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https://github.com/huggingface/datasets/issues/1633
|
social_i_qa wrong format of labels
|
@lhoestq, should I raise a PR for this? Just a minor change while reading labels text file
|
Hi,
there is extra "\n" in labels of social_i_qa datasets, no big deal, but I was wondering if you could remove it to make it consistent.
so label is 'label': '1\n', not '1'
thanks
```
>>> import datasets
>>> from datasets import load_dataset
>>> dataset = load_dataset(
... 'social_i_qa')
cahce dir /julia/cache/datasets
Downloading: 4.72kB [00:00, 3.52MB/s]
cahce dir /julia/cache/datasets
Downloading: 2.19kB [00:00, 1.81MB/s]
Using custom data configuration default
Reusing dataset social_i_qa (/julia/datasets/social_i_qa/default/0.1.0/4a4190cc2d2482d43416c2167c0c5dccdd769d4482e84893614bd069e5c3ba06)
>>> dataset['train'][0]
{'answerA': 'like attending', 'answerB': 'like staying home', 'answerC': 'a good friend to have', 'context': 'Cameron decided to have a barbecue and gathered her friends together.', 'label': '1\n', 'question': 'How would Others feel as a result?'}
```
| 17 |
social_i_qa wrong format of labels
|
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] |
https://github.com/huggingface/datasets/issues/1630
|
Adding UKP Argument Aspect Similarity Corpus
|
Adding a link to the guide on adding a dataset if someone want to give it a try: https://github.com/huggingface/datasets#add-a-new-dataset-to-the-hub
we should add this guide to the issue template @lhoestq
|
Hi, this would be great to have this dataset included.
## Adding a Dataset
- **Name:** UKP Argument Aspect Similarity Corpus
- **Description:** The UKP Argument Aspect Similarity Corpus (UKP ASPECT) includes 3,595 sentence pairs over 28 controversial topics. Each sentence pair was annotated via crowdsourcing as either “high similarity”, “some similarity”, “no similarity” or “not related” with respect to the topic.
- **Paper:** https://www.aclweb.org/anthology/P19-1054/
- **Data:** https://tudatalib.ulb.tu-darmstadt.de/handle/tudatalib/1998
- **Motivation:** this is one of the datasets currently used frequently in recent adapter papers like https://arxiv.org/pdf/2005.00247.pdf
Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
Thank you
| 29 |
Adding UKP Argument Aspect Similarity Corpus
|
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] |
https://github.com/huggingface/datasets/issues/1630
|
Adding UKP Argument Aspect Similarity Corpus
|
thanks @thomwolf , this is added now. The template is correct, sorry my mistake not to include it.
|
Hi, this would be great to have this dataset included.
## Adding a Dataset
- **Name:** UKP Argument Aspect Similarity Corpus
- **Description:** The UKP Argument Aspect Similarity Corpus (UKP ASPECT) includes 3,595 sentence pairs over 28 controversial topics. Each sentence pair was annotated via crowdsourcing as either “high similarity”, “some similarity”, “no similarity” or “not related” with respect to the topic.
- **Paper:** https://www.aclweb.org/anthology/P19-1054/
- **Data:** https://tudatalib.ulb.tu-darmstadt.de/handle/tudatalib/1998
- **Motivation:** this is one of the datasets currently used frequently in recent adapter papers like https://arxiv.org/pdf/2005.00247.pdf
Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
Thank you
| 18 |
Adding UKP Argument Aspect Similarity Corpus
|
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] |
https://github.com/huggingface/datasets/issues/1627
|
`Dataset.map` disable progress bar
|
Progress bar can be disabled like this:
```python
from datasets.utils.logging import set_verbosity_error
set_verbosity_error()
```
There is this line in `Dataset.map`:
```python
not_verbose = bool(logger.getEffectiveLevel() > WARNING)
```
So any logging level higher than `WARNING` turns off the progress bar.
|
I can't find anything to turn off the `tqdm` progress bars while running a preprocessing function using `Dataset.map`. I want to do akin to `disable_tqdm=True` in the case of `transformers`. Is there something like that?
| 39 |
`Dataset.map` disable progress bar
|
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] |
https://github.com/huggingface/datasets/issues/1627
|
`Dataset.map` disable progress bar
|
From the linked issues above, an up-to-date solution is:
```python
from datasets.utils.logging import disable_progress_bar
disable_progress_bar()
```
https://github.com/huggingface/datasets/blob/c6e08fcfc3a04e53430c26fa7c07da4cb18d977d/src/datasets/utils/logging.py#L233-L236
|
I can't find anything to turn off the `tqdm` progress bars while running a preprocessing function using `Dataset.map`. I want to do akin to `disable_tqdm=True` in the case of `transformers`. Is there something like that?
| 17 |
`Dataset.map` disable progress bar
|
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] |
https://github.com/huggingface/datasets/issues/1627
|
`Dataset.map` disable progress bar
|
+1. We shouldn't need to play with logging levels for a simple thing like this. For instance, trainers have an option `show_progress` that does exactly this.
|
I can't find anything to turn off the `tqdm` progress bars while running a preprocessing function using `Dataset.map`. I want to do akin to `disable_tqdm=True` in the case of `transformers`. Is there something like that?
| 26 |
`Dataset.map` disable progress bar
|
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] |
https://github.com/huggingface/datasets/issues/1624
|
Cannot download ade_corpus_v2
|
Hi @him1411, the dataset you are trying to load has been added during the community sprint and has not been released yet. It will be available with the v2 of `datasets`.
For now, you should be able to load the datasets after installing the latest (master) version of `datasets` using pip:
`pip install git+https://github.com/huggingface/datasets.git@master`
|
I tried this to get the dataset following this url : https://huggingface.co/datasets/ade_corpus_v2
but received this error :
`Traceback (most recent call last):
File "/opt/anaconda3/lib/python3.7/site-packages/datasets/load.py", line 267, in prepare_module
local_path = cached_path(file_path, download_config=download_config)
File "/opt/anaconda3/lib/python3.7/site-packages/datasets/utils/file_utils.py", line 308, in cached_path
use_etag=download_config.use_etag,
File "/opt/anaconda3/lib/python3.7/site-packages/datasets/utils/file_utils.py", line 486, in get_from_cache
raise FileNotFoundError("Couldn't find file at {}".format(url))
FileNotFoundError: Couldn't find file at https://raw.githubusercontent.com/huggingface/datasets/1.1.3/datasets/ade_corpus_v2/ade_corpus_v2.py
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/opt/anaconda3/lib/python3.7/site-packages/datasets/load.py", line 278, in prepare_module
local_path = cached_path(file_path, download_config=download_config)
File "/opt/anaconda3/lib/python3.7/site-packages/datasets/utils/file_utils.py", line 308, in cached_path
use_etag=download_config.use_etag,
File "/opt/anaconda3/lib/python3.7/site-packages/datasets/utils/file_utils.py", line 486, in get_from_cache
raise FileNotFoundError("Couldn't find file at {}".format(url))
FileNotFoundError: Couldn't find file at https://s3.amazonaws.com/datasets.huggingface.co/datasets/datasets/ade_corpus_v2/ade_corpus_v2.py
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/opt/anaconda3/lib/python3.7/site-packages/datasets/load.py", line 589, in load_dataset
path, script_version=script_version, download_config=download_config, download_mode=download_mode, dataset=True
File "/opt/anaconda3/lib/python3.7/site-packages/datasets/load.py", line 282, in prepare_module
combined_path, github_file_path, file_path
FileNotFoundError: Couldn't find file locally at ade_corpus_v2/ade_corpus_v2.py, or remotely at https://raw.githubusercontent.com/huggingface/datasets/1.1.3/datasets/ade_corpus_v2/ade_corpus_v2.py or https://s3.amazonaws.com/datasets.huggingface.co/datasets/datasets/ade_corpus_v2/ade_corpus_v2.py`
| 54 |
Cannot download ade_corpus_v2
|
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] |
https://github.com/huggingface/datasets/issues/1624
|
Cannot download ade_corpus_v2
|
`ade_corpus_v2` was added recently, that's why it wasn't available yet.
To load it you can just update `datasets`
```
pip install --upgrade datasets
```
and then you can load `ade_corpus_v2` with
```python
from datasets import load_dataset
dataset = load_dataset("ade_corpus_v2", "Ade_corpos_v2_drug_ade_relation")
```
(looks like there is a typo in the configuration name, we'll fix it for the v2.0 release of `datasets` soon)
|
I tried this to get the dataset following this url : https://huggingface.co/datasets/ade_corpus_v2
but received this error :
`Traceback (most recent call last):
File "/opt/anaconda3/lib/python3.7/site-packages/datasets/load.py", line 267, in prepare_module
local_path = cached_path(file_path, download_config=download_config)
File "/opt/anaconda3/lib/python3.7/site-packages/datasets/utils/file_utils.py", line 308, in cached_path
use_etag=download_config.use_etag,
File "/opt/anaconda3/lib/python3.7/site-packages/datasets/utils/file_utils.py", line 486, in get_from_cache
raise FileNotFoundError("Couldn't find file at {}".format(url))
FileNotFoundError: Couldn't find file at https://raw.githubusercontent.com/huggingface/datasets/1.1.3/datasets/ade_corpus_v2/ade_corpus_v2.py
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/opt/anaconda3/lib/python3.7/site-packages/datasets/load.py", line 278, in prepare_module
local_path = cached_path(file_path, download_config=download_config)
File "/opt/anaconda3/lib/python3.7/site-packages/datasets/utils/file_utils.py", line 308, in cached_path
use_etag=download_config.use_etag,
File "/opt/anaconda3/lib/python3.7/site-packages/datasets/utils/file_utils.py", line 486, in get_from_cache
raise FileNotFoundError("Couldn't find file at {}".format(url))
FileNotFoundError: Couldn't find file at https://s3.amazonaws.com/datasets.huggingface.co/datasets/datasets/ade_corpus_v2/ade_corpus_v2.py
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/opt/anaconda3/lib/python3.7/site-packages/datasets/load.py", line 589, in load_dataset
path, script_version=script_version, download_config=download_config, download_mode=download_mode, dataset=True
File "/opt/anaconda3/lib/python3.7/site-packages/datasets/load.py", line 282, in prepare_module
combined_path, github_file_path, file_path
FileNotFoundError: Couldn't find file locally at ade_corpus_v2/ade_corpus_v2.py, or remotely at https://raw.githubusercontent.com/huggingface/datasets/1.1.3/datasets/ade_corpus_v2/ade_corpus_v2.py or https://s3.amazonaws.com/datasets.huggingface.co/datasets/datasets/ade_corpus_v2/ade_corpus_v2.py`
| 61 |
Cannot download ade_corpus_v2
|
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] |
https://github.com/huggingface/datasets/issues/1618
|
Can't filter language:EN on https://huggingface.co/datasets
|
Cool @mapmeld ! My 2 cents (for a next iteration), it would be cool to have a small search widget in the filter dropdown as you have a ton of languages now here! Closing this in the meantime.
|
When visiting https://huggingface.co/datasets, I don't see an obvious way to filter only English datasets. This is unexpected for me, am I missing something? I'd expect English to be selectable in the language widget. This problem reproduced on Mozilla Firefox and MS Edge:
| 38 |
Can't filter language:EN on https://huggingface.co/datasets
|
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] |
https://github.com/huggingface/datasets/issues/1615
|
Bug: Can't download TriviaQA with `load_dataset` - custom `cache_dir`
|
Hi @SapirWeissbuch,
When you are saying it freezes, at that time it is unzipping the file from the zip file it downloaded. Since it's a very heavy file it'll take some time. It was taking ~11GB after unzipping when it started reading examples for me. Hope that helps!
|
Hello,
I'm having issue downloading TriviaQA dataset with `load_dataset`.
## Environment info
- `datasets` version: 1.1.3
- Platform: Linux-4.19.129-aufs-1-x86_64-with-debian-10.1
- Python version: 3.7.3
## The code I'm running:
```python
import datasets
dataset = datasets.load_dataset("trivia_qa", "rc", cache_dir = "./datasets")
```
## The output:
1. Download begins:
```
Downloading and preparing dataset trivia_qa/rc (download: 2.48 GiB, generated: 14.92 GiB, post-processed: Unknown size, total: 17.40 GiB) to /cs/labs/gabis/sapirweissbuch/tr
ivia_qa/rc/1.1.0/e734e28133f4d9a353af322aa52b9f266f6f27cbf2f072690a1694e577546b0d...
Downloading: 17%|███████████████████▉ | 446M/2.67G [00:37<04:45, 7.77MB/s]
```
2. 100% is reached
3. It got stuck here for about an hour, and added additional 30G of data to "./datasets" directory. I killed the process eventually.
A similar issue can be observed in Google Colab:
https://colab.research.google.com/drive/1nn1Lw02GhfGFylzbS2j6yksGjPo7kkN-?usp=sharing
## Expected behaviour:
The dataset "TriviaQA" should be successfully downloaded.
| 54 |
Bug: Can't download TriviaQA with `load_dataset` - custom `cache_dir`
|
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] |
https://github.com/huggingface/datasets/issues/1615
|
Bug: Can't download TriviaQA with `load_dataset` - custom `cache_dir`
|
Hi @bhavitvyamalik
Thanks for the reply!
Actually I let it run for 30 minutes before I killed the process. In this time, 30GB were extracted (much more than 11GB), I checked the size of the destination directory.
What version of Datasets are you using?
|
Hello,
I'm having issue downloading TriviaQA dataset with `load_dataset`.
## Environment info
- `datasets` version: 1.1.3
- Platform: Linux-4.19.129-aufs-1-x86_64-with-debian-10.1
- Python version: 3.7.3
## The code I'm running:
```python
import datasets
dataset = datasets.load_dataset("trivia_qa", "rc", cache_dir = "./datasets")
```
## The output:
1. Download begins:
```
Downloading and preparing dataset trivia_qa/rc (download: 2.48 GiB, generated: 14.92 GiB, post-processed: Unknown size, total: 17.40 GiB) to /cs/labs/gabis/sapirweissbuch/tr
ivia_qa/rc/1.1.0/e734e28133f4d9a353af322aa52b9f266f6f27cbf2f072690a1694e577546b0d...
Downloading: 17%|███████████████████▉ | 446M/2.67G [00:37<04:45, 7.77MB/s]
```
2. 100% is reached
3. It got stuck here for about an hour, and added additional 30G of data to "./datasets" directory. I killed the process eventually.
A similar issue can be observed in Google Colab:
https://colab.research.google.com/drive/1nn1Lw02GhfGFylzbS2j6yksGjPo7kkN-?usp=sharing
## Expected behaviour:
The dataset "TriviaQA" should be successfully downloaded.
| 44 |
Bug: Can't download TriviaQA with `load_dataset` - custom `cache_dir`
|
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] |
https://github.com/huggingface/datasets/issues/1615
|
Bug: Can't download TriviaQA with `load_dataset` - custom `cache_dir`
|
I'm using datasets version: 1.1.3. I think you should drop `cache_dir` and use only
`dataset = datasets.load_dataset("trivia_qa", "rc")`
Tried that on colab and it's working there too
|
Hello,
I'm having issue downloading TriviaQA dataset with `load_dataset`.
## Environment info
- `datasets` version: 1.1.3
- Platform: Linux-4.19.129-aufs-1-x86_64-with-debian-10.1
- Python version: 3.7.3
## The code I'm running:
```python
import datasets
dataset = datasets.load_dataset("trivia_qa", "rc", cache_dir = "./datasets")
```
## The output:
1. Download begins:
```
Downloading and preparing dataset trivia_qa/rc (download: 2.48 GiB, generated: 14.92 GiB, post-processed: Unknown size, total: 17.40 GiB) to /cs/labs/gabis/sapirweissbuch/tr
ivia_qa/rc/1.1.0/e734e28133f4d9a353af322aa52b9f266f6f27cbf2f072690a1694e577546b0d...
Downloading: 17%|███████████████████▉ | 446M/2.67G [00:37<04:45, 7.77MB/s]
```
2. 100% is reached
3. It got stuck here for about an hour, and added additional 30G of data to "./datasets" directory. I killed the process eventually.
A similar issue can be observed in Google Colab:
https://colab.research.google.com/drive/1nn1Lw02GhfGFylzbS2j6yksGjPo7kkN-?usp=sharing
## Expected behaviour:
The dataset "TriviaQA" should be successfully downloaded.
| 28 |
Bug: Can't download TriviaQA with `load_dataset` - custom `cache_dir`
|
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] |
https://github.com/huggingface/datasets/issues/1615
|
Bug: Can't download TriviaQA with `load_dataset` - custom `cache_dir`
|
Train, Validation, and Test splits contain 138384, 18669, and 17210 samples respectively. It takes some time to read the samples. Even in your colab notebook it was reading the samples before you killed the process. Let me know if it works now!
|
Hello,
I'm having issue downloading TriviaQA dataset with `load_dataset`.
## Environment info
- `datasets` version: 1.1.3
- Platform: Linux-4.19.129-aufs-1-x86_64-with-debian-10.1
- Python version: 3.7.3
## The code I'm running:
```python
import datasets
dataset = datasets.load_dataset("trivia_qa", "rc", cache_dir = "./datasets")
```
## The output:
1. Download begins:
```
Downloading and preparing dataset trivia_qa/rc (download: 2.48 GiB, generated: 14.92 GiB, post-processed: Unknown size, total: 17.40 GiB) to /cs/labs/gabis/sapirweissbuch/tr
ivia_qa/rc/1.1.0/e734e28133f4d9a353af322aa52b9f266f6f27cbf2f072690a1694e577546b0d...
Downloading: 17%|███████████████████▉ | 446M/2.67G [00:37<04:45, 7.77MB/s]
```
2. 100% is reached
3. It got stuck here for about an hour, and added additional 30G of data to "./datasets" directory. I killed the process eventually.
A similar issue can be observed in Google Colab:
https://colab.research.google.com/drive/1nn1Lw02GhfGFylzbS2j6yksGjPo7kkN-?usp=sharing
## Expected behaviour:
The dataset "TriviaQA" should be successfully downloaded.
| 42 |
Bug: Can't download TriviaQA with `load_dataset` - custom `cache_dir`
|
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] |
https://github.com/huggingface/datasets/issues/1615
|
Bug: Can't download TriviaQA with `load_dataset` - custom `cache_dir`
|
Hi, it works on colab but it still doesn't work on my computer, same problem as before - overly large and long extraction process.
I have to use a custom 'cache_dir' because I don't have any space left in my home directory where it is defaulted, maybe this could be the issue?
|
Hello,
I'm having issue downloading TriviaQA dataset with `load_dataset`.
## Environment info
- `datasets` version: 1.1.3
- Platform: Linux-4.19.129-aufs-1-x86_64-with-debian-10.1
- Python version: 3.7.3
## The code I'm running:
```python
import datasets
dataset = datasets.load_dataset("trivia_qa", "rc", cache_dir = "./datasets")
```
## The output:
1. Download begins:
```
Downloading and preparing dataset trivia_qa/rc (download: 2.48 GiB, generated: 14.92 GiB, post-processed: Unknown size, total: 17.40 GiB) to /cs/labs/gabis/sapirweissbuch/tr
ivia_qa/rc/1.1.0/e734e28133f4d9a353af322aa52b9f266f6f27cbf2f072690a1694e577546b0d...
Downloading: 17%|███████████████████▉ | 446M/2.67G [00:37<04:45, 7.77MB/s]
```
2. 100% is reached
3. It got stuck here for about an hour, and added additional 30G of data to "./datasets" directory. I killed the process eventually.
A similar issue can be observed in Google Colab:
https://colab.research.google.com/drive/1nn1Lw02GhfGFylzbS2j6yksGjPo7kkN-?usp=sharing
## Expected behaviour:
The dataset "TriviaQA" should be successfully downloaded.
| 52 |
Bug: Can't download TriviaQA with `load_dataset` - custom `cache_dir`
|
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] |
https://github.com/huggingface/datasets/issues/1615
|
Bug: Can't download TriviaQA with `load_dataset` - custom `cache_dir`
|
I tried running this again - More details of the problem:
Code:
```
datasets.load_dataset("trivia_qa", "rc", cache_dir="/path/to/cache")
```
The output:
```
Downloading and preparing dataset trivia_qa/rc (download: 2.48 GiB, generated: 14.92 GiB, post-processed: Unknown size, total: 17.40 GiB) to path/to/cache/trivia_qa/rc/1.1.0/e734e28133f4d9a353af322aa52b9f266f6f27cbf2f072690a1694e577546b0d...
Downloading: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 2.67G/2.67G [03:38<00:00, 12.2MB/s]
```
The process continues (no progress bar is visible).
I tried `du -sh .` in `path/to/cache`, and the size keeps increasing, reached 35G before I killed the process.
Google Colab with custom `cache_dir` has same issue.
https://colab.research.google.com/drive/1nn1Lw02GhfGFylzbS2j6yksGjPo7kkN-?usp=sharing#scrollTo=2G2O0AeNIXan
|
Hello,
I'm having issue downloading TriviaQA dataset with `load_dataset`.
## Environment info
- `datasets` version: 1.1.3
- Platform: Linux-4.19.129-aufs-1-x86_64-with-debian-10.1
- Python version: 3.7.3
## The code I'm running:
```python
import datasets
dataset = datasets.load_dataset("trivia_qa", "rc", cache_dir = "./datasets")
```
## The output:
1. Download begins:
```
Downloading and preparing dataset trivia_qa/rc (download: 2.48 GiB, generated: 14.92 GiB, post-processed: Unknown size, total: 17.40 GiB) to /cs/labs/gabis/sapirweissbuch/tr
ivia_qa/rc/1.1.0/e734e28133f4d9a353af322aa52b9f266f6f27cbf2f072690a1694e577546b0d...
Downloading: 17%|███████████████████▉ | 446M/2.67G [00:37<04:45, 7.77MB/s]
```
2. 100% is reached
3. It got stuck here for about an hour, and added additional 30G of data to "./datasets" directory. I killed the process eventually.
A similar issue can be observed in Google Colab:
https://colab.research.google.com/drive/1nn1Lw02GhfGFylzbS2j6yksGjPo7kkN-?usp=sharing
## Expected behaviour:
The dataset "TriviaQA" should be successfully downloaded.
| 81 |
Bug: Can't download TriviaQA with `load_dataset` - custom `cache_dir`
|
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] |
https://github.com/huggingface/datasets/issues/1615
|
Bug: Can't download TriviaQA with `load_dataset` - custom `cache_dir`
|
1) You can clear the huggingface folder in your `.cache` directory to use default directory for datasets. Speed of extraction and loading of samples depends a lot on your machine's configurations too.
2) I tried on colab `dataset = datasets.load_dataset("trivia_qa", "rc", cache_dir = "./datasets")`. After memory usage reached around 42GB (starting from 32GB used already), the dataset was loaded in the memory. Even Your colab notebook shows
which means it's loaded now.
|
Hello,
I'm having issue downloading TriviaQA dataset with `load_dataset`.
## Environment info
- `datasets` version: 1.1.3
- Platform: Linux-4.19.129-aufs-1-x86_64-with-debian-10.1
- Python version: 3.7.3
## The code I'm running:
```python
import datasets
dataset = datasets.load_dataset("trivia_qa", "rc", cache_dir = "./datasets")
```
## The output:
1. Download begins:
```
Downloading and preparing dataset trivia_qa/rc (download: 2.48 GiB, generated: 14.92 GiB, post-processed: Unknown size, total: 17.40 GiB) to /cs/labs/gabis/sapirweissbuch/tr
ivia_qa/rc/1.1.0/e734e28133f4d9a353af322aa52b9f266f6f27cbf2f072690a1694e577546b0d...
Downloading: 17%|███████████████████▉ | 446M/2.67G [00:37<04:45, 7.77MB/s]
```
2. 100% is reached
3. It got stuck here for about an hour, and added additional 30G of data to "./datasets" directory. I killed the process eventually.
A similar issue can be observed in Google Colab:
https://colab.research.google.com/drive/1nn1Lw02GhfGFylzbS2j6yksGjPo7kkN-?usp=sharing
## Expected behaviour:
The dataset "TriviaQA" should be successfully downloaded.
| 73 |
Bug: Can't download TriviaQA with `load_dataset` - custom `cache_dir`
|
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] |
https://github.com/huggingface/datasets/issues/1615
|
Bug: Can't download TriviaQA with `load_dataset` - custom `cache_dir`
|
Facing the same issue.
I am able to download datasets without `cache_dir`, however, when I specify the `cache_dir`, the process hangs indefinitely after partial download.
Tried for `data = load_dataset("cnn_dailymail", "3.0.0")`
|
Hello,
I'm having issue downloading TriviaQA dataset with `load_dataset`.
## Environment info
- `datasets` version: 1.1.3
- Platform: Linux-4.19.129-aufs-1-x86_64-with-debian-10.1
- Python version: 3.7.3
## The code I'm running:
```python
import datasets
dataset = datasets.load_dataset("trivia_qa", "rc", cache_dir = "./datasets")
```
## The output:
1. Download begins:
```
Downloading and preparing dataset trivia_qa/rc (download: 2.48 GiB, generated: 14.92 GiB, post-processed: Unknown size, total: 17.40 GiB) to /cs/labs/gabis/sapirweissbuch/tr
ivia_qa/rc/1.1.0/e734e28133f4d9a353af322aa52b9f266f6f27cbf2f072690a1694e577546b0d...
Downloading: 17%|███████████████████▉ | 446M/2.67G [00:37<04:45, 7.77MB/s]
```
2. 100% is reached
3. It got stuck here for about an hour, and added additional 30G of data to "./datasets" directory. I killed the process eventually.
A similar issue can be observed in Google Colab:
https://colab.research.google.com/drive/1nn1Lw02GhfGFylzbS2j6yksGjPo7kkN-?usp=sharing
## Expected behaviour:
The dataset "TriviaQA" should be successfully downloaded.
| 31 |
Bug: Can't download TriviaQA with `load_dataset` - custom `cache_dir`
|
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] |
https://github.com/huggingface/datasets/issues/1615
|
Bug: Can't download TriviaQA with `load_dataset` - custom `cache_dir`
|
Hi @ashutoshml,
I tried this and it worked for me:
`data = load_dataset("cnn_dailymail", "3.0.0", cache_dir="./dummy")`
I'm using datasets==1.8.0. It took around 3-4 mins for dataset to unpack and start loading examples.
|
Hello,
I'm having issue downloading TriviaQA dataset with `load_dataset`.
## Environment info
- `datasets` version: 1.1.3
- Platform: Linux-4.19.129-aufs-1-x86_64-with-debian-10.1
- Python version: 3.7.3
## The code I'm running:
```python
import datasets
dataset = datasets.load_dataset("trivia_qa", "rc", cache_dir = "./datasets")
```
## The output:
1. Download begins:
```
Downloading and preparing dataset trivia_qa/rc (download: 2.48 GiB, generated: 14.92 GiB, post-processed: Unknown size, total: 17.40 GiB) to /cs/labs/gabis/sapirweissbuch/tr
ivia_qa/rc/1.1.0/e734e28133f4d9a353af322aa52b9f266f6f27cbf2f072690a1694e577546b0d...
Downloading: 17%|███████████████████▉ | 446M/2.67G [00:37<04:45, 7.77MB/s]
```
2. 100% is reached
3. It got stuck here for about an hour, and added additional 30G of data to "./datasets" directory. I killed the process eventually.
A similar issue can be observed in Google Colab:
https://colab.research.google.com/drive/1nn1Lw02GhfGFylzbS2j6yksGjPo7kkN-?usp=sharing
## Expected behaviour:
The dataset "TriviaQA" should be successfully downloaded.
| 31 |
Bug: Can't download TriviaQA with `load_dataset` - custom `cache_dir`
|
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] |
https://github.com/huggingface/datasets/issues/1615
|
Bug: Can't download TriviaQA with `load_dataset` - custom `cache_dir`
|
Ok. I waited for 20-30 mins, and it still is stuck.
I am using datasets==1.8.0.
Is there anyway to check what is happening? like a` --verbose` flag?
|
Hello,
I'm having issue downloading TriviaQA dataset with `load_dataset`.
## Environment info
- `datasets` version: 1.1.3
- Platform: Linux-4.19.129-aufs-1-x86_64-with-debian-10.1
- Python version: 3.7.3
## The code I'm running:
```python
import datasets
dataset = datasets.load_dataset("trivia_qa", "rc", cache_dir = "./datasets")
```
## The output:
1. Download begins:
```
Downloading and preparing dataset trivia_qa/rc (download: 2.48 GiB, generated: 14.92 GiB, post-processed: Unknown size, total: 17.40 GiB) to /cs/labs/gabis/sapirweissbuch/tr
ivia_qa/rc/1.1.0/e734e28133f4d9a353af322aa52b9f266f6f27cbf2f072690a1694e577546b0d...
Downloading: 17%|███████████████████▉ | 446M/2.67G [00:37<04:45, 7.77MB/s]
```
2. 100% is reached
3. It got stuck here for about an hour, and added additional 30G of data to "./datasets" directory. I killed the process eventually.
A similar issue can be observed in Google Colab:
https://colab.research.google.com/drive/1nn1Lw02GhfGFylzbS2j6yksGjPo7kkN-?usp=sharing
## Expected behaviour:
The dataset "TriviaQA" should be successfully downloaded.
| 34 |
Bug: Can't download TriviaQA with `load_dataset` - custom `cache_dir`
|
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] |
https://github.com/huggingface/datasets/issues/1611
|
shuffle with torch generator
|
Is there a way one can convert the two generator? not sure overall what alternatives I could have to shuffle the datasets with a torch generator, thanks
|
Hi
I need to shuffle mutliple large datasets with `generator = torch.Generator()` for a distributed sampler which needs to make sure datasets are consistent across different cores, for this, this is really necessary for me to use torch generator, based on documentation this generator is not supported with datasets, I really need to make shuffle work with this generator and I was wondering what I can do about this issue, thanks for your help
@lhoestq
| 27 |
shuffle with torch generator
|
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] |
https://github.com/huggingface/datasets/issues/1611
|
shuffle with torch generator
|
@lhoestq let me please expalin in more details, maybe you could help me suggesting an alternative to solve the issue for now, I have multiple large datasets using huggingface library, then I need to define a distributed sampler on top of it, for this I need to shard the datasets and give each shard to each core, but before sharding I need to shuffle the dataset, if you are familiar with distributed sampler in pytorch, this needs to be done based on seed+epoch generator to make it consistent across the cores they do it through defining a torch generator, I was wondering if you could tell me how I can shuffle the data for now, I am unfortunately blocked by this and have a limited time left, and I greatly appreciate your help on this. thanks
|
Hi
I need to shuffle mutliple large datasets with `generator = torch.Generator()` for a distributed sampler which needs to make sure datasets are consistent across different cores, for this, this is really necessary for me to use torch generator, based on documentation this generator is not supported with datasets, I really need to make shuffle work with this generator and I was wondering what I can do about this issue, thanks for your help
@lhoestq
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shuffle with torch generator
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] |
https://github.com/huggingface/datasets/issues/1611
|
shuffle with torch generator
|
@lhoestq Is there a way I could shuffle the datasets from this library with a custom defined shuffle function? thanks for your help on this.
|
Hi
I need to shuffle mutliple large datasets with `generator = torch.Generator()` for a distributed sampler which needs to make sure datasets are consistent across different cores, for this, this is really necessary for me to use torch generator, based on documentation this generator is not supported with datasets, I really need to make shuffle work with this generator and I was wondering what I can do about this issue, thanks for your help
@lhoestq
| 25 |
shuffle with torch generator
|
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] |
https://github.com/huggingface/datasets/issues/1611
|
shuffle with torch generator
|
Right now the shuffle method only accepts the `seed` (optional int) or `generator` (optional `np.random.Generator`) parameters.
Here is a suggestion to shuffle the data using your own shuffle method using `select`.
`select` can be used to re-order the dataset samples or simply pick a few ones if you want.
It's what is used under the hood when you call `dataset.shuffle`.
To use `select` you must have the list of re-ordered indices of your samples.
Let's say you have a `shuffle` methods that you want to use. Then you can first build your shuffled list of indices:
```python
shuffled_indices = shuffle(range(len(dataset)))
```
Then you can shuffle your dataset using the shuffled indices with
```python
shuffled_dataset = dataset.select(shuffled_indices)
```
Hope that helps
|
Hi
I need to shuffle mutliple large datasets with `generator = torch.Generator()` for a distributed sampler which needs to make sure datasets are consistent across different cores, for this, this is really necessary for me to use torch generator, based on documentation this generator is not supported with datasets, I really need to make shuffle work with this generator and I was wondering what I can do about this issue, thanks for your help
@lhoestq
| 120 |
shuffle with torch generator
|
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] |
https://github.com/huggingface/datasets/issues/1611
|
shuffle with torch generator
|
thank you @lhoestq thank you very much for responding to my question, this greatly helped me and remove the blocking for continuing my work, thanks.
|
Hi
I need to shuffle mutliple large datasets with `generator = torch.Generator()` for a distributed sampler which needs to make sure datasets are consistent across different cores, for this, this is really necessary for me to use torch generator, based on documentation this generator is not supported with datasets, I really need to make shuffle work with this generator and I was wondering what I can do about this issue, thanks for your help
@lhoestq
| 25 |
shuffle with torch generator
|
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] |
https://github.com/huggingface/datasets/issues/1611
|
shuffle with torch generator
|
@lhoestq could you confirm the method proposed does not bring the whole data into memory? thanks
|
Hi
I need to shuffle mutliple large datasets with `generator = torch.Generator()` for a distributed sampler which needs to make sure datasets are consistent across different cores, for this, this is really necessary for me to use torch generator, based on documentation this generator is not supported with datasets, I really need to make shuffle work with this generator and I was wondering what I can do about this issue, thanks for your help
@lhoestq
| 16 |
shuffle with torch generator
|
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] |
https://github.com/huggingface/datasets/issues/1610
|
shuffle does not accept seed
|
Hi Thomas
thanks for reponse, yes, I did checked it, but this does not work for me please see
```
(internship) rkarimi@italix17:/idiap/user/rkarimi/dev$ python
Python 3.7.9 (default, Aug 31 2020, 12:42:55)
[GCC 7.3.0] :: Anaconda, Inc. on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import datasets
2020-12-20 01:48:50.766004: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'libcudart.so.11.0'; dlerror: libcudart.so.11.0: cannot open shared object file: No such file or directory
2020-12-20 01:48:50.766029: I tensorflow/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.
>>> data = datasets.load_dataset("scitail", "snli_format")
cahce dir /idiap/temp/rkarimi/cache_home_1/datasets
cahce dir /idiap/temp/rkarimi/cache_home_1/datasets
Reusing dataset scitail (/idiap/temp/rkarimi/cache_home_1/datasets/scitail/snli_format/1.1.0/fd8ccdfc3134ce86eb4ef10ba7f21ee2a125c946e26bb1dd3625fe74f48d3b90)
>>> data.shuffle(seed=2)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
TypeError: shuffle() got an unexpected keyword argument 'seed'
```
datasets version
`datasets 1.1.2 <pip>
`
|
Hi
I need to shuffle the dataset, but this needs to be based on epoch+seed to be consistent across the cores, when I pass seed to shuffle, this does not accept seed, could you assist me with this? thanks @lhoestq
| 134 |
shuffle does not accept seed
|
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] |
https://github.com/huggingface/datasets/issues/1610
|
shuffle does not accept seed
|
Thanks for reporting !
Indeed it looks like an issue with `suffle` on `DatasetDict`. We're going to fix that.
In the meantime you can shuffle each split (train, validation, test) separately:
```python
shuffled_train_dataset = data["train"].shuffle(seed=42)
```
|
Hi
I need to shuffle the dataset, but this needs to be based on epoch+seed to be consistent across the cores, when I pass seed to shuffle, this does not accept seed, could you assist me with this? thanks @lhoestq
| 36 |
shuffle does not accept seed
|
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] |
https://github.com/huggingface/datasets/issues/1609
|
Not able to use 'jigsaw_toxicity_pred' dataset
|
Hi @jassimran,
The `jigsaw_toxicity_pred` dataset has not been released yet, it will be available with version 2 of `datasets`, coming soon.
You can still access it by installing the master (unreleased) version of datasets directly :
`pip install git+https://github.com/huggingface/datasets.git@master`
Please let me know if this helps
|
When trying to use jigsaw_toxicity_pred dataset, like this in a [colab](https://colab.research.google.com/drive/1LwO2A5M2X5dvhkAFYE4D2CUT3WUdWnkn?usp=sharing):
```
from datasets import list_datasets, list_metrics, load_dataset, load_metric
ds = load_dataset("jigsaw_toxicity_pred")
```
I see below error:
> FileNotFoundError: Couldn't find file at https://raw.githubusercontent.com/huggingface/datasets/1.1.3/datasets/jigsaw_toxicity_pred/jigsaw_toxicity_pred.py
During handling of the above exception, another exception occurred:
FileNotFoundError Traceback (most recent call last)
FileNotFoundError: Couldn't find file at https://s3.amazonaws.com/datasets.huggingface.co/datasets/datasets/jigsaw_toxicity_pred/jigsaw_toxicity_pred.py
During handling of the above exception, another exception occurred:
FileNotFoundError Traceback (most recent call last)
/usr/local/lib/python3.6/dist-packages/datasets/load.py in prepare_module(path, script_version, download_config, download_mode, dataset, force_local_path, **download_kwargs)
280 raise FileNotFoundError(
281 "Couldn't find file locally at {}, or remotely at {} or {}".format(
--> 282 combined_path, github_file_path, file_path
283 )
284 )
FileNotFoundError: Couldn't find file locally at jigsaw_toxicity_pred/jigsaw_toxicity_pred.py, or remotely at https://raw.githubusercontent.com/huggingface/datasets/1.1.3/datasets/jigsaw_toxicity_pred/jigsaw_toxicity_pred.py or https://s3.amazonaws.com/datasets.huggingface.co/datasets/datasets/jigsaw_toxicity_pred/jigsaw_toxicity_pred.py
| 46 |
Not able to use 'jigsaw_toxicity_pred' dataset
|
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] |
https://github.com/huggingface/datasets/issues/1600
|
AttributeError: 'DatasetDict' object has no attribute 'train_test_split'
|
Hi @david-waterworth!
As indicated in the error message, `load_dataset("csv")` returns a `DatasetDict` object, which is mapping of `str` to `Dataset` objects. I believe in this case the behavior is to return a `train` split with all the data.
`train_test_split` is a method of the `Dataset` object, so you will need to do something like this:
```python
dataset_dict = load_dataset(`'csv', data_files='data.txt')
dataset = dataset_dict['split name, eg train']
dataset.train_test_split(test_size=0.1)
```
Please let me know if this helps. 🙂
|
The following code fails with "'DatasetDict' object has no attribute 'train_test_split'" - am I doing something wrong?
```
from datasets import load_dataset
dataset = load_dataset('csv', data_files='data.txt')
dataset = dataset.train_test_split(test_size=0.1)
```
> AttributeError: 'DatasetDict' object has no attribute 'train_test_split'
| 76 |
AttributeError: 'DatasetDict' object has no attribute 'train_test_split'
|
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] |
https://github.com/huggingface/datasets/issues/1600
|
AttributeError: 'DatasetDict' object has no attribute 'train_test_split'
|
Thanks, that's working - the same issue also tripped me up with training.
I also agree https://github.com/huggingface/datasets/issues/767 would be a useful addition.
|
The following code fails with "'DatasetDict' object has no attribute 'train_test_split'" - am I doing something wrong?
```
from datasets import load_dataset
dataset = load_dataset('csv', data_files='data.txt')
dataset = dataset.train_test_split(test_size=0.1)
```
> AttributeError: 'DatasetDict' object has no attribute 'train_test_split'
| 22 |
AttributeError: 'DatasetDict' object has no attribute 'train_test_split'
|
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] |
https://github.com/huggingface/datasets/issues/1600
|
AttributeError: 'DatasetDict' object has no attribute 'train_test_split'
|
> ```python
> dataset_dict = load_dataset(`'csv', data_files='data.txt')
> dataset = dataset_dict['split name, eg train']
> dataset.train_test_split(test_size=0.1)
> ```
I am getting error like
KeyError: 'split name, eg train'
Could you please tell me how to solve this?
|
The following code fails with "'DatasetDict' object has no attribute 'train_test_split'" - am I doing something wrong?
```
from datasets import load_dataset
dataset = load_dataset('csv', data_files='data.txt')
dataset = dataset.train_test_split(test_size=0.1)
```
> AttributeError: 'DatasetDict' object has no attribute 'train_test_split'
| 37 |
AttributeError: 'DatasetDict' object has no attribute 'train_test_split'
|
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] |
https://github.com/huggingface/datasets/issues/1600
|
AttributeError: 'DatasetDict' object has no attribute 'train_test_split'
|
!curl -L "https://app.roboflow.com/ds/YQYgzFyKns?key=f0IwaEetrr" > roboflow.zip; unzip roboflow.zip; rm roboflow.zip
from datasets import load_dataset
dataset = load_dataset("imagefolder", data_dir="/content/")
dataset["train"][0]
dataset["train"][-1]
train_ds = load_dataset("imagefolder", data_dir="/content/train/")
test_ds = load_dataset("imagefolder", data_dir="/content/test/")
val_ds = load_dataset("imagefolder", data_dir="/content/valid/")
train_ds.features
and i got error
AttributeError Traceback (most recent call last)
[<ipython-input-6-289222110c33>](https://localhost:8080/#) in <cell line: 1>()
----> 1 train_ds.features
AttributeError: 'DatasetDict' object has no attribute 'features'
|
The following code fails with "'DatasetDict' object has no attribute 'train_test_split'" - am I doing something wrong?
```
from datasets import load_dataset
dataset = load_dataset('csv', data_files='data.txt')
dataset = dataset.train_test_split(test_size=0.1)
```
> AttributeError: 'DatasetDict' object has no attribute 'train_test_split'
| 57 |
AttributeError: 'DatasetDict' object has no attribute 'train_test_split'
|
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] |
https://github.com/huggingface/datasets/issues/1594
|
connection error
|
This happen quite often when they are too many concurrent requests to github.
i can understand it’s a bit cumbersome to handle on the user side. Maybe we should try a few times in the lib (eg with timeout) before failing, what do you think @lhoestq ?
|
Hi
I am hitting to this error, thanks
```
> Traceback (most recent call last):
File "finetune_t5_trainer.py", line 379, in <module>
main()
File "finetune_t5_trainer.py", line 208, in main
if training_args.do_eval or training_args.evaluation_strategy != EvaluationStrategy.NO
File "finetune_t5_trainer.py", line 207, in <dictcomp>
for task in data_args.eval_tasks}
File "/workdir/seq2seq/data/tasks.py", line 70, in get_dataset
dataset = self.load_dataset(split=split)
File "/workdir/seq2seq/data/tasks.py", line 66, in load_dataset
return datasets.load_dataset(self.task.name, split=split, script_version="master")
File "/usr/local/lib/python3.6/dist-packages/datasets/load.py", line 589, in load_dataset
path, script_version=script_version, download_config=download_config, download_mode=download_mode, dataset=True
File "/usr/local/lib/python3.6/dist-packages/datasets/load.py", line 267, in prepare_module
local_path = cached_path(file_path, download_config=download_config)
File "/usr/local/lib/python3.6/dist-packages/datasets/utils/file_utils.py", line 308, in cached_path
use_etag=download_config.use_etag,
File "/usr/local/lib/python3.6/dist-packages/datasets/utils/file_utils.py", line 487, in get_from_cache
raise ConnectionError("Couldn't reach {}".format(url))
ConnectionError: Couldn't reach https://raw.githubusercontent.com/huggingface/datasets/master/datasets/boolq/boolq.py
el/0 I1217 01:11:33.898849 354161 main shadow.py:210 Current job status: FINISHED
```
| 47 |
connection error
|
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0.0065324995666742325,
0.22784271836280823,
-0.09698403626680374,
-0.1006067544221878,
0.24632525444030762,
-0.15625736117362976,
-0.09777562320232391,
0.14946208894252777,
-0.12805508077144623,
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] |
https://github.com/huggingface/datasets/issues/1594
|
connection error
|
Hi @lhoestq thank you for the modification, I will use`script_version="master"` for now :), to my experience, also setting timeout to a larger number like 3*60 which I normally use helps a lot on this.
|
Hi
I am hitting to this error, thanks
```
> Traceback (most recent call last):
File "finetune_t5_trainer.py", line 379, in <module>
main()
File "finetune_t5_trainer.py", line 208, in main
if training_args.do_eval or training_args.evaluation_strategy != EvaluationStrategy.NO
File "finetune_t5_trainer.py", line 207, in <dictcomp>
for task in data_args.eval_tasks}
File "/workdir/seq2seq/data/tasks.py", line 70, in get_dataset
dataset = self.load_dataset(split=split)
File "/workdir/seq2seq/data/tasks.py", line 66, in load_dataset
return datasets.load_dataset(self.task.name, split=split, script_version="master")
File "/usr/local/lib/python3.6/dist-packages/datasets/load.py", line 589, in load_dataset
path, script_version=script_version, download_config=download_config, download_mode=download_mode, dataset=True
File "/usr/local/lib/python3.6/dist-packages/datasets/load.py", line 267, in prepare_module
local_path = cached_path(file_path, download_config=download_config)
File "/usr/local/lib/python3.6/dist-packages/datasets/utils/file_utils.py", line 308, in cached_path
use_etag=download_config.use_etag,
File "/usr/local/lib/python3.6/dist-packages/datasets/utils/file_utils.py", line 487, in get_from_cache
raise ConnectionError("Couldn't reach {}".format(url))
ConnectionError: Couldn't reach https://raw.githubusercontent.com/huggingface/datasets/master/datasets/boolq/boolq.py
el/0 I1217 01:11:33.898849 354161 main shadow.py:210 Current job status: FINISHED
```
| 34 |
connection error
|
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] |
https://github.com/huggingface/datasets/issues/1593
|
Access to key in DatasetDict map
|
Indeed that would be cool
Also FYI right now the easiest way to do this is
```python
dataset_dict["train"] = dataset_dict["train"].map(my_transform_for_the_train_set)
dataset_dict["test"] = dataset_dict["test"].map(my_transform_for_the_test_set)
```
|
It is possible that we want to do different things in the `map` function (and possibly other functions too) of a `DatasetDict`, depending on the key. I understand that `DatasetDict.map` is a really thin wrapper of `Dataset.map`, so it is easy to directly implement this functionality in the client code. Still, it'd be nice if there can be a flag, similar to `with_indices`, that allows the callable to know the key inside `DatasetDict`.
| 24 |
Access to key in DatasetDict map
|
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] |
https://github.com/huggingface/datasets/issues/1593
|
Access to key in DatasetDict map
|
I don't feel like adding an extra param for this simple usage makes sense, considering how many args `map` already has.
(Feel free to re-open this issue if you don't agree with me)
|
It is possible that we want to do different things in the `map` function (and possibly other functions too) of a `DatasetDict`, depending on the key. I understand that `DatasetDict.map` is a really thin wrapper of `Dataset.map`, so it is easy to directly implement this functionality in the client code. Still, it'd be nice if there can be a flag, similar to `with_indices`, that allows the callable to know the key inside `DatasetDict`.
| 33 |
Access to key in DatasetDict map
|
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] |
https://github.com/huggingface/datasets/issues/1593
|
Access to key in DatasetDict map
|
I still think this is useful, since it's common that the data processing is different for training/dev/testing. And I don't know if the fact that `map` currently takes many arguments is a good reason not to support a useful feature.
|
It is possible that we want to do different things in the `map` function (and possibly other functions too) of a `DatasetDict`, depending on the key. I understand that `DatasetDict.map` is a really thin wrapper of `Dataset.map`, so it is easy to directly implement this functionality in the client code. Still, it'd be nice if there can be a flag, similar to `with_indices`, that allows the callable to know the key inside `DatasetDict`.
| 40 |
Access to key in DatasetDict map
|
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] |
https://github.com/huggingface/datasets/issues/1591
|
IWSLT-17 Link Broken
|
Sorry, this is a duplicate of #1287. Not sure why it didn't come up when I searched `iwslt` in the issues list.
|
```
FileNotFoundError: Couldn't find file at https://wit3.fbk.eu/archive/2017-01-trnmted//texts/DeEnItNlRo/DeEnItNlRo/DeEnItNlRo-DeEnItNlRo.tgz
```
| 22 |
IWSLT-17 Link Broken
|
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] |
https://github.com/huggingface/datasets/issues/1590
|
Add helper to resolve namespace collision
|
I was thinking about using something like [importlib](https://docs.python.org/3/library/importlib.html#importing-a-source-file-directly) to over-ride the collision.
**Reason requested**: I use the [following template](https://github.com/jramapuram/ml_base/) repo where I house all my datasets as a submodule.
|
Many projects use a module called `datasets`, however this is incompatible with huggingface datasets. It would be great if there if there was some helper or similar function to resolve such a common conflict.
| 29 |
Add helper to resolve namespace collision
|
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] |
https://github.com/huggingface/datasets/issues/1590
|
Add helper to resolve namespace collision
|
Alternatively huggingface could consider some submodule type structure like:
`import huggingface.datasets`
`import huggingface.transformers`
`datasets` is a very common module in ML and should be an end-user decision and not scope all of python ¯\_(ツ)_/¯
|
Many projects use a module called `datasets`, however this is incompatible with huggingface datasets. It would be great if there if there was some helper or similar function to resolve such a common conflict.
| 34 |
Add helper to resolve namespace collision
|
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] |
https://github.com/huggingface/datasets/issues/1590
|
Add helper to resolve namespace collision
|
It also wasn't initially obvious to me that the samples which contain `import datasets` were in fact importing a huggingface library (in fact all the huggingface imports are very generic - transformers, tokenizers, datasets...)
|
Many projects use a module called `datasets`, however this is incompatible with huggingface datasets. It would be great if there if there was some helper or similar function to resolve such a common conflict.
| 34 |
Add helper to resolve namespace collision
|
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] |
https://github.com/huggingface/datasets/issues/1585
|
FileNotFoundError for `amazon_polarity`
|
Hi @phtephanx , the `amazon_polarity` dataset has not been released yet. It will be available in the coming soon v2of `datasets` :)
You can still access it now if you want, but you will need to install datasets via the master branch:
`pip install git+https://github.com/huggingface/datasets.git@master`
|
Version: `datasets==v1.1.3`
### Reproduction
```python
from datasets import load_dataset
data = load_dataset("amazon_polarity")
```
crashes with
```bash
FileNotFoundError: Couldn't find file at https://raw.githubusercontent.com/huggingface/datasets/1.1.3/datasets/amazon_polarity/amazon_polarity.py
```
and
```bash
FileNotFoundError: Couldn't find file at https://s3.amazonaws.com/datasets.huggingface.co/datasets/datasets/amazon_polarity/amazon_polarity.py
```
and
```bash
FileNotFoundError: Couldn't find file locally at amazon_polarity/amazon_polarity.py, or remotely at https://raw.githubusercontent.com/huggingface/datasets/1.1.3/datasets/amazon_polarity/amazon_polarity.py or https://s3.amazonaws.com/datasets.huggingface.co/datasets/datasets/amazon_polarity/amazon_polarity.py
```
| 45 |
FileNotFoundError for `amazon_polarity`
|
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] |
https://github.com/huggingface/datasets/issues/1581
|
Installing datasets and transformers in a tensorflow docker image throws Permission Error on 'import transformers'
|
Thanks for reporting !
You can override the directory in which cache file are stored using for example
```
ENV HF_HOME="/root/cache/hf_cache_home"
```
This way both `transformers` and `datasets` will use this directory instead of the default `.cache`
|
I am using a docker container, based on latest tensorflow-gpu image, to run transformers and datasets (4.0.1 and 1.1.3 respectively - Dockerfile attached below). Importing transformers throws a Permission Error to access `/.cache`:
```
$ docker run --gpus=all --rm -it -u $(id -u):$(id -g) -v $(pwd)/data:/root/data -v $(pwd):/root -v $(pwd)/models/:/root/models -v $(pwd)/saved_models/:/root/saved_models -e "HOST_HOSTNAME=$(hostname)" hf-error:latest /bin/bash
________ _______________
___ __/__________________________________ ____/__ /________ __
__ / _ _ \_ __ \_ ___/ __ \_ ___/_ /_ __ /_ __ \_ | /| / /
_ / / __/ / / /(__ )/ /_/ / / _ __/ _ / / /_/ /_ |/ |/ /
/_/ \___//_/ /_//____/ \____//_/ /_/ /_/ \____/____/|__/
You are running this container as user with ID 1000 and group 1000,
which should map to the ID and group for your user on the Docker host. Great!
tf-docker /root > python
Python 3.6.9 (default, Oct 8 2020, 12:12:24)
[GCC 8.4.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import transformers
2020-12-15 23:53:21.165827: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/usr/local/lib/python3.6/dist-packages/transformers/__init__.py", line 22, in <module>
from .integrations import ( # isort:skip
File "/usr/local/lib/python3.6/dist-packages/transformers/integrations.py", line 5, in <module>
from .trainer_utils import EvaluationStrategy
File "/usr/local/lib/python3.6/dist-packages/transformers/trainer_utils.py", line 25, in <module>
from .file_utils import is_tf_available, is_torch_available, is_torch_tpu_available
File "/usr/local/lib/python3.6/dist-packages/transformers/file_utils.py", line 88, in <module>
import datasets # noqa: F401
File "/usr/local/lib/python3.6/dist-packages/datasets/__init__.py", line 26, in <module>
from .arrow_dataset import Dataset, concatenate_datasets
File "/usr/local/lib/python3.6/dist-packages/datasets/arrow_dataset.py", line 40, in <module>
from .arrow_reader import ArrowReader
File "/usr/local/lib/python3.6/dist-packages/datasets/arrow_reader.py", line 31, in <module>
from .utils import cached_path, logging
File "/usr/local/lib/python3.6/dist-packages/datasets/utils/__init__.py", line 20, in <module>
from .download_manager import DownloadManager, GenerateMode
File "/usr/local/lib/python3.6/dist-packages/datasets/utils/download_manager.py", line 25, in <module>
from .file_utils import HF_DATASETS_CACHE, cached_path, get_from_cache, hash_url_to_filename
File "/usr/local/lib/python3.6/dist-packages/datasets/utils/file_utils.py", line 118, in <module>
os.makedirs(HF_MODULES_CACHE, exist_ok=True)
File "/usr/lib/python3.6/os.py", line 210, in makedirs
makedirs(head, mode, exist_ok)
File "/usr/lib/python3.6/os.py", line 210, in makedirs
makedirs(head, mode, exist_ok)
File "/usr/lib/python3.6/os.py", line 220, in makedirs
mkdir(name, mode)
PermissionError: [Errno 13] Permission denied: '/.cache'
```
I've pinned the problem to `RUN pip install datasets`, and by commenting it you can actually import transformers correctly. Another workaround I've found is creating the directory and giving permissions to it directly on the Dockerfile.
```
FROM tensorflow/tensorflow:latest-gpu-jupyter
WORKDIR /root
EXPOSE 80
EXPOSE 8888
EXPOSE 6006
ENV SHELL /bin/bash
ENV PATH="/root/.local/bin:${PATH}"
ENV CUDA_CACHE_PATH="/root/cache/cuda"
ENV CUDA_CACHE_MAXSIZE="4294967296"
ENV TFHUB_CACHE_DIR="/root/cache/tfhub"
RUN pip install --upgrade pip
RUN apt update -y && apt upgrade -y
RUN pip install transformers
#Installing datasets will throw the error, try commenting and rebuilding
RUN pip install datasets
#Another workaround is creating the directory and give permissions explicitly
#RUN mkdir /.cache
#RUN chmod 777 /.cache
```
| 37 |
Installing datasets and transformers in a tensorflow docker image throws Permission Error on 'import transformers'
|
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] |
https://github.com/huggingface/datasets/issues/1581
|
Installing datasets and transformers in a tensorflow docker image throws Permission Error on 'import transformers'
|
> Thanks for reporting !
> You can override the directory in which cache file are stored using for example
>
> ```
> ENV HF_HOME="/root/cache/hf_cache_home"
> ```
>
> This way both `transformers` and `datasets` will use this directory instead of the default `.cache`
can we disable caching directly?
|
I am using a docker container, based on latest tensorflow-gpu image, to run transformers and datasets (4.0.1 and 1.1.3 respectively - Dockerfile attached below). Importing transformers throws a Permission Error to access `/.cache`:
```
$ docker run --gpus=all --rm -it -u $(id -u):$(id -g) -v $(pwd)/data:/root/data -v $(pwd):/root -v $(pwd)/models/:/root/models -v $(pwd)/saved_models/:/root/saved_models -e "HOST_HOSTNAME=$(hostname)" hf-error:latest /bin/bash
________ _______________
___ __/__________________________________ ____/__ /________ __
__ / _ _ \_ __ \_ ___/ __ \_ ___/_ /_ __ /_ __ \_ | /| / /
_ / / __/ / / /(__ )/ /_/ / / _ __/ _ / / /_/ /_ |/ |/ /
/_/ \___//_/ /_//____/ \____//_/ /_/ /_/ \____/____/|__/
You are running this container as user with ID 1000 and group 1000,
which should map to the ID and group for your user on the Docker host. Great!
tf-docker /root > python
Python 3.6.9 (default, Oct 8 2020, 12:12:24)
[GCC 8.4.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import transformers
2020-12-15 23:53:21.165827: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/usr/local/lib/python3.6/dist-packages/transformers/__init__.py", line 22, in <module>
from .integrations import ( # isort:skip
File "/usr/local/lib/python3.6/dist-packages/transformers/integrations.py", line 5, in <module>
from .trainer_utils import EvaluationStrategy
File "/usr/local/lib/python3.6/dist-packages/transformers/trainer_utils.py", line 25, in <module>
from .file_utils import is_tf_available, is_torch_available, is_torch_tpu_available
File "/usr/local/lib/python3.6/dist-packages/transformers/file_utils.py", line 88, in <module>
import datasets # noqa: F401
File "/usr/local/lib/python3.6/dist-packages/datasets/__init__.py", line 26, in <module>
from .arrow_dataset import Dataset, concatenate_datasets
File "/usr/local/lib/python3.6/dist-packages/datasets/arrow_dataset.py", line 40, in <module>
from .arrow_reader import ArrowReader
File "/usr/local/lib/python3.6/dist-packages/datasets/arrow_reader.py", line 31, in <module>
from .utils import cached_path, logging
File "/usr/local/lib/python3.6/dist-packages/datasets/utils/__init__.py", line 20, in <module>
from .download_manager import DownloadManager, GenerateMode
File "/usr/local/lib/python3.6/dist-packages/datasets/utils/download_manager.py", line 25, in <module>
from .file_utils import HF_DATASETS_CACHE, cached_path, get_from_cache, hash_url_to_filename
File "/usr/local/lib/python3.6/dist-packages/datasets/utils/file_utils.py", line 118, in <module>
os.makedirs(HF_MODULES_CACHE, exist_ok=True)
File "/usr/lib/python3.6/os.py", line 210, in makedirs
makedirs(head, mode, exist_ok)
File "/usr/lib/python3.6/os.py", line 210, in makedirs
makedirs(head, mode, exist_ok)
File "/usr/lib/python3.6/os.py", line 220, in makedirs
mkdir(name, mode)
PermissionError: [Errno 13] Permission denied: '/.cache'
```
I've pinned the problem to `RUN pip install datasets`, and by commenting it you can actually import transformers correctly. Another workaround I've found is creating the directory and giving permissions to it directly on the Dockerfile.
```
FROM tensorflow/tensorflow:latest-gpu-jupyter
WORKDIR /root
EXPOSE 80
EXPOSE 8888
EXPOSE 6006
ENV SHELL /bin/bash
ENV PATH="/root/.local/bin:${PATH}"
ENV CUDA_CACHE_PATH="/root/cache/cuda"
ENV CUDA_CACHE_MAXSIZE="4294967296"
ENV TFHUB_CACHE_DIR="/root/cache/tfhub"
RUN pip install --upgrade pip
RUN apt update -y && apt upgrade -y
RUN pip install transformers
#Installing datasets will throw the error, try commenting and rebuilding
RUN pip install datasets
#Another workaround is creating the directory and give permissions explicitly
#RUN mkdir /.cache
#RUN chmod 777 /.cache
```
| 50 |
Installing datasets and transformers in a tensorflow docker image throws Permission Error on 'import transformers'
|
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] |
https://github.com/huggingface/datasets/issues/1581
|
Installing datasets and transformers in a tensorflow docker image throws Permission Error on 'import transformers'
|
Hi ! Unfortunately no since we need this directory to load datasets.
When you load a dataset, it downloads the raw data files in the cache directory inside <cache_dir>/downloads. Then it builds the dataset and saves it as arrow data inside <cache_dir>/<dataset_name>.
However you can specify the directory of your choice, and it can be a temporary directory if you want to clean everything up at one point.
|
I am using a docker container, based on latest tensorflow-gpu image, to run transformers and datasets (4.0.1 and 1.1.3 respectively - Dockerfile attached below). Importing transformers throws a Permission Error to access `/.cache`:
```
$ docker run --gpus=all --rm -it -u $(id -u):$(id -g) -v $(pwd)/data:/root/data -v $(pwd):/root -v $(pwd)/models/:/root/models -v $(pwd)/saved_models/:/root/saved_models -e "HOST_HOSTNAME=$(hostname)" hf-error:latest /bin/bash
________ _______________
___ __/__________________________________ ____/__ /________ __
__ / _ _ \_ __ \_ ___/ __ \_ ___/_ /_ __ /_ __ \_ | /| / /
_ / / __/ / / /(__ )/ /_/ / / _ __/ _ / / /_/ /_ |/ |/ /
/_/ \___//_/ /_//____/ \____//_/ /_/ /_/ \____/____/|__/
You are running this container as user with ID 1000 and group 1000,
which should map to the ID and group for your user on the Docker host. Great!
tf-docker /root > python
Python 3.6.9 (default, Oct 8 2020, 12:12:24)
[GCC 8.4.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import transformers
2020-12-15 23:53:21.165827: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/usr/local/lib/python3.6/dist-packages/transformers/__init__.py", line 22, in <module>
from .integrations import ( # isort:skip
File "/usr/local/lib/python3.6/dist-packages/transformers/integrations.py", line 5, in <module>
from .trainer_utils import EvaluationStrategy
File "/usr/local/lib/python3.6/dist-packages/transformers/trainer_utils.py", line 25, in <module>
from .file_utils import is_tf_available, is_torch_available, is_torch_tpu_available
File "/usr/local/lib/python3.6/dist-packages/transformers/file_utils.py", line 88, in <module>
import datasets # noqa: F401
File "/usr/local/lib/python3.6/dist-packages/datasets/__init__.py", line 26, in <module>
from .arrow_dataset import Dataset, concatenate_datasets
File "/usr/local/lib/python3.6/dist-packages/datasets/arrow_dataset.py", line 40, in <module>
from .arrow_reader import ArrowReader
File "/usr/local/lib/python3.6/dist-packages/datasets/arrow_reader.py", line 31, in <module>
from .utils import cached_path, logging
File "/usr/local/lib/python3.6/dist-packages/datasets/utils/__init__.py", line 20, in <module>
from .download_manager import DownloadManager, GenerateMode
File "/usr/local/lib/python3.6/dist-packages/datasets/utils/download_manager.py", line 25, in <module>
from .file_utils import HF_DATASETS_CACHE, cached_path, get_from_cache, hash_url_to_filename
File "/usr/local/lib/python3.6/dist-packages/datasets/utils/file_utils.py", line 118, in <module>
os.makedirs(HF_MODULES_CACHE, exist_ok=True)
File "/usr/lib/python3.6/os.py", line 210, in makedirs
makedirs(head, mode, exist_ok)
File "/usr/lib/python3.6/os.py", line 210, in makedirs
makedirs(head, mode, exist_ok)
File "/usr/lib/python3.6/os.py", line 220, in makedirs
mkdir(name, mode)
PermissionError: [Errno 13] Permission denied: '/.cache'
```
I've pinned the problem to `RUN pip install datasets`, and by commenting it you can actually import transformers correctly. Another workaround I've found is creating the directory and giving permissions to it directly on the Dockerfile.
```
FROM tensorflow/tensorflow:latest-gpu-jupyter
WORKDIR /root
EXPOSE 80
EXPOSE 8888
EXPOSE 6006
ENV SHELL /bin/bash
ENV PATH="/root/.local/bin:${PATH}"
ENV CUDA_CACHE_PATH="/root/cache/cuda"
ENV CUDA_CACHE_MAXSIZE="4294967296"
ENV TFHUB_CACHE_DIR="/root/cache/tfhub"
RUN pip install --upgrade pip
RUN apt update -y && apt upgrade -y
RUN pip install transformers
#Installing datasets will throw the error, try commenting and rebuilding
RUN pip install datasets
#Another workaround is creating the directory and give permissions explicitly
#RUN mkdir /.cache
#RUN chmod 777 /.cache
```
| 68 |
Installing datasets and transformers in a tensorflow docker image throws Permission Error on 'import transformers'
|
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] |
https://github.com/huggingface/datasets/issues/1541
|
connection issue while downloading data
|
could you tell me how I can avoid download, by pre-downloading the data first, put them in a folder so the code does not try to redownload? could you tell me the path to put the downloaded data, and how to do it? thanks
@lhoestq
|
Hi
I am running my codes on google cloud, and I am getting this error resulting in the failure of the codes when trying to download the data, could you assist me to solve this? also as a temporary solution, could you tell me how I can increase the number of retries and timeout to at least let the models run for now. thanks
```
Traceback (most recent call last):
File "finetune_t5_trainer.py", line 361, in <module>
main()
File "finetune_t5_trainer.py", line 269, in main
add_prefix=False if training_args.train_adapters else True)
File "/workdir/seq2seq/data/tasks.py", line 70, in get_dataset
dataset = self.load_dataset(split=split)
File "/workdir/seq2seq/data/tasks.py", line 306, in load_dataset
return datasets.load_dataset('glue', 'cola', split=split)
File "/usr/local/lib/python3.6/dist-packages/datasets/load.py", line 589, in load_dataset
path, script_version=script_version, download_config=download_config, download_mode=download_mode, dataset=True
File "/usr/local/lib/python3.6/dist-packages/datasets/load.py", line 263, in prepare_module
head_hf_s3(path, filename=name, dataset=dataset)
File "/usr/local/lib/python3.6/dist-packages/datasets/utils/file_utils.py", line 200, in head_hf_s3
return http_head(hf_bucket_url(identifier=identifier, filename=filename, use_cdn=use_cdn, dataset=dataset))
File "/usr/local/lib/python3.6/dist-packages/datasets/utils/file_utils.py", line 403, in http_head
url, proxies=proxies, headers=headers, cookies=cookies, allow_redirects=allow_redirects, timeout=timeout
File "/usr/local/lib/python3.6/dist-packages/requests/api.py", line 104, in head
return request('head', url, **kwargs)
File "/usr/local/lib/python3.6/dist-packages/requests/api.py", line 61, in request
return session.request(method=method, url=url, **kwargs)
File "/usr/local/lib/python3.6/dist-packages/requests/sessions.py", line 542, in request
resp = self.send(prep, **send_kwargs)
File "/usr/local/lib/python3.6/dist-packages/requests/sessions.py", line 655, in send
r = adapter.send(request, **kwargs)
File "/usr/local/lib/python3.6/dist-packages/requests/adapters.py", line 504, in send
raise ConnectTimeout(e, request=request)
requests.exceptions.ConnectTimeout: HTTPSConnectionPool(host='s3.amazonaws.com', port=443): Max retries exceeded with url: /datasets.huggingface.co/datasets/datasets/glue/glue.py (Caused by ConnectTimeoutError(<urllib3.connection.HTTPSConnection object at 0x7f47db511e80>, 'Connection to s3.amazonaws.com timed out. (connect timeout=10)'))
```
| 45 |
connection issue while downloading data
|
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] |
https://github.com/huggingface/datasets/issues/1541
|
connection issue while downloading data
|
Does your instance have an internet connection ?
If you don't have an internet connection you'll need to have the dataset on the instance disk.
To do so first download the dataset on another machine using `load_dataset` and then you can save it in a folder using `my_dataset.save_to_disk("path/to/folder")`. Once the folder is copied on your instance you can reload the dataset with `datasets.load_from_disk("path/to/folder")`
|
Hi
I am running my codes on google cloud, and I am getting this error resulting in the failure of the codes when trying to download the data, could you assist me to solve this? also as a temporary solution, could you tell me how I can increase the number of retries and timeout to at least let the models run for now. thanks
```
Traceback (most recent call last):
File "finetune_t5_trainer.py", line 361, in <module>
main()
File "finetune_t5_trainer.py", line 269, in main
add_prefix=False if training_args.train_adapters else True)
File "/workdir/seq2seq/data/tasks.py", line 70, in get_dataset
dataset = self.load_dataset(split=split)
File "/workdir/seq2seq/data/tasks.py", line 306, in load_dataset
return datasets.load_dataset('glue', 'cola', split=split)
File "/usr/local/lib/python3.6/dist-packages/datasets/load.py", line 589, in load_dataset
path, script_version=script_version, download_config=download_config, download_mode=download_mode, dataset=True
File "/usr/local/lib/python3.6/dist-packages/datasets/load.py", line 263, in prepare_module
head_hf_s3(path, filename=name, dataset=dataset)
File "/usr/local/lib/python3.6/dist-packages/datasets/utils/file_utils.py", line 200, in head_hf_s3
return http_head(hf_bucket_url(identifier=identifier, filename=filename, use_cdn=use_cdn, dataset=dataset))
File "/usr/local/lib/python3.6/dist-packages/datasets/utils/file_utils.py", line 403, in http_head
url, proxies=proxies, headers=headers, cookies=cookies, allow_redirects=allow_redirects, timeout=timeout
File "/usr/local/lib/python3.6/dist-packages/requests/api.py", line 104, in head
return request('head', url, **kwargs)
File "/usr/local/lib/python3.6/dist-packages/requests/api.py", line 61, in request
return session.request(method=method, url=url, **kwargs)
File "/usr/local/lib/python3.6/dist-packages/requests/sessions.py", line 542, in request
resp = self.send(prep, **send_kwargs)
File "/usr/local/lib/python3.6/dist-packages/requests/sessions.py", line 655, in send
r = adapter.send(request, **kwargs)
File "/usr/local/lib/python3.6/dist-packages/requests/adapters.py", line 504, in send
raise ConnectTimeout(e, request=request)
requests.exceptions.ConnectTimeout: HTTPSConnectionPool(host='s3.amazonaws.com', port=443): Max retries exceeded with url: /datasets.huggingface.co/datasets/datasets/glue/glue.py (Caused by ConnectTimeoutError(<urllib3.connection.HTTPSConnection object at 0x7f47db511e80>, 'Connection to s3.amazonaws.com timed out. (connect timeout=10)'))
```
| 63 |
connection issue while downloading data
|
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