code failing to load | Good catch ! We recently did a breaking change in `get_patterns_in_dataset_repository`, I think we can revert it | ## Describe the bug
codeparrot/github-code fails to load with a `TypeError: get_patterns_in_dataset_repository() missing 1 required positional argument: 'base_path'`
## Steps to reproduce the bug
```python
from datasets import load_dataset
```
## Expected results
loaded dataset object
## Actual results
`... | 17 | codeparrot/github-code failing to load
## Describe the bug
codeparrot/github-code fails to load with a `TypeError: get_patterns_in_dataset_repository() missing 1 required positional argument: 'base_path'`
## Steps to reproduce the bug
```python
from datasets import load_dataset
```
## Expected results
loa... | [
-0.21699845790863037,
-0.06861083209514618,
-0.08182676136493683,
0.21229784190654755,
0.22685489058494568,
0.02494252473115921,
0.42694762349128723,
0.5157313346862793,
0.07178185880184174,
-0.03193691372871399,
0.2613385021686554,
0.543058454990387,
-0.08034840226173401,
0.21459496021270... |
https://github.com/huggingface/datasets/issues/4610 | codeparrot/github-code failing to load | > Good catch ! We recently did a breaking change in `get_patterns_in_dataset_repository`, I think we can revert it
I can't wait for that releasee. Broke my application | ## Describe the bug
codeparrot/github-code fails to load with a `TypeError: get_patterns_in_dataset_repository() missing 1 required positional argument: 'base_path'`
## Steps to reproduce the bug
```python
from datasets import load_dataset
```
## Expected results
loaded dataset object
## Actual results
`... | 27 | codeparrot/github-code failing to load
## Describe the bug
codeparrot/github-code fails to load with a `TypeError: get_patterns_in_dataset_repository() missing 1 required positional argument: 'base_path'`
## Steps to reproduce the bug
```python
from datasets import load_dataset
```
## Expected results
loa... | [
-0.21699845790863037,
-0.06861083209514618,
-0.08182676136493683,
0.21229784190654755,
0.22685489058494568,
0.02494252473115921,
0.42694762349128723,
0.5157313346862793,
0.07178185880184174,
-0.03193691372871399,
0.2613385021686554,
0.543058454990387,
-0.08034840226173401,
0.21459496021270... |
https://github.com/huggingface/datasets/issues/4610 | codeparrot/github-code failing to load | This simple workaround should fix: https://huggingface.co/datasets/codeparrot/github-code/discussions/2
`get_patterns_in_dataset_repository` can treat whether `base_path=None`, so we just need to make sure that codeparrot/github-code `_split_generators` calls with such an argument. | ## Describe the bug
codeparrot/github-code fails to load with a `TypeError: get_patterns_in_dataset_repository() missing 1 required positional argument: 'base_path'`
## Steps to reproduce the bug
```python
from datasets import load_dataset
```
## Expected results
loaded dataset object
## Actual results
`... | 26 | codeparrot/github-code failing to load
## Describe the bug
codeparrot/github-code fails to load with a `TypeError: get_patterns_in_dataset_repository() missing 1 required positional argument: 'base_path'`
## Steps to reproduce the bug
```python
from datasets import load_dataset
```
## Expected results
loa... | [
-0.21699845790863037,
-0.06861083209514618,
-0.08182676136493683,
0.21229784190654755,
0.22685489058494568,
0.02494252473115921,
0.42694762349128723,
0.5157313346862793,
0.07178185880184174,
-0.03193691372871399,
0.2613385021686554,
0.543058454990387,
-0.08034840226173401,
0.21459496021270... |
https://github.com/huggingface/datasets/issues/4610 | codeparrot/github-code failing to load | I am afraid your suggested change @gugarosa will break compatibility with older datasets versions that don't have `base_path` argument in `get_patterns_in_dataset_repository`, as a workaround while the issue gets resolved in `datasets` can you downgrade your datasets version to `<=2.1.0` ?
@lvwerra do you think we s... | ## Describe the bug
codeparrot/github-code fails to load with a `TypeError: get_patterns_in_dataset_repository() missing 1 required positional argument: 'base_path'`
## Steps to reproduce the bug
```python
from datasets import load_dataset
```
## Expected results
loaded dataset object
## Actual results
`... | 57 | codeparrot/github-code failing to load
## Describe the bug
codeparrot/github-code fails to load with a `TypeError: get_patterns_in_dataset_repository() missing 1 required positional argument: 'base_path'`
## Steps to reproduce the bug
```python
from datasets import load_dataset
```
## Expected results
loa... | [
-0.21699845790863037,
-0.06861083209514618,
-0.08182676136493683,
0.21229784190654755,
0.22685489058494568,
0.02494252473115921,
0.42694762349128723,
0.5157313346862793,
0.07178185880184174,
-0.03193691372871399,
0.2613385021686554,
0.543058454990387,
-0.08034840226173401,
0.21459496021270... |
https://github.com/huggingface/datasets/issues/4610 | codeparrot/github-code failing to load | Actually I think it's just simpler to fix it in the dataset itself, let me open a PR
EDIT: PR opened here: https://huggingface.co/datasets/codeparrot/github-code/discussions/3 | ## Describe the bug
codeparrot/github-code fails to load with a `TypeError: get_patterns_in_dataset_repository() missing 1 required positional argument: 'base_path'`
## Steps to reproduce the bug
```python
from datasets import load_dataset
```
## Expected results
loaded dataset object
## Actual results
`... | 23 | codeparrot/github-code failing to load
## Describe the bug
codeparrot/github-code fails to load with a `TypeError: get_patterns_in_dataset_repository() missing 1 required positional argument: 'base_path'`
## Steps to reproduce the bug
```python
from datasets import load_dataset
```
## Expected results
loa... | [
-0.21699845790863037,
-0.06861083209514618,
-0.08182676136493683,
0.21229784190654755,
0.22685489058494568,
0.02494252473115921,
0.42694762349128723,
0.5157313346862793,
0.07178185880184174,
-0.03193691372871399,
0.2613385021686554,
0.543058454990387,
-0.08034840226173401,
0.21459496021270... |
https://github.com/huggingface/datasets/issues/4610 | codeparrot/github-code failing to load | > I am afraid your suggested change @gugarosa will break compatibility with older datasets versions that don't have `base_path` argument in `get_patterns_in_dataset_repository`, as a workaround while the issue gets resolved in `datasets` can you downgrade your datasets version to `<=2.1.0` ?
> @lvwerra do you think we... | ## Describe the bug
codeparrot/github-code fails to load with a `TypeError: get_patterns_in_dataset_repository() missing 1 required positional argument: 'base_path'`
## Steps to reproduce the bug
```python
from datasets import load_dataset
```
## Expected results
loaded dataset object
## Actual results
`... | 83 | codeparrot/github-code failing to load
## Describe the bug
codeparrot/github-code fails to load with a `TypeError: get_patterns_in_dataset_repository() missing 1 required positional argument: 'base_path'`
## Steps to reproduce the bug
```python
from datasets import load_dataset
```
## Expected results
loa... | [
-0.21699845790863037,
-0.06861083209514618,
-0.08182676136493683,
0.21229784190654755,
0.22685489058494568,
0.02494252473115921,
0.42694762349128723,
0.5157313346862793,
0.07178185880184174,
-0.03193691372871399,
0.2613385021686554,
0.543058454990387,
-0.08034840226173401,
0.21459496021270... |
https://github.com/huggingface/datasets/issues/4609 | librispeech dataset has to download whole subset when specifing the split to use | Hi! You can use streaming to fetch only a subset of the data:
```python
raw_dataset = load_dataset("librispeech_asr", "clean", split="train.100", streaming=True)
```
Also, we plan to make it possible to download a particular split in the non-streaming mode, but this task is not easy due to how our dataset scripts a... | ## Describe the bug
librispeech dataset has to download whole subset when specifing the split to use
## Steps to reproduce the bug
see below
# Sample code to reproduce the bug
```
!pip install datasets
from datasets import load_dataset
raw_dataset = load_dataset("librispeech_asr", "clean", split="train.100")
... | 51 | librispeech dataset has to download whole subset when specifing the split to use
## Describe the bug
librispeech dataset has to download whole subset when specifing the split to use
## Steps to reproduce the bug
see below
# Sample code to reproduce the bug
```
!pip install datasets
from datasets import load_... | [
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0.34216219186782837,
0.1499776989221573,
0.17393366992473602,
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0.13586130738258362,
0.07201629877090454,
0.330099821090698... |
https://github.com/huggingface/datasets/issues/4606 | evaluation result changes after `datasets` version change | Hi! The GH/no-namespace datasets versioning is synced with the version of the `datasets` lib, which means that the `wikiann` script was modified between the two compared versions. In this scenario, you can ensure reproducibility by pinning the script version, which is done by passing `revision="x.y.z"` (e.g. `revision=... | ## Describe the bug
evaluation result changes after `datasets` version change
## Steps to reproduce the bug
1. Train a model on WikiAnn
2. reload the ckpt -> test accuracy becomes same as eval accuracy
3. such behavior is gone after downgrading `datasets`
https://colab.research.google.com/drive/1kYz7-aZRGdaya... | 49 | evaluation result changes after `datasets` version change
## Describe the bug
evaluation result changes after `datasets` version change
## Steps to reproduce the bug
1. Train a model on WikiAnn
2. reload the ckpt -> test accuracy becomes same as eval accuracy
3. such behavior is gone after downgrading `dataset... | [
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0.2176782339811325,
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https://github.com/huggingface/datasets/issues/4605 | Dataset Viewer issue for boris/gis_filtered | Yes, this dataset is "gated": you first have to go to https://huggingface.co/datasets/boris/gis_filtered and click "Access repository" (if you accept to share your contact information with the repository authors). | ### Link
https://huggingface.co/datasets/boris/gis_filtered/viewer/boris--gis_filtered/train
### Description
When I try to access this from the website I get this error:
Status code: 400
Exception: ClientResponseError
Message: 401, message='Unauthorized', url=URL('https://huggingface.co/datase... | 28 | Dataset Viewer issue for boris/gis_filtered
### Link
https://huggingface.co/datasets/boris/gis_filtered/viewer/boris--gis_filtered/train
### Description
When I try to access this from the website I get this error:
Status code: 400
Exception: ClientResponseError
Message: 401, message='Unautho... | [
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0.05963234603404999,
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0.0706980973482132,
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-0.12292274087667465,
0.2470500... |
https://github.com/huggingface/datasets/issues/4605 | Dataset Viewer issue for boris/gis_filtered | I could reproduce the error, even though I provided my token and accepted the gate form. It looks like an error from `datasets` | ### Link
https://huggingface.co/datasets/boris/gis_filtered/viewer/boris--gis_filtered/train
### Description
When I try to access this from the website I get this error:
Status code: 400
Exception: ClientResponseError
Message: 401, message='Unauthorized', url=URL('https://huggingface.co/datase... | 23 | Dataset Viewer issue for boris/gis_filtered
### Link
https://huggingface.co/datasets/boris/gis_filtered/viewer/boris--gis_filtered/train
### Description
When I try to access this from the website I get this error:
Status code: 400
Exception: ClientResponseError
Message: 401, message='Unautho... | [
-0.05710578337311745,
0.05060245096683502,
0.023847457021474838,
0.37848860025405884,
0.28513962030410767,
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0.34150850772857666,
0.21559298038482666,
0.024247795343399048,
0.0655883252620697,
-0.2898719012737274,
-0.04889508709311485,
-0.045673105865716934,
0.273820132... |
https://github.com/huggingface/datasets/issues/4605 | Dataset Viewer issue for boris/gis_filtered | This is indeed a bug in `datasets`. Parquet datasets in gated/private repositories can't be streamed properly, which caused the viewer to fail. I opened a PR at https://github.com/huggingface/datasets/pull/4608 | ### Link
https://huggingface.co/datasets/boris/gis_filtered/viewer/boris--gis_filtered/train
### Description
When I try to access this from the website I get this error:
Status code: 400
Exception: ClientResponseError
Message: 401, message='Unauthorized', url=URL('https://huggingface.co/datase... | 28 | Dataset Viewer issue for boris/gis_filtered
### Link
https://huggingface.co/datasets/boris/gis_filtered/viewer/boris--gis_filtered/train
### Description
When I try to access this from the website I get this error:
Status code: 400
Exception: ClientResponseError
Message: 401, message='Unautho... | [
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0.04953332245349884,
0.04688606038689613,
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0.27279728651046753,
0.17340967059135437,
0.020985424518585205,
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0.023459542542696,
-0.12111867219209671,
0.33108198642... |
https://github.com/huggingface/datasets/issues/4597 | Streaming issue for financial_phrasebank | cc @huggingface/datasets: it seems like https://www.researchgate.net/ is flaky for datasets hosting (I put the "hosted-on-google-drive" tag since it's the same kind of issue I think) | ### Link
https://huggingface.co/datasets/financial_phrasebank/viewer/sentences_allagree/train
### Description
As reported by a community member using [AutoTrain Evaluate](https://huggingface.co/spaces/autoevaluate/model-evaluator/discussions/5#62bc217436d0e5d316a768f0), there seems to be a problem streaming this dat... | 25 | Streaming issue for financial_phrasebank
### Link
https://huggingface.co/datasets/financial_phrasebank/viewer/sentences_allagree/train
### Description
As reported by a community member using [AutoTrain Evaluate](https://huggingface.co/spaces/autoevaluate/model-evaluator/discussions/5#62bc217436d0e5d316a768f0), the... | [
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0.2318277657032013,
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0.20251834392547607,
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0.25727370381355286,
0.04684041440486908,
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0.08009576052427292,
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0.51984709501266... |
https://github.com/huggingface/datasets/issues/4597 | Streaming issue for financial_phrasebank | License is Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported (CC BY-NC-SA 3.0).
We can host their data on the Hub. | ### Link
https://huggingface.co/datasets/financial_phrasebank/viewer/sentences_allagree/train
### Description
As reported by a community member using [AutoTrain Evaluate](https://huggingface.co/spaces/autoevaluate/model-evaluator/discussions/5#62bc217436d0e5d316a768f0), there seems to be a problem streaming this dat... | 18 | Streaming issue for financial_phrasebank
### Link
https://huggingface.co/datasets/financial_phrasebank/viewer/sentences_allagree/train
### Description
As reported by a community member using [AutoTrain Evaluate](https://huggingface.co/spaces/autoevaluate/model-evaluator/discussions/5#62bc217436d0e5d316a768f0), the... | [
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0.19916777312755585,
0.36410027742385864,
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0.2073410451412201,
0.13552851974964142,
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0.007971175014972687,
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0.07511910051107407,
0.014804861508309841,
0.5022214651... |
https://github.com/huggingface/datasets/issues/4596 | Dataset Viewer issue for universal_dependencies | Finally fixed! We updated the dataset viewer and it fixed the issue.
https://huggingface.co/datasets/universal_dependencies/viewer/aqz_tudet/train
<img width="1561" alt="Capture d’écran 2022-09-07 à 13 29 18" src="https://user-images.githubusercontent.com/1676121/188867795-4f7dd438-d4f2-46cd-8a92-20a37fb2d6bc.p... | ### Link
https://huggingface.co/datasets/universal_dependencies
### Description
invalid json response body at https://datasets-server.huggingface.co/splits?dataset=universal_dependencies reason: Unexpected token I in JSON at position 0
### Owner
_No response_ | 23 | Dataset Viewer issue for universal_dependencies
### Link
https://huggingface.co/datasets/universal_dependencies
### Description
invalid json response body at https://datasets-server.huggingface.co/splits?dataset=universal_dependencies reason: Unexpected token I in JSON at position 0
### Owner
_No response_
Fin... | [
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0.21133314073085785,
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0.128121510... |
https://github.com/huggingface/datasets/issues/4595 | Dataset Viewer issue with False positive PII redaction | The value is in the data, it's not an issue with the "dataset-viewer".
<img width="1161" alt="Capture d’écran 2022-06-29 à 10 25 51" src="https://user-images.githubusercontent.com/1676121/176389325-4d2a9a7f-1583-45b8-aa7a-960ffaa6a36a.png">
Maybe open a PR: https://huggingface.co/datasets/cakiki/rosetta-code/d... | ### Link
https://huggingface.co/datasets/cakiki/rosetta-code
### Description
Hello, I just noticed an entry being redacted that shouldn't have been:
`RootMeanSquare@Range[10]` is being displayed as `[email protected][10]`
### Owner
_No response_ | 28 | Dataset Viewer issue with False positive PII redaction
### Link
https://huggingface.co/datasets/cakiki/rosetta-code
### Description
Hello, I just noticed an entry being redacted that shouldn't have been:
`RootMeanSquare@Range[10]` is being displayed as `[email protected][10]`
### Owner
_No response_
The val... | [
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0.35337501764297485,
0.058472007513046265,
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0.5019266605377197,
0.25943246483802795,
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0.26952117681503296,
0.6419990... |
https://github.com/huggingface/datasets/issues/4595 | Dataset Viewer issue with False positive PII redaction | This was indeed a scraping issue which I assumed was a display issue; sorry about that! | ### Link
https://huggingface.co/datasets/cakiki/rosetta-code
### Description
Hello, I just noticed an entry being redacted that shouldn't have been:
`RootMeanSquare@Range[10]` is being displayed as `[email protected][10]`
### Owner
_No response_ | 16 | Dataset Viewer issue with False positive PII redaction
### Link
https://huggingface.co/datasets/cakiki/rosetta-code
### Description
Hello, I just noticed an entry being redacted that shouldn't have been:
`RootMeanSquare@Range[10]` is being displayed as `[email protected][10]`
### Owner
_No response_
This wa... | [
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0.03597968816757202,
0.3285611867904663,
0.21663859486579895,
0.773828268051... |
https://github.com/huggingface/datasets/issues/4592 | Issue with jalFaizy/detect_chess_pieces when running datasets-cli test | Hi @faizankshaikh
Please note that we have recently launched the Community feature, specifically targeted to create Discussions (about issues/questions/asking-for-help) on each Dataset on the Hub:
- Blog post: https://huggingface.co/blog/community-update
- Docs: https://huggingface.co/docs/hub/repositories-pull-re... | ### Link
https://huggingface.co/datasets/jalFaizy/detect_chess_pieces
### Description
I am trying to write a appropriate data loader for [a custom dataset](https://huggingface.co/datasets/jalFaizy/detect_chess_pieces) using [this script](https://huggingface.co/datasets/jalFaizy/detect_chess_pieces/blob/main/detect_c... | 74 | Issue with jalFaizy/detect_chess_pieces when running datasets-cli test
### Link
https://huggingface.co/datasets/jalFaizy/detect_chess_pieces
### Description
I am trying to write a appropriate data loader for [a custom dataset](https://huggingface.co/datasets/jalFaizy/detect_chess_pieces) using [this script](https:... | [
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0.07623693346977234,
0.006530933082103729,
0.5506225228309631,
0.24864014983177185,
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0.5403976440429688,
0.4607197642326355,
0.33619260787963867,
0.08060021698474884,
0.06632126867771149,
0.05398640036582947,
-0.29010137915611267,
0.127565264701843... |
https://github.com/huggingface/datasets/issues/4592 | Issue with jalFaizy/detect_chess_pieces when running datasets-cli test | Thank you @albertvillanova , I will keep that in mind.
Just a quick note - I posted the issue on Github because the dataset viewer suggested me to "open an issue for direct support". Maybe it can be updated with your suggestion
 using [this script](https://huggingface.co/datasets/jalFaizy/detect_chess_pieces/blob/main/detect_c... | 43 | Issue with jalFaizy/detect_chess_pieces when running datasets-cli test
### Link
https://huggingface.co/datasets/jalFaizy/detect_chess_pieces
### Description
I am trying to write a appropriate data loader for [a custom dataset](https://huggingface.co/datasets/jalFaizy/detect_chess_pieces) using [this script](https:... | [
-0.32051923871040344,
0.07623693346977234,
0.006530933082103729,
0.5506225228309631,
0.24864014983177185,
-0.1461583971977234,
0.5403976440429688,
0.4607197642326355,
0.33619260787963867,
0.08060021698474884,
0.06632126867771149,
0.05398640036582947,
-0.29010137915611267,
0.127565264701843... |
https://github.com/huggingface/datasets/issues/4592 | Issue with jalFaizy/detect_chess_pieces when running datasets-cli test | Thank you pointing this out: yes, definitely, we should fix the error message. We are working on this. | ### Link
https://huggingface.co/datasets/jalFaizy/detect_chess_pieces
### Description
I am trying to write a appropriate data loader for [a custom dataset](https://huggingface.co/datasets/jalFaizy/detect_chess_pieces) using [this script](https://huggingface.co/datasets/jalFaizy/detect_chess_pieces/blob/main/detect_c... | 18 | Issue with jalFaizy/detect_chess_pieces when running datasets-cli test
### Link
https://huggingface.co/datasets/jalFaizy/detect_chess_pieces
### Description
I am trying to write a appropriate data loader for [a custom dataset](https://huggingface.co/datasets/jalFaizy/detect_chess_pieces) using [this script](https:... | [
-0.32051923871040344,
0.07623693346977234,
0.006530933082103729,
0.5506225228309631,
0.24864014983177185,
-0.1461583971977234,
0.5403976440429688,
0.4607197642326355,
0.33619260787963867,
0.08060021698474884,
0.06632126867771149,
0.05398640036582947,
-0.29010137915611267,
0.127565264701843... |
https://github.com/huggingface/datasets/issues/4591 | Can't push Images to hub with manual Dataset | Hi, thanks for reporting! This issue stems from the changes introduced in https://github.com/huggingface/datasets/pull/4282 (cc @lhoestq), in which list casts are ignored if they don't change the list type (required to preserve `null` values). And `push_to_hub` does a special cast to embed external image files but does... | ## Describe the bug
If I create a dataset including an 'Image' feature manually, when pushing to hub decoded images are not pushed,
instead it looks for image where image local path is/used to be.
This doesn't (at least didn't used to) happen with imagefolder. I want to build dataset manually because it is compli... | 52 | Can't push Images to hub with manual Dataset
## Describe the bug
If I create a dataset including an 'Image' feature manually, when pushing to hub decoded images are not pushed,
instead it looks for image where image local path is/used to be.
This doesn't (at least didn't used to) happen with imagefolder. I want... | [
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0.04066668078303337,
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-0.15583676099777222,
-0.0233688354492... |
https://github.com/huggingface/datasets/issues/4581 | Dataset Viewer issue for pn_summary | Note that I refreshed twice this dataset, and I still have (another) error on one of the splits
```
Status code: 400
Exception: ClientResponseError
Message: 403, message='Forbidden', url=URL('https://doc-14-4c-docs.googleusercontent.com/docs/securesc/ha0ro937gcuc7l7deffksulhg5h7mbp1/pgotjmcuh77q0lk7p4... | ### Link
https://huggingface.co/datasets/pn_summary/viewer/1.0.0/validation
### Description
Getting an index error on the `validation` and `test` splits:
```
Server error
Status code: 400
Exception: IndexError
Message: list index out of range
```
### Owner
No | 51 | Dataset Viewer issue for pn_summary
### Link
https://huggingface.co/datasets/pn_summary/viewer/1.0.0/validation
### Description
Getting an index error on the `validation` and `test` splits:
```
Server error
Status code: 400
Exception: IndexError
Message: list index out of range
```
### Owner
... | [
-0.2351139485836029,
0.13610345125198364,
-0.07504594326019287,
0.5219371318817139,
-0.1526188999414444,
0.10366693884134293,
0.15769927203655243,
0.2575743794441223,
0.06413610279560089,
0.12530608475208282,
-0.40464234352111816,
-0.283712774515152,
0.19132331013679504,
0.3474635481834411... |
https://github.com/huggingface/datasets/issues/4580 | Dataset Viewer issue for multi_news | Thanks for reporting, @lewtun.
I forced the refreshing of the preview and it worked OK for train and validation splits.
I guess the error has to do with the data files being hosted at Google Drive: this gives errors when requested automatically using scripts.
We should host them to fix the error. Let's see if th... | ### Link
https://huggingface.co/datasets/multi_news
### Description
Not sure what the index error is referring to here:
```
Status code: 400
Exception: IndexError
Message: list index out of range
```
### Owner
No | 59 | Dataset Viewer issue for multi_news
### Link
https://huggingface.co/datasets/multi_news
### Description
Not sure what the index error is referring to here:
```
Status code: 400
Exception: IndexError
Message: list index out of range
```
### Owner
No
Thanks for reporting, @lewtun.
I forced ... | [
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0.1423681080341339,
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0.3871573209762573... |
https://github.com/huggingface/datasets/issues/4578 | [Multi Configs] Use directories to differentiate between subsets/configurations | How to set new split names, instead of train/test/validation? For example, I have a local dataset, consists of several subsets, named "A", "B", and "C". How can I create a huggingface dataset, with splits A/B/C ?
The document in https://huggingface.co/docs/datasets/dataset_script only tells me how to create datasets... | Currently to define several subsets/configurations of your dataset, you need to use a dataset script.
However it would be nice to have a no-code way to to this.
For example we could specify different configurations of a dataset (for example, if a dataset contains different languages) with one directory per confi... | 64 | [Multi Configs] Use directories to differentiate between subsets/configurations
Currently to define several subsets/configurations of your dataset, you need to use a dataset script.
However it would be nice to have a no-code way to to this.
For example we could specify different configurations of a dataset (fo... | [
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0.02036118507385254,
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0.2816470265388489,
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0.56383150815... |
https://github.com/huggingface/datasets/issues/4578 | [Multi Configs] Use directories to differentiate between subsets/configurations | > The document in https://huggingface.co/docs/datasets/dataset_script only tells me how to create datasets with subsets that is hosted on another server. How to do it if my datasets are local?
It works the same - you just need to use local paths instead of URLs | Currently to define several subsets/configurations of your dataset, you need to use a dataset script.
However it would be nice to have a no-code way to to this.
For example we could specify different configurations of a dataset (for example, if a dataset contains different languages) with one directory per confi... | 44 | [Multi Configs] Use directories to differentiate between subsets/configurations
Currently to define several subsets/configurations of your dataset, you need to use a dataset script.
However it would be nice to have a no-code way to to this.
For example we could specify different configurations of a dataset (fo... | [
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0.37209489941596985,
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0.3564247488975525,
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0.513029932... |
https://github.com/huggingface/datasets/issues/4575 | Problem about wmt17 zh-en dataset | @winterfell2021 Hi, I wonder where the code you provided should be added. I tried to add them in the `datasets/table.py` in `array_cast` function, however, the 'zh' item is none. | It seems that in subset casia2015, some samples are like `{'c[hn]':'xxx', 'en': 'aa'}`.
So when using `data = load_dataset('wmt17', "zh-en")` to load the wmt17 zh-en dataset, which will raise the exception:
```
Traceback (most recent call last):
File "train.py", line 78, in <module>
data = load_dataset(args.... | 29 | Problem about wmt17 zh-en dataset
It seems that in subset casia2015, some samples are like `{'c[hn]':'xxx', 'en': 'aa'}`.
So when using `data = load_dataset('wmt17', "zh-en")` to load the wmt17 zh-en dataset, which will raise the exception:
```
Traceback (most recent call last):
File "train.py", line 78, in <mo... | [
-0.3377845883369446,
-0.467081218957901,
0.042393047362565994,
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0.2732115089893341,
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0.0498819500207901,
0.11882953345775604,
0.1963013857603073,
0.06979179382324219,
0.09495574235916138,... |
https://github.com/huggingface/datasets/issues/4575 | Problem about wmt17 zh-en dataset | I found some 'zh' item is none while 'c[hn]' is not.
So the code may change to:
```python
if 'c[hn]' in str(array.type):
py_array = array.to_pylist()
data_list = []
for vo in py_array:
tmp = {
'en': vo['en'],
}
if vo.get('zh'):
... | It seems that in subset casia2015, some samples are like `{'c[hn]':'xxx', 'en': 'aa'}`.
So when using `data = load_dataset('wmt17', "zh-en")` to load the wmt17 zh-en dataset, which will raise the exception:
```
Traceback (most recent call last):
File "train.py", line 78, in <module>
data = load_dataset(args.... | 58 | Problem about wmt17 zh-en dataset
It seems that in subset casia2015, some samples are like `{'c[hn]':'xxx', 'en': 'aa'}`.
So when using `data = load_dataset('wmt17', "zh-en")` to load the wmt17 zh-en dataset, which will raise the exception:
```
Traceback (most recent call last):
File "train.py", line 78, in <mo... | [
-0.3377845883369446,
-0.467081218957901,
0.042393047362565994,
0.32191354036331177,
0.3430138826370239,
0.13319173455238342,
0.2732115089893341,
0.07307456433773041,
0.004815666005015373,
0.0498819500207901,
0.11882953345775604,
0.1963013857603073,
0.06979179382324219,
0.09495574235916138,... |
https://github.com/huggingface/datasets/issues/4575 | Problem about wmt17 zh-en dataset | I just pushed a fix, we'll do a new release of `datasets` soon to include this fix. In the meantime you can use the fixed dataset by passing `revision="main"` to `load_dataset` | It seems that in subset casia2015, some samples are like `{'c[hn]':'xxx', 'en': 'aa'}`.
So when using `data = load_dataset('wmt17', "zh-en")` to load the wmt17 zh-en dataset, which will raise the exception:
```
Traceback (most recent call last):
File "train.py", line 78, in <module>
data = load_dataset(args.... | 31 | Problem about wmt17 zh-en dataset
It seems that in subset casia2015, some samples are like `{'c[hn]':'xxx', 'en': 'aa'}`.
So when using `data = load_dataset('wmt17', "zh-en")` to load the wmt17 zh-en dataset, which will raise the exception:
```
Traceback (most recent call last):
File "train.py", line 78, in <mo... | [
-0.3377845883369446,
-0.467081218957901,
0.042393047362565994,
0.32191354036331177,
0.3430138826370239,
0.13319173455238342,
0.2732115089893341,
0.07307456433773041,
0.004815666005015373,
0.0498819500207901,
0.11882953345775604,
0.1963013857603073,
0.06979179382324219,
0.09495574235916138,... |
https://github.com/huggingface/datasets/issues/4572 | Dataset Viewer issue for mlsum | Thanks for reporting, @lewtun.
After investigation, it seems that the server https://gitlab.lip6.fr does not allow HTTP Range requests.
We are trying to find a workaround... | ### Link
https://huggingface.co/datasets/mlsum/viewer/de/train
### Description
There's seems to be a problem with the download / streaming of this dataset:
```
Server error
Status code: 400
Exception: BadZipFile
Message: File is not a zip file
```
### Owner
No | 25 | Dataset Viewer issue for mlsum
### Link
https://huggingface.co/datasets/mlsum/viewer/de/train
### Description
There's seems to be a problem with the download / streaming of this dataset:
```
Server error
Status code: 400
Exception: BadZipFile
Message: File is not a zip file
```
### Owner
No
... | [
-0.35809168219566345,
-0.02585393190383911,
0.009452801197767258,
0.3169584274291992,
0.4466959238052368,
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0.17195793986320496,
0.09539017081260681,
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0.04269435256719589,
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0.11927293241024017,
0.007780604064464569,
0.0432305932... |
https://github.com/huggingface/datasets/issues/4571 | move under the facebook org? | I'm just wondering why we don't have this dataset under:
- the `facebook` namespace
- or the canonical dataset `flores`: why does this only have 2 languages? | ### Link
https://huggingface.co/datasets/gsarti/flores_101
### Description
It seems like streaming isn't supported for this dataset:
```
Server Error
Status code: 400
Exception: NotImplementedError
Message: Extraction protocol for TAR archives like 'https://dl.fbaipublicfiles.com/flores101/dataset... | 27 | move under the facebook org?
### Link
https://huggingface.co/datasets/gsarti/flores_101
### Description
It seems like streaming isn't supported for this dataset:
```
Server Error
Status code: 400
Exception: NotImplementedError
Message: Extraction protocol for TAR archives like 'https://dl.fbaipu... | [
-0.14406871795654297,
-0.047828659415245056,
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0.3923361897468567,
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0.1519559770822525,
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0.35567304491996765,
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0.1303248554468155,
0.4247348010540... |
https://github.com/huggingface/datasets/issues/4570 | Dataset sharding non-contiguous? | This was silly; I was sure I'd looked for a `contiguous` argument, and was certain there wasn't one the first time I looked :smile:
Sorry about that. | ## Describe the bug
I'm not sure if this is a bug; more likely normal behavior but i wanted to double check.
Is it normal that `datasets.shard` does not produce chunks that, when concatenated produce the original ordering of the sharded dataset?
This might be related to this pull request (https://github.com/huggi... | 27 | Dataset sharding non-contiguous?
## Describe the bug
I'm not sure if this is a bug; more likely normal behavior but i wanted to double check.
Is it normal that `datasets.shard` does not produce chunks that, when concatenated produce the original ordering of the sharded dataset?
This might be related to this pul... | [
0.046326231211423874,
-0.2496725171804428,
0.015279624611139297,
0.20713412761688232,
0.06308206915855408,
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0.4303715229034424,
0.027586719021201134,
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0.07158948481082916,
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0.289346307516098,
-0.10150031000... |
https://github.com/huggingface/datasets/issues/4570 | Dataset sharding non-contiguous? | Hi! You can pass `contiguous=True` to `.shard()` get contiguous shards. More info on this and the default behavior can be found in the [docs](https://huggingface.co/docs/datasets/v2.3.2/en/package_reference/main_classes#datasets.Dataset.shard).
EDIT: Answered as you closed the thread 😄 | ## Describe the bug
I'm not sure if this is a bug; more likely normal behavior but i wanted to double check.
Is it normal that `datasets.shard` does not produce chunks that, when concatenated produce the original ordering of the sharded dataset?
This might be related to this pull request (https://github.com/huggi... | 32 | Dataset sharding non-contiguous?
## Describe the bug
I'm not sure if this is a bug; more likely normal behavior but i wanted to double check.
Is it normal that `datasets.shard` does not produce chunks that, when concatenated produce the original ordering of the sharded dataset?
This might be related to this pul... | [
0.03986923024058342,
-0.2767412066459656,
0.018833663314580917,
0.2221575379371643,
0.08324537426233292,
-0.04516338184475899,
0.4172833561897278,
0.02987079881131649,
-0.535105288028717,
-0.012742787599563599,
0.03597630560398102,
-0.05815023183822632,
0.2801959812641144,
-0.0886437222361... |
https://github.com/huggingface/datasets/issues/4570 | Dataset sharding non-contiguous? | Hahaha I'm sorry; my excuse is: it's Sunday. (Which makes me all the more grateful for your response :smiley: | ## Describe the bug
I'm not sure if this is a bug; more likely normal behavior but i wanted to double check.
Is it normal that `datasets.shard` does not produce chunks that, when concatenated produce the original ordering of the sharded dataset?
This might be related to this pull request (https://github.com/huggi... | 19 | Dataset sharding non-contiguous?
## Describe the bug
I'm not sure if this is a bug; more likely normal behavior but i wanted to double check.
Is it normal that `datasets.shard` does not produce chunks that, when concatenated produce the original ordering of the sharded dataset?
This might be related to this pul... | [
0.043960053473711014,
-0.2885074019432068,
0.01620539277791977,
0.22780950367450714,
0.07851532101631165,
-0.04400944709777832,
0.44279545545578003,
0.02506532520055771,
-0.5470185875892639,
-0.02623714506626129,
0.01898418553173542,
-0.061626043170690536,
0.2754443883895874,
-0.0275831390... |
https://github.com/huggingface/datasets/issues/4570 | Dataset sharding non-contiguous? | @mariosasko Sorry for reviving this, but I was curious as to why `contiguous=False` was the default. This might be a personal bias, but I feel that a user would expect the opposite to be the default. :thinking: | ## Describe the bug
I'm not sure if this is a bug; more likely normal behavior but i wanted to double check.
Is it normal that `datasets.shard` does not produce chunks that, when concatenated produce the original ordering of the sharded dataset?
This might be related to this pull request (https://github.com/huggi... | 37 | Dataset sharding non-contiguous?
## Describe the bug
I'm not sure if this is a bug; more likely normal behavior but i wanted to double check.
Is it normal that `datasets.shard` does not produce chunks that, when concatenated produce the original ordering of the sharded dataset?
This might be related to this pul... | [
0.015164632350206375,
-0.28071820735931396,
0.009299837052822113,
0.1995406448841095,
0.06202252581715584,
-0.04880893975496292,
0.4298073351383209,
0.01510808989405632,
-0.5076970458030701,
-0.009925439953804016,
0.02195538952946663,
-0.09410683065652847,
0.3282988965511322,
-0.1315434277... |
https://github.com/huggingface/datasets/issues/4569 | Dataset Viewer issue for sst2 | Hi @lewtun, thanks for reporting.
I have checked locally and refreshed the preview and it seems working smooth now:
```python
In [8]: ds
Out[8]:
DatasetDict({
train: Dataset({
features: ['idx', 'sentence', 'label'],
num_rows: 67349
})
validation: Dataset({
features: ['i... | ### Link
https://huggingface.co/datasets/sst2
### Description
Not sure what is causing this, however it seems that `load_dataset("sst2")` also hangs (even though it downloads the files without problem):
```
Status code: 400
Exception: Exception
Message: Give up after 5 attempts with Connectio... | 57 | Dataset Viewer issue for sst2
### Link
https://huggingface.co/datasets/sst2
### Description
Not sure what is causing this, however it seems that `load_dataset("sst2")` also hangs (even though it downloads the files without problem):
```
Status code: 400
Exception: Exception
Message: Give up... | [
-0.33056482672691345,
0.08098076283931732,
-0.036532819271087646,
0.4152414798736572,
0.323622465133667,
0.05482601374387741,
0.2566252052783966,
0.2366028130054474,
0.158323273062706,
-0.027765780687332153,
-0.06476853042840958,
0.14777663350105286,
0.08745720982551575,
0.2538834512233734... |
https://github.com/huggingface/datasets/issues/4569 | Dataset Viewer issue for sst2 | Thanks @albertvillanova - it is indeed working now (not sure what caused the error in the first place). Closing this :) | ### Link
https://huggingface.co/datasets/sst2
### Description
Not sure what is causing this, however it seems that `load_dataset("sst2")` also hangs (even though it downloads the files without problem):
```
Status code: 400
Exception: Exception
Message: Give up after 5 attempts with Connectio... | 21 | Dataset Viewer issue for sst2
### Link
https://huggingface.co/datasets/sst2
### Description
Not sure what is causing this, however it seems that `load_dataset("sst2")` also hangs (even though it downloads the files without problem):
```
Status code: 400
Exception: Exception
Message: Give up... | [
-0.5275052785873413,
0.003740087151527405,
-0.06523788720369339,
0.36791014671325684,
0.20841823518276215,
-0.02099015563726425,
0.21451550722122192,
0.2552020847797394,
0.14038358628749847,
0.13036814332008362,
-0.06094881147146225,
0.09275010973215103,
0.17426402866840363,
0.254013150930... |
https://github.com/huggingface/datasets/issues/4568 | XNLI cache reload is very slow | Hi,
Could you tell us how you are running this code?
I tested on my machine (M1 Mac). And it is running fine both on and off internet.
<img width="1033" alt="Screen Shot 2022-07-03 at 1 32 25 AM" src="https://user-images.githubusercontent.com/8711912/177026364-4ad7cedb-e524-4513-97f7-7961bbb34c90.png">
Tested on ... | ### Reproduce
Using `2.3.3.dev0`
`from datasets import load_dataset`
`load_dataset("xnli", "en")`
Turn off Internet
`load_dataset("xnli", "en")`
I cancelled the second `load_dataset` eventually cuz it took super long. It would be great to have something to specify e.g. `only_load_from_cache` and avoid the ... | 46 | XNLI cache reload is very slow
### Reproduce
Using `2.3.3.dev0`
`from datasets import load_dataset`
`load_dataset("xnli", "en")`
Turn off Internet
`load_dataset("xnli", "en")`
I cancelled the second `load_dataset` eventually cuz it took super long. It would be great to have something to specify e.g. `only... | [
-0.14584548771381378,
0.058431729674339294,
0.006329108029603958,
-0.04914678633213043,
0.02681650221347809,
-0.23214468359947205,
0.19745635986328125,
0.2437468022108078,
0.18252934515476227,
-0.08453693985939026,
0.04058806598186493,
0.3258123993873596,
0.08739824593067169,
-0.1938986629... |
https://github.com/huggingface/datasets/issues/4568 | XNLI cache reload is very slow | Sure, I was running it on a Linux machine.
I found that if I turn the Internet off, it would still try to make a HTTPS call which would slow down the cache loading. If you can't reproduce then we can close the issue. | ### Reproduce
Using `2.3.3.dev0`
`from datasets import load_dataset`
`load_dataset("xnli", "en")`
Turn off Internet
`load_dataset("xnli", "en")`
I cancelled the second `load_dataset` eventually cuz it took super long. It would be great to have something to specify e.g. `only_load_from_cache` and avoid the ... | 44 | XNLI cache reload is very slow
### Reproduce
Using `2.3.3.dev0`
`from datasets import load_dataset`
`load_dataset("xnli", "en")`
Turn off Internet
`load_dataset("xnli", "en")`
I cancelled the second `load_dataset` eventually cuz it took super long. It would be great to have something to specify e.g. `only... | [
-0.14584548771381378,
0.058431729674339294,
0.006329108029603958,
-0.04914678633213043,
0.02681650221347809,
-0.23214468359947205,
0.19745635986328125,
0.2437468022108078,
0.18252934515476227,
-0.08453693985939026,
0.04058806598186493,
0.3258123993873596,
0.08739824593067169,
-0.1938986629... |
https://github.com/huggingface/datasets/issues/4568 | XNLI cache reload is very slow | Hi @Muennighoff! You can set the env variable `HF_DATASETS_OFFLINE` to `1` to avoid this behavior in offline mode. More info is available [here](https://huggingface.co/docs/datasets/master/en/loading#offline). | ### Reproduce
Using `2.3.3.dev0`
`from datasets import load_dataset`
`load_dataset("xnli", "en")`
Turn off Internet
`load_dataset("xnli", "en")`
I cancelled the second `load_dataset` eventually cuz it took super long. It would be great to have something to specify e.g. `only_load_from_cache` and avoid the ... | 23 | XNLI cache reload is very slow
### Reproduce
Using `2.3.3.dev0`
`from datasets import load_dataset`
`load_dataset("xnli", "en")`
Turn off Internet
`load_dataset("xnli", "en")`
I cancelled the second `load_dataset` eventually cuz it took super long. It would be great to have something to specify e.g. `only... | [
-0.14584548771381378,
0.058431729674339294,
0.006329108029603958,
-0.04914678633213043,
0.02681650221347809,
-0.23214468359947205,
0.19745635986328125,
0.2437468022108078,
0.18252934515476227,
-0.08453693985939026,
0.04058806598186493,
0.3258123993873596,
0.08739824593067169,
-0.1938986629... |
https://github.com/huggingface/datasets/issues/4566 | Document link #load_dataset_enhancing_performance points to nowhere | Hi! This is indeed the link the docstring should point to. Are you interested in submitting a PR to fix this? | ## Describe the bug
A clear and concise description of what the bug is.
The [load_dataset_enhancing_performance](https://huggingface.co/docs/datasets/v2.3.2/en/package_reference/main_classes#load_dat... | 21 | Document link #load_dataset_enhancing_performance points to nowhere
## Describe the bug
A clear and concise description of what the bug is.
The [load_dataset_enhancing_performance](https://huggingf... | [
-0.02718716859817505,
-0.4029790461063385,
-0.0349782332777977,
0.5097891092300415,
0.22108270227909088,
0.2674890160560608,
-0.04379759356379509,
0.26350343227386475,
0.029088251292705536,
0.066148541867733,
0.18902206420898438,
0.17872244119644165,
0.14725759625434875,
-0.163204625248909... |
https://github.com/huggingface/datasets/issues/4566 | Document link #load_dataset_enhancing_performance points to nowhere | https://github.com/huggingface/datasets/blame/master/docs/source/cache.mdx#L93
There seems already an anchor here. Somehow it doesn't work. I am not very familiar with how this online documentation works. | ## Describe the bug
A clear and concise description of what the bug is.
The [load_dataset_enhancing_performance](https://huggingface.co/docs/datasets/v2.3.2/en/package_reference/main_classes#load_dat... | 22 | Document link #load_dataset_enhancing_performance points to nowhere
## Describe the bug
A clear and concise description of what the bug is.
The [load_dataset_enhancing_performance](https://huggingf... | [
0.1365206241607666,
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-0.01797308772802353,
0.29911839962005615,
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https://github.com/huggingface/datasets/issues/4562 | Dataset Viewer issue for allocine | Note that the underlying issue is that datasets containing TAR files are not streamable out of the box: they need being iterated with `dl_manager.iter_archive` to avoid performance issues because they access their file content *sequentially* (no random access). | ### Link
https://huggingface.co/datasets/allocine
### Description
Not sure if this is a problem with `bz2` compression, but I thought these datasets could be streamed:
```
Status code: 400
Exception: AttributeError
Message: 'TarContainedFile' object has no attribute 'readable'
```
### Owner
No | 38 | Dataset Viewer issue for allocine
### Link
https://huggingface.co/datasets/allocine
### Description
Not sure if this is a problem with `bz2` compression, but I thought these datasets could be streamed:
```
Status code: 400
Exception: AttributeError
Message: 'TarContainedFile' object has no attrib... | [
-0.367940217256546,
-0.06806222349405289,
-0.00010710582137107849,
0.7290315628051758,
0.31127840280532837,
0.09571170061826706,
-0.12551069259643555,
0.329306036233902,
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0.26617664098739624,
-0.33151957392692566,
0.09606558829545975,
-0.3103848099708557,
0.04245790094... |
https://github.com/huggingface/datasets/issues/4562 | Dataset Viewer issue for allocine | > Note that the underlying issue is that datasets containing TAR files are not streamable out of the box: they need being iterated with `dl_manager.iter_archive` to avoid performance issues because they access their file content _sequentially_ (no random access).
Ah thanks for the clarification! I'll look out for th... | ### Link
https://huggingface.co/datasets/allocine
### Description
Not sure if this is a problem with `bz2` compression, but I thought these datasets could be streamed:
```
Status code: 400
Exception: AttributeError
Message: 'TarContainedFile' object has no attribute 'readable'
```
### Owner
No | 57 | Dataset Viewer issue for allocine
### Link
https://huggingface.co/datasets/allocine
### Description
Not sure if this is a problem with `bz2` compression, but I thought these datasets could be streamed:
```
Status code: 400
Exception: AttributeError
Message: 'TarContainedFile' object has no attrib... | [
-0.3704456388950348,
-0.07295586168766022,
0.011078424751758575,
0.676191508769989,
0.3053102493286133,
0.07710147649049759,
-0.09609650075435638,
0.38547754287719727,
-0.09366674721240997,
0.21664907038211823,
-0.3123401403427124,
0.11120874434709549,
-0.2770206332206726,
0.09945391863584... |
https://github.com/huggingface/datasets/issues/4550 | imdb source error | Thanks for reporting, @Muhtasham.
Indeed IMDB dataset is not accessible from yesterday, because the data is hosted on the data owners servers at Stanford (http://ai.stanford.edu/) and these are down due to a power outage originated by a fire: https://twitter.com/StanfordAILab/status/1539472302399623170?s=20&t=1HU1hr... | ## Describe the bug
imdb dataset not loading
## Steps to reproduce the bug
```python
from datasets import load_dataset
dataset = load_dataset("imdb")
```
## Expected results
## Actual results
```bash
06/23/2022 14:45:18 - INFO - datasets.builder - Dataset not on Hf google storage. Downloading and pr... | 58 | imdb source error
## Describe the bug
imdb dataset not loading
## Steps to reproduce the bug
```python
from datasets import load_dataset
dataset = load_dataset("imdb")
```
## Expected results
## Actual results
```bash
06/23/2022 14:45:18 - INFO - datasets.builder - Dataset not on Hf google storage... | [
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0.15562114119529724,
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0.30303269624710083,
0.24203068017959595,
0.25008004903793335,
0.16574518382549286,
-0.13026617467403412,
-0.16933122277259827,
0.2551252245903015,
0.082684017717838... |
https://github.com/huggingface/datasets/issues/4548 | Metadata.jsonl for Imagefolder is ignored if it's in a parent directory to the splits directories/do not have "{split}_" prefix | I agree it would be nice to support this. It doesn't fit really well in the current data_files.py, where files of each splits are separated in different folder though, maybe we have to modify a bit the logic here.
One idea would be to extend `get_patterns_in_dataset_repository` and `get_patterns_locally` to additio... | If data contains a single `metadata.jsonl` file for several splits, it won't be included in a dataset's `data_files` and therefore ignored.
This happens when a directory is structured like as follows:
```
train/
file_1.jpg
file_2.jpg
test/
file_3.jpg
file_4.jpg
metadata.jsonl
```
or like as follows:... | 91 | Metadata.jsonl for Imagefolder is ignored if it's in a parent directory to the splits directories/do not have "{split}_" prefix
If data contains a single `metadata.jsonl` file for several splits, it won't be included in a dataset's `data_files` and therefore ignored.
This happens when a directory is structured like... | [
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0.3551522493362427,
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0.39058631658554077,
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0.1683419793844223,
0.014017962850630283,
0.23228803277015686,
-0.3527262210845947,
0.2398290187120... |
https://github.com/huggingface/datasets/issues/4542 | [to_tf_dataset] Use Feather for better compatibility with TensorFlow ? | This has so much potential to be great! Also I think you tagged some poor random dude on the internet whose name is also Joao, lol, edited that for you! | To have better performance in TensorFlow, it is important to provide lists of data files in supported formats. For example sharded TFRecords datasets are extremely performant. This is because tf.data can better leverage parallelism in this case, and load one file at a time in memory.
It seems that using `tensorflow_... | 30 | [to_tf_dataset] Use Feather for better compatibility with TensorFlow ?
To have better performance in TensorFlow, it is important to provide lists of data files in supported formats. For example sharded TFRecords datasets are extremely performant. This is because tf.data can better leverage parallelism in this case, a... | [
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0.13927793502807617,
0.6314025521278381,
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0.0345197468996048,
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0.53013014793396,
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-0.15838204324245... |
https://github.com/huggingface/datasets/issues/4542 | [to_tf_dataset] Use Feather for better compatibility with TensorFlow ? | Noted and I will look into the thread in detail tomorrow once I log back in. | To have better performance in TensorFlow, it is important to provide lists of data files in supported formats. For example sharded TFRecords datasets are extremely performant. This is because tf.data can better leverage parallelism in this case, and load one file at a time in memory.
It seems that using `tensorflow_... | 16 | [to_tf_dataset] Use Feather for better compatibility with TensorFlow ?
To have better performance in TensorFlow, it is important to provide lists of data files in supported formats. For example sharded TFRecords datasets are extremely performant. This is because tf.data can better leverage parallelism in this case, a... | [
-0.21949516236782074,
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0.16388170421123505,
0.6277858018875122,
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0.027159854769706726,
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0.525818407535553,
0.025152914226055145,
-0.151396855711... |
https://github.com/huggingface/datasets/issues/4542 | [to_tf_dataset] Use Feather for better compatibility with TensorFlow ? | @lhoestq I have used TFRecords with `tf.data` for both vision and text and I can say that they are quite performant. I haven't worked with Feather yet as similarly as I have with TFRecords. If you haven't started the benchmarking script yet, I can prepare a Colab notebook that loads Feather files, converts them into a ... | To have better performance in TensorFlow, it is important to provide lists of data files in supported formats. For example sharded TFRecords datasets are extremely performant. This is because tf.data can better leverage parallelism in this case, and load one file at a time in memory.
It seems that using `tensorflow_... | 86 | [to_tf_dataset] Use Feather for better compatibility with TensorFlow ?
To have better performance in TensorFlow, it is important to provide lists of data files in supported formats. For example sharded TFRecords datasets are extremely performant. This is because tf.data can better leverage parallelism in this case, a... | [
-0.25734996795654297,
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0.3299427032470703,
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0.19334548711776733,
0.6237207651138306,
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0.0033727511763572693,
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0.471015602350235,
0.02251257747411728,
-0.234227359294... |
https://github.com/huggingface/datasets/issues/4542 | [to_tf_dataset] Use Feather for better compatibility with TensorFlow ? | > Not yet sure if it's good for modalities like images.
We store images pretty much the same way as tensorflow_datasets (i.e. storing the encoded image bytes, or a path to the local image, so that the image can be decoded on-the-fly), so as long as we use something similar as TFDS for image decoding it should be ok | To have better performance in TensorFlow, it is important to provide lists of data files in supported formats. For example sharded TFRecords datasets are extremely performant. This is because tf.data can better leverage parallelism in this case, and load one file at a time in memory.
It seems that using `tensorflow_... | 59 | [to_tf_dataset] Use Feather for better compatibility with TensorFlow ?
To have better performance in TensorFlow, it is important to provide lists of data files in supported formats. For example sharded TFRecords datasets are extremely performant. This is because tf.data can better leverage parallelism in this case, a... | [
-0.19923469424247742,
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0.13910046219825745,
0.6205322742462158,
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0.033259548246860504,
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0.4609624147415161,
-0.0301036573946476,
-0.17199487984... |
https://github.com/huggingface/datasets/issues/4542 | [to_tf_dataset] Use Feather for better compatibility with TensorFlow ? | So for image datasets, we could potentially store the paths in the feather format and decode and read them on the fly? But it introduces an I/O redundancy of having to read the images every time.
With caching it could be somewhat mitigated but it's not a good solution for bigger image datasets. | To have better performance in TensorFlow, it is important to provide lists of data files in supported formats. For example sharded TFRecords datasets are extremely performant. This is because tf.data can better leverage parallelism in this case, and load one file at a time in memory.
It seems that using `tensorflow_... | 53 | [to_tf_dataset] Use Feather for better compatibility with TensorFlow ?
To have better performance in TensorFlow, it is important to provide lists of data files in supported formats. For example sharded TFRecords datasets are extremely performant. This is because tf.data can better leverage parallelism in this case, a... | [
-0.22257301211357117,
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0.36468958854675293,
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0.16813993453979492,
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0.5340715646743774,
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-0.1502863913774... |
https://github.com/huggingface/datasets/issues/4542 | [to_tf_dataset] Use Feather for better compatibility with TensorFlow ? | > So for image datasets, we could potentially store the paths in the feather format and decode and read them on the fly?
hopefully yes :)
I double-checked the TFDS source code and they always save the bytes actually, not the path. Anyway we'll see if we run into issues or not (as a first step we can require the ... | To have better performance in TensorFlow, it is important to provide lists of data files in supported formats. For example sharded TFRecords datasets are extremely performant. This is because tf.data can better leverage parallelism in this case, and load one file at a time in memory.
It seems that using `tensorflow_... | 67 | [to_tf_dataset] Use Feather for better compatibility with TensorFlow ?
To have better performance in TensorFlow, it is important to provide lists of data files in supported formats. For example sharded TFRecords datasets are extremely performant. This is because tf.data can better leverage parallelism in this case, a... | [
-0.2071114033460617,
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0.028287097811698914,
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0.5183919668197632,
-0.16292768716812134,
-0.18630404770374... |
https://github.com/huggingface/datasets/issues/4542 | [to_tf_dataset] Use Feather for better compatibility with TensorFlow ? | Yes. For images, TFDS actually prepares TFRecords first for encoding and then reuses them for every subsequent call. | To have better performance in TensorFlow, it is important to provide lists of data files in supported formats. For example sharded TFRecords datasets are extremely performant. This is because tf.data can better leverage parallelism in this case, and load one file at a time in memory.
It seems that using `tensorflow_... | 18 | [to_tf_dataset] Use Feather for better compatibility with TensorFlow ?
To have better performance in TensorFlow, it is important to provide lists of data files in supported formats. For example sharded TFRecords datasets are extremely performant. This is because tf.data can better leverage parallelism in this case, a... | [
-0.23023538291454315,
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-0.21482475101... |
https://github.com/huggingface/datasets/issues/4542 | [to_tf_dataset] Use Feather for better compatibility with TensorFlow ? | @lhoestq @Rocketknight1 I worked on [this PoC](https://gist.github.com/sayakpaul/f7d5cc312cd01cb31098fad3fd9c6b59) that
* Creates Feather files from a medium resolution dataset (`tf_flowers`).
* Explores different options with TensorFlow IO to load the Feather files.
I haven't benchmarked those different option... | To have better performance in TensorFlow, it is important to provide lists of data files in supported formats. For example sharded TFRecords datasets are extremely performant. This is because tf.data can better leverage parallelism in this case, and load one file at a time in memory.
It seems that using `tensorflow_... | 61 | [to_tf_dataset] Use Feather for better compatibility with TensorFlow ?
To have better performance in TensorFlow, it is important to provide lists of data files in supported formats. For example sharded TFRecords datasets are extremely performant. This is because tf.data can better leverage parallelism in this case, a... | [
-0.215074822306633,
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0.04900551959872246,
-0.216002464294433... |
https://github.com/huggingface/datasets/issues/4542 | [to_tf_dataset] Use Feather for better compatibility with TensorFlow ? | Cool thanks ! If I understand correctly in your PoC you store the flattened array of pixels in the feather file. This will take a lot of disk space.
Maybe we could just save the encoded bytes and let users apply a `map` to decode/transform them into the format they need for training ? Users can use tf.image to do so... | To have better performance in TensorFlow, it is important to provide lists of data files in supported formats. For example sharded TFRecords datasets are extremely performant. This is because tf.data can better leverage parallelism in this case, and load one file at a time in memory.
It seems that using `tensorflow_... | 63 | [to_tf_dataset] Use Feather for better compatibility with TensorFlow ?
To have better performance in TensorFlow, it is important to provide lists of data files in supported formats. For example sharded TFRecords datasets are extremely performant. This is because tf.data can better leverage parallelism in this case, a... | [
-0.16578981280326843,
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0.335033655166626,
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-0.02583644911646843... |
https://github.com/huggingface/datasets/issues/4542 | [to_tf_dataset] Use Feather for better compatibility with TensorFlow ? | @lhoestq this is what I tried:
```py
def read_image(path):
with open(path, "rb") as f:
return f.read()
total_images_written = 0
for step in tqdm.tnrange(int(math.ceil(len(image_paths) / batch_size))):
batch_image_paths = image_paths[step * batch_size : (step + 1) * batch_size]
batch_... | To have better performance in TensorFlow, it is important to provide lists of data files in supported formats. For example sharded TFRecords datasets are extremely performant. This is because tf.data can better leverage parallelism in this case, and load one file at a time in memory.
It seems that using `tensorflow_... | 413 | [to_tf_dataset] Use Feather for better compatibility with TensorFlow ?
To have better performance in TensorFlow, it is important to provide lists of data files in supported formats. For example sharded TFRecords datasets are extremely performant. This is because tf.data can better leverage parallelism in this case, a... | [
-0.2916852831840515,
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0.2313348352909088,
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0.12490998208522797,
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-0.25731316208... |
https://github.com/huggingface/datasets/issues/4542 | [to_tf_dataset] Use Feather for better compatibility with TensorFlow ? | @lhoestq I think I was able to make it work in the way you were envisioning. Here's the PoC:
https://gist.github.com/sayakpaul/f7d5cc312cd01cb31098fad3fd9c6b59#file-feather-tf-poc-bytes-ipynb
Some details:
* I am currently serializing the images as strings with `base64`). In comparison to the flattened arrays as... | To have better performance in TensorFlow, it is important to provide lists of data files in supported formats. For example sharded TFRecords datasets are extremely performant. This is because tf.data can better leverage parallelism in this case, and load one file at a time in memory.
It seems that using `tensorflow_... | 107 | [to_tf_dataset] Use Feather for better compatibility with TensorFlow ?
To have better performance in TensorFlow, it is important to provide lists of data files in supported formats. For example sharded TFRecords datasets are extremely performant. This is because tf.data can better leverage parallelism in this case, a... | [
-0.15111899375915527,
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0.33229172229766846,
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0.08291283249855042,
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0.4283265173435211,
-0.04531325399875641,
-0.21035680174827... |
https://github.com/huggingface/datasets/issues/4542 | [to_tf_dataset] Use Feather for better compatibility with TensorFlow ? | Cool thanks ! Too bad the Arrow binary type doesn't seem to be supported in `arrow_io.ArrowFeatherDataset` :/ We would also need it to support Arrow struct type. Indeed images in `datasets` are represented using an Arrow type
```python
pa.struct({"path": pa.string(), "bytes": pa.binary()})
```
not sure yet how hard... | To have better performance in TensorFlow, it is important to provide lists of data files in supported formats. For example sharded TFRecords datasets are extremely performant. This is because tf.data can better leverage parallelism in this case, and load one file at a time in memory.
It seems that using `tensorflow_... | 78 | [to_tf_dataset] Use Feather for better compatibility with TensorFlow ?
To have better performance in TensorFlow, it is important to provide lists of data files in supported formats. For example sharded TFRecords datasets are extremely performant. This is because tf.data can better leverage parallelism in this case, a... | [
-0.22203543782234192,
-0.3213922381401062,
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0.3587227463722229,
0.23031316697597504,
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0.5902265310287476,
-0.04628640413284302,
-0.139491319656... |
https://github.com/huggingface/datasets/issues/4542 | [to_tf_dataset] Use Feather for better compatibility with TensorFlow ? | If the ArrowFeatherDataset doesn't yet support it, I guess our hands are a bit tied at the moment.
IIUC, in my [latest PoC notebook](https://gist.github.com/sayakpaul/f7d5cc312cd01cb31098fad3fd9c6b59#file-feather-tf-poc-bytes-ipynb), you wanted to see each entry in the feather file to be represented like so?
```... | To have better performance in TensorFlow, it is important to provide lists of data files in supported formats. For example sharded TFRecords datasets are extremely performant. This is because tf.data can better leverage parallelism in this case, and load one file at a time in memory.
It seems that using `tensorflow_... | 52 | [to_tf_dataset] Use Feather for better compatibility with TensorFlow ?
To have better performance in TensorFlow, it is important to provide lists of data files in supported formats. For example sharded TFRecords datasets are extremely performant. This is because tf.data can better leverage parallelism in this case, a... | [
-0.2572590708732605,
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0.5051928758621216,
0.01807660423219204,
-0.131314232945442... |
https://github.com/huggingface/datasets/issues/4542 | [to_tf_dataset] Use Feather for better compatibility with TensorFlow ? | > IIUC, in my [latest PoC notebook](https://gist.github.com/sayakpaul/f7d5cc312cd01cb31098fad3fd9c6b59#file-feather-tf-poc-bytes-ipynb), you wanted to see each entry in the feather file to be represented like so?
>
> pa.struct({"path": pa.string(), "bytes": pa.binary()})
Yea because that's the data format we're u... | To have better performance in TensorFlow, it is important to provide lists of data files in supported formats. For example sharded TFRecords datasets are extremely performant. This is because tf.data can better leverage parallelism in this case, and load one file at a time in memory.
It seems that using `tensorflow_... | 108 | [to_tf_dataset] Use Feather for better compatibility with TensorFlow ?
To have better performance in TensorFlow, it is important to provide lists of data files in supported formats. For example sharded TFRecords datasets are extremely performant. This is because tf.data can better leverage parallelism in this case, a... | [
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https://github.com/huggingface/datasets/issues/4542 | [to_tf_dataset] Use Feather for better compatibility with TensorFlow ? | > Maybe it would take too much time to be worth exploring, but according to https://github.com/tensorflow/io/issues/1361#issuecomment-819029002 it's possible to add support for binary type in ArrowFeatherDataset.
Should be possible as per the comment but there hasn't been any progress and it's been more than a year.... | To have better performance in TensorFlow, it is important to provide lists of data files in supported formats. For example sharded TFRecords datasets are extremely performant. This is because tf.data can better leverage parallelism in this case, and load one file at a time in memory.
It seems that using `tensorflow_... | 117 | [to_tf_dataset] Use Feather for better compatibility with TensorFlow ?
To have better performance in TensorFlow, it is important to provide lists of data files in supported formats. For example sharded TFRecords datasets are extremely performant. This is because tf.data can better leverage parallelism in this case, a... | [
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https://github.com/huggingface/datasets/issues/4542 | [to_tf_dataset] Use Feather for better compatibility with TensorFlow ? | > I don't understand this. I would think TFRecords would also need something similar but I need the context you're coming from.
Users already have a copy of the dataset in Arrow format (we can change this to Feather). So to load the Arrow/feather files to a TF dataset we need TF IO or something like that. Otherwise ... | To have better performance in TensorFlow, it is important to provide lists of data files in supported formats. For example sharded TFRecords datasets are extremely performant. This is because tf.data can better leverage parallelism in this case, and load one file at a time in memory.
It seems that using `tensorflow_... | 116 | [to_tf_dataset] Use Feather for better compatibility with TensorFlow ?
To have better performance in TensorFlow, it is important to provide lists of data files in supported formats. For example sharded TFRecords datasets are extremely performant. This is because tf.data can better leverage parallelism in this case, a... | [
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https://github.com/huggingface/datasets/issues/4542 | [to_tf_dataset] Use Feather for better compatibility with TensorFlow ? | Yeah, it looks like in its current state the tfio support for `Feather` is incomplete, so we'd end up having to write a lot of it, or do a conversion that defeats the whole point (because if we're going to convert the whole dataset we might as well convert to `TFRecord`). | To have better performance in TensorFlow, it is important to provide lists of data files in supported formats. For example sharded TFRecords datasets are extremely performant. This is because tf.data can better leverage parallelism in this case, and load one file at a time in memory.
It seems that using `tensorflow_... | 51 | [to_tf_dataset] Use Feather for better compatibility with TensorFlow ?
To have better performance in TensorFlow, it is important to provide lists of data files in supported formats. For example sharded TFRecords datasets are extremely performant. This is because tf.data can better leverage parallelism in this case, a... | [
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https://github.com/huggingface/datasets/issues/4542 | [to_tf_dataset] Use Feather for better compatibility with TensorFlow ? | @lhoestq Although I think this is a dead-end for now unfortunately, because of the limitations at TF's end, we could still explore automatic conversion to TFRecord, or I could dive into refining `to_tf_dataset()` to yield unbatched samples and/or load samples with multiprocessing to improve throughput. Do you have any ... | To have better performance in TensorFlow, it is important to provide lists of data files in supported formats. For example sharded TFRecords datasets are extremely performant. This is because tf.data can better leverage parallelism in this case, and load one file at a time in memory.
It seems that using `tensorflow_... | 51 | [to_tf_dataset] Use Feather for better compatibility with TensorFlow ?
To have better performance in TensorFlow, it is important to provide lists of data files in supported formats. For example sharded TFRecords datasets are extremely performant. This is because tf.data can better leverage parallelism in this case, a... | [
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https://github.com/huggingface/datasets/issues/4542 | [to_tf_dataset] Use Feather for better compatibility with TensorFlow ? | > @lhoestq Although I think this is a dead-end for now unfortunately, because of the limitations at TF's end, we could still explore automatic conversion to TFRecord, or I could dive into refining `to_tf_dataset()` to yield unbatched samples and/or load samples with multiprocessing to improve throughput. Do you have an... | To have better performance in TensorFlow, it is important to provide lists of data files in supported formats. For example sharded TFRecords datasets are extremely performant. This is because tf.data can better leverage parallelism in this case, and load one file at a time in memory.
It seems that using `tensorflow_... | 58 | [to_tf_dataset] Use Feather for better compatibility with TensorFlow ?
To have better performance in TensorFlow, it is important to provide lists of data files in supported formats. For example sharded TFRecords datasets are extremely performant. This is because tf.data can better leverage parallelism in this case, a... | [
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https://github.com/huggingface/datasets/issues/4542 | [to_tf_dataset] Use Feather for better compatibility with TensorFlow ? | If `to_tf_dataset` can be unbatched, then it should be fairly easy for users to convert the TF dataset to TFRecords right ? | To have better performance in TensorFlow, it is important to provide lists of data files in supported formats. For example sharded TFRecords datasets are extremely performant. This is because tf.data can better leverage parallelism in this case, and load one file at a time in memory.
It seems that using `tensorflow_... | 22 | [to_tf_dataset] Use Feather for better compatibility with TensorFlow ?
To have better performance in TensorFlow, it is important to provide lists of data files in supported formats. For example sharded TFRecords datasets are extremely performant. This is because tf.data can better leverage parallelism in this case, a... | [
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0.02891974151134491,
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0.5038834810256958,
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https://github.com/huggingface/datasets/issues/4542 | [to_tf_dataset] Use Feather for better compatibility with TensorFlow ? | > If to_tf_dataset can be unbatched, then it should be fairly easy for users to convert the TF dataset to TFRecords right ?
Sort of! A `tf.data.Dataset` is more like an iterator, and does not support sample indexing. `to_tf_dataset()` creates an iterator, but to convert that to `TFRecord`, the user would have to ite... | To have better performance in TensorFlow, it is important to provide lists of data files in supported formats. For example sharded TFRecords datasets are extremely performant. This is because tf.data can better leverage parallelism in this case, and load one file at a time in memory.
It seems that using `tensorflow_... | 67 | [to_tf_dataset] Use Feather for better compatibility with TensorFlow ?
To have better performance in TensorFlow, it is important to provide lists of data files in supported formats. For example sharded TFRecords datasets are extremely performant. This is because tf.data can better leverage parallelism in this case, a... | [
-0.2197135090827942,
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0.09936442971229553,
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0.5110944509506226,
-0.03801554813981056,
-0.2157175391912460... |
https://github.com/huggingface/datasets/issues/4542 | [to_tf_dataset] Use Feather for better compatibility with TensorFlow ? | Someone would like to try to dive into tfio to fix this ? Sounds like a good opportunity to learn what are the best ways to load a dataset for TF, and also the connections between Arrow and TF.
If we can at least have the Arrow `binary` type working for TF that would be awesome already (issue https://github.com/tens... | To have better performance in TensorFlow, it is important to provide lists of data files in supported formats. For example sharded TFRecords datasets are extremely performant. This is because tf.data can better leverage parallelism in this case, and load one file at a time in memory.
It seems that using `tensorflow_... | 68 | [to_tf_dataset] Use Feather for better compatibility with TensorFlow ?
To have better performance in TensorFlow, it is important to provide lists of data files in supported formats. For example sharded TFRecords datasets are extremely performant. This is because tf.data can better leverage parallelism in this case, a... | [
-0.19004784524440765,
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https://github.com/huggingface/datasets/issues/4542 | [to_tf_dataset] Use Feather for better compatibility with TensorFlow ? | > Sounds like a good opportunity to learn what are the best ways to load a dataset for TF
The recommended way would likely be a combination of TFRecords and `tf.data`.
Exploring the connection between Arrow and TensorFlow is definitely worth pursuing though. But I am not sure about the implications of storing im... | To have better performance in TensorFlow, it is important to provide lists of data files in supported formats. For example sharded TFRecords datasets are extremely performant. This is because tf.data can better leverage parallelism in this case, and load one file at a time in memory.
It seems that using `tensorflow_... | 91 | [to_tf_dataset] Use Feather for better compatibility with TensorFlow ?
To have better performance in TensorFlow, it is important to provide lists of data files in supported formats. For example sharded TFRecords datasets are extremely performant. This is because tf.data can better leverage parallelism in this case, a... | [
-0.19480963051319122,
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https://github.com/huggingface/datasets/issues/4542 | [to_tf_dataset] Use Feather for better compatibility with TensorFlow ? | I am currently working on a fine-tuning notebook for the TFSegFormer model (Semantic Segmentation). The resolution is high for both the input images and the labels - (512, 512, 3). Here's the [Colab Notebook](https://colab.research.google.com/drive/1jAtR7Z0lYX6m6JsDI5VByh5vFaNhHIbP?usp=sharing) (it's a WIP so please be... | To have better performance in TensorFlow, it is important to provide lists of data files in supported formats. For example sharded TFRecords datasets are extremely performant. This is because tf.data can better leverage parallelism in this case, and load one file at a time in memory.
It seems that using `tensorflow_... | 62 | [to_tf_dataset] Use Feather for better compatibility with TensorFlow ?
To have better performance in TensorFlow, it is important to provide lists of data files in supported formats. For example sharded TFRecords datasets are extremely performant. This is because tf.data can better leverage parallelism in this case, a... | [
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https://github.com/huggingface/datasets/issues/4542 | [to_tf_dataset] Use Feather for better compatibility with TensorFlow ? | Here's a notebook showing the performance difference: https://colab.research.google.com/gist/sayakpaul/d7ca67c90beb47e354942c9d8c0bd8ef/scratchpad.ipynb.
Note that I acknowledge that it's not an apples-to-apples comparison in many aspects (the dataset isn't the same, data serialization format isn't the same, etc.) ... | To have better performance in TensorFlow, it is important to provide lists of data files in supported formats. For example sharded TFRecords datasets are extremely performant. This is because tf.data can better leverage parallelism in this case, and load one file at a time in memory.
It seems that using `tensorflow_... | 41 | [to_tf_dataset] Use Feather for better compatibility with TensorFlow ?
To have better performance in TensorFlow, it is important to provide lists of data files in supported formats. For example sharded TFRecords datasets are extremely performant. This is because tf.data can better leverage parallelism in this case, a... | [
-0.21969950199127197,
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0.5323149561882019,
0.02723846584558487,
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https://github.com/huggingface/datasets/issues/4542 | [to_tf_dataset] Use Feather for better compatibility with TensorFlow ? | Thanks ! I think the speed difference can be partly explained: you use ds.shuffle in your dataset, which is an exact shuffling (compared to TFDS which does buffer shuffling): it slows down query time by 2x to 10x since it has to play with data that are not contiguous.
The rest of the speed difference seems to be cau... | To have better performance in TensorFlow, it is important to provide lists of data files in supported formats. For example sharded TFRecords datasets are extremely performant. This is because tf.data can better leverage parallelism in this case, and load one file at a time in memory.
It seems that using `tensorflow_... | 66 | [to_tf_dataset] Use Feather for better compatibility with TensorFlow ?
To have better performance in TensorFlow, it is important to provide lists of data files in supported formats. For example sharded TFRecords datasets are extremely performant. This is because tf.data can better leverage parallelism in this case, a... | [
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https://github.com/huggingface/datasets/issues/4542 | [to_tf_dataset] Use Feather for better compatibility with TensorFlow ? | Fair enough. Can do one without shuffling too. But it's an important one to consider I guess. | To have better performance in TensorFlow, it is important to provide lists of data files in supported formats. For example sharded TFRecords datasets are extremely performant. This is because tf.data can better leverage parallelism in this case, and load one file at a time in memory.
It seems that using `tensorflow_... | 17 | [to_tf_dataset] Use Feather for better compatibility with TensorFlow ?
To have better performance in TensorFlow, it is important to provide lists of data files in supported formats. For example sharded TFRecords datasets are extremely performant. This is because tf.data can better leverage parallelism in this case, a... | [
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... |
https://github.com/huggingface/datasets/issues/4540 | Avoid splitting by` .py` for the file. | Hi @espoirMur, thanks for reporting.
You are right: that code line could be improved and made more generically valid.
On the other hand, I would suggest using `os.path.splitext` instead.
Are you willing to open a PR? :) | https://github.com/huggingface/datasets/blob/90b3a98065556fc66380cafd780af9b1814b9426/src/datasets/load.py#L272
Hello,
Thanks you for this library .
I was using it and I had one edge case. my home folder name ends with `.py` it is `/home/espoir.py` so anytime I am running the code to load a local module thi... | 37 | Avoid splitting by` .py` for the file.
https://github.com/huggingface/datasets/blob/90b3a98065556fc66380cafd780af9b1814b9426/src/datasets/load.py#L272
Hello,
Thanks you for this library .
I was using it and I had one edge case. my home folder name ends with `.py` it is `/home/espoir.py` so anytime I am ru... | [
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0.06515146791934967,
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0.09560815989971161,
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0.44398683309555054,
-0.029078099876642227,
0.27612841129... |
https://github.com/huggingface/datasets/issues/4538 | Dataset Viewer issue for Pile of Law | Thanks so much for adding the docs. I was able to successfully hide the viewer using the
```
viewer: false
```
flag in the README.md of the dataset. I'm closing the issue because this is resolved. Thanks again! | ### Link
https://huggingface.co/datasets/pile-of-law/pile-of-law
### Description
Hi, I would like to turn off the dataset viewer for our dataset without enabling access requests. To comply with upstream dataset creator requests/licenses, we would like to make sure that the data is not indexed by search engines... | 38 | Dataset Viewer issue for Pile of Law
### Link
https://huggingface.co/datasets/pile-of-law/pile-of-law
### Description
Hi, I would like to turn off the dataset viewer for our dataset without enabling access requests. To comply with upstream dataset creator requests/licenses, we would like to make sure that th... | [
0.005177520215511322,
0.5496143102645874,
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0.0285667683929... |
https://github.com/huggingface/datasets/issues/4538 | Dataset Viewer issue for Pile of Law | Just for the record:
- the doc
<img width="1430" alt="Capture d’écran 2022-06-27 à 09 29 27" src="https://user-images.githubusercontent.com/1676121/175884089-bca6c0d5-6387-473e-98ca-86a910ede4bd.png">
- the dataset main page
<img width="1134" alt="Capture d’écran 2022-06-27 à 09 29 05" src="https://us... | ### Link
https://huggingface.co/datasets/pile-of-law/pile-of-law
### Description
Hi, I would like to turn off the dataset viewer for our dataset without enabling access requests. To comply with upstream dataset creator requests/licenses, we would like to make sure that the data is not indexed by search engines... | 47 | Dataset Viewer issue for Pile of Law
### Link
https://huggingface.co/datasets/pile-of-law/pile-of-law
### Description
Hi, I would like to turn off the dataset viewer for our dataset without enabling access requests. To comply with upstream dataset creator requests/licenses, we would like to make sure that th... | [
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0.6128958463668823,
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0.14462190866470337,
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0.07956277... |
https://github.com/huggingface/datasets/issues/4531 | Dataset Viewer issue for CSV datasets | Confirmed, it's fixed now. Thanks for reporting, and thanks @coyotte508 for fixing it
<img width="1123" alt="Capture d’écran 2022-06-21 à 10 28 05" src="https://user-images.githubusercontent.com/1676121/174753833-1b453a5a-6a90-4717-bca1-1b5fc6b75e4a.png">
| ### Link
https://huggingface.co/datasets/scikit-learn/breast-cancer-wisconsin
### Description
I'm populating CSV datasets [here](https://huggingface.co/scikit-learn) but the viewer is not enabled and it looks for a dataset loading script, the datasets aren't on queue as well.
You can replicate the problem by sim... | 23 | Dataset Viewer issue for CSV datasets
### Link
https://huggingface.co/datasets/scikit-learn/breast-cancer-wisconsin
### Description
I'm populating CSV datasets [here](https://huggingface.co/scikit-learn) but the viewer is not enabled and it looks for a dataset loading script, the datasets aren't on queue as well. ... | [
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0.2713307440280914... |
https://github.com/huggingface/datasets/issues/4529 | Ecoset | Hi! Very cool dataset! I answered your questions on the forum. Also, feel free to comment `#self-assign` on this issue to self-assign it. | ## Adding a Dataset
- **Name:** *Ecoset*
- **Description:** *https://www.kietzmannlab.org/ecoset/*
- **Paper:** *https://doi.org/10.1073/pnas.2011417118*
- **Data:** *https://codeocean.com/capsule/9570390/tree/v1*
- **Motivation:**
**Ecoset** was created as a clean and ecologically valid alternative to **Imagen... | 23 | Ecoset
## Adding a Dataset
- **Name:** *Ecoset*
- **Description:** *https://www.kietzmannlab.org/ecoset/*
- **Paper:** *https://doi.org/10.1073/pnas.2011417118*
- **Data:** *https://codeocean.com/capsule/9570390/tree/v1*
- **Motivation:**
**Ecoset** was created as a clean and ecologically valid alternative to... | [
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0.49795812368... |
https://github.com/huggingface/datasets/issues/4529 | Ecoset | Hey There, thanks for closing 🤗
Forgot the issue existed, so I didn't close it after implementing the downloader :) | ## Adding a Dataset
- **Name:** *Ecoset*
- **Description:** *https://www.kietzmannlab.org/ecoset/*
- **Paper:** *https://doi.org/10.1073/pnas.2011417118*
- **Data:** *https://codeocean.com/capsule/9570390/tree/v1*
- **Motivation:**
**Ecoset** was created as a clean and ecologically valid alternative to **Imagen... | 20 | Ecoset
## Adding a Dataset
- **Name:** *Ecoset*
- **Description:** *https://www.kietzmannlab.org/ecoset/*
- **Paper:** *https://doi.org/10.1073/pnas.2011417118*
- **Data:** *https://codeocean.com/capsule/9570390/tree/v1*
- **Motivation:**
**Ecoset** was created as a clean and ecologically valid alternative to... | [
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0.46639496088... |
https://github.com/huggingface/datasets/issues/4528 | Memory leak when iterating a Dataset | Here is a modified repro example that makes it easier to see the leak:
```
$ cat ds2.py
import gc, sys
import time
from datasets import load_dataset
import os, psutil
process = psutil.Process(os.getpid())
print(process.memory_info().rss/2**20)
corpus = load_dataset("BeIR/msmarco", 'corpus', keep_in_mem... | e## Describe the bug
It seems that memory never gets freed after iterating a `Dataset` (using `.map()` or a simple `for` loop)
## Steps to reproduce the bug
```python
import gc
import logging
import time
import pyarrow
from datasets import load_dataset
from tqdm import trange
import os, psutil
logging.ba... | 160 | Memory leak when iterating a Dataset
e## Describe the bug
It seems that memory never gets freed after iterating a `Dataset` (using `.map()` or a simple `for` loop)
## Steps to reproduce the bug
```python
import gc
import logging
import time
import pyarrow
from datasets import load_dataset
from tqdm import ... | [
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0.16322122514247894,
0.3858795762062073,
-0.14323654770851135,
-0.215461... |
https://github.com/huggingface/datasets/issues/4528 | Memory leak when iterating a Dataset | @NouamaneTazi, please check my analysis here https://github.com/huggingface/datasets/issues/4883#issuecomment-1242599722 so if you agree with my research this Issue can be closed as well.
I also made a suggestion at how to proceed to hunt for a real leak here https://github.com/huggingface/datasets/issues/4883#issue... | e## Describe the bug
It seems that memory never gets freed after iterating a `Dataset` (using `.map()` or a simple `for` loop)
## Steps to reproduce the bug
```python
import gc
import logging
import time
import pyarrow
from datasets import load_dataset
from tqdm import trange
import os, psutil
logging.ba... | 49 | Memory leak when iterating a Dataset
e## Describe the bug
It seems that memory never gets freed after iterating a `Dataset` (using `.map()` or a simple `for` loop)
## Steps to reproduce the bug
```python
import gc
import logging
import time
import pyarrow
from datasets import load_dataset
from tqdm import ... | [
-0.15567363798618317,
-0.16557979583740234,
-0.01564326509833336,
0.3840182423591614,
0.13620826601982117,
-0.029722709208726883,
-0.06453169882297516,
0.019132450222969055,
-0.13223832845687866,
-0.10357432067394257,
0.16322122514247894,
0.3858795762062073,
-0.14323654770851135,
-0.215461... |
https://github.com/huggingface/datasets/issues/4528 | Memory leak when iterating a Dataset | Amazing job! Thanks for taking time to debug this 🤗
For my side, I tried to do some more research as well, but to no avail. https://github.com/huggingface/datasets/issues/4883#issuecomment-1243415957 | e## Describe the bug
It seems that memory never gets freed after iterating a `Dataset` (using `.map()` or a simple `for` loop)
## Steps to reproduce the bug
```python
import gc
import logging
import time
import pyarrow
from datasets import load_dataset
from tqdm import trange
import os, psutil
logging.ba... | 27 | Memory leak when iterating a Dataset
e## Describe the bug
It seems that memory never gets freed after iterating a `Dataset` (using `.map()` or a simple `for` loop)
## Steps to reproduce the bug
```python
import gc
import logging
import time
import pyarrow
from datasets import load_dataset
from tqdm import ... | [
-0.15567363798618317,
-0.16557979583740234,
-0.01564326509833336,
0.3840182423591614,
0.13620826601982117,
-0.029722709208726883,
-0.06453169882297516,
0.019132450222969055,
-0.13223832845687866,
-0.10357432067394257,
0.16322122514247894,
0.3858795762062073,
-0.14323654770851135,
-0.215461... |
https://github.com/huggingface/datasets/issues/4526 | split cache used when processing different split | I was not able to reproduce this behavior (I tried without using pytorch lightning though, since I don't know what code you ran in pytorch lightning to get this).
If you can provide a MWE that would be perfect ! :) | ## Describe the bug`
```
ds1 = load_dataset('squad', split='validation')
ds2 = load_dataset('squad', split='train')
ds1 = ds1.map(some_function)
ds2 = ds2.map(some_function)
assert ds1 == ds2
```
This happens when ds1 and ds2 are created in `pytorch_lightning.DataModule` through
```
class myDataModule:
... | 41 | split cache used when processing different split
## Describe the bug`
```
ds1 = load_dataset('squad', split='validation')
ds2 = load_dataset('squad', split='train')
ds1 = ds1.map(some_function)
ds2 = ds2.map(some_function)
assert ds1 == ds2
```
This happens when ds1 and ds2 are created in `pytorch_lightning.D... | [
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0.004680555313825607,
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0.34816986322402954,
0.07826729863882065,
-0.08422911167144... |
https://github.com/huggingface/datasets/issues/4526 | split cache used when processing different split | Hi, I think the issue happened because I was loading datasets under an `if` ... `else` statement and the condition would change the dataset I would need to load but instead the cached one was always returned. However, I believe that is expected behaviour, if so I'll close the issue.
Otherwise I will try to provide a... | ## Describe the bug`
```
ds1 = load_dataset('squad', split='validation')
ds2 = load_dataset('squad', split='train')
ds1 = ds1.map(some_function)
ds2 = ds2.map(some_function)
assert ds1 == ds2
```
This happens when ds1 and ds2 are created in `pytorch_lightning.DataModule` through
```
class myDataModule:
... | 58 | split cache used when processing different split
## Describe the bug`
```
ds1 = load_dataset('squad', split='validation')
ds2 = load_dataset('squad', split='train')
ds1 = ds1.map(some_function)
ds2 = ds2.map(some_function)
assert ds1 == ds2
```
This happens when ds1 and ds2 are created in `pytorch_lightning.D... | [
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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.
Tr... | [
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-0.12448765337467194,
-0.04219004511833191,
0.325805127620697,
0.3414510488510132,
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0.2916374206542969,
0.17966338992118835,
-0.20729193091392517,
0.2970901727676391... |
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.
Tr... | [
-0.3179207444190979,
-0.12448765337467194,
-0.04219004511833191,
0.325805127620697,
0.3414510488510132,
-0.14221429824829102,
-0.09138506650924683,
0.4362598657608032,
-0.1771542876958847,
0.3672865331172943,
0.2916374206542969,
0.17966338992118835,
-0.20729193091392517,
0.2970901727676391... |
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.
Tr... | [
-0.3179207444190979,
-0.12448765337467194,
-0.04219004511833191,
0.325805127620697,
0.3414510488510132,
-0.14221429824829102,
-0.09138506650924683,
0.4362598657608032,
-0.1771542876958847,
0.3672865331172943,
0.2916374206542969,
0.17966338992118835,
-0.20729193091392517,
0.2970901727676391... |
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