html_url stringlengths 48 51 | title stringlengths 5 280 | comments stringlengths 63 51.8k | body stringlengths 0 36.2k ⌀ | comment_length int64 16 1.52k | text stringlengths 159 54.1k | embeddings listlengths 768 768 |
|---|---|---|---|---|---|---|
https://github.com/huggingface/datasets/issues/4886 | Loading huggan/CelebA-HQ throws pyarrow.lib.ArrowInvalid | Hey,
Yes the notebook I used to upload this dataset can be found here: https://colab.research.google.com/drive/141LJCcM2XyqprPY83nIQ-Zk3BbxWeahq?usp=sharing.
If you have time to regenerate the dataset, would be great. | ## Describe the bug
Loading huggan/CelebA-HQ throws pyarrow.lib.ArrowInvalid
## Steps to reproduce the bug
```python
from datasets import load_dataset
dataset = load_dataset('huggan/CelebA-HQ')
```
## Expected results
See https://colab.research.google.com/drive/141LJCcM2XyqprPY83nIQ-Zk3BbxWeahq?usp=sharing#... | 26 | Loading huggan/CelebA-HQ throws pyarrow.lib.ArrowInvalid
## Describe the bug
Loading huggan/CelebA-HQ throws pyarrow.lib.ArrowInvalid
## Steps to reproduce the bug
```python
from datasets import load_dataset
dataset = load_dataset('huggan/CelebA-HQ')
```
## Expected results
See https://colab.research.goog... | [
-0.10748839378356934,
-0.1885012537240982,
-0.039607081562280655,
0.3444852828979492,
0.2344798892736435,
-0.11021281033754349,
0.1118069738149643,
0.4497286379337311,
-0.2684803009033203,
0.24177247285842896,
-0.07293921709060669,
0.6089426875114441,
-0.11537941545248032,
0.00878512673079... |
https://github.com/huggingface/datasets/issues/4886 | Loading huggan/CelebA-HQ throws pyarrow.lib.ArrowInvalid | Sorry, maybe I wasn't clear enough that it's a different dataset `laion2B-multi-joined-translated-to-en`. I think there should be checks in the upload, tests on the server, or validation after download (hashes) to catch these problems.
Lots of bandwidth wasted otherwise! /cc @mariosasko | ## Describe the bug
Loading huggan/CelebA-HQ throws pyarrow.lib.ArrowInvalid
## Steps to reproduce the bug
```python
from datasets import load_dataset
dataset = load_dataset('huggan/CelebA-HQ')
```
## Expected results
See https://colab.research.google.com/drive/141LJCcM2XyqprPY83nIQ-Zk3BbxWeahq?usp=sharing#... | 41 | Loading huggan/CelebA-HQ throws pyarrow.lib.ArrowInvalid
## Describe the bug
Loading huggan/CelebA-HQ throws pyarrow.lib.ArrowInvalid
## Steps to reproduce the bug
```python
from datasets import load_dataset
dataset = load_dataset('huggan/CelebA-HQ')
```
## Expected results
See https://colab.research.goog... | [
-0.10748839378356934,
-0.1885012537240982,
-0.039607081562280655,
0.3444852828979492,
0.2344798892736435,
-0.11021281033754349,
0.1118069738149643,
0.4497286379337311,
-0.2684803009033203,
0.24177247285842896,
-0.07293921709060669,
0.6089426875114441,
-0.11537941545248032,
0.00878512673079... |
https://github.com/huggingface/datasets/issues/4886 | Loading huggan/CelebA-HQ throws pyarrow.lib.ArrowInvalid | Yes @alexjc sorry was more a reply to @JeanKaddour.
And indeed it'd be great to have additional checks to avoid these errors. | ## Describe the bug
Loading huggan/CelebA-HQ throws pyarrow.lib.ArrowInvalid
## Steps to reproduce the bug
```python
from datasets import load_dataset
dataset = load_dataset('huggan/CelebA-HQ')
```
## Expected results
See https://colab.research.google.com/drive/141LJCcM2XyqprPY83nIQ-Zk3BbxWeahq?usp=sharing#... | 22 | Loading huggan/CelebA-HQ throws pyarrow.lib.ArrowInvalid
## Describe the bug
Loading huggan/CelebA-HQ throws pyarrow.lib.ArrowInvalid
## Steps to reproduce the bug
```python
from datasets import load_dataset
dataset = load_dataset('huggan/CelebA-HQ')
```
## Expected results
See https://colab.research.goog... | [
-0.10748839378356934,
-0.1885012537240982,
-0.039607081562280655,
0.3444852828979492,
0.2344798892736435,
-0.11021281033754349,
0.1118069738149643,
0.4497286379337311,
-0.2684803009033203,
0.24177247285842896,
-0.07293921709060669,
0.6089426875114441,
-0.11537941545248032,
0.00878512673079... |
https://github.com/huggingface/datasets/issues/4886 | Loading huggan/CelebA-HQ throws pyarrow.lib.ArrowInvalid | Hi,
It seems the problem is still persist. I have encountered the exact same problem using just 2 line of code above.
The error code is as follows:
```
發生例外狀況: DatasetGenerationError
An error occurred while generating the dataset
pyarrow.lib.ArrowInvalid: Parquet magic bytes not found in footer. Either the... | ## Describe the bug
Loading huggan/CelebA-HQ throws pyarrow.lib.ArrowInvalid
## Steps to reproduce the bug
```python
from datasets import load_dataset
dataset = load_dataset('huggan/CelebA-HQ')
```
## Expected results
See https://colab.research.google.com/drive/141LJCcM2XyqprPY83nIQ-Zk3BbxWeahq?usp=sharing#... | 88 | Loading huggan/CelebA-HQ throws pyarrow.lib.ArrowInvalid
## Describe the bug
Loading huggan/CelebA-HQ throws pyarrow.lib.ArrowInvalid
## Steps to reproduce the bug
```python
from datasets import load_dataset
dataset = load_dataset('huggan/CelebA-HQ')
```
## Expected results
See https://colab.research.goog... | [
-0.10748839378356934,
-0.1885012537240982,
-0.039607081562280655,
0.3444852828979492,
0.2344798892736435,
-0.11021281033754349,
0.1118069738149643,
0.4497286379337311,
-0.2684803009033203,
0.24177247285842896,
-0.07293921709060669,
0.6089426875114441,
-0.11537941545248032,
0.00878512673079... |
https://github.com/huggingface/datasets/issues/4886 | Loading huggan/CelebA-HQ throws pyarrow.lib.ArrowInvalid | Yes for the moment refer to the notebook linked above if you want to create a HF dataset yourself | ## Describe the bug
Loading huggan/CelebA-HQ throws pyarrow.lib.ArrowInvalid
## Steps to reproduce the bug
```python
from datasets import load_dataset
dataset = load_dataset('huggan/CelebA-HQ')
```
## Expected results
See https://colab.research.google.com/drive/141LJCcM2XyqprPY83nIQ-Zk3BbxWeahq?usp=sharing#... | 19 | Loading huggan/CelebA-HQ throws pyarrow.lib.ArrowInvalid
## Describe the bug
Loading huggan/CelebA-HQ throws pyarrow.lib.ArrowInvalid
## Steps to reproduce the bug
```python
from datasets import load_dataset
dataset = load_dataset('huggan/CelebA-HQ')
```
## Expected results
See https://colab.research.goog... | [
-0.10748839378356934,
-0.1885012537240982,
-0.039607081562280655,
0.3444852828979492,
0.2344798892736435,
-0.11021281033754349,
0.1118069738149643,
0.4497286379337311,
-0.2684803009033203,
0.24177247285842896,
-0.07293921709060669,
0.6089426875114441,
-0.11537941545248032,
0.00878512673079... |
https://github.com/huggingface/datasets/issues/4886 | Loading huggan/CelebA-HQ throws pyarrow.lib.ArrowInvalid | Hi @NielsRogge ,
I can help to push the dataset to the cloud. However, I cannot locate the situation so far. I wonder if
1. the downloaded files so far has corruption s.t. the file cannot generate properly, or
2. the downloaded files has no bug, the bug is caused by buggy upload program so that I can use what I hav... | ## Describe the bug
Loading huggan/CelebA-HQ throws pyarrow.lib.ArrowInvalid
## Steps to reproduce the bug
```python
from datasets import load_dataset
dataset = load_dataset('huggan/CelebA-HQ')
```
## Expected results
See https://colab.research.google.com/drive/141LJCcM2XyqprPY83nIQ-Zk3BbxWeahq?usp=sharing#... | 70 | Loading huggan/CelebA-HQ throws pyarrow.lib.ArrowInvalid
## Describe the bug
Loading huggan/CelebA-HQ throws pyarrow.lib.ArrowInvalid
## Steps to reproduce the bug
```python
from datasets import load_dataset
dataset = load_dataset('huggan/CelebA-HQ')
```
## Expected results
See https://colab.research.goog... | [
-0.10748839378356934,
-0.1885012537240982,
-0.039607081562280655,
0.3444852828979492,
0.2344798892736435,
-0.11021281033754349,
0.1118069738149643,
0.4497286379337311,
-0.2684803009033203,
0.24177247285842896,
-0.07293921709060669,
0.6089426875114441,
-0.11537941545248032,
0.00878512673079... |
https://github.com/huggingface/datasets/issues/4885 | Create dataset from list of dicts | Hi @sanderland, thanks for your enhancement proposal.
I agree with you that this would be useful.
Please note that under the hood, we use PyArrow tables as backend:
- The implementation of `Dataset.from_dict` uses the PyArrow `Table.from_pydict`
Therefore, I would suggest:
- Implementing `Dataset.from_list`... | I often find myself with data from a variety of sources, and a list of dicts is very common among these.
However, converting this to a Dataset is a little awkward, requiring either
```Dataset.from_pandas(pd.DataFrame(formatted_training_data))```
Which can error out on some more exotic values as 2-d arrays for reas... | 60 | Create dataset from list of dicts
I often find myself with data from a variety of sources, and a list of dicts is very common among these.
However, converting this to a Dataset is a little awkward, requiring either
```Dataset.from_pandas(pd.DataFrame(formatted_training_data))```
Which can error out on some more ... | [
0.048299822956323624,
0.09022103250026703,
-0.07030387222766876,
0.03249180689454079,
0.18122033774852753,
0.12492900341749191,
0.2358868271112442,
0.3337085247039795,
0.14719447493553162,
-0.1132781058549881,
0.018525324761867523,
0.6201065182685852,
-0.2998390793800354,
0.238888308405876... |
https://github.com/huggingface/datasets/issues/4885 | Create dataset from list of dicts | Thanks for the quick and positive reply @albertvillanova!
`from_list` seems sensible. Have opened a PR so we can discuss details there. | I often find myself with data from a variety of sources, and a list of dicts is very common among these.
However, converting this to a Dataset is a little awkward, requiring either
```Dataset.from_pandas(pd.DataFrame(formatted_training_data))```
Which can error out on some more exotic values as 2-d arrays for reas... | 21 | Create dataset from list of dicts
I often find myself with data from a variety of sources, and a list of dicts is very common among these.
However, converting this to a Dataset is a little awkward, requiring either
```Dataset.from_pandas(pd.DataFrame(formatted_training_data))```
Which can error out on some more ... | [
0.07389438152313232,
-0.06402075290679932,
-0.11433322727680206,
0.05473331734538078,
0.1746685802936554,
0.151888906955719,
0.2088438719511032,
0.2566526234149933,
0.4002479612827301,
-0.07812778651714325,
0.048212289810180664,
0.5458565950393677,
-0.34055453538894653,
0.2892850339412689,... |
https://github.com/huggingface/datasets/issues/4883 | With dataloader RSS memory consumed by HF datasets monotonically increases | Are you sure there is a leak? How can I see it? You shared the script but not the output which you believe should indicate a leak.
I modified your reproduction script to print only once per try as your original was printing too much info and you absolutely must add `gc.collect()` when doing any memory measurements, ... | ## Describe the bug
When the HF datasets is used in conjunction with PyTorch Dataloader, the RSS memory of the process keeps on increasing when it should stay constant.
## Steps to reproduce the bug
Run and observe the output of this snippet which logs RSS memory.
```python
import psutil
import os
from transf... | 226 | With dataloader RSS memory consumed by HF datasets monotonically increases
## Describe the bug
When the HF datasets is used in conjunction with PyTorch Dataloader, the RSS memory of the process keeps on increasing when it should stay constant.
## Steps to reproduce the bug
Run and observe the output of this sni... | [
-0.11197682470083237,
-0.03989267349243164,
0.13984118402004242,
0.18200340867042542,
0.23067383468151093,
-0.14632582664489746,
0.18177445232868195,
0.020412715151906013,
0.00939258560538292,
0.2771010994911194,
-0.020981086418032646,
0.3817747235298157,
-0.24682985246181488,
-0.288210421... |
https://github.com/huggingface/datasets/issues/4883 | With dataloader RSS memory consumed by HF datasets monotonically increases | Unless of course you're referring the memory growth during the first try. Is that what you're referring to? And since your ds is small it's hard to see the growth - could it be just because some records are longer and it needs to allocate more memory for those?
Though while experimenting with this I have observed a ... | ## Describe the bug
When the HF datasets is used in conjunction with PyTorch Dataloader, the RSS memory of the process keeps on increasing when it should stay constant.
## Steps to reproduce the bug
Run and observe the output of this snippet which logs RSS memory.
```python
import psutil
import os
from transf... | 123 | With dataloader RSS memory consumed by HF datasets monotonically increases
## Describe the bug
When the HF datasets is used in conjunction with PyTorch Dataloader, the RSS memory of the process keeps on increasing when it should stay constant.
## Steps to reproduce the bug
Run and observe the output of this sni... | [
-0.11197682470083237,
-0.03989267349243164,
0.13984118402004242,
0.18200340867042542,
0.23067383468151093,
-0.14632582664489746,
0.18177445232868195,
0.020412715151906013,
0.00939258560538292,
0.2771010994911194,
-0.020981086418032646,
0.3817747235298157,
-0.24682985246181488,
-0.288210421... |
https://github.com/huggingface/datasets/issues/4883 | With dataloader RSS memory consumed by HF datasets monotonically increases | It is hard to say if it is directly reproducible in this setup. Maybe it is specific to the images stored in the CM4 case which cause a memory leak. I am still running your script and seeing if I can reproduce that particular leak in this case. | ## Describe the bug
When the HF datasets is used in conjunction with PyTorch Dataloader, the RSS memory of the process keeps on increasing when it should stay constant.
## Steps to reproduce the bug
Run and observe the output of this snippet which logs RSS memory.
```python
import psutil
import os
from transf... | 48 | With dataloader RSS memory consumed by HF datasets monotonically increases
## Describe the bug
When the HF datasets is used in conjunction with PyTorch Dataloader, the RSS memory of the process keeps on increasing when it should stay constant.
## Steps to reproduce the bug
Run and observe the output of this sni... | [
-0.11197682470083237,
-0.03989267349243164,
0.13984118402004242,
0.18200340867042542,
0.23067383468151093,
-0.14632582664489746,
0.18177445232868195,
0.020412715151906013,
0.00939258560538292,
0.2771010994911194,
-0.020981086418032646,
0.3817747235298157,
-0.24682985246181488,
-0.288210421... |
https://github.com/huggingface/datasets/issues/4883 | With dataloader RSS memory consumed by HF datasets monotonically increases | I was able to reproduce the leak with:
```
import psutil
import os
import gc
from datasets import load_from_disk
import time
DATASET_PATH = "/hf/m4-master/data/cm4/cm4-10000-v0.1"
dataset = load_from_disk(DATASET_PATH)
# truncate to a tiny dataset
dataset = dataset.select(range(1000))
print(f"datas... | ## Describe the bug
When the HF datasets is used in conjunction with PyTorch Dataloader, the RSS memory of the process keeps on increasing when it should stay constant.
## Steps to reproduce the bug
Run and observe the output of this snippet which logs RSS memory.
```python
import psutil
import os
from transf... | 143 | With dataloader RSS memory consumed by HF datasets monotonically increases
## Describe the bug
When the HF datasets is used in conjunction with PyTorch Dataloader, the RSS memory of the process keeps on increasing when it should stay constant.
## Steps to reproduce the bug
Run and observe the output of this sni... | [
-0.11197682470083237,
-0.03989267349243164,
0.13984118402004242,
0.18200340867042542,
0.23067383468151093,
-0.14632582664489746,
0.18177445232868195,
0.020412715151906013,
0.00939258560538292,
0.2771010994911194,
-0.020981086418032646,
0.3817747235298157,
-0.24682985246181488,
-0.288210421... |
https://github.com/huggingface/datasets/issues/4883 | With dataloader RSS memory consumed by HF datasets monotonically increases | This issue has nothing to do with `PIL`'s decoder. I removed it and the problem is still there.
I then traced this leak to this single call: `pa_table.to_pydict()` here:
https://github.com/huggingface/datasets/blob/08a7b389cdd6fb49264a72aa8ccfc49a233494b6/src/datasets/formatting/formatting.py#L138-L140
I can m... | ## Describe the bug
When the HF datasets is used in conjunction with PyTorch Dataloader, the RSS memory of the process keeps on increasing when it should stay constant.
## Steps to reproduce the bug
Run and observe the output of this snippet which logs RSS memory.
```python
import psutil
import os
from transf... | 182 | With dataloader RSS memory consumed by HF datasets monotonically increases
## Describe the bug
When the HF datasets is used in conjunction with PyTorch Dataloader, the RSS memory of the process keeps on increasing when it should stay constant.
## Steps to reproduce the bug
Run and observe the output of this sni... | [
-0.11197682470083237,
-0.03989267349243164,
0.13984118402004242,
0.18200340867042542,
0.23067383468151093,
-0.14632582664489746,
0.18177445232868195,
0.020412715151906013,
0.00939258560538292,
0.2771010994911194,
-0.020981086418032646,
0.3817747235298157,
-0.24682985246181488,
-0.288210421... |
https://github.com/huggingface/datasets/issues/4883 | With dataloader RSS memory consumed by HF datasets monotonically increases | This appears to be the same issue I think: https://github.com/huggingface/datasets/issues/4528
I dug into the repro code there and it's the same behavior with the same leak, but it's a pure nlp dataset and thus much faster to work with.
| ## Describe the bug
When the HF datasets is used in conjunction with PyTorch Dataloader, the RSS memory of the process keeps on increasing when it should stay constant.
## Steps to reproduce the bug
Run and observe the output of this snippet which logs RSS memory.
```python
import psutil
import os
from transf... | 39 | With dataloader RSS memory consumed by HF datasets monotonically increases
## Describe the bug
When the HF datasets is used in conjunction with PyTorch Dataloader, the RSS memory of the process keeps on increasing when it should stay constant.
## Steps to reproduce the bug
Run and observe the output of this sni... | [
-0.11197682470083237,
-0.03989267349243164,
0.13984118402004242,
0.18200340867042542,
0.23067383468151093,
-0.14632582664489746,
0.18177445232868195,
0.020412715151906013,
0.00939258560538292,
0.2771010994911194,
-0.020981086418032646,
0.3817747235298157,
-0.24682985246181488,
-0.288210421... |
https://github.com/huggingface/datasets/issues/4883 | With dataloader RSS memory consumed by HF datasets monotonically increases | I went all the way back to `pyarrow==1.0.0` and `datasets==1.12.0` and the problem is still there. How is it even possible that it wasn't noticed all this time.
Could it be that the leak is in some 3rd party component `pyarrow` relies on? as while downgrading I have only downgraded the above 2 packages.
| ## Describe the bug
When the HF datasets is used in conjunction with PyTorch Dataloader, the RSS memory of the process keeps on increasing when it should stay constant.
## Steps to reproduce the bug
Run and observe the output of this snippet which logs RSS memory.
```python
import psutil
import os
from transf... | 54 | With dataloader RSS memory consumed by HF datasets monotonically increases
## Describe the bug
When the HF datasets is used in conjunction with PyTorch Dataloader, the RSS memory of the process keeps on increasing when it should stay constant.
## Steps to reproduce the bug
Run and observe the output of this sni... | [
-0.11197682470083237,
-0.03989267349243164,
0.13984118402004242,
0.18200340867042542,
0.23067383468151093,
-0.14632582664489746,
0.18177445232868195,
0.020412715151906013,
0.00939258560538292,
0.2771010994911194,
-0.020981086418032646,
0.3817747235298157,
-0.24682985246181488,
-0.288210421... |
https://github.com/huggingface/datasets/issues/4883 | With dataloader RSS memory consumed by HF datasets monotonically increases | Also found this warning
> Be careful: if you don't pass the ArrowArray struct to a consumer,
> array memory will leak. This is a low-level function intended for
> expert users.
see: https://github.com/apache/arrow/blob/99b57e84277f24e8ec1ddadbb11ef8b4f43c8c89/python/pyarrow/table.pxi#L... | ## Describe the bug
When the HF datasets is used in conjunction with PyTorch Dataloader, the RSS memory of the process keeps on increasing when it should stay constant.
## Steps to reproduce the bug
Run and observe the output of this snippet which logs RSS memory.
```python
import psutil
import os
from transf... | 57 | With dataloader RSS memory consumed by HF datasets monotonically increases
## Describe the bug
When the HF datasets is used in conjunction with PyTorch Dataloader, the RSS memory of the process keeps on increasing when it should stay constant.
## Steps to reproduce the bug
Run and observe the output of this sni... | [
-0.11197682470083237,
-0.03989267349243164,
0.13984118402004242,
0.18200340867042542,
0.23067383468151093,
-0.14632582664489746,
0.18177445232868195,
0.020412715151906013,
0.00939258560538292,
0.2771010994911194,
-0.020981086418032646,
0.3817747235298157,
-0.24682985246181488,
-0.288210421... |
https://github.com/huggingface/datasets/issues/4883 | With dataloader RSS memory consumed by HF datasets monotonically increases | Does it crash with OOM at some point? If it doesn't, it isn't a leak, just agressive caching or a custom allocator that doesn't like to give memory back (not uncommon). #4528 looks like it hits a steady state.
I believe the underlying arrow libs use a custom C allocator. Some of those are designed not to give back t... | ## Describe the bug
When the HF datasets is used in conjunction with PyTorch Dataloader, the RSS memory of the process keeps on increasing when it should stay constant.
## Steps to reproduce the bug
Run and observe the output of this snippet which logs RSS memory.
```python
import psutil
import os
from transf... | 110 | With dataloader RSS memory consumed by HF datasets monotonically increases
## Describe the bug
When the HF datasets is used in conjunction with PyTorch Dataloader, the RSS memory of the process keeps on increasing when it should stay constant.
## Steps to reproduce the bug
Run and observe the output of this sni... | [
-0.11197682470083237,
-0.03989267349243164,
0.13984118402004242,
0.18200340867042542,
0.23067383468151093,
-0.14632582664489746,
0.18177445232868195,
0.020412715151906013,
0.00939258560538292,
0.2771010994911194,
-0.020981086418032646,
0.3817747235298157,
-0.24682985246181488,
-0.288210421... |
https://github.com/huggingface/datasets/issues/4883 | With dataloader RSS memory consumed by HF datasets monotonically increases | > Does it crash with OOM at some point?
In the original setup where we noticed this problem, it was indeed ending in an OOM | ## Describe the bug
When the HF datasets is used in conjunction with PyTorch Dataloader, the RSS memory of the process keeps on increasing when it should stay constant.
## Steps to reproduce the bug
Run and observe the output of this snippet which logs RSS memory.
```python
import psutil
import os
from transf... | 25 | With dataloader RSS memory consumed by HF datasets monotonically increases
## Describe the bug
When the HF datasets is used in conjunction with PyTorch Dataloader, the RSS memory of the process keeps on increasing when it should stay constant.
## Steps to reproduce the bug
Run and observe the output of this sni... | [
-0.11197682470083237,
-0.03989267349243164,
0.13984118402004242,
0.18200340867042542,
0.23067383468151093,
-0.14632582664489746,
0.18177445232868195,
0.020412715151906013,
0.00939258560538292,
0.2771010994911194,
-0.020981086418032646,
0.3817747235298157,
-0.24682985246181488,
-0.288210421... |
https://github.com/huggingface/datasets/issues/4883 | With dataloader RSS memory consumed by HF datasets monotonically increases | > https://github.com/huggingface/datasets/issues/4528 looks like it hits a steady state.
@rwightman in the plot I shared, the steady state comes from the `time.sleep(100)` I added in the end of the script, to showcase that even the garbage collector couldn't free that allocated memory.
| ## Describe the bug
When the HF datasets is used in conjunction with PyTorch Dataloader, the RSS memory of the process keeps on increasing when it should stay constant.
## Steps to reproduce the bug
Run and observe the output of this snippet which logs RSS memory.
```python
import psutil
import os
from transf... | 42 | With dataloader RSS memory consumed by HF datasets monotonically increases
## Describe the bug
When the HF datasets is used in conjunction with PyTorch Dataloader, the RSS memory of the process keeps on increasing when it should stay constant.
## Steps to reproduce the bug
Run and observe the output of this sni... | [
-0.11197682470083237,
-0.03989267349243164,
0.13984118402004242,
0.18200340867042542,
0.23067383468151093,
-0.14632582664489746,
0.18177445232868195,
0.020412715151906013,
0.00939258560538292,
0.2771010994911194,
-0.020981086418032646,
0.3817747235298157,
-0.24682985246181488,
-0.288210421... |
https://github.com/huggingface/datasets/issues/4883 | With dataloader RSS memory consumed by HF datasets monotonically increases | Could this be related to this discussion about a potential memory leak in pyarrow: https://issues.apache.org/jira/browse/ARROW-11007 ?
(Note: I've tried `import pyarrow; pyarrow.jemalloc_set_decay_ms(0)` and the memory leak is still happening on your toy example) | ## Describe the bug
When the HF datasets is used in conjunction with PyTorch Dataloader, the RSS memory of the process keeps on increasing when it should stay constant.
## Steps to reproduce the bug
Run and observe the output of this snippet which logs RSS memory.
```python
import psutil
import os
from transf... | 33 | With dataloader RSS memory consumed by HF datasets monotonically increases
## Describe the bug
When the HF datasets is used in conjunction with PyTorch Dataloader, the RSS memory of the process keeps on increasing when it should stay constant.
## Steps to reproduce the bug
Run and observe the output of this sni... | [
-0.11197682470083237,
-0.03989267349243164,
0.13984118402004242,
0.18200340867042542,
0.23067383468151093,
-0.14632582664489746,
0.18177445232868195,
0.020412715151906013,
0.00939258560538292,
0.2771010994911194,
-0.020981086418032646,
0.3817747235298157,
-0.24682985246181488,
-0.288210421... |
https://github.com/huggingface/datasets/issues/4883 | With dataloader RSS memory consumed by HF datasets monotonically increases | > @lhoestq - do you know what might be happening inside pa_table.to_pydict(), as this is in the pyarrow domain. Perhaps you know someone to tag from that project?
`to_pydict` calls `to_pylist` on each column (i.e. on each PyArrow Array). Then it iterates on the array and calls `as_py` on each element. The `as_py` im... | ## Describe the bug
When the HF datasets is used in conjunction with PyTorch Dataloader, the RSS memory of the process keeps on increasing when it should stay constant.
## Steps to reproduce the bug
Run and observe the output of this snippet which logs RSS memory.
```python
import psutil
import os
from transf... | 138 | With dataloader RSS memory consumed by HF datasets monotonically increases
## Describe the bug
When the HF datasets is used in conjunction with PyTorch Dataloader, the RSS memory of the process keeps on increasing when it should stay constant.
## Steps to reproduce the bug
Run and observe the output of this sni... | [
-0.11197682470083237,
-0.03989267349243164,
0.13984118402004242,
0.18200340867042542,
0.23067383468151093,
-0.14632582664489746,
0.18177445232868195,
0.020412715151906013,
0.00939258560538292,
0.2771010994911194,
-0.020981086418032646,
0.3817747235298157,
-0.24682985246181488,
-0.288210421... |
https://github.com/huggingface/datasets/issues/4883 | With dataloader RSS memory consumed by HF datasets monotonically increases | > That would be ideal indeed. Would be happy to help on this, can you give me access to the bucket so I can try with your data ?
I added you to the bucket @lhoestq | ## Describe the bug
When the HF datasets is used in conjunction with PyTorch Dataloader, the RSS memory of the process keeps on increasing when it should stay constant.
## Steps to reproduce the bug
Run and observe the output of this snippet which logs RSS memory.
```python
import psutil
import os
from transf... | 36 | With dataloader RSS memory consumed by HF datasets monotonically increases
## Describe the bug
When the HF datasets is used in conjunction with PyTorch Dataloader, the RSS memory of the process keeps on increasing when it should stay constant.
## Steps to reproduce the bug
Run and observe the output of this sni... | [
-0.11197682470083237,
-0.03989267349243164,
0.13984118402004242,
0.18200340867042542,
0.23067383468151093,
-0.14632582664489746,
0.18177445232868195,
0.020412715151906013,
0.00939258560538292,
0.2771010994911194,
-0.020981086418032646,
0.3817747235298157,
-0.24682985246181488,
-0.288210421... |
https://github.com/huggingface/datasets/issues/4883 | With dataloader RSS memory consumed by HF datasets monotonically increases | It looks like an issue with memory mapping:
- the amount of memory used in the end corresponds to the size of the dataset
- setting `keep_in_memory=True` in `load_from_disk` loads the dataset in RAM, and **doesn't cause any memory leak** | ## Describe the bug
When the HF datasets is used in conjunction with PyTorch Dataloader, the RSS memory of the process keeps on increasing when it should stay constant.
## Steps to reproduce the bug
Run and observe the output of this snippet which logs RSS memory.
```python
import psutil
import os
from transf... | 40 | With dataloader RSS memory consumed by HF datasets monotonically increases
## Describe the bug
When the HF datasets is used in conjunction with PyTorch Dataloader, the RSS memory of the process keeps on increasing when it should stay constant.
## Steps to reproduce the bug
Run and observe the output of this sni... | [
-0.11197682470083237,
-0.03989267349243164,
0.13984118402004242,
0.18200340867042542,
0.23067383468151093,
-0.14632582664489746,
0.18177445232868195,
0.020412715151906013,
0.00939258560538292,
0.2771010994911194,
-0.020981086418032646,
0.3817747235298157,
-0.24682985246181488,
-0.288210421... |
https://github.com/huggingface/datasets/issues/4883 | With dataloader RSS memory consumed by HF datasets monotonically increases | Here is a code to reproduce this issue using only PyArrow and a dummy arrow file:
```python
import psutil
import os
import gc
import pyarrow as pa
import time
ARROW_PATH = "tmp.arrow"
if not os.path.exists(ARROW_PATH):
arr = pa.array([b"a" * (200 * 1024)] * 1000) # ~200MB
table = pa.table({"a": a... | ## Describe the bug
When the HF datasets is used in conjunction with PyTorch Dataloader, the RSS memory of the process keeps on increasing when it should stay constant.
## Steps to reproduce the bug
Run and observe the output of this snippet which logs RSS memory.
```python
import psutil
import os
from transf... | 161 | With dataloader RSS memory consumed by HF datasets monotonically increases
## Describe the bug
When the HF datasets is used in conjunction with PyTorch Dataloader, the RSS memory of the process keeps on increasing when it should stay constant.
## Steps to reproduce the bug
Run and observe the output of this sni... | [
-0.11197682470083237,
-0.03989267349243164,
0.13984118402004242,
0.18200340867042542,
0.23067383468151093,
-0.14632582664489746,
0.18177445232868195,
0.020412715151906013,
0.00939258560538292,
0.2771010994911194,
-0.020981086418032646,
0.3817747235298157,
-0.24682985246181488,
-0.288210421... |
https://github.com/huggingface/datasets/issues/4883 | With dataloader RSS memory consumed by HF datasets monotonically increases | @lhoestq that does indeed increase in memory, but if you iterate over array again after the first time, or re-open and remap the same file (repeat `table = memory_mapped_arrow_table_from_file(ARROW_PATH)`) before re-iterating, it doesn't move pas 195MB.... it would appear another step is needed to continue consuming me... | ## Describe the bug
When the HF datasets is used in conjunction with PyTorch Dataloader, the RSS memory of the process keeps on increasing when it should stay constant.
## Steps to reproduce the bug
Run and observe the output of this snippet which logs RSS memory.
```python
import psutil
import os
from transf... | 219 | With dataloader RSS memory consumed by HF datasets monotonically increases
## Describe the bug
When the HF datasets is used in conjunction with PyTorch Dataloader, the RSS memory of the process keeps on increasing when it should stay constant.
## Steps to reproduce the bug
Run and observe the output of this sni... | [
-0.11197682470083237,
-0.03989267349243164,
0.13984118402004242,
0.18200340867042542,
0.23067383468151093,
-0.14632582664489746,
0.18177445232868195,
0.020412715151906013,
0.00939258560538292,
0.2771010994911194,
-0.020981086418032646,
0.3817747235298157,
-0.24682985246181488,
-0.288210421... |
https://github.com/huggingface/datasets/issues/4883 | With dataloader RSS memory consumed by HF datasets monotonically increases | Yes, we have already established here https://github.com/huggingface/datasets/issues/4883#issuecomment-1232063891 that when one iterates over the whole dataset multiple times, it consumes a bit more memory in the next few repetitions and then remains steady.
Which means that when a new iterator is created over the ... | ## Describe the bug
When the HF datasets is used in conjunction with PyTorch Dataloader, the RSS memory of the process keeps on increasing when it should stay constant.
## Steps to reproduce the bug
Run and observe the output of this snippet which logs RSS memory.
```python
import psutil
import os
from transf... | 145 | With dataloader RSS memory consumed by HF datasets monotonically increases
## Describe the bug
When the HF datasets is used in conjunction with PyTorch Dataloader, the RSS memory of the process keeps on increasing when it should stay constant.
## Steps to reproduce the bug
Run and observe the output of this sni... | [
-0.11197682470083237,
-0.03989267349243164,
0.13984118402004242,
0.18200340867042542,
0.23067383468151093,
-0.14632582664489746,
0.18177445232868195,
0.020412715151906013,
0.00939258560538292,
0.2771010994911194,
-0.020981086418032646,
0.3817747235298157,
-0.24682985246181488,
-0.288210421... |
https://github.com/huggingface/datasets/issues/4883 | With dataloader RSS memory consumed by HF datasets monotonically increases | @stas00 my point was, I'm not convinced @lhoestq last example illustrates the leak, but rather the differences between memory mapping and in memory usage patterns. If you destroy arr, memory map impl goes back to 0 each iteration. The amount of memory that 'looks' like it is leaked in first pass differes quite a bit be... | ## Describe the bug
When the HF datasets is used in conjunction with PyTorch Dataloader, the RSS memory of the process keeps on increasing when it should stay constant.
## Steps to reproduce the bug
Run and observe the output of this snippet which logs RSS memory.
```python
import psutil
import os
from transf... | 88 | With dataloader RSS memory consumed by HF datasets monotonically increases
## Describe the bug
When the HF datasets is used in conjunction with PyTorch Dataloader, the RSS memory of the process keeps on increasing when it should stay constant.
## Steps to reproduce the bug
Run and observe the output of this sni... | [
-0.11197682470083237,
-0.03989267349243164,
0.13984118402004242,
0.18200340867042542,
0.23067383468151093,
-0.14632582664489746,
0.18177445232868195,
0.020412715151906013,
0.00939258560538292,
0.2771010994911194,
-0.020981086418032646,
0.3817747235298157,
-0.24682985246181488,
-0.288210421... |
https://github.com/huggingface/datasets/issues/4883 | With dataloader RSS memory consumed by HF datasets monotonically increases | Thank you for clarifying, Ross.
I think we agree that it's almost certain that the `datasets` iterator traps some inner variable that prevents object freeing, since if we create the iterator multiple times (and drain it) after a few runs no new memory is allocated. We could try to dig in more with `objgraph` - my m... | ## Describe the bug
When the HF datasets is used in conjunction with PyTorch Dataloader, the RSS memory of the process keeps on increasing when it should stay constant.
## Steps to reproduce the bug
Run and observe the output of this snippet which logs RSS memory.
```python
import psutil
import os
from transf... | 102 | With dataloader RSS memory consumed by HF datasets monotonically increases
## Describe the bug
When the HF datasets is used in conjunction with PyTorch Dataloader, the RSS memory of the process keeps on increasing when it should stay constant.
## Steps to reproduce the bug
Run and observe the output of this sni... | [
-0.11197682470083237,
-0.03989267349243164,
0.13984118402004242,
0.18200340867042542,
0.23067383468151093,
-0.14632582664489746,
0.18177445232868195,
0.020412715151906013,
0.00939258560538292,
0.2771010994911194,
-0.020981086418032646,
0.3817747235298157,
-0.24682985246181488,
-0.288210421... |
https://github.com/huggingface/datasets/issues/4883 | With dataloader RSS memory consumed by HF datasets monotonically increases | FWIW, I revisted some code I had in the works to use HF datasets w/ timm train & val scripts. There is no leak there across multipe epochs. It uses the defaults.
It's worth noting that with imagenet `keep_in_memory=True` isn't even an option because the train arrow file is ~140GB and my local memory is less. The vi... | ## Describe the bug
When the HF datasets is used in conjunction with PyTorch Dataloader, the RSS memory of the process keeps on increasing when it should stay constant.
## Steps to reproduce the bug
Run and observe the output of this snippet which logs RSS memory.
```python
import psutil
import os
from transf... | 96 | With dataloader RSS memory consumed by HF datasets monotonically increases
## Describe the bug
When the HF datasets is used in conjunction with PyTorch Dataloader, the RSS memory of the process keeps on increasing when it should stay constant.
## Steps to reproduce the bug
Run and observe the output of this sni... | [
-0.11197682470083237,
-0.03989267349243164,
0.13984118402004242,
0.18200340867042542,
0.23067383468151093,
-0.14632582664489746,
0.18177445232868195,
0.020412715151906013,
0.00939258560538292,
0.2771010994911194,
-0.020981086418032646,
0.3817747235298157,
-0.24682985246181488,
-0.288210421... |
https://github.com/huggingface/datasets/issues/4883 | With dataloader RSS memory consumed by HF datasets monotonically increases | # Notes
After reading many issues and trying many things here is the summary of my learning
I'm now using @lhoestq repro case as it's pyarrow-isolated: https://github.com/huggingface/datasets/issues/4883#issuecomment-1242034985
## 1. pyarrow memory backends
it has 3 backends, I tried them all with the sa... | ## Describe the bug
When the HF datasets is used in conjunction with PyTorch Dataloader, the RSS memory of the process keeps on increasing when it should stay constant.
## Steps to reproduce the bug
Run and observe the output of this snippet which logs RSS memory.
```python
import psutil
import os
from transf... | 482 | With dataloader RSS memory consumed by HF datasets monotonically increases
## Describe the bug
When the HF datasets is used in conjunction with PyTorch Dataloader, the RSS memory of the process keeps on increasing when it should stay constant.
## Steps to reproduce the bug
Run and observe the output of this sni... | [
-0.11197682470083237,
-0.03989267349243164,
0.13984118402004242,
0.18200340867042542,
0.23067383468151093,
-0.14632582664489746,
0.18177445232868195,
0.020412715151906013,
0.00939258560538292,
0.2771010994911194,
-0.020981086418032646,
0.3817747235298157,
-0.24682985246181488,
-0.288210421... |
https://github.com/huggingface/datasets/issues/4883 | With dataloader RSS memory consumed by HF datasets monotonically increases | # There is no leak, just badly communicated linux RSS memory usage stats
Next, lets revisit @rwightman's suggestion that there is actually no leak.
After all - we are using mmap which **will try to map** the file to RAM as much as it can and then page out if there is no memory. i.e. MMAP is only fast if you have ... | ## Describe the bug
When the HF datasets is used in conjunction with PyTorch Dataloader, the RSS memory of the process keeps on increasing when it should stay constant.
## Steps to reproduce the bug
Run and observe the output of this snippet which logs RSS memory.
```python
import psutil
import os
from transf... | 479 | With dataloader RSS memory consumed by HF datasets monotonically increases
## Describe the bug
When the HF datasets is used in conjunction with PyTorch Dataloader, the RSS memory of the process keeps on increasing when it should stay constant.
## Steps to reproduce the bug
Run and observe the output of this sni... | [
-0.11197682470083237,
-0.03989267349243164,
0.13984118402004242,
0.18200340867042542,
0.23067383468151093,
-0.14632582664489746,
0.18177445232868195,
0.020412715151906013,
0.00939258560538292,
0.2771010994911194,
-0.020981086418032646,
0.3817747235298157,
-0.24682985246181488,
-0.288210421... |
https://github.com/huggingface/datasets/issues/4883 | With dataloader RSS memory consumed by HF datasets monotonically increases | The original leak in the multi-modal code is very likely something else. But of course now it'd be very difficult to trace it using mmap.
I think to debug we have to set `keep_in_memory=True` in `load_from_disk` to load the small dataset in RAM, so there will be no mmap misleading reporting component and then contin... | ## Describe the bug
When the HF datasets is used in conjunction with PyTorch Dataloader, the RSS memory of the process keeps on increasing when it should stay constant.
## Steps to reproduce the bug
Run and observe the output of this snippet which logs RSS memory.
```python
import psutil
import os
from transf... | 62 | With dataloader RSS memory consumed by HF datasets monotonically increases
## Describe the bug
When the HF datasets is used in conjunction with PyTorch Dataloader, the RSS memory of the process keeps on increasing when it should stay constant.
## Steps to reproduce the bug
Run and observe the output of this sni... | [
-0.11197682470083237,
-0.03989267349243164,
0.13984118402004242,
0.18200340867042542,
0.23067383468151093,
-0.14632582664489746,
0.18177445232868195,
0.020412715151906013,
0.00939258560538292,
0.2771010994911194,
-0.020981086418032646,
0.3817747235298157,
-0.24682985246181488,
-0.288210421... |
https://github.com/huggingface/datasets/issues/4883 | With dataloader RSS memory consumed by HF datasets monotonically increases | To add to what @stas00 found, I'm gonna leave some links to where I believe the confusion came from in pyarrow's APIs, for future reference:
* In the section where they talk about [efficiently writing and reading arrow data](https://arrow.apache.org/docs/dev/python/ipc.html?#efficiently-writing-and-reading-arrow-data)... | ## Describe the bug
When the HF datasets is used in conjunction with PyTorch Dataloader, the RSS memory of the process keeps on increasing when it should stay constant.
## Steps to reproduce the bug
Run and observe the output of this snippet which logs RSS memory.
```python
import psutil
import os
from transf... | 272 | With dataloader RSS memory consumed by HF datasets monotonically increases
## Describe the bug
When the HF datasets is used in conjunction with PyTorch Dataloader, the RSS memory of the process keeps on increasing when it should stay constant.
## Steps to reproduce the bug
Run and observe the output of this sni... | [
-0.11197682470083237,
-0.03989267349243164,
0.13984118402004242,
0.18200340867042542,
0.23067383468151093,
-0.14632582664489746,
0.18177445232868195,
0.020412715151906013,
0.00939258560538292,
0.2771010994911194,
-0.020981086418032646,
0.3817747235298157,
-0.24682985246181488,
-0.288210421... |
https://github.com/huggingface/datasets/issues/4883 | With dataloader RSS memory consumed by HF datasets monotonically increases | @lhoestq, I have been working on a detailed article that shows that MMAP doesn't leak and it's mostly ready. I will share when it's ready.
The issue is that we still need to be able to debug memory leaks by turning MMAP off.
But, once I tried to show the user that using `load_dataset(... keep_in_memory=True)` is ... | ## Describe the bug
When the HF datasets is used in conjunction with PyTorch Dataloader, the RSS memory of the process keeps on increasing when it should stay constant.
## Steps to reproduce the bug
Run and observe the output of this snippet which logs RSS memory.
```python
import psutil
import os
from transf... | 183 | With dataloader RSS memory consumed by HF datasets monotonically increases
## Describe the bug
When the HF datasets is used in conjunction with PyTorch Dataloader, the RSS memory of the process keeps on increasing when it should stay constant.
## Steps to reproduce the bug
Run and observe the output of this sni... | [
-0.11197682470083237,
-0.03989267349243164,
0.13984118402004242,
0.18200340867042542,
0.23067383468151093,
-0.14632582664489746,
0.18177445232868195,
0.020412715151906013,
0.00939258560538292,
0.2771010994911194,
-0.020981086418032646,
0.3817747235298157,
-0.24682985246181488,
-0.288210421... |
https://github.com/huggingface/datasets/issues/4883 | With dataloader RSS memory consumed by HF datasets monotonically increases | as I suggested on slack perhaps it was due to dataset records length variation, so with your help I wrote another repro with synthetic records which are all identical - which should remove my hypothese from the equation and we should expect 0 incremental growth as we iterate over the datasets. But alas this is not the ... | ## Describe the bug
When the HF datasets is used in conjunction with PyTorch Dataloader, the RSS memory of the process keeps on increasing when it should stay constant.
## Steps to reproduce the bug
Run and observe the output of this snippet which logs RSS memory.
```python
import psutil
import os
from transf... | 386 | With dataloader RSS memory consumed by HF datasets monotonically increases
## Describe the bug
When the HF datasets is used in conjunction with PyTorch Dataloader, the RSS memory of the process keeps on increasing when it should stay constant.
## Steps to reproduce the bug
Run and observe the output of this sni... | [
-0.11197682470083237,
-0.03989267349243164,
0.13984118402004242,
0.18200340867042542,
0.23067383468151093,
-0.14632582664489746,
0.18177445232868195,
0.020412715151906013,
0.00939258560538292,
0.2771010994911194,
-0.020981086418032646,
0.3817747235298157,
-0.24682985246181488,
-0.288210421... |
https://github.com/huggingface/datasets/issues/4883 | With dataloader RSS memory consumed by HF datasets monotonically increases | @stas00 my 2 cents from having looked at a LOT of memory leaks over the years, esp in Python, .3% memory increase over that many iterations of something is difficult to say with certainty it is a leak.
Also, just looking at RSS makes it hard to analyze leaks. RSS can stay near constant while you are leaking. RSS is... | ## Describe the bug
When the HF datasets is used in conjunction with PyTorch Dataloader, the RSS memory of the process keeps on increasing when it should stay constant.
## Steps to reproduce the bug
Run and observe the output of this snippet which logs RSS memory.
```python
import psutil
import os
from transf... | 98 | With dataloader RSS memory consumed by HF datasets monotonically increases
## Describe the bug
When the HF datasets is used in conjunction with PyTorch Dataloader, the RSS memory of the process keeps on increasing when it should stay constant.
## Steps to reproduce the bug
Run and observe the output of this sni... | [
-0.11197682470083237,
-0.03989267349243164,
0.13984118402004242,
0.18200340867042542,
0.23067383468151093,
-0.14632582664489746,
0.18177445232868195,
0.020412715151906013,
0.00939258560538292,
0.2771010994911194,
-0.020981086418032646,
0.3817747235298157,
-0.24682985246181488,
-0.288210421... |
https://github.com/huggingface/datasets/issues/4883 | With dataloader RSS memory consumed by HF datasets monotonically increases | yes, that's true, but unless the leak is big, I'm yet to find another measurement tool.
To prove your point here is a very simple IO in a loop program that also reads the same line all over again:
```
$ cat mmap-no-leak-debug.py
import gc
import mmap
import os
import psutil
import sys
proc = psutil.Proce... | ## Describe the bug
When the HF datasets is used in conjunction with PyTorch Dataloader, the RSS memory of the process keeps on increasing when it should stay constant.
## Steps to reproduce the bug
Run and observe the output of this snippet which logs RSS memory.
```python
import psutil
import os
from transf... | 339 | With dataloader RSS memory consumed by HF datasets monotonically increases
## Describe the bug
When the HF datasets is used in conjunction with PyTorch Dataloader, the RSS memory of the process keeps on increasing when it should stay constant.
## Steps to reproduce the bug
Run and observe the output of this sni... | [
-0.11197682470083237,
-0.03989267349243164,
0.13984118402004242,
0.18200340867042542,
0.23067383468151093,
-0.14632582664489746,
0.18177445232868195,
0.020412715151906013,
0.00939258560538292,
0.2771010994911194,
-0.020981086418032646,
0.3817747235298157,
-0.24682985246181488,
-0.288210421... |
https://github.com/huggingface/datasets/issues/4883 | With dataloader RSS memory consumed by HF datasets monotonically increases | @stas00 if you aren't using memory maps, you should be able to clearly see the increase in the virtual mem for the process as well. Even then, it could still be challenging to determine if it's leak vs fragmentation due to problematic allocation patterns (not uncommon with Python). Using a better mem allocator like tcm... | ## Describe the bug
When the HF datasets is used in conjunction with PyTorch Dataloader, the RSS memory of the process keeps on increasing when it should stay constant.
## Steps to reproduce the bug
Run and observe the output of this snippet which logs RSS memory.
```python
import psutil
import os
from transf... | 83 | With dataloader RSS memory consumed by HF datasets monotonically increases
## Describe the bug
When the HF datasets is used in conjunction with PyTorch Dataloader, the RSS memory of the process keeps on increasing when it should stay constant.
## Steps to reproduce the bug
Run and observe the output of this sni... | [
-0.11197682470083237,
-0.03989267349243164,
0.13984118402004242,
0.18200340867042542,
0.23067383468151093,
-0.14632582664489746,
0.18177445232868195,
0.020412715151906013,
0.00939258560538292,
0.2771010994911194,
-0.020981086418032646,
0.3817747235298157,
-0.24682985246181488,
-0.288210421... |
https://github.com/huggingface/datasets/issues/4881 | Language names and language codes: connecting to a big database (rather than slow enrichment of custom list) | Thanks for opening this discussion, @alexis-michaud.
As the language validation procedure is shared with other Hugging Face projects, I'm tagging them as well.
CC: @huggingface/moon-landing | **The problem:**
Language diversity is an important dimension of the diversity of datasets. To find one's way around datasets, being able to search by language name and by standardized codes appears crucial.
Currently the list of language codes is [here](https://github.com/huggingface/datasets/blob/main/src/datase... | 25 | Language names and language codes: connecting to a big database (rather than slow enrichment of custom list)
**The problem:**
Language diversity is an important dimension of the diversity of datasets. To find one's way around datasets, being able to search by language name and by standardized codes appears crucial.... | [
-0.08816187083721161,
0.15403899550437927,
-0.21726644039154053,
0.13301202654838562,
-0.0076340436935424805,
-0.01771789789199829,
-0.08835642039775848,
0.2977529466152191,
0.30438223481178284,
0.005143448710441589,
-0.18575237691402435,
-0.3358423709869385,
-0.04399453103542328,
0.024324... |
https://github.com/huggingface/datasets/issues/4881 | Language names and language codes: connecting to a big database (rather than slow enrichment of custom list) | on the Hub side, there is not fine grained validation we just check that `language:` contains an array of lowercase strings between 2 and 3 characters long =)
and for `language_bcp47:` we just check it's an array of strings.
The only page where we have a hardcoded list of languages is https://huggingface.co/langu... | **The problem:**
Language diversity is an important dimension of the diversity of datasets. To find one's way around datasets, being able to search by language name and by standardized codes appears crucial.
Currently the list of language codes is [here](https://github.com/huggingface/datasets/blob/main/src/datase... | 116 | Language names and language codes: connecting to a big database (rather than slow enrichment of custom list)
**The problem:**
Language diversity is an important dimension of the diversity of datasets. To find one's way around datasets, being able to search by language name and by standardized codes appears crucial.... | [
-0.08816187083721161,
0.15403899550437927,
-0.21726644039154053,
0.13301202654838562,
-0.0076340436935424805,
-0.01771789789199829,
-0.08835642039775848,
0.2977529466152191,
0.30438223481178284,
0.005143448710441589,
-0.18575237691402435,
-0.3358423709869385,
-0.04399453103542328,
0.024324... |
https://github.com/huggingface/datasets/issues/4881 | Language names and language codes: connecting to a big database (rather than slow enrichment of custom list) | PS @alexis-michaud is there a DB of language codes you would recommend? That would contain all `ISO 639-1, 639-2 or 639-3 codes` and be kept up to date, and ideally that would be accessible as a Node.js npm package?
cc @albertvillanova too | **The problem:**
Language diversity is an important dimension of the diversity of datasets. To find one's way around datasets, being able to search by language name and by standardized codes appears crucial.
Currently the list of language codes is [here](https://github.com/huggingface/datasets/blob/main/src/datase... | 42 | Language names and language codes: connecting to a big database (rather than slow enrichment of custom list)
**The problem:**
Language diversity is an important dimension of the diversity of datasets. To find one's way around datasets, being able to search by language name and by standardized codes appears crucial.... | [
-0.08816187083721161,
0.15403899550437927,
-0.21726644039154053,
0.13301202654838562,
-0.0076340436935424805,
-0.01771789789199829,
-0.08835642039775848,
0.2977529466152191,
0.30438223481178284,
0.005143448710441589,
-0.18575237691402435,
-0.3358423709869385,
-0.04399453103542328,
0.024324... |
https://github.com/huggingface/datasets/issues/4881 | Language names and language codes: connecting to a big database (rather than slow enrichment of custom list) | > PS @alexis-michaud is there a DB of language codes you would recommend? That would contain all `ISO 639-1, 639-2 or 639-3 codes` and be kept up to date, and ideally that would be accessible as a Node.js npm package?
>
> cc @albertvillanova too
Many thanks for your answer!
The Glottolog database is kept up t... | **The problem:**
Language diversity is an important dimension of the diversity of datasets. To find one's way around datasets, being able to search by language name and by standardized codes appears crucial.
Currently the list of language codes is [here](https://github.com/huggingface/datasets/blob/main/src/datase... | 141 | Language names and language codes: connecting to a big database (rather than slow enrichment of custom list)
**The problem:**
Language diversity is an important dimension of the diversity of datasets. To find one's way around datasets, being able to search by language name and by standardized codes appears crucial.... | [
-0.08816187083721161,
0.15403899550437927,
-0.21726644039154053,
0.13301202654838562,
-0.0076340436935424805,
-0.01771789789199829,
-0.08835642039775848,
0.2977529466152191,
0.30438223481178284,
0.005143448710441589,
-0.18575237691402435,
-0.3358423709869385,
-0.04399453103542328,
0.024324... |
https://github.com/huggingface/datasets/issues/4881 | Language names and language codes: connecting to a big database (rather than slow enrichment of custom list) | I just tried pyglottolog to generate a file with all the current IDs (first column).
`glottolog languoids` inside the `glottolog` repository.
[glottolog-languoids-v4.6-10-g5c66eec874.csv](https://github.com/huggingface/datasets/files/9417456/glottolog-languoids-v4.6-10-g5c66eec874.csv)
| **The problem:**
Language diversity is an important dimension of the diversity of datasets. To find one's way around datasets, being able to search by language name and by standardized codes appears crucial.
Currently the list of language codes is [here](https://github.com/huggingface/datasets/blob/main/src/datase... | 22 | Language names and language codes: connecting to a big database (rather than slow enrichment of custom list)
**The problem:**
Language diversity is an important dimension of the diversity of datasets. To find one's way around datasets, being able to search by language name and by standardized codes appears crucial.... | [
-0.08816187083721161,
0.15403899550437927,
-0.21726644039154053,
0.13301202654838562,
-0.0076340436935424805,
-0.01771789789199829,
-0.08835642039775848,
0.2977529466152191,
0.30438223481178284,
0.005143448710441589,
-0.18575237691402435,
-0.3358423709869385,
-0.04399453103542328,
0.024324... |
https://github.com/huggingface/datasets/issues/4881 | Language names and language codes: connecting to a big database (rather than slow enrichment of custom list) | Greetings @alexis-michaud and others,
I think perhaps a standards-based approach here would help everyone out both at the technical and social layers of technical innovations.
Let me say a few things:
1. there are multiple kinds of assets in AI that should have associated language codes.
* AI Training Data se... | **The problem:**
Language diversity is an important dimension of the diversity of datasets. To find one's way around datasets, being able to search by language name and by standardized codes appears crucial.
Currently the list of language codes is [here](https://github.com/huggingface/datasets/blob/main/src/datase... | 687 | Language names and language codes: connecting to a big database (rather than slow enrichment of custom list)
**The problem:**
Language diversity is an important dimension of the diversity of datasets. To find one's way around datasets, being able to search by language name and by standardized codes appears crucial.... | [
-0.08816187083721161,
0.15403899550437927,
-0.21726644039154053,
0.13301202654838562,
-0.0076340436935424805,
-0.01771789789199829,
-0.08835642039775848,
0.2977529466152191,
0.30438223481178284,
0.005143448710441589,
-0.18575237691402435,
-0.3358423709869385,
-0.04399453103542328,
0.024324... |
https://github.com/huggingface/datasets/issues/4881 | Language names and language codes: connecting to a big database (rather than slow enrichment of custom list) | Hi everybody!
About the point:
> also cc'ing @lbourdois who's been active and helpful on those subjects in the past!
Discussions on the need to improve the Hub's tagging system (applying to both datasets and models) can be found in the following discussion: https://github.com/huggingface/hub-docs/issues/193
Onc... | **The problem:**
Language diversity is an important dimension of the diversity of datasets. To find one's way around datasets, being able to search by language name and by standardized codes appears crucial.
Currently the list of language codes is [here](https://github.com/huggingface/datasets/blob/main/src/datase... | 590 | Language names and language codes: connecting to a big database (rather than slow enrichment of custom list)
**The problem:**
Language diversity is an important dimension of the diversity of datasets. To find one's way around datasets, being able to search by language name and by standardized codes appears crucial.... | [
-0.08816187083721161,
0.15403899550437927,
-0.21726644039154053,
0.13301202654838562,
-0.0076340436935424805,
-0.01771789789199829,
-0.08835642039775848,
0.2977529466152191,
0.30438223481178284,
0.005143448710441589,
-0.18575237691402435,
-0.3358423709869385,
-0.04399453103542328,
0.024324... |
https://github.com/huggingface/datasets/issues/4881 | Language names and language codes: connecting to a big database (rather than slow enrichment of custom list) | > I invite you to read them. But as a quick summary, the exchanges were oriented towards the ISO standard (the first HF system was based on it and it is generally the standard indicated in AI/DL papers) by favouring ISO 639-1 if it exists, and fallback to ISO 639-2 or ISO 639-3 if it doesn't. In addition, it is possibl... | **The problem:**
Language diversity is an important dimension of the diversity of datasets. To find one's way around datasets, being able to search by language name and by standardized codes appears crucial.
Currently the list of language codes is [here](https://github.com/huggingface/datasets/blob/main/src/datase... | 311 | Language names and language codes: connecting to a big database (rather than slow enrichment of custom list)
**The problem:**
Language diversity is an important dimension of the diversity of datasets. To find one's way around datasets, being able to search by language name and by standardized codes appears crucial.... | [
-0.08816187083721161,
0.15403899550437927,
-0.21726644039154053,
0.13301202654838562,
-0.0076340436935424805,
-0.01771789789199829,
-0.08835642039775848,
0.2977529466152191,
0.30438223481178284,
0.005143448710441589,
-0.18575237691402435,
-0.3358423709869385,
-0.04399453103542328,
0.024324... |
https://github.com/huggingface/datasets/issues/4881 | Language names and language codes: connecting to a big database (rather than slow enrichment of custom list) | > * Are there any databases that take into account all the existing sign languages in the world?
> It would be nice to have them included on the Hub.
Sign Languages present an interesting case. As I understand the situation. The identification of sign languages has been identified as a component of their endangerme... | **The problem:**
Language diversity is an important dimension of the diversity of datasets. To find one's way around datasets, being able to search by language name and by standardized codes appears crucial.
Currently the list of language codes is [here](https://github.com/huggingface/datasets/blob/main/src/datase... | 136 | Language names and language codes: connecting to a big database (rather than slow enrichment of custom list)
**The problem:**
Language diversity is an important dimension of the diversity of datasets. To find one's way around datasets, being able to search by language name and by standardized codes appears crucial.... | [
-0.08816187083721161,
0.15403899550437927,
-0.21726644039154053,
0.13301202654838562,
-0.0076340436935424805,
-0.01771789789199829,
-0.08835642039775848,
0.2977529466152191,
0.30438223481178284,
0.005143448710441589,
-0.18575237691402435,
-0.3358423709869385,
-0.04399453103542328,
0.024324... |
https://github.com/huggingface/datasets/issues/4881 | Language names and language codes: connecting to a big database (rather than slow enrichment of custom list) | > * Is there an international classification of languages?
> A bit like the [International Classification of Diseases](https://en.wikipedia.org/wiki/International_Classification_of_Diseases) in medicine, which is established by the WHO and used as a reference throughout the world. The idea would be to have a precise... | **The problem:**
Language diversity is an important dimension of the diversity of datasets. To find one's way around datasets, being able to search by language name and by standardized codes appears crucial.
Currently the list of language codes is [here](https://github.com/huggingface/datasets/blob/main/src/datase... | 168 | Language names and language codes: connecting to a big database (rather than slow enrichment of custom list)
**The problem:**
Language diversity is an important dimension of the diversity of datasets. To find one's way around datasets, being able to search by language name and by standardized codes appears crucial.... | [
-0.08816187083721161,
0.15403899550437927,
-0.21726644039154053,
0.13301202654838562,
-0.0076340436935424805,
-0.01771789789199829,
-0.08835642039775848,
0.2977529466152191,
0.30438223481178284,
0.005143448710441589,
-0.18575237691402435,
-0.3358423709869385,
-0.04399453103542328,
0.024324... |
https://github.com/huggingface/datasets/issues/4881 | Language names and language codes: connecting to a big database (rather than slow enrichment of custom list) | >* When you look up a language on Wikipedia, it usually shows, in addition to the ISO standard, the codes in the Glottolog (which you have already mentioned), [ELP](https://www.endangeredlanguages.com/?hl=en) and [Linguasphere](http://www.linguasphere.info/jr/index.php?l1=home&l2=welcome) databases. Would you have any ... | **The problem:**
Language diversity is an important dimension of the diversity of datasets. To find one's way around datasets, being able to search by language name and by standardized codes appears crucial.
Currently the list of language codes is [here](https://github.com/huggingface/datasets/blob/main/src/datase... | 135 | Language names and language codes: connecting to a big database (rather than slow enrichment of custom list)
**The problem:**
Language diversity is an important dimension of the diversity of datasets. To find one's way around datasets, being able to search by language name and by standardized codes appears crucial.... | [
-0.08816187083721161,
0.15403899550437927,
-0.21726644039154053,
0.13301202654838562,
-0.0076340436935424805,
-0.01771789789199829,
-0.08835642039775848,
0.2977529466152191,
0.30438223481178284,
0.005143448710441589,
-0.18575237691402435,
-0.3358423709869385,
-0.04399453103542328,
0.024324... |
https://github.com/huggingface/datasets/issues/4881 | Language names and language codes: connecting to a big database (rather than slow enrichment of custom list) | > * Do you think it's possible to easily handle tags that have been deprecated potentially for decades?
>For example (I'm taking the case of Hebrew but this has happened for other languages) I [tag](https://huggingface.co/models?language=iw&sort=downloads)ged Google models with the "iw" tag because I based it on what ... | **The problem:**
Language diversity is an important dimension of the diversity of datasets. To find one's way around datasets, being able to search by language name and by standardized codes appears crucial.
Currently the list of language codes is [here](https://github.com/huggingface/datasets/blob/main/src/datase... | 150 | Language names and language codes: connecting to a big database (rather than slow enrichment of custom list)
**The problem:**
Language diversity is an important dimension of the diversity of datasets. To find one's way around datasets, being able to search by language name and by standardized codes appears crucial.... | [
-0.08816187083721161,
0.15403899550437927,
-0.21726644039154053,
0.13301202654838562,
-0.0076340436935424805,
-0.01771789789199829,
-0.08835642039775848,
0.2977529466152191,
0.30438223481178284,
0.005143448710441589,
-0.18575237691402435,
-0.3358423709869385,
-0.04399453103542328,
0.024324... |
https://github.com/huggingface/datasets/issues/4881 | Language names and language codes: connecting to a big database (rather than slow enrichment of custom list) | > * On the Hub, there is the following dataset where French people speak in English: https://huggingface.co/datasets/Datatang/French_Speaking_English_Speech_Data_by_Mobile_Phone
Is there a database to take this case into account? I have not found any code in the Glottolog database. If based on an IETF BCP-47 standard,... | **The problem:**
Language diversity is an important dimension of the diversity of datasets. To find one's way around datasets, being able to search by language name and by standardized codes appears crucial.
Currently the list of language codes is [here](https://github.com/huggingface/datasets/blob/main/src/datase... | 493 | Language names and language codes: connecting to a big database (rather than slow enrichment of custom list)
**The problem:**
Language diversity is an important dimension of the diversity of datasets. To find one's way around datasets, being able to search by language name and by standardized codes appears crucial.... | [
-0.08816187083721161,
0.15403899550437927,
-0.21726644039154053,
0.13301202654838562,
-0.0076340436935424805,
-0.01771789789199829,
-0.08835642039775848,
0.2977529466152191,
0.30438223481178284,
0.005143448710441589,
-0.18575237691402435,
-0.3358423709869385,
-0.04399453103542328,
0.024324... |
https://github.com/huggingface/datasets/issues/4881 | Language names and language codes: connecting to a big database (rather than slow enrichment of custom list) | Hi @lbourdois ! Many thanks for the detailed information.
> Discussions on the need to improve the Hub's tagging system (applying to both datasets and models) can be found in the following discussion: [huggingface/hub-docs#193](https://github.com/huggingface/hub-docs/issues/193)
Fascinating topic! To me, the follo... | **The problem:**
Language diversity is an important dimension of the diversity of datasets. To find one's way around datasets, being able to search by language name and by standardized codes appears crucial.
Currently the list of language codes is [here](https://github.com/huggingface/datasets/blob/main/src/datase... | 1,285 | Language names and language codes: connecting to a big database (rather than slow enrichment of custom list)
**The problem:**
Language diversity is an important dimension of the diversity of datasets. To find one's way around datasets, being able to search by language name and by standardized codes appears crucial.... | [
-0.08816187083721161,
0.15403899550437927,
-0.21726644039154053,
0.13301202654838562,
-0.0076340436935424805,
-0.01771789789199829,
-0.08835642039775848,
0.2977529466152191,
0.30438223481178284,
0.005143448710441589,
-0.18575237691402435,
-0.3358423709869385,
-0.04399453103542328,
0.024324... |
https://github.com/huggingface/datasets/issues/4881 | Language names and language codes: connecting to a big database (rather than slow enrichment of custom list) | > The idea of letting people use their favourite nomenclature and automatically adding the ISO 639-3 three-letter code as a tag is appealing. Thus all the HF datasets would have three-letter language tags (handy for basic search), alongside the authors' preferred tags and language names (including Glottolog tags as wel... | **The problem:**
Language diversity is an important dimension of the diversity of datasets. To find one's way around datasets, being able to search by language name and by standardized codes appears crucial.
Currently the list of language codes is [here](https://github.com/huggingface/datasets/blob/main/src/datase... | 421 | Language names and language codes: connecting to a big database (rather than slow enrichment of custom list)
**The problem:**
Language diversity is an important dimension of the diversity of datasets. To find one's way around datasets, being able to search by language name and by standardized codes appears crucial.... | [
-0.08816187083721161,
0.15403899550437927,
-0.21726644039154053,
0.13301202654838562,
-0.0076340436935424805,
-0.01771789789199829,
-0.08835642039775848,
0.2977529466152191,
0.30438223481178284,
0.005143448710441589,
-0.18575237691402435,
-0.3358423709869385,
-0.04399453103542328,
0.024324... |
https://github.com/huggingface/datasets/issues/4881 | Language names and language codes: connecting to a big database (rather than slow enrichment of custom list) | To get a visual idea of these first exchanges, I coded a Streamlit app that I put online on Spaces: https://huggingface.co/spaces/lbourdois/Language-tags-demo.
The code is in Python so I don't know if it can be used by HF who seems to need something in Node.js but it serves as a proof of concept. The advantage is als... | **The problem:**
Language diversity is an important dimension of the diversity of datasets. To find one's way around datasets, being able to search by language name and by standardized codes appears crucial.
Currently the list of language codes is [here](https://github.com/huggingface/datasets/blob/main/src/datase... | 920 | Language names and language codes: connecting to a big database (rather than slow enrichment of custom list)
**The problem:**
Language diversity is an important dimension of the diversity of datasets. To find one's way around datasets, being able to search by language name and by standardized codes appears crucial.... | [
-0.08816187083721161,
0.15403899550437927,
-0.21726644039154053,
0.13301202654838562,
-0.0076340436935424805,
-0.01771789789199829,
-0.08835642039775848,
0.2977529466152191,
0.30438223481178284,
0.005143448710441589,
-0.18575237691402435,
-0.3358423709869385,
-0.04399453103542328,
0.024324... |
https://github.com/huggingface/datasets/issues/4881 | Language names and language codes: connecting to a big database (rather than slow enrichment of custom list) | Very impressive! Using the prompt 'Japhug' (a language name), the app finds the intended language:
A first question: based on the Glottocode, would it be possible to grab the closest ISO639-3 code? In case... | **The problem:**
Language diversity is an important dimension of the diversity of datasets. To find one's way around datasets, being able to search by language name and by standardized codes appears crucial.
Currently the list of language codes is [here](https://github.com/huggingface/datasets/blob/main/src/datase... | 127 | Language names and language codes: connecting to a big database (rather than slow enrichment of custom list)
**The problem:**
Language diversity is an important dimension of the diversity of datasets. To find one's way around datasets, being able to search by language name and by standardized codes appears crucial.... | [
-0.08816187083721161,
0.15403899550437927,
-0.21726644039154053,
0.13301202654838562,
-0.0076340436935424805,
-0.01771789789199829,
-0.08835642039775848,
0.2977529466152191,
0.30438223481178284,
0.005143448710441589,
-0.18575237691402435,
-0.3358423709869385,
-0.04399453103542328,
0.024324... |
https://github.com/huggingface/datasets/issues/4881 | Language names and language codes: connecting to a big database (rather than slow enrichment of custom list) | > on line 1 of the database, we can see that the Glottocode database gives an ISO 639-3 code (column ISO639P3code) but not the ISO 639 database (column 639-3). Do you have an explanation for this phenomenon?
That is because the language name 'Aewa' is not found in the Ethnologue (ISO 639-3) export that you are using... | **The problem:**
Language diversity is an important dimension of the diversity of datasets. To find one's way around datasets, being able to search by language name and by standardized codes appears crucial.
Currently the list of language codes is [here](https://github.com/huggingface/datasets/blob/main/src/datase... | 236 | Language names and language codes: connecting to a big database (rather than slow enrichment of custom list)
**The problem:**
Language diversity is an important dimension of the diversity of datasets. To find one's way around datasets, being able to search by language name and by standardized codes appears crucial.... | [
-0.08816187083721161,
0.15403899550437927,
-0.21726644039154053,
0.13301202654838562,
-0.0076340436935424805,
-0.01771789789199829,
-0.08835642039775848,
0.2977529466152191,
0.30438223481178284,
0.005143448710441589,
-0.18575237691402435,
-0.3358423709869385,
-0.04399453103542328,
0.024324... |
https://github.com/huggingface/datasets/issues/4881 | Language names and language codes: connecting to a big database (rather than slow enrichment of custom list) | I will add these two points to my TODO list.
- Since Glottolog can be trust, I will add a condition to the code that if there is no ISO 639-3 code in the "official" database (https://iso639-3.sil.org/sites/iso639-3/files/downloads/iso-639-3.tab), look for it in the "ISO639P3code" column of Glottolog.
- For the point ... | **The problem:**
Language diversity is an important dimension of the diversity of datasets. To find one's way around datasets, being able to search by language name and by standardized codes appears crucial.
Currently the list of language codes is [here](https://github.com/huggingface/datasets/blob/main/src/datase... | 106 | Language names and language codes: connecting to a big database (rather than slow enrichment of custom list)
**The problem:**
Language diversity is an important dimension of the diversity of datasets. To find one's way around datasets, being able to search by language name and by standardized codes appears crucial.... | [
-0.08816187083721161,
0.15403899550437927,
-0.21726644039154053,
0.13301202654838562,
-0.0076340436935424805,
-0.01771789789199829,
-0.08835642039775848,
0.2977529466152191,
0.30438223481178284,
0.005143448710441589,
-0.18575237691402435,
-0.3358423709869385,
-0.04399453103542328,
0.024324... |
https://github.com/huggingface/datasets/issues/4881 | Language names and language codes: connecting to a big database (rather than slow enrichment of custom list) | > * Integrate ISO 3166-1 alpha 2 territories (https://www.iso.org/obp/ui#iso:pub:PUB500001:en)? They offer a finer granularity than ISO 3166-1 alpha 1 which is limited to the country level, but they are very administrative (for French, ISO 3166-1 alpha 2 gives us the "départements" for example).
I'm concerned with t... | **The problem:**
Language diversity is an important dimension of the diversity of datasets. To find one's way around datasets, being able to search by language name and by standardized codes appears crucial.
Currently the list of language codes is [here](https://github.com/huggingface/datasets/blob/main/src/datase... | 115 | Language names and language codes: connecting to a big database (rather than slow enrichment of custom list)
**The problem:**
Language diversity is an important dimension of the diversity of datasets. To find one's way around datasets, being able to search by language name and by standardized codes appears crucial.... | [
-0.08816187083721161,
0.15403899550437927,
-0.21726644039154053,
0.13301202654838562,
-0.0076340436935424805,
-0.01771789789199829,
-0.08835642039775848,
0.2977529466152191,
0.30438223481178284,
0.005143448710441589,
-0.18575237691402435,
-0.3358423709869385,
-0.04399453103542328,
0.024324... |
https://github.com/huggingface/datasets/issues/4881 | Language names and language codes: connecting to a big database (rather than slow enrichment of custom list) | Good job for the application!
> On the Hub, there is the following dataset where French people speak in English: https://huggingface.co/datasets/Datatang/French_Speaking_English_Speech_Data_by_Mobile_Phone
Is there a database to take this case into account? I have not found any code in the Glottolog databa... | **The problem:**
Language diversity is an important dimension of the diversity of datasets. To find one's way around datasets, being able to search by language name and by standardized codes appears crucial.
Currently the list of language codes is [here](https://github.com/huggingface/datasets/blob/main/src/datase... | 699 | Language names and language codes: connecting to a big database (rather than slow enrichment of custom list)
**The problem:**
Language diversity is an important dimension of the diversity of datasets. To find one's way around datasets, being able to search by language name and by standardized codes appears crucial.... | [
-0.08816187083721161,
0.15403899550437927,
-0.21726644039154053,
0.13301202654838562,
-0.0076340436935424805,
-0.01771789789199829,
-0.08835642039775848,
0.2977529466152191,
0.30438223481178284,
0.005143448710441589,
-0.18575237691402435,
-0.3358423709869385,
-0.04399453103542328,
0.024324... |
https://github.com/huggingface/datasets/issues/4881 | Language names and language codes: connecting to a big database (rather than slow enrichment of custom list) | > To get a visual idea of these first exchanges, I coded a Streamlit app that I put online on Spaces: https://huggingface.co/spaces/lbourdois/Language-tags-demo.
> The code is in Python so I don't know if it can be used by HF who seems to need something in Node.js but it serves as a proof of concept. The advantage is ... | **The problem:**
Language diversity is an important dimension of the diversity of datasets. To find one's way around datasets, being able to search by language name and by standardized codes appears crucial.
Currently the list of language codes is [here](https://github.com/huggingface/datasets/blob/main/src/datase... | 201 | Language names and language codes: connecting to a big database (rather than slow enrichment of custom list)
**The problem:**
Language diversity is an important dimension of the diversity of datasets. To find one's way around datasets, being able to search by language name and by standardized codes appears crucial.... | [
-0.08816187083721161,
0.15403899550437927,
-0.21726644039154053,
0.13301202654838562,
-0.0076340436935424805,
-0.01771789789199829,
-0.08835642039775848,
0.2977529466152191,
0.30438223481178284,
0.005143448710441589,
-0.18575237691402435,
-0.3358423709869385,
-0.04399453103542328,
0.024324... |
https://github.com/huggingface/datasets/issues/4881 | Language names and language codes: connecting to a big database (rather than slow enrichment of custom list) | > In practice, what I do is if we enter `fr-CA` is that the letters before the `-` refer to a language in the `Name` column for a `639-1` == `fr` (`639-3` for `fra` or `fre`) in the base of my image above. Then I look at the letters after the `-` which refers to a territory. It comes out `French (Canada)`. I used https... | **The problem:**
Language diversity is an important dimension of the diversity of datasets. To find one's way around datasets, being able to search by language name and by standardized codes appears crucial.
Currently the list of language codes is [here](https://github.com/huggingface/datasets/blob/main/src/datase... | 120 | Language names and language codes: connecting to a big database (rather than slow enrichment of custom list)
**The problem:**
Language diversity is an important dimension of the diversity of datasets. To find one's way around datasets, being able to search by language name and by standardized codes appears crucial.... | [
-0.08816187083721161,
0.15403899550437927,
-0.21726644039154053,
0.13301202654838562,
-0.0076340436935424805,
-0.01771789789199829,
-0.08835642039775848,
0.2977529466152191,
0.30438223481178284,
0.005143448710441589,
-0.18575237691402435,
-0.3358423709869385,
-0.04399453103542328,
0.024324... |
https://github.com/huggingface/datasets/issues/4881 | Language names and language codes: connecting to a big database (rather than slow enrichment of custom list) | > A first question: based on the Glottocode, would it be possible to grab the closest ISO639-3 code? In case there is no match for the exact language variety, one needs to explore the higher-level groupings, level by level. For this language (Japhug), the information provided in the extracted CSV file (`glottolog-langu... | **The problem:**
Language diversity is an important dimension of the diversity of datasets. To find one's way around datasets, being able to search by language name and by standardized codes appears crucial.
Currently the list of language codes is [here](https://github.com/huggingface/datasets/blob/main/src/datase... | 198 | Language names and language codes: connecting to a big database (rather than slow enrichment of custom list)
**The problem:**
Language diversity is an important dimension of the diversity of datasets. To find one's way around datasets, being able to search by language name and by standardized codes appears crucial.... | [
-0.08816187083721161,
0.15403899550437927,
-0.21726644039154053,
0.13301202654838562,
-0.0076340436935424805,
-0.01771789789199829,
-0.08835642039775848,
0.2977529466152191,
0.30438223481178284,
0.005143448710441589,
-0.18575237691402435,
-0.3358423709869385,
-0.04399453103542328,
0.024324... |
https://github.com/huggingface/datasets/issues/4881 | Language names and language codes: connecting to a big database (rather than slow enrichment of custom list) | @lbourdois
> * Since Glottolog can be trust, I will add a condition to the code that if there is no ISO 639-3 code in the "official" database (https://iso639-3.sil.org/sites/iso639-3/files/downloads/iso-639-3.tab), look for it in the "ISO639P3code" column of Glottolog.
I'm confused here... if there is no ISO639-3 ... | **The problem:**
Language diversity is an important dimension of the diversity of datasets. To find one's way around datasets, being able to search by language name and by standardized codes appears crucial.
Currently the list of language codes is [here](https://github.com/huggingface/datasets/blob/main/src/datase... | 71 | Language names and language codes: connecting to a big database (rather than slow enrichment of custom list)
**The problem:**
Language diversity is an important dimension of the diversity of datasets. To find one's way around datasets, being able to search by language name and by standardized codes appears crucial.... | [
-0.08816187083721161,
0.15403899550437927,
-0.21726644039154053,
0.13301202654838562,
-0.0076340436935424805,
-0.01771789789199829,
-0.08835642039775848,
0.2977529466152191,
0.30438223481178284,
0.005143448710441589,
-0.18575237691402435,
-0.3358423709869385,
-0.04399453103542328,
0.024324... |
https://github.com/huggingface/datasets/issues/4881 | Language names and language codes: connecting to a big database (rather than slow enrichment of custom list) | > For the point of adding the closest ISO 639-3 code for a Glottolog code, what convention should be adopted for the output? Just the ISO 639-3 code, or the ISO 639-3 code - Glottolog code, or the ISO 639-3 code - language name?
To use the example of Japhug , should it be just jya, or jya-japh1234 or jya-Japhug?
(a... | **The problem:**
Language diversity is an important dimension of the diversity of datasets. To find one's way around datasets, being able to search by language name and by standardized codes appears crucial.
Currently the list of language codes is [here](https://github.com/huggingface/datasets/blob/main/src/datase... | 331 | Language names and language codes: connecting to a big database (rather than slow enrichment of custom list)
**The problem:**
Language diversity is an important dimension of the diversity of datasets. To find one's way around datasets, being able to search by language name and by standardized codes appears crucial.... | [
-0.08816187083721161,
0.15403899550437927,
-0.21726644039154053,
0.13301202654838562,
-0.0076340436935424805,
-0.01771789789199829,
-0.08835642039775848,
0.2977529466152191,
0.30438223481178284,
0.005143448710441589,
-0.18575237691402435,
-0.3358423709869385,
-0.04399453103542328,
0.024324... |
https://github.com/huggingface/datasets/issues/4881 | Language names and language codes: connecting to a big database (rather than slow enrichment of custom list) | The problem seems to have already been raised here: https://drops.dagstuhl.de/opus/volltexte/2019/10368/pdf/OASIcs-LDK-2019-4.pdf
An example can be seen here :
> 3.1.2 The use of privateuse sub-tag
In light of unambiguous language codes being available for the two Khoisan varieties, we
propose to combine the IS... | **The problem:**
Language diversity is an important dimension of the diversity of datasets. To find one's way around datasets, being able to search by language name and by standardized codes appears crucial.
Currently the list of language codes is [here](https://github.com/huggingface/datasets/blob/main/src/datase... | 92 | Language names and language codes: connecting to a big database (rather than slow enrichment of custom list)
**The problem:**
Language diversity is an important dimension of the diversity of datasets. To find one's way around datasets, being able to search by language name and by standardized codes appears crucial.... | [
-0.08816187083721161,
0.15403899550437927,
-0.21726644039154053,
0.13301202654838562,
-0.0076340436935424805,
-0.01771789789199829,
-0.08835642039775848,
0.2977529466152191,
0.30438223481178284,
0.005143448710441589,
-0.18575237691402435,
-0.3358423709869385,
-0.04399453103542328,
0.024324... |
https://github.com/huggingface/datasets/issues/4881 | Language names and language codes: connecting to a big database (rather than slow enrichment of custom list) | > > * Since Glottolog can be trust, I will add a condition to the code that if there is no ISO 639-3 code in the "official" database (https://iso639-3.sil.org/sites/iso639-3/files/downloads/iso-639-3.tab), look for it in the "ISO639P3code" column of Glottolog.
>
> I'm confused here... if there is no ISO639-3 code in... | **The problem:**
Language diversity is an important dimension of the diversity of datasets. To find one's way around datasets, being able to search by language name and by standardized codes appears crucial.
Currently the list of language codes is [here](https://github.com/huggingface/datasets/blob/main/src/datase... | 242 | Language names and language codes: connecting to a big database (rather than slow enrichment of custom list)
**The problem:**
Language diversity is an important dimension of the diversity of datasets. To find one's way around datasets, being able to search by language name and by standardized codes appears crucial.... | [
-0.08816187083721161,
0.15403899550437927,
-0.21726644039154053,
0.13301202654838562,
-0.0076340436935424805,
-0.01771789789199829,
-0.08835642039775848,
0.2977529466152191,
0.30438223481178284,
0.005143448710441589,
-0.18575237691402435,
-0.3358423709869385,
-0.04399453103542328,
0.024324... |
https://github.com/huggingface/datasets/issues/4881 | Language names and language codes: connecting to a big database (rather than slow enrichment of custom list) | > By the way, while searching for this, I came across this application: https://huggingface.co/spaces/cdleong/langcode-search
Really relevant Space, so tagging its author @cdleong, just in case! | **The problem:**
Language diversity is an important dimension of the diversity of datasets. To find one's way around datasets, being able to search by language name and by standardized codes appears crucial.
Currently the list of language codes is [here](https://github.com/huggingface/datasets/blob/main/src/datase... | 25 | Language names and language codes: connecting to a big database (rather than slow enrichment of custom list)
**The problem:**
Language diversity is an important dimension of the diversity of datasets. To find one's way around datasets, being able to search by language name and by standardized codes appears crucial.... | [
-0.08816187083721161,
0.15403899550437927,
-0.21726644039154053,
0.13301202654838562,
-0.0076340436935424805,
-0.01771789789199829,
-0.08835642039775848,
0.2977529466152191,
0.30438223481178284,
0.005143448710441589,
-0.18575237691402435,
-0.3358423709869385,
-0.04399453103542328,
0.024324... |
https://github.com/huggingface/datasets/issues/4881 | Language names and language codes: connecting to a big database (rather than slow enrichment of custom list) | @cdleong A one-stop shop for language codes: terrific!
How do you feel about the use of Glottocodes? When searching the language names 'Japhug' and 'Yongning Na' (real examples, related to a HF Datasets deposit & various research projects), the relevant Glottocodes are retrieved, and that is great (and not that easy, ... | **The problem:**
Language diversity is an important dimension of the diversity of datasets. To find one's way around datasets, being able to search by language name and by standardized codes appears crucial.
Currently the list of language codes is [here](https://github.com/huggingface/datasets/blob/main/src/datase... | 249 | Language names and language codes: connecting to a big database (rather than slow enrichment of custom list)
**The problem:**
Language diversity is an important dimension of the diversity of datasets. To find one's way around datasets, being able to search by language name and by standardized codes appears crucial.... | [
-0.08816187083721161,
0.15403899550437927,
-0.21726644039154053,
0.13301202654838562,
-0.0076340436935424805,
-0.01771789789199829,
-0.08835642039775848,
0.2977529466152191,
0.30438223481178284,
0.005143448710441589,
-0.18575237691402435,
-0.3358423709869385,
-0.04399453103542328,
0.024324... |
https://github.com/huggingface/datasets/issues/4876 | Move DatasetInfo from `datasets_infos.json` to the YAML tags in `README.md` | Love this in principle 🚀
Let's keep in mind users might rely on `dataset_infos.json` already.
I'm not convinced by the two-syntax solution, wouldn't it be simpler to have only one syntax with a `default` config for datasets with only one config? ie, always having the `configs` field. This makes parsing the meta... | Currently there are two places to find metadata for datasets:
- datasets_infos.json, which contains **per dataset config**
- description
- citation
- license
- splits and sizes
- checksums of the data files
- feature types
- and more
- YAML tags, which contain
- license
- language
- trai... | 111 | Move DatasetInfo from `datasets_infos.json` to the YAML tags in `README.md`
Currently there are two places to find metadata for datasets:
- datasets_infos.json, which contains **per dataset config**
- description
- citation
- license
- splits and sizes
- checksums of the data files
- feature types
... | [
0.0013892464339733124,
0.22179293632507324,
-0.021893955767154694,
0.2056550830602646,
0.4584723114967346,
0.3661663830280304,
0.19599571824073792,
0.5665823817253113,
-0.06621095538139343,
0.026283271610736847,
-0.14909374713897705,
0.4044564366340637,
0.20290599763393402,
0.2336096018552... |
https://github.com/huggingface/datasets/issues/4876 | Move DatasetInfo from `datasets_infos.json` to the YAML tags in `README.md` | > Let's keep in mind users might rely on dataset_infos.json already.
Yea we'll full full backward compatibility
> Let's also keep in mind that extracting YAML metadata from a markdown readme is a bit more fastidious for users than just parsing a JSON file.
The main things that may use or ingest these data IMO ... | Currently there are two places to find metadata for datasets:
- datasets_infos.json, which contains **per dataset config**
- description
- citation
- license
- splits and sizes
- checksums of the data files
- feature types
- and more
- YAML tags, which contain
- license
- language
- trai... | 195 | Move DatasetInfo from `datasets_infos.json` to the YAML tags in `README.md`
Currently there are two places to find metadata for datasets:
- datasets_infos.json, which contains **per dataset config**
- description
- citation
- license
- splits and sizes
- checksums of the data files
- feature types
... | [
0.0013892464339733124,
0.22179293632507324,
-0.021893955767154694,
0.2056550830602646,
0.4584723114967346,
0.3661663830280304,
0.19599571824073792,
0.5665823817253113,
-0.06621095538139343,
0.026283271610736847,
-0.14909374713897705,
0.4044564366340637,
0.20290599763393402,
0.2336096018552... |
https://github.com/huggingface/datasets/issues/4876 | Move DatasetInfo from `datasets_infos.json` to the YAML tags in `README.md` | love the idea, and the trend in general to move more things (like tasks) to a single place (YAML).
also, if you browse files on a dataset's page (in "Files and versions"), raw `README.md` files looks nice and readable, while `.json` files are just one long line that users need to scroll.
> Let's also keep in min... | Currently there are two places to find metadata for datasets:
- datasets_infos.json, which contains **per dataset config**
- description
- citation
- license
- splits and sizes
- checksums of the data files
- feature types
- and more
- YAML tags, which contain
- license
- language
- trai... | 86 | Move DatasetInfo from `datasets_infos.json` to the YAML tags in `README.md`
Currently there are two places to find metadata for datasets:
- datasets_infos.json, which contains **per dataset config**
- description
- citation
- license
- splits and sizes
- checksums of the data files
- feature types
... | [
0.0013892464339733124,
0.22179293632507324,
-0.021893955767154694,
0.2056550830602646,
0.4584723114967346,
0.3661663830280304,
0.19599571824073792,
0.5665823817253113,
-0.06621095538139343,
0.026283271610736847,
-0.14909374713897705,
0.4044564366340637,
0.20290599763393402,
0.2336096018552... |
https://github.com/huggingface/datasets/issues/4876 | Move DatasetInfo from `datasets_infos.json` to the YAML tags in `README.md` | > do users often parse datasets_infos.json file themselves?
Not AFAIK, but I'm sure there should be a few users.
Users that access these info via the `DatasetInfo` from `datasets` won't see the change though e.g.
```python
>> from datasets import get_datasets_infos
>>> get_datasets_infos("squad")
{'plain_text':... | Currently there are two places to find metadata for datasets:
- datasets_infos.json, which contains **per dataset config**
- description
- citation
- license
- splits and sizes
- checksums of the data files
- feature types
- and more
- YAML tags, which contain
- license
- language
- trai... | 49 | Move DatasetInfo from `datasets_infos.json` to the YAML tags in `README.md`
Currently there are two places to find metadata for datasets:
- datasets_infos.json, which contains **per dataset config**
- description
- citation
- license
- splits and sizes
- checksums of the data files
- feature types
... | [
0.0013892464339733124,
0.22179293632507324,
-0.021893955767154694,
0.2056550830602646,
0.4584723114967346,
0.3661663830280304,
0.19599571824073792,
0.5665823817253113,
-0.06621095538139343,
0.026283271610736847,
-0.14909374713897705,
0.4044564366340637,
0.20290599763393402,
0.2336096018552... |
https://github.com/huggingface/datasets/issues/4876 | Move DatasetInfo from `datasets_infos.json` to the YAML tags in `README.md` | > Maybe one single syntax like this then ?
LGTM!
> The main things that may use or ingest these data IMO are:
> - users in the UI or IDE
> - datasets to populate DatasetInfo python object
> - moon landing which is already parsing YAML
Fair point!
Having dataset info in the README's YAML is great for API ... | Currently there are two places to find metadata for datasets:
- datasets_infos.json, which contains **per dataset config**
- description
- citation
- license
- splits and sizes
- checksums of the data files
- feature types
- and more
- YAML tags, which contain
- license
- language
- trai... | 80 | Move DatasetInfo from `datasets_infos.json` to the YAML tags in `README.md`
Currently there are two places to find metadata for datasets:
- datasets_infos.json, which contains **per dataset config**
- description
- citation
- license
- splits and sizes
- checksums of the data files
- feature types
... | [
0.0013892464339733124,
0.22179293632507324,
-0.021893955767154694,
0.2056550830602646,
0.4584723114967346,
0.3661663830280304,
0.19599571824073792,
0.5665823817253113,
-0.06621095538139343,
0.026283271610736847,
-0.14909374713897705,
0.4044564366340637,
0.20290599763393402,
0.2336096018552... |
https://github.com/huggingface/datasets/issues/4876 | Move DatasetInfo from `datasets_infos.json` to the YAML tags in `README.md` | Very supportive of this!
Nesting an array of configs inside `dataset_infos: ` sounds good to me. One small tweak is that `config: default` can be optional for the default config (which can be the first one by convention)
We'll be able to implement metadata validation on the Hub side so we ensure that those metada... | Currently there are two places to find metadata for datasets:
- datasets_infos.json, which contains **per dataset config**
- description
- citation
- license
- splits and sizes
- checksums of the data files
- feature types
- and more
- YAML tags, which contain
- license
- language
- trai... | 181 | Move DatasetInfo from `datasets_infos.json` to the YAML tags in `README.md`
Currently there are two places to find metadata for datasets:
- datasets_infos.json, which contains **per dataset config**
- description
- citation
- license
- splits and sizes
- checksums of the data files
- feature types
... | [
0.0013892464339733124,
0.22179293632507324,
-0.021893955767154694,
0.2056550830602646,
0.4584723114967346,
0.3661663830280304,
0.19599571824073792,
0.5665823817253113,
-0.06621095538139343,
0.026283271610736847,
-0.14909374713897705,
0.4044564366340637,
0.20290599763393402,
0.2336096018552... |
https://github.com/huggingface/datasets/issues/4876 | Move DatasetInfo from `datasets_infos.json` to the YAML tags in `README.md` | re: `config: default`
Note also that the default config is not named `default`, afaiu, but create from the repo name, eg: https://huggingface.co/datasets/nbtpj/bionlp2021SAS default config is `nbtpj--bionlp2021SAS` (which is awful) | Currently there are two places to find metadata for datasets:
- datasets_infos.json, which contains **per dataset config**
- description
- citation
- license
- splits and sizes
- checksums of the data files
- feature types
- and more
- YAML tags, which contain
- license
- language
- trai... | 29 | Move DatasetInfo from `datasets_infos.json` to the YAML tags in `README.md`
Currently there are two places to find metadata for datasets:
- datasets_infos.json, which contains **per dataset config**
- description
- citation
- license
- splits and sizes
- checksums of the data files
- feature types
... | [
0.0013892464339733124,
0.22179293632507324,
-0.021893955767154694,
0.2056550830602646,
0.4584723114967346,
0.3661663830280304,
0.19599571824073792,
0.5665823817253113,
-0.06621095538139343,
0.026283271610736847,
-0.14909374713897705,
0.4044564366340637,
0.20290599763393402,
0.2336096018552... |
https://github.com/huggingface/datasets/issues/4876 | Move DatasetInfo from `datasets_infos.json` to the YAML tags in `README.md` | > Note also that the default config is not named default, afaiu, but create from the repo name, eg: https://huggingface.co/datasets/nbtpj/bionlp2021SAS default config is nbtpj--bionlp2021SAS (which is awful)
We can change this to `default` I think or something else | Currently there are two places to find metadata for datasets:
- datasets_infos.json, which contains **per dataset config**
- description
- citation
- license
- splits and sizes
- checksums of the data files
- feature types
- and more
- YAML tags, which contain
- license
- language
- trai... | 38 | Move DatasetInfo from `datasets_infos.json` to the YAML tags in `README.md`
Currently there are two places to find metadata for datasets:
- datasets_infos.json, which contains **per dataset config**
- description
- citation
- license
- splits and sizes
- checksums of the data files
- feature types
... | [
0.0013892464339733124,
0.22179293632507324,
-0.021893955767154694,
0.2056550830602646,
0.4584723114967346,
0.3661663830280304,
0.19599571824073792,
0.5665823817253113,
-0.06621095538139343,
0.026283271610736847,
-0.14909374713897705,
0.4044564366340637,
0.20290599763393402,
0.2336096018552... |
https://github.com/huggingface/datasets/issues/4876 | Move DatasetInfo from `datasets_infos.json` to the YAML tags in `README.md` | > From a quick glance the features might be the harder part to validate here, any doc will be welcome.
I dug into features validation, see:
- the OpenAPI spec: https://github.com/huggingface/datasets-server/blob/main/chart/static-files/openapi.json#L460-L697
- the node.js code: https://github.com/huggingface/moo... | Currently there are two places to find metadata for datasets:
- datasets_infos.json, which contains **per dataset config**
- description
- citation
- license
- splits and sizes
- checksums of the data files
- feature types
- and more
- YAML tags, which contain
- license
- language
- trai... | 36 | Move DatasetInfo from `datasets_infos.json` to the YAML tags in `README.md`
Currently there are two places to find metadata for datasets:
- datasets_infos.json, which contains **per dataset config**
- description
- citation
- license
- splits and sizes
- checksums of the data files
- feature types
... | [
0.0013892464339733124,
0.22179293632507324,
-0.021893955767154694,
0.2056550830602646,
0.4584723114967346,
0.3661663830280304,
0.19599571824073792,
0.5665823817253113,
-0.06621095538139343,
0.026283271610736847,
-0.14909374713897705,
0.4044564366340637,
0.20290599763393402,
0.2336096018552... |
https://github.com/huggingface/datasets/issues/4876 | Move DatasetInfo from `datasets_infos.json` to the YAML tags in `README.md` | > We can change this to default I think or something else
I created https://github.com/huggingface/datasets/issues/4902 to discuss that | Currently there are two places to find metadata for datasets:
- datasets_infos.json, which contains **per dataset config**
- description
- citation
- license
- splits and sizes
- checksums of the data files
- feature types
- and more
- YAML tags, which contain
- license
- language
- trai... | 18 | Move DatasetInfo from `datasets_infos.json` to the YAML tags in `README.md`
Currently there are two places to find metadata for datasets:
- datasets_infos.json, which contains **per dataset config**
- description
- citation
- license
- splits and sizes
- checksums of the data files
- feature types
... | [
0.0013892464339733124,
0.22179293632507324,
-0.021893955767154694,
0.2056550830602646,
0.4584723114967346,
0.3661663830280304,
0.19599571824073792,
0.5665823817253113,
-0.06621095538139343,
0.026283271610736847,
-0.14909374713897705,
0.4044564366340637,
0.20290599763393402,
0.2336096018552... |
https://github.com/huggingface/datasets/issues/4876 | Move DatasetInfo from `datasets_infos.json` to the YAML tags in `README.md` | > Note also that the default config is not named `default`, afaiu, but create from the repo name
in case of single-config you can even hide the config name from the UI IMO
> I dug into features validation, see: the OpenAPI spec
in moon-landing we use [Joi](https://joi.dev/api/) to validate metadata so we would... | Currently there are two places to find metadata for datasets:
- datasets_infos.json, which contains **per dataset config**
- description
- citation
- license
- splits and sizes
- checksums of the data files
- feature types
- and more
- YAML tags, which contain
- license
- language
- trai... | 84 | Move DatasetInfo from `datasets_infos.json` to the YAML tags in `README.md`
Currently there are two places to find metadata for datasets:
- datasets_infos.json, which contains **per dataset config**
- description
- citation
- license
- splits and sizes
- checksums of the data files
- feature types
... | [
0.0013892464339733124,
0.22179293632507324,
-0.021893955767154694,
0.2056550830602646,
0.4584723114967346,
0.3661663830280304,
0.19599571824073792,
0.5665823817253113,
-0.06621095538139343,
0.026283271610736847,
-0.14909374713897705,
0.4044564366340637,
0.20290599763393402,
0.2336096018552... |
https://github.com/huggingface/datasets/issues/4876 | Move DatasetInfo from `datasets_infos.json` to the YAML tags in `README.md` | I remember there was an ongoing discussion on this topic:
- #3507
I recall some of the concerns raised on that discussion:
- @lhoestq: Tensorflow Datasets catalog includes a community catalog where you can find and use HF datasets. They are using the exported dataset_infos.json files from github to get the metada... | Currently there are two places to find metadata for datasets:
- datasets_infos.json, which contains **per dataset config**
- description
- citation
- license
- splits and sizes
- checksums of the data files
- feature types
- and more
- YAML tags, which contain
- license
- language
- trai... | 136 | Move DatasetInfo from `datasets_infos.json` to the YAML tags in `README.md`
Currently there are two places to find metadata for datasets:
- datasets_infos.json, which contains **per dataset config**
- description
- citation
- license
- splits and sizes
- checksums of the data files
- feature types
... | [
0.0013892464339733124,
0.22179293632507324,
-0.021893955767154694,
0.2056550830602646,
0.4584723114967346,
0.3661663830280304,
0.19599571824073792,
0.5665823817253113,
-0.06621095538139343,
0.026283271610736847,
-0.14909374713897705,
0.4044564366340637,
0.20290599763393402,
0.2336096018552... |
https://github.com/huggingface/datasets/issues/4876 | Move DatasetInfo from `datasets_infos.json` to the YAML tags in `README.md` | Thanks for bringing these points up !
> @lhoestq: Tensorflow Datasets catalog includes a community catalog where you can find and use HF datasets. They are using the exported dataset_infos.json files from github to get the metadata: https://github.com/huggingface/datasets/issues/3507#issuecomment-1056997627
The T... | Currently there are two places to find metadata for datasets:
- datasets_infos.json, which contains **per dataset config**
- description
- citation
- license
- splits and sizes
- checksums of the data files
- feature types
- and more
- YAML tags, which contain
- license
- language
- trai... | 158 | Move DatasetInfo from `datasets_infos.json` to the YAML tags in `README.md`
Currently there are two places to find metadata for datasets:
- datasets_infos.json, which contains **per dataset config**
- description
- citation
- license
- splits and sizes
- checksums of the data files
- feature types
... | [
0.0013892464339733124,
0.22179293632507324,
-0.021893955767154694,
0.2056550830602646,
0.4584723114967346,
0.3661663830280304,
0.19599571824073792,
0.5665823817253113,
-0.06621095538139343,
0.026283271610736847,
-0.14909374713897705,
0.4044564366340637,
0.20290599763393402,
0.2336096018552... |
https://github.com/huggingface/datasets/issues/4875 | `_resolve_features` ignores the token | Hi ! Your HF_ENDPOINT seems wrong because of the extra "/"
```diff
- os.environ["HF_ENDPOINT"] = "https://hub-ci.huggingface.co/"
+ os.environ["HF_ENDPOINT"] = "https://hub-ci.huggingface.co"
```
can you try again without the extra "/" ? | ## Describe the bug
When calling [`_resolve_features()`](https://github.com/huggingface/datasets/blob/54b532a8a2f5353fdb0207578162153f7b2da2ec/src/datasets/iterable_dataset.py#L1255) on a gated dataset, ie. a dataset which requires a token to be loaded, the token seems to be ignored even if it has been provided to `... | 30 | `_resolve_features` ignores the token
## Describe the bug
When calling [`_resolve_features()`](https://github.com/huggingface/datasets/blob/54b532a8a2f5353fdb0207578162153f7b2da2ec/src/datasets/iterable_dataset.py#L1255) on a gated dataset, ie. a dataset which requires a token to be loaded, the token seems to be i... | [
-0.040648654103279114,
-0.13932183384895325,
0.004608139395713806,
-0.11634822189807892,
0.29191064834594727,
0.0000600963830947876,
0.5858665704727173,
0.10497675836086273,
0.18346552550792694,
-0.0210077166557312,
0.19130101799964905,
0.31997042894363403,
0.0904184952378273,
0.3020302951... |
https://github.com/huggingface/datasets/issues/4875 | `_resolve_features` ignores the token | Oh, yes, sorry, but it's not the issue.
In my code, I set `HF_ENDPOINT=https://hub-ci.huggingface.co`. I added `os.environ["HF_ENDPOINT"] = "https://hub-ci.huggingface.co/"` afterward just to indicate that we had to have this env var and made a mistake there | ## Describe the bug
When calling [`_resolve_features()`](https://github.com/huggingface/datasets/blob/54b532a8a2f5353fdb0207578162153f7b2da2ec/src/datasets/iterable_dataset.py#L1255) on a gated dataset, ie. a dataset which requires a token to be loaded, the token seems to be ignored even if it has been provided to `... | 36 | `_resolve_features` ignores the token
## Describe the bug
When calling [`_resolve_features()`](https://github.com/huggingface/datasets/blob/54b532a8a2f5353fdb0207578162153f7b2da2ec/src/datasets/iterable_dataset.py#L1255) on a gated dataset, ie. a dataset which requires a token to be loaded, the token seems to be i... | [
-0.040648654103279114,
-0.13932183384895325,
0.004608139395713806,
-0.11634822189807892,
0.29191064834594727,
0.0000600963830947876,
0.5858665704727173,
0.10497675836086273,
0.18346552550792694,
-0.0210077166557312,
0.19130101799964905,
0.31997042894363403,
0.0904184952378273,
0.3020302951... |
https://github.com/huggingface/datasets/issues/4875 | `_resolve_features` ignores the token | I can't reproduce on my side. I tried using a private dataset repo with a CSV file on hub-ci
What's your version of `huggingface_hub` ? | ## Describe the bug
When calling [`_resolve_features()`](https://github.com/huggingface/datasets/blob/54b532a8a2f5353fdb0207578162153f7b2da2ec/src/datasets/iterable_dataset.py#L1255) on a gated dataset, ie. a dataset which requires a token to be loaded, the token seems to be ignored even if it has been provided to `... | 25 | `_resolve_features` ignores the token
## Describe the bug
When calling [`_resolve_features()`](https://github.com/huggingface/datasets/blob/54b532a8a2f5353fdb0207578162153f7b2da2ec/src/datasets/iterable_dataset.py#L1255) on a gated dataset, ie. a dataset which requires a token to be loaded, the token seems to be i... | [
-0.040648654103279114,
-0.13932183384895325,
0.004608139395713806,
-0.11634822189807892,
0.29191064834594727,
0.0000600963830947876,
0.5858665704727173,
0.10497675836086273,
0.18346552550792694,
-0.0210077166557312,
0.19130101799964905,
0.31997042894363403,
0.0904184952378273,
0.3020302951... |
https://github.com/huggingface/datasets/issues/4875 | `_resolve_features` ignores the token | I can't reproduce either... Not sure what has occurred, very sorry to have made you lost your time on that | ## Describe the bug
When calling [`_resolve_features()`](https://github.com/huggingface/datasets/blob/54b532a8a2f5353fdb0207578162153f7b2da2ec/src/datasets/iterable_dataset.py#L1255) on a gated dataset, ie. a dataset which requires a token to be loaded, the token seems to be ignored even if it has been provided to `... | 20 | `_resolve_features` ignores the token
## Describe the bug
When calling [`_resolve_features()`](https://github.com/huggingface/datasets/blob/54b532a8a2f5353fdb0207578162153f7b2da2ec/src/datasets/iterable_dataset.py#L1255) on a gated dataset, ie. a dataset which requires a token to be loaded, the token seems to be i... | [
-0.040648654103279114,
-0.13932183384895325,
0.004608139395713806,
-0.11634822189807892,
0.29191064834594727,
0.0000600963830947876,
0.5858665704727173,
0.10497675836086273,
0.18346552550792694,
-0.0210077166557312,
0.19130101799964905,
0.31997042894363403,
0.0904184952378273,
0.3020302951... |
https://github.com/huggingface/datasets/issues/4875 | `_resolve_features` ignores the token | I got something similar in https://github.com/huggingface/datasets-server/pull/608. Look how changing the order of the tests (https://github.com/huggingface/datasets-server/pull/608/commits/2c50fe833323de3dfdc76c5cd68639279e0887f8) change the result, which means that something has a side-effect:
- https://github.com/h... | ## Describe the bug
When calling [`_resolve_features()`](https://github.com/huggingface/datasets/blob/54b532a8a2f5353fdb0207578162153f7b2da2ec/src/datasets/iterable_dataset.py#L1255) on a gated dataset, ie. a dataset which requires a token to be loaded, the token seems to be ignored even if it has been provided to `... | 42 | `_resolve_features` ignores the token
## Describe the bug
When calling [`_resolve_features()`](https://github.com/huggingface/datasets/blob/54b532a8a2f5353fdb0207578162153f7b2da2ec/src/datasets/iterable_dataset.py#L1255) on a gated dataset, ie. a dataset which requires a token to be loaded, the token seems to be i... | [
-0.040648654103279114,
-0.13932183384895325,
0.004608139395713806,
-0.11634822189807892,
0.29191064834594727,
0.0000600963830947876,
0.5858665704727173,
0.10497675836086273,
0.18346552550792694,
-0.0210077166557312,
0.19130101799964905,
0.31997042894363403,
0.0904184952378273,
0.3020302951... |
https://github.com/huggingface/datasets/issues/4875 | `_resolve_features` ignores the token | The issue happens because `extend_module_for_streaming` can't be used several times on packaged builders like `csv` to apply a new auth token. Indeed `extend_module_for_streaming` only applies authentication once, and on subsequent calls does nothing:
https://github.com/huggingface/datasets/blob/07b7c38d9e9c72c74b02... | ## Describe the bug
When calling [`_resolve_features()`](https://github.com/huggingface/datasets/blob/54b532a8a2f5353fdb0207578162153f7b2da2ec/src/datasets/iterable_dataset.py#L1255) on a gated dataset, ie. a dataset which requires a token to be loaded, the token seems to be ignored even if it has been provided to `... | 96 | `_resolve_features` ignores the token
## Describe the bug
When calling [`_resolve_features()`](https://github.com/huggingface/datasets/blob/54b532a8a2f5353fdb0207578162153f7b2da2ec/src/datasets/iterable_dataset.py#L1255) on a gated dataset, ie. a dataset which requires a token to be loaded, the token seems to be i... | [
-0.040648654103279114,
-0.13932183384895325,
0.004608139395713806,
-0.11634822189807892,
0.29191064834594727,
0.0000600963830947876,
0.5858665704727173,
0.10497675836086273,
0.18346552550792694,
-0.0210077166557312,
0.19130101799964905,
0.31997042894363403,
0.0904184952378273,
0.3020302951... |
https://github.com/huggingface/datasets/issues/4875 | `_resolve_features` ignores the token | > This can be fixed by storing a dict token_per_repo_id instead of use_auth_token in the authentication wrapper, and by making it possible to update the authentication wrapper with a new token
If I call the module on the same repo twice: first with authentication, then without authentication, would the second call u... | ## Describe the bug
When calling [`_resolve_features()`](https://github.com/huggingface/datasets/blob/54b532a8a2f5353fdb0207578162153f7b2da2ec/src/datasets/iterable_dataset.py#L1255) on a gated dataset, ie. a dataset which requires a token to be loaded, the token seems to be ignored even if it has been provided to `... | 69 | `_resolve_features` ignores the token
## Describe the bug
When calling [`_resolve_features()`](https://github.com/huggingface/datasets/blob/54b532a8a2f5353fdb0207578162153f7b2da2ec/src/datasets/iterable_dataset.py#L1255) on a gated dataset, ie. a dataset which requires a token to be loaded, the token seems to be i... | [
-0.040648654103279114,
-0.13932183384895325,
0.004608139395713806,
-0.11634822189807892,
0.29191064834594727,
0.0000600963830947876,
0.5858665704727173,
0.10497675836086273,
0.18346552550792694,
-0.0210077166557312,
0.19130101799964905,
0.31997042894363403,
0.0904184952378273,
0.3020302951... |
https://github.com/huggingface/datasets/issues/4873 | Multiple dataloader memory error | Hi!
200+ data loaders is a lot. Have you tried to reduce the number of datasets by concatenating/interleaving the ones with the same structure/task (the API is `{concatenate_datasets/interleave_datasets}([dset1, ..., dset_N])`)? | For the use of multiple datasets and tasks, we use around more than 200+ dataloaders, then pass it into `dataloader1, dataloader2, ..., dataloader200=accelerate.prepare(dataloader1, dataloader2, ..., dataloader200)`
It causes the memory error when generating batches. Any solutions to it?
```bash
File "/home/xxx/... | 30 | Multiple dataloader memory error
For the use of multiple datasets and tasks, we use around more than 200+ dataloaders, then pass it into `dataloader1, dataloader2, ..., dataloader200=accelerate.prepare(dataloader1, dataloader2, ..., dataloader200)`
It causes the memory error when generating batches. Any solutions to... | [
-0.3603481948375702,
-0.04721894860267639,
-0.10115733742713928,
0.5487484335899353,
0.2818191647529602,
-0.04169483482837677,
0.27157947421073914,
0.20091070234775543,
0.22190330922603607,
0.30902305245399475,
0.1223437562584877,
0.031112680211663246,
-0.20396031439304352,
-0.060576446354... |
https://github.com/huggingface/datasets/issues/4873 | Multiple dataloader memory error | Hi @mariosasko, thank you for your reply. I tried pre-concatenating different datasets into one, but one key need is to keep each batch the same data type. Considering that the concatenate-then-segment operation for prefetched samples may span across different data types after concatenating/interleaving (cuz different ... | For the use of multiple datasets and tasks, we use around more than 200+ dataloaders, then pass it into `dataloader1, dataloader2, ..., dataloader200=accelerate.prepare(dataloader1, dataloader2, ..., dataloader200)`
It causes the memory error when generating batches. Any solutions to it?
```bash
File "/home/xxx/... | 60 | Multiple dataloader memory error
For the use of multiple datasets and tasks, we use around more than 200+ dataloaders, then pass it into `dataloader1, dataloader2, ..., dataloader200=accelerate.prepare(dataloader1, dataloader2, ..., dataloader200)`
It causes the memory error when generating batches. Any solutions to... | [
-0.3603481948375702,
-0.04721894860267639,
-0.10115733742713928,
0.5487484335899353,
0.2818191647529602,
-0.04169483482837677,
0.27157947421073914,
0.20091070234775543,
0.22190330922603607,
0.30902305245399475,
0.1223437562584877,
0.031112680211663246,
-0.20396031439304352,
-0.060576446354... |
https://github.com/huggingface/datasets/issues/4873 | Multiple dataloader memory error | @cyk1337 have you found any solutions to it?
@mariosasko I tried with interleave_datasets to sample batches from two large datasets (wikipedia alike) and it results in out-of-memory error during data loading (16gpus, >1TB physical memory). Do you have any idea about it? | For the use of multiple datasets and tasks, we use around more than 200+ dataloaders, then pass it into `dataloader1, dataloader2, ..., dataloader200=accelerate.prepare(dataloader1, dataloader2, ..., dataloader200)`
It causes the memory error when generating batches. Any solutions to it?
```bash
File "/home/xxx/... | 42 | Multiple dataloader memory error
For the use of multiple datasets and tasks, we use around more than 200+ dataloaders, then pass it into `dataloader1, dataloader2, ..., dataloader200=accelerate.prepare(dataloader1, dataloader2, ..., dataloader200)`
It causes the memory error when generating batches. Any solutions to... | [
-0.3603481948375702,
-0.04721894860267639,
-0.10115733742713928,
0.5487484335899353,
0.2818191647529602,
-0.04169483482837677,
0.27157947421073914,
0.20091070234775543,
0.22190330922603607,
0.30902305245399475,
0.1223437562584877,
0.031112680211663246,
-0.20396031439304352,
-0.060576446354... |
https://github.com/huggingface/datasets/issues/4865 | Dataset Viewer issue for MoritzLaurer/multilingual_nli | Thanks for reporting @MoritzLaurer.
Currently, the dataset preview is working properly: https://huggingface.co/datasets/MoritzLaurer/multilingual_nli
Please note that when a dataset is modified, it might take some time until the preview is completely updated.
@severo might it be worth adding a clearer error m... | ### Link
_No response_
### Description
I've just uploaded a new dataset to the hub and the viewer does not work for some reason, see here: https://huggingface.co/datasets/MoritzLaurer/multilingual_nli
It displays the error:
```
Status code: 400
Exception: Status400Error
Message: The dataset... | 50 | Dataset Viewer issue for MoritzLaurer/multilingual_nli
### Link
_No response_
### Description
I've just uploaded a new dataset to the hub and the viewer does not work for some reason, see here: https://huggingface.co/datasets/MoritzLaurer/multilingual_nli
It displays the error:
```
Status code: 400
... | [
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0.0894695371389389,
0.4716784954071045,
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0.38089561462402344,
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0.21699556708335876,
-0.06428735703229904,
0.05089675635099411,
-0.11489065736532211,
-0.09472821652... |
https://github.com/huggingface/datasets/issues/4865 | Dataset Viewer issue for MoritzLaurer/multilingual_nli | Thanks for your response. You are right, its now working well. I had waited for 30 min or so and refreshed several times and thought there was some other error. Yeah, a different error message sounds like a good idea to avoid confusion. | ### Link
_No response_
### Description
I've just uploaded a new dataset to the hub and the viewer does not work for some reason, see here: https://huggingface.co/datasets/MoritzLaurer/multilingual_nli
It displays the error:
```
Status code: 400
Exception: Status400Error
Message: The dataset... | 43 | Dataset Viewer issue for MoritzLaurer/multilingual_nli
### Link
_No response_
### Description
I've just uploaded a new dataset to the hub and the viewer does not work for some reason, see here: https://huggingface.co/datasets/MoritzLaurer/multilingual_nli
It displays the error:
```
Status code: 400
... | [
-0.2839988172054291,
-0.18147766590118408,
0.10039108991622925,
0.575805127620697,
-0.009439859539270401,
0.0489201545715332,
0.4215768873691559,
0.270027756690979,
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0.20727400481700897,
-0.05809474736452103,
0.031924083828926086,
-0.11529862135648727,
-0.109165556728839... |
https://github.com/huggingface/datasets/issues/4865 | Dataset Viewer issue for MoritzLaurer/multilingual_nli | > @severo might it be worth adding a clearer error message, something like "The preview is updating, please retry later"?
Yes, it's a known issue, and we're about to ship a better version | ### Link
_No response_
### Description
I've just uploaded a new dataset to the hub and the viewer does not work for some reason, see here: https://huggingface.co/datasets/MoritzLaurer/multilingual_nli
It displays the error:
```
Status code: 400
Exception: Status400Error
Message: The dataset... | 33 | Dataset Viewer issue for MoritzLaurer/multilingual_nli
### Link
_No response_
### Description
I've just uploaded a new dataset to the hub and the viewer does not work for some reason, see here: https://huggingface.co/datasets/MoritzLaurer/multilingual_nli
It displays the error:
```
Status code: 400
... | [
-0.34113579988479614,
-0.11367043107748032,
0.09403979778289795,
0.5236725211143494,
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0.03693035989999771,
0.4001799523830414,
0.3113575279712677,
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0.2099694311618805,
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0.01459730789065361,
-0.10247867554426193,
-0.1295171827... |
https://github.com/huggingface/datasets/issues/4864 | Allow pathlib PoxisPath in Dataset.read_json | @cccntu I want to make a quick fix for this, but I am struggling to find where the json dataset builder is. Do you know? | **Is your feature request related to a problem? Please describe.**
```
from pathlib import Path
from datasets import Dataset
ds = Dataset.read_json(Path('data.json'))
```
causes an error
```
AttributeError: 'PosixPath' object has no attribute 'decode'
```
**Describe the solution you'd like**
It should be... | 25 | Allow pathlib PoxisPath in Dataset.read_json
**Is your feature request related to a problem? Please describe.**
```
from pathlib import Path
from datasets import Dataset
ds = Dataset.read_json(Path('data.json'))
```
causes an error
```
AttributeError: 'PosixPath' object has no attribute 'decode'
```
**Des... | [
-0.05640802159905434,
0.1484840214252472,
-0.13980835676193237,
0.43619799613952637,
0.4390369653701782,
0.09516885131597519,
-0.026697393506765366,
0.14132735133171082,
0.07359257340431213,
0.17195330560207367,
0.11664091050624847,
0.7626716494560242,
-0.05945820361375809,
0.3103781342506... |
https://github.com/huggingface/datasets/issues/4864 | Allow pathlib PoxisPath in Dataset.read_json | @vvvm23 I think you mean think:
```python
ds = datasets.load_dataset('json', data_files=[Path('test.jsonl')])
```
And the place you want to modify is here:
```
utils/file_utils.py:64, in is_remote_url(url_or_filename)
63 def is_remote_url(url_or_filename: str) -> bool:
---> 64 parsed = urlparse(url_or_... | **Is your feature request related to a problem? Please describe.**
```
from pathlib import Path
from datasets import Dataset
ds = Dataset.read_json(Path('data.json'))
```
causes an error
```
AttributeError: 'PosixPath' object has no attribute 'decode'
```
**Describe the solution you'd like**
It should be... | 90 | Allow pathlib PoxisPath in Dataset.read_json
**Is your feature request related to a problem? Please describe.**
```
from pathlib import Path
from datasets import Dataset
ds = Dataset.read_json(Path('data.json'))
```
causes an error
```
AttributeError: 'PosixPath' object has no attribute 'decode'
```
**Des... | [
0.06083710864186287,
0.04320251941680908,
-0.11298975348472595,
0.19121889770030975,
0.34578919410705566,
-0.03741282969713211,
-0.034144993871450424,
0.22308148443698883,
0.15708838403224945,
-0.014970183372497559,
-0.10834550112485886,
0.7623046040534973,
-0.07996836304664612,
0.15963710... |
https://github.com/huggingface/datasets/issues/4864 | Allow pathlib PoxisPath in Dataset.read_json | > @vvvm23 I think you mean think:
You are correct, thanks!
> Probably just need to check first if url_or_filename is [PathLike](https://docs.python.org/3/library/os.html#os.PathLike) and return False early.
Is PathLike sufficient, or should I check the file exists here? Or is that handled later? | **Is your feature request related to a problem? Please describe.**
```
from pathlib import Path
from datasets import Dataset
ds = Dataset.read_json(Path('data.json'))
```
causes an error
```
AttributeError: 'PosixPath' object has no attribute 'decode'
```
**Describe the solution you'd like**
It should be... | 42 | Allow pathlib PoxisPath in Dataset.read_json
**Is your feature request related to a problem? Please describe.**
```
from pathlib import Path
from datasets import Dataset
ds = Dataset.read_json(Path('data.json'))
```
causes an error
```
AttributeError: 'PosixPath' object has no attribute 'decode'
```
**Des... | [
0.09360086917877197,
-0.07396523654460907,
-0.10973867774009705,
0.33342719078063965,
0.40239542722702026,
-0.09170276671648026,
-0.06900425255298615,
0.2436937540769577,
0.18564145267009735,
0.0035425573587417603,
-0.03321041911840439,
0.6618059277534485,
-0.15123966336250305,
0.203285992... |
https://github.com/huggingface/datasets/issues/4864 | Allow pathlib PoxisPath in Dataset.read_json | I think here we just want to avoid passing Path to urlparse. A simpler solution is to add a str() call and convert the input to string before passing to the next step. No need to check anything. | **Is your feature request related to a problem? Please describe.**
```
from pathlib import Path
from datasets import Dataset
ds = Dataset.read_json(Path('data.json'))
```
causes an error
```
AttributeError: 'PosixPath' object has no attribute 'decode'
```
**Describe the solution you'd like**
It should be... | 38 | Allow pathlib PoxisPath in Dataset.read_json
**Is your feature request related to a problem? Please describe.**
```
from pathlib import Path
from datasets import Dataset
ds = Dataset.read_json(Path('data.json'))
```
causes an error
```
AttributeError: 'PosixPath' object has no attribute 'decode'
```
**Des... | [
0.03500945493578911,
0.0013352259993553162,
-0.10183858871459961,
0.22808675467967987,
0.5507002472877502,
-0.14522147178649902,
-0.025602277368307114,
0.23174157738685608,
0.03983930125832558,
0.13871000707149506,
-0.06380748003721237,
0.7362851500511169,
-0.06573653966188431,
0.257582426... |
https://github.com/huggingface/datasets/issues/4864 | Allow pathlib PoxisPath in Dataset.read_json | Above PR should do your first suggestion. Hope that works for you, as I am going on holiday and won't be able to change much :wink: | **Is your feature request related to a problem? Please describe.**
```
from pathlib import Path
from datasets import Dataset
ds = Dataset.read_json(Path('data.json'))
```
causes an error
```
AttributeError: 'PosixPath' object has no attribute 'decode'
```
**Describe the solution you'd like**
It should be... | 26 | Allow pathlib PoxisPath in Dataset.read_json
**Is your feature request related to a problem? Please describe.**
```
from pathlib import Path
from datasets import Dataset
ds = Dataset.read_json(Path('data.json'))
```
causes an error
```
AttributeError: 'PosixPath' object has no attribute 'decode'
```
**Des... | [
-0.028976958245038986,
-0.03523745387792587,
-0.14714370667934418,
0.27945536375045776,
0.4800269603729248,
-0.05978160724043846,
-0.01852830871939659,
0.25403526425361633,
0.13730061054229736,
0.16156995296478271,
-0.1300649493932724,
0.7647238969802856,
-0.047634437680244446,
0.347775131... |
https://github.com/huggingface/datasets/issues/4863 | TFDS wiki_dialog dataset to Huggingface dataset | @albertvillanova any help ? The linked dataset is in beam format which is similar to wikipedia dataset in huggingface that you scripted.. | ## Adding a Dataset
- **Name:** *Wiki_dialog*
- **Description: https://github.com/google-research/dialog-inpainting#:~:text=JSON%20object%2C%20for-,example,-%3A
- **Paper: https://arxiv.org/abs/2205.09073
- **Data: https://github.com/google-research/dialog-inpainting
- **Motivation:** *Research and Development on ... | 22 | TFDS wiki_dialog dataset to Huggingface dataset
## Adding a Dataset
- **Name:** *Wiki_dialog*
- **Description: https://github.com/google-research/dialog-inpainting#:~:text=JSON%20object%2C%20for-,example,-%3A
- **Paper: https://arxiv.org/abs/2205.09073
- **Data: https://github.com/google-research/dialog-inpaintin... | [
-0.011967062950134277,
-0.3182222545146942,
-0.015078390948474407,
0.3440629839897156,
0.09529385715723038,
0.2960657775402069,
0.08297007530927658,
0.2282542586326599,
0.14890483021736145,
0.04415624588727951,
-0.4362179934978485,
0.11124090105295181,
-0.15581926703453064,
0.5062382221221... |
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