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https://api.github.com/repos/huggingface/datasets/issues/2547 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2547/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2547/comments | https://api.github.com/repos/huggingface/datasets/issues/2547/events | https://github.com/huggingface/datasets/issues/2547 | 929,192,329 | MDU6SXNzdWU5MjkxOTIzMjk= | 2,547 | Dataset load_from_disk is too slow | [
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"description": "Something isn't working",
"id": 1935892857,
"name": "bug",
"node_id": "MDU6TGFiZWwxOTM1ODkyODU3",
"url": "https://api.github.com/repos/huggingface/datasets/labels/bug"
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] | open | false | null | 3 | 2021-06-24T12:45:44Z | 2021-06-25T14:56:38Z | null | null | @lhoestq
## Describe the bug
It's not normal that I have to wait 7-8 hours for a dataset to be loaded from disk, as there are no preprocessing steps, it's only loading it with load_from_disk. I have 96 cpus, however only 1 is used for this, which is inefficient. Moreover, its usage is at 1%... This is happening in the context of a language model training, therefore I'm wasting 100$ each time I have to load the dataset from disk again (because the spot instance was stopped by aws and I need to relaunch it for example).
## Steps to reproduce the bug
Just get the oscar in spanish (around 150GGB) and try to first save in disk and then load the processed dataset. It's not dependent on the task you're doing, it just depends on the size of the text dataset.
## Expected results
I expect the dataset to be loaded in a normal time, by using the whole machine for loading it, I mean if you store the dataset in multiple files (.arrow) and then load it from multiple files, you can use multiprocessing for that and therefore don't waste so much time.
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.8.0
- Platform: Ubuntu 18
- Python version: 3.8
I've seen you're planning to include a streaming mode for load_dataset, but that only saves the downloading and processing time, that's not being a problem for me, you cannot save the pure loading from disk time, therefore that's not a solution for my use case or for anyone who wants to use your library for training a language model. | {
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} | https://api.github.com/repos/huggingface/datasets/issues/2547/timeline | null | null | null | null | false | [
"Hi ! It looks like an issue with the virtual disk you are using.\r\n\r\nWe load datasets using memory mapping. In general it makes it possible to load very big files instantaneously since it doesn't have to read the file (it just assigns virtual memory to the file on disk).\r\nHowever there happens to be issues wi... |
https://api.github.com/repos/huggingface/datasets/issues/4627 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4627/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4627/comments | https://api.github.com/repos/huggingface/datasets/issues/4627/events | https://github.com/huggingface/datasets/pull/4627 | 1,293,287,798 | PR_kwDODunzps46zfNa | 4,627 | fixed duplicate calculation of spearmanr function in metrics wrapper. | [] | closed | false | null | 3 | 2022-07-04T15:02:01Z | 2022-07-07T12:41:09Z | 2022-07-07T12:41:09Z | null | During _compute, the scipy.stats spearmanr function was called twice, redundantly, once for calculating the score and once for calculating the p-value, under the conditional branch where return_pvalue=True. I adjusted the _compute function to execute the spearmanr function once, store the results tuple in a temporary variable, and then pass the indexed contents to the expected keys of the returned dictionary. | {
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"Great, can open a PR in `evaluate` as well to optimize this.\r\n\r\nRelatedly, I wanted to add a new metric, Kendall Tau (https://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.kendalltau.html). If I were to open a PR with the wrapper, description, citation, docstrings, readme, etc. would it make more se... |
https://api.github.com/repos/huggingface/datasets/issues/5207 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5207/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5207/comments | https://api.github.com/repos/huggingface/datasets/issues/5207/events | https://github.com/huggingface/datasets/issues/5207 | 1,437,858,506 | I_kwDODunzps5Vs_rK | 5,207 | Connection error of the HuggingFace's dataset Hub due to SSLError with proxy | [] | open | false | null | 3 | 2022-11-07T06:56:23Z | 2022-11-12T15:31:58Z | null | null | ### Describe the bug
It's weird. I could not normally connect the dataset Hub of HuggingFace due to a SSLError in my office.
Even when I try to connect using my company's proxy address (e.g., http_proxy and https_proxy),
I'm getting the SSLError issue. What should I do to download the datanet stored in HuggingFace normally?
I welcome any comments. I think those comments will be helpful to me.
* Dataset address - https://huggingface.co/datasets/moyix/debian_csrc/viewer/moyix--debian_csrc
* Log message
```
............ OMISSION ..............
Traceback (most recent call last):
File "/data/home/geunsik-lim/qtlab/./transformers/examples/pytorch/language-modeling/run_clm.py", line 587, in <module>
main()
File "/data/home/geunsik-lim/qtlab/./transformers/examples/pytorch/language-modeling/run_clm.py", line 278, in main
raw_datasets = load_dataset(
File "/home/geunsik-lim/anaconda3/envs/deepspeed/lib/python3.10/site-packages/datasets/load.py", line 1719, in load_dataset
builder_instance = load_dataset_builder(
File "/home/geunsik-lim/anaconda3/envs/deepspeed/lib/python3.10/site-packages/datasets/load.py", line 1497, in load_dataset_builder
dataset_module = dataset_module_factory(
File "/home/geunsik-lim/anaconda3/envs/deepspeed/lib/python3.10/site-packages/datasets/load.py", line 1222, in dataset_module_factory
raise e1 from None
File "/home/geunsik-lim/anaconda3/envs/deepspeed/lib/python3.10/site-packages/datasets/load.py", line 1179, in dataset_module_factory
raise ConnectionError(f"Couldn't reach '{path}' on the Hub ({type(e).__name__})")
ConnectionError: Couldn't reach 'moyix/debian_csrc' on the Hub (SSLError)
[2022-11-07 15:23:38,476] [INFO] [launch.py:318:sigkill_handler] Killing subprocess 6760
[2022-11-07 15:23:38,476] [ERROR] [launch.py:324:sigkill_handler] ['/home/geunsik-lim/anaconda3/envs/deepspeed/bin/python', '-u', './transformers/examples/pytorch/language-modeling/run_clm.py', '--local_rank=0', '--model_name_or_path=Salesforce/codegen-350M-multi', '--per_device_train_batch_size=1', '--learning_rate', '2e-5', '--num_train_epochs', '1', '--output_dir=./codegen-350M-finetuned', '--overwrite_output_dir', '--dataset_name', 'moyix/debian_csrc', '--cache_dir', '/data/home/geunsik-lim/.cache', '--tokenizer_name', 'Salesforce/codegen-350M-multi', '--block_size', '2048', '--gradient_accumulation_steps', '32', '--do_train', '--fp16', '--deepspeed', 'ds_config_zero2.json'] exits with return code = 1
real 0m7.742s
user 0m4.930s
```
### Steps to reproduce the bug
Steps to reproduce this behavior.
```
(deepspeed) geunsik-lim@ai02:~/qtlab$ ./test_debian_csrc_dataset.py
Traceback (most recent call last):
File "/data/home/geunsik-lim/qtlab/./test_debian_csrc_dataset.py", line 6, in <module>
dataset = load_dataset("moyix/debian_csrc")
File "/home/geunsik-lim/anaconda3/envs/deepspeed/lib/python3.10/site-packages/datasets/load.py", line 1719, in load_dataset
builder_instance = load_dataset_builder(
File "/home/geunsik-lim/anaconda3/envs/deepspeed/lib/python3.10/site-packages/datasets/load.py", line 1497, in load_dataset_builder
dataset_module = dataset_module_factory(
File "/home/geunsik-lim/anaconda3/envs/deepspeed/lib/python3.10/site-packages/datasets/load.py", line 1222, in dataset_module_factory
raise e1 from None
File "/home/geunsik-lim/anaconda3/envs/deepspeed/lib/python3.10/site-packages/datasets/load.py", line 1179, in dataset_module_factory
raise ConnectionError(f"Couldn't reach '{path}' on the Hub ({type(e).__name__})")
ConnectionError: Couldn't reach 'moyix/debian_csrc' on the Hub (SSLError)
(deepspeed) geunsik-lim@ai02:~/qtlab$
(deepspeed) geunsik-lim@ai02:~/qtlab$
(deepspeed) geunsik-lim@ai02:~/qtlab$
(deepspeed) geunsik-lim@ai02:~/qtlab$ cat ./test_debian_csrc_dataset.py
#!/usr/bin/env python
from datasets import load_dataset
dataset = load_dataset("moyix/debian_csrc")
```
1. Adde proxy address of a company in /etc/profile
2. Download dataset with load_dataset() function of datasets package that is provided by HuggingFace.
3. In this case, the address would be "moyix--debian_csrc".
4. I get the "`ConnectionError: Couldn't reach 'moyix/debian_csrc' on the Hub (SSLError`)" error message.
### Expected behavior
* error message:
ConnectionError: Couldn't reach 'moyix/debian_csrc' on the Hub (SSLError)
### Environment info
* software version information:
```
(deepspeed) geunsik-lim@ai02:~$
(deepspeed) geunsik-lim@ai02:~$ conda list -f pytorch
# packages in environment at /home/geunsik-lim/anaconda3/envs/deepspeed:
#
# Name Version Build Channel
pytorch 1.13.0 py3.10_cuda11.7_cudnn8.5.0_0 pytorch
(deepspeed) geunsik-lim@ai02:~$ conda list -f python
# packages in environment at /home/geunsik-lim/anaconda3/envs/deepspeed:
#
# Name Version Build Channel
python 3.10.6 haa1d7c7_1
(deepspeed) geunsik-lim@ai02:~$ conda list -f datasets
# packages in environment at /home/geunsik-lim/anaconda3/envs/deepspeed:
#
# Name Version Build Channel
datasets 2.6.1 py_0 huggingface
(deepspeed) geunsik-lim@ai02:~$ uname -a
Linux ai02 5.4.0-131-generic #147-Ubuntu SMP Fri Oct 14 17:07:22 UTC 2022 x86_64 x86_64 x86_64 GNU/Linux
(deepspeed) geunsik-lim@ai02:~$ cat /etc/lsb-release
DISTRIB_ID=Ubuntu
DISTRIB_RELEASE=20.04
DISTRIB_CODENAME=focal
DISTRIB_DESCRIPTION="Ubuntu 20.04.5 LTS"
``` | {
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"Hi ! It looks like an issue with your python environment, can you make sure you're able to run GET requests to https://huggingface.co using `requests` in python ?",
"Thanks for your reply. Does this mean that I have to use the `do_dataset `function and the `requests `function to download the dataset from the com... |
https://api.github.com/repos/huggingface/datasets/issues/1412 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1412/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1412/comments | https://api.github.com/repos/huggingface/datasets/issues/1412/events | https://github.com/huggingface/datasets/pull/1412 | 760,607,959 | MDExOlB1bGxSZXF1ZXN0NTM1NDEyMDg2 | 1,412 | Adding the ASSIN dataset | [] | closed | false | null | 0 | 2020-12-09T19:27:06Z | 2020-12-11T10:41:10Z | 2020-12-11T10:41:10Z | null | Adding the ASSIN dataset, a Portuguese language dataset for Natural Language Inference and Semantic Similarity Scoring | {
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https://api.github.com/repos/huggingface/datasets/issues/5850 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5850/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5850/comments | https://api.github.com/repos/huggingface/datasets/issues/5850/events | https://github.com/huggingface/datasets/pull/5850 | 1,707,678,911 | PR_kwDODunzps5QZALv | 5,850 | Make packaged builders skip non-supported file formats | [] | open | false | null | 10 | 2023-05-12T13:52:34Z | 2023-06-07T12:26:38Z | null | null | This PR makes packaged builders skip non-supported file formats:
- Csv builder skips non-CSV files
- Analogously for the other builders
Fix #5849. | {
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} | true | [
"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_5850). All of your documentation changes will be reflected on that endpoint.",
"Good idea. @mariosasko!!!\r\n\r\nPlease note that before this PR, the files are not evenly distributed for archives: `_generate_examples` gets a li... |
https://api.github.com/repos/huggingface/datasets/issues/5274 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5274/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5274/comments | https://api.github.com/repos/huggingface/datasets/issues/5274/events | https://github.com/huggingface/datasets/issues/5274 | 1,458,646,455 | I_kwDODunzps5W8S23 | 5,274 | load_dataset possibly broken for gated datasets? | [] | closed | false | null | 9 | 2022-11-21T21:59:53Z | 2023-05-27T00:06:14Z | 2022-11-28T02:50:42Z | null | ### Describe the bug
When trying to download the [winoground dataset](https://huggingface.co/datasets/facebook/winoground), I get this error unless I roll back the version of huggingface-hub:
```
[/usr/local/lib/python3.7/dist-packages/huggingface_hub/utils/_validators.py](https://localhost:8080/#) in validate_repo_id(repo_id)
165 if repo_id.count("/") > 1:
166 raise HFValidationError(
--> 167 "Repo id must be in the form 'repo_name' or 'namespace/repo_name':"
168 f" '{repo_id}'. Use `repo_type` argument if needed."
169 )
HFValidationError: Repo id must be in the form 'repo_name' or 'namespace/repo_name': 'datasets/facebook/winoground'. Use `repo_type` argument if needed
```
### Steps to reproduce the bug
Install requirements:
```
pip install transformers
pip install datasets
# It works if you uncomment the following line, rolling back huggingface hub:
# pip install huggingface-hub==0.10.1
```
Then:
```
from datasets import load_dataset
auth_token = "" # Replace with an auth token, which you can get from your huggingface account: Profile -> Settings -> Access Tokens -> New Token
winoground = load_dataset("facebook/winoground", use_auth_token=auth_token)["test"]
```
### Expected behavior
Downloading of the datset
### Environment info
Just a google colab; see here: https://colab.research.google.com/drive/15wwOSte2CjTazdnCWYUm2VPlFbk2NGc0?usp=sharing | {
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"@BradleyHsu",
"Btw, thanks very much for finding the hub rollback temporary fix and bringing the issue to our attention @KhoomeiK!",
"I see the same issue when calling `load_dataset('poloclub/diffusiondb', 'large_random_1k')` with `datasets==2.7.1` and `huggingface-hub=0.11.0`. No issue with `datasets=2.6.1` a... |
https://api.github.com/repos/huggingface/datasets/issues/5628 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5628/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5628/comments | https://api.github.com/repos/huggingface/datasets/issues/5628/events | https://github.com/huggingface/datasets/pull/5628 | 1,619,641,810 | PR_kwDODunzps5LzVKi | 5,628 | add kwargs to index search | [] | closed | false | null | 1 | 2023-03-10T21:24:58Z | 2023-03-15T14:48:47Z | 2023-03-15T14:46:04Z | null | This PR proposes to add kwargs to index search methods.
This is particularly useful for setting the timeout of a query on elasticsearch.
A typical use case would be:
```python
dset.add_elasticsearch_index("filename", es_client=es_client)
scores, examples = dset.get_nearest_examples("filename", "my_name-train_29", request_timeout=60)
``` | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] |
https://api.github.com/repos/huggingface/datasets/issues/1768 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1768/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1768/comments | https://api.github.com/repos/huggingface/datasets/issues/1768/events | https://github.com/huggingface/datasets/pull/1768 | 792,150,745 | MDExOlB1bGxSZXF1ZXN0NTYwMDgyNzIx | 1,768 | Mention kwargs in the Dataset Formatting docs | [] | closed | false | null | 0 | 2021-01-22T16:43:20Z | 2021-01-31T12:33:10Z | 2021-01-25T09:14:59Z | null | Hi,
This was discussed in Issue #1762 where the docs didn't mention that keyword arguments to `datasets.Dataset.set_format()` are allowed.
To prevent people from having to check the code/method docs, I just added a couple of lines in the docs.
Please let me know your thoughts on this.
Thanks,
Gunjan
@lhoestq | {
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https://api.github.com/repos/huggingface/datasets/issues/5778 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5778/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5778/comments | https://api.github.com/repos/huggingface/datasets/issues/5778/events | https://github.com/huggingface/datasets/issues/5778 | 1,678,125,951 | I_kwDODunzps5kBit_ | 5,778 | Schrödinger's dataset_dict | [] | closed | false | null | 1 | 2023-04-21T08:38:12Z | 2023-07-24T15:15:14Z | 2023-07-24T15:15:14Z | null | ### Describe the bug
If you use load_dataset('json', data_files="path/test.json"), it will return DatasetDict({train:...}).
And if you use load_dataset("path"), it will return DatasetDict({test:...}).
Why can't the output behavior be unified?
### Steps to reproduce the bug
as description above.
### Expected behavior
consistent predictable output.
### Environment info
'2.11.0' | {
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"Hi ! Passing `data_files=\"path/test.json\"` is equivalent to `data_files={\"train\": [\"path/test.json\"]}`, that's why you end up with a train split. If you don't pass `data_files=`, then split names are inferred from the data files names"
] |
https://api.github.com/repos/huggingface/datasets/issues/188 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/188/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/188/comments | https://api.github.com/repos/huggingface/datasets/issues/188/events | https://github.com/huggingface/datasets/issues/188 | 623,890,430 | MDU6SXNzdWU2MjM4OTA0MzA= | 188 | When will the remaining math_dataset modules be added as dataset objects | [] | closed | false | null | 3 | 2020-05-24T15:46:52Z | 2020-05-24T18:53:48Z | 2020-05-24T18:53:48Z | null | Currently only the algebra_linear_1d is supported. Is there a timeline for making the other modules supported. If no timeline is established, how can I help? | {
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"On a similar note it would be nice to differentiate between train-easy, train-medium, and train-hard",
"Hi @tylerroost, we don't have a timeline for this at the moment.\r\nIf you want to give it a look we would be happy to review a PR on it.\r\nAlso, the library is one week old so everything is quite barebones, ... |
https://api.github.com/repos/huggingface/datasets/issues/229 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/229/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/229/comments | https://api.github.com/repos/huggingface/datasets/issues/229/events | https://github.com/huggingface/datasets/pull/229 | 629,956,490 | MDExOlB1bGxSZXF1ZXN0NDI3MTcxMzc5 | 229 | Rename dataset_infos.json to dataset_info.json | [] | closed | false | null | 1 | 2020-06-03T12:31:44Z | 2020-06-03T12:52:54Z | 2020-06-03T12:48:33Z | null | As the file required for the viewing in the live nlp viewer is named as dataset_info.json | {
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"\r\nThis was actually the right name. `dataset_infos.json` is used to have the infos of all the dataset configurations.\r\n\r\nOn the other hand `dataset_info.json` (without 's') is a cache file with the info of one specific configuration.\r\n\r\nTo fix #228, we probably just have to clear and reload the nlp-viewe... |
https://api.github.com/repos/huggingface/datasets/issues/1070 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1070/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1070/comments | https://api.github.com/repos/huggingface/datasets/issues/1070/events | https://github.com/huggingface/datasets/pull/1070 | 756,442,481 | MDExOlB1bGxSZXF1ZXN0NTMxOTg2Nzcz | 1,070 | add conv_ai | [] | closed | false | null | 2 | 2020-12-03T18:25:20Z | 2020-12-04T07:58:35Z | 2020-12-04T06:44:34Z | null | Adding ConvAI dataset https://github.com/DeepPavlov/convai/tree/master/2017 | {
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"This one will make @thomwolf reminisce ;)",
"Merging."
] |
https://api.github.com/repos/huggingface/datasets/issues/2818 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2818/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2818/comments | https://api.github.com/repos/huggingface/datasets/issues/2818/events | https://github.com/huggingface/datasets/issues/2818 | 974,552,009 | MDU6SXNzdWU5NzQ1NTIwMDk= | 2,818 | cannot load data from my loacal path | [
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] | closed | false | null | 1 | 2021-08-19T11:13:30Z | 2023-07-25T17:42:15Z | 2023-07-25T17:42:15Z | null | ## Describe the bug
I just want to directly load data from my local path,but find a bug.And I compare it with pandas to provide my local path is real.
here is my code
```python3
# print my local path
print(config.train_path)
# read data and print data length
tarin=pd.read_csv(config.train_path)
print(len(tarin))
# loading data by load_dataset
data = load_dataset('csv',data_files=config.train_path)
print(len(data))
```
## Steps to reproduce the bug
```python
C:\Users\wie\Documents\项目\文本分类\data\train.csv
7613
Traceback (most recent call last):
File "c:/Users/wie/Documents/项目/文本分类/lib/DataPrecess.py", line 17, in <module>
data = load_dataset('csv',data_files=config.train_path)
File "C:\Users\wie\Miniconda3\lib\site-packages\datasets\load.py", line 830, in load_dataset
**config_kwargs,
File "C:\Users\wie\Miniconda3\lib\site-packages\datasets\load.py", line 710, in load_dataset_builder
**config_kwargs,
File "C:\Users\wie\Miniconda3\lib\site-packages\datasets\builder.py", line 271, in __init__
**config_kwargs,
File "C:\Users\wie\Miniconda3\lib\site-packages\datasets\builder.py", line 386, in _create_builder_config
config_kwargs, custom_features=custom_features, use_auth_token=self.use_auth_token
File "C:\Users\wie\Miniconda3\lib\site-packages\datasets\builder.py", line 156, in create_config_id
raise ValueError("Please provide a valid `data_files` in `DatasetBuilder`")
ValueError: Please provide a valid `data_files` in `DatasetBuilder`
```
## Expected results
A clear and concise description of the expected results.
## Actual results
Specify the actual results or traceback.
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.11.0
- Platform: win10
- Python version: 3.7.9
- PyArrow version: 5.0.0
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"Hi ! The `data_files` parameter must be a string, a list/tuple or a python dict.\r\n\r\nCan you check the type of your `config.train_path` please ? Or use `data_files=str(config.train_path)` ?"
] |
https://api.github.com/repos/huggingface/datasets/issues/2065 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2065/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2065/comments | https://api.github.com/repos/huggingface/datasets/issues/2065/events | https://github.com/huggingface/datasets/issues/2065 | 833,291,432 | MDU6SXNzdWU4MzMyOTE0MzI= | 2,065 | Only user permission of saved cache files, not group | [
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"default": true... | closed | false | null | 26 | 2021-03-17T00:20:22Z | 2023-03-31T12:17:06Z | 2021-05-10T06:45:29Z | null | Hello,
It seems when a cached file is saved from calling `dataset.map` for preprocessing, it gets the user permissions and none of the user's group permissions. As we share data files across members of our team, this is causing a bit of an issue as we have to continually reset the permission of the files. Do you know any ways around this or a way to correctly set the permissions? | {
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"Hi ! Thanks for reporting.\r\n\r\nCurrently there's no way to specify this.\r\n\r\nWhen loading/processing a dataset, the arrow file is written using a temporary file. Then once writing is finished, it's moved to the cache directory (using `shutil.move` [here](https://github.com/huggingface/datasets/blob/f6b8251eb... |
https://api.github.com/repos/huggingface/datasets/issues/1297 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1297/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1297/comments | https://api.github.com/repos/huggingface/datasets/issues/1297/events | https://github.com/huggingface/datasets/pull/1297 | 759,404,103 | MDExOlB1bGxSZXF1ZXN0NTM0NDE1ODMx | 1,297 | OPUS Ted Talks 2013 | [] | closed | false | null | 0 | 2020-12-08T12:25:39Z | 2020-12-08T12:35:50Z | 2020-12-08T12:35:50Z | null | {
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https://api.github.com/repos/huggingface/datasets/issues/3875 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3875/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3875/comments | https://api.github.com/repos/huggingface/datasets/issues/3875/events | https://github.com/huggingface/datasets/pull/3875 | 1,164,029,673 | PR_kwDODunzps40LUuw | 3,875 | Module namespace cleanup for v2.0 | [] | closed | false | null | 4 | 2022-03-09T14:43:07Z | 2022-03-11T15:42:06Z | 2022-03-11T15:42:05Z | null | This is an attempt to make the user-facing `datasets`' submodule namespace cleaner:
In particular, this PR does the following:
* removes the unused `zip_nested` and `flatten_nest_dict` and their accompanying tests
* removes `pyarrow` from the top-level namespace
* properly uses `__all__` and the `from <module> import *` syntax to avoid importing the `<module>`'s submodules
* cleans up the `utils` namespace
* moves the `temp_seed` context manage from `datasets/utils/file_utils.py` to `datasets/utils/py_utils.py` | {
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"will it solve https://github.com/huggingface/datasets-preview-backend/blob/4c542a74244045929615640ccbba5a902c344c5a/pyproject.toml#L85-L89?",
"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3875). All of your documentation changes will be reflected on that endpoint.",
"@s... |
https://api.github.com/repos/huggingface/datasets/issues/1198 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1198/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1198/comments | https://api.github.com/repos/huggingface/datasets/issues/1198/events | https://github.com/huggingface/datasets/pull/1198 | 757,903,453 | MDExOlB1bGxSZXF1ZXN0NTMzMTgwNjAz | 1,198 | Add ALT | [] | closed | false | null | 3 | 2020-12-06T11:25:30Z | 2020-12-10T04:18:12Z | 2020-12-10T04:18:12Z | null | ALT dataset -- https://www2.nict.go.jp/astrec-att/member/mutiyama/ALT/ | {
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"the `RemoteDatasetTest ` erros in the CI are fixed on master so it's fine",
"used `Translation ` feature type and fixed few typos as you suggested.",
"Sorry, I made a mistake. please see new PR here. https://github.com/huggingface/datasets/pull/1436"
] |
https://api.github.com/repos/huggingface/datasets/issues/758 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/758/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/758/comments | https://api.github.com/repos/huggingface/datasets/issues/758/events | https://github.com/huggingface/datasets/issues/758 | 728,638,559 | MDU6SXNzdWU3Mjg2Mzg1NTk= | 758 | Process 0 very slow when using num_procs with map to tokenizer | [] | closed | false | null | 6 | 2020-10-24T02:40:20Z | 2020-10-28T03:59:46Z | 2020-10-28T03:59:45Z | null | <img width="721" alt="image" src="https://user-images.githubusercontent.com/17930170/97066109-776d0d00-15ed-11eb-8bba-bb4d2e0fcc33.png">
The code I am using is
```
dataset = load_dataset("text", data_files=[file_path], split='train')
dataset = dataset.map(lambda ex: tokenizer(ex["text"], add_special_tokens=True,
truncation=True, max_length=args.block_size), num_proc=8)
dataset.set_format(type='torch', columns=['input_ids'])
dataset.save_to_disk(file_path+'.arrow')
```
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"Hi ! Thanks for reporting.\r\nIs the distribution of text length of your data evenly distributed across your dataset ? I mean, could it be because the examples in the first part of your dataset are slower to process ?\r\nAlso could how many CPUs can you use for multiprocessing ?\r\n```python\r\nimport multiprocess... |
https://api.github.com/repos/huggingface/datasets/issues/2106 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2106/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2106/comments | https://api.github.com/repos/huggingface/datasets/issues/2106/events | https://github.com/huggingface/datasets/issues/2106 | 839,084,264 | MDU6SXNzdWU4MzkwODQyNjQ= | 2,106 | WMT19 Dataset for Kazakh-English is not formatted correctly | [
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] | open | false | null | 1 | 2021-03-23T20:14:47Z | 2021-03-25T21:36:20Z | null | null | In addition to the bug of languages being switched from Issue @415, there are incorrect translations in the dataset because the English-Kazakh translations have a one off formatting error.
The News Commentary v14 parallel data set for kk-en from http://www.statmt.org/wmt19/translation-task.html has a bug here:
> Line 94. The Swiss National Bank, for its part, has been battling with the deflationary effects of the franc’s dramatic appreciation over the past few years. Швейцарияның Ұлттық банкі өз тарапынан, соңғы бірнеше жыл ішінде франк құнының қатты өсуінің дефляциялық әсерімен күресіп келеді.
>
> Line 95. Дефляциялық күштер 2008 жылы терең және ұзаққа созылған жаһандық дағдарысқа байланысты орын алған ірі экономикалық және қаржылық орын алмасулардың арқасында босатылды. Жеке қарыз қаражаты үлесінің қысқаруы орталық банктің рефляцияға жұмсалған күш-жігеріне тұрақты соққан қарсы желдей болды.
>
> Line 96. The deflationary forces were unleashed by the major economic and financial dislocations associated with the deep and protracted global crisis that erupted in 2008. Private deleveraging became a steady headwind to central bank efforts to reflate. 2009 жылы, алдыңғы қатарлы экономикалардың шамамен үштен бірі бағаның төмендеуін көрсетті, бұл соғыстан кейінгі жоғары деңгей болды.
As you can see, line 95 has only the Kazakh translation which should be part of line 96. This causes all of the following English-Kazakh translation pairs to be one off rendering ALL of those translations incorrect. This issue was not fixed when the dataset was imported to Huggingface. By running this code
```
import datasets
from datasets import load_dataset
dataset = load_dataset('wmt19', 'kk-en')
for key in dataset['train']['translation']:
if 'The deflationary forces were unleashed by the major economic and financial dislocations associated with the deep and protracted global crisis that erupted in 2008.' in key['kk']:
print(key['en'])
print(key['kk'])
break
```
we get:
> 2009 жылы, алдыңғы қатарлы экономикалардың шамамен үштен бірі бағаның төмендеуін көрсетті, бұл соғыстан кейінгі жоғары деңгей болды.
> The deflationary forces were unleashed by the major economic and financial dislocations associated with the deep and protracted global crisis that erupted in 2008. Private deleveraging became a steady headwind to central bank efforts to reflate.
which shows that the issue still persists in the Huggingface dataset. The Kazakh sentence matches up to the next English sentence in the dataset instead of the current one.
Please let me know if there's you have any ideas to fix this one-off error from the dataset or if this can be fixed by Huggingface. | {
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"Hi ! Thanks for reporting\r\n\r\nBy looking at the raw `news-commentary-v14.en-kk.tsv` file, it looks like there are at least 17 lines with this issue.\r\nMoreover these issues are not always the same:\r\n- L97 is only `kk` text and must be appended at the end of the `kk` text of the **next** line\r\n- L2897 is on... |
https://api.github.com/repos/huggingface/datasets/issues/4546 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4546/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4546/comments | https://api.github.com/repos/huggingface/datasets/issues/4546/events | https://github.com/huggingface/datasets/pull/4546 | 1,282,093,288 | PR_kwDODunzps46Oe_K | 4,546 | [CI] fixing seqeval install in ci by pinning setuptools-scm | [] | closed | false | null | 1 | 2022-06-23T09:24:37Z | 2022-06-23T10:24:16Z | 2022-06-23T10:13:44Z | null | The latest setuptools-scm version supported on 3.6 is 6.4.2. However for some reason circleci has version 7, which doesn't work.
I fixed this by pinning the version of setuptools-scm in the circleci job
Fix https://github.com/huggingface/datasets/issues/4544 | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] |
https://api.github.com/repos/huggingface/datasets/issues/3097 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3097/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3097/comments | https://api.github.com/repos/huggingface/datasets/issues/3097/events | https://github.com/huggingface/datasets/issues/3097 | 1,027,750,811 | I_kwDODunzps49Qjub | 3,097 | `ModuleNotFoundError: No module named 'fsspec.exceptions'` | [
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] | closed | false | null | 1 | 2021-10-15T19:34:38Z | 2021-10-18T07:51:54Z | 2021-10-18T07:51:54Z | null | ## Describe the bug
I keep runnig into a fsspec ModuleNotFound error
## Steps to reproduce the bug
```python
>>> from datasets import get_dataset_infos
2021-10-15 15:25:37.863206: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcudart.so.11.0'; dlerror: libcudart.so.11.0: cannot open shared object file: No such file or directory
2021-10-15 15:25:37.863252: 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.
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/hf/dev/promptsource/.venv/lib/python3.7/site-packages/datasets/__init__.py", line 37, in <module>
from .builder import ArrowBasedBuilder, BeamBasedBuilder, BuilderConfig, DatasetBuilder, GeneratorBasedBuilder
File "/home/hf/dev/promptsource/.venv/lib/python3.7/site-packages/datasets/builder.py", line 56, in <module>
from .utils.streaming_download_manager import StreamingDownloadManager
File "/home/hf/dev/promptsource/.venv/lib/python3.7/site-packages/datasets/utils/streaming_download_manager.py", line 11, in <module>
from fsspec.exceptions import FSTimeoutError
ModuleNotFoundError: No module named 'fsspec.exceptions'
```
Yet, I do have `fsspec`:
```bash
hf@victor-scale:~/dev/promptsource$ pip show fsspec
Name: fsspec
Version: 2021.5.0
Summary: File-system specification
Home-page: http://github.com/intake/filesystem_spec
Author: None
Author-email: None
License: BSD
Location: /home/hf/dev/promptsource/.venv/lib/python3.7/site-packages
Requires:
Required-by: datasets
```
With the same version of fsspec and `datasets==1.9.0`, I don't see this problem....
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
I can't even run `datasets-cli env` actually.., but here's my env:
- `datasets` version: 1.13.3
- Platform: Ubuntu 18.04
- Python version: 3.7.10
- PyArrow version: 3.0.0
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"Thanks for reporting, @VictorSanh.\r\n\r\nI'm fixing it."
] |
https://api.github.com/repos/huggingface/datasets/issues/1148 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1148/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1148/comments | https://api.github.com/repos/huggingface/datasets/issues/1148/events | https://github.com/huggingface/datasets/pull/1148 | 757,503,918 | MDExOlB1bGxSZXF1ZXN0NTMyODY5NzM0 | 1,148 | adding polemo2 dataset | [] | closed | false | null | 0 | 2020-12-05T01:25:29Z | 2020-12-05T16:51:39Z | 2020-12-05T16:51:39Z | null | {
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https://api.github.com/repos/huggingface/datasets/issues/5078 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5078/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5078/comments | https://api.github.com/repos/huggingface/datasets/issues/5078/events | https://github.com/huggingface/datasets/pull/5078 | 1,398,335,148 | PR_kwDODunzps5APjkH | 5,078 | Fix header level in Audio docs | [] | closed | false | null | 1 | 2022-10-05T20:22:44Z | 2022-10-06T08:12:23Z | 2022-10-06T08:09:41Z | null | Fixes header level so `Dataset features` is the doc title instead of `The Audio type`:
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"_The documentation is not available anymore as the PR was closed or merged._"
] |
https://api.github.com/repos/huggingface/datasets/issues/1650 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1650/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1650/comments | https://api.github.com/repos/huggingface/datasets/issues/1650/events | https://github.com/huggingface/datasets/pull/1650 | 775,545,912 | MDExOlB1bGxSZXF1ZXN0NTQ2MjA0MzYy | 1,650 | Update README.md | [] | closed | false | null | 0 | 2020-12-28T19:09:05Z | 2020-12-29T10:43:14Z | 2020-12-29T10:43:14Z | null | added dataset summary | {
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https://api.github.com/repos/huggingface/datasets/issues/711 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/711/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/711/comments | https://api.github.com/repos/huggingface/datasets/issues/711/events | https://github.com/huggingface/datasets/pull/711 | 714,236,408 | MDExOlB1bGxSZXF1ZXN0NDk3Mzc3NzU3 | 711 | New Update bertscore.py | [] | closed | false | null | 0 | 2020-10-04T05:13:09Z | 2020-10-05T16:26:51Z | 2020-10-05T16:26:51Z | null | {
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https://api.github.com/repos/huggingface/datasets/issues/4367 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4367/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4367/comments | https://api.github.com/repos/huggingface/datasets/issues/4367/events | https://github.com/huggingface/datasets/pull/4367 | 1,240,011,602 | PR_kwDODunzps44B340 | 4,367 | Remove config names as yaml keys | [] | closed | false | null | 3 | 2022-05-18T13:59:24Z | 2022-05-20T09:35:26Z | 2022-05-20T09:27:19Z | null | Many datasets have dots in their config names. However it causes issues with the YAML tags of the dataset cards since we can't have dots in YAML keys.
I fix this, I removed the tags separations per config name completely, and have a single flat YAML for all configurations. Dataset search doesn't use this info anyway. I removed all the config names used as YAML keys, and I moved them in under a new `config:` key.
This is related to https://github.com/huggingface/datasets/pull/2362 (internal https://github.com/huggingface/moon-landing/issues/946).
Also removing the dots in the YAML keys would allow us to do as in https://github.com/huggingface/datasets/pull/4302 which removes a hack that replaces all the dots by underscores in the YAML tags.
I also added a test in the CI that checks that all the YAML tags to make sure that:
- they can be parsed using a YAML parser
- they contain only valid YAML tags like languages or task_ids | {
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"I included the change from https://github.com/huggingface/datasets/pull/4302 directly in this PR, this way the datasets will be updated right away in the CI (the CI is only triggered when a dataset card is changed)",
"_The documentation is not available anymore as the PR was closed or merged._",
"Alright it's ... |
https://api.github.com/repos/huggingface/datasets/issues/3242 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3242/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3242/comments | https://api.github.com/repos/huggingface/datasets/issues/3242/events | https://github.com/huggingface/datasets/issues/3242 | 1,048,527,232 | I_kwDODunzps4-f0GA | 3,242 | Adding ANERcorp-CAMeLLab dataset | [
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"Adding ANERcorp dataset\r\n\r\n## Adding a Dataset\r\n- **Name:** *ANERcorp-CAMeLLab*\r\n- **Description:** *Since its creation in 2008, the ANERcorp dataset (Benajiba & Rosso, 2008) has been a standard reference used by Arabic named entity recognition researchers around the world. However, over time, this dataset... |
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See https://github.com/huggingface/datasets/actions/runs/5401870932/jobs/9812337078 for the errors | {
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"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_a... |
https://api.github.com/repos/huggingface/datasets/issues/5777 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5777/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5777/comments | https://api.github.com/repos/huggingface/datasets/issues/5777/events | https://github.com/huggingface/datasets/issues/5777 | 1,677,655,969 | I_kwDODunzps5j_v-h | 5,777 | datasets.load_dataset("code_search_net", "python") : NotADirectoryError: [Errno 20] Not a directory | [] | closed | false | null | 6 | 2023-04-21T02:08:07Z | 2023-06-05T05:49:52Z | 2023-05-11T11:51:56Z | null | ### Describe the bug
While checking out the [tokenizer tutorial](https://huggingface.co/course/chapter6/2?fw=pt), i noticed getting an error while initially downloading the python dataset used in the examples.
The [collab with the error is here](https://colab.research.google.com/github/huggingface/notebooks/blob/master/course/en/chapter6/section2.ipynb#scrollTo=hGb69Yo3eV8S)
```
from datasets import load_dataset
import os
os.environ["HF_DATASETS_CACHE"] = "/workspace"
# This can take a few minutes to load, so grab a coffee or tea while you wait!
raw_datasets = load_dataset("code_search_net", "python")
```
yeilds:
```
ile /opt/conda/lib/python3.10/site-packages/datasets/download/streaming_download_manager.py:524, in xlistdir(path, use_auth_token)
522 main_hop, *rest_hops = _as_str(path).split("::")
523 if is_local_path(main_hop):
--> 524 return os.listdir(path)
525 else:
526 # globbing inside a zip in a private repo requires authentication
527 if not rest_hops and (main_hop.startswith("http://") or main_hop.startswith("https://")):
NotADirectoryError: [Errno 20] Not a directory: '/workspace/downloads/25ceeb4c25ab737d688bd56ea92bfbb1f199fe572470456cf2d675479f342ac7/python/final/jsonl/train'
```
I was able to reproduce this erro both in the collab and on my own pytorch/pytorch container pulled from the dockerhub official pytorch image, so i think it may be a server side thing.
### Steps to reproduce the bug
Steps to reproduce the issue:
1. run `raw_datasets = load_dataset("code_search_net", "python")`
### Expected behavior
expect the code to not exception during dataset pull.
### Environment info
i tried both the default HF_DATASETS_CACHE on Collab, and on my local container. i then pointed to the HF_DATASETS_CACHE to a large capacity local storage and the problem was consisten across all 3 scenarios. | {
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"Note:\r\nI listed the datasets and grepped around to find what appears to be an alternative source for this:\r\n\r\nraw_datasets = load_dataset(\"espejelomar/code_search_net_python_10000_examples\", \"python\")",
"Thanks for reporting, @jason-brian-anderson.\r\n\r\nYes, this is a known issue: the [CodeSearchNet]... |
https://api.github.com/repos/huggingface/datasets/issues/3670 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3670/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3670/comments | https://api.github.com/repos/huggingface/datasets/issues/3670/events | https://github.com/huggingface/datasets/pull/3670 | 1,122,439,827 | PR_kwDODunzps4x_kBx | 3,670 | feat: 🎸 generate info if dataset_infos.json does not exist | [] | closed | false | null | 3 | 2022-02-02T22:11:56Z | 2022-02-21T15:57:11Z | 2022-02-21T15:57:10Z | null | in get_dataset_infos(). Also: add the `use_auth_token` parameter, and create get_dataset_config_info()
✅ Closes: #3013 | {
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"It's a first attempt at solving https://github.com/huggingface/datasets/issues/3013.",
"I only kept these ones:\r\n```\r\n path: str,\r\n data_files: Optional[Union[Dict, List, str]] = None,\r\n download_config: Optional[DownloadConfig] = None,\r\n download_mode: Optional[GenerateMode] = None,\r\n ... |
https://api.github.com/repos/huggingface/datasets/issues/934 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/934/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/934/comments | https://api.github.com/repos/huggingface/datasets/issues/934/events | https://github.com/huggingface/datasets/pull/934 | 753,860,095 | MDExOlB1bGxSZXF1ZXN0NTI5ODU2ODY4 | 934 | small updates to the "add new dataset" guide | [] | closed | false | null | 1 | 2020-11-30T22:49:10Z | 2020-12-01T04:56:22Z | 2020-11-30T23:14:00Z | null | small updates (corrections/typos) to the "add new dataset" guide | {
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"cc @yjernite @lhoestq @thomwolf "
] |
https://api.github.com/repos/huggingface/datasets/issues/3592 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3592/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3592/comments | https://api.github.com/repos/huggingface/datasets/issues/3592/events | https://github.com/huggingface/datasets/pull/3592 | 1,107,026,723 | PR_kwDODunzps4xNYIW | 3,592 | Add QuickDraw dataset | [] | closed | false | null | 1 | 2022-01-18T15:13:39Z | 2022-06-09T10:04:54Z | 2022-06-09T09:56:13Z | null | Add the QuickDraw dataset.
TODOs:
* [x] add dummy data
* [x] add dataset card
* [x] generate `dataset_info.json` | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] |
https://api.github.com/repos/huggingface/datasets/issues/4995 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4995/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4995/comments | https://api.github.com/repos/huggingface/datasets/issues/4995/events | https://github.com/huggingface/datasets/issues/4995 | 1,379,108,482 | I_kwDODunzps5SM4aC | 4,995 | Get a specific Exception when the dataset has no data | [
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"default": fals... | closed | false | null | 0 | 2022-09-20T09:31:59Z | 2022-09-21T12:21:25Z | 2022-09-21T12:21:25Z | null | In the dataset viewer on the Hub (https://huggingface.co/datasets/glue/viewer), we would like (https://github.com/huggingface/moon-landing/issues/3882) to show a specific message when the repository lacks any data files.
In that case, instead of showing a complex traceback, we want to show a call to action to help the user upload data.
To do that, it would be very helpful to know for sure that the repository is missing any (supported) data files.
It could be done by raising a custom exception, for example, `NoDataError`. | {
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https://api.github.com/repos/huggingface/datasets/issues/6087 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6087/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6087/comments | https://api.github.com/repos/huggingface/datasets/issues/6087/events | https://github.com/huggingface/datasets/issues/6087 | 1,825,133,741 | I_kwDODunzps5syVSt | 6,087 | fsspec dependency is set too low | [] | open | false | null | 0 | 2023-07-27T20:08:22Z | 2023-07-27T20:08:22Z | null | null | ### Describe the bug
fsspec.callbacks.TqdmCallback (used in https://github.com/huggingface/datasets/blob/73bed12ecda17d1573fd3bf73ed5db24d3622f86/src/datasets/utils/file_utils.py#L338) was first released in fsspec [2022.3.0](https://github.com/fsspec/filesystem_spec/releases/tag/2022.3.0, commit where it was added: https://github.com/fsspec/filesystem_spec/commit/9577c8a482eb0a69092913b81580942a68d66a76#diff-906155c7e926a9ff58b9f23369bb513b09b445f5b0f41fa2a84015d0b471c68cR180), however the dependency is set to 2021.11.1 https://github.com/huggingface/datasets/blob/main/setup.py#L129
### Steps to reproduce the bug
1. Install fsspec==2021.11.1
2. Install latest datasets==2.14.1
3. Import datasets, import fails due to lack of `fsspec.callbacks.TqdmCallback`
### Expected behavior
No import issue
### Environment info
N/A | {
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"Thanks for reporting! A PR with a fix has just been merged."
] |
https://api.github.com/repos/huggingface/datasets/issues/3167 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3167/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3167/comments | https://api.github.com/repos/huggingface/datasets/issues/3167/events | https://github.com/huggingface/datasets/issues/3167 | 1,036,488,992 | I_kwDODunzps49x5Eg | 3,167 | bookcorpusopen no longer works | [
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] | closed | false | null | 3 | 2021-10-26T16:06:15Z | 2021-11-17T15:53:46Z | 2021-11-17T15:53:46Z | null | ## Describe the bug
When using the latest version of datasets (1.14.0), I cannot use the `bookcorpusopen` dataset. The process blocks always around `9924 examples [00:06, 1439.61 examples/s]` when preparing the dataset. I also noticed that after half an hour the process is automatically killed because of the RAM usage (the machine has 1TB of RAM...).
This did not happen with 1.4.1.
I tried also `rm -rf ~/.cache/huggingface` but did not help.
Changing python version between 3.7, 3.8 and 3.9 did not help too.
## Steps to reproduce the bug
```python
import datasets
d = datasets.load_dataset('bookcorpusopen')
```
## Expected results
A clear and concise description of the expected results.
## Actual results
Specify the actual results or traceback.
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.14.0
- Platform: Linux-5.4.0-1054-aws-x86_64-with-glibc2.27
- Python version: 3.9.7
- PyArrow version: 4.0.1
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"Hi ! Thanks for reporting :) I think #3280 should fix this",
"I tried with the latest changes from #3280 on google colab and it worked fine :)\r\nWe'll do a new release soon, in the meantime you can use the updated version with:\r\n```python\r\nload_dataset(\"bookcorpusopen\", revision=\"master\")\r\n```",
"Fi... |
https://api.github.com/repos/huggingface/datasets/issues/5304 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5304/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5304/comments | https://api.github.com/repos/huggingface/datasets/issues/5304/events | https://github.com/huggingface/datasets/issues/5304 | 1,465,110,367 | I_kwDODunzps5XU89f | 5,304 | timit_asr doesn't load the test split. | [] | closed | false | null | 1 | 2022-11-26T10:18:22Z | 2023-02-10T16:33:21Z | 2023-02-10T16:33:21Z | null | ### Describe the bug
When I use the function ```timit = load_dataset('timit_asr', data_dir=data_dir)```, it only loads train split, not test split.
I tried to change the directory and filename to lower case to upper case for the test split, but it does not work at all.
```python
DatasetDict({
train: Dataset({
features: ['file', 'audio', 'text', 'phonetic_detail', 'word_detail', 'dialect_region', 'sentence_type', 'speaker_id', 'id'],
num_rows: 4620
})
test: Dataset({
features: ['file', 'audio', 'text', 'phonetic_detail', 'word_detail', 'dialect_region', 'sentence_type', 'speaker_id', 'id'],
num_rows: 0
})
})
```
The directory structure of both splits are same. (DIALECT_REGION / SPEAKER_CODE / DATA_FILES)
### Steps to reproduce the bug
1. just use ```timit = load_dataset('timit_asr', data_dir=data_dir)```
### Expected behavior
```python
DatasetDict({
train: Dataset({
features: ['file', 'audio', 'text', 'phonetic_detail', 'word_detail', 'dialect_region', 'sentence_type', 'speaker_id', 'id'],
num_rows: 4620
})
test: Dataset({
features: ['file', 'audio', 'text', 'phonetic_detail', 'word_detail', 'dialect_region', 'sentence_type', 'speaker_id', 'id'],
num_rows: 1680
})
})
```
### Environment info
- ubuntu 20.04
- python 3.9.13
- datasets 2.7.1 | {
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"The [timit_asr.py](https://huggingface.co/datasets/timit_asr/blob/main/timit_asr.py) script iterates over the WAV files per split directory using this:\r\n```python\r\nwav_paths = sorted(Path(data_dir).glob(f\"**/{split}/**/*.wav\"))\r\nwav_paths = wav_paths if wav_paths else sorted(Path(data_dir).glob(f\"**/{spli... |
https://api.github.com/repos/huggingface/datasets/issues/262 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/262/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/262/comments | https://api.github.com/repos/huggingface/datasets/issues/262/events | https://github.com/huggingface/datasets/pull/262 | 636,702,849 | MDExOlB1bGxSZXF1ZXN0NDMyODI3Mzcz | 262 | Add new dataset ANLI Round 1 | [] | closed | false | null | 1 | 2020-06-11T04:14:57Z | 2020-06-12T22:03:03Z | 2020-06-12T22:03:03Z | null | Adding new dataset [ANLI](https://github.com/facebookresearch/anli/).
I'm not familiar with how to add new dataset. Let me know if there is any issue. I only include round 1 data here. There will be round 2, round 3 and more in the future with potentially different format. I think it will be better to separate them. | {
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"Hello ! Thanks for adding this one :)\r\n\r\nThis looks great, you just have to do the last steps to make the CI pass.\r\nI can see that two things are missing:\r\n1. the dummy data that is used to test that the script is working as expected\r\n2. the json file with all the infos about the dataset\r\n\r\nYou can s... |
https://api.github.com/repos/huggingface/datasets/issues/896 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/896/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/896/comments | https://api.github.com/repos/huggingface/datasets/issues/896/events | https://github.com/huggingface/datasets/pull/896 | 751,834,265 | MDExOlB1bGxSZXF1ZXN0NTI4MjcyMjc0 | 896 | Add template and documentation for dataset card | [] | closed | false | null | 0 | 2020-11-26T21:30:25Z | 2020-11-28T01:10:15Z | 2020-11-28T01:10:15Z | null | This PR adds a template for dataset cards, as well as a guide to filling out the template and a completed example for the ELI5 dataset, building on the work of @mcmillanmajora
New pull requests adding datasets should now have a README.md file which serves both to hold the tags we will have to index the datasets and as a data statement.
The template is designed to be pretty extensive. The idea is that the person who uploads the dataset should put in all the basic information (at least the Dataset Description section) and whatever else they feel comfortable adding and leave the `[More Information Needed]` annotation everywhere else as a placeholder.
We will then work with @mcmillanmajora to involve the data authors more directly in filling out the remaining information.
Direct links to:
- [Documentation](https://github.com/yjernite/datasets/blob/add_dataset_card_doc/templates/README_guide.md)
- [Empty template](https://github.com/yjernite/datasets/blob/add_dataset_card_doc/templates/README.md)
- [ELI5 example](https://github.com/yjernite/datasets/blob/add_dataset_card_doc/datasets/eli5/README.md) | {
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https://api.github.com/repos/huggingface/datasets/issues/2960 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2960/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2960/comments | https://api.github.com/repos/huggingface/datasets/issues/2960/events | https://github.com/huggingface/datasets/pull/2960 | 1,006,222,850 | PR_kwDODunzps4sOl0Y | 2,960 | Support pandas 1.3 new `read_csv` parameters | [] | closed | false | null | 0 | 2021-09-24T08:37:24Z | 2021-09-24T11:22:31Z | 2021-09-24T11:22:30Z | null | Support two new arguments introduced in pandas v1.3.0:
- `encoding_errors`
- `on_bad_lines`
`read_csv` reference: https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.read_csv.html | {
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https://api.github.com/repos/huggingface/datasets/issues/2510 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2510/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2510/comments | https://api.github.com/repos/huggingface/datasets/issues/2510/events | https://github.com/huggingface/datasets/pull/2510 | 923,735,485 | MDExOlB1bGxSZXF1ZXN0NjcyNDY3MzY3 | 2,510 | Add align_labels_with_mapping to DatasetDict | [] | closed | false | null | 0 | 2021-06-17T10:03:35Z | 2021-06-17T10:45:25Z | 2021-06-17T10:45:24Z | null | https://github.com/huggingface/datasets/pull/2457 added the `Dataset.align_labels_with_mapping` method.
In this PR I also added `DatasetDict.align_labels_with_mapping` | {
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https://api.github.com/repos/huggingface/datasets/issues/2766 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2766/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2766/comments | https://api.github.com/repos/huggingface/datasets/issues/2766/events | https://github.com/huggingface/datasets/pull/2766 | 962,994,198 | MDExOlB1bGxSZXF1ZXN0NzA1NzAyNjM5 | 2,766 | fix typo (ShuffingConfig -> ShufflingConfig) | [] | closed | false | null | 0 | 2021-08-06T19:31:40Z | 2021-08-10T14:17:03Z | 2021-08-10T14:17:02Z | null | pretty straightforward, it should be Shuffling instead of Shuffing | {
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https://api.github.com/repos/huggingface/datasets/issues/4217 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4217/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4217/comments | https://api.github.com/repos/huggingface/datasets/issues/4217/events | https://github.com/huggingface/datasets/issues/4217 | 1,214,688,141 | I_kwDODunzps5IZquN | 4,217 | Big_Patent dataset broken | [
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] | closed | false | null | 3 | 2022-04-25T15:31:45Z | 2022-05-26T06:29:43Z | 2022-05-02T18:21:15Z | null | ## Dataset viewer issue for '*big_patent*'
**Link:** *[link to the dataset viewer page](https://huggingface.co/datasets/big_patent/viewer/all/train)*
*Unable to view because it says FileNotFound, also cannot download it through the python API*
Am I the one who added this dataset ? No
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} | https://api.github.com/repos/huggingface/datasets/issues/4217/timeline | null | completed | null | null | false | [
"Thanks for reporting. The issue seems not to be directly related to the dataset viewer or the `datasets` library, but instead to it being hosted on Google Drive.\r\n\r\nSee related issues: https://github.com/huggingface/datasets/issues?q=is%3Aissue+is%3Aopen+drive.google.com\r\n\r\nTo quote [@lhoestq](https://gith... |
https://api.github.com/repos/huggingface/datasets/issues/4822 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4822/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4822/comments | https://api.github.com/repos/huggingface/datasets/issues/4822/events | https://github.com/huggingface/datasets/issues/4822 | 1,335,675,352 | I_kwDODunzps5PnMnY | 4,822 | Moving dataset between namespaces breaks dataset viewer | [
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] | open | false | null | 1 | 2022-08-11T09:05:30Z | 2022-09-16T20:03:09Z | null | null | ## Describe the bug
I moved a dataset from my own namespace to an org and that broke the dataset viewer. To fix it I had to manually edit the `dataset_info.json` file and change the first key in the json from `username--datasetname` to `orgname--datasetname`
## Steps to reproduce the bug
What I did was:
1- Upload a dataset to my own namespace using `push_to_hub`
2- Move the dataset from my namespace to an org using the web interface.
## Expected results
For the file to be changed accordingly.
## Actual results
Broken dataset viewer.
## Environment info
- `datasets` version: 2.3.3.dev0
- Platform: Linux-4.15.0-189-generic-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.7.5
- PyArrow version: 7.0.0
- Pandas version: 1.3.5
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"Let's keep open for now. We should try to reproduce"
] |
https://api.github.com/repos/huggingface/datasets/issues/446 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/446/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/446/comments | https://api.github.com/repos/huggingface/datasets/issues/446/events | https://github.com/huggingface/datasets/pull/446 | 666,837,351 | MDExOlB1bGxSZXF1ZXN0NDU3NjEyNTg5 | 446 | [BugFix] fix wrong import of DEFAULT_TOKENIZER | [] | closed | false | null | 0 | 2020-07-28T07:32:47Z | 2020-07-28T07:34:46Z | 2020-07-28T07:33:59Z | null | Fixed the path to `DEFAULT_TOKENIZER`
#445 | {
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https://api.github.com/repos/huggingface/datasets/issues/3952 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3952/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3952/comments | https://api.github.com/repos/huggingface/datasets/issues/3952/events | https://github.com/huggingface/datasets/issues/3952 | 1,171,895,531 | I_kwDODunzps5F2bTr | 3,952 | Checksum error for glue sst2, stsb, rte etc datasets | [
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] | closed | false | null | 1 | 2022-03-17T03:45:47Z | 2022-03-17T07:10:15Z | 2022-03-17T07:10:14Z | null | ## Describe the bug
Checksum error for glue sst2, stsb, rte etc datasets
## Steps to reproduce the bug
```python
>>> nlp.load_dataset('glue', 'sst2')
Downloading and preparing dataset glue/sst2 (download: 7.09 MiB, generated: 4.81 MiB, post-processed: Unknown sizetotal: 11.90 MiB) to
Downloading: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 73.0/73.0 [00:00<00:00, 18.2kB/s]
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/Library/Python/3.8/lib/python/site-packages/nlp/load.py", line 548, in load_dataset
builder_instance.download_and_prepare(
File "/Library/Python/3.8/lib/python/site-packages/nlp/builder.py", line 462, in download_and_prepare
self._download_and_prepare(
File "/Library/Python/3.8/lib/python/site-packages/nlp/builder.py", line 521, in _download_and_prepare
verify_checksums(
File "/Library/Python/3.8/lib/python/site-packages/nlp/utils/info_utils.py", line 38, in verify_checksums
raise NonMatchingChecksumError(error_msg + str(bad_urls))
nlp.utils.info_utils.NonMatchingChecksumError: Checksums didn't match for dataset source files:
['https://firebasestorage.googleapis.com/v0/b/mtl-sentence-representations.appspot.com/o/data%2FSST-2.zip?alt=media&token=aabc5f6b-e466-44a2-b9b4-cf6337f84ac8']
```
## Expected results
dataset load should succeed without checksum error.
## Actual results
```
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/Library/Python/3.8/lib/python/site-packages/nlp/load.py", line 548, in load_dataset
builder_instance.download_and_prepare(
File "/Library/Python/3.8/lib/python/site-packages/nlp/builder.py", line 462, in download_and_prepare
self._download_and_prepare(
File "/Library/Python/3.8/lib/python/site-packages/nlp/builder.py", line 521, in _download_and_prepare
verify_checksums(
File "/Library/Python/3.8/lib/python/site-packages/nlp/utils/info_utils.py", line 38, in verify_checksums
raise NonMatchingChecksumError(error_msg + str(bad_urls))
nlp.utils.info_utils.NonMatchingChecksumError: Checksums didn't match for dataset source files:
['https://firebasestorage.googleapis.com/v0/b/mtl-sentence-representations.appspot.com/o/data%2FSST-2.zip?alt=media&token=aabc5f6b-e466-44a2-b9b4-cf6337f84ac8']
```
## Environment info
- `datasets` version: '1.18.3'
- Platform: Mac OS
- Python version: Python 3.8.9
- PyArrow version: '7.0.0'
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"Hi, @ravindra-ut.\r\n\r\nI'm sorry but I can't reproduce your problem:\r\n```python\r\nIn [1]: from datasets import load_dataset\r\n\r\nIn [2]: ds = load_dataset(\"glue\", \"sst2\")\r\nDownloading builder script: 28.8kB [00:00, 11.6MB/s] ... |
https://api.github.com/repos/huggingface/datasets/issues/2845 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2845/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2845/comments | https://api.github.com/repos/huggingface/datasets/issues/2845/events | https://github.com/huggingface/datasets/issues/2845 | 981,487,861 | MDU6SXNzdWU5ODE0ODc4NjE= | 2,845 | [feature request] adding easy to remember `datasets.cache_dataset()` + `datasets.is_dataset_cached()` | [
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] | open | false | null | 0 | 2021-08-27T18:21:51Z | 2021-08-27T18:24:05Z | null | null | Often, there is a need to prepare a dataset but not use it immediately, e.g. think tests suite setup, so it'd be really useful to be able to do:
```
if not datasets.is_dataset_cached(ds): datasets.cache_dataset(ds)
```
This can already be done with:
```
builder = load_dataset_builder(ds)
if not os.path.idsir(builder.cache_dir):
builder.download_and_prepare()
```
but the current way is a way less intuitive and much harder to remember than the proposed API, IMHO.
One more way is to do:
```
_ = load_dataset(ds)
```
but it wastes resources loading the dataset when it's not needed.
this has been discussed at https://huggingface.slack.com/archives/C01229B19EX/p1630021912025800
Thank you!
@lhoestq
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https://api.github.com/repos/huggingface/datasets/issues/4498 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4498/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4498/comments | https://api.github.com/repos/huggingface/datasets/issues/4498/events | https://github.com/huggingface/datasets/issues/4498 | 1,272,100,549 | I_kwDODunzps5L0rbF | 4,498 | WER and CER > 1 | [
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] | closed | false | null | 1 | 2022-06-15T11:35:12Z | 2022-06-15T16:38:05Z | 2022-06-15T16:38:05Z | null | ## Describe the bug
It seems that in some cases in which the `prediction` is longer than the `reference` we may have word/character error rate higher than 1 which is a bit odd.
If it's a real bug I think I can solve it with a PR changing [this](https://github.com/huggingface/datasets/blob/master/metrics/wer/wer.py#L105) line to
```python
return min(incorrect / total, 1.0)
```
## Steps to reproduce the bug
```python
from datasets import load_metric
wer = load_metric("wer")
wer_value = wer.compute(predictions=["Hi World vka"], references=["Hello"])
print(wer_value)
```
## Expected results
```
1.0
```
## Actual results
```
3.0
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 2.3.0
- Platform: Linux-5.4.188+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.7.13
- PyArrow version: 6.0.1
- Pandas version: 1.3.5 | {
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"WER can have values bigger than 1.0, this is expected when there are too many insertions\r\n\r\nFrom [wikipedia](https://en.wikipedia.org/wiki/Word_error_rate):\r\n> Note that since N is the number of words in the reference, the word error rate can be larger than 1.0"
] |
https://api.github.com/repos/huggingface/datasets/issues/5608 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5608/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5608/comments | https://api.github.com/repos/huggingface/datasets/issues/5608/events | https://github.com/huggingface/datasets/issues/5608 | 1,609,996,563 | I_kwDODunzps5f9pkT | 5,608 | audiofolder only creates dataset of 13 rows (files) when the data folder it's reading from has 20,000 mp3 files. | [] | closed | false | null | 2 | 2023-03-05T00:14:45Z | 2023-03-12T00:02:57Z | 2023-03-12T00:02:57Z | null | ### Describe the bug
x = load_dataset("audiofolder", data_dir="x")
When running this, x is a dataset of 13 rows (files) when it should be 20,000 rows (files) as the data_dir "x" has 20,000 mp3 files. Does anyone know what could possibly cause this (naming convention of mp3 files, etc.)
### Steps to reproduce the bug
x = load_dataset("audiofolder", data_dir="x")
### Expected behavior
x = load_dataset("audiofolder", data_dir="x") should create a dataset of 20,000 rows (files).
### Environment info
- `datasets` version: 2.9.0
- Platform: Linux-3.10.0-1160.80.1.el7.x86_64-x86_64-with-glibc2.17
- Python version: 3.9.16
- PyArrow version: 11.0.0
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"Hi!\r\n\r\n> naming convention of mp3 files\r\n\r\nYes, this could be the problem. MP3 files should end with `.mp3`/`.MP3` to be recognized as audio files.\r\n\r\nIf the file names are not the culprit, can you paste the audio folder's directory structure to help us reproduce the error (e.g., by running the `tree ... |
https://api.github.com/repos/huggingface/datasets/issues/2603 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2603/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2603/comments | https://api.github.com/repos/huggingface/datasets/issues/2603/events | https://github.com/huggingface/datasets/pull/2603 | 938,588,149 | MDExOlB1bGxSZXF1ZXN0Njg0OTQ0ODcz | 2,603 | Fix DuplicatedKeysError in omp | [] | closed | false | {
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} | 0 | 2021-07-07T07:38:32Z | 2021-07-12T14:10:41Z | 2021-07-07T12:56:35Z | null | Close #2598. | {
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https://api.github.com/repos/huggingface/datasets/issues/6062 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6062/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6062/comments | https://api.github.com/repos/huggingface/datasets/issues/6062/events | https://github.com/huggingface/datasets/pull/6062 | 1,818,341,584 | PR_kwDODunzps5WOj62 | 6,062 | Improve `Dataset.from_list` docstring | [] | closed | false | null | 4 | 2023-07-24T12:36:38Z | 2023-07-24T14:43:48Z | 2023-07-24T14:34:43Z | null | null | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | rea... |
https://api.github.com/repos/huggingface/datasets/issues/3910 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3910/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3910/comments | https://api.github.com/repos/huggingface/datasets/issues/3910/events | https://github.com/huggingface/datasets/pull/3910 | 1,168,579,694 | PR_kwDODunzps40aAiX | 3,910 | Fix text loader to split only on universal newlines | [] | closed | false | null | 6 | 2022-03-14T15:54:58Z | 2022-03-15T16:16:11Z | 2022-03-15T16:16:09Z | null | Currently, `text` loader breaks on a superset of universal newlines, which also contains Unicode line boundaries. See: https://docs.python.org/3/library/stdtypes.html#str.splitlines
However, the expected behavior is to get the lines splitted only on universal newlines: "\n", "\r\n" and "\r".
See: oscar-corpus/corpus#18
Fix #3729. | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3910). All of your documentation changes will be reflected on that endpoint.",
"Looks like the test needs to be updated for windows ^^'",
"I don't think this is the same issue as in https://github.com/oscar-corpus/corpus/issu... |
https://api.github.com/repos/huggingface/datasets/issues/2204 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2204/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2204/comments | https://api.github.com/repos/huggingface/datasets/issues/2204/events | https://github.com/huggingface/datasets/pull/2204 | 855,144,431 | MDExOlB1bGxSZXF1ZXN0NjEyOTU1MzM2 | 2,204 | Add configurable options to `seqeval` metric | [] | closed | false | null | 0 | 2021-04-10T19:58:19Z | 2021-04-15T13:49:46Z | 2021-04-15T13:49:46Z | null | Fixes #2148
Adds options to use strict mode, different schemes of evaluation, sample weight and adjust zero_division behavior, if encountered.
`seqeval` provides schemes as objects, hence dynamic import from string, to avoid making the user do the import (thanks to @albertvillanova for the `importlib` idea). | {
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https://api.github.com/repos/huggingface/datasets/issues/4287 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4287/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4287/comments | https://api.github.com/repos/huggingface/datasets/issues/4287/events | https://github.com/huggingface/datasets/issues/4287 | 1,226,806,652 | I_kwDODunzps5JH5V8 | 4,287 | "NameError: name 'faiss' is not defined" on `.add_faiss_index` when `device` is not None | [
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] | closed | false | null | 3 | 2022-05-05T15:09:45Z | 2022-05-10T13:53:19Z | 2022-05-10T13:53:19Z | null | ## Describe the bug
When using `datasets` to calculate the FAISS indices of a dataset, the exception `NameError: name 'faiss' is not defined` is triggered when trying to calculate those on a device (GPU), so `.add_faiss_index(..., device=0)` fails with that exception.
All that assuming that `datasets` is properly installed and `faiss-gpu` too, as well as all the CUDA drivers required.
## Steps to reproduce the bug
```python
# Sample code to reproduce the bug
from transformers import DPRContextEncoder, DPRContextEncoderTokenizer
import torch
torch.set_grad_enabled(False)
ctx_encoder = DPRContextEncoder.from_pretrained("facebook/dpr-ctx_encoder-single-nq-base")
ctx_tokenizer = DPRContextEncoderTokenizer.from_pretrained("facebook/dpr-ctx_encoder-single-nq-base")
from datasets import load_dataset
ds = load_dataset('crime_and_punish', split='train[:100]')
ds_with_embeddings = ds.map(lambda example: {'embeddings': ctx_encoder(**ctx_tokenizer(example["line"], return_tensors="pt"))[0][0].numpy()})
ds_with_embeddings.add_faiss_index(column='embeddings', device=0) # default `device=None`
```
## Expected results
A new column named `embeddings` in the dataset that we're adding the index to.
## Actual results
An exception is triggered with the following message `NameError: name 'faiss' is not defined`.
## Environment info
- `datasets` version: 2.1.0
- Platform: Linux-5.13.0-1022-azure-x86_64-with-glibc2.31
- Python version: 3.9.12
- PyArrow version: 7.0.0
- Pandas version: 1.4.2
| {
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"So I managed to solve this by adding a missing `import faiss` in the `@staticmethod` defined in https://github.com/huggingface/datasets/blob/f51b6994db27ea69261ef919fb7775928f9ec10b/src/datasets/search.py#L305, triggered from https://github.com/huggingface/datasets/blob/f51b6994db27ea69261ef919fb7775928f9ec10b/src... |
https://api.github.com/repos/huggingface/datasets/issues/3803 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3803/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3803/comments | https://api.github.com/repos/huggingface/datasets/issues/3803/events | https://github.com/huggingface/datasets/pull/3803 | 1,157,271,679 | PR_kwDODunzps4z1T48 | 3,803 | Remove deprecated methods/params (preparation for v2.0) | [] | closed | false | null | 0 | 2022-03-02T14:29:12Z | 2022-03-02T14:53:21Z | 2022-03-02T14:53:21Z | null | This PR removes the following deprecated methos/params:
* `Dataset.cast_`/`DatasetDict.cast_`
* `Dataset.dictionary_encode_column_`/`DatasetDict.dictionary_encode_column_`
* `Dataset.remove_columns_`/`DatasetDict.remove_columns_`
* `Dataset.rename_columns_`/`DatasetDict.rename_columns_`
* `prepare_module`
* param `script_version` in `load_dataset`/`load_metric`
* param `version` in `hf_github_url`
| {
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https://api.github.com/repos/huggingface/datasets/issues/6070 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6070/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6070/comments | https://api.github.com/repos/huggingface/datasets/issues/6070/events | https://github.com/huggingface/datasets/pull/6070 | 1,820,836,330 | PR_kwDODunzps5WXDLc | 6,070 | Fix Quickstart notebook link | [] | closed | false | null | 3 | 2023-07-25T17:48:37Z | 2023-07-25T18:19:01Z | 2023-07-25T18:10:16Z | null | Reported in https://github.com/huggingface/datasets/pull/5902#issuecomment-1649885621 (cc @alvarobartt) | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | rea... |
https://api.github.com/repos/huggingface/datasets/issues/2266 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2266/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2266/comments | https://api.github.com/repos/huggingface/datasets/issues/2266/events | https://github.com/huggingface/datasets/pull/2266 | 867,864,353 | MDExOlB1bGxSZXF1ZXN0NjIzNDY1OTI5 | 2,266 | Make tests run faster | [] | closed | false | null | 3 | 2021-04-26T15:55:40Z | 2021-04-29T10:00:13Z | 2021-04-29T10:00:04Z | null | From 7min to 2min to run pytest.
Ideally we should keep the whole CI run time below 10min.
In this PR I removed the remote tests that were never used.
I also replaced nested parametrized tests with unit tests.
This makes me think that we could still add more high level tests to check for a few combinations of parameters (but not all of them since there are too many of them).
Let me know what you think
Finally in another PR we can also separate in two circleci jobs:
- the tests of the code code of the lib
- the tests of the all the dataset/metric scripts. | {
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"LOL, I was also working on something similar 😅. I'm gonna have a look!!!",
"Sorry I didn't know you were also working on it ^^'\r\nAnd yes I 100% agree with you on the points you mentioned. We should definitely improve the coverage. It would be nice to have a clearer separation to know which tests in the suite ... |
https://api.github.com/repos/huggingface/datasets/issues/1782 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1782/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1782/comments | https://api.github.com/repos/huggingface/datasets/issues/1782/events | https://github.com/huggingface/datasets/pull/1782 | 794,167,920 | MDExOlB1bGxSZXF1ZXN0NTYxNzI5OTc3 | 1,782 | Update pyarrow import warning | [] | closed | false | null | 0 | 2021-01-26T11:47:11Z | 2021-01-26T13:50:50Z | 2021-01-26T13:50:49Z | null | Update the minimum version to >=0.17.1 in the pyarrow version check and update the message.
I also moved the check at the top of the __init__.py | {
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https://api.github.com/repos/huggingface/datasets/issues/2354 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2354/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2354/comments | https://api.github.com/repos/huggingface/datasets/issues/2354/events | https://github.com/huggingface/datasets/issues/2354 | 890,439,523 | MDU6SXNzdWU4OTA0Mzk1MjM= | 2,354 | Document DatasetInfo attributes | [
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] | closed | false | null | 0 | 2021-05-12T20:01:29Z | 2021-05-22T09:26:14Z | 2021-05-22T09:26:14Z | null | **Is your feature request related to a problem? Please describe.**
As noted in PR #2255, the attributes of `DatasetInfo` are not documented in the [docs](https://huggingface.co/docs/datasets/package_reference/main_classes.html?highlight=datasetinfo#datasetinfo). It would be nice to do so :)
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https://api.github.com/repos/huggingface/datasets/issues/5548 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5548/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5548/comments | https://api.github.com/repos/huggingface/datasets/issues/5548/events | https://github.com/huggingface/datasets/issues/5548 | 1,590,835,479 | I_kwDODunzps5e0jkX | 5,548 | Apply flake8-comprehensions to codebase | [
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] | closed | false | null | 0 | 2023-02-19T20:05:38Z | 2023-02-23T13:59:41Z | 2023-02-23T13:59:41Z | null | ### Feature request
Apply ruff flake8 comprehension checks to codebase.
### Motivation
This should strictly improve the performance / readability of the codebase by removing unnecessary iteration, function calls, etc. This should generate better Python bytecode which should strictly improve performance.
I already applied this fixes to PyTorch and Sympy with little issue and have opened PRs to diffusers and transformers todo this as well.
### Your contribution
Making a PR. | {
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https://api.github.com/repos/huggingface/datasets/issues/5529 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5529/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5529/comments | https://api.github.com/repos/huggingface/datasets/issues/5529/events | https://github.com/huggingface/datasets/pull/5529 | 1,582,501,233 | PR_kwDODunzps5J26Fq | 5,529 | Fix `datasets.load_from_disk`, `DatasetDict.load_from_disk` and `Dataset.load_from_disk` | [] | closed | false | null | 12 | 2023-02-13T14:54:55Z | 2023-02-23T18:14:32Z | 2023-02-23T18:05:26Z | null | ## What's in this PR?
After playing around a little bit with 🤗`datasets` in Google Cloud Storage (GCS), I found out some things that should be fixed IMO in the code:
* `datasets.load_from_disk` is not checking whether `state.json` is there too when trying to load a `Dataset`, just `dataset_info.json` is checked
* `DatasetDict.load_from_disk` is not checking whether `state.json` is there too when redirecting the user to load it as `datasets.load_from_disk`, just `dataset_info.json` is checked, which is misleading, as it won't be loadable that way either
* `Dataset.load_from_disk` is missing the `extract_path_from_uri` call before checking in the `fs` whether `dataset_info.json` and `dataset_dict.json` exist, which when using `gcsfs` leads to 400 error code (not blocking) due to `gcsfs.retry.HttpError: Invalid bucket name: 'gs:', 400`
* And, finally, the exception messages are a little bit misleading / incomplete IMO so I've tried to include all the relevant information in the messages to avoid issues when interpreting the exceptions | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"Hmm, should this also be updated in `Dataset.load_from_disk` and `DatasetDict.load_from_disk`? https://github.com/huggingface/datasets/pull/5466 As there the paths are joined using `Path(..., ...)` and it won't work on Windows OS acc... |
https://api.github.com/repos/huggingface/datasets/issues/687 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/687/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/687/comments | https://api.github.com/repos/huggingface/datasets/issues/687/events | https://github.com/huggingface/datasets/issues/687 | 711,664,810 | MDU6SXNzdWU3MTE2NjQ4MTA= | 687 | `ArrowInvalid` occurs while running `Dataset.map()` function | [] | closed | false | null | 2 | 2020-09-30T06:16:50Z | 2020-09-30T09:53:03Z | 2020-09-30T09:53:03Z | null | It seems to fail to process the final batch. This [colab](https://colab.research.google.com/drive/1_byLZRHwGP13PHMkJWo62Wp50S_Z2HMD?usp=sharing) can reproduce the error.
Code:
```python
# train_ds = Dataset(features: {
# 'title': Value(dtype='string', id=None),
# 'score': Value(dtype='float64', id=None)
# }, num_rows: 99999)
# suggested in #665
class PicklableTokenizer(BertJapaneseTokenizer):
def __getstate__(self):
state = dict(self.__dict__)
state['do_lower_case'] = self.word_tokenizer.do_lower_case
state['never_split'] = self.word_tokenizer.never_split
del state['word_tokenizer']
return state
def __setstate(self):
do_lower_case = state.pop('do_lower_case')
never_split = state.pop('never_split')
self.__dict__ = state
self.word_tokenizer = MecabTokenizer(
do_lower_case=do_lower_case, never_split=never_split
)
t = PicklableTokenizer.from_pretrained('bert-base-japanese-whole-word-masking')
encoded = train_ds.map(
lambda examples: {'tokens': t.encode(examples['title'], max_length=1000)}, batched=True, batch_size=1000
)
```
Error Message:
```
99% 99/100 [00:22<00:00, 39.07ba/s]
---------------------------------------------------------------------------
ArrowInvalid Traceback (most recent call last)
<timed exec> in <module>
/usr/local/lib/python3.6/site-packages/datasets/arrow_dataset.py in map(self, function, with_indices, input_columns, batched, batch_size, drop_last_batch, remove_columns, keep_in_memory, load_from_cache_file, cache_file_name, writer_batch_size, features, disable_nullable, fn_kwargs, num_proc, suffix_template, new_fingerprint)
1242 fn_kwargs=fn_kwargs,
1243 new_fingerprint=new_fingerprint,
-> 1244 update_data=update_data,
1245 )
1246 else:
/usr/local/lib/python3.6/site-packages/datasets/arrow_dataset.py in wrapper(*args, **kwargs)
151 "output_all_columns": self._output_all_columns,
152 }
--> 153 out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs)
154 if new_format["columns"] is not None:
155 new_format["columns"] = list(set(new_format["columns"]) & set(out.column_names))
/usr/local/lib/python3.6/site-packages/datasets/fingerprint.py in wrapper(*args, **kwargs)
161 # Call actual function
162
--> 163 out = func(self, *args, **kwargs)
164
165 # Update fingerprint of in-place transforms + update in-place history of transforms
/usr/local/lib/python3.6/site-packages/datasets/arrow_dataset.py in _map_single(self, function, with_indices, input_columns, batched, batch_size, drop_last_batch, remove_columns, keep_in_memory, load_from_cache_file, cache_file_name, writer_batch_size, features, disable_nullable, fn_kwargs, new_fingerprint, rank, offset, update_data)
1496 if update_data:
1497 batch = cast_to_python_objects(batch)
-> 1498 writer.write_batch(batch)
1499 if update_data:
1500 writer.finalize() # close_stream=bool(buf_writer is None)) # We only close if we are writing in a file
/usr/local/lib/python3.6/site-packages/datasets/arrow_writer.py in write_batch(self, batch_examples, writer_batch_size)
271 typed_sequence = TypedSequence(batch_examples[col], type=col_type, try_type=col_try_type)
272 typed_sequence_examples[col] = typed_sequence
--> 273 pa_table = pa.Table.from_pydict(typed_sequence_examples)
274 self.write_table(pa_table)
275
/usr/local/lib/python3.6/site-packages/pyarrow/table.pxi in pyarrow.lib.Table.from_pydict()
/usr/local/lib/python3.6/site-packages/pyarrow/table.pxi in pyarrow.lib.Table.from_arrays()
/usr/local/lib/python3.6/site-packages/pyarrow/table.pxi in pyarrow.lib.Table.validate()
/usr/local/lib/python3.6/site-packages/pyarrow/error.pxi in pyarrow.lib.check_status()
ArrowInvalid: Column 4 named tokens expected length 999 but got length 1000
```
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"Hi !\r\n\r\nThis is because `encode` expects one single text as input (str), or one tokenized text (List[str]).\r\nI believe that you actually wanted to use `encode_batch` which expects a batch of texts.\r\nHowever this method is only available for our \"fast\" tokenizers (ex: BertTokenizerFast).\r\nBertJapanese i... |
https://api.github.com/repos/huggingface/datasets/issues/2528 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2528/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2528/comments | https://api.github.com/repos/huggingface/datasets/issues/2528/events | https://github.com/huggingface/datasets/issues/2528 | 926,314,656 | MDU6SXNzdWU5MjYzMTQ2NTY= | 2,528 | Logging cannot be set to NOTSET similar to transformers | [
{
"color": "d73a4a",
"default": true,
"description": "Something isn't working",
"id": 1935892857,
"name": "bug",
"node_id": "MDU6TGFiZWwxOTM1ODkyODU3",
"url": "https://api.github.com/repos/huggingface/datasets/labels/bug"
}
] | closed | false | null | 1 | 2021-06-21T15:04:54Z | 2021-06-24T14:42:47Z | 2021-06-24T14:42:47Z | null | ## Describe the bug
In the transformers library you can set the verbosity level to logging.NOTSET to work around the usage of tqdm and IPywidgets, however in Datasets this is no longer possible. This is because transformers set the verbosity level of tqdm with [this](https://github.com/huggingface/transformers/blob/b53bc55ba9bb10d5ee279eab51a2f0acc5af2a6b/src/transformers/file_utils.py#L1449)
`disable=bool(logging.get_verbosity() == logging.NOTSET)`
and datasets accomplishes this like [so](https://github.com/huggingface/datasets/blob/83554e410e1ab8c6f705cfbb2df7953638ad3ac1/src/datasets/utils/file_utils.py#L493)
`not_verbose = bool(logger.getEffectiveLevel() > WARNING)`
## Steps to reproduce the bug
```python
import datasets
import logging
datasets.logging.get_verbosity = lambda : logging.NOTSET
datasets.load_dataset("patrickvonplaten/librispeech_asr_dummy")
```
## Expected results
The code should download and load the dataset as normal without displaying progress bars
## Actual results
```ImportError Traceback (most recent call last)
<ipython-input-4-aec65c0509c6> in <module>
----> 1 datasets.load_dataset("patrickvonplaten/librispeech_asr_dummy")
~/venv/lib/python3.7/site-packages/datasets/load.py in load_dataset(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, ignore_verifications, keep_in_memory, save_infos, script_version, use_auth_token, task, **config_kwargs)
713 dataset=True,
714 return_resolved_file_path=True,
--> 715 use_auth_token=use_auth_token,
716 )
717 # Set the base path for downloads as the parent of the script location
~/venv/lib/python3.7/site-packages/datasets/load.py in prepare_module(path, script_version, download_config, download_mode, dataset, force_local_path, dynamic_modules_path, return_resolved_file_path, **download_kwargs)
350 file_path = hf_bucket_url(path, filename=name, dataset=False)
351 try:
--> 352 local_path = cached_path(file_path, download_config=download_config)
353 except FileNotFoundError:
354 raise FileNotFoundError(
~/venv/lib/python3.7/site-packages/datasets/utils/file_utils.py in cached_path(url_or_filename, download_config, **download_kwargs)
289 use_etag=download_config.use_etag,
290 max_retries=download_config.max_retries,
--> 291 use_auth_token=download_config.use_auth_token,
292 )
293 elif os.path.exists(url_or_filename):
~/venv/lib/python3.7/site-packages/datasets/utils/file_utils.py in get_from_cache(url, cache_dir, force_download, proxies, etag_timeout, resume_download, user_agent, local_files_only, use_etag, max_retries, use_auth_token)
668 headers=headers,
669 cookies=cookies,
--> 670 max_retries=max_retries,
671 )
672
~/venv/lib/python3.7/site-packages/datasets/utils/file_utils.py in http_get(url, temp_file, proxies, resume_size, headers, cookies, timeout, max_retries)
493 initial=resume_size,
494 desc="Downloading",
--> 495 disable=not_verbose,
496 )
497 for chunk in response.iter_content(chunk_size=1024):
~/venv/lib/python3.7/site-packages/tqdm/notebook.py in __init__(self, *args, **kwargs)
217 total = self.total * unit_scale if self.total else self.total
218 self.container = self.status_printer(
--> 219 self.fp, total, self.desc, self.ncols)
220 self.sp = self.display
221
~/venv/lib/python3.7/site-packages/tqdm/notebook.py in status_printer(_, total, desc, ncols)
95 if IProgress is None: # #187 #451 #558 #872
96 raise ImportError(
---> 97 "IProgress not found. Please update jupyter and ipywidgets."
98 " See https://ipywidgets.readthedocs.io/en/stable"
99 "/user_install.html")
ImportError: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.8.0
- Platform: Linux-5.4.95-42.163.amzn2.x86_64-x86_64-with-debian-10.8
- Python version: 3.7.10
- PyArrow version: 3.0.0
I am running this code on Deepnote and which important to this issue **does not** support IPywidgets
| {
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} | https://api.github.com/repos/huggingface/datasets/issues/2528/timeline | null | completed | null | null | false | [
"Hi @joshzwiebel, thanks for reporting. We are going to align with `transformers`."
] |
https://api.github.com/repos/huggingface/datasets/issues/1479 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1479/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1479/comments | https://api.github.com/repos/huggingface/datasets/issues/1479/events | https://github.com/huggingface/datasets/pull/1479 | 762,320,736 | MDExOlB1bGxSZXF1ZXN0NTM2ODc3NTEz | 1,479 | Add narrativeQA | [] | closed | false | null | 2 | 2020-12-11T12:58:31Z | 2020-12-11T13:33:23Z | 2020-12-11T13:33:23Z | null | Redo of #1368 #309 #499
In redoing the dummy data a few times, I ended up adding a load of files to git. Hopefully this should work. | {
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} | true | [
"@lhoestq this is now only failing some random windows test (it appears to be somewhere in wnut_17)",
"This is a connection error, you can ignore it :) \r\nThe level of activity on the lib is quite overwhelming, it stresses a bit the CI ^^"
] |
https://api.github.com/repos/huggingface/datasets/issues/682 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/682/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/682/comments | https://api.github.com/repos/huggingface/datasets/issues/682/events | https://github.com/huggingface/datasets/pull/682 | 710,325,399 | MDExOlB1bGxSZXF1ZXN0NDk0MTkzMzEw | 682 | Update navbar chapter titles color | [] | closed | false | null | 0 | 2020-09-28T14:35:17Z | 2020-09-28T17:30:13Z | 2020-09-28T17:30:12Z | null | Consistency with the color change that was done in transformers at https://github.com/huggingface/transformers/pull/7423
It makes the background-color of the chapter titles in the docs navbar darker, to differentiate them from the inner sections.
see changes [here](https://691-250213286-gh.circle-artifacts.com/0/docs/_build/html/index.html) | {
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https://api.github.com/repos/huggingface/datasets/issues/5970 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5970/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5970/comments | https://api.github.com/repos/huggingface/datasets/issues/5970/events | https://github.com/huggingface/datasets/issues/5970 | 1,766,010,356 | I_kwDODunzps5pQy30 | 5,970 | description disappearing from Info when Uploading a Dataset Created with `from_dict` | [] | open | false | null | 2 | 2023-06-20T19:18:26Z | 2023-06-22T14:23:56Z | null | null | ### Describe the bug
When uploading a dataset created locally using `from_dict` with a specified `description` field. It appears before upload, but is missing after upload and re-download.
### Steps to reproduce the bug
I think the most relevant pattern in the code might be the following lines:
```
description_json_str = json.dumps(
{
"dataset_id": dataset.spec.dataset_id,
"env_name": dataset.spec.env_spec.id,
"action_space": serialize_space(dataset.spec.action_space),
"observation_space": serialize_space(dataset.spec.observation_space),
}
)
hugging_face_dataset = Dataset.from_dict(
episodes_dict, info=DatasetInfo(description=description_json_str)
)
```
Which comes from this function https://github.com/balisujohn/minarai/blob/8e023727f0a8488c4451651d9f7a79b981412c40/minari/integrations/hugging_face.py#L39
To replicate,
clone this branch of my Minari fork https://github.com/balisujohn/minarai/tree/dev-huggingface then run
```
python3.8 -m venv env
source env/bin/activate
python3 -m pip install -e .
python3 -m pip install pytest
```
The change the hugging face repo path in the test called `test_hugging_face_push_and_pull_dataset` in `tests/integrations/test_hugging_face.py` to one you have permissions to write to.
Then run:
```
pytest tests/integrations/test_hugging_face.py::test_hugging_face_push_and_pull_dataset
```
### Expected behavior
DATASET INFO BEFORE UPLOADING
DatasetInfo(description='{"dataset_id": "dummy-combo-test-v0", "env_name": "DummyComboEnv-v0", "action_space": "{\\"type\\": \\"Tuple\\", \\"subspaces\\": [{\\"type\\": \\"Box\\", \\"dtype\\": \\"float32\\", \\"shape\\": [1], \\"low\\": [2.0], \\"high\\": [3.0]}, {\\"type\\": \\"Box\\", \\"dtype\\": \\"float32\\", \\"shape\\": [1], \\"low\\": [4.0], \\"high\\": [5.0]}]}", "observation_space": "{\\"type\\": \\"Tuple\\", \\"subspaces\\": [{\\"type\\": \\"Box\\", \\"dtype\\": \\"float32\\", \\"shape\\": [1], \\"low\\": [2.0], \\"high\\": [3.0]}, {\\"type\\": \\"Tuple\\", \\"subspaces\\": [{\\"type\\": \\"Box\\", \\"dtype\\": \\"float32\\", \\"shape\\": [1], \\"low\\": [2.0], \\"high\\": [3.0]}, {\\"type\\": \\"Dict\\", \\"subspaces\\": {\\"component_1\\": {\\"type\\": \\"Box\\", \\"dtype\\": \\"float32\\", \\"shape\\": [1], \\"low\\": [-1.0], \\"high\\": [1.0]}, \\"component_2\\": {\\"type\\": \\"Dict\\", \\"subspaces\\": {\\"subcomponent_1\\": {\\"type\\": \\"Box\\", \\"dtype\\": \\"float32\\", \\"shape\\": [1], \\"low\\": [2.0], \\"high\\": [3.0]}, \\"subcomponent_2\\": {\\"type\\": \\"Tuple\\", \\"subspaces\\": [{\\"type\\": \\"Box\\", \\"dtype\\": \\"float32\\", \\"shape\\": [1], \\"low\\": [4.0], \\"high\\": [5.0]}, {\\"type\\": \\"Discrete\\", \\"dtype\\": \\"int64\\", \\"start\\": 0, \\"n\\": 10}]}}}}}]}]}"}', citation='', homepage='', license='', features={'observations': {'_index_0': Sequence(feature=Value(dtype='float32', id=None), length=-1, id=None), '_index_1': {'_index_0': Sequence(feature=Value(dtype='float32', id=None), length=-1, id=None), '_index_1': {'component_1': Sequence(feature=Value(dtype='float32', id=None), length=-1, id=None), 'component_2': {'subcomponent_1': Sequence(feature=Value(dtype='float32', id=None), length=-1, id=None), 'subcomponent_2': {'_index_0': Sequence(feature=Value(dtype='float32', id=None), length=-1, id=None), '_index_1': Value(dtype='int64', id=None)}}}}}, 'actions': {'_index_0': Sequence(feature=Value(dtype='float32', id=None), length=-1, id=None), '_index_1': Sequence(feature=Value(dtype='float32', id=None), length=-1, id=None)}, 'rewards': Value(dtype='int64', id=None), 'truncations': Value(dtype='bool', id=None), 'terminations': Value(dtype='bool', id=None), 'episode_ids': Value(dtype='int64', id=None)}, post_processed=None, supervised_keys=None, task_templates=None, builder_name=None, config_name=None, version=None, splits=None, download_checksums=None, download_size=None, post_processing_size=None, dataset_size=None, size_in_bytes=None)
...
DATASET INFO AFTER UPLOADING AND DOWNLOADING
DatasetInfo(description='', citation='', homepage='', license='', features={'observations': {'_index_0': Sequence(feature=Value(dtype='float32', id=None), length=-1, id=None), '_index_1': {'_index_0': Sequence(feature=Value(dtype='float32', id=None), length=-1, id=None), '_index_1': {'component_1': Sequence(feature=Value(dtype='float32', id=None), length=-1, id=None), 'component_2': {'subcomponent_1': Sequence(feature=Value(dtype='float32', id=None), length=-1, id=None), 'subcomponent_2': {'_index_0': Sequence(feature=Value(dtype='float32', id=None), length=-1, id=None), '_index_1': Value(dtype='int64', id=None)}}}}}, 'actions': {'_index_0': Sequence(feature=Value(dtype='float32', id=None), length=-1, id=None), '_index_1': Sequence(feature=Value(dtype='float32', id=None), length=-1, id=None)}, 'rewards': Value(dtype='int64', id=None), 'truncations': Value(dtype='bool', id=None), 'terminations': Value(dtype='bool', id=None), 'episode_ids': Value(dtype='int64', id=None)}, post_processed=None, supervised_keys=None, task_templates=None, builder_name=None, config_name=None, version=None, splits={'train': SplitInfo(name='train', num_bytes=4846, num_examples=60, shard_lengths=None, dataset_name='parquet')}, download_checksums={'https://huggingface.co/datasets/balisujohn/minari_test/resolve/8217b614ff9ba5edc1a30c7df430e92a46f65363/data/train-00000-of-00001-7c5900b93b35745e.parquet': {'num_bytes': 9052, 'checksum': None}}, download_size=9052, post_processing_size=None, dataset_size=4846, size_in_bytes=13898)
...
### Environment info
- `datasets` version: 2.13.0
- Platform: Linux-5.15.0-75-generic-x86_64-with-glibc2.29
- Python version: 3.8.10
- Huggingface_hub version: 0.15.1
- PyArrow version: 12.0.1
- Pandas version: 2.0.2
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"Here's a minimal way to reproduce the bug, for the sake of convenience.\r\n````\r\nfrom datasets import Dataset, DatasetInfo, load_dataset\r\n\r\n\r\nepisodes_dict = {\"test\":[1,2,3],\"test2\": [1,2,4]}\r\n\r\nhugging_face_dataset = Dataset.from_dict(\r\n episodes_dict, info=DatasetInfo(description=\"test_str\... |
https://api.github.com/repos/huggingface/datasets/issues/5684 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5684/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5684/comments | https://api.github.com/repos/huggingface/datasets/issues/5684/events | https://github.com/huggingface/datasets/pull/5684 | 1,646,013,226 | PR_kwDODunzps5NLXWm | 5,684 | Release: 2.11.0 | [] | closed | false | null | 5 | 2023-03-29T15:06:07Z | 2023-03-29T18:30:34Z | 2023-03-29T18:15:54Z | null | null | {
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} | true | [
"_The documentation is not available anymore as the PR was closed or merged._",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | rea... |
https://api.github.com/repos/huggingface/datasets/issues/2301 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2301/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2301/comments | https://api.github.com/repos/huggingface/datasets/issues/2301/events | https://github.com/huggingface/datasets/issues/2301 | 873,941,266 | MDU6SXNzdWU4NzM5NDEyNjY= | 2,301 | Unable to setup dev env on Windows | [] | closed | false | null | 2 | 2021-05-02T13:20:42Z | 2021-05-03T15:18:01Z | 2021-05-03T15:17:34Z | null | Hi
I tried installing the `".[dev]"` version on Windows 10 after cloning.
Here is the error I'm facing:
```bat
(env) C:\testing\datasets>pip install -e ".[dev]"
Obtaining file:///C:/testing/datasets
Requirement already satisfied: numpy>=1.17 in c:\programdata\anaconda3\envs\env\lib\site-packages (from datasets==1.5.0.dev0) (1.19.5)
Collecting pyarrow>=0.17.1
Using cached pyarrow-4.0.0-cp37-cp37m-win_amd64.whl (13.3 MB)
Requirement already satisfied: dill in c:\programdata\anaconda3\envs\env\lib\site-packages (from datasets==1.5.0.dev0) (0.3.1.1)
Collecting pandas
Using cached pandas-1.2.4-cp37-cp37m-win_amd64.whl (9.1 MB)
Requirement already satisfied: requests>=2.19.0 in c:\programdata\anaconda3\envs\env\lib\site-packages (from datasets==1.5.0.dev0) (2.25.1)
Requirement already satisfied: tqdm<4.50.0,>=4.27 in c:\programdata\anaconda3\envs\env\lib\site-packages (from datasets==1.5.0.dev0) (4.49.0)
Requirement already satisfied: xxhash in c:\programdata\anaconda3\envs\env\lib\site-packages (from datasets==1.5.0.dev0) (2.0.2)
Collecting multiprocess
Using cached multiprocess-0.70.11.1-py37-none-any.whl (108 kB)
Requirement already satisfied: fsspec in c:\programdata\anaconda3\envs\env\lib\site-packages (from datasets==1.5.0.dev0) (2021.4.0)
Collecting huggingface_hub<0.1.0
Using cached huggingface_hub-0.0.8-py3-none-any.whl (34 kB)
Requirement already satisfied: importlib_metadata in c:\programdata\anaconda3\envs\env\lib\site-packages (from datasets==1.5.0.dev0) (4.0.1)
Requirement already satisfied: absl-py in c:\programdata\anaconda3\envs\env\lib\site-packages (from datasets==1.5.0.dev0) (0.12.0)
Requirement already satisfied: pytest in c:\programdata\anaconda3\envs\env\lib\site-packages (from datasets==1.5.0.dev0) (6.2.3)
Collecting pytest-xdist
Using cached pytest_xdist-2.2.1-py3-none-any.whl (37 kB)
Collecting apache-beam>=2.24.0
Using cached apache_beam-2.29.0-cp37-cp37m-win_amd64.whl (3.7 MB)
Collecting elasticsearch
Using cached elasticsearch-7.12.1-py2.py3-none-any.whl (339 kB)
Requirement already satisfied: boto3==1.16.43 in c:\programdata\anaconda3\envs\env\lib\site-packages (from datasets==1.5.0.dev0) (1.16.43)
Requirement already satisfied: botocore==1.19.43 in c:\programdata\anaconda3\envs\env\lib\site-packages (from datasets==1.5.0.dev0) (1.19.43)
Collecting moto[s3]==1.3.16
Using cached moto-1.3.16-py2.py3-none-any.whl (879 kB)
Collecting rarfile>=4.0
Using cached rarfile-4.0-py3-none-any.whl (28 kB)
Collecting tensorflow>=2.3
Using cached tensorflow-2.4.1-cp37-cp37m-win_amd64.whl (370.7 MB)
Requirement already satisfied: torch in c:\programdata\anaconda3\envs\env\lib\site-packages (from datasets==1.5.0.dev0) (1.8.1)
Requirement already satisfied: transformers in c:\programdata\anaconda3\envs\env\lib\site-packages (from datasets==1.5.0.dev0) (4.5.1)
Collecting bs4
Using cached bs4-0.0.1-py3-none-any.whl
Collecting conllu
Using cached conllu-4.4-py2.py3-none-any.whl (15 kB)
Collecting langdetect
Using cached langdetect-1.0.8-py3-none-any.whl
Collecting lxml
Using cached lxml-4.6.3-cp37-cp37m-win_amd64.whl (3.5 MB)
Collecting mwparserfromhell
Using cached mwparserfromhell-0.6-cp37-cp37m-win_amd64.whl (101 kB)
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Requirement already satisfied: colorama in c:\programdata\anaconda3\envs\env\lib\site-packages (from pytest->datasets==1.5.0.dev0) (0.4.4)
Collecting pytest-forked
Using cached pytest_forked-1.3.0-py2.py3-none-any.whl (4.7 kB)
Collecting execnet>=1.1
Using cached execnet-1.8.0-py2.py3-none-any.whl (39 kB)
Requirement already satisfied: apipkg>=1.4 in c:\programdata\anaconda3\envs\env\lib\site-packages (from execnet>=1.1->pytest-xdist->datasets==1.5.0.dev0) (1.5)
Collecting portalocker==2.0.0
Using cached portalocker-2.0.0-py2.py3-none-any.whl (11 kB)
Requirement already satisfied: scikit-learn>=0.21.3 in c:\programdata\anaconda3\envs\env\lib\site-packages (from seqeval->datasets==1.5.0.dev0) (0.24.2)
Requirement already satisfied: threadpoolctl>=2.0.0 in c:\programdata\anaconda3\envs\env\lib\site-packages (from scikit-learn>=0.21.3->seqeval->datasets==1.5.0.dev0) (2.1.0)
Building wheels for collected packages: python-Levenshtein
Building wheel for python-Levenshtein (setup.py) ... error
ERROR: Command errored out with exit status 1:
command: 'C:\ProgramData\Anaconda3\envs\env\python.exe' -u -c 'import sys, setuptools, tokenize; sys.argv[0] = '"'"'C:\\Users\\VKC~1\\AppData\\Local\\Temp\\pip-install-ynt_dbm4\\python-levenshtein_c02e7e6f9def4629a475349654670ae9\\setup.py'"'"'; __file__='"'"'C:\\Users\\VKC~1\\AppData\\Local\\Temp\\pip-install-ynt_dbm4\\python-levenshtein_c02e7e6f9def4629a475349654670ae9\\setup.py'"'"';f=getattr(tokenize, '"'"'open'"'"', open)(__file__);code=f.read().replace('"'"'\r\n'"'"', '"'"'\n'"'"');f.close();exec(compile(code, __file__, '"'"'exec'"'"'))' bdist_wheel -d 'C:\Users\VKC~1\AppData\Local\Temp\pip-wheel-8jh7fm18'
cwd: C:\Users\VKC~1\AppData\Local\Temp\pip-install-ynt_dbm4\python-levenshtein_c02e7e6f9def4629a475349654670ae9\
Complete output (27 lines):
running bdist_wheel
running build
running build_py
creating build
creating build\lib.win-amd64-3.7
creating build\lib.win-amd64-3.7\Levenshtein
copying Levenshtein\StringMatcher.py -> build\lib.win-amd64-3.7\Levenshtein
copying Levenshtein\__init__.py -> build\lib.win-amd64-3.7\Levenshtein
running egg_info
writing python_Levenshtein.egg-info\PKG-INFO
writing dependency_links to python_Levenshtein.egg-info\dependency_links.txt
writing entry points to python_Levenshtein.egg-info\entry_points.txt
writing namespace_packages to python_Levenshtein.egg-info\namespace_packages.txt
writing requirements to python_Levenshtein.egg-info\requires.txt
writing top-level names to python_Levenshtein.egg-info\top_level.txt
reading manifest file 'python_Levenshtein.egg-info\SOURCES.txt'
reading manifest template 'MANIFEST.in'
warning: no previously-included files matching '*pyc' found anywhere in distribution
warning: no previously-included files matching '*so' found anywhere in distribution
warning: no previously-included files matching '.project' found anywhere in distribution
warning: no previously-included files matching '.pydevproject' found anywhere in distribution
writing manifest file 'python_Levenshtein.egg-info\SOURCES.txt'
copying Levenshtein\_levenshtein.c -> build\lib.win-amd64-3.7\Levenshtein
copying Levenshtein\_levenshtein.h -> build\lib.win-amd64-3.7\Levenshtein
running build_ext
building 'Levenshtein._levenshtein' extension
error: Microsoft Visual C++ 14.0 or greater is required. Get it with "Microsoft C++ Build Tools": https://visualstudio.microsoft.com/visual-cpp-build-tools/
----------------------------------------
ERROR: Failed building wheel for python-Levenshtein
Running setup.py clean for python-Levenshtein
Failed to build python-Levenshtein
Installing collected packages: python-Levenshtein, pytest-forked, pyppmd, pymongo, pyflakes, pydot, pycryptodome, pycodestyle, pyarrow, portalocker, pathspec, pandas, opt-einsum, oauth2client, nltk, mypy-extensions, multivolumefile, multiprocess, moto, mccabe, matplotlib, keras-preprocessing, huggingface-hub, hdfs, h5py, google-pasta, gast, flatbuffers, fastavro, execnet, et-xmlfile, entrypoints, crcmod, beautifulsoup4, bcj-cffi, avro-python3, astunparse, appdirs, zstandard, tldextract, tensorflow, sklearn, seqeval, sacrebleu, rouge-score, rarfile, pytest-xdist, py7zr, openpyxl, mwparserfromhell, lxml, langdetect, jiwer, isort, flake8, elasticsearch, datasets, conllu, bs4, black, bert-score, apache-beam
Running setup.py install for python-Levenshtein ... error
ERROR: Command errored out with exit status 1:
command: 'C:\ProgramData\Anaconda3\envs\env\python.exe' -u -c 'import sys, setuptools, tokenize; sys.argv[0] = '"'"'C:\\Users\\VKC~1\\AppData\\Local\\Temp\\pip-install-ynt_dbm4\\python-levenshtein_c02e7e6f9def4629a475349654670ae9\\setup.py'"'"'; __file__='"'"'C:\\Users\\VKC~1\\AppData\\Local\\Temp\\pip-install-ynt_dbm4\\python-levenshtein_c02e7e6f9def4629a475349654670ae9\\setup.py'"'"';f=getattr(tokenize, '"'"'open'"'"', open)(__file__);code=f.read().replace('"'"'\r\n'"'"', '"'"'\n'"'"');f.close();exec(compile(code, __file__, '"'"'exec'"'"'))' install --record 'C:\Users\VKC~1\AppData\Local\Temp\pip-record-v7l7zitb\install-record.txt' --single-version-externally-managed --compile --install-headers 'C:\ProgramData\Anaconda3\envs\env\Include\python-Levenshtein'
cwd: C:\Users\VKC~1\AppData\Local\Temp\pip-install-ynt_dbm4\python-levenshtein_c02e7e6f9def4629a475349654670ae9\
Complete output (27 lines):
running install
running build
running build_py
creating build
creating build\lib.win-amd64-3.7
creating build\lib.win-amd64-3.7\Levenshtein
copying Levenshtein\StringMatcher.py -> build\lib.win-amd64-3.7\Levenshtein
copying Levenshtein\__init__.py -> build\lib.win-amd64-3.7\Levenshtein
running egg_info
writing python_Levenshtein.egg-info\PKG-INFO
writing dependency_links to python_Levenshtein.egg-info\dependency_links.txt
writing entry points to python_Levenshtein.egg-info\entry_points.txt
writing namespace_packages to python_Levenshtein.egg-info\namespace_packages.txt
writing requirements to python_Levenshtein.egg-info\requires.txt
writing top-level names to python_Levenshtein.egg-info\top_level.txt
reading manifest file 'python_Levenshtein.egg-info\SOURCES.txt'
reading manifest template 'MANIFEST.in'
warning: no previously-included files matching '*pyc' found anywhere in distribution
warning: no previously-included files matching '*so' found anywhere in distribution
warning: no previously-included files matching '.project' found anywhere in distribution
warning: no previously-included files matching '.pydevproject' found anywhere in distribution
writing manifest file 'python_Levenshtein.egg-info\SOURCES.txt'
copying Levenshtein\_levenshtein.c -> build\lib.win-amd64-3.7\Levenshtein
copying Levenshtein\_levenshtein.h -> build\lib.win-amd64-3.7\Levenshtein
running build_ext
building 'Levenshtein._levenshtein' extension
error: Microsoft Visual C++ 14.0 or greater is required. Get it with "Microsoft C++ Build Tools": https://visualstudio.microsoft.com/visual-cpp-build-tools/
----------------------------------------
ERROR: Command errored out with exit status 1: 'C:\ProgramData\Anaconda3\envs\env\python.exe' -u -c 'import sys, setuptools, tokenize; sys.argv[0] = '"'"'C:\\Users\\VKC~1\\AppData\\Local\\Temp\\pip-install-ynt_dbm4\\python-levenshtein_c02e7e6f9def4629a475349654670ae9\\setup.py'"'"'; __file__='"'"'C:\\Users\\VKC~1\\AppData\\Local\\Temp\\pip-install-ynt_dbm4\\python-levenshtein_c02e7e6f9def4629a475349654670ae9\\setup.py'"'"';f=getattr(tokenize, '"'"'open'"'"', open)(__file__);code=f.read().replace('"'"'\r\n'"'"', '"'"'\n'"'"');f.close();exec(compile(code, __file__, '"'"'exec'"'"'))' install --record 'C:\Users\VKC~1\AppData\Local\Temp\pip-record-v7l7zitb\install-record.txt' --single-version-externally-managed --compile --install-headers 'C:\ProgramData\Anaconda3\envs\env\Include\python-Levenshtein' Check the logs for full command output.
```
Here are conda and python versions:
```bat
(env) C:\testing\datasets>conda --version
conda 4.9.2
(env) C:\testing\datasets>python --version
Python 3.7.10
```
Please help me out. Thanks. | {
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} | https://api.github.com/repos/huggingface/datasets/issues/2301/timeline | null | completed | null | null | false | [
"Hi @gchhablani, \r\n\r\nThere are some 3rd-party dependencies that require to build code in C. In this case, it is the library `python-Levenshtein`.\r\n\r\nOn Windows, in order to be able to build C code, you need to install at least `Microsoft C++ Build Tools` version 14. You can find more info here: https://visu... |
https://api.github.com/repos/huggingface/datasets/issues/4712 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4712/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4712/comments | https://api.github.com/repos/huggingface/datasets/issues/4712/events | https://github.com/huggingface/datasets/pull/4712 | 1,309,177,302 | PR_kwDODunzps47ohdr | 4,712 | Highlight non-commercial license in amazon_reviews_multi dataset card | [] | closed | false | null | 1 | 2022-07-19T08:36:20Z | 2022-07-27T16:09:40Z | 2022-07-27T15:57:41Z | null | Highlight that the licence granted by Amazon only covers non-commercial research use. | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] |
https://api.github.com/repos/huggingface/datasets/issues/1794 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1794/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1794/comments | https://api.github.com/repos/huggingface/datasets/issues/1794/events | https://github.com/huggingface/datasets/pull/1794 | 796,975,588 | MDExOlB1bGxSZXF1ZXN0NTY0MDYyMTkw | 1,794 | Move silicone directory | [] | closed | false | null | 0 | 2021-01-29T15:33:15Z | 2021-01-29T16:31:39Z | 2021-01-29T16:31:38Z | null | The dataset was added in #1761 but not in the right directory. I'm moving it to /datasets | {
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https://api.github.com/repos/huggingface/datasets/issues/1451 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1451/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1451/comments | https://api.github.com/repos/huggingface/datasets/issues/1451/events | https://github.com/huggingface/datasets/pull/1451 | 761,102,770 | MDExOlB1bGxSZXF1ZXN0NTM1ODIwOTY3 | 1,451 | Add European Center for Disease Control and Preventions's (ECDC) Translation Memory dataset | [] | closed | false | null | 0 | 2020-12-10T10:14:20Z | 2020-12-11T16:50:09Z | 2020-12-11T16:50:09Z | null | ECDC-TM homepage: https://ec.europa.eu/jrc/en/language-technologies/ecdc-translation-memory | {
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https://api.github.com/repos/huggingface/datasets/issues/5538 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5538/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5538/comments | https://api.github.com/repos/huggingface/datasets/issues/5538/events | https://github.com/huggingface/datasets/issues/5538 | 1,587,732,596 | I_kwDODunzps5eouB0 | 5,538 | load_dataset in seaborn is not working for me. getting this error. | [] | closed | false | null | 1 | 2023-02-16T14:01:58Z | 2023-02-16T14:44:36Z | 2023-02-16T14:44:36Z | null | TimeoutError Traceback (most recent call last)
~\anaconda3\lib\urllib\request.py in do_open(self, http_class, req, **http_conn_args)
1345 try:
-> 1346 h.request(req.get_method(), req.selector, req.data, headers,
1347 encode_chunked=req.has_header('Transfer-encoding'))
~\anaconda3\lib\http\client.py in request(self, method, url, body, headers, encode_chunked)
1278 """Send a complete request to the server."""
-> 1279 self._send_request(method, url, body, headers, encode_chunked)
1280
~\anaconda3\lib\http\client.py in _send_request(self, method, url, body, headers, encode_chunked)
1324 body = _encode(body, 'body')
-> 1325 self.endheaders(body, encode_chunked=encode_chunked)
1326
~\anaconda3\lib\http\client.py in endheaders(self, message_body, encode_chunked)
1273 raise CannotSendHeader()
-> 1274 self._send_output(message_body, encode_chunked=encode_chunked)
1275
~\anaconda3\lib\http\client.py in _send_output(self, message_body, encode_chunked)
1033 del self._buffer[:]
-> 1034 self.send(msg)
1035
~\anaconda3\lib\http\client.py in send(self, data)
973 if self.auto_open:
--> 974 self.connect()
975 else:
~\anaconda3\lib\http\client.py in connect(self)
1440
-> 1441 super().connect()
1442
~\anaconda3\lib\http\client.py in connect(self)
944 """Connect to the host and port specified in __init__."""
--> 945 self.sock = self._create_connection(
946 (self.host,self.port), self.timeout, self.source_address)
~\anaconda3\lib\socket.py in create_connection(address, timeout, source_address)
843 try:
--> 844 raise err
845 finally:
~\anaconda3\lib\socket.py in create_connection(address, timeout, source_address)
831 sock.bind(source_address)
--> 832 sock.connect(sa)
833 # Break explicitly a reference cycle
TimeoutError: [WinError 10060] A connection attempt failed because the connected party did not properly respond after a period of time, or established connection failed because connected host has failed to respond
During handling of the above exception, another exception occurred:
URLError Traceback (most recent call last)
~\AppData\Local\Temp/ipykernel_12220/2927704185.py in <module>
1 import seaborn as sn
----> 2 iris = sn.load_dataset('iris')
~\anaconda3\lib\site-packages\seaborn\utils.py in load_dataset(name, cache, data_home, **kws)
594 if name not in get_dataset_names():
595 raise ValueError(f"'{name}' is not one of the example datasets.")
--> 596 urlretrieve(url, cache_path)
597 full_path = cache_path
598 else:
~\anaconda3\lib\urllib\request.py in urlretrieve(url, filename, reporthook, data)
237 url_type, path = _splittype(url)
238
--> 239 with contextlib.closing(urlopen(url, data)) as fp:
240 headers = fp.info()
241
~\anaconda3\lib\urllib\request.py in urlopen(url, data, timeout, cafile, capath, cadefault, context)
212 else:
213 opener = _opener
--> 214 return opener.open(url, data, timeout)
215
216 def install_opener(opener):
~\anaconda3\lib\urllib\request.py in open(self, fullurl, data, timeout)
515
516 sys.audit('urllib.Request', req.full_url, req.data, req.headers, req.get_method())
--> 517 response = self._open(req, data)
518
519 # post-process response
~\anaconda3\lib\urllib\request.py in _open(self, req, data)
532
533 protocol = req.type
--> 534 result = self._call_chain(self.handle_open, protocol, protocol +
535 '_open', req)
536 if result:
~\anaconda3\lib\urllib\request.py in _call_chain(self, chain, kind, meth_name, *args)
492 for handler in handlers:
493 func = getattr(handler, meth_name)
--> 494 result = func(*args)
495 if result is not None:
496 return result
~\anaconda3\lib\urllib\request.py in https_open(self, req)
1387
1388 def https_open(self, req):
-> 1389 return self.do_open(http.client.HTTPSConnection, req,
1390 context=self._context, check_hostname=self._check_hostname)
1391
~\anaconda3\lib\urllib\request.py in do_open(self, http_class, req, **http_conn_args)
1347 encode_chunked=req.has_header('Transfer-encoding'))
1348 except OSError as err: # timeout error
-> 1349 raise URLError(err)
1350 r = h.getresponse()
1351 except:
URLError: <urlopen error [WinError 10060] A connection attempt failed because the connected party did not properly respond after a period of time, or established connection failed because connected host has failed to respond>
| {
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} | https://api.github.com/repos/huggingface/datasets/issues/5538/timeline | null | completed | null | null | false | [
"Hi! `seaborn`'s `load_dataset` pulls datasets from [here](https://github.com/mwaskom/seaborn-data) and not from our Hub, so this issue is not related to our library in any way and should be reported in their repo instead."
] |
https://api.github.com/repos/huggingface/datasets/issues/546 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/546/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/546/comments | https://api.github.com/repos/huggingface/datasets/issues/546/events | https://github.com/huggingface/datasets/issues/546 | 689,186,526 | MDU6SXNzdWU2ODkxODY1MjY= | 546 | Very slow data loading on large dataset | [] | closed | false | null | 22 | 2020-08-31T12:57:23Z | 2022-06-17T17:06:51Z | 2020-09-08T10:19:57Z | null | I made a simple python script to check the NLP library speed, which loads 1.1 TB of textual data.
It has been 8 hours and still, it is on the loading steps.
It does work when the text dataset size is small about 1 GB, but it doesn't scale.
It also uses a single thread during the data loading step.
```
train_files = glob.glob("xxx/*.txt",recursive=True)
random.shuffle(train_files)
print(train_files)
dataset = nlp.load_dataset('text',
data_files=train_files,
name="customDataset",
version="1.0.0",
cache_dir="xxx/nlp")
```
Is there something that I am missing ? | {
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} | https://api.github.com/repos/huggingface/datasets/issues/546/timeline | null | completed | null | null | false | [
"When you load a text file for the first time with `nlp`, the file is converted into Apache Arrow format. Arrow allows to use memory-mapping, which means that you can load an arbitrary large dataset.\r\n\r\nNote that as soon as the conversion has been done once, the next time you'll load the dataset it will be much... |
https://api.github.com/repos/huggingface/datasets/issues/134 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/134/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/134/comments | https://api.github.com/repos/huggingface/datasets/issues/134/events | https://github.com/huggingface/datasets/pull/134 | 619,112,641 | MDExOlB1bGxSZXF1ZXN0NDE4Njk5OTYz | 134 | Update README.md | [] | closed | false | null | 1 | 2020-05-15T16:56:14Z | 2020-05-28T08:21:49Z | 2020-05-28T08:21:49Z | null | {
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} | true | [
"the readme got removed, closing this one"
] | |
https://api.github.com/repos/huggingface/datasets/issues/1466 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1466/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1466/comments | https://api.github.com/repos/huggingface/datasets/issues/1466/events | https://github.com/huggingface/datasets/pull/1466 | 761,554,357 | MDExOlB1bGxSZXF1ZXN0NTM2MjA0OTMx | 1,466 | Add Turkish News Category Dataset (270K).Updates were made for review… | [] | closed | false | null | 4 | 2020-12-10T19:41:12Z | 2020-12-11T14:27:15Z | 2020-12-11T14:27:15Z | null | This PR adds the **Turkish News Categories Dataset (270K)** dataset which is a text classification dataset by me and @yavuzKomecoglu. Turkish news dataset consisting of **273601 news in 17 categories**, compiled from printed media and news websites between 2010 and 2017 by the [Interpress](https://www.interpress.com/) media monitoring company.
**Note**: Resubmitted as a clean version of the previous Pull Request(#1419). @SBrandeis @lhoestq | {
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"@SBrandeis, What exactly is it that makes the tests fail? Can you help me please?",
"These errors\r\n```\r\n=========================== short test summary info ============================\r\nFAILED tests/test_dataset_common.py::LocalDatasetTest::test_load_dataset_ajgt_twitter_ar\r\nFAILED tests/test_dataset_com... |
https://api.github.com/repos/huggingface/datasets/issues/3975 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3975/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3975/comments | https://api.github.com/repos/huggingface/datasets/issues/3975/events | https://github.com/huggingface/datasets/pull/3975 | 1,174,678,942 | PR_kwDODunzps40tKdS | 3,975 | Update many missing tags to dataset README's | [] | closed | false | null | 0 | 2022-03-20T20:42:27Z | 2022-03-21T18:39:52Z | 2022-03-21T18:39:52Z | null | I've started to go through the datasets available and noticed that there are 127 datasets that does not have all the tags so I started filling them in; starting with some of the most common and QA datasets
Not 100% certain that the task_id is correct for SuperGLUE
If anyone is browsing the issues and would like to help make Hugging face datasets even more feature complete and awesome, feel free to use this tool I wrote to find the missing tags in the [datacards](https://github.com/Hugging-Face-Supporter/datacards) | {
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https://api.github.com/repos/huggingface/datasets/issues/1818 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1818/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1818/comments | https://api.github.com/repos/huggingface/datasets/issues/1818/events | https://github.com/huggingface/datasets/issues/1818 | 800,958,776 | MDU6SXNzdWU4MDA5NTg3NzY= | 1,818 | Loading local dataset raise requests.exceptions.ConnectTimeout | [] | closed | false | null | 1 | 2021-02-04T05:55:23Z | 2022-06-01T15:38:42Z | 2022-06-01T15:38:42Z | null | Load local dataset:
```
dataset = load_dataset('json', data_files=["../../data/json.json"])
train = dataset["train"]
print(train.features)
train1 = train.map(lambda x: {"labels": 1})
print(train1[:2])
```
but it raised requests.exceptions.ConnectTimeout:
```
/Users/littlely/myvirtual/tf2/bin/python3.7 /Users/littlely/projects/python_projects/pytorch_learning/nlp/dataset/transformers_datasets.py
Traceback (most recent call last):
File "/Users/littlely/myvirtual/tf2/lib/python3.7/site-packages/urllib3/connection.py", line 160, in _new_conn
(self._dns_host, self.port), self.timeout, **extra_kw
File "/Users/littlely/myvirtual/tf2/lib/python3.7/site-packages/urllib3/util/connection.py", line 84, in create_connection
raise err
File "/Users/littlely/myvirtual/tf2/lib/python3.7/site-packages/urllib3/util/connection.py", line 74, in create_connection
sock.connect(sa)
socket.timeout: timed out
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/Users/littlely/myvirtual/tf2/lib/python3.7/site-packages/urllib3/connectionpool.py", line 677, in urlopen
chunked=chunked,
File "/Users/littlely/myvirtual/tf2/lib/python3.7/site-packages/urllib3/connectionpool.py", line 381, in _make_request
self._validate_conn(conn)
File "/Users/littlely/myvirtual/tf2/lib/python3.7/site-packages/urllib3/connectionpool.py", line 978, in _validate_conn
conn.connect()
File "/Users/littlely/myvirtual/tf2/lib/python3.7/site-packages/urllib3/connection.py", line 309, in connect
conn = self._new_conn()
File "/Users/littlely/myvirtual/tf2/lib/python3.7/site-packages/urllib3/connection.py", line 167, in _new_conn
% (self.host, self.timeout),
urllib3.exceptions.ConnectTimeoutError: (<urllib3.connection.HTTPSConnection object at 0x1181e9940>, 'Connection to s3.amazonaws.com timed out. (connect timeout=10)')
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/Users/littlely/myvirtual/tf2/lib/python3.7/site-packages/requests/adapters.py", line 449, in send
timeout=timeout
File "/Users/littlely/myvirtual/tf2/lib/python3.7/site-packages/urllib3/connectionpool.py", line 727, in urlopen
method, url, error=e, _pool=self, _stacktrace=sys.exc_info()[2]
File "/Users/littlely/myvirtual/tf2/lib/python3.7/site-packages/urllib3/util/retry.py", line 439, in increment
raise MaxRetryError(_pool, url, error or ResponseError(cause))
urllib3.exceptions.MaxRetryError: HTTPSConnectionPool(host='s3.amazonaws.com', port=443): Max retries exceeded with url: /datasets.huggingface.co/datasets/datasets/json/json.py (Caused by ConnectTimeoutError(<urllib3.connection.HTTPSConnection object at 0x1181e9940>, 'Connection to s3.amazonaws.com timed out. (connect timeout=10)'))
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/Users/littlely/projects/python_projects/pytorch_learning/nlp/dataset/transformers_datasets.py", line 12, in <module>
dataset = load_dataset('json', data_files=["../../data/json.json"])
File "/Users/littlely/myvirtual/tf2/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/littlely/myvirtual/tf2/lib/python3.7/site-packages/datasets/load.py", line 263, in prepare_module
head_hf_s3(path, filename=name, dataset=dataset, max_retries=download_config.max_retries)
File "/Users/littlely/myvirtual/tf2/lib/python3.7/site-packages/datasets/utils/file_utils.py", line 232, in head_hf_s3
max_retries=max_retries,
File "/Users/littlely/myvirtual/tf2/lib/python3.7/site-packages/datasets/utils/file_utils.py", line 523, in http_head
max_retries=max_retries,
File "/Users/littlely/myvirtual/tf2/lib/python3.7/site-packages/datasets/utils/file_utils.py", line 458, in _request_with_retry
raise err
File "/Users/littlely/myvirtual/tf2/lib/python3.7/site-packages/datasets/utils/file_utils.py", line 454, in _request_with_retry
response = requests.request(verb.upper(), url, **params)
File "/Users/littlely/myvirtual/tf2/lib/python3.7/site-packages/requests/api.py", line 61, in request
return session.request(method=method, url=url, **kwargs)
File "/Users/littlely/myvirtual/tf2/lib/python3.7/site-packages/requests/sessions.py", line 530, in request
resp = self.send(prep, **send_kwargs)
File "/Users/littlely/myvirtual/tf2/lib/python3.7/site-packages/requests/sessions.py", line 643, in send
r = adapter.send(request, **kwargs)
File "/Users/littlely/myvirtual/tf2/lib/python3.7/site-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/json/json.py (Caused by ConnectTimeoutError(<urllib3.connection.HTTPSConnection object at 0x1181e9940>, 'Connection to s3.amazonaws.com timed out. (connect timeout=10)'))
Process finished with exit code 1
```
Why it want to connect a remote url when I load local datasets, and how can I fix it? | {
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} | https://api.github.com/repos/huggingface/datasets/issues/1818/timeline | null | completed | null | null | false | [
"Hi ! Thanks for reporting. This was indeed a bug introduced when we moved the `json` dataset loader inside the `datasets` package (before that, the `json` loader was fetched online, as all the other dataset scripts).\r\n\r\nThis should be fixed on master now. Feel free to install `datasets` from source to try it o... |
https://api.github.com/repos/huggingface/datasets/issues/4034 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4034/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4034/comments | https://api.github.com/repos/huggingface/datasets/issues/4034/events | https://github.com/huggingface/datasets/pull/4034 | 1,183,033,285 | PR_kwDODunzps41IpN1 | 4,034 | Fix null checksum in xcopa dataset | [] | closed | false | null | 0 | 2022-03-28T07:48:14Z | 2022-03-28T08:06:14Z | 2022-03-28T08:06:14Z | null | null | {
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https://api.github.com/repos/huggingface/datasets/issues/1730 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1730/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1730/comments | https://api.github.com/repos/huggingface/datasets/issues/1730/events | https://github.com/huggingface/datasets/pull/1730 | 784,617,525 | MDExOlB1bGxSZXF1ZXN0NTUzNzgxMDY0 | 1,730 | Add MNIST dataset | [] | closed | false | null | 0 | 2021-01-12T21:48:02Z | 2021-01-13T10:19:47Z | 2021-01-13T10:19:46Z | null | This PR adds the MNIST dataset to the library. | {
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https://api.github.com/repos/huggingface/datasets/issues/4567 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4567/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4567/comments | https://api.github.com/repos/huggingface/datasets/issues/4567/events | https://github.com/huggingface/datasets/pull/4567 | 1,284,528,474 | PR_kwDODunzps46Wh0- | 4,567 | Add evaluation data for amazon_reviews_multi | [
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"_The documentation is not available anymore as the PR was closed or merged._",
"As discussed with @lewtun, we are closing this PR, because it requires first the task names to be aligned between AutoTrain and datasets."
] |
https://api.github.com/repos/huggingface/datasets/issues/3532 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3532/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3532/comments | https://api.github.com/repos/huggingface/datasets/issues/3532/events | https://github.com/huggingface/datasets/pull/3532 | 1,094,035,066 | PR_kwDODunzps4wi1ft | 3,532 | Give clearer instructions to add the YAML tags | [] | closed | false | null | 1 | 2022-01-05T06:47:52Z | 2022-01-17T15:54:37Z | 2022-01-17T15:54:36Z | null | Fix #3531.
CC: @julien-c @VictorSanh | {
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"this is great, maybe just put all of it in one line?\r\n\r\n> TODO: Add YAML tags here. Copy-paste the tags obtained with the online tagging app: https://huggingface.co/spaces/huggingface/datasets-tagging"
] |
https://api.github.com/repos/huggingface/datasets/issues/3862 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3862/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3862/comments | https://api.github.com/repos/huggingface/datasets/issues/3862/events | https://github.com/huggingface/datasets/pull/3862 | 1,162,753,733 | PR_kwDODunzps40HFht | 3,862 | Manipulate columns on IterableDataset (rename columns, cast, etc.) | [] | closed | false | null | 2 | 2022-03-08T14:53:57Z | 2022-03-10T16:40:22Z | 2022-03-10T16:40:21Z | null | I added:
- add_column
- cast
- rename_column
- rename_columns
related to https://github.com/huggingface/datasets/issues/3444
TODO:
- [x] docs
- [x] tests | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3862). All of your documentation changes will be reflected on that endpoint.",
"> IIUC we check if columns are present/not present directly in the yielded examples and not in info.features because info.features can be None (aft... |
https://api.github.com/repos/huggingface/datasets/issues/1118 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1118/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1118/comments | https://api.github.com/repos/huggingface/datasets/issues/1118/events | https://github.com/huggingface/datasets/pull/1118 | 757,142,350 | MDExOlB1bGxSZXF1ZXN0NTMyNTY3ODMw | 1,118 | Add Tashkeela dataset | [] | closed | false | null | 2 | 2020-12-04T14:26:18Z | 2020-12-04T15:47:01Z | 2020-12-04T15:46:51Z | null | Arabic Vocalized Words Dataset. | {
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"Sorry @lhoestq for the trouble, sometime I forget to change the names :/",
"> Sorry @lhoestq for the trouble, sometime I forget to change the names :/\r\n\r\nhaha it's ok ;)"
] |
https://api.github.com/repos/huggingface/datasets/issues/1526 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1526/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1526/comments | https://api.github.com/repos/huggingface/datasets/issues/1526/events | https://github.com/huggingface/datasets/pull/1526 | 764,591,243 | MDExOlB1bGxSZXF1ZXN0NTM4NTgxNDg4 | 1,526 | added Hebrew thisworld corpus | [] | closed | false | null | 1 | 2020-12-12T23:42:52Z | 2020-12-18T10:47:30Z | 2020-12-18T10:47:30Z | null | added corpus from https://thisworld.online/ , https://github.com/thisworld1/thisworld.online | {
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"merging since the CI is fixed on master"
] |
https://api.github.com/repos/huggingface/datasets/issues/3204 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3204/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3204/comments | https://api.github.com/repos/huggingface/datasets/issues/3204/events | https://github.com/huggingface/datasets/issues/3204 | 1,043,707,307 | I_kwDODunzps4-NbWr | 3,204 | FileNotFoundError for TupleIE dataste | [
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] | closed | false | null | 3 | 2021-11-03T14:56:55Z | 2021-11-05T15:51:15Z | 2021-11-05T14:16:05Z | null | Hi,
`dataset = datasets.load_dataset('tuple_ie', 'all')`
returns a FileNotFound error. Is the data not available?
Many thanks.
| {
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"@mariosasko @lhoestq Could you give me an update on how to load the dataset after the fix?\r\nThanks.",
"Hi @arda-vianai,\r\n\r\nfirst, you can try:\r\n```python\r\nimport datasets\r\ndataset = datasets.load_dataset('tuple_ie', 'all', revision=\"master\")\r\n```\r\nIf this doesn't work, your version of `datasets... |
https://api.github.com/repos/huggingface/datasets/issues/2000 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2000/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2000/comments | https://api.github.com/repos/huggingface/datasets/issues/2000/events | https://github.com/huggingface/datasets/issues/2000 | 823,899,910 | MDU6SXNzdWU4MjM4OTk5MTA= | 2,000 | Windows Permission Error (most recent version of datasets) | [] | closed | false | null | 5 | 2021-03-07T11:55:28Z | 2021-03-09T12:42:57Z | 2021-03-09T12:42:57Z | null | Hi everyone,
Can anyone help me with why the dataset loading script below raises a Windows Permission Error? I stuck quite closely to https://github.com/huggingface/datasets/blob/master/datasets/conll2003/conll2003.py , only I want to load the data from three local three-column tsv-files (id\ttokens\tpos_tags\n). I am using the most recent version of datasets. Thank you in advance!
Luisa
My script:
```
import datasets
import csv
logger = datasets.logging.get_logger(__name__)
class SampleConfig(datasets.BuilderConfig):
def __init__(self, **kwargs):
super(SampleConfig, self).__init__(**kwargs)
class Sample(datasets.GeneratorBasedBuilder):
BUILDER_CONFIGS = [
SampleConfig(name="conll2003", version=datasets.Version("1.0.0"), description="Conll2003 dataset"),
]
def _info(self):
return datasets.DatasetInfo(
description="Dataset with words and their POS-Tags",
features=datasets.Features(
{
"id": datasets.Value("string"),
"tokens": datasets.Sequence(datasets.Value("string")),
"pos_tags": datasets.Sequence(
datasets.features.ClassLabel(
names=[
"''",
",",
"-LRB-",
"-RRB-",
".",
":",
"CC",
"CD",
"DT",
"EX",
"FW",
"HYPH",
"IN",
"JJ",
"JJR",
"JJS",
"MD",
"NN",
"NNP",
"NNPS",
"NNS",
"PDT",
"POS",
"PRP",
"PRP$",
"RB",
"RBR",
"RBS",
"RP",
"TO",
"UH",
"VB",
"VBD",
"VBG",
"VBN",
"VBP",
"VBZ",
"WDT",
"WP",
"WRB",
"``"
]
)
),
}
),
supervised_keys=None,
homepage="https://catalog.ldc.upenn.edu/LDC2011T03",
citation="Weischedel, Ralph, et al. OntoNotes Release 4.0 LDC2011T03. Web Download. Philadelphia: Linguistic Data Consortium, 2011.",
)
def _split_generators(self, dl_manager):
loaded_files = dl_manager.download_and_extract(self.config.data_files)
return [
datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": loaded_files["train"]}),
datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": loaded_files["test"]}),
datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": loaded_files["val"]})
]
def _generate_examples(self, filepath):
logger.info("generating examples from = %s", filepath)
with open(filepath, encoding="cp1252") as f:
data = csv.reader(f, delimiter="\t")
ids = list()
tokens = list()
pos_tags = list()
for id_, line in enumerate(data):
#print(line)
if len(line) == 1:
if tokens:
yield id_, {"id": ids, "tokens": tokens, "pos_tags": pos_tags}
ids = list()
tokens = list()
pos_tags = list()
else:
ids.append(line[0])
tokens.append(line[1])
pos_tags.append(line[2])
# last example
yield id_, {"id": ids, "tokens": tokens, "pos_tags": pos_tags}
def main():
dataset = datasets.load_dataset(
"data_loading.py", data_files={
"train": "train.tsv",
"test": "test.tsv",
"val": "val.tsv"
}
)
#print(dataset)
if __name__=="__main__":
main()
```
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} | https://api.github.com/repos/huggingface/datasets/issues/2000/timeline | null | completed | null | null | false | [
"Hi @itsLuisa !\r\n\r\nCould you give us more information about the error you're getting, please?\r\nA copy-paste of the Traceback would be nice to get a better understanding of what is wrong :) ",
"Hello @SBrandeis , this is it:\r\n```\r\nTraceback (most recent call last):\r\n File \"C:\\Users\\Luisa\\AppData\\... |
https://api.github.com/repos/huggingface/datasets/issues/3124 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3124/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3124/comments | https://api.github.com/repos/huggingface/datasets/issues/3124/events | https://github.com/huggingface/datasets/pull/3124 | 1,031,976,286 | PR_kwDODunzps4td-5w | 3,124 | More efficient nested features encoding | [] | closed | false | null | 2 | 2021-10-21T01:55:31Z | 2021-11-02T15:07:13Z | 2021-11-02T11:04:04Z | null | Nested encoding of features wastes a lot of time on operations which are effectively doing nothing when lists are used.
For example, if in the input we have a list of integers, `encoded_nested_example` will iterate over it and apply `encoded_nested_example` on every element even though it just return the int as is.
A similar issue is handled at an earlier stage when casting pytorch/tensorflow/pandas objects to python lists/numpy arrays:
https://github.com/huggingface/datasets/blob/c98c23c4260edadab00f997d1a5d66b7f2e93ce9/src/datasets/features/features.py#L149-L156
https://github.com/huggingface/datasets/blob/c98c23c4260edadab00f997d1a5d66b7f2e93ce9/src/datasets/features/features.py#L212-L228
In this pull request I suggest to use the same approach in `encoded_nested_example`.
In my setup there was a major speedup with this change: loading the data was at least x4 faster. | {
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} | true | [
"@lhoestq @albertvillanova @mariosasko\r\nCan you please check this out?",
"Thanks, done!"
] |
https://api.github.com/repos/huggingface/datasets/issues/2214 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2214/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2214/comments | https://api.github.com/repos/huggingface/datasets/issues/2214/events | https://github.com/huggingface/datasets/issues/2214 | 856,333,657 | MDU6SXNzdWU4NTYzMzM2NTc= | 2,214 | load_metric error: module 'datasets.utils.file_utils' has no attribute 'add_start_docstrings' | [
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] | closed | false | null | 4 | 2021-04-12T20:26:01Z | 2021-04-23T15:20:02Z | 2021-04-23T15:20:02Z | null | I'm having the same problem as [Notebooks issue 10](https://github.com/huggingface/notebooks/issues/10) on datasets 1.2.1, and it seems to be an issue with the datasets package.
```python
>>> from datasets import load_metric
>>> metric = load_metric("glue", "sst2")
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/ext3/miniconda3/lib/python3.8/site-packages/datasets-1.2.1-py3.8.egg/datasets/load.py", line 502, in load_metric
File "/ext3/miniconda3/lib/python3.8/site-packages/datasets-1.2.1-py3.8.egg/datasets/load.py", line 66, in import_main_class
File "/ext3/miniconda3/lib/python3.8/importlib/__init__.py", line 127, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "<frozen importlib._bootstrap>", line 1014, in _gcd_import
File "<frozen importlib._bootstrap>", line 991, in _find_and_load
File "<frozen importlib._bootstrap>", line 975, in _find_and_load_unlocked
File "<frozen importlib._bootstrap>", line 671, in _load_unlocked
File "<frozen importlib._bootstrap_external>", line 783, in exec_module
File "<frozen importlib._bootstrap>", line 219, in _call_with_frames_removed
File "/home/ns4008/.cache/huggingface/modules/datasets_modules/metrics/glue/e4606ab9804a36bcd5a9cebb2cb65bb14b6ac78ee9e6d5981fa679a495dd55de/glue.py", line 105, in <module>
@datasets.utils.file_utils.add_start_docstrings(_DESCRIPTION, _KWARGS_DESCRIPTION)
AttributeError: module 'datasets.utils.file_utils' has no attribute 'add_start_docstrings'
``` | {
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} | https://api.github.com/repos/huggingface/datasets/issues/2214/timeline | null | completed | null | null | false | [
"Hi @nsaphra, thanks for reporting.\r\n\r\nThis issue was fixed in `datasets` version 1.3.0. Could you please update `datasets` and tell me if the problem persists?\r\n```shell\r\npip install -U datasets\r\n```",
"There might be a bug in the conda version of `datasets` 1.2.1 where the datasets/metric scripts are ... |
https://api.github.com/repos/huggingface/datasets/issues/4128 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4128/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4128/comments | https://api.github.com/repos/huggingface/datasets/issues/4128/events | https://github.com/huggingface/datasets/pull/4128 | 1,197,326,311 | PR_kwDODunzps4138I6 | 4,128 | More robust `cast_to_python_objects` in `TypedSequence` | [] | closed | false | null | 1 | 2022-04-08T13:33:35Z | 2022-04-13T14:07:41Z | 2022-04-13T14:01:16Z | null | Adds a fallback to run an expensive version of `cast_to_python_objects` which exhaustively checks entire lists to avoid the `ArrowInvalid: Could not convert` error in `TypedSequence`. Currently, this error can happen in situations where only some images are decoded in `map`, in which case `cast_to_python_objects` fails to recognize that it needs to cast `PIL.Image` objects if they are not at the beginning of the sequence and stops after the first image dictionary (e.g., if `data` is `[{"bytes": None, "path": "some path"}, PIL.Image(), ...]`)
Fix #4124 | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] |
https://api.github.com/repos/huggingface/datasets/issues/610 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/610/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/610/comments | https://api.github.com/repos/huggingface/datasets/issues/610/events | https://github.com/huggingface/datasets/issues/610 | 698,349,388 | MDU6SXNzdWU2OTgzNDkzODg= | 610 | Load text file for RoBERTa pre-training. | [] | closed | false | null | 43 | 2020-09-10T18:41:38Z | 2022-11-22T13:51:24Z | 2022-11-22T13:51:23Z | null | I migrate my question from https://github.com/huggingface/transformers/pull/4009#issuecomment-690039444
I tried to train a Roberta from scratch using transformers. But I got OOM issues with loading a large text file.
According to the suggestion from @thomwolf , I tried to implement `datasets` to load my text file. This test.txt is a simple sample where each line is a sentence.
```
from datasets import load_dataset
dataset = load_dataset('text', data_files='test.txt',cache_dir="./")
dataset.set_format(type='torch',columns=["text"])
dataloader = torch.utils.data.DataLoader(dataset, batch_size=8)
next(iter(dataloader))
```
But dataload cannot yield sample and error is:
```
---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
<ipython-input-12-388aca337e2f> in <module>
----> 1 next(iter(dataloader))
/Library/Python/3.7/site-packages/torch/utils/data/dataloader.py in __next__(self)
361
362 def __next__(self):
--> 363 data = self._next_data()
364 self._num_yielded += 1
365 if self._dataset_kind == _DatasetKind.Iterable and \
/Library/Python/3.7/site-packages/torch/utils/data/dataloader.py in _next_data(self)
401 def _next_data(self):
402 index = self._next_index() # may raise StopIteration
--> 403 data = self._dataset_fetcher.fetch(index) # may raise StopIteration
404 if self._pin_memory:
405 data = _utils.pin_memory.pin_memory(data)
/Library/Python/3.7/site-packages/torch/utils/data/_utils/fetch.py in fetch(self, possibly_batched_index)
42 def fetch(self, possibly_batched_index):
43 if self.auto_collation:
---> 44 data = [self.dataset[idx] for idx in possibly_batched_index]
45 else:
46 data = self.dataset[possibly_batched_index]
/Library/Python/3.7/site-packages/torch/utils/data/_utils/fetch.py in <listcomp>(.0)
42 def fetch(self, possibly_batched_index):
43 if self.auto_collation:
---> 44 data = [self.dataset[idx] for idx in possibly_batched_index]
45 else:
46 data = self.dataset[possibly_batched_index]
KeyError: 0
```
`dataset.set_format(type='torch',columns=["text"])` returns a log says:
```
Set __getitem__(key) output type to torch for ['text'] columns (when key is int or slice) and don't output other (un-formatted) columns.
```
I noticed the dataset is `DatasetDict({'train': Dataset(features: {'text': Value(dtype='string', id=None)}, num_rows: 44)})`.
Each sample can be accessed by `dataset["train"]["text"]` instead of `dataset["text"]`.
Could you please give me any suggestions on how to modify this code to load the text file?
Versions:
Python version 3.7.3
PyTorch version 1.6.0
TensorFlow version 2.3.0
datasets version: 1.0.1 | {
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"Could you try\r\n```python\r\nload_dataset('text', data_files='test.txt',cache_dir=\"./\", split=\"train\")\r\n```\r\n?\r\n\r\n`load_dataset` returns a dictionary by default, like {\"train\": your_dataset}",
"Hi @lhoestq\r\nThanks for your suggestion.\r\n\r\nI tried \r\n```\r\ndataset = load_dataset('text', data... |
https://api.github.com/repos/huggingface/datasets/issues/4868 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4868/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4868/comments | https://api.github.com/repos/huggingface/datasets/issues/4868/events | https://github.com/huggingface/datasets/pull/4868 | 1,345,191,322 | PR_kwDODunzps49gBk0 | 4,868 | adding mafand to datasets | [
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] | closed | false | null | 6 | 2022-08-20T15:26:14Z | 2022-08-22T11:00:50Z | 2022-08-22T08:52:23Z | null | I'm addding the MAFAND dataset by Masakhane based on the paper/repository below:
Paper: https://aclanthology.org/2022.naacl-main.223/
Code: https://github.com/masakhane-io/lafand-mt
Please, help merge this
Everything works except for creating dummy data file | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"Hi @dadelani, thanks for your awesome contribution!!! :heart: \r\n\r\nHowever, now we are using the Hub to add new datasets, instead of this GitHub repo. \r\n\r\nYou could share this dataset under your Hub organization namespace: [Ma... |
https://api.github.com/repos/huggingface/datasets/issues/4210 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4210/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4210/comments | https://api.github.com/repos/huggingface/datasets/issues/4210/events | https://github.com/huggingface/datasets/issues/4210 | 1,214,089,130 | I_kwDODunzps5IXYeq | 4,210 | TypeError: Cannot cast array data from dtype('O') to dtype('int64') according to the rule 'safe' | [
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] | closed | false | null | 5 | 2022-04-25T07:28:42Z | 2022-05-31T12:16:31Z | 2022-05-31T12:16:31Z | null | ### System Info
```shell
- `transformers` version: 4.18.0
- Platform: Linux-5.4.144+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.7.13
- Huggingface_hub version: 0.5.1
- PyTorch version (GPU?): 1.10.0+cu111 (True)
- Tensorflow version (GPU?): 2.8.0 (True)
- Flax version (CPU?/GPU?/TPU?): not installed (NA)
- Jax version: not installed
- JaxLib version: not installed
- Using GPU in script?: <fill in>
- Using distributed or parallel set-up in script?: <fill in>
```
### Who can help?
@LysandreJik
### Information
- [ ] The official example scripts
- [X] My own modified scripts
### Tasks
- [ ] An officially supported task in the `examples` folder (such as GLUE/SQuAD, ...)
- [X] My own task or dataset (give details below)
### Reproduction
```python
from datasets import load_dataset,Features,Value,ClassLabel
class_names = ["cmn","deu","rus","fra","eng","jpn","spa","ita","kor","vie","nld","epo","por","tur","heb","hun","ell","ind","ara","arz","fin","bul","yue","swe","ukr","bel","que","ces","swh","nno","wuu","nob","zsm","est","kat","pol","lat","urd","sqi","isl","fry","afr","ron","fao","san","bre","tat","yid","uig","uzb","srp","qya","dan","pes","slk","eus","cycl","acm","tgl","lvs","kaz","hye","hin","lit","ben","cat","bos","hrv","tha","orv","cha","mon","lzh","scn","gle","mkd","slv","frm","glg","vol","ain","jbo","tok","ina","nds","mal","tlh","roh","ltz","oss","ido","gla","mlt","sco","ast","jav","oci","ile","ota","xal","tel","sjn","nov","khm","tpi","ang","aze","tgk","tuk","chv","hsb","dsb","bod","sme","cym","mri","ksh","kmr","ewe","kab","ber","tpw","udm","lld","pms","lad","grn","mlg","xho","pnb","grc","hat","lao","npi","cor","nah","avk","mar","guj","pan","kir","myv","prg","sux","crs","ckt","bak","zlm","hil","cbk","chr","nav","lkt","enm","arq","lin","abk","pcd","rom","gsw","tam","zul","awa","wln","amh","bar","hbo","mhr","bho","mrj","ckb","osx","pfl","mgm","sna","mah","hau","kan","nog","sin","glv","dng","kal","liv","vro","apc","jdt","fur","che","haw","yor","crh","pdc","ppl","kin","shs","mnw","tet","sah","kum","ngt","nya","pus","hif","mya","moh","wol","tir","ton","lzz","oar","lug","brx","non","mww","hak","nlv","ngu","bua","aym","vec","ibo","tkl","bam","kha","ceb","lou","fuc","smo","gag","lfn","arg","umb","tyv","kjh","oji","cyo","urh","kzj","pam","srd","lmo","swg","mdf","gil","snd","tso","sot","zza","tsn","pau","som","egl","ady","asm","ori","dtp","cho","max","kam","niu","sag","ilo","kaa","fuv","nch","hoc","iba","gbm","sun","war","mvv","pap","ary","kxi","csb","pag","cos","rif","kek","krc","aii","ban","ssw","tvl","mfe","tah","bvy","bcl","hnj","nau","nst","afb","quc","min","tmw","mad","bjn","mai","cjy","got","hsn","gan","tzl","dws","ldn","afh","sgs","krl","vep","rue","tly","mic","ext","izh","sma","jam","cmo","mwl","kpv","koi","bis","ike","run","evn","ryu","mnc","aoz","otk","kas","aln","akl","yua","shy","fkv","gos","fij","thv","zgh","gcf","cay","xmf","tig","div","lij","rap","hrx","cpi","tts","gaa","tmr","iii","ltg","bzt","syc","emx","gom","chg","osp","stq","frr","fro","nys","toi","new","phn","jpa","rel","drt","chn","pli","laa","bal","hdn","hax","mik","ajp","xqa","pal","crk","mni","lut","ayl","ood","sdh","ofs","nus","kiu","diq","qxq","alt","bfz","klj","mus","srn","guc","lim","zea","shi","mnr","bom","sat","szl"]
features = Features({ 'label': ClassLabel(names=class_names), 'text': Value('string')})
num_labels = features['label'].num_classes
data_files = { "train": "train.csv", "test": "test.csv" }
sentences = load_dataset("loretoparisi/tatoeba-sentences",
data_files=data_files,
delimiter='\t',
column_names=['label', 'text'],
features = features
```
ERROR:
```
ClassLabel(num_classes=403, names=['cmn', 'deu', 'rus', 'fra', 'eng', 'jpn', 'spa', 'ita', 'kor', 'vie', 'nld', 'epo', 'por', 'tur', 'heb', 'hun', 'ell', 'ind', 'ara', 'arz', 'fin', 'bul', 'yue', 'swe', 'ukr', 'bel', 'que', 'ces', 'swh', 'nno', 'wuu', 'nob', 'zsm', 'est', 'kat', 'pol', 'lat', 'urd', 'sqi', 'isl', 'fry', 'afr', 'ron', 'fao', 'san', 'bre', 'tat', 'yid', 'uig', 'uzb', 'srp', 'qya', 'dan', 'pes', 'slk', 'eus', 'cycl', 'acm', 'tgl', 'lvs', 'kaz', 'hye', 'hin', 'lit', 'ben', 'cat', 'bos', 'hrv', 'tha', 'orv', 'cha', 'mon', 'lzh', 'scn', 'gle', 'mkd', 'slv', 'frm', 'glg', 'vol', 'ain', 'jbo', 'tok', 'ina', 'nds', 'mal', 'tlh', 'roh', 'ltz', 'oss', 'ido', 'gla', 'mlt', 'sco', 'ast', 'jav', 'oci', 'ile', 'ota', 'xal', 'tel', 'sjn', 'nov', 'khm', 'tpi', 'ang', 'aze', 'tgk', 'tuk', 'chv', 'hsb', 'dsb', 'bod', 'sme', 'cym', 'mri', 'ksh', 'kmr', 'ewe', 'kab', 'ber', 'tpw', 'udm', 'lld', 'pms', 'lad', 'grn', 'mlg', 'xho', 'pnb', 'grc', 'hat', 'lao', 'npi', 'cor', 'nah', 'avk', 'mar', 'guj', 'pan', 'kir', 'myv', 'prg', 'sux', 'crs', 'ckt', 'bak', 'zlm', 'hil', 'cbk', 'chr', 'nav', 'lkt', 'enm', 'arq', 'lin', 'abk', 'pcd', 'rom', 'gsw', 'tam', 'zul', 'awa', 'wln', 'amh', 'bar', 'hbo', 'mhr', 'bho', 'mrj', 'ckb', 'osx', 'pfl', 'mgm', 'sna', 'mah', 'hau', 'kan', 'nog', 'sin', 'glv', 'dng', 'kal', 'liv', 'vro', 'apc', 'jdt', 'fur', 'che', 'haw', 'yor', 'crh', 'pdc', 'ppl', 'kin', 'shs', 'mnw', 'tet', 'sah', 'kum', 'ngt', 'nya', 'pus', 'hif', 'mya', 'moh', 'wol', 'tir', 'ton', 'lzz', 'oar', 'lug', 'brx', 'non', 'mww', 'hak', 'nlv', 'ngu', 'bua', 'aym', 'vec', 'ibo', 'tkl', 'bam', 'kha', 'ceb', 'lou', 'fuc', 'smo', 'gag', 'lfn', 'arg', 'umb', 'tyv', 'kjh', 'oji', 'cyo', 'urh', 'kzj', 'pam', 'srd', 'lmo', 'swg', 'mdf', 'gil', 'snd', 'tso', 'sot', 'zza', 'tsn', 'pau', 'som', 'egl', 'ady', 'asm', 'ori', 'dtp', 'cho', 'max', 'kam', 'niu', 'sag', 'ilo', 'kaa', 'fuv', 'nch', 'hoc', 'iba', 'gbm', 'sun', 'war', 'mvv', 'pap', 'ary', 'kxi', 'csb', 'pag', 'cos', 'rif', 'kek', 'krc', 'aii', 'ban', 'ssw', 'tvl', 'mfe', 'tah', 'bvy', 'bcl', 'hnj', 'nau', 'nst', 'afb', 'quc', 'min', 'tmw', 'mad', 'bjn', 'mai', 'cjy', 'got', 'hsn', 'gan', 'tzl', 'dws', 'ldn', 'afh', 'sgs', 'krl', 'vep', 'rue', 'tly', 'mic', 'ext', 'izh', 'sma', 'jam', 'cmo', 'mwl', 'kpv', 'koi', 'bis', 'ike', 'run', 'evn', 'ryu', 'mnc', 'aoz', 'otk', 'kas', 'aln', 'akl', 'yua', 'shy', 'fkv', 'gos', 'fij', 'thv', 'zgh', 'gcf', 'cay', 'xmf', 'tig', 'div', 'lij', 'rap', 'hrx', 'cpi', 'tts', 'gaa', 'tmr', 'iii', 'ltg', 'bzt', 'syc', 'emx', 'gom', 'chg', 'osp', 'stq', 'frr', 'fro', 'nys', 'toi', 'new', 'phn', 'jpa', 'rel', 'drt', 'chn', 'pli', 'laa', 'bal', 'hdn', 'hax', 'mik', 'ajp', 'xqa', 'pal', 'crk', 'mni', 'lut', 'ayl', 'ood', 'sdh', 'ofs', 'nus', 'kiu', 'diq', 'qxq', 'alt', 'bfz', 'klj', 'mus', 'srn', 'guc', 'lim', 'zea', 'shi', 'mnr', 'bom', 'sat', 'szl'], id=None)
Value(dtype='string', id=None)
Using custom data configuration loretoparisi--tatoeba-sentences-7b2c5e991f398f39
Downloading and preparing dataset csv/loretoparisi--tatoeba-sentences to /root/.cache/huggingface/datasets/csv/loretoparisi--tatoeba-sentences-7b2c5e991f398f39/0.0.0/433e0ccc46f9880962cc2b12065189766fbb2bee57a221866138fb9203c83519...
Downloading data files: 100%
2/2 [00:18<00:00, 8.06s/it]
Downloading data: 100%
391M/391M [00:13<00:00, 35.3MB/s]
Downloading data: 100%
92.4M/92.4M [00:02<00:00, 36.5MB/s]
Failed to read file '/root/.cache/huggingface/datasets/downloads/933132df9905194ea9faeb30cabca8c49318795612f6495fcb941a290191dd5d' with error <class 'ValueError'>: invalid literal for int() with base 10: 'cmn'
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
/usr/local/lib/python3.7/dist-packages/pandas/_libs/parsers.pyx in pandas._libs.parsers.TextReader._convert_tokens()
TypeError: Cannot cast array data from dtype('O') to dtype('int64') according to the rule 'safe'
During handling of the above exception, another exception occurred:
ValueError Traceback (most recent call last)
15 frames
/usr/local/lib/python3.7/dist-packages/pandas/_libs/parsers.pyx in pandas._libs.parsers.TextReader._convert_tokens()
ValueError: invalid literal for int() with base 10: 'cmn'
```
while loading without `features` it loads without errors
```
sentences = load_dataset("loretoparisi/tatoeba-sentences",
data_files=data_files,
delimiter='\t',
column_names=['label', 'text']
)
```
but the `label` col seems to be wrong (without the `ClassLabel` object):
```
sentences['train'].features
{'label': Value(dtype='string', id=None),
'text': Value(dtype='string', id=None)}
```
The dataset was https://huggingface.co/datasets/loretoparisi/tatoeba-sentences
Dataset format is:
```
ces Nechci vědět, co je tam uvnitř.
ces Kdo o tom chce slyšet?
deu Tom sagte, er fühle sich nicht wohl.
ber Mel-iyi-d anida-t tura ?
hun Gondom lesz rá rögtön.
ber Mel-iyi-d anida-tt tura ?
deu Ich will dich nicht reden hören.
```
### Expected behavior
```shell
correctly load train and test files.
``` | {
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} | https://api.github.com/repos/huggingface/datasets/issues/4210/timeline | null | completed | null | null | false | [
"Hi! Casting class labels from strings is currently not supported in the CSV loader, but you can get the same result with an additional map as follows:\r\n```python\r\nfrom datasets import load_dataset,Features,Value,ClassLabel\r\nclass_names = [\"cmn\",\"deu\",\"rus\",\"fra\",\"eng\",\"jpn\",\"spa\",\"ita\",\"kor\... |
https://api.github.com/repos/huggingface/datasets/issues/5391 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5391/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5391/comments | https://api.github.com/repos/huggingface/datasets/issues/5391/events | https://github.com/huggingface/datasets/issues/5391 | 1,510,350,400 | I_kwDODunzps5aBh5A | 5,391 | Whisper Event - RuntimeError: The size of tensor a (504) must match the size of tensor b (448) at non-singleton dimension 1 100% 1000/1000 [2:52:21<00:00, 10.34s/it] | [] | closed | false | null | 2 | 2022-12-25T15:17:14Z | 2023-07-21T14:29:47Z | 2023-07-21T14:29:47Z | null | Done in a VM with a GPU (Ubuntu) following the [Whisper Event - PYTHON](https://github.com/huggingface/community-events/tree/main/whisper-fine-tuning-event#python-script) instructions.
Attempted using [RuntimeError: he size of tensor a (504) must match the size of tensor b (448) at non-singleton dimension 1 100% 1000/1000 - WEB](https://discuss.huggingface.co/t/trainer-runtimeerror-the-size-of-tensor-a-462-must-match-the-size-of-tensor-b-448-at-non-singleton-dimension-1/26010/10 ) - another person experiencing the same issue. But could not resolve the issue with the google/fleurs data. __Not clear what can be modified in the PY code to resolve the input data size mismatch, as the training data is already very small__.
Tried posting on Discord, @sanchit-gandhi and @vaibhavs10. Was hoping that the event is over and some input/help is now available. [Hugging Face - whisper-small-amet](https://huggingface.co/drmeeseeks/whisper-small-amet).
The paper [Robust Speech Recognition via Large-Scale Weak Supervision](https://arxiv.org/abs/2212.04356) am_et is a low resource language (Table E), with the WER results ranging from 120-229, based on model size. (Whisper small WER=120.2).
# ---> Initial Training Output
/usr/local/lib/python3.8/dist-packages/transformers/optimization.py:306: FutureWarning: This implementation of AdamW is deprecated and will be removed in a future version. Use the PyTorch implementation torch.optim.AdamW instead, or set `no_deprecation_warning=True` to disable this warning
warnings.warn(
[INFO|trainer.py:1641] 2022-12-18 05:23:28,799 >> ***** Running training *****
[INFO|trainer.py:1642] 2022-12-18 05:23:28,799 >> Num examples = 446
[INFO|trainer.py:1643] 2022-12-18 05:23:28,799 >> Num Epochs = 72
[INFO|trainer.py:1644] 2022-12-18 05:23:28,799 >> Instantaneous batch size per device = 16
[INFO|trainer.py:1645] 2022-12-18 05:23:28,799 >> Total train batch size (w. parallel, distributed & accumulation) = 32
[INFO|trainer.py:1646] 2022-12-18 05:23:28,799 >> Gradient Accumulation steps = 2
[INFO|trainer.py:1647] 2022-12-18 05:23:28,800 >> Total optimization steps = 1000
[INFO|trainer.py:1648] 2022-12-18 05:23:28,801 >> Number of trainable parameters = 241734912
# ---> Error
14% 9/65 [07:07<48:34, 52.04s/it][INFO|configuration_utils.py:523] 2022-12-18 05:03:07,941 >> Generate config GenerationConfig {
"begin_suppress_tokens": [
220,
50257
],
"bos_token_id": 50257,
"decoder_start_token_id": 50258,
"eos_token_id": 50257,
"max_length": 448,
"pad_token_id": 50257,
"transformers_version": "4.26.0.dev0",
"use_cache": false
}
Traceback (most recent call last):
File "run_speech_recognition_seq2seq_streaming.py", line 629, in <module>
main()
File "run_speech_recognition_seq2seq_streaming.py", line 578, in main
train_result = trainer.train(resume_from_checkpoint=checkpoint)
File "/usr/local/lib/python3.8/dist-packages/transformers/trainer.py", line 1534, in train
return inner_training_loop(
File "/usr/local/lib/python3.8/dist-packages/transformers/trainer.py", line 1859, in _inner_training_loop
self._maybe_log_save_evaluate(tr_loss, model, trial, epoch, ignore_keys_for_eval)
File "/usr/local/lib/python3.8/dist-packages/transformers/trainer.py", line 2122, in _maybe_log_save_evaluate
metrics = self.evaluate(ignore_keys=ignore_keys_for_eval)
File "/usr/local/lib/python3.8/dist-packages/transformers/trainer_seq2seq.py", line 78, in evaluate
return super().evaluate(eval_dataset, ignore_keys=ignore_keys, metric_key_prefix=metric_key_prefix)
File "/usr/local/lib/python3.8/dist-packages/transformers/trainer.py", line 2818, in evaluate
output = eval_loop(
File "/usr/local/lib/python3.8/dist-packages/transformers/trainer.py", line 3000, in evaluation_loop
loss, logits, labels = self.prediction_step(model, inputs, prediction_loss_only, ignore_keys=ignore_keys)
File "/usr/local/lib/python3.8/dist-packages/transformers/trainer_seq2seq.py", line 213, in prediction_step
outputs = model(**inputs)
File "/usr/local/lib/python3.8/dist-packages/torch/nn/modules/module.py", line 1190, in _call_impl
return forward_call(*input, **kwargs)
File "/usr/local/lib/python3.8/dist-packages/transformers/models/whisper/modeling_whisper.py", line 1197, in forward
outputs = self.model(
File "/usr/local/lib/python3.8/dist-packages/torch/nn/modules/module.py", line 1190, in _call_impl
return forward_call(*input, **kwargs)
File "/usr/local/lib/python3.8/dist-packages/transformers/models/whisper/modeling_whisper.py", line 1066, in forward
decoder_outputs = self.decoder(
File "/usr/local/lib/python3.8/dist-packages/torch/nn/modules/module.py", line 1190, in _call_impl
return forward_call(*input, **kwargs)
File "/usr/local/lib/python3.8/dist-packages/transformers/models/whisper/modeling_whisper.py", line 873, in forward
hidden_states = inputs_embeds + positions
RuntimeError: The size of tensor a (504) must match the size of tensor b (448) at non-singleton dimension 1
100% 1000/1000 [2:52:21<00:00, 10.34s/it]
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} | https://api.github.com/repos/huggingface/datasets/issues/5391/timeline | null | completed | null | null | false | [
"Hey @catswithbats! Super sorry for the late reply! This is happening because there is data with label length (504) that exceeds the model's max length (448). \r\n\r\nThere are two options here:\r\n1. Increase the model's `max_length` parameter: \r\n```python\r\nmodel.config.max_length = 512\r\n```\r\n2. Filter dat... |
https://api.github.com/repos/huggingface/datasets/issues/6069 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6069/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6069/comments | https://api.github.com/repos/huggingface/datasets/issues/6069/events | https://github.com/huggingface/datasets/issues/6069 | 1,820,831,535 | I_kwDODunzps5sh68v | 6,069 | KeyError: dataset has no key "image" | [] | closed | false | null | 6 | 2023-07-25T17:45:50Z | 2023-07-27T12:42:17Z | 2023-07-27T12:42:17Z | null | ### Describe the bug
I've loaded a local image dataset with:
`ds = laod_dataset("imagefolder", data_dir=path-to-data)`
And defined a transform to process the data, following the Datasets docs.
However, I get a keyError error, indicating there's no "image" key in my dataset. When I printed out the example_batch sent to the transformation function, it shows only the labels are being sent to the function.
For some reason, the images are not in the example batches.
### Steps to reproduce the bug
I'm using the latest stable version of datasets
### Expected behavior
I expect the example_batches to contain both images and labels
### Environment info
I'm using the latest stable version of datasets | {
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"You can list the dataset's columns with `ds.column_names` before `.map` to check whether the dataset has an `image` column. If it doesn't, then this is a bug. Otherwise, please paste the line with the `.map` call.\r\n\r\n\r\n",
"This is the piece of code I am running:\r\n```\r\ndata_transforms = utils.get_data_a... |
https://api.github.com/repos/huggingface/datasets/issues/2581 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2581/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2581/comments | https://api.github.com/repos/huggingface/datasets/issues/2581/events | https://github.com/huggingface/datasets/pull/2581 | 935,783,588 | MDExOlB1bGxSZXF1ZXN0NjgyNjQwMDY4 | 2,581 | Faster search_batch for ElasticsearchIndex due to threading | [] | closed | false | {
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} | 0 | 2021-07-02T13:42:07Z | 2021-07-12T14:13:46Z | 2021-07-12T09:52:51Z | null | Hey,
I think it makes sense to perform search_batch threaded, so ES can perform search in parallel.
Cheers! | {
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https://api.github.com/repos/huggingface/datasets/issues/1452 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1452/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1452/comments | https://api.github.com/repos/huggingface/datasets/issues/1452/events | https://github.com/huggingface/datasets/issues/1452 | 761,104,924 | MDU6SXNzdWU3NjExMDQ5MjQ= | 1,452 | SNLI dataset contains labels with value -1 | [] | closed | false | null | 2 | 2020-12-10T10:16:55Z | 2020-12-10T17:49:55Z | 2020-12-10T17:49:55Z | null | ```
import datasets
nli_data = datasets.load_dataset("snli")
train_data = nli_data['train']
train_labels = train_data['label']
label_set = set(train_labels)
print(label_set)
```
**Output:**
`{0, 1, 2, -1}` | {
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} | https://api.github.com/repos/huggingface/datasets/issues/1452/timeline | null | completed | null | null | false | [
"I believe the `-1` label is used for missing/NULL data as per HuggingFace Dataset conventions. If I recall correctly SNLI has some entries with no (gold) labels in the dataset.",
"Ah, you're right. The dataset has some pairs with missing labels. Thanks for reminding me."
] |
https://api.github.com/repos/huggingface/datasets/issues/2328 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2328/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2328/comments | https://api.github.com/repos/huggingface/datasets/issues/2328/events | https://github.com/huggingface/datasets/pull/2328 | 877,673,896 | MDExOlB1bGxSZXF1ZXN0NjMxNTg2MzU2 | 2,328 | Add Matthews/Pearson/Spearman correlation metrics | [] | closed | false | null | 0 | 2021-05-06T16:09:27Z | 2021-05-06T16:58:10Z | 2021-05-06T16:58:10Z | null | Added three metrics:
- The Matthews correlation coefficient (from sklearn)
- The Pearson correlation coefficient (from scipy)
- The Spearman correlation coefficient (from scipy)
cc @sgugger | {
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} | https://api.github.com/repos/huggingface/datasets/issues/2328/timeline | null | null | false | {
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"url": "https://api.github.com/repos/huggingface/datasets/pulls/2328"
} | true | [] |
https://api.github.com/repos/huggingface/datasets/issues/3865 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3865/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3865/comments | https://api.github.com/repos/huggingface/datasets/issues/3865/events | https://github.com/huggingface/datasets/pull/3865 | 1,162,821,908 | PR_kwDODunzps40HT9K | 3,865 | Add logo img | [] | closed | false | null | 2 | 2022-03-08T15:50:59Z | 2022-03-08T16:01:59Z | 2022-03-08T16:01:59Z | null | null | {
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} | https://api.github.com/repos/huggingface/datasets/issues/3865/timeline | null | null | false | {
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} | true | [
"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3865). All of your documentation changes will be reflected on that endpoint.",
"Superceded by https://github.com/huggingface/datasets/pull/3866"
] |
https://api.github.com/repos/huggingface/datasets/issues/5149 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5149/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5149/comments | https://api.github.com/repos/huggingface/datasets/issues/5149/events | https://github.com/huggingface/datasets/pull/5149 | 1,420,415,639 | PR_kwDODunzps5BZJab | 5,149 | Make iter_files deterministic | [] | closed | false | null | 1 | 2022-10-24T08:16:27Z | 2022-10-27T09:53:23Z | 2022-10-27T09:51:09Z | null | Fix #5145. | {
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} | https://api.github.com/repos/huggingface/datasets/issues/5149/timeline | null | null | false | {
"diff_url": "https://github.com/huggingface/datasets/pull/5149.diff",
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"url": "https://api.github.com/repos/huggingface/datasets/pulls/5149"
} | true | [
"_The documentation is not available anymore as the PR was closed or merged._"
] |
https://api.github.com/repos/huggingface/datasets/issues/4976 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4976/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4976/comments | https://api.github.com/repos/huggingface/datasets/issues/4976/events | https://github.com/huggingface/datasets/issues/4976 | 1,372,322,382 | I_kwDODunzps5Ry_pO | 4,976 | Hope to adapt Python3.9 as soon as possible | [
{
"color": "a2eeef",
"default": true,
"description": "New feature or request",
"id": 1935892871,
"name": "enhancement",
"node_id": "MDU6TGFiZWwxOTM1ODkyODcx",
"url": "https://api.github.com/repos/huggingface/datasets/labels/enhancement"
}
] | open | false | null | 3 | 2022-09-14T04:42:22Z | 2022-09-26T16:32:35Z | null | null | **Is your feature request related to a problem? Please describe.**
A clear and concise description of what the problem is.
**Describe the solution you'd like**
A clear and concise description of what you want to happen.
**Describe alternatives you've considered**
A clear and concise description of any alternative solutions or features you've considered.
**Additional context**
Add any other context about the feature request here.
| {
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} | https://api.github.com/repos/huggingface/datasets/issues/4976/timeline | null | null | null | null | false | [
"Hi! `datasets` should work in Python 3.9. What kind of issue have you encountered?",
"There is this related issue already: https://github.com/huggingface/datasets/issues/4113\r\nAnd I guess we need a CI job for 3.9 ^^",
"Perhaps we should report this issue in the `filelock` repo?"
] |
https://api.github.com/repos/huggingface/datasets/issues/507 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/507/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/507/comments | https://api.github.com/repos/huggingface/datasets/issues/507/events | https://github.com/huggingface/datasets/issues/507 | 679,400,683 | MDU6SXNzdWU2Nzk0MDA2ODM= | 507 | Errors when I use | [] | closed | false | null | 1 | 2020-08-14T21:03:57Z | 2020-08-14T21:39:10Z | 2020-08-14T21:39:10Z | null | I tried the following example code from https://huggingface.co/deepset/roberta-base-squad2 and got errors
I am using **transformers 3.0.2** code .
from transformers.pipelines import pipeline
from transformers.modeling_auto import AutoModelForQuestionAnswering
from transformers.tokenization_auto import AutoTokenizer
model_name = "deepset/roberta-base-squad2"
nlp = pipeline('question-answering', model=model_name, tokenizer=model_name)
QA_input = {
'question': 'Why is model conversion important?',
'context': 'The option to convert models between FARM and transformers gives freedom to the user and let people easily switch between frameworks.'
}
res = nlp(QA_input)
The errors are :
res = nlp(QA_input)
File ".local/lib/python3.6/site-packages/transformers/pipelines.py", line 1316, in __call__
for s, e, score in zip(starts, ends, scores)
File ".local/lib/python3.6/site-packages/transformers/pipelines.py", line 1316, in <listcomp>
for s, e, score in zip(starts, ends, scores)
KeyError: 0
| {
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} | https://api.github.com/repos/huggingface/datasets/issues/507/timeline | null | completed | null | null | false | [
"Looks like an issue with 3.0.2 transformers version. Works fine when I use \"master\" version of transformers."
] |
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