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https://github.com/huggingface/datasets/issues/3475 | Hi @puzzler10, thanks for reporting.
Please note this dataset is not hosted on Hugging Face Hub. See:
https://github.com/huggingface/datasets/blob/c8f914473b041833fd47178fa4373cdcb56ac522/datasets/rotten_tomatoes/rotten_tomatoes.py#L42
If there are issues with the source data of a dataset, you should contact th... | The rotten_tomatoes dataset of movie reviews contains some reviews in Spanish | ## Describe the bug
See title. I don't think this is intentional and they probably should be removed. If they stay the dataset description should be at least updated to make it clear to the user.
## Steps to reproduce the bug
Go to the [dataset viewer](https://huggingface.co/datasets/viewer/?dataset=rotten_tomato... | 95 | The rotten_tomatoes dataset of movie reviews contains some reviews in Spanish
## Describe the bug
See title. I don't think this is intentional and they probably should be removed. If they stay the dataset description should be at least updated to make it clear to the user.
## Steps to reproduce the bug
Go to t... | [
0.07759794592857361,
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0.28727012872695923,
0.3433725833892822,
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0.09299157559871674,
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0.0967244952917099,
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0.0033950544893741608,
0.011461351066827774,
-0.1756011843681... |
https://github.com/huggingface/datasets/issues/3473 | As discussed, I remember I set `decoded=False` here to avoid decoding just by iterating over examples of dataset. We wanted to decode only if the "audio" field (for Audio feature) was accessed. | Iterating over a vision dataset doesn't decode the images | ## Describe the bug
If I load `mnist` and I iterate over the dataset, the images are not decoded, and the dictionary with the bytes is returned.
## Steps to reproduce the bug
```python
from datasets import load_dataset
import PIL
mnist = load_dataset("mnist", split="train")
first_image = mnist[0]["image"... | 32 | Iterating over a vision dataset doesn't decode the images
## Describe the bug
If I load `mnist` and I iterate over the dataset, the images are not decoded, and the dictionary with the bytes is returned.
## Steps to reproduce the bug
```python
from datasets import load_dataset
import PIL
mnist = load_datas... | [
-0.12675897777080536,
-0.3187016546726227,
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0.5622796416282654,
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https://github.com/huggingface/datasets/issues/3473 | > I set decoded=False here to avoid decoding just by iterating over examples of dataset. We wanted to decode only if the "audio" field (for Audio feature) was accessed
https://github.com/huggingface/datasets/pull/3430 will add more control to decoding, so I think it's OK to enable decoding in `__iter__` for now. Aft... | Iterating over a vision dataset doesn't decode the images | ## Describe the bug
If I load `mnist` and I iterate over the dataset, the images are not decoded, and the dictionary with the bytes is returned.
## Steps to reproduce the bug
```python
from datasets import load_dataset
import PIL
mnist = load_dataset("mnist", split="train")
first_image = mnist[0]["image"... | 61 | Iterating over a vision dataset doesn't decode the images
## Describe the bug
If I load `mnist` and I iterate over the dataset, the images are not decoded, and the dictionary with the bytes is returned.
## Steps to reproduce the bug
```python
from datasets import load_dataset
import PIL
mnist = load_datas... | [
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0.5809369683265686,
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https://github.com/huggingface/datasets/issues/3473 | @mariosasko I wonder why there is no issue in `Audio` feature with decoding disabled in `__iter__`, whereas there is in `Image` feature.
Enabling decoding in `__iter__` will make fail Audio regressions tests: https://github.com/huggingface/datasets/runs/4608657230?check_suite_focus=true
```
=======================... | Iterating over a vision dataset doesn't decode the images | ## Describe the bug
If I load `mnist` and I iterate over the dataset, the images are not decoded, and the dictionary with the bytes is returned.
## Steps to reproduce the bug
```python
from datasets import load_dataset
import PIL
mnist = load_dataset("mnist", split="train")
first_image = mnist[0]["image"... | 52 | Iterating over a vision dataset doesn't decode the images
## Describe the bug
If I load `mnist` and I iterate over the dataset, the images are not decoded, and the dictionary with the bytes is returned.
## Steps to reproduce the bug
```python
from datasets import load_dataset
import PIL
mnist = load_datas... | [
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0.2798421084880829,
0.1267051100730896,
0.562263011932373,
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-0.177530318498... |
https://github.com/huggingface/datasets/issues/3473 | Please also note that the regression tests were implemented in accordance with the specifications:
- when doing a `map` (wich calls `__iter__`) of a function that doesn't access the audio field, the decoding should be disabled; this is why the decoding is disabled in `__iter__` (and only enabled in `__getitem__`). | Iterating over a vision dataset doesn't decode the images | ## Describe the bug
If I load `mnist` and I iterate over the dataset, the images are not decoded, and the dictionary with the bytes is returned.
## Steps to reproduce the bug
```python
from datasets import load_dataset
import PIL
mnist = load_dataset("mnist", split="train")
first_image = mnist[0]["image"... | 50 | Iterating over a vision dataset doesn't decode the images
## Describe the bug
If I load `mnist` and I iterate over the dataset, the images are not decoded, and the dictionary with the bytes is returned.
## Steps to reproduce the bug
```python
from datasets import load_dataset
import PIL
mnist = load_datas... | [
-0.17897158861160278,
-0.2866586446762085,
-0.08697322010993958,
0.3713635206222534,
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-0.2217884957790... |
https://github.com/huggingface/datasets/issues/3473 | > I wonder why there is no issue in Audio feature with decoding disabled in __iter__, whereas there is in Image feature.
@albertvillanova Not sure if I understand this part. Currently, both the Image and the Audio feature don't decode data in `__iter__`, so their behavior is aligned there.
| Iterating over a vision dataset doesn't decode the images | ## Describe the bug
If I load `mnist` and I iterate over the dataset, the images are not decoded, and the dictionary with the bytes is returned.
## Steps to reproduce the bug
```python
from datasets import load_dataset
import PIL
mnist = load_dataset("mnist", split="train")
first_image = mnist[0]["image"... | 49 | Iterating over a vision dataset doesn't decode the images
## Describe the bug
If I load `mnist` and I iterate over the dataset, the images are not decoded, and the dictionary with the bytes is returned.
## Steps to reproduce the bug
```python
from datasets import load_dataset
import PIL
mnist = load_datas... | [
-0.09086047112941742,
-0.3369821012020111,
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https://github.com/huggingface/datasets/issues/3473 | Therefore, this is not an issue, neither for Audio nor Image feature.
Could you please elaborate more on the expected use case? @lhoestq @NielsRogge
The expected use cases (in accordance with the specs: see #2324):
- decoding should be enabled when accessing a specific item (`__getitem__`)
- decoding should be... | Iterating over a vision dataset doesn't decode the images | ## Describe the bug
If I load `mnist` and I iterate over the dataset, the images are not decoded, and the dictionary with the bytes is returned.
## Steps to reproduce the bug
```python
from datasets import load_dataset
import PIL
mnist = load_dataset("mnist", split="train")
first_image = mnist[0]["image"... | 88 | Iterating over a vision dataset doesn't decode the images
## Describe the bug
If I load `mnist` and I iterate over the dataset, the images are not decoded, and the dictionary with the bytes is returned.
## Steps to reproduce the bug
```python
from datasets import load_dataset
import PIL
mnist = load_datas... | [
-0.130966916680336,
-0.31124165654182434,
-0.06793108582496643,
0.39010950922966003,
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-0.1515947580... |
https://github.com/huggingface/datasets/issues/3473 | For me it's not an issue, actually. I just (mistakenly) tried to iterate over a PyTorch Dataset instead of a PyTorch DataLoader,
i.e. I did this:
`batch = next(iter(train_ds)) `
whereas I actually wanted to do
`batch = next(iter(train_dataloader))`
and then it turned out that in the first case, the imag... | Iterating over a vision dataset doesn't decode the images | ## Describe the bug
If I load `mnist` and I iterate over the dataset, the images are not decoded, and the dictionary with the bytes is returned.
## Steps to reproduce the bug
```python
from datasets import load_dataset
import PIL
mnist = load_dataset("mnist", split="train")
first_image = mnist[0]["image"... | 66 | Iterating over a vision dataset doesn't decode the images
## Describe the bug
If I load `mnist` and I iterate over the dataset, the images are not decoded, and the dictionary with the bytes is returned.
## Steps to reproduce the bug
```python
from datasets import load_dataset
import PIL
mnist = load_datas... | [
-0.08787306398153305,
-0.30963268876075745,
-0.04000169038772583,
0.3918702304363251,
0.13346555829048157,
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0.18964265286922455,
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0.2231496125459671,
0.1672266125679016,
0.5336775779724121,
-0.09779538214206696,
-0.1827501356601... |
https://github.com/huggingface/datasets/issues/3473 | Thanks @NielsRogge for the context.
So IMO everything is working as expected.
I'm closing this issue. Feel free to reopen it again if further changes of the specs should be addressed. | Iterating over a vision dataset doesn't decode the images | ## Describe the bug
If I load `mnist` and I iterate over the dataset, the images are not decoded, and the dictionary with the bytes is returned.
## Steps to reproduce the bug
```python
from datasets import load_dataset
import PIL
mnist = load_dataset("mnist", split="train")
first_image = mnist[0]["image"... | 31 | Iterating over a vision dataset doesn't decode the images
## Describe the bug
If I load `mnist` and I iterate over the dataset, the images are not decoded, and the dictionary with the bytes is returned.
## Steps to reproduce the bug
```python
from datasets import load_dataset
import PIL
mnist = load_datas... | [
-0.09116116911172867,
-0.3595888912677765,
-0.05083273723721504,
0.4086553454399109,
0.14124129712581635,
-0.013650931417942047,
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0.19493302702903748,
0.17921434342861176,
0.5321477055549622,
-0.04391554743051529,
-0.123993277... |
https://github.com/huggingface/datasets/issues/3473 | Thanks for the details :)
I still think that it's unexpected to get different results when doing
```python
for i in range(len(dataset)):
sample = dataset[i]
```
and
```python
for sample in dataset:
pass
```
even though I understand that if you don't need to decode the data, then decoding image or a... | Iterating over a vision dataset doesn't decode the images | ## Describe the bug
If I load `mnist` and I iterate over the dataset, the images are not decoded, and the dictionary with the bytes is returned.
## Steps to reproduce the bug
```python
from datasets import load_dataset
import PIL
mnist = load_dataset("mnist", split="train")
first_image = mnist[0]["image"... | 83 | Iterating over a vision dataset doesn't decode the images
## Describe the bug
If I load `mnist` and I iterate over the dataset, the images are not decoded, and the dictionary with the bytes is returned.
## Steps to reproduce the bug
```python
from datasets import load_dataset
import PIL
mnist = load_datas... | [
-0.02349381148815155,
-0.3361242711544037,
-0.11522024869918823,
0.4020478427410126,
0.10956674814224243,
-0.06735433638095856,
0.18373656272888184,
0.054037075489759445,
-0.007079817354679108,
0.21135713160037994,
0.15596362948417664,
0.556505024433136,
-0.020243363454937935,
-0.134561657... |
https://github.com/huggingface/datasets/issues/3465 | Hi @talha1503, thanks for reporting.
It seems there is an issue with one of the data files hosted at Google Drive:
```
Google Drive - Quota exceeded
Sorry, you can't view or download this file at this time.
Too many users have viewed or downloaded this file recently. Please try accessing the file again later... | Unable to load 'cnn_dailymail' dataset | ## Describe the bug
I wanted to load cnn_dailymail dataset from huggingface datasets on Google Colab, but I am getting an error while loading it.
## Steps to reproduce the bug
```python
from datasets import load_dataset
dataset = load_dataset('cnn_dailymail', '3.0.0', ignore_verifications = True)
```
## Expe... | 141 | Unable to load 'cnn_dailymail' dataset
## Describe the bug
I wanted to load cnn_dailymail dataset from huggingface datasets on Google Colab, but I am getting an error while loading it.
## Steps to reproduce the bug
```python
from datasets import load_dataset
dataset = load_dataset('cnn_dailymail', '3.0.0', ign... | [
0.023011043667793274,
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0.387969344854... |
https://github.com/huggingface/datasets/issues/3464 | Hi ! Can you try setting `datasets.config.MAX_TABLE_NBYTES_FOR_PICKLING` to a smaller value than `4 << 30` (4GiB), for example `500 << 20` (500MiB) ? It should reduce the maximum size of the arrow table being pickled during multiprocessing.
If it fixes the issue, we can consider lowering the default value for everyo... | struct.error: 'i' format requires -2147483648 <= number <= 2147483647 | ## Describe the bug
A clear and concise description of what the bug is.
using latest datasets=datasets-1.16.1-py3-none-any.whl
process my own multilingual dataset by following codes, and the number of rows in all dataset is 306000, the max_length of each sentence is 256:
. The motion file is the AMC file (Acclaim Motion Capture data). ]
Some questions :
1. How do we go about representing these features using datasets.Features and generate examples ?
2. The dataset download link ... | Add CMU Graphics Lab Motion Capture dataset | ## Adding a Dataset
- **Name:** CMU Graphics Lab Motion Capture database
- **Description:** The database contains free motions which you can download and use.
- **Data:** http://mocap.cs.cmu.edu/
- **Motivation:** Nice motion capture dataset
Instructions to add a new dataset can be found [here](https://github.c... | 149 | Add CMU Graphics Lab Motion Capture dataset
## Adding a Dataset
- **Name:** CMU Graphics Lab Motion Capture database
- **Description:** The database contains free motions which you can download and use.
- **Data:** http://mocap.cs.cmu.edu/
- **Motivation:** Nice motion capture dataset
Instructions to add a ne... | [
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0.2164121717... |
https://github.com/huggingface/datasets/issues/3457 | Hi @dnaveenr! Thanks for working on this!
1. We can use the `Sequence(Value("string"))` feature type for the subject's AMC files and `Value("string")` for the subject's ASF file (`Value("string")` represents the file paths) + the types for categories/subcategories and descriptions.
2. We can use this URL to downloa... | Add CMU Graphics Lab Motion Capture dataset | ## Adding a Dataset
- **Name:** CMU Graphics Lab Motion Capture database
- **Description:** The database contains free motions which you can download and use.
- **Data:** http://mocap.cs.cmu.edu/
- **Motivation:** Nice motion capture dataset
Instructions to add a new dataset can be found [here](https://github.c... | 181 | Add CMU Graphics Lab Motion Capture dataset
## Adding a Dataset
- **Name:** CMU Graphics Lab Motion Capture database
- **Description:** The database contains free motions which you can download and use.
- **Data:** http://mocap.cs.cmu.edu/
- **Motivation:** Nice motion capture dataset
Instructions to add a ne... | [
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0.299666613340... |
https://github.com/huggingface/datasets/issues/3457 | Hi @mariosasko ,
1. Thanks for this, so we can add the file paths.
2. Yes, I had already mailed the authors a couple of days back actually, asking for the metadata details[ i.e category, sub-category and motion description] . They are yet to respond though, I will wait for a couple of days and try to follow up with... | Add CMU Graphics Lab Motion Capture dataset | ## Adding a Dataset
- **Name:** CMU Graphics Lab Motion Capture database
- **Description:** The database contains free motions which you can download and use.
- **Data:** http://mocap.cs.cmu.edu/
- **Motivation:** Nice motion capture dataset
Instructions to add a new dataset can be found [here](https://github.c... | 107 | Add CMU Graphics Lab Motion Capture dataset
## Adding a Dataset
- **Name:** CMU Graphics Lab Motion Capture database
- **Description:** The database contains free motions which you can download and use.
- **Data:** http://mocap.cs.cmu.edu/
- **Motivation:** Nice motion capture dataset
Instructions to add a ne... | [
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0.33929097652... |
https://github.com/huggingface/datasets/issues/3455 | Hi ! I guess you are talking about the dataset cards that are in this repository on github ?
I think github allows to submit a PR even for 1 line though the `Edit file` button on the page of the dataset card.
Maybe let's mention this in `CONTRIBUTING.md` ? | Easier information editing | **Is your feature request related to a problem? Please describe.**
It requires a lot of effort to improve a datasheet.
**Describe the solution you'd like**
UI or at least a link to the place where the code that needs to be edited is (and an easy way to edit this code directly from the site, without cloning, branc... | 50 | Easier information editing
**Is your feature request related to a problem? Please describe.**
It requires a lot of effort to improve a datasheet.
**Describe the solution you'd like**
UI or at least a link to the place where the code that needs to be edited is (and an easy way to edit this code directly from the... | [
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0.16187919676303864,
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0.20051902532577515,
0.3080872893333435,
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0.2243680506944... |
https://github.com/huggingface/datasets/issues/3455 | We now host all the datasets on the HF Hub, where you can easily edit them through UI (for single file changes) or Git workflow (for single/multiple file changes) | Easier information editing | **Is your feature request related to a problem? Please describe.**
It requires a lot of effort to improve a datasheet.
**Describe the solution you'd like**
UI or at least a link to the place where the code that needs to be edited is (and an easy way to edit this code directly from the site, without cloning, branc... | 29 | Easier information editing
**Is your feature request related to a problem? Please describe.**
It requires a lot of effort to improve a datasheet.
**Describe the solution you'd like**
UI or at least a link to the place where the code that needs to be edited is (and an easy way to edit this code directly from the... | [
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0.272258579730... |
https://github.com/huggingface/datasets/issues/3452 | Hi ! It's simply not added yet :)
If someone wants to contribute to add the `stratify` parameter I'd be happy to give some pointers.
In the meantime, I guess you can use `sklearn` or other tools to do a stratified train/test split over the **indices** of your dataset and then do
```
train_dataset = dataset.sele... | why the stratify option is omitted from test_train_split function? | why the stratify option is omitted from test_train_split function?
is there any other way implement the stratify option while splitting the dataset? as it is important point to be considered while splitting the dataset. | 60 | why the stratify option is omitted from test_train_split function?
why the stratify option is omitted from test_train_split function?
is there any other way implement the stratify option while splitting the dataset? as it is important point to be considered while splitting the dataset.
Hi ! It's simply not added... | [
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https://github.com/huggingface/datasets/issues/3452 | Hi @lhoestq I would like to add `stratify` parameter, can you give me some pointers for adding the same ? | why the stratify option is omitted from test_train_split function? | why the stratify option is omitted from test_train_split function?
is there any other way implement the stratify option while splitting the dataset? as it is important point to be considered while splitting the dataset. | 20 | why the stratify option is omitted from test_train_split function?
why the stratify option is omitted from test_train_split function?
is there any other way implement the stratify option while splitting the dataset? as it is important point to be considered while splitting the dataset.
Hi @lhoestq I would like t... | [
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https://github.com/huggingface/datasets/issues/3452 | Hi ! Sure :)
The `train_test_split` method is defined here:
https://github.com/huggingface/datasets/blob/dc62232fa1b3bcfe2fbddcb721f2d141f8908943/src/datasets/arrow_dataset.py#L3253-L3253
and inside `train_test_split ` we need to create the right `train_indices` and `test_indices` that are passed here to `.se... | why the stratify option is omitted from test_train_split function? | why the stratify option is omitted from test_train_split function?
is there any other way implement the stratify option while splitting the dataset? as it is important point to be considered while splitting the dataset. | 114 | why the stratify option is omitted from test_train_split function?
why the stratify option is omitted from test_train_split function?
is there any other way implement the stratify option while splitting the dataset? as it is important point to be considered while splitting the dataset.
Hi ! Sure :)
The `train... | [
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https://github.com/huggingface/datasets/issues/3450 | Hi ! This is an issue with `datasets` 1.12. Sorry for the inconvenience. Can you update to `>=1.13` ?
see https://github.com/huggingface/datasets/issues/3190
Maybe we should also backport the bug fix to `1.12` (in a new version `1.12.2`) | Unexpected behavior doing Split + Filter | ## Describe the bug
I observed unexpected behavior when applying 'train_test_split' followed by 'filter' on dataset. Elements of the training dataset eventually end up in the test dataset (after applying the 'filter')
## Steps to reproduce the bug
```
from datasets import Dataset
import pandas as pd
dic = {'x'... | 36 | Unexpected behavior doing Split + Filter
## Describe the bug
I observed unexpected behavior when applying 'train_test_split' followed by 'filter' on dataset. Elements of the training dataset eventually end up in the test dataset (after applying the 'filter')
## Steps to reproduce the bug
```
from datasets impo... | [
-0.13840065896511078,
-0.13383205235004425,
-0.11009343713521957,
0.09648397564888,
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0.1856798529624939,
0.25523048639297485,
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0.47418245673179626,
0.007550619542598724,
0.403278112411... |
https://github.com/huggingface/datasets/issues/3449 | I was going through the codebase, and I believe the implementation of __add__() and __iadd__() will be similar to concatenate_datasets() after the elimination of code for arguments other than the list of datasets (info, split, axis).
(Assuming elimination of axis means concatenating over axis 1.) | Add `__add__()`, `__iadd__()` and similar to `Dataset` class | **Is your feature request related to a problem? Please describe.**
No.
**Describe the solution you'd like**
I would like to be able to concatenate datasets as follows:
```python
>>> dataset["train"] += dataset["validation"]
```
... instead of using `concatenate_datasets()`:
```python
>>> raw_datasets["trai... | 45 | Add `__add__()`, `__iadd__()` and similar to `Dataset` class
**Is your feature request related to a problem? Please describe.**
No.
**Describe the solution you'd like**
I would like to be able to concatenate datasets as follows:
```python
>>> dataset["train"] += dataset["validation"]
```
... instead of usi... | [
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0.017441093921661377,
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0.41349974274635315,
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0.15600356459617615,
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0.345527708530426,
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0.218938887119293... |
https://github.com/huggingface/datasets/issues/3449 | Most data frame libraries (Polars, Pandas, ...) override `__add__` to perform (mathematical) summation, so having different behavior here is a bad idea. | Add `__add__()`, `__iadd__()` and similar to `Dataset` class | **Is your feature request related to a problem? Please describe.**
No.
**Describe the solution you'd like**
I would like to be able to concatenate datasets as follows:
```python
>>> dataset["train"] += dataset["validation"]
```
... instead of using `concatenate_datasets()`:
```python
>>> raw_datasets["trai... | 22 | Add `__add__()`, `__iadd__()` and similar to `Dataset` class
**Is your feature request related to a problem? Please describe.**
No.
**Describe the solution you'd like**
I would like to be able to concatenate datasets as follows:
```python
>>> dataset["train"] += dataset["validation"]
```
... instead of usi... | [
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0.14234203100204468,
-0.0760965645313263,
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0.2898493707180023,
-0.039136242121458054,
0.27559947967529... |
https://github.com/huggingface/datasets/issues/3448 | Hi ! I think the issue comes from the dataset_infos.json file: it has the "flat" field twice.
Can you try deleting this file and regenerating it please ? | JSONDecodeError with HuggingFace dataset viewer | ## Dataset viewer issue for 'pubmed_neg'
**Link:** https://huggingface.co/datasets/IGESML/pubmed_neg
I am getting the error:
Status code: 400
Exception: JSONDecodeError
Message: Expecting property name enclosed in double quotes: line 61 column 2 (char 1202)
I have checked all files - I am not u... | 28 | JSONDecodeError with HuggingFace dataset viewer
## Dataset viewer issue for 'pubmed_neg'
**Link:** https://huggingface.co/datasets/IGESML/pubmed_neg
I am getting the error:
Status code: 400
Exception: JSONDecodeError
Message: Expecting property name enclosed in double quotes: line 61 column 2 (c... | [
0.2295418083667755,
-0.12012786418199539,
0.04900544136762619,
0.23034468293190002,
0.16956910490989685,
0.057723358273506165,
0.08529110997915268,
0.16236604750156403,
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0.09629207849502563,
0.16684682667255402,
0.2956419587135315,
-0.1245155781507492,
0.0679472908377... |
https://github.com/huggingface/datasets/issues/3448 | Thanks! That fixed that, but now I am getting:
Server Error
Status code: 400
Exception: KeyError
Message: 'feature'
I checked the dataset_infos.json and pubmed_neg.py script, I don't use 'feature' anywhere as a key. Is the dataset viewer expecting that I do? | JSONDecodeError with HuggingFace dataset viewer | ## Dataset viewer issue for 'pubmed_neg'
**Link:** https://huggingface.co/datasets/IGESML/pubmed_neg
I am getting the error:
Status code: 400
Exception: JSONDecodeError
Message: Expecting property name enclosed in double quotes: line 61 column 2 (char 1202)
I have checked all files - I am not u... | 41 | JSONDecodeError with HuggingFace dataset viewer
## Dataset viewer issue for 'pubmed_neg'
**Link:** https://huggingface.co/datasets/IGESML/pubmed_neg
I am getting the error:
Status code: 400
Exception: JSONDecodeError
Message: Expecting property name enclosed in double quotes: line 61 column 2 (c... | [
0.3349670171737671,
-0.16928432881832123,
0.05797412991523743,
0.17839041352272034,
0.11598606407642365,
0.0022668465971946716,
0.16587787866592407,
0.029386188834905624,
-0.03549095243215561,
0.08846540749073029,
0.24156635999679565,
0.28079864382743835,
-0.1743423342704773,
0.19495022296... |
https://github.com/huggingface/datasets/issues/3448 | It seems that the `feature` key is missing from some feature type definition in your dataset_infos.json:
```json
"tokens": {
"dtype": "list",
"id": null,
"_type": "Sequence"
},
"tags": {
"dtype": "list",
"id": null,
"_type": "Sequence"
}
```
They should be
```json
"... | JSONDecodeError with HuggingFace dataset viewer | ## Dataset viewer issue for 'pubmed_neg'
**Link:** https://huggingface.co/datasets/IGESML/pubmed_neg
I am getting the error:
Status code: 400
Exception: JSONDecodeError
Message: Expecting property name enclosed in double quotes: line 61 column 2 (char 1202)
I have checked all files - I am not u... | 98 | JSONDecodeError with HuggingFace dataset viewer
## Dataset viewer issue for 'pubmed_neg'
**Link:** https://huggingface.co/datasets/IGESML/pubmed_neg
I am getting the error:
Status code: 400
Exception: JSONDecodeError
Message: Expecting property name enclosed in double quotes: line 61 column 2 (c... | [
0.10931265354156494,
-0.03486365079879761,
0.034162458032369614,
0.12410736829042435,
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0.09111492335796356,
0.18194499611854553,
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0.13438817858695984,
0.16038033366203308,
0.39061689376831055,
-0.22606894373893738,
0.17792671918... |
https://github.com/huggingface/datasets/issues/3447 | Hi ! Indeed it says "downloading and preparing" but in your case it didn't need to download anything since you used local files (it would have thrown an error otherwise). I think we can improve the logging to make it clearer in this case | HF_DATASETS_OFFLINE=1 didn't stop datasets.builder from downloading | ## Describe the bug
According to https://huggingface.co/docs/datasets/loading_datasets.html#loading-a-dataset-builder, setting HF_DATASETS_OFFLINE to 1 should make datasets to "run in full offline mode". It didn't work for me. At the very beginning, datasets still tried to download "custom data configuration" for JSON... | 44 | HF_DATASETS_OFFLINE=1 didn't stop datasets.builder from downloading
## Describe the bug
According to https://huggingface.co/docs/datasets/loading_datasets.html#loading-a-dataset-builder, setting HF_DATASETS_OFFLINE to 1 should make datasets to "run in full offline mode". It didn't work for me. At the very beginning... | [
-0.3771057724952698,
0.36455482244491577,
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0.2978966236114502,
0.24783512949943542,
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0.24482032656669617,
0.18767523765563965,
0.2710859179496765,
0.06063772365450859,
-0.05636683106422424,
0.0012007839977741241,
-0.04779556021094322,
0.22445608675... |
https://github.com/huggingface/datasets/issues/3447 | @lhoestq Thank you for explaining. I am sorry but I was not clear about my intention. I didn't want to kill internet traffic; I wanted to kill all write activity. In other words, you can imagine that my storage has only read access but crashes on write.
When run_clm.py is invoked with the same parameters, the hash i... | HF_DATASETS_OFFLINE=1 didn't stop datasets.builder from downloading | ## Describe the bug
According to https://huggingface.co/docs/datasets/loading_datasets.html#loading-a-dataset-builder, setting HF_DATASETS_OFFLINE to 1 should make datasets to "run in full offline mode". It didn't work for me. At the very beginning, datasets still tried to download "custom data configuration" for JSON... | 201 | HF_DATASETS_OFFLINE=1 didn't stop datasets.builder from downloading
## Describe the bug
According to https://huggingface.co/docs/datasets/loading_datasets.html#loading-a-dataset-builder, setting HF_DATASETS_OFFLINE to 1 should make datasets to "run in full offline mode". It didn't work for me. At the very beginning... | [
-0.3771057724952698,
0.36455482244491577,
0.05455685406923294,
0.2978966236114502,
0.24783512949943542,
-0.024279378354549408,
0.24482032656669617,
0.18767523765563965,
0.2710859179496765,
0.06063772365450859,
-0.05636683106422424,
0.0012007839977741241,
-0.04779556021094322,
0.22445608675... |
https://github.com/huggingface/datasets/issues/3447 | Hi ! `load_dataset` may re-generate your dataset if some parameters changed indeed. If you want to freeze a dataset loaded with `load_dataset`, I think the best solution is just to save it somewhere on your disk with `.save_to_disk(my_dataset_dir)` and reload it with `load_from_disk(my_dataset_dir)`. This way you will ... | HF_DATASETS_OFFLINE=1 didn't stop datasets.builder from downloading | ## Describe the bug
According to https://huggingface.co/docs/datasets/loading_datasets.html#loading-a-dataset-builder, setting HF_DATASETS_OFFLINE to 1 should make datasets to "run in full offline mode". It didn't work for me. At the very beginning, datasets still tried to download "custom data configuration" for JSON... | 58 | HF_DATASETS_OFFLINE=1 didn't stop datasets.builder from downloading
## Describe the bug
According to https://huggingface.co/docs/datasets/loading_datasets.html#loading-a-dataset-builder, setting HF_DATASETS_OFFLINE to 1 should make datasets to "run in full offline mode". It didn't work for me. At the very beginning... | [
-0.3771057724952698,
0.36455482244491577,
0.05455685406923294,
0.2978966236114502,
0.24783512949943542,
-0.024279378354549408,
0.24482032656669617,
0.18767523765563965,
0.2710859179496765,
0.06063772365450859,
-0.05636683106422424,
0.0012007839977741241,
-0.04779556021094322,
0.22445608675... |
https://github.com/huggingface/datasets/issues/3444 | Yes I agree, these should be as aligned as possible. Maybe we can also check the feedback in the survey at http://hf.co/oss-survey and see if people mentioned related things on the API (in particular if we go the breaking change way, it would be good to be sure we are taking the right direction for the community). | Align the Dataset and IterableDataset processing API | ## Intro
items marked like <s>this</s> are done already :)
Currently the two classes have two distinct API for processing:
### The `.map()` method
Both have those parameters in common: function, batched, batch_size
- IterableDataset is missing those parameters:
<s>with_indices</s>, with_rank, <s>input_c... | 57 | Align the Dataset and IterableDataset processing API
## Intro
items marked like <s>this</s> are done already :)
Currently the two classes have two distinct API for processing:
### The `.map()` method
Both have those parameters in common: function, batched, batch_size
- IterableDataset is missing those ... | [
-0.2987126410007477,
-0.05432654917240143,
-0.19314606487751007,
0.061763111501932144,
0.1235782653093338,
0.17043417692184448,
0.39588168263435364,
0.5176238417625427,
0.04174280911684036,
0.2871117889881134,
-0.20620471239089966,
0.28705236315727234,
0.03123454377055168,
0.27907428145408... |
https://github.com/huggingface/datasets/issues/3444 | I like this proposal.
> There is also an important difference in terms of behavior:
Dataset.map adds new columns (with dict.update)
BUT
IterableDataset discards previous columns (it overwrites the dict)
IMO the two methods should have the same behavior. This would be an important breaking change though.
> The... | Align the Dataset and IterableDataset processing API | ## Intro
items marked like <s>this</s> are done already :)
Currently the two classes have two distinct API for processing:
### The `.map()` method
Both have those parameters in common: function, batched, batch_size
- IterableDataset is missing those parameters:
<s>with_indices</s>, with_rank, <s>input_c... | 322 | Align the Dataset and IterableDataset processing API
## Intro
items marked like <s>this</s> are done already :)
Currently the two classes have two distinct API for processing:
### The `.map()` method
Both have those parameters in common: function, batched, batch_size
- IterableDataset is missing those ... | [
-0.2987126410007477,
-0.05432654917240143,
-0.19314606487751007,
0.061763111501932144,
0.1235782653093338,
0.17043417692184448,
0.39588168263435364,
0.5176238417625427,
0.04174280911684036,
0.2871117889881134,
-0.20620471239089966,
0.28705236315727234,
0.03123454377055168,
0.27907428145408... |
https://github.com/huggingface/datasets/issues/3444 | > If I understand this part correctly, the idea would be for Dataset.map to behave similarly to Dataset.with_transform (lazy processing) and to have an option to cache processed data (with .cache()). This idea is really nice because it can also be applied to IterableDataset to fix #3142 (again we get the aligned APIs).... | Align the Dataset and IterableDataset processing API | ## Intro
items marked like <s>this</s> are done already :)
Currently the two classes have two distinct API for processing:
### The `.map()` method
Both have those parameters in common: function, batched, batch_size
- IterableDataset is missing those parameters:
<s>with_indices</s>, with_rank, <s>input_c... | 105 | Align the Dataset and IterableDataset processing API
## Intro
items marked like <s>this</s> are done already :)
Currently the two classes have two distinct API for processing:
### The `.map()` method
Both have those parameters in common: function, batched, batch_size
- IterableDataset is missing those ... | [
-0.2987126410007477,
-0.05432654917240143,
-0.19314606487751007,
0.061763111501932144,
0.1235782653093338,
0.17043417692184448,
0.39588168263435364,
0.5176238417625427,
0.04174280911684036,
0.2871117889881134,
-0.20620471239089966,
0.28705236315727234,
0.03123454377055168,
0.27907428145408... |
https://github.com/huggingface/datasets/issues/3444 | Yes indeed, thanks. I added it to the list of methods to align in the first post | Align the Dataset and IterableDataset processing API | ## Intro
items marked like <s>this</s> are done already :)
Currently the two classes have two distinct API for processing:
### The `.map()` method
Both have those parameters in common: function, batched, batch_size
- IterableDataset is missing those parameters:
<s>with_indices</s>, with_rank, <s>input_c... | 17 | Align the Dataset and IterableDataset processing API
## Intro
items marked like <s>this</s> are done already :)
Currently the two classes have two distinct API for processing:
### The `.map()` method
Both have those parameters in common: function, batched, batch_size
- IterableDataset is missing those ... | [
-0.2987126410007477,
-0.05432654917240143,
-0.19314606487751007,
0.061763111501932144,
0.1235782653093338,
0.17043417692184448,
0.39588168263435364,
0.5176238417625427,
0.04174280911684036,
0.2871117889881134,
-0.20620471239089966,
0.28705236315727234,
0.03123454377055168,
0.27907428145408... |
https://github.com/huggingface/datasets/issues/3444 | I just encountered the problem of the missing `fn_kwargs` parameter in the `map` method. I am commenting to give a workaround in case someone has the same problem and does not find a solution.
You can wrap your function call inside a class that contains the other parameters needed by the function called by map, like t... | Align the Dataset and IterableDataset processing API | ## Intro
items marked like <s>this</s> are done already :)
Currently the two classes have two distinct API for processing:
### The `.map()` method
Both have those parameters in common: function, batched, batch_size
- IterableDataset is missing those parameters:
<s>with_indices</s>, with_rank, <s>input_c... | 96 | Align the Dataset and IterableDataset processing API
## Intro
items marked like <s>this</s> are done already :)
Currently the two classes have two distinct API for processing:
### The `.map()` method
Both have those parameters in common: function, batched, batch_size
- IterableDataset is missing those ... | [
-0.2987126410007477,
-0.05432654917240143,
-0.19314606487751007,
0.061763111501932144,
0.1235782653093338,
0.17043417692184448,
0.39588168263435364,
0.5176238417625427,
0.04174280911684036,
0.2871117889881134,
-0.20620471239089966,
0.28705236315727234,
0.03123454377055168,
0.27907428145408... |
https://github.com/huggingface/datasets/issues/3444 | The main differences have been addressed (map, formatting) but there are still a few things to implement like Dataset.take, Dataset.skip, IterableDataset.set_format, IterableDataset.formatted_as, IterableDataset.reset_format.
The rest cannot be implemented for the general case. E.g. train_test_split and select can o... | Align the Dataset and IterableDataset processing API | ## Intro
items marked like <s>this</s> are done already :)
Currently the two classes have two distinct API for processing:
### The `.map()` method
Both have those parameters in common: function, batched, batch_size
- IterableDataset is missing those parameters:
<s>with_indices</s>, with_rank, <s>input_c... | 65 | Align the Dataset and IterableDataset processing API
## Intro
items marked like <s>this</s> are done already :)
Currently the two classes have two distinct API for processing:
### The `.map()` method
Both have those parameters in common: function, batched, batch_size
- IterableDataset is missing those ... | [
-0.2987126410007477,
-0.05432654917240143,
-0.19314606487751007,
0.061763111501932144,
0.1235782653093338,
0.17043417692184448,
0.39588168263435364,
0.5176238417625427,
0.04174280911684036,
0.2871117889881134,
-0.20620471239089966,
0.28705236315727234,
0.03123454377055168,
0.27907428145408... |
https://github.com/huggingface/datasets/issues/3440 | Hi ! What version of `datasets` are you using ? Can you also provide the logs you get before it raises the error ? | datasets keeps reading from cached files, although I disabled it | ## Describe the bug
Hi,
I am trying to avoid dataset library using cached files, I get the following bug when this tried to read the cached files. I tried to do the followings:
```
from datasets import set_caching_enabled
set_caching_enabled(False)
```
also force redownlaod:
```
download_mode='force_redownloa... | 24 | datasets keeps reading from cached files, although I disabled it
## Describe the bug
Hi,
I am trying to avoid dataset library using cached files, I get the following bug when this tried to read the cached files. I tried to do the followings:
```
from datasets import set_caching_enabled
set_caching_enabled(False)... | [
-0.13479158282279968,
0.025202572345733643,
0.000902567058801651,
0.5154467225074768,
0.4938993453979492,
0.26463305950164795,
0.05779135599732399,
0.3259376883506775,
0.015479542315006256,
-0.015513800084590912,
-0.21430999040603638,
0.2182268500328064,
-0.08560245484113693,
-0.3043366372... |
https://github.com/huggingface/datasets/issues/3431 | Hi ! `load_dataset` accepts as input either a local dataset directory or a dataset name from the Hugging Face Hub.
So here you are getting this error the second time because it tries to load the local `wiki_dpr` directory, instead of `wiki_dpr` from the Hub. It doesn't work since it's a **cache** directory, not a **... | Unable to resolve any data file after loading once | when I rerun my program, it occurs this error
" Unable to resolve any data file that matches '['**train*']' at /data2/whr/lzy/open_domain_data/retrieval/wiki_dpr with any supported extension ['csv', 'tsv', 'json', 'jsonl', 'parquet', 'txt', 'zip']", so how could i deal with this problem?
thx.
And below is my code .
... | 70 | Unable to resolve any data file after loading once
when I rerun my program, it occurs this error
" Unable to resolve any data file that matches '['**train*']' at /data2/whr/lzy/open_domain_data/retrieval/wiki_dpr with any supported extension ['csv', 'tsv', 'json', 'jsonl', 'parquet', 'txt', 'zip']", so how could i d... | [
0.023501068353652954,
-0.09233047068119049,
-0.08532169461250305,
0.5271120667457581,
0.37984493374824524,
0.1411338597536087,
0.07990583777427673,
0.5025755167007446,
0.20327404141426086,
0.07570146024227142,
0.11050023883581161,
-0.010860640555620193,
0.17593413591384888,
0.0473018437623... |
https://github.com/huggingface/datasets/issues/3425 | It looks like it's currently calling `HfFileSystem.ls()` ~8 times at the root and for each subdirectory:
- ""
- "en.noblocklist"
- "en.noclean"
- "en"
- "multilingual"
- "realnewslike"
Currently `ls` is slow because it iterates on all the files inside the repository.
An easy optimization would be to cache t... | Getting configs names takes too long |
## Steps to reproduce the bug
```python
from datasets import get_dataset_config_names
get_dataset_config_names("allenai/c4")
```
## Expected results
I would expect to get the answer quickly, at least in less than 10s
## Actual results
It takes about 45s on my environment
## Environment info
- `d... | 76 | Getting configs names takes too long
## Steps to reproduce the bug
```python
from datasets import get_dataset_config_names
get_dataset_config_names("allenai/c4")
```
## Expected results
I would expect to get the answer quickly, at least in less than 10s
## Actual results
It takes about 45s on my env... | [
-0.3283519744873047,
0.17222994565963745,
-0.18804141879081726,
0.3770352303981781,
0.1999283730983734,
-0.1003856435418129,
0.13859298825263977,
0.49155038595199585,
-0.02905726060271263,
0.3562118411064148,
-0.1960754692554474,
0.35292989015579224,
0.132097527384758,
-0.24323749542236328... |
https://github.com/huggingface/datasets/issues/3423 | Hi ! Thanks for reporting :)
When using a PyTorch's data loader with `num_workers>1` and an iterable dataset, each worker streams the exact same data by default, resulting in duplicate data when iterating using the data loader.
We can probably fix this in `datasets` by checking `torch.utils.data.get_worker_info()... | data duplicate when setting num_works > 1 with streaming data | ## Describe the bug
The data is repeated num_works times when we load_dataset with streaming and set num_works > 1 when construct dataloader
## Steps to reproduce the bug
```python
# Sample code to reproduce the bug
import pandas as pd
import numpy as np
import os
from datasets import load_dataset
from tor... | 55 | data duplicate when setting num_works > 1 with streaming data
## Describe the bug
The data is repeated num_works times when we load_dataset with streaming and set num_works > 1 when construct dataloader
## Steps to reproduce the bug
```python
# Sample code to reproduce the bug
import pandas as pd
import numpy... | [
-0.23257632553577423,
-0.37529608607292175,
-0.01616865023970604,
0.3272431790828705,
0.2545713484287262,
-0.17621585726737976,
0.5691008567810059,
0.3358849883079529,
-0.2572707235813141,
0.42119985818862915,
0.09563610702753067,
0.20091485977172852,
-0.008096165955066681,
0.1235201060771... |
https://github.com/huggingface/datasets/issues/3423 | > Hi ! Thanks for reporting :)
>
> When using a PyTorch's data loader with `num_workers>1` and an iterable dataset, each worker streams the exact same data by default, resulting in duplicate data when iterating using the data loader.
>
> We can probably fix this in `datasets` by checking `torch.utils.data.get_wor... | data duplicate when setting num_works > 1 with streaming data | ## Describe the bug
The data is repeated num_works times when we load_dataset with streaming and set num_works > 1 when construct dataloader
## Steps to reproduce the bug
```python
# Sample code to reproduce the bug
import pandas as pd
import numpy as np
import os
from datasets import load_dataset
from tor... | 74 | data duplicate when setting num_works > 1 with streaming data
## Describe the bug
The data is repeated num_works times when we load_dataset with streaming and set num_works > 1 when construct dataloader
## Steps to reproduce the bug
```python
# Sample code to reproduce the bug
import pandas as pd
import numpy... | [
-0.23257632553577423,
-0.37529608607292175,
-0.01616865023970604,
0.3272431790828705,
0.2545713484287262,
-0.17621585726737976,
0.5691008567810059,
0.3358849883079529,
-0.2572707235813141,
0.42119985818862915,
0.09563610702753067,
0.20091485977172852,
-0.008096165955066681,
0.1235201060771... |
https://github.com/huggingface/datasets/issues/3423 | Isn’t that somehow a bug on PyTorch side? (Just asking because this behavior seems quite general and maybe not what would be intended) | data duplicate when setting num_works > 1 with streaming data | ## Describe the bug
The data is repeated num_works times when we load_dataset with streaming and set num_works > 1 when construct dataloader
## Steps to reproduce the bug
```python
# Sample code to reproduce the bug
import pandas as pd
import numpy as np
import os
from datasets import load_dataset
from tor... | 23 | data duplicate when setting num_works > 1 with streaming data
## Describe the bug
The data is repeated num_works times when we load_dataset with streaming and set num_works > 1 when construct dataloader
## Steps to reproduce the bug
```python
# Sample code to reproduce the bug
import pandas as pd
import numpy... | [
-0.23257632553577423,
-0.37529608607292175,
-0.01616865023970604,
0.3272431790828705,
0.2545713484287262,
-0.17621585726737976,
0.5691008567810059,
0.3358849883079529,
-0.2572707235813141,
0.42119985818862915,
0.09563610702753067,
0.20091485977172852,
-0.008096165955066681,
0.1235201060771... |
https://github.com/huggingface/datasets/issues/3423 | From PyTorch's documentation [here](https://pytorch.org/docs/stable/data.html#dataset-types):
> When using an IterableDataset with multi-process data loading. The same dataset object is replicated on each worker process, and thus the replicas must be configured differently to avoid duplicated data. See [IterableData... | data duplicate when setting num_works > 1 with streaming data | ## Describe the bug
The data is repeated num_works times when we load_dataset with streaming and set num_works > 1 when construct dataloader
## Steps to reproduce the bug
```python
# Sample code to reproduce the bug
import pandas as pd
import numpy as np
import os
from datasets import load_dataset
from tor... | 127 | data duplicate when setting num_works > 1 with streaming data
## Describe the bug
The data is repeated num_works times when we load_dataset with streaming and set num_works > 1 when construct dataloader
## Steps to reproduce the bug
```python
# Sample code to reproduce the bug
import pandas as pd
import numpy... | [
-0.23257632553577423,
-0.37529608607292175,
-0.01616865023970604,
0.3272431790828705,
0.2545713484287262,
-0.17621585726737976,
0.5691008567810059,
0.3358849883079529,
-0.2572707235813141,
0.42119985818862915,
0.09563610702753067,
0.20091485977172852,
-0.008096165955066681,
0.1235201060771... |
https://github.com/huggingface/datasets/issues/3423 | Hi there @lhoestq @cloudyuyuyu
I met that problem recently, and #4375 is really useful because I finally found out I am training with duplicate data.
However, in multi-GPU training, I'm using DDP mode and IterableDataset, which still yields duplicate data for each progress. And this is dangerous because users maybe ... | data duplicate when setting num_works > 1 with streaming data | ## Describe the bug
The data is repeated num_works times when we load_dataset with streaming and set num_works > 1 when construct dataloader
## Steps to reproduce the bug
```python
# Sample code to reproduce the bug
import pandas as pd
import numpy as np
import os
from datasets import load_dataset
from tor... | 54 | data duplicate when setting num_works > 1 with streaming data
## Describe the bug
The data is repeated num_works times when we load_dataset with streaming and set num_works > 1 when construct dataloader
## Steps to reproduce the bug
```python
# Sample code to reproduce the bug
import pandas as pd
import numpy... | [
-0.23257632553577423,
-0.37529608607292175,
-0.01616865023970604,
0.3272431790828705,
0.2545713484287262,
-0.17621585726737976,
0.5691008567810059,
0.3358849883079529,
-0.2572707235813141,
0.42119985818862915,
0.09563610702753067,
0.20091485977172852,
-0.008096165955066681,
0.1235201060771... |
https://github.com/huggingface/datasets/issues/3423 | If the worker_info.id is unique per process it should work fine, could you check that they're unique ?
The code to get the worker_info in each worker is `torch.utils.data.get_worker_info()` | data duplicate when setting num_works > 1 with streaming data | ## Describe the bug
The data is repeated num_works times when we load_dataset with streaming and set num_works > 1 when construct dataloader
## Steps to reproduce the bug
```python
# Sample code to reproduce the bug
import pandas as pd
import numpy as np
import os
from datasets import load_dataset
from tor... | 29 | data duplicate when setting num_works > 1 with streaming data
## Describe the bug
The data is repeated num_works times when we load_dataset with streaming and set num_works > 1 when construct dataloader
## Steps to reproduce the bug
```python
# Sample code to reproduce the bug
import pandas as pd
import numpy... | [
-0.23257632553577423,
-0.37529608607292175,
-0.01616865023970604,
0.3272431790828705,
0.2545713484287262,
-0.17621585726737976,
0.5691008567810059,
0.3358849883079529,
-0.2572707235813141,
0.42119985818862915,
0.09563610702753067,
0.20091485977172852,
-0.008096165955066681,
0.1235201060771... |
https://github.com/huggingface/datasets/issues/3423 | test.py
```python
import json
import os
import torch
from torch.utils.data import IterableDataset, DataLoader
from transformers import PreTrainedTokenizer, TrainingArguments
from common.arguments import DataTrainingArguments, ModelArguments
class MyIterableDataset(IterableDataset):
def __iter__(sel... | data duplicate when setting num_works > 1 with streaming data | ## Describe the bug
The data is repeated num_works times when we load_dataset with streaming and set num_works > 1 when construct dataloader
## Steps to reproduce the bug
```python
# Sample code to reproduce the bug
import pandas as pd
import numpy as np
import os
from datasets import load_dataset
from tor... | 84 | data duplicate when setting num_works > 1 with streaming data
## Describe the bug
The data is repeated num_works times when we load_dataset with streaming and set num_works > 1 when construct dataloader
## Steps to reproduce the bug
```python
# Sample code to reproduce the bug
import pandas as pd
import numpy... | [
-0.23257632553577423,
-0.37529608607292175,
-0.01616865023970604,
0.3272431790828705,
0.2545713484287262,
-0.17621585726737976,
0.5691008567810059,
0.3358849883079529,
-0.2572707235813141,
0.42119985818862915,
0.09563610702753067,
0.20091485977172852,
-0.008096165955066681,
0.1235201060771... |
https://github.com/huggingface/datasets/issues/3423 | It looks like a bug from pytorch no ? How can we know which data should go in which process when using DDP ?
I guess we need to check `torch.distributed.get_world_size()` and `torch.distributed.get_rank()` as well. Not fan of the design here tbh, but that's how it is | data duplicate when setting num_works > 1 with streaming data | ## Describe the bug
The data is repeated num_works times when we load_dataset with streaming and set num_works > 1 when construct dataloader
## Steps to reproduce the bug
```python
# Sample code to reproduce the bug
import pandas as pd
import numpy as np
import os
from datasets import load_dataset
from tor... | 47 | data duplicate when setting num_works > 1 with streaming data
## Describe the bug
The data is repeated num_works times when we load_dataset with streaming and set num_works > 1 when construct dataloader
## Steps to reproduce the bug
```python
# Sample code to reproduce the bug
import pandas as pd
import numpy... | [
-0.23257632553577423,
-0.37529608607292175,
-0.01616865023970604,
0.3272431790828705,
0.2545713484287262,
-0.17621585726737976,
0.5691008567810059,
0.3358849883079529,
-0.2572707235813141,
0.42119985818862915,
0.09563610702753067,
0.20091485977172852,
-0.008096165955066681,
0.1235201060771... |
https://github.com/huggingface/datasets/issues/3423 | > It looks like a bug from pytorch no ? How can we know which data should go in which process when using DDP ?
>
> I guess we need to check `torch.distributed.get_world_size()` and `torch.distributed.get_rank()` as well. Not fan of the design here tbh, but that's how it is
Maybe we should document it? | data duplicate when setting num_works > 1 with streaming data | ## Describe the bug
The data is repeated num_works times when we load_dataset with streaming and set num_works > 1 when construct dataloader
## Steps to reproduce the bug
```python
# Sample code to reproduce the bug
import pandas as pd
import numpy as np
import os
from datasets import load_dataset
from tor... | 55 | data duplicate when setting num_works > 1 with streaming data
## Describe the bug
The data is repeated num_works times when we load_dataset with streaming and set num_works > 1 when construct dataloader
## Steps to reproduce the bug
```python
# Sample code to reproduce the bug
import pandas as pd
import numpy... | [
-0.23257632553577423,
-0.37529608607292175,
-0.01616865023970604,
0.3272431790828705,
0.2545713484287262,
-0.17621585726737976,
0.5691008567810059,
0.3358849883079529,
-0.2572707235813141,
0.42119985818862915,
0.09563610702753067,
0.20091485977172852,
-0.008096165955066681,
0.1235201060771... |
https://github.com/huggingface/datasets/issues/3423 | hmm actually let me open a new issue on DDP - original post was for single node | data duplicate when setting num_works > 1 with streaming data | ## Describe the bug
The data is repeated num_works times when we load_dataset with streaming and set num_works > 1 when construct dataloader
## Steps to reproduce the bug
```python
# Sample code to reproduce the bug
import pandas as pd
import numpy as np
import os
from datasets import load_dataset
from tor... | 17 | data duplicate when setting num_works > 1 with streaming data
## Describe the bug
The data is repeated num_works times when we load_dataset with streaming and set num_works > 1 when construct dataloader
## Steps to reproduce the bug
```python
# Sample code to reproduce the bug
import pandas as pd
import numpy... | [
-0.23257632553577423,
-0.37529608607292175,
-0.01616865023970604,
0.3272431790828705,
0.2545713484287262,
-0.17621585726737976,
0.5691008567810059,
0.3358849883079529,
-0.2572707235813141,
0.42119985818862915,
0.09563610702753067,
0.20091485977172852,
-0.008096165955066681,
0.1235201060771... |
https://github.com/huggingface/datasets/issues/3422 | Hi ! I wasn't able to reproduce your error.
Can you try to clear your cache at `~/.cache/huggingface/modules` and try again ? | Error about load_metric | ## Describe the bug
File "/opt/conda/lib/python3.8/site-packages/datasets/load.py", line 1371, in load_metric
metric = metric_cls(
TypeError: 'NoneType' object is not callable
## Steps to reproduce the bug
```python
metric = load_metric("glue", "sst2")
```
## Environment info
- `datasets` version: ... | 22 | Error about load_metric
## Describe the bug
File "/opt/conda/lib/python3.8/site-packages/datasets/load.py", line 1371, in load_metric
metric = metric_cls(
TypeError: 'NoneType' object is not callable
## Steps to reproduce the bug
```python
metric = load_metric("glue", "sst2")
```
## Environment in... | [
-0.15431877970695496,
-0.36345332860946655,
0.009982027113437653,
0.3949093818664551,
0.47802817821502686,
-0.007649742066860199,
0.18259713053703308,
0.18992000818252563,
0.1398090422153473,
0.12646666169166565,
-0.2365792691707611,
0.07038502395153046,
0.03904847800731659,
0.269751876592... |
https://github.com/huggingface/datasets/issues/3419 | Hi ! It's slower indeed because a datasets on which `select`/`shard`/`train_test_split`/`shuffle` has been called has to do additional steps to retrieve the data of the dataset table in the right order.
Indeed, if you call `dataset.select([0, 5, 10])`, the underlying table of the dataset is not altered to keep the e... | `.to_json` is extremely slow after `.select` | ## Describe the bug
Saving a dataset to JSON with `to_json` is extremely slow after using `.select` on the original dataset.
## Steps to reproduce the bug
```python
from datasets import load_dataset
original = load_dataset("squad", split="train")
original.to_json("from_original.json") # Takes 0 seconds
se... | 208 | `.to_json` is extremely slow after `.select`
## Describe the bug
Saving a dataset to JSON with `to_json` is extremely slow after using `.select` on the original dataset.
## Steps to reproduce the bug
```python
from datasets import load_dataset
original = load_dataset("squad", split="train")
original.to_json... | [
-0.31343477964401245,
0.18875038623809814,
-0.061073221266269684,
-0.06519970297813416,
0.2008448839187622,
0.07442190498113632,
0.08423752337694168,
0.4034845232963562,
-0.2616819739341736,
0.21372488141059875,
0.006462715566158295,
0.706722617149353,
-0.007227765396237373,
-0.03520082309... |
https://github.com/huggingface/datasets/issues/3419 | Hi, thanks for the response!
I still don't understand why it is so much slower than iterating and saving:
```python
from datasets import load_dataset
original = load_dataset("squad", split="train")
original.to_json("from_original.json") # Takes 0 seconds
selected_subset1 = original.select([i for i in range(l... | `.to_json` is extremely slow after `.select` | ## Describe the bug
Saving a dataset to JSON with `to_json` is extremely slow after using `.select` on the original dataset.
## Steps to reproduce the bug
```python
from datasets import load_dataset
original = load_dataset("squad", split="train")
original.to_json("from_original.json") # Takes 0 seconds
se... | 157 | `.to_json` is extremely slow after `.select`
## Describe the bug
Saving a dataset to JSON with `to_json` is extremely slow after using `.select` on the original dataset.
## Steps to reproduce the bug
```python
from datasets import load_dataset
original = load_dataset("squad", split="train")
original.to_json... | [
-0.1415250450372696,
0.05719663202762604,
-0.07221802324056625,
0.06819890439510345,
0.13612467050552368,
0.219497412443161,
0.04674702510237694,
0.3875997066497803,
-0.22740207612514496,
0.09003861993551254,
0.024286948144435883,
0.5975733995437622,
0.10359574854373932,
-0.005102731287479... |
https://github.com/huggingface/datasets/issues/3419 | There are slight differences between what you're doing and what `to_json` is actually doing.
In particular `to_json` currently converts batches of rows (as an arrow table) to a pandas dataframe, and then to JSON Lines. From your benchmark it looks like it's faster if we don't use pandas.
Thanks for investigating, I... | `.to_json` is extremely slow after `.select` | ## Describe the bug
Saving a dataset to JSON with `to_json` is extremely slow after using `.select` on the original dataset.
## Steps to reproduce the bug
```python
from datasets import load_dataset
original = load_dataset("squad", split="train")
original.to_json("from_original.json") # Takes 0 seconds
se... | 62 | `.to_json` is extremely slow after `.select`
## Describe the bug
Saving a dataset to JSON with `to_json` is extremely slow after using `.select` on the original dataset.
## Steps to reproduce the bug
```python
from datasets import load_dataset
original = load_dataset("squad", split="train")
original.to_json... | [
-0.2503957748413086,
0.23780295252799988,
-0.12493850290775299,
-0.17131173610687256,
0.1673326939344406,
0.04350423067808151,
0.06358066201210022,
0.6106274724006653,
-0.22180931270122528,
0.09391727298498154,
-0.021422898396849632,
0.6983179450035095,
0.07077737897634506,
-0.079195939004... |
https://github.com/huggingface/datasets/issues/3419 | Thanks for your observations, @eladsegal! I spent some time with this and tried different approaches. Turns out that https://github.com/huggingface/datasets/blob/bb13373637b1acc55f8a468a8927a56cf4732230/src/datasets/io/json.py#L100 is giving the problem when we use `to_json` after `select`. This is when `indices` param... | `.to_json` is extremely slow after `.select` | ## Describe the bug
Saving a dataset to JSON with `to_json` is extremely slow after using `.select` on the original dataset.
## Steps to reproduce the bug
```python
from datasets import load_dataset
original = load_dataset("squad", split="train")
original.to_json("from_original.json") # Takes 0 seconds
se... | 100 | `.to_json` is extremely slow after `.select`
## Describe the bug
Saving a dataset to JSON with `to_json` is extremely slow after using `.select` on the original dataset.
## Steps to reproduce the bug
```python
from datasets import load_dataset
original = load_dataset("squad", split="train")
original.to_json... | [
-0.22121639549732208,
0.10272455215454102,
-0.018625926226377487,
0.11876051127910614,
0.2550521492958069,
0.12812364101409912,
-0.0699116513133049,
0.4468904733657837,
-0.1404295265674591,
0.07427750527858734,
-0.0600852444767952,
0.7489500641822815,
0.12893103063106537,
0.048108503222465... |
https://github.com/huggingface/datasets/issues/3419 | Posting it in @eladsegal's format:
For `squad`:
Saving examples using current `to_json` in 3.63 secs
Saving examples to `from_select1_fast.json` in 5.00 secs
Saving examples to `from_select2_fast.json` in 2.45 secs
Saving examples to `from_select3_fast.json` in 2.50 secs
For `squad_v2`:
Saving examples using... | `.to_json` is extremely slow after `.select` | ## Describe the bug
Saving a dataset to JSON with `to_json` is extremely slow after using `.select` on the original dataset.
## Steps to reproduce the bug
```python
from datasets import load_dataset
original = load_dataset("squad", split="train")
original.to_json("from_original.json") # Takes 0 seconds
se... | 67 | `.to_json` is extremely slow after `.select`
## Describe the bug
Saving a dataset to JSON with `to_json` is extremely slow after using `.select` on the original dataset.
## Steps to reproduce the bug
```python
from datasets import load_dataset
original = load_dataset("squad", split="train")
original.to_json... | [
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0.08594490587711334,
0.061780937016010284,
0.6600292325019836,
0.05252547189593315,
0.0195460841059... |
https://github.com/huggingface/datasets/issues/3416 | Hi, thanks for reporting! This is a duplicate of https://github.com/huggingface/datasets/issues/3240. We are working on a fix.
| disaster_response_messages unavailable | ## Dataset viewer issue for '* disaster_response_messages*'
**Link:** https://huggingface.co/datasets/disaster_response_messages
Dataset unavailable. Link dead: https://datasets.appen.com/appen_datasets/disaster_response_data/disaster_response_messages_training.csv
Am I the one who added this dataset ?No
| 16 | disaster_response_messages unavailable
## Dataset viewer issue for '* disaster_response_messages*'
**Link:** https://huggingface.co/datasets/disaster_response_messages
Dataset unavailable. Link dead: https://datasets.appen.com/appen_datasets/disaster_response_data/disaster_response_messages_training.csv
Am I... | [
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0.072873793... |
https://github.com/huggingface/datasets/issues/3415 | I think it might come from two different issues:
1. Google Drive is an unreliable host, mainly because of quota limitations
2. the staging environment can sometimes raise some errors
For Google Drive tests we could set up some retries with backup URLs if necessary I guess.
For staging on the other hand, I guess w... | Non-deterministic tests: CI tests randomly fail | ## Describe the bug
Some CI tests fail randomly.
1. In https://github.com/huggingface/datasets/pull/3375/commits/c10275fe36085601cb7bdb9daee9a8f1fc734f48, there were 3 failing tests, only on Linux:
```
=========================== short test summary info ============================
FAILED tests/test_str... | 67 | Non-deterministic tests: CI tests randomly fail
## Describe the bug
Some CI tests fail randomly.
1. In https://github.com/huggingface/datasets/pull/3375/commits/c10275fe36085601cb7bdb9daee9a8f1fc734f48, there were 3 failing tests, only on Linux:
```
=========================== short test summary info ====... | [
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0.5563316345214844,
0.13679195940494537,
0.04703116789460182,
-0.16941094398498535,
0.34884378314... |
https://github.com/huggingface/datasets/issues/3401 | As we are planning to stop using Apache Beam (our `datasets.BeamBasedBuilder`) for the generation of some datasets (including [Wikipedia](https://huggingface.co/datasets/wikipedia/blob/main/wikipedia.py)), I have been working on [wikimedia/wikipedia](https://huggingface.co/datasets/wikimedia/wikipedia) to:
- Port the ... | Add Wikimedia pre-processed datasets | ## Adding a Dataset
- **Name:** Add pre-processed data to:
- *wikimedia/wikipedia*: https://huggingface.co/datasets/wikimedia/wikipedia
- *wikimedia/wikisource*: https://huggingface.co/datasets/wikimedia/wikisource
- **Description:** Add pre-processed data to the Hub for all languages
- **Paper:** *link to the... | 147 | Add Wikimedia pre-processed datasets
## Adding a Dataset
- **Name:** Add pre-processed data to:
- *wikimedia/wikipedia*: https://huggingface.co/datasets/wikimedia/wikipedia
- *wikimedia/wikisource*: https://huggingface.co/datasets/wikimedia/wikisource
- **Description:** Add pre-processed data to the Hub for a... | [
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0.13329853117465973,
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0.229402095079422,
0.23470158874988556,
0.4406098425388336,
0.2088828831911087,
0.02009986713528633,
-0.0057893916964530945,
0.1950497329235077,
-0.05611912161111832,
-0.12095195055... |
https://github.com/huggingface/datasets/issues/3400 | Thanks! See https://public.paws.wmcloud.org/User:Isaac_(WMF)/HuggingFace%20Wikipedia%20Processing.ipynb for more implementation details / some data around the overhead induced by adding the extra preprocessing steps (stripping link prefixes and magic words) | Improve Wikipedia loading script | As reported by @geohci, the "wikipedia" processing/loading script could be improved by some additional small suggested processing functions:
- _extract_content(filepath):
- Replace .startswith("#redirect") with more structured approach: if elem.find(f"./{namespace}redirect") is None: continue
- _parse_and_clean_wi... | 26 | Improve Wikipedia loading script
As reported by @geohci, the "wikipedia" processing/loading script could be improved by some additional small suggested processing functions:
- _extract_content(filepath):
- Replace .startswith("#redirect") with more structured approach: if elem.find(f"./{namespace}redirect") is No... | [
0.1939675211906433,
0.015728041529655457,
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0.011372409760951996,
0.19966720044612885,
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0.0286976620554924,
0.08133377134799957,
0.17222341895103455,
-0.0693216547... |
https://github.com/huggingface/datasets/issues/3398 | @geohci, I think the field "url" does not appear in the Wikimedia dumps. Therefore I guess we should generate it, using the "title" field and making some transformation of it (replacing spaces with underscores) and prepending the domain (created using the language)? | Add URL field to Wikimedia dataset instances: wikipedia,... | As reported by @geohci, in order to host pre-processed data in the Hub, we should add the full URL to data instances (new field "url"), so that we conform to proper attribution from license requirement. See, e.g.: https://fair-trec.github.io/docs/Fair_Ranking_2021_Participant_Instructions.pdf#subsection.3.2
This sho... | 42 | Add URL field to Wikimedia dataset instances: wikipedia,...
As reported by @geohci, in order to host pre-processed data in the Hub, we should add the full URL to data instances (new field "url"), so that we conform to proper attribution from license requirement. See, e.g.: https://fair-trec.github.io/docs/Fair_Rankin... | [
0.15710464119911194,
0.2313973307609558,
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0.16111738979816437,
0.12875989079475403,
0.39922481775283813,
0.24277612566947937,
-0.0161259323358... |
https://github.com/huggingface/datasets/issues/3398 | Indeed:
> To re-distribute text on Wikipedia in any form, provide credit to the authors either by including a) a [hyperlink](https://en.wikipedia.org/wiki/Hyperlink) (where possible) or [URL](https://en.wikipedia.org/wiki/URL) to the page or pages you are re-using, b) a hyperlink (where possible) or URL to an altern... | Add URL field to Wikimedia dataset instances: wikipedia,... | As reported by @geohci, in order to host pre-processed data in the Hub, we should add the full URL to data instances (new field "url"), so that we conform to proper attribution from license requirement. See, e.g.: https://fair-trec.github.io/docs/Fair_Ranking_2021_Participant_Instructions.pdf#subsection.3.2
This sho... | 190 | Add URL field to Wikimedia dataset instances: wikipedia,...
As reported by @geohci, in order to host pre-processed data in the Hub, we should add the full URL to data instances (new field "url"), so that we conform to proper attribution from license requirement. See, e.g.: https://fair-trec.github.io/docs/Fair_Rankin... | [
0.1469033807516098,
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0.5451570153236389,
0.32937437295913696,
-0.03478521481156... |
https://github.com/huggingface/datasets/issues/3398 | yep, sorry forgot that that wasn't already in the dumps. specifically `f"https://{language}.wikipedia.org/wiki/{title.replace(' ', '_')}` should do it | Add URL field to Wikimedia dataset instances: wikipedia,... | As reported by @geohci, in order to host pre-processed data in the Hub, we should add the full URL to data instances (new field "url"), so that we conform to proper attribution from license requirement. See, e.g.: https://fair-trec.github.io/docs/Fair_Ranking_2021_Participant_Instructions.pdf#subsection.3.2
This sho... | 17 | Add URL field to Wikimedia dataset instances: wikipedia,...
As reported by @geohci, in order to host pre-processed data in the Hub, we should add the full URL to data instances (new field "url"), so that we conform to proper attribution from license requirement. See, e.g.: https://fair-trec.github.io/docs/Fair_Rankin... | [
0.1569751501083374,
0.1533060371875763,
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0.3304098844528198,
-0.0482819825410842... |
https://github.com/huggingface/datasets/issues/3398 | Thanks @geohci.
I had already been looking for information about the conversion from title to URL and I found that apart from replacing blanks with underscores, some other special character must also be percent-encoded (e.g. `"` to `%22`): https://meta.wikimedia.org/wiki/Help:URL
Therefore, I have finally used `u... | Add URL field to Wikimedia dataset instances: wikipedia,... | As reported by @geohci, in order to host pre-processed data in the Hub, we should add the full URL to data instances (new field "url"), so that we conform to proper attribution from license requirement. See, e.g.: https://fair-trec.github.io/docs/Fair_Ranking_2021_Participant_Instructions.pdf#subsection.3.2
This sho... | 123 | Add URL field to Wikimedia dataset instances: wikipedia,...
As reported by @geohci, in order to host pre-processed data in the Hub, we should add the full URL to data instances (new field "url"), so that we conform to proper attribution from license requirement. See, e.g.: https://fair-trec.github.io/docs/Fair_Rankin... | [
0.234003484249115,
0.20187413692474365,
0.0728769302368164,
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0.19741375744342804,
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0.15331652760505676,
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0.6567928194999695,
0.24751237034797668,
-0.083240114152431... |
https://github.com/huggingface/datasets/issues/3396 | https://huggingface.co/datasets/projecte-aina/parlament_parla -> works (but we still have to show an audio player)
https://huggingface.co/datasets/openslr -> another issue: `Message: [Errno 2] No such file or directory: '/home/hf/datasets-preview-backend/zip:/asr_javanese/data/00/00004fe6aa.flac'` | Install Audio dependencies to support audio decoding | ## Dataset viewer issue for '*openslr*', '*projecte-aina/parlament_parla*'
**Link:** *https://huggingface.co/datasets/openslr*
**Link:** *https://huggingface.co/datasets/projecte-aina/parlament_parla*
Error:
```
Status code: 400
Exception: ImportError
Message: To support decoding audio files, ple... | 25 | Install Audio dependencies to support audio decoding
## Dataset viewer issue for '*openslr*', '*projecte-aina/parlament_parla*'
**Link:** *https://huggingface.co/datasets/openslr*
**Link:** *https://huggingface.co/datasets/projecte-aina/parlament_parla*
Error:
```
Status code: 400
Exception: ImportErr... | [
-0.2341924011707306,
0.08295610547065735,
-0.12282148748636246,
0.2838069498538971,
0.1610812246799469,
0.01638239622116089,
-0.07111437618732452,
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0.22932499647140503,
-0.39680296182632446,
0.37558513879776,
-0.04069862142205238,
0.046440064907073... |
https://github.com/huggingface/datasets/issues/3396 | But https://huggingface.co/datasets/openslr/viewer does not work
<img width="678" alt="Capture d’écran 2022-04-12 à 13 59 46" src="https://user-images.githubusercontent.com/1676121/162958013-e31ef2ae-f886-47b7-9f27-664ed3d4b5a1.png">
Same issue as #4126:
```
Status code: 400
Exception: TypeError
Mes... | Install Audio dependencies to support audio decoding | ## Dataset viewer issue for '*openslr*', '*projecte-aina/parlament_parla*'
**Link:** *https://huggingface.co/datasets/openslr*
**Link:** *https://huggingface.co/datasets/projecte-aina/parlament_parla*
Error:
```
Status code: 400
Exception: ImportError
Message: To support decoding audio files, ple... | 34 | Install Audio dependencies to support audio decoding
## Dataset viewer issue for '*openslr*', '*projecte-aina/parlament_parla*'
**Link:** *https://huggingface.co/datasets/openslr*
**Link:** *https://huggingface.co/datasets/projecte-aina/parlament_parla*
Error:
```
Status code: 400
Exception: ImportErr... | [
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0.071923077... |
https://github.com/huggingface/datasets/issues/3394 | According to this [comment in the forum](https://discuss.huggingface.co/t/save-datasetdict-to-huggingface-hub/12075/8?u=lhoestq), using `push_to_hub` on a dataset with `ClassLabel` can also make the feature simply disappear when it's reloaded ! | Preserve all feature types when saving a dataset on the Hub with `push_to_hub` | Currently, if one of the dataset features is of type `ClassLabel`, saving the dataset with `push_to_hub` and reloading the dataset with `load_dataset` will return the feature of type `Value`. To fix this, we should do something similar to `save_to_disk` (which correctly preserves the types) and not only push the parque... | 25 | Preserve all feature types when saving a dataset on the Hub with `push_to_hub`
Currently, if one of the dataset features is of type `ClassLabel`, saving the dataset with `push_to_hub` and reloading the dataset with `load_dataset` will return the feature of type `Value`. To fix this, we should do something similar to ... | [
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https://github.com/huggingface/datasets/issues/3394 | Maybe we can also fix https://github.com/huggingface/datasets/issues/3035 while working on this because, as pointed out in my initial post, `save_to_disk` also saves the `dataset_info.json` file. | Preserve all feature types when saving a dataset on the Hub with `push_to_hub` | Currently, if one of the dataset features is of type `ClassLabel`, saving the dataset with `push_to_hub` and reloading the dataset with `load_dataset` will return the feature of type `Value`. To fix this, we should do something similar to `save_to_disk` (which correctly preserves the types) and not only push the parque... | 24 | Preserve all feature types when saving a dataset on the Hub with `push_to_hub`
Currently, if one of the dataset features is of type `ClassLabel`, saving the dataset with `push_to_hub` and reloading the dataset with `load_dataset` will return the feature of type `Value`. To fix this, we should do something similar to ... | [
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0.62115973234176... |
https://github.com/huggingface/datasets/issues/3392 | This issue was fixed by me calling `all_datasets.push_to_hub("hackernews_hiring_posts")`.
The previous problems were from calling `all_datasets.save_to_disk` and then pushing with `my_repo.git_add` and `my_repo.push_to_hub`.
| Dataset viewer issue for `dansbecker/hackernews_hiring_posts` | ## Dataset viewer issue for `dansbecker/hackernews_hiring_posts`
**Link:** https://huggingface.co/datasets/dansbecker/hackernews_hiring_posts
*short description of the issue*
Dataset preview not showing for uploaded DatasetDict. See https://discuss.huggingface.co/t/dataset-preview-not-showing-for-uploaded-data... | 22 | Dataset viewer issue for `dansbecker/hackernews_hiring_posts`
## Dataset viewer issue for `dansbecker/hackernews_hiring_posts`
**Link:** https://huggingface.co/datasets/dansbecker/hackernews_hiring_posts
*short description of the issue*
Dataset preview not showing for uploaded DatasetDict. See https://discus... | [
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0.076242178... |
https://github.com/huggingface/datasets/issues/3389 | Datasets are not tracked in this repository anymore. But you can make your own dataset in the huggingface hub | Add EDGAR | ## Adding a Dataset
- **Name:** EDGAR Database
- **Description:** https://www.sec.gov/edgar/about EDGAR, the Electronic Data Gathering, Analysis, and Retrieval system, is the primary system for companies and others submitting documents under the Securities Act of 1933, the Securities Exchange Act of 1934, the Trust I... | 19 | Add EDGAR
## Adding a Dataset
- **Name:** EDGAR Database
- **Description:** https://www.sec.gov/edgar/about EDGAR, the Electronic Data Gathering, Analysis, and Retrieval system, is the primary system for companies and others submitting documents under the Securities Act of 1933, the Securities Exchange Act of 1934,... | [
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0.41698297858... |
https://github.com/huggingface/datasets/issues/3385 | Hi ! Thanks for the suggestion :)
It makes sense to me, and it can surely be implemented by wrapping the user's function to make it a batched function. However I'm not a big fan of the inconsistency it would create with `map`: `with_transform` is batched by default while `map` isn't.
Is there something you would li... | None batched `with_transform`, `set_transform` | **Is your feature request related to a problem? Please describe.**
A `torch.utils.data.Dataset.__getitem__` operates on a single example.
But 🤗 `Datasets.with_transform` doesn't seem to allow non-batched transform.
**Describe the solution you'd like**
Have a `batched=True` argument in `Datasets.with_transfor... | 69 | None batched `with_transform`, `set_transform`
**Is your feature request related to a problem? Please describe.**
A `torch.utils.data.Dataset.__getitem__` operates on a single example.
But 🤗 `Datasets.with_transform` doesn't seem to allow non-batched transform.
**Describe the solution you'd like**
Have a `... | [
-0.4295310378074646,
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-0.26388627290... |
https://github.com/huggingface/datasets/issues/3385 | Hi @lhoestq ,
Sorry I missed your reply.
I would love to contribute. But I don't know which solution would be the best for this repo.
> However I'm not a big fan of the inconsistency it would create with map: with_transform is batched by default while map isn't.
I agree. What do you think about the alternativ... | None batched `with_transform`, `set_transform` | **Is your feature request related to a problem? Please describe.**
A `torch.utils.data.Dataset.__getitem__` operates on a single example.
But 🤗 `Datasets.with_transform` doesn't seem to allow non-batched transform.
**Describe the solution you'd like**
Have a `batched=True` argument in `Datasets.with_transfor... | 315 | None batched `with_transform`, `set_transform`
**Is your feature request related to a problem? Please describe.**
A `torch.utils.data.Dataset.__getitem__` operates on a single example.
But 🤗 `Datasets.with_transform` doesn't seem to allow non-batched transform.
**Describe the solution you'd like**
Have a `... | [
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0.6519105434417725,
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-0.3571738600... |
https://github.com/huggingface/datasets/issues/3385 | I like the idea of lazy map. On the other hand we should only have either lazy map or `with_transform` (not both). That's why I'd rather stick with `with_transform` for now (but maybe we can consider it for later major releases like `datasets` v2).
I understand the issue with `with_transform` and `with_format` being... | None batched `with_transform`, `set_transform` | **Is your feature request related to a problem? Please describe.**
A `torch.utils.data.Dataset.__getitem__` operates on a single example.
But 🤗 `Datasets.with_transform` doesn't seem to allow non-batched transform.
**Describe the solution you'd like**
Have a `batched=True` argument in `Datasets.with_transfor... | 83 | None batched `with_transform`, `set_transform`
**Is your feature request related to a problem? Please describe.**
A `torch.utils.data.Dataset.__getitem__` operates on a single example.
But 🤗 `Datasets.with_transform` doesn't seem to allow non-batched transform.
**Describe the solution you'd like**
Have a `... | [
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0.4868512451648712,
0.40934205055236816,
-0.1548076868057251,
-0.0003176778554916382,
-0.11382850259542465,
0.5173218250274658,
-0.35309773683547974,
-0.102649271... |
https://github.com/huggingface/datasets/issues/3381 | Hi ! Feel free to access `batch["audio"]["array"]` and `batch["audio"]["sampling_rate"]` instead
`datasets` 1.16 introduced some changes in `common_voice` and now the `path` field is no longer a path to a local file (but rather the path to the file in the archive it's extracted from) | Unable to load audio_features from common_voice dataset | ## Describe the bug
I am not able to load audio features from common_voice dataset
## Steps to reproduce the bug
```
from datasets import load_dataset
import torchaudio
test_dataset = load_dataset("common_voice", "hi", split="test[:2%]")
resampler = torchaudio.transforms.Resample(48_000, 16_000)
def spe... | 44 | Unable to load audio_features from common_voice dataset
## Describe the bug
I am not able to load audio features from common_voice dataset
## Steps to reproduce the bug
```
from datasets import load_dataset
import torchaudio
test_dataset = load_dataset("common_voice", "hi", split="test[:2%]")
resampler =... | [
-0.27756547927856445,
-0.37769925594329834,
-0.008247319608926773,
0.42916175723075867,
0.3689376413822174,
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0.25374141335487366,
0.23593676090240479,
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0.15663424134254456,
-0.4660596251487732,
0.40844666957855225,
-0.09263080358505249,
-0.19938179... |
https://github.com/huggingface/datasets/issues/3374 | Seems like the issue still exists,:
`Downloading and preparing dataset clue/chid (download: 127.15 MiB, generated: 259.71 MiB, post-processed: Unknown size, total: 386.86 MiB) to /mnt/cache/tanhaochen/.cache/huggingface/datasets/clue/chid/1.0.0/e55b490cb7809dcd8db31b9a87119f2e2ec87cdc060da8a9ac070b070ca3e379...
Trace... | NonMatchingChecksumError for the CLUE:cluewsc2020, chid, c3 and tnews | Hi, it seems like there are updates in cluewsc2020, chid, c3 and tnews, since i could not load them due to the checksum error. | 80 | NonMatchingChecksumError for the CLUE:cluewsc2020, chid, c3 and tnews
Hi, it seems like there are updates in cluewsc2020, chid, c3 and tnews, since i could not load them due to the checksum error.
Seems like the issue still exists,:
`Downloading and preparing dataset clue/chid (download: 127.15 MiB, generated: 259... | [
0.020523637533187866,
0.02955728769302368,
-0.039549678564071655,
0.08444855362176895,
0.09496402740478516,
-0.019827909767627716,
0.0076568047516047955,
0.3946431875228882,
-0.026205506175756454,
0.25921374559402466,
-0.1515904814004898,
0.19831843674182892,
0.048418134450912476,
-0.03982... |
https://github.com/huggingface/datasets/issues/3369 | This requires implementing `cast_column` for iterable datasets, it could be a very nice addition !
<s>It can also be useful to be able to disable the audio/image decoding for the dataset viewer (see PR https://github.com/huggingface/datasets/pull/3430) cc @severo </s>
EDIT: actually following https://github.com/hug... | [Audio] Allow resampling for audio datasets in streaming mode | Many audio datasets like Common Voice always need to be resampled. This can very easily be done in non-streaming mode as follows:
```python
from datasets import load_dataset
ds = load_dataset("common_voice", "ab", split="test")
ds = ds.cast_column("audio", Audio(sampling_rate=16_000))
```
However in strea... | 50 | [Audio] Allow resampling for audio datasets in streaming mode
Many audio datasets like Common Voice always need to be resampled. This can very easily be done in non-streaming mode as follows:
```python
from datasets import load_dataset
ds = load_dataset("common_voice", "ab", split="test")
ds = ds.cast_colum... | [
-0.5598964095115662,
-0.03991022706031799,
-0.0683555006980896,
-0.14066046476364136,
0.4281198978424072,
0.07942812144756317,
-0.019700035452842712,
0.30219918489456177,
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0.3280913233757019,
-0.49382615089416504,
0.29272326827049255,
-0.2910313010215759,
0.23124691843... |
https://github.com/huggingface/datasets/issues/3369 | Just to clarify a bit. This feature is **always** needed when using the common voice dataset in streaming mode. So I think it's quite important | [Audio] Allow resampling for audio datasets in streaming mode | Many audio datasets like Common Voice always need to be resampled. This can very easily be done in non-streaming mode as follows:
```python
from datasets import load_dataset
ds = load_dataset("common_voice", "ab", split="test")
ds = ds.cast_column("audio", Audio(sampling_rate=16_000))
```
However in strea... | 25 | [Audio] Allow resampling for audio datasets in streaming mode
Many audio datasets like Common Voice always need to be resampled. This can very easily be done in non-streaming mode as follows:
```python
from datasets import load_dataset
ds = load_dataset("common_voice", "ab", split="test")
ds = ds.cast_colum... | [
-0.6024314761161804,
-0.08081433176994324,
-0.04220091924071312,
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0.38061466813087463,
0.11277459561824799,
0.014463353902101517,
0.2519491910934448,
0.01380409300327301,
0.2485649585723877,
-0.38962453603744507,
0.1837809681892395,
-0.32103848457336426,
0.1334300637245... |
https://github.com/huggingface/datasets/issues/3365 | The Hub pulls these tags from [here](https://github.com/huggingface/hub-docs/blob/main/js/src/lib/interfaces/Types.ts) (allows multimodal tasks) now, so I'm closing this issue. | Add task tags for multimodal datasets | ## **Is your feature request related to a problem? Please describe.**
Currently, task tags are either exclusively related to text or speech processing:
- https://github.com/huggingface/datasets/blob/master/src/datasets/utils/resources/tasks.json
## **Describe the solution you'd like**
We should also add tasks... | 16 | Add task tags for multimodal datasets
## **Is your feature request related to a problem? Please describe.**
Currently, task tags are either exclusively related to text or speech processing:
- https://github.com/huggingface/datasets/blob/master/src/datasets/utils/resources/tasks.json
## **Describe the solution ... | [
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0.20397613942623138,
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0.3996905982494354,
0.17135125398635864,
0.13978563249111176,
0.19469952583312988,
-0.21250322461128235,
0.365987628698349,
-0.32299038767814636,
0.482997119426... |
https://github.com/huggingface/datasets/issues/3358 | Hi,
could you please post this question on our [Forum](https://discuss.huggingface.co/) as we keep issues for bugs and feature requests? | add new field, and get errors | after adding new field **tokenized_examples["example_id"]**, and get errors below,
I think it is due to changing data to tensor, and **tokenized_examples["example_id"]** is string list
**all fields**
```
***************** train_dataset 1: Dataset({
features: ['attention_mask', 'end_positions', 'example_id', '... | 19 | add new field, and get errors
after adding new field **tokenized_examples["example_id"]**, and get errors below,
I think it is due to changing data to tensor, and **tokenized_examples["example_id"]** is string list
**all fields**
```
***************** train_dataset 1: Dataset({
features: ['attention_mask', ... | [
0.044621869921684265,
-0.4576033353805542,
-0.05849689245223999,
0.21619057655334473,
0.3088058531284332,
0.22194132208824158,
0.5154498815536499,
0.3203383684158325,
-0.09049803018569946,
0.18905755877494812,
0.338534951210022,
-0.0441405326128006,
-0.09890826046466827,
0.1437216401100158... |
https://github.com/huggingface/datasets/issues/3358 | > Hi,
>
> could you please post this question on our [Forum](https://discuss.huggingface.co/) as we keep issues for bugs and feature requests?
ok. | add new field, and get errors | after adding new field **tokenized_examples["example_id"]**, and get errors below,
I think it is due to changing data to tensor, and **tokenized_examples["example_id"]** is string list
**all fields**
```
***************** train_dataset 1: Dataset({
features: ['attention_mask', 'end_positions', 'example_id', '... | 23 | add new field, and get errors
after adding new field **tokenized_examples["example_id"]**, and get errors below,
I think it is due to changing data to tensor, and **tokenized_examples["example_id"]** is string list
**all fields**
```
***************** train_dataset 1: Dataset({
features: ['attention_mask', ... | [
0.04946398735046387,
-0.45958444476127625,
-0.04163657873868942,
0.2271222174167633,
0.29889532923698425,
0.21765288710594177,
0.5312832593917847,
0.3263183534145355,
-0.10522152483463287,
0.19344790279865265,
0.3319588601589203,
-0.05348430573940277,
-0.09545042365789413,
0.14284709095954... |
https://github.com/huggingface/datasets/issues/3353 | Hi ! Your function looks fine, I used to map `squad` locally and it indeed added the `example_id` field correctly.
However I think that in the `compute_loss` method only a subset of the fields are available: the model inputs. Since `example_id` is not a model input (it's not passed as a parameter to the model), the ... | add one field "example_id", but I can't see it in the "comput_loss" function | Hi, I add one field **example_id**, but I can't see it in the **comput_loss** function, how can I do this? below is the information of inputs
```
*********************** inputs: {'attention_mask': tensor([[1, 1, 1, ..., 0, 0, 0],
[1, 1, 1, ..., 0, 0, 0],
[1, 1, 1, ..., 0, 0, 0],
...,
... | 118 | add one field "example_id", but I can't see it in the "comput_loss" function
Hi, I add one field **example_id**, but I can't see it in the **comput_loss** function, how can I do this? below is the information of inputs
```
*********************** inputs: {'attention_mask': tensor([[1, 1, 1, ..., 0, 0, 0],
... | [
-0.1465505063533783,
-0.5799239277839661,
-0.27407190203666687,
0.12024873495101929,
0.154510959982872,
0.02435808628797531,
0.5186564326286316,
0.1191994845867157,
0.2118411660194397,
0.46522027254104614,
0.3532586693763733,
0.3118034303188324,
0.20097029209136963,
-0.12374438345432281,
... |
https://github.com/huggingface/datasets/issues/3353 | Hi, I have set **args.remove_unused_columns=False** and **training_args.remove_unused_columns=False**, but the field doesn't been contained yet.
```
def main():
argp = HfArgumentParser(TrainingArguments)
# The HfArgumentParser object collects command-line arguments into an object (and provides default valu... | add one field "example_id", but I can't see it in the "comput_loss" function | Hi, I add one field **example_id**, but I can't see it in the **comput_loss** function, how can I do this? below is the information of inputs
```
*********************** inputs: {'attention_mask': tensor([[1, 1, 1, ..., 0, 0, 0],
[1, 1, 1, ..., 0, 0, 0],
[1, 1, 1, ..., 0, 0, 0],
...,
... | 373 | add one field "example_id", but I can't see it in the "comput_loss" function
Hi, I add one field **example_id**, but I can't see it in the **comput_loss** function, how can I do this? below is the information of inputs
```
*********************** inputs: {'attention_mask': tensor([[1, 1, 1, ..., 0, 0, 0],
... | [
-0.1465505063533783,
-0.5799239277839661,
-0.27407190203666687,
0.12024873495101929,
0.154510959982872,
0.02435808628797531,
0.5186564326286316,
0.1191994845867157,
0.2118411660194397,
0.46522027254104614,
0.3532586693763733,
0.3118034303188324,
0.20097029209136963,
-0.12374438345432281,
... |
https://github.com/huggingface/datasets/issues/3353 | Hi, I print the value, all are set to False, but don't work.
```
********************* training_args: TrainingArguments(
_n_gpu=1,
adafactor=False,
adam_beta1=0.9,
adam_beta2=0.999,
adam_epsilon=1e-08,
dataloader_drop_last=False,
dataloader_num_workers=0,
dataloader_pin_memory=True,
ddp_find_unused_parameter... | add one field "example_id", but I can't see it in the "comput_loss" function | Hi, I add one field **example_id**, but I can't see it in the **comput_loss** function, how can I do this? below is the information of inputs
```
*********************** inputs: {'attention_mask': tensor([[1, 1, 1, ..., 0, 0, 0],
[1, 1, 1, ..., 0, 0, 0],
[1, 1, 1, ..., 0, 0, 0],
...,
... | 247 | add one field "example_id", but I can't see it in the "comput_loss" function
Hi, I add one field **example_id**, but I can't see it in the **comput_loss** function, how can I do this? below is the information of inputs
```
*********************** inputs: {'attention_mask': tensor([[1, 1, 1, ..., 0, 0, 0],
... | [
-0.1465505063533783,
-0.5799239277839661,
-0.27407190203666687,
0.12024873495101929,
0.154510959982872,
0.02435808628797531,
0.5186564326286316,
0.1191994845867157,
0.2118411660194397,
0.46522027254104614,
0.3532586693763733,
0.3118034303188324,
0.20097029209136963,
-0.12374438345432281,
... |
https://github.com/huggingface/datasets/issues/3353 | Hmmm, it might be because the default data collator removes all the fields with `string` type:
https://github.com/huggingface/transformers/blob/4c0dd199c8305903564c2edeae23d294edd4b321/src/transformers/data/data_collator.py#L107-L112
I guess you also need a custom data collator that doesn't remove them. | add one field "example_id", but I can't see it in the "comput_loss" function | Hi, I add one field **example_id**, but I can't see it in the **comput_loss** function, how can I do this? below is the information of inputs
```
*********************** inputs: {'attention_mask': tensor([[1, 1, 1, ..., 0, 0, 0],
[1, 1, 1, ..., 0, 0, 0],
[1, 1, 1, ..., 0, 0, 0],
...,
... | 30 | add one field "example_id", but I can't see it in the "comput_loss" function
Hi, I add one field **example_id**, but I can't see it in the **comput_loss** function, how can I do this? below is the information of inputs
```
*********************** inputs: {'attention_mask': tensor([[1, 1, 1, ..., 0, 0, 0],
... | [
-0.1465505063533783,
-0.5799239277839661,
-0.27407190203666687,
0.12024873495101929,
0.154510959982872,
0.02435808628797531,
0.5186564326286316,
0.1191994845867157,
0.2118411660194397,
0.46522027254104614,
0.3532586693763733,
0.3118034303188324,
0.20097029209136963,
-0.12374438345432281,
... |
https://github.com/huggingface/datasets/issues/3353 | I overwrite **get_train_dataloader**, and remove **_remove_unused_columns**, but it doesn't work.
```
def get_train_dataloader(self) -> DataLoader:
"""
Returns the training :class:`~torch.utils.data.DataLoader`.
Will use no sampler if :obj:`self.train_dataset` does not implement :ob... | add one field "example_id", but I can't see it in the "comput_loss" function | Hi, I add one field **example_id**, but I can't see it in the **comput_loss** function, how can I do this? below is the information of inputs
```
*********************** inputs: {'attention_mask': tensor([[1, 1, 1, ..., 0, 0, 0],
[1, 1, 1, ..., 0, 0, 0],
[1, 1, 1, ..., 0, 0, 0],
...,
... | 116 | add one field "example_id", but I can't see it in the "comput_loss" function
Hi, I add one field **example_id**, but I can't see it in the **comput_loss** function, how can I do this? below is the information of inputs
```
*********************** inputs: {'attention_mask': tensor([[1, 1, 1, ..., 0, 0, 0],
... | [
-0.1465505063533783,
-0.5799239277839661,
-0.27407190203666687,
0.12024873495101929,
0.154510959982872,
0.02435808628797531,
0.5186564326286316,
0.1191994845867157,
0.2118411660194397,
0.46522027254104614,
0.3532586693763733,
0.3118034303188324,
0.20097029209136963,
-0.12374438345432281,
... |
https://github.com/huggingface/datasets/issues/3353 | Hi, it works now, thank you.
1. **args.remove_unused_columns=False** and **training_args.remove_unused_columns=False**
2. overwrite **get_train_dataloader**, and remove **_remove_unused_columns**
3. add new fields, and can be got in **inputs**. | add one field "example_id", but I can't see it in the "comput_loss" function | Hi, I add one field **example_id**, but I can't see it in the **comput_loss** function, how can I do this? below is the information of inputs
```
*********************** inputs: {'attention_mask': tensor([[1, 1, 1, ..., 0, 0, 0],
[1, 1, 1, ..., 0, 0, 0],
[1, 1, 1, ..., 0, 0, 0],
...,
... | 26 | add one field "example_id", but I can't see it in the "comput_loss" function
Hi, I add one field **example_id**, but I can't see it in the **comput_loss** function, how can I do this? below is the information of inputs
```
*********************** inputs: {'attention_mask': tensor([[1, 1, 1, ..., 0, 0, 0],
... | [
-0.1465505063533783,
-0.5799239277839661,
-0.27407190203666687,
0.12024873495101929,
0.154510959982872,
0.02435808628797531,
0.5186564326286316,
0.1191994845867157,
0.2118411660194397,
0.46522027254104614,
0.3532586693763733,
0.3118034303188324,
0.20097029209136963,
-0.12374438345432281,
... |
https://github.com/huggingface/datasets/issues/3346 | Actually, re-opening this issue cause the error persists
```python
>>> load_dataset("qed")
Downloading and preparing dataset qed/qed (download: 13.43 MiB, generated: 9.70 MiB, post-processed: Unknown size, total: 23.14 MiB) to /home/victor_huggingface_co/.cache/huggingface/datasets/qed/qed/1.0.0/47d8b6f033393aa520... | Failed to convert `string` with pyarrow for QED since 1.15.0 | ## Describe the bug
Loading QED was fine until 1.15.0.
related: bigscience-workshop/promptsource#659, bigscience-workshop/promptsource#670
Not sure where the root cause is, but here are some candidates:
- #3158
- #3120
- #3196
- #2891
## Steps to reproduce the bug
```python
load_dataset("qed")
```
## ... | 222 | Failed to convert `string` with pyarrow for QED since 1.15.0
## Describe the bug
Loading QED was fine until 1.15.0.
related: bigscience-workshop/promptsource#659, bigscience-workshop/promptsource#670
Not sure where the root cause is, but here are some candidates:
- #3158
- #3120
- #3196
- #2891
## Steps t... | [
-0.3966262936592102,
-0.029386982321739197,
-0.010125454515218735,
-0.025371462106704712,
0.4371274709701538,
-0.2806429862976074,
0.33867594599723816,
0.5561791658401489,
-0.4660201966762543,
0.31572645902633667,
0.04335818439722061,
0.49633562564849854,
-0.04443195462226868,
0.2531989514... |
https://github.com/huggingface/datasets/issues/3345 | Hi,
the dataset is downloaded normally on my machine. Maybe the URL was down at the time of your download. Could you try again? | Failed to download species_800 from Google Drive zip file | ## Describe the bug
One can manually download the zip file on Google Drive, but `load_dataset()` cannot.
related: #3248
## Steps to reproduce the bug
```shell
> python
Python 3.7.12 (default, Sep 5 2021, 08:34:29)
[Clang 11.0.3 (clang-1103.0.32.62)] on darwin
Type "help", "copyright", "credits" or "license" ... | 24 | Failed to download species_800 from Google Drive zip file
## Describe the bug
One can manually download the zip file on Google Drive, but `load_dataset()` cannot.
related: #3248
## Steps to reproduce the bug
```shell
> python
Python 3.7.12 (default, Sep 5 2021, 08:34:29)
[Clang 11.0.3 (clang-1103.0.32.62)] ... | [
-0.314179927110672,
-0.03847537934780121,
-0.04923107102513313,
0.20208537578582764,
0.16466934978961945,
0.161715567111969,
0.22587577998638153,
0.24758365750312805,
0.1551794707775116,
-0.010347917675971985,
-0.10637703537940979,
0.2193595916032791,
-0.018068544566631317,
0.2488588392734... |
https://github.com/huggingface/datasets/issues/3345 | > Hi,
>
> the dataset is downloaded normally on my machine. Maybe the URL was down at the time of your download. Could you try again?
I have tried that many times with both load_dataset() and a browser almost simultaneously. The browser always works for me while load_dataset() fails. | Failed to download species_800 from Google Drive zip file | ## Describe the bug
One can manually download the zip file on Google Drive, but `load_dataset()` cannot.
related: #3248
## Steps to reproduce the bug
```shell
> python
Python 3.7.12 (default, Sep 5 2021, 08:34:29)
[Clang 11.0.3 (clang-1103.0.32.62)] on darwin
Type "help", "copyright", "credits" or "license" ... | 50 | Failed to download species_800 from Google Drive zip file
## Describe the bug
One can manually download the zip file on Google Drive, but `load_dataset()` cannot.
related: #3248
## Steps to reproduce the bug
```shell
> python
Python 3.7.12 (default, Sep 5 2021, 08:34:29)
[Clang 11.0.3 (clang-1103.0.32.62)] ... | [
-0.314179927110672,
-0.03847537934780121,
-0.04923107102513313,
0.20208537578582764,
0.16466934978961945,
0.161715567111969,
0.22587577998638153,
0.24758365750312805,
0.1551794707775116,
-0.010347917675971985,
-0.10637703537940979,
0.2193595916032791,
-0.018068544566631317,
0.2488588392734... |
https://github.com/huggingface/datasets/issues/3345 | @mariosasko
> the dataset is downloaded normally on my machine. Maybe the URL was down at the time of your download. Could you try again?
I've tried yet again just a moment ago. This time I realize that, the step `(... post-processed: Unknown size, total: 20.89 MiB) to /Users/mike/.cache/huggingface/datasets/speci... | Failed to download species_800 from Google Drive zip file | ## Describe the bug
One can manually download the zip file on Google Drive, but `load_dataset()` cannot.
related: #3248
## Steps to reproduce the bug
```shell
> python
Python 3.7.12 (default, Sep 5 2021, 08:34:29)
[Clang 11.0.3 (clang-1103.0.32.62)] on darwin
Type "help", "copyright", "credits" or "license" ... | 102 | Failed to download species_800 from Google Drive zip file
## Describe the bug
One can manually download the zip file on Google Drive, but `load_dataset()` cannot.
related: #3248
## Steps to reproduce the bug
```shell
> python
Python 3.7.12 (default, Sep 5 2021, 08:34:29)
[Clang 11.0.3 (clang-1103.0.32.62)] ... | [
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0.2488588392734... |
https://github.com/huggingface/datasets/issues/3341 | I created a GitHub project to keep track of what needs to be done:
https://github.com/huggingface/datasets/projects/3
I also store my code in a (private for now) repository at https://github.com/huggingface/mirror_canonical_datasets_on_hub | Mirror the canonical datasets to the Hugging Face Hub | - [ ] create a repo on https://hf.co/datasets for every canonical dataset
- [ ] on every commit related to a dataset, update the hf.co repo
See https://github.com/huggingface/moon-landing/pull/1562
@SBrandeis: I let you edit this description if needed to precise the intent. | 28 | Mirror the canonical datasets to the Hugging Face Hub
- [ ] create a repo on https://hf.co/datasets for every canonical dataset
- [ ] on every commit related to a dataset, update the hf.co repo
See https://github.com/huggingface/moon-landing/pull/1562
@SBrandeis: I let you edit this description if needed to pr... | [
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0.4645622968... |
https://github.com/huggingface/datasets/issues/3341 | I understand that the datasets are mirrored on the Hub now, right? Might I close @lhoestq @SBrandeis? | Mirror the canonical datasets to the Hugging Face Hub | - [ ] create a repo on https://hf.co/datasets for every canonical dataset
- [ ] on every commit related to a dataset, update the hf.co repo
See https://github.com/huggingface/moon-landing/pull/1562
@SBrandeis: I let you edit this description if needed to precise the intent. | 17 | Mirror the canonical datasets to the Hugging Face Hub
- [ ] create a repo on https://hf.co/datasets for every canonical dataset
- [ ] on every commit related to a dataset, update the hf.co repo
See https://github.com/huggingface/moon-landing/pull/1562
@SBrandeis: I let you edit this description if needed to pr... | [
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0.37578684... |
https://github.com/huggingface/datasets/issues/3339 | This might be related to https://github.com/tensorflow/tensorflow/issues/38762 , what do you think @Rocketknight1 ?
> Dataset.from_generator is expected to not work with TPUs as it uses py_function underneath which is incompatible with Cloud TPU 2VM setup. If you would like to read from large datasets, maybe try to ma... | to_tf_dataset fails on TPU | Using `to_tf_dataset` to create a dataset and then putting it in `model.fit` results in an internal error on TPUs. I've only tried on Colab and Kaggle TPUs, not GCP TPUs.
## Steps to reproduce the bug
I made a colab to show the error. https://colab.research.google.com/drive/12x_PFKzGouFxqD4OuWfnycW_1TaT276z?usp=s... | 55 | to_tf_dataset fails on TPU
Using `to_tf_dataset` to create a dataset and then putting it in `model.fit` results in an internal error on TPUs. I've only tried on Colab and Kaggle TPUs, not GCP TPUs.
## Steps to reproduce the bug
I made a colab to show the error. https://colab.research.google.com/drive/12x_PFKzGo... | [
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0.2911761403083801,
0.25148311257362366,
0.492923855781555... |
https://github.com/huggingface/datasets/issues/3339 | Hi @lhoestq @nbroad1881, I think it's very similar, yes. Unfortunately `to_tf_dataset` uses `tf.numpy_function` which can't be compiled - this is a necessary evil to load from the underlying Arrow dataset. We need to update the notebooks/examples to clarify that this won't work, or to identify a workaround. You may be ... | to_tf_dataset fails on TPU | Using `to_tf_dataset` to create a dataset and then putting it in `model.fit` results in an internal error on TPUs. I've only tried on Colab and Kaggle TPUs, not GCP TPUs.
## Steps to reproduce the bug
I made a colab to show the error. https://colab.research.google.com/drive/12x_PFKzGouFxqD4OuWfnycW_1TaT276z?usp=s... | 73 | to_tf_dataset fails on TPU
Using `to_tf_dataset` to create a dataset and then putting it in `model.fit` results in an internal error on TPUs. I've only tried on Colab and Kaggle TPUs, not GCP TPUs.
## Steps to reproduce the bug
I made a colab to show the error. https://colab.research.google.com/drive/12x_PFKzGo... | [
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0.180120587348938,
-0.055424273014068604,
0.2911761403083801,
0.25148311257362366,
0.492923855781555... |
https://github.com/huggingface/datasets/issues/3339 | Thank you for the explanation. I didn't realize the nuances of `tf.numpy_function`. In this scenario, would it be better to use `export(format='tfrecord')` ? It's not quite the same, but for very large datasets that don't fit in memory it looks like it is the only option. I haven't used `export` before, but I do recal... | to_tf_dataset fails on TPU | Using `to_tf_dataset` to create a dataset and then putting it in `model.fit` results in an internal error on TPUs. I've only tried on Colab and Kaggle TPUs, not GCP TPUs.
## Steps to reproduce the bug
I made a colab to show the error. https://colab.research.google.com/drive/12x_PFKzGouFxqD4OuWfnycW_1TaT276z?usp=s... | 163 | to_tf_dataset fails on TPU
Using `to_tf_dataset` to create a dataset and then putting it in `model.fit` results in an internal error on TPUs. I've only tried on Colab and Kaggle TPUs, not GCP TPUs.
## Steps to reproduce the bug
I made a colab to show the error. https://colab.research.google.com/drive/12x_PFKzGo... | [
-0.23771564662456512,
-0.13588355481624603,
0.15925009548664093,
0.20368288457393646,
0.415363073348999,
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0.36434897780418396,
0.02571447193622589,
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0.180120587348938,
-0.055424273014068604,
0.2911761403083801,
0.25148311257362366,
0.492923855781555... |
https://github.com/huggingface/datasets/issues/3339 | Yeah, this is something we really should have a proper guide on. I'll make a note to test some things and make a 'TF TPU best practices' notebook at some point, but in the meantime I think your solution of exporting TFRecords will probably work. | to_tf_dataset fails on TPU | Using `to_tf_dataset` to create a dataset and then putting it in `model.fit` results in an internal error on TPUs. I've only tried on Colab and Kaggle TPUs, not GCP TPUs.
## Steps to reproduce the bug
I made a colab to show the error. https://colab.research.google.com/drive/12x_PFKzGouFxqD4OuWfnycW_1TaT276z?usp=s... | 45 | to_tf_dataset fails on TPU
Using `to_tf_dataset` to create a dataset and then putting it in `model.fit` results in an internal error on TPUs. I've only tried on Colab and Kaggle TPUs, not GCP TPUs.
## Steps to reproduce the bug
I made a colab to show the error. https://colab.research.google.com/drive/12x_PFKzGo... | [
-0.23771564662456512,
-0.13588355481624603,
0.15925009548664093,
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0.415363073348999,
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0.02571447193622589,
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0.180120587348938,
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0.2911761403083801,
0.25148311257362366,
0.492923855781555... |
https://github.com/huggingface/datasets/issues/3337 | Hi ! Thanks for the suggestion, I didn't know about this decorator.
If you are interesting in contributing, feel free to open a pull request to add the overload methods for each typing combination :) To assign you to this issue, you can comment `#self-assign` in this thread.
`Dataset.__getitem__` is defined right... | Typing of Dataset.__getitem__ could be improved. | ## Describe the bug
The newly added typing for Dataset.__getitem__ is Union[Dict, List]. This makes tools like mypy a bit awkward to use as we need to check the type manually. We could use type overloading to make this easier. [Documentation](https://docs.python.org/3/library/typing.html#typing.overload)
## Steps... | 54 | Typing of Dataset.__getitem__ could be improved.
## Describe the bug
The newly added typing for Dataset.__getitem__ is Union[Dict, List]. This makes tools like mypy a bit awkward to use as we need to check the type manually. We could use type overloading to make this easier. [Documentation](https://docs.python.org... | [
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https://github.com/huggingface/datasets/issues/3334 | Polars has grown rapidly in popularity over the last year - could you consider integrating the Polars functionality again?
I don't think the "custom" implementation should be a barrier, it still conforms to the Arrow specification | Integrate Polars library | Check potential integration of the Polars library: https://github.com/pola-rs/polars
- Benchmark: https://h2oai.github.io/db-benchmark/
CC: @thomwolf @lewtun
| 36 | Integrate Polars library
Check potential integration of the Polars library: https://github.com/pola-rs/polars
- Benchmark: https://h2oai.github.io/db-benchmark/
CC: @thomwolf @lewtun
Polars has grown rapidly in popularity over the last year - could you consider integrating the Polars functionality again?
... | [
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0.13809986412... |
https://github.com/huggingface/datasets/issues/3334 | Is there some direction regarding this from the HF team @lewtun ? Can conversion from polars to HF dataset be implemented with limited/zero copy? So, something like ``Dataset.from_polars()`` and ``Dataset.to_polars()`` like you mentioned. Happy to contribute if I can get some pointers on how this may be implemented. | Integrate Polars library | Check potential integration of the Polars library: https://github.com/pola-rs/polars
- Benchmark: https://h2oai.github.io/db-benchmark/
CC: @thomwolf @lewtun
| 48 | Integrate Polars library
Check potential integration of the Polars library: https://github.com/pola-rs/polars
- Benchmark: https://h2oai.github.io/db-benchmark/
CC: @thomwolf @lewtun
Is there some direction regarding this from the HF team @lewtun ? Can conversion from polars to HF dataset be implemented with... | [
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https://github.com/huggingface/datasets/issues/3333 | Hi ! The message you're getting is not an error. It simply says that your JSON dataset is being prepared to a location in `/root/.cache/huggingface/datasets` | load JSON files, get the errors | Hi, does this bug be fixed? when I load JSON files, I get the same errors by the command
`!python3 run.py --do_train --task qa --dataset squad-retrain-data/train-v2.0.json --output_dir ./re_trained_model/`
change the dateset to load json by refering to https://huggingface.co/docs/datasets/loading.html
`dataset = ... | 25 | load JSON files, get the errors
Hi, does this bug be fixed? when I load JSON files, I get the same errors by the command
`!python3 run.py --do_train --task qa --dataset squad-retrain-data/train-v2.0.json --output_dir ./re_trained_model/`
change the dateset to load json by refering to https://huggingface.co/docs... | [
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0.3266996443... |
https://github.com/huggingface/datasets/issues/3333 | >
but I want to load local JSON file by command
`python3 run.py --do_train --task qa --dataset squad-retrain-data/train-v2.0.json --output_dir ./re_trained_model/`
**squad-retrain-data/train-v2.0.json** is the local JSON file, how to load it and map it to a special structure? | load JSON files, get the errors | Hi, does this bug be fixed? when I load JSON files, I get the same errors by the command
`!python3 run.py --do_train --task qa --dataset squad-retrain-data/train-v2.0.json --output_dir ./re_trained_model/`
change the dateset to load json by refering to https://huggingface.co/docs/datasets/loading.html
`dataset = ... | 37 | load JSON files, get the errors
Hi, does this bug be fixed? when I load JSON files, I get the same errors by the command
`!python3 run.py --do_train --task qa --dataset squad-retrain-data/train-v2.0.json --output_dir ./re_trained_model/`
change the dateset to load json by refering to https://huggingface.co/docs... | [
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0.292006731033325... |
https://github.com/huggingface/datasets/issues/3333 | You can load it with `dataset = datasets.load_dataset('json', data_files=args.dataset)` as you said.
Then if you need to apply additional processing to map it to a special structure, you can use rename columns or use `dataset.map`. For more information, you can check the documentation here: https://huggingface.co/docs... | load JSON files, get the errors | Hi, does this bug be fixed? when I load JSON files, I get the same errors by the command
`!python3 run.py --do_train --task qa --dataset squad-retrain-data/train-v2.0.json --output_dir ./re_trained_model/`
change the dateset to load json by refering to https://huggingface.co/docs/datasets/loading.html
`dataset = ... | 59 | load JSON files, get the errors
Hi, does this bug be fixed? when I load JSON files, I get the same errors by the command
`!python3 run.py --do_train --task qa --dataset squad-retrain-data/train-v2.0.json --output_dir ./re_trained_model/`
change the dateset to load json by refering to https://huggingface.co/docs... | [
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0.4676977097988... |
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