ahmedfarazsyk/datasets-github-issues huggingface dataset:
Connection Issues
Author: SaeedNajafi
State: closed

Today, I am getting connection issues while loading a dataset and the metric.
```
Traceback (most recent call last):
  File "src/train.py", line 180, in <module>
    train_dataset, dev_dataset, test_dataset = create_race_dataset()
  File "src/train.py", line 130, in create_race_dataset
    train_dataset = load_dataset("race", "all", split="train")
  File "/Users/saeed/Desktop/codes/repos/dreamscape-qa/env/lib/python3.7/site-packages/datasets/load.py", line 591, in load_dataset
    path, script_version=script_version, download_config=download_config, download_mode=download_mode, dataset=True
  File "/Users/saeed/Desktop/codes/repos/dreamscape-qa/env/lib/python3.7/site-packages/datasets/load.py", line 267, in prepare_module
    local_path = cached_path(file_path, download_config=download_config)
  File "/Users/saeed/Desktop/codes/repos/dreamscape-qa/env/lib/python3.7/site-packages/datasets/utils/file_utils.py", line 343, in cached_path
    max_retries=download_config.max_retries,
  File "/Users/saeed/Desktop/codes/repos/dreamscape-qa/env/lib/python3.7/site-packages/datasets/utils/file_utils.py", line 617, in get_from_cache
    raise ConnectionError("Couldn't reach {}".format(url))
ConnectionError: Couldn't reach https://raw.githubusercontent.com/huggingface/datasets/1.2.1/datasets/race/race.py
```

Or

```
Traceback (most recent call last):
  File "src/train.py", line 105, in <module>
    rouge = datasets.load_metric("rouge")
  File "/Users/saeed/Desktop/codes/repos/dreamscape-qa/env/lib/python3.7/site-packages/datasets/load.py", line 500, in load_metric
    dataset=False,
  File "/Users/saeed/Desktop/codes/repos/dreamscape-qa/env/lib/python3.7/site-packages/datasets/load.py", line 267, in prepare_module
    local_path = cached_path(file_path, download_config=download_config)
  File "/Users/saeed/Desktop/codes/repos/dreamscape-qa/env/lib/python3.7/site-packages/datasets/utils/file_utils.py", line 343, in cached_path
    max_retries=download_config.max_retries,
  File "/Users/saeed/Desktop/codes/repos/dreamscape-qa/env/lib/python3.7/site-packages/datasets/utils/file_utils.py", line 617, in get_from_cache
    raise ConnectionError("Couldn't reach {}".format(url))
ConnectionError: Couldn't reach https://raw.githubusercontent.com/huggingface/datasets/1.2.1/metrics/rouge/rouge.py
```

Comments: Academic WIFI was blocking.
Unable to format dataset to CUDA Tensors
Author: gchhablani
State: closed

Hi,

I came across this [link](https://huggingface.co/docs/datasets/torch_tensorflow.html) where the docs show show to convert a dataset to a particular format. I see that there is an option to convert it to tensors, but I don't see any option to convert it to CUDA tensors.

I tried this, but Dataset doesn't support assignment:
```
  columns=['input_ids', 'token_type_ids', 'attention_mask', 'start_positions','end_positions']

        samples.set_format(type='torch', columns = columns)
        for column in columns:
            samples[column].to(torch.device(self.config.device))
```
There should be an option to do so, or if there is already a way to do this, please let me know.

Thanks,
Gunjan

Comments: Hi ! You can get CUDA tensors with

```python
dataset.set_format("torch", columns=columns, device="cuda")
```

Indeed `set_format` passes the `**kwargs` to `torch.tensor`

Hi @lhoestq,

Thanks a lot. Is this true for all format types?

As in, for 'torch', I can have `**kwargs` to `torch.tensor` and for 'tf' those args are passed to `tf.Tensor`, and the same for 'numpy' and 'pandas'?

Yes the keywords arguments are passed to the convert function like `np.array`, `torch.tensor` or `tensorflow.ragged.constant`.
We don't support the kwargs for pandas on the other hand.

Thanks @lhoestq,
Would it be okay if I added this to the docs and made a PR?

Sure ! Feel free to open a PR to improve the documentation :) 

Closing this issue as it has been resolved.
wikipedia dataset incomplete
Author: ChrisDelClea
State: closed

Hey guys,

I am using the https://github.com/huggingface/datasets/tree/master/datasets/wikipedia dataset.
Unfortunately, I found out that there is an incompleteness for the German dataset.
 For reasons unknown to me, the number of inhabitants has been removed from many pages:
Thorey-sur-Ouche has 128 inhabitants according to the webpage (https://de.wikipedia.org/wiki/Thorey-sur-Ouche).
The pickle file however shows: französische Gemeinde mit  Einwohnern (Stand).
 Is it possible to fix this?

Best regards 
Chris


Comments: Hi !
From what pickle file fo you get this ?
I guess you mean the dataset loaded using `load_dataset` ?

yes sorry, I used the `load_dataset`function and saved the data to a pickle file so I don't always have to reload it and are able to work offline. 

The wikipedia articles are processed using the `mwparserfromhell` library. Even if it works well in most cases, such issues can happen unfortunately. You can find the repo here: https://github.com/earwig/mwparserfromhell

There also exist other datasets based on wikipedia that were processed differently (and are often cleaner) such as `wiki40b`.



ok great. Thank you, @lhoestq.
FewRel
Author: dspoka
State: closed
Labels: name: dataset request

## Adding a Dataset
- **Name:** FewRel
- **Description:**  Large-Scale Supervised Few-Shot Relation Classification Dataset
- **Paper:** @inproceedings{han2018fewrel,
               title={FewRel:A Large-Scale Supervised Few-Shot Relation Classification Dataset with State-of-the-Art Evaluation},
               author={Han, Xu and Zhu, Hao and Yu, Pengfei and Wang, Ziyun and Yao, Yuan and Liu, Zhiyuan and Sun, Maosong},
               booktitle={EMNLP},
               year={2018}}
- **Data:** https://github.com/ProKil/FewRel
- **Motivation:** relationship extraction dataset that's been used by some state of the art systems that should be incorporated.

Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).


Comments: +1

@dspoka Please check the following link : https://github.com/thunlp/FewRel
This link mentions two versions of the datasets. Also, this one seems to be the official link.

I am assuming this is the correct link and implementing based on the same.

Hi @lhoestq,

This issue can be closed, I guess.

Yes :) closing
Thanks again for adding FewRel !

Thanks for adding this @gchhablani ! Sorry didn't see the email notifications sooner!
Ccaligned multilingual translation dataset
Author: flozi00
State: closed
Labels: name: dataset request

## Adding a Dataset
- **Name:** *name of the dataset*
- **Description:** *short description of the dataset (or link to social media or blog post)*
- CCAligned consists of parallel or comparable web-document pairs in 137 languages aligned with English. These web-document pairs were constructed by performing language identification on raw web-documents, and ensuring corresponding language codes were corresponding in the URLs of web documents. This pattern matching approach yielded more than 100 million aligned documents paired with English. Recognizing that each English document was often aligned to mulitple documents in different target language, we can join on English documents to obtain aligned documents that directly pair two non-English documents (e.g., Arabic-French).
- **Paper:** *link to the dataset paper if available*
- https://www.aclweb.org/anthology/2020.emnlp-main.480.pdf
- **Data:** *link to the Github repository or current dataset location*
- http://www.statmt.org/cc-aligned/
- **Motivation:** *what are some good reasons to have this dataset*
- The authors says it's an high quality dataset.
- it's pretty large and includes many language pairs. It could be interesting training mt5 on this task.

Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
datasets slicing with seed 
Author: ghost
State: closed

Hi
I need to slice a dataset with random seed, I looked into documentation here https://huggingface.co/docs/datasets/splits.html 
I could not find a seed option, could you assist me please how I can get a slice for different seeds?
thank you.
@lhoestq  

Comments: Hi :) 
The slicing API from https://huggingface.co/docs/datasets/splits.html doesn't shuffle the data.
You can shuffle and then take a subset of your dataset with
```python
# shuffle and take the first 100 examples
dataset = dataset.shuffle(seed=42).select(range(100))
```

You can find more information about shuffling and selecting rows in the documentation: https://huggingface.co/docs/datasets/processing.html#selecting-sorting-shuffling-splitting-rows

thank you so much

On Mon, Jan 18, 2021 at 3:17 PM Quentin Lhoest <notifications@github.com>
wrote:

> Hi :)
> The slicing API doesn't shuffle the data.
> You can shuffle and then take a subset of your dataset with
>
> # shuffle and take the first 100 examplesdataset = dataset.shuffle(seed=42).select(range(100))
>
> You can find more information about shuffling and selecting rows in the
> documentation:
> https://huggingface.co/docs/datasets/processing.html#selecting-sorting-shuffling-splitting-rows
>
> —
> You are receiving this because you authored the thread.
> Reply to this email directly, view it on GitHub
> <https://github.com/huggingface/datasets/issues/1747#issuecomment-762278134>,
> or unsubscribe
> <https://github.com/notifications/unsubscribe-auth/AM3GZM5D5MDPLJGI4IG3UADS2Q7GPANCNFSM4WHLOZJQ>
> .
>
difference between wsc and wsc.fixed for superglue
Author: ghost
State: closed

Hi
I see two versions of wsc in superglue, and I am not sure what is the differences and which one is the original one. could you help to discuss the differences? thanks @lhoestq 

Comments: From the description given in the dataset script for `wsc.fixed`:
```
This version fixes issues where the spans are not actually substrings of the text.
```
error when run fine_tuning on text_classification
Author: XiaoYang66
State: closed

dataset:sem_eval_2014_task_1
pretrained_model:bert-base-uncased

error description:
when i use these resoruce to train fine_tuning a text_classification on sem_eval_2014_task_1,there always be some problem(when i use other dataset ,there exist the error too). And i followed the colab code (url:https://colab.research.google.com/github/huggingface/notebooks/blob/master/examples/text_classification.ipynb#scrollTo=TlqNaB8jIrJW).


the error is like this :
`File "train.py", line 69, in <module>
    trainer.train()
  File "/home/projects/anaconda3/envs/calibration/lib/python3.7/site-packages/transformers/trainer.py", line 784, in train
    for step, inputs in enumerate(epoch_iterator):
  File "/home/projects/anaconda3/envs/calibration/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 435, in __next__
    data = self._next_data()
  File "/home/projects/anaconda3/envs/calibration/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 475, in _next_data
    data = self._dataset_fetcher.fetch(index)  # may raise StopIteration
  File "/home/projects/anaconda3/envs/calibration/lib/python3.7/site-packages/torch/utils/data/_utils/fetch.py", line 44, in fetch
    data = [self.dataset[idx] for idx in possibly_batched_index]
  File "/home/projects/anaconda3/envs/calibration/lib/python3.7/site-packages/torch/utils/data/_utils/fetch.py", line 44, in <listcomp>
    data = [self.dataset[idx] for idx in possibly_batched_index]
KeyError: 2`

this is my code :
```dataset_name = 'sem_eval_2014_task_1'
num_labels_size = 3
batch_size = 4
model_checkpoint = 'bert-base-uncased'
number_train_epoch = 5

def tokenize(batch):
return tokenizer(batch['premise'], batch['hypothesis'], truncation=True, )

def compute_metrics(pred):
labels = pred.label_ids
preds = pred.predictions.argmax(-1)
precision, recall, f1, _ = precision_recall_fscore_support(labels, preds, average='micro')
acc = accuracy_score(labels, preds)
return {
'accuracy': acc,
'f1': f1,
'precision': precision,
'recall': recall
}

model = BertForSequenceClassification.from_pretrained(model_checkpoint, num_labels=num_labels_size)
tokenizer = BertTokenizerFast.from_pretrained(model_checkpoint, use_fast=True)

train_dataset = load_dataset(dataset_name, split='train')
test_dataset = load_dataset(dataset_name, split='test')

train_encoded_dataset = train_dataset.map(tokenize, batched=True)
test_encoded_dataset = test_dataset.map(tokenize, batched=True)

args = TrainingArguments(
output_dir='./results',
evaluation_strategy="epoch",
learning_rate=2e-5,
per_device_train_batch_size=batch_size,
per_device_eval_batch_size=batch_size,
num_train_epochs=number_train_epoch,
weight_decay=0.01,
do_predict=True,
)
trainer = Trainer(
model=model,
args=args,
compute_metrics=compute_metrics,
train_dataset=train_encoded_dataset,
eval_dataset=test_encoded_dataset,
tokenizer=tokenizer
)

trainer.train()
trainer.evaluate()



Comments: none
connection issue with glue, what is the data url for glue? 
Author: ghost
State: closed

Hi
my codes sometimes fails due to connection issue with glue, could you tell me how I can have the URL datasets library is trying to read GLUE from to test the machines I am working on if there is an issue on my side or not
thanks 

Comments: Hello @juliahane, which config of GLUE causes you trouble?
The URLs are defined in the dataset script source code: https://github.com/huggingface/datasets/blob/master/datasets/glue/glue.py
Couldn't reach swda.py
Author: yangp725
State: closed

ConnectionError: Couldn't reach https://raw.githubusercontent.com/huggingface/datasets/1.2.0/datasets/swda/swda.py


Comments: Hi @yangp725,
The SWDA has been added very recently and has not been released yet, thus it is not available in the `1.2.0` version of 🤗`datasets`.
You can still access it by installing the latest version of the library (master branch), by following instructions in [this issue](https://github.com/huggingface/datasets/issues/1641#issuecomment-751571471).
Let me know if this helps !

Thanks @SBrandeis ,
Problem solved by downloading and installing the latest version datasets.
Is there support for Deep learning datasets?
Author: pablodz
State: closed

I looked around this repository and looking the datasets I think that there's no support for images-datasets. Or am I missing something? For example to add a repo like this https://github.com/DZPeru/fish-datasets

Comments: Hi @ZurMaD!
Thanks for your interest in 🤗 `datasets`. Support for image datasets is at an early stage, with CIFAR-10 added in #1617 
MNIST is also on the way: #1730 

If you feel like adding another image dataset, I would advise starting by reading the [ADD_NEW_DATASET.md](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md) guide. New datasets are always very much appreciated 🚀
load the local dataset
Author: xinjicong
State: closed

your guidebook's example is like
>>>from datasets import load_dataset
>>> dataset = load_dataset('json', data_files='my_file.json')
but the first arg is path...
so how should i do if i want to load the local dataset for model training?
i will be grateful if you can help me handle this problem!
thanks a lot!

Comments: You should rephrase your question or give more examples and details on what you want to do.

it’s not possible to understand it and help you with only this information.

sorry for that.
i want to know how could i load the train set and the test set from the local ,which api or function should i use .


Did you try to follow the instructions in the documentation?
Here: https://huggingface.co/docs/datasets/loading_datasets.html#from-local-files

thanks a lot 
i find that the problem is i dont use vpn...
so i have to keep my net work even if i want to load the local data ?

We will solve this soon (cf #1724)

thanks a lot

Hi! `json` is a packaged dataset now, which means its script comes with the library and doesn't require an internet connection.
could not run models on a offline server successfully
Author: lkcao
State: closed

Hi, I really need your help about this.
I am trying to fine-tuning a RoBERTa on a remote server, which is strictly banning internet. I try to install all the packages by hand and try to run run_mlm.py on the server. It works well on colab, but when I try to run it on this offline server, it shows:
![image](https://user-images.githubusercontent.com/49967236/104276256-25a88600-546a-11eb-9776-8ec695dfa24e.png)

is there anything I can do? Is it possible to download all the things in cache and upload it to the server? Please help me out...

Comments: Transferred to `datasets` based on the stack trace.

Hi @lkcao !
Your issue is indeed related to `datasets`. In addition to installing the package manually, you will need to download the `text.py` script on your server. You'll find it (under `datasets/datasets/text`: https://github.com/huggingface/datasets/blob/master/datasets/text/text.py.
Then you can change the line 221 of `run_mlm_new.py` into:
```python
  datasets = load_dataset('/path/to/text.py', data_files=data_files)
```
Where `/path/to/text.py` is the path on the server where you saved the `text.py` script.

We're working on including the local dataset builders (csv, text, json etc.) directly in the `datasets` package so that they can be used offline

The local dataset builders (csv, text , json and pandas) are now part of the `datasets` package since #1726 :)
You can now use them offline
```python
datasets = load_dataset('text', data_files=data_files)
```

We'll do a new release soon

> The local dataset builders (csv, text , json and pandas) are now part of the `datasets` package since #1726 :)
> You can now use them offline
> 
> ```python
> datasets = load_dataset('text', data_files=data_files)
> ```
> 
> We'll do a new release soon

so the new version release now?

Yes it's been available since datasets 1.3.0 !
SciFact dataset - minor changes
Author: dwadden
State: closed

Hi,

SciFact dataset creator here. First of all, thanks for adding the dataset to Huggingface, much appreciated!

I'd like to make a few minor changes, including the citation information and the `_URL` from which to download the dataset. Can I submit a PR for this?

It also looks like the dataset is being downloaded directly from Huggingface's Google cloud account rather than via the `_URL` in [scifact.py](https://github.com/huggingface/datasets/blob/master/datasets/scifact/scifact.py). Can you help me update the version on gcloud?

Thanks,

Dave

Comments: Hi Dave,
You are more than welcome to open a PR to make these changes! 🤗
You will find the relevant information about opening a PR in the [contributing guide](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md) and in the [dataset addition guide](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).

Pinging also @lhoestq for the Google cloud matter.

> I'd like to make a few minor changes, including the citation information and the `_URL` from which to download the dataset. Can I submit a PR for this?

Sure ! Also feel free to ping us for reviews or if we can help :)

> It also looks like the dataset is being downloaded directly from Huggingface's Google cloud account rather than via the `_URL` in [scifact.py](https://github.com/huggingface/datasets/blob/master/datasets/scifact/scifact.py). Can you help me update the version on gcloud?

What makes you think that ?
Afaik there's no scifact on our google storage




> > I'd like to make a few minor changes, including the citation information and the `_URL` from which to download the dataset. Can I submit a PR for this?
> 
> Sure ! Also feel free to ping us for reviews or if we can help :)
> 
OK! We're organizing a [shared task](https://sdproc.org/2021/sharedtasks.html#sciver) based on the dataset, and I made some updates and changed the download URL - so the current code points to a dead URL. I'll update appropriately once the task is finalized and make a PR.

> > It also looks like the dataset is being downloaded directly from Huggingface's Google cloud account rather than via the `_URL` in [scifact.py](https://github.com/huggingface/datasets/blob/master/datasets/scifact/scifact.py). Can you help me update the version on gcloud?
> 
> What makes you think that ?
> Afaik there's no scifact on our google storage

You're right, I had the data cached on my machine somewhere. 



I opened a PR about this: https://github.com/huggingface/datasets/pull/1780. Closing this issue, will continue there.
Installation using conda
Author: pranav-s
State: closed

Will a conda package for installing datasets be added to the huggingface conda channel? I have installed transformers using conda and would like to use the datasets library to use some of the scripts in the transformers/examples folder but am unable to do so at the moment as datasets can only be installed using pip and using pip in a conda environment is generally a bad idea in my experience.

Comments: Yes indeed the idea is to have the next release on conda cc @LysandreJik 

Great! Did you guys have a timeframe in mind for the next release?

Thank you for all the great work in developing this library.

I think we can have `datasets` on conda by next week. Will see what I can do!

Thank you. Looking forward to it.

`datasets` has been added to the huggingface channel thanks to @LysandreJik :)
It depends on conda-forge though

```
conda install -c huggingface -c conda-forge datasets
```
Databases
Author: JimmyJim1
State: closed

## Adding a Dataset
- **Name:** *name of the dataset*
- **Description:** *short description of the dataset (or link to social media or blog post)*
- **Paper:** *link to the dataset paper if available*
- **Data:** *link to the Github repository or current dataset location*
- **Motivation:** *what are some good reasons to have this dataset*

Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
<html dir="ltr" lang="en" class="focus-outline-visible"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8">
Author: Louiejay54
State: closed

## Adding a Dataset
- **Name:** *name of the dataset*
- **Description:** *short description of the dataset (or link to social media or blog post)*
- **Paper:** *link to the dataset paper if available*
- **Data:** *link to the Github repository or current dataset location*
- **Motivation:** *what are some good reasons to have this dataset*

Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
Some datasets miss dataset_infos.json or dummy_data.zip
Author: madlag
State: closed

While working on dataset REAME generation script at https://github.com/madlag/datasets_readme_generator , I noticed that some datasets miss a dataset_infos.json : 

```
c4
lm1b
reclor
wikihow
```

And some does not have a dummy_data.zip : 

```
kor_nli
math_dataset
mlqa
ms_marco
newsgroup
qa4mre
qangaroo
reddit_tifu
super_glue
trivia_qa
web_of_science
wmt14
wmt15
wmt16
wmt17
wmt18
wmt19
xtreme
```

But it seems that some of those last do have a "dummy" directory .



Comments: Thanks for reporting.
We should indeed add all the missing dummy_data.zip and also the dataset_infos.json at least for lm1b, reclor and wikihow.

For c4 I haven't tested the script and I think we'll require some optimizations regarding beam datasets before processing it.


Closing since the dummy data generation is deprecated now (and the issue with missing metadata seems to be addressed).