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2025-08-05 09:28:51
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2025-08-05 11:39:56
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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1,058,718,957
|
https://api.github.com/repos/huggingface/datasets/issues/3301
|
https://github.com/huggingface/datasets/pull/3301
| 3,301
|
Add wikipedia tags
|
closed
| 0
| 2021-11-19T16:39:25
| 2021-11-19T16:49:30
| 2021-11-19T16:49:29
|
lhoestq
|
[] |
Add the missing tags to the wikipedia dataset card.
I also added the missing languages code in our language codes list.
This should also fix the code snippet that is presented on the Hub to load the dataset: fix https://github.com/huggingface/datasets/issues/3292
| true
|
1,058,644,459
|
https://api.github.com/repos/huggingface/datasets/issues/3300
|
https://github.com/huggingface/datasets/issues/3300
| 3,300
|
❓ Dataset loading script from Hugging Face Hub
|
closed
| 8
| 2021-11-19T15:20:52
| 2021-12-22T10:57:56
| 2021-12-22T10:57:56
|
pietrolesci
|
[
"dataset request",
"dataset-viewer"
] |
Hi there,
I am trying to add my custom `ag_news` with its own loading script on the Hugging Face datasets hub. In particular, I would like to test the addition of a second configuration to the existing `ag_news` dataset. Once it works in my hub, I plan to make a PR to the original dataset. However, in trying to do so I have encountered certain problems as detailed below.
Issues I have encountered:
- Without a loading script, the train and test files are loaded together into a unique `dataset.Dataset` -> so I wrote a loading script. Also, I need a loading script otherwise I cannot specify multiple configurations
- Once my loading script is working locally, I do not manage to make it work on the hub. In particular, I would like to be able to load the dataset like this
```python
load_dataset("pietrolesci/ag_news", name="my_configuration")
```
Apparently, the `load_dataset` is able to pick up the loading script from the hub and run it. However, it errors because it is unable to find the files. The structure of my hub repo is the following
```
ag_news.py
train.csv
test.csv
```
and the loading script I specify `data_dir=Path(__file__).parent` and `data_files=DataFilesDict({"train": "train.csv", "test": "test.csv"})`. In the documentation I could not find info regarding loading a dataset from the hub using a loading script present on the hub.
Any suggestion is very much appreciated.
Best,
Pietro
Link to the hub repo: https://huggingface.co/datasets/pietrolesci/ag_news
BONUS: how can I make the data viewer work in this specific case? :)
| false
|
1,058,518,213
|
https://api.github.com/repos/huggingface/datasets/issues/3299
|
https://github.com/huggingface/datasets/issues/3299
| 3,299
|
Add option to find unique elements in nested sequences when calling `Dataset.unique`
|
open
| 4
| 2021-11-19T13:16:06
| 2023-05-19T14:45:40
| null |
mariosasko
|
[
"enhancement"
] |
It would be nice to have an option to flatten nested sequences to find unique elements stored in them when calling `Dataset.unique`. ~~Currently, `Dataset.unique` only supports finding unique sequences and not unique elements in that situation.~~
| false
|
1,058,420,201
|
https://api.github.com/repos/huggingface/datasets/issues/3298
|
https://github.com/huggingface/datasets/issues/3298
| 3,298
|
Agnews dataset viewer is not working
|
closed
| 3
| 2021-11-19T11:18:59
| 2021-12-21T16:24:05
| 2021-12-21T16:24:05
|
pietrolesci
|
[
"dataset-viewer"
] |
## Dataset viewer issue for '*name of the dataset*'
**Link:** https://huggingface.co/datasets/ag_news
Hi there, the `ag_news` dataset viewer is not working.
Am I the one who added this dataset? No
| false
|
1,058,263,859
|
https://api.github.com/repos/huggingface/datasets/issues/3297
|
https://github.com/huggingface/datasets/issues/3297
| 3,297
|
.map() cache is wrongfully reused - only happens when the mapping function is imported
|
open
| 5
| 2021-11-19T08:18:36
| 2025-07-31T16:29:29
| null |
eladsegal
|
[
"bug"
] |
## Describe the bug
When `.map` is used with a mapping function that is imported, the cache is reused even if the mapping function has been modified.
The reason for this is that `dill` that is used for creating the fingerprint [pickles imported functions by reference](https://stackoverflow.com/a/67851411).
I guess it is not a widespread case, but it can still lead to unwanted results unnoticeably.
## Steps to reproduce the bug
Create files `a.py` and `b.py`:
```python
# a.py
from datasets import load_dataset
def main():
squad = load_dataset("squad")
squad.map(mapping_func, batched=True)
def mapping_func(examples):
ID_LENGTH = 4
examples["id"] = [id_[:ID_LENGTH] for id_ in examples["id"]]
return examples
if __name__ == "__main__":
main()
```
```python
# b.py
from datasets import load_dataset
from a import mapping_func
def main():
squad = load_dataset("squad")
squad.map(mapping_func, batched=True)
if __name__ == "__main__":
main()
```
Run `python b.py` twice: In the first run you will see tqdm bars showing that the data is processed, and in the second run you will see "Loading cached processed dataset at...".
Now change `ID_LENGTH` to another number in order to change the mapping function, and run `python b.py` again. You'll see that `.map` loads from the cache the result of the previous mapping function.
## Expected results
Run `python a.py` twice: In the first run you will see tqdm bars showing that the data is processed, and in the second run you will see "Loading cached processed dataset at...".
Now change `ID_LENGTH` to another number in order to change the mapping function, and run `python a.py` again. You'll see that the dataset is being processed and that there's no reuse of the previous mapping function result.
## Workaround
Put the mapping function inside a dummy class as a static method:
```python
# a.py
class MappingFuncClass:
@staticmethod
def mapping_func(examples):
ID_LENGTH = 4
examples["id"] = [id_[:ID_LENGTH] for id_ in examples["id"]]
return examples
```
```python
# b.py
from datasets import load_dataset
from a import MappingFuncClass
def main():
squad = load_dataset("squad")
squad.map(MappingFuncClass.mapping_func, batched=True)
if __name__ == "__main__":
main()
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.15.1
- Platform: Linux-4.4.0-19041-Microsoft-x86_64-with-glibc2.17
- Python version: 3.8.10
- PyArrow version: 4.0.1
| false
|
1,057,970,638
|
https://api.github.com/repos/huggingface/datasets/issues/3296
|
https://github.com/huggingface/datasets/pull/3296
| 3,296
|
Fix temporary dataset_path creation for URIs related to remote fs
|
closed
| 2
| 2021-11-18T23:32:45
| 2021-12-06T10:45:04
| 2021-12-06T10:45:04
|
francisco-perez-sorrosal
|
[] |
This aims to close #3295
| true
|
1,057,954,892
|
https://api.github.com/repos/huggingface/datasets/issues/3295
|
https://github.com/huggingface/datasets/issues/3295
| 3,295
|
Temporary dataset_path for remote fs URIs not built properly in arrow_dataset.py::load_from_disk
|
closed
| 1
| 2021-11-18T23:24:02
| 2021-12-06T10:45:04
| 2021-12-06T10:45:04
|
francisco-perez-sorrosal
|
[
"bug"
] |
## Describe the bug
When trying to build a temporary dataset path from a remote URI in this block of code:
https://github.com/huggingface/datasets/blob/42f6b1d18a4a1b6009b6e62d115491be16dfca22/src/datasets/arrow_dataset.py#L1038-L1042
the result is not the expected when passing an absolute path in an URI like `hdfs:///absolute/path`.
## Steps to reproduce the bug
```python
dataset_path = "hdfs:///absolute/path"
src_dataset_path = extract_path_from_uri(dataset_path)
tmp_dir = get_temporary_cache_files_directory()
dataset_path = Path(tmp_dir, src_dataset_path)
print(dataset_path)
```
## Expected results
With the code above, we would expect a value in `dataset_path` similar to:
`/tmp/tmpnwxyvao5/absolute/path`
## Actual results
However, we get a `dataset_path` value like:
`/absolute/path`
This is because this line here: https://github.com/huggingface/datasets/blob/42f6b1d18a4a1b6009b6e62d115491be16dfca22/src/datasets/arrow_dataset.py#L1041
returns the last absolute path when two absolute paths (the one in `tmp_dir` and the one extracted from the URI in `src_dataset_path`) are passed as arguments.
## Environment info
- `datasets` version: 1.13.3
- Platform: Linux-3.10.0-1160.15.2.el7.x86_64-x86_64-with-glibc2.33
- Python version: 3.9.7
- PyArrow version: 5.0.0
| false
|
1,057,495,473
|
https://api.github.com/repos/huggingface/datasets/issues/3294
|
https://github.com/huggingface/datasets/issues/3294
| 3,294
|
Add Natural Adversarial Objects dataset
|
open
| 0
| 2021-11-18T15:34:44
| 2021-12-08T12:00:02
| null |
osanseviero
|
[
"dataset request",
"vision"
] |
## Adding a Dataset
- **Name:** Natural Adversarial Objects (NAO)
- **Description:** Natural Adversarial Objects (NAO) is a new dataset to evaluate the robustness of object detection models. NAO contains 7,934 images and 9,943 objects that are unmodified and representative of real-world scenarios, but cause state-of-the-art detection models to misclassify with high confidence.
- **Paper:** https://arxiv.org/abs/2111.04204v1
- **Data:** https://drive.google.com/drive/folders/15P8sOWoJku6SSEiHLEts86ORfytGezi8
- **Motivation:** interesting object detection dataset useful for miscclassifications
cc @NielsRogge
Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
| false
|
1,057,004,431
|
https://api.github.com/repos/huggingface/datasets/issues/3293
|
https://github.com/huggingface/datasets/pull/3293
| 3,293
|
Pin version exclusion for Markdown
|
closed
| 0
| 2021-11-18T06:56:01
| 2021-11-18T10:28:05
| 2021-11-18T10:28:04
|
albertvillanova
|
[] |
As Markdown version 3.3.5 has a bug, it is better to exclude it in case the users have it previously installed in their environment.
Related to #3289, #3286.
| true
|
1,056,962,554
|
https://api.github.com/repos/huggingface/datasets/issues/3292
|
https://github.com/huggingface/datasets/issues/3292
| 3,292
|
Not able to load 'wikipedia' dataset
|
closed
| 1
| 2021-11-18T05:41:18
| 2021-11-19T16:49:29
| 2021-11-19T16:49:29
|
abhibisht89
|
[
"bug"
] |
## Describe the bug
I am following the instruction for loading the wikipedia dataset using datasets. However getting the below error.
## Steps to reproduce the bug
from datasets import load_dataset
dataset = load_dataset("wikipedia")
```
## Expected results
A clear and concise description of the expected results.
## Actual results
~/anaconda3/envs/pytorch_p36/lib/python3.6/site-packages/datasets/builder.py in _create_builder_config(self, name, custom_features, **config_kwargs)
339 "Config name is missing."
340 "\nPlease pick one among the available configs: %s" % list(self.builder_configs.keys())
--> 341 + "\nExample of usage:\n\t`{}`".format(example_of_usage)
342 )
343 builder_config = self.BUILDER_CONFIGS[0]
ValueError: Config name is missing.
Please pick one among the available configs: ['20200501.aa', '20200501.ab', '20200501.ace', '20200501.ady', '20200501.af', '20200501.ak', '20200501.als', '20200501.am', '20200501.an', '20200501.ang', '20200501.ar', '20200501.arc', '20200501.arz', '20200501.as', '20200501.ast', '20200501.atj', '20200501.av', '20200501.ay', '20200501.az', '20200501.azb', '20200501.ba', '20200501.bar', '20200501.bat-smg', '20200501.bcl', '20200501.be', '20200501.be-x-old', '20200501.bg', '20200501.bh', '20200501.bi', '20200501.bjn', '20200501.bm', '20200501.bn', '20200501.bo', '20200501.bpy', '20200501.br', '20200501.bs', '20200501.bug', '20200501.bxr', '20200501.ca', '20200501.cbk-zam', '20200501.cdo', '20200501.ce', '20200501.ceb', '20200501.ch', '20200501.cho', '20200501.chr', '20200501.chy', '20200501.ckb', '20200501.co', '20200501.cr', '20200501.crh', '20200501.cs', '20200501.csb', '20200501.cu', '20200501.cv', '20200501.cy', '20200501.da', '20200501.de', '20200501.din', '20200501.diq', '20200501.dsb', '20200501.dty', '20200501.dv', '20200501.dz', '20200501.ee', '20200501.el', '20200501.eml', '20200501.en', '20200501.eo', '20200501.es', '20200501.et', '20200501.eu', '20200501.ext', '20200501.fa', '20200501.ff', '20200501.fi', '20200501.fiu-vro', '20200501.fj', '20200501.fo', '20200501.fr', '20200501.frp', '20200501.frr', '20200501.fur', '20200501.fy', '20200501.ga', '20200501.gag', '20200501.gan', '20200501.gd', '20200501.gl', '20200501.glk', '20200501.gn', '20200501.gom', '20200501.gor', '20200501.got', '20200501.gu', '20200501.gv', '20200501.ha', '20200501.hak', '20200501.haw', '20200501.he', '20200501.hi', '20200501.hif', '20200501.ho', '20200501.hr', '20200501.hsb', '20200501.ht', '20200501.hu', '20200501.hy', '20200501.ia', '20200501.id', '20200501.ie', '20200501.ig', '20200501.ii', '20200501.ik', '20200501.ilo', '20200501.inh', '20200501.io', '20200501.is', '20200501.it', '20200501.iu', '20200501.ja', '20200501.jam', '20200501.jbo', '20200501.jv', '20200501.ka', '20200501.kaa', '20200501.kab', '20200501.kbd', '20200501.kbp', '20200501.kg', '20200501.ki', '20200501.kj', '20200501.kk', '20200501.kl', '20200501.km', '20200501.kn', '20200501.ko', '20200501.koi', '20200501.krc', '20200501.ks', '20200501.ksh', '20200501.ku', '20200501.kv', '20200501.kw', '20200501.ky', '20200501.la', '20200501.lad', '20200501.lb', '20200501.lbe', '20200501.lez', '20200501.lfn', '20200501.lg', '20200501.li', '20200501.lij', '20200501.lmo', '20200501.ln', '20200501.lo', '20200501.lrc', '20200501.lt', '20200501.ltg', '20200501.lv', '20200501.mai', '20200501.map-bms', '20200501.mdf', '20200501.mg', '20200501.mh', '20200501.mhr', '20200501.mi', '20200501.min', '20200501.mk', '20200501.ml', '20200501.mn', '20200501.mr', '20200501.mrj', '20200501.ms', '20200501.mt', '20200501.mus', '20200501.mwl', '20200501.my', '20200501.myv', '20200501.mzn', '20200501.na', '20200501.nah', '20200501.nap', '20200501.nds', '20200501.nds-nl', '20200501.ne', '20200501.new', '20200501.ng', '20200501.nl', '20200501.nn', '20200501.no', '20200501.nov', '20200501.nrm', '20200501.nso', '20200501.nv', '20200501.ny', '20200501.oc', '20200501.olo', '20200501.om', '20200501.or', '20200501.os', '20200501.pa', '20200501.pag', '20200501.pam', '20200501.pap', '20200501.pcd', '20200501.pdc', '20200501.pfl', '20200501.pi', '20200501.pih', '20200501.pl', '20200501.pms', '20200501.pnb', '20200501.pnt', '20200501.ps', '20200501.pt', '20200501.qu', '20200501.rm', '20200501.rmy', '20200501.rn', '20200501.ro', '20200501.roa-rup', '20200501.roa-tara', '20200501.ru', '20200501.rue', '20200501.rw', '20200501.sa', '20200501.sah', '20200501.sat', '20200501.sc', '20200501.scn', '20200501.sco', '20200501.sd', '20200501.se', '20200501.sg', '20200501.sh', '20200501.si', '20200501.simple', '20200501.sk', '20200501.sl', '20200501.sm', '20200501.sn', '20200501.so', '20200501.sq', '20200501.sr', '20200501.srn', '20200501.ss', '20200501.st', '20200501.stq', '20200501.su', '20200501.sv', '20200501.sw', '20200501.szl', '20200501.ta', '20200501.tcy', '20200501.te', '20200501.tet', '20200501.tg', '20200501.th', '20200501.ti', '20200501.tk', '20200501.tl', '20200501.tn', '20200501.to', '20200501.tpi', '20200501.tr', '20200501.ts', '20200501.tt', '20200501.tum', '20200501.tw', '20200501.ty', '20200501.tyv', '20200501.udm', '20200501.ug', '20200501.uk', '20200501.ur', '20200501.uz', '20200501.ve', '20200501.vec', '20200501.vep', '20200501.vi', '20200501.vls', '20200501.vo', '20200501.wa', '20200501.war', '20200501.wo', '20200501.wuu', '20200501.xal', '20200501.xh', '20200501.xmf', '20200501.yi', '20200501.yo', '20200501.za', '20200501.zea', '20200501.zh', '20200501.zh-classical', '20200501.zh-min-nan', '20200501.zh-yue', '20200501.zu']
Example of usage:
`load_dataset('wikipedia', '20200501.aa')`
I think the other parameter is missing in the load_dataset function that is not shown in the instruction.
| false
|
1,056,689,876
|
https://api.github.com/repos/huggingface/datasets/issues/3291
|
https://github.com/huggingface/datasets/pull/3291
| 3,291
|
Use f-strings in the dataset scripts
|
closed
| 0
| 2021-11-17T22:20:19
| 2021-11-22T16:40:16
| 2021-11-22T16:40:16
|
Carlosbogo
|
[] |
Uses f-strings to format the .py files in the dataset folder
| true
|
1,056,414,856
|
https://api.github.com/repos/huggingface/datasets/issues/3290
|
https://github.com/huggingface/datasets/pull/3290
| 3,290
|
Make several audio datasets streamable
|
closed
| 4
| 2021-11-17T17:43:41
| 2022-02-01T21:00:52
| 2021-11-19T15:08:57
|
lhoestq
|
[] |
<s>Needs https://github.com/huggingface/datasets/pull/3129 to be merged first</s>
Make those audio datasets streamable:
- [x] common_voice
- [x] openslr
- [x] vivos
- [x] librispeech_asr <s>(still has some issues to read FLAC)</s> *actually it's ok*
- [ ] <s>multilingual_librispeech (yet to be converted)</S> *TODO in a separate PR*
| true
|
1,056,323,715
|
https://api.github.com/repos/huggingface/datasets/issues/3289
|
https://github.com/huggingface/datasets/pull/3289
| 3,289
|
Unpin markdown for build_docs now that it's fixed
|
closed
| 0
| 2021-11-17T16:22:53
| 2021-11-17T16:23:09
| 2021-11-17T16:23:08
|
lhoestq
|
[] |
`markdown`'s bug has been fixed, so this PR reverts #3286
| true
|
1,056,145,703
|
https://api.github.com/repos/huggingface/datasets/issues/3288
|
https://github.com/huggingface/datasets/pull/3288
| 3,288
|
Allow datasets with indices table when concatenating along axis=1
|
closed
| 0
| 2021-11-17T13:41:28
| 2021-11-17T15:41:12
| 2021-11-17T15:41:11
|
mariosasko
|
[] |
Calls `flatten_indices` on the datasets with indices table in `concatenate_datasets` to fix issues when concatenating along `axis=1`.
cc @lhoestq: I decided to flatten all the datasets instead of flattening all the datasets except the largest one in the end. The latter approach fails on the following example:
```python
a = Dataset.from_dict({"a": [10, 20, 30, 40]})
b = Dataset.from_dict({"b": [10, 20, 30, 40, 50, 60]}) # largest dataset
a = a.select([1, 2, 3])
b = b.select([1, 2, 3])
concatenate_datasets([a, b], axis=1) # fails at line concat_tables(...) because the real length of b's data is 6 and a's length is 3 after flattening (was 4 before flattening)
```
Also, it requires additional re-ordering of indices to prepare them for working with the indices table of the largest dataset. IMO not worth when we save only one `flatten_indices` call. (feel free to check the code of that approach at https://github.com/huggingface/datasets/commit/6acd10481c70950dcfdbfd2bab0bf0c74ad80bcb if you are interested)
Fixes #3273
| true
|
1,056,079,724
|
https://api.github.com/repos/huggingface/datasets/issues/3287
|
https://github.com/huggingface/datasets/pull/3287
| 3,287
|
Add The Pile dataset and PubMed Central subset
|
closed
| 0
| 2021-11-17T12:35:58
| 2021-12-01T15:29:08
| 2021-12-01T15:29:07
|
albertvillanova
|
[] |
Add:
- The complete final version of The Pile dataset: "all" config
- PubMed Central subset of The Pile: "pubmed_central" config
Close #1675, close bigscience-workshop/data_tooling#74.
CC: @StellaAthena, @lewtun
| true
|
1,056,008,586
|
https://api.github.com/repos/huggingface/datasets/issues/3286
|
https://github.com/huggingface/datasets/pull/3286
| 3,286
|
Fix build_docs CI
|
closed
| 0
| 2021-11-17T11:18:56
| 2021-11-17T11:19:20
| 2021-11-17T11:19:19
|
lhoestq
|
[] |
Because of https://github.com/Python-Markdown/markdown/issues/1196 we have to temporarily pin `markdown` to 3.3.4 for the docs to build without issues
| true
|
1,055,506,730
|
https://api.github.com/repos/huggingface/datasets/issues/3285
|
https://github.com/huggingface/datasets/issues/3285
| 3,285
|
Add IEMOCAP dataset
|
open
| 8
| 2021-11-16T22:47:20
| 2023-06-10T08:14:52
| null |
osanseviero
|
[
"dataset request",
"speech",
"vision"
] |
## Adding a Dataset
- **Name:** IEMOCAP
- **Description:** acted, multimodal and multispeaker database
- **Paper:** https://sail.usc.edu/iemocap/Busso_2008_iemocap.pdf
- **Data:** https://sail.usc.edu/iemocap/index.html
- **Motivation:** Useful multimodal dataset
cc @anton-l
Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
| false
|
1,055,502,909
|
https://api.github.com/repos/huggingface/datasets/issues/3284
|
https://github.com/huggingface/datasets/issues/3284
| 3,284
|
Add VoxLingua107 dataset
|
open
| 1
| 2021-11-16T22:44:08
| 2021-12-06T09:49:45
| null |
osanseviero
|
[
"dataset request",
"speech"
] |
## Adding a Dataset
- **Name:** VoxLingua107
- **Description:** VoxLingua107 is a speech dataset for training spoken language identification models. The dataset consists of short speech segments automatically extracted from YouTube videos and labeled according the language of the video title and description, with some post-processing steps to filter out false positives.
- **Paper:** https://arxiv.org/abs/2011.12998
- **Data:** http://bark.phon.ioc.ee/voxlingua107/
- **Motivation:** Nice audio classification dataset
cc @anton-l
Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
| false
|
1,055,495,874
|
https://api.github.com/repos/huggingface/datasets/issues/3283
|
https://github.com/huggingface/datasets/issues/3283
| 3,283
|
Add Speech Commands dataset
|
closed
| 1
| 2021-11-16T22:39:56
| 2021-12-10T10:30:15
| 2021-12-10T10:30:15
|
osanseviero
|
[
"dataset request",
"speech"
] |
## Adding a Dataset
- **Name:** Speech commands
- **Description:** A Dataset for Limited-Vocabulary Speech Recognition
- **Paper:** https://arxiv.org/abs/1804.03209
- **Data:** https://www.tensorflow.org/datasets/catalog/speech_commands, Available:
http://download.tensorflow.org/data/speech_commands_v0.02.tar.gz
- **Motivation:** Nice dataset for audio classification training
cc @anton-l
Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
| false
|
1,055,054,898
|
https://api.github.com/repos/huggingface/datasets/issues/3282
|
https://github.com/huggingface/datasets/issues/3282
| 3,282
|
ConnectionError: Couldn't reach https://huggingface.co/datasets/oscar-corpus/OSCAR-2109/resolve/main/OSCAR-2109.py
|
closed
| 7
| 2021-11-16T16:05:19
| 2022-04-12T11:57:43
| 2022-04-12T11:57:43
|
MinionAttack
|
[
"dataset-viewer"
] |
## Dataset viewer issue for '*oscar-corpus/OSCAR-2109*'
**Link:** *[link to the dataset viewer page](https://huggingface.co/datasets/oscar-corpus/OSCAR-2109)*
*The dataset library cannot download any language from the oscar-corpus/OSCAR-2109 dataset. By entering the URL in your browser I can access the file.*
```
raise ConnectionError("Couldn't reach {}".format(url))
ConnectionError: Couldn't reach https://huggingface.co/datasets/oscar-corpus/OSCAR-2109/resolve/main/OSCAR-2109.py
```
Am I the one who added this dataset ? No
Using the older version of [OSCAR](https://huggingface.co/datasets/oscar) I don't have any issues downloading languages with the dataset library.
| false
|
1,055,018,876
|
https://api.github.com/repos/huggingface/datasets/issues/3281
|
https://github.com/huggingface/datasets/pull/3281
| 3,281
|
[Datasets] Improve Covost 2
|
closed
| 2
| 2021-11-16T15:32:19
| 2022-01-26T16:17:06
| 2021-11-18T10:44:04
|
patrickvonplaten
|
[] |
It's currently quite confusing to understand the manual data download instruction of Covost and not very user-friendly.
Currenty the user has to:
1. Go on Common Voice website
2. Find the correct dataset which is **not** mentioned in the error message
3. Download it
4. Untar it
5. Create a language id folder (why? this folder does not exist in the `.tar` downloaded file)
6. pass the folder containing the created language id folder
This PR improves this to:
1. Go on Common Voice website
2. Find the correct dataset which **is** mentioned in the error message
3. Download it
4. Untar it
5. pass the untared folder
**Note**: This PR is not at all time-critical
| true
|
1,054,766,828
|
https://api.github.com/repos/huggingface/datasets/issues/3280
|
https://github.com/huggingface/datasets/pull/3280
| 3,280
|
Fix bookcorpusopen RAM usage
|
closed
| 0
| 2021-11-16T11:27:52
| 2021-11-17T15:53:28
| 2021-11-16T13:34:30
|
lhoestq
|
[] |
Each document is a full book, so the default arrow writer batch size of 10,000 is too big, and it can fill up RAM quickly before flushing the first batch on disk. I changed its batch size to 256 to use maximum 100MB of memory
Fix #3167.
| true
|
1,054,711,852
|
https://api.github.com/repos/huggingface/datasets/issues/3279
|
https://github.com/huggingface/datasets/pull/3279
| 3,279
|
Minor Typo Fix - Precision to Recall
|
closed
| 0
| 2021-11-16T10:32:22
| 2021-11-16T11:18:03
| 2021-11-16T11:18:02
|
SebastinSanty
|
[] | null | true
|
1,054,249,463
|
https://api.github.com/repos/huggingface/datasets/issues/3278
|
https://github.com/huggingface/datasets/pull/3278
| 3,278
|
Proposed update to the documentation for WER
|
closed
| 0
| 2021-11-15T23:28:31
| 2021-11-16T11:19:37
| 2021-11-16T11:19:37
|
wooters
|
[] |
I wanted to submit a minor update to the description of WER for your consideration.
Because of the possibility of insertions, the numerator in the WER formula can be larger than N, so the value of WER can be greater than 1.0:
```
>>> from datasets import load_metric
>>> metric = load_metric("wer")
>>> metric.compute(predictions=["hello how are you"], references=["hello"])
3.0
```
and similarly from the underlying jiwer module's `wer` function:
```
>>> from jiwer import wer
>>> wer("hello", "hello how are you")
3.0
```
| true
|
1,054,122,656
|
https://api.github.com/repos/huggingface/datasets/issues/3277
|
https://github.com/huggingface/datasets/pull/3277
| 3,277
|
f-string formatting
|
closed
| 1
| 2021-11-15T21:37:05
| 2021-11-19T20:40:08
| 2021-11-17T16:18:38
|
Mehdi2402
|
[] |
**Fix #3257**
Replaced _.format()_ and _%_ by f-strings in the following modules :
- [x] **tests**
- [x] **metrics**
- [x] **benchmarks**
- [x] **utils**
- [x] **templates**
- [x] **src/Datasets/\*.py**
Modules in **_src/Datasets/_**:
- [x] **commands**
- [x] **features**
- [x] **formatting**
- [x] **io**
- [x] **tasks**
- [x] **utils**
Module **datasets** will not be edited as asked by @mariosasko
-A correction of the first PR (#3267)-
| true
|
1,053,793,063
|
https://api.github.com/repos/huggingface/datasets/issues/3276
|
https://github.com/huggingface/datasets/pull/3276
| 3,276
|
Update KILT metadata JSON
|
closed
| 0
| 2021-11-15T15:25:25
| 2021-11-16T11:21:59
| 2021-11-16T11:21:58
|
albertvillanova
|
[] |
Fix #3265.
| true
|
1,053,698,898
|
https://api.github.com/repos/huggingface/datasets/issues/3275
|
https://github.com/huggingface/datasets/pull/3275
| 3,275
|
Force data files extraction if download_mode='force_redownload'
|
closed
| 0
| 2021-11-15T14:00:24
| 2021-11-15T14:45:23
| 2021-11-15T14:45:23
|
mariosasko
|
[] |
Avoids weird issues when redownloading a dataset due to cached data not being fully updated.
With this change, issues #3122 and https://github.com/huggingface/datasets/issues/2956 (not a fix, but a workaround) can be fixed as follows:
```python
dset = load_dataset(..., download_mode="force_redownload")
```
| true
|
1,053,689,140
|
https://api.github.com/repos/huggingface/datasets/issues/3274
|
https://github.com/huggingface/datasets/pull/3274
| 3,274
|
Fix some contact information formats
|
closed
| 1
| 2021-11-15T13:50:34
| 2021-11-15T14:43:55
| 2021-11-15T14:43:54
|
lhoestq
|
[] |
As reported in https://github.com/huggingface/datasets/issues/3188 some contact information are not displayed correctly.
This PR fixes this for CoNLL-2002 and some other datasets with the same issue
| true
|
1,053,554,038
|
https://api.github.com/repos/huggingface/datasets/issues/3273
|
https://github.com/huggingface/datasets/issues/3273
| 3,273
|
Respect row ordering when concatenating datasets along axis=1
|
closed
| 0
| 2021-11-15T11:27:14
| 2021-11-17T15:41:11
| 2021-11-17T15:41:11
|
mariosasko
|
[
"bug"
] |
Currently, there is a bug when concatenating datasets along `axis=1` if more than one dataset has the `_indices` attribute defined. In that scenario, all indices mappings except the first one get ignored.
A minimal reproducible example:
```python
>>> from datasets import Dataset, concatenate_datasets
>>> a = Dataset.from_dict({"a": [30, 20, 10]})
>>> b = Dataset.from_dict({"b": [2, 1, 3]})
>>> d = concatenate_datasets([a.sort("a"), b.sort("b")], axis=1)
>>> print(d[:3]) # expected: {'a': [10, 20, 30], 'b': [1, 2, 3]}
{'a': [10, 20, 30], 'b': [3, 1, 2]}
```
I've noticed the bug while working on #3195.
| false
|
1,053,516,479
|
https://api.github.com/repos/huggingface/datasets/issues/3272
|
https://github.com/huggingface/datasets/issues/3272
| 3,272
|
Make iter_archive work with ZIP files
|
open
| 4
| 2021-11-15T10:50:42
| 2021-11-25T00:08:47
| null |
lhoestq
|
[
"enhancement"
] |
Currently users can use `dl_manager.iter_archive` in their dataset script to iterate over all the files of a TAR archive.
It would be nice if it could work with ZIP files too !
| false
|
1,053,482,919
|
https://api.github.com/repos/huggingface/datasets/issues/3271
|
https://github.com/huggingface/datasets/pull/3271
| 3,271
|
Decode audio from remote
|
closed
| 0
| 2021-11-15T10:25:56
| 2021-11-16T11:35:58
| 2021-11-16T11:35:58
|
lhoestq
|
[] |
Currently the Audio feature type can only decode local audio files, not remote files.
To fix this I replaced `open` with our `xopen` functoin that is compatible with remote files in audio.py
cc @albertvillanova @mariosasko
| true
|
1,053,465,662
|
https://api.github.com/repos/huggingface/datasets/issues/3270
|
https://github.com/huggingface/datasets/pull/3270
| 3,270
|
Add os.listdir for streaming
|
closed
| 0
| 2021-11-15T10:14:04
| 2021-11-15T10:27:03
| 2021-11-15T10:27:03
|
lhoestq
|
[] |
Extend `os.listdir` to support streaming data from remote files. This is often used to navigate in remote ZIP files for example
| true
|
1,053,218,769
|
https://api.github.com/repos/huggingface/datasets/issues/3269
|
https://github.com/huggingface/datasets/issues/3269
| 3,269
|
coqa NonMatchingChecksumError
|
closed
| 18
| 2021-11-15T05:04:07
| 2022-01-19T13:58:19
| 2022-01-19T13:58:19
|
ZhaofengWu
|
[
"bug"
] |
```
>>> from datasets import load_dataset
>>> dataset = load_dataset("coqa")
Downloading: 3.82kB [00:00, 1.26MB/s]
Downloading: 1.79kB [00:00, 733kB/s]
Using custom data configuration default
Downloading and preparing dataset coqa/default (download: 55.40 MiB, generated: 18.35 MiB, post-processed: Unknown size, total: 73.75 MiB) to /Users/zhaofengw/.cache/huggingface/datasets/coqa/default/1.0.0/553ce70bfdcd15ff4b5f4abc4fc2f37137139cde1f58f4f60384a53a327716f0...
Downloading: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 222/222 [00:00<00:00, 1.38MB/s]
Downloading: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 222/222 [00:00<00:00, 1.32MB/s]
100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 2/2 [00:01<00:00, 1.91it/s]
100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 2/2 [00:00<00:00, 1117.44it/s]
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/Users/zhaofengw/miniconda3/lib/python3.9/site-packages/datasets/load.py", line 1632, in load_dataset
builder_instance.download_and_prepare(
File "/Users/zhaofengw/miniconda3/lib/python3.9/site-packages/datasets/builder.py", line 607, in download_and_prepare
self._download_and_prepare(
File "/Users/zhaofengw/miniconda3/lib/python3.9/site-packages/datasets/builder.py", line 679, in _download_and_prepare
verify_checksums(
File "/Users/zhaofengw/miniconda3/lib/python3.9/site-packages/datasets/utils/info_utils.py", line 40, in verify_checksums
raise NonMatchingChecksumError(error_msg + str(bad_urls))
datasets.utils.info_utils.NonMatchingChecksumError: Checksums didn't match for dataset source files:
['https://nlp.stanford.edu/data/coqa/coqa-train-v1.0.json', 'https://nlp.stanford.edu/data/coqa/coqa-dev-v1.0.json']
```
| false
|
1,052,992,681
|
https://api.github.com/repos/huggingface/datasets/issues/3268
|
https://github.com/huggingface/datasets/issues/3268
| 3,268
|
Dataset viewer issue for 'liweili/c4_200m'
|
closed
| 5
| 2021-11-14T17:18:46
| 2021-12-21T10:25:20
| 2021-12-21T10:24:51
|
liliwei25
|
[
"dataset-viewer"
] |
## Dataset viewer issue for '*liweili/c4_200m*'
**Link:** *[link to the dataset viewer page](https://huggingface.co/datasets/liweili/c4_200m)*
*Server Error*
```
Status code: 404
Exception: Status404Error
Message: Not found. Maybe the cache is missing, or maybe the ressource does not exist.
```
Am I the one who added this dataset ? Yes
| false
|
1,052,750,084
|
https://api.github.com/repos/huggingface/datasets/issues/3267
|
https://github.com/huggingface/datasets/pull/3267
| 3,267
|
Replacing .format() and % by f-strings
|
closed
| 4
| 2021-11-13T19:12:02
| 2021-11-16T21:00:26
| 2021-11-16T14:55:43
|
Mehdi2402
|
[] |
**Fix #3257**
Replaced _.format()_ and _%_ by f-strings in the following modules :
- [x] **tests**
- [x] **metrics**
- [x] **benchmarks**
- [x] **utils**
- [x] **templates**
Will follow in the next PR the modules left :
- [ ] **src**
Module **datasets** will not be edited as asked by @mariosasko
PS : black and isort applied to files
| true
|
1,052,700,155
|
https://api.github.com/repos/huggingface/datasets/issues/3266
|
https://github.com/huggingface/datasets/pull/3266
| 3,266
|
Fix URLs for WikiAuto Manual, jeopardy and definite_pronoun_resolution
|
closed
| 10
| 2021-11-13T15:01:34
| 2021-12-06T11:16:31
| 2021-12-06T11:16:31
|
LashaO
|
[] |
[#3264](https://github.com/huggingface/datasets/issues/3264)
| true
|
1,052,666,558
|
https://api.github.com/repos/huggingface/datasets/issues/3265
|
https://github.com/huggingface/datasets/issues/3265
| 3,265
|
Checksum error for kilt_task_wow
|
closed
| 2
| 2021-11-13T12:04:17
| 2021-11-16T11:23:53
| 2021-11-16T11:21:58
|
slyviacassell
|
[
"bug"
] |
## Describe the bug
Checksum failed when downloads kilt_tasks_wow. See error output for details.
## Steps to reproduce the bug
```python
import datasets
datasets.load_datasets('kilt_tasks','wow')
```
## Expected results
Download successful
## Actual results
```
Downloading and preparing dataset kilt_tasks/wow (download: 72.07 MiB, generated: 61.82 MiB, post-processed: Unknown size, total: 133.89 MiB) to /root/.cache/huggingface/datasets/kilt_tasks/wow/1.0.0/57dc8b2431e76637e0c6ef79689ca4af61ed3a330e2e0cd62c8971465a35db3a...
100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<00:00, 5121.25it/s]
100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<00:00, 1527.42it/s]
Traceback (most recent call last):
File "kilt_wow.py", line 30, in <module>
main()
File "kilt_wow.py", line 27, in main
train, dev, test = dataset.generate_k_shot_data(k=32, seed=seed, path="../data/")
File "/workspace/projects/CrossFit/tasks/fewshot_gym_dataset.py", line 79, in generate_k_shot_data
dataset = self.load_dataset()
File "kilt_wow.py", line 21, in load_dataset
return datasets.load_dataset('kilt_tasks','wow')
File "/opt/conda/lib/python3.8/site-packages/datasets/load.py", line 1632, in load_dataset
builder_instance.download_and_prepare(
File "/opt/conda/lib/python3.8/site-packages/datasets/builder.py", line 607, in download_and_prepare
self._download_and_prepare(
File "/opt/conda/lib/python3.8/site-packages/datasets/builder.py", line 679, in _download_and_prepare
verify_checksums(
File "/opt/conda/lib/python3.8/site-packages/datasets/utils/info_utils.py", line 40, in verify_checksums
raise NonMatchingChecksumError(error_msg + str(bad_urls))
datasets.utils.info_utils.NonMatchingChecksumError: Checksums didn't match for dataset source files:
['http://dl.fbaipublicfiles.com/KILT/wow-train-kilt.jsonl', 'http://dl.fbaipublicfiles.com/KILT/wow-dev-kilt.jsonl']
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.15.1
- Platform: Linux-4.15.0-161-generic-x86_64-with-glibc2.10
- Python version: 3.8.3
- PyArrow version: 4.0.1
| false
|
1,052,663,513
|
https://api.github.com/repos/huggingface/datasets/issues/3264
|
https://github.com/huggingface/datasets/issues/3264
| 3,264
|
Downloading URL change for WikiAuto Manual, jeopardy and definite_pronoun_resolution
|
closed
| 3
| 2021-11-13T11:47:12
| 2022-06-01T17:38:16
| 2022-06-01T17:38:16
|
slyviacassell
|
[
"bug"
] |
## Describe the bug
- WikiAuto Manual
The original manual datasets with the following downloading URL in this [repository](https://github.com/chaojiang06/wiki-auto) was [deleted](https://github.com/chaojiang06/wiki-auto/commit/0af9b066f2b4e02726fb8a9be49283c0ad25367f) by the author.
```
https://github.com/chaojiang06/wiki-auto/raw/master/wiki-manual/train.tsv
```
- jeopardy
The downloading URL for jeopardy may move from
```
http://skeeto.s3.amazonaws.com/share/JEOPARDY_QUESTIONS1.json.gz
```
to
```
https://drive.google.com/file/d/0BwT5wj_P7BKXb2hfM3d2RHU1ckE/view?resourcekey=0-1abK4cJq-mqxFoSg86ieIg
```
- definite_pronoun_resolution
The following downloading URL for definite_pronoun_resolution cannot be reached for some reasons.
```
http://www.hlt.utdallas.edu/~vince/data/emnlp12/train.c.txt
```
## Steps to reproduce the bug
```python
import datasets
datasets.load_datasets('wiki_auto','manual')
datasets.load_datasets('jeopardy')
datasets.load_datasets('definite_pronoun_resolution')
```
## Expected results
Download successfully
## Actual results
- WikiAuto Manual
```
Downloading and preparing dataset wiki_auto/manual (download: 151.65 MiB, generated: 155.97 MiB, post-processed: Unknown size, total: 307.61 MiB) to /root/.cache/huggingface/datasets/wiki_auto/manual/1.0.0/5ffdd9fc62422d29bd02675fb9606f77c1251ee17169ac10b143ce07ef2f4db8...
0%| | 0/3 [00:00<?, ?it/s]Traceback (most recent call last):
File "wiki_auto.py", line 43, in <module>
main()
File "wiki_auto.py", line 40, in main
train, dev, test = dataset.generate_k_shot_data(k=16, seed=seed, path="../data/")
File "/workspace/projects/CrossFit/tasks/fewshot_gym_dataset.py", line 24, in generate_k_shot_data
dataset = self.load_dataset()
File "wiki_auto.py", line 34, in load_dataset
return datasets.load_dataset('wiki_auto', 'manual')
File "/opt/conda/lib/python3.8/site-packages/datasets/load.py", line 1632, in load_dataset
builder_instance.download_and_prepare(
File "/opt/conda/lib/python3.8/site-packages/datasets/builder.py", line 607, in download_and_prepare
self._download_and_prepare(
File "/opt/conda/lib/python3.8/site-packages/datasets/builder.py", line 675, in _download_and_prepare
split_generators = self._split_generators(dl_manager, **split_generators_kwargs)
File "/root/.cache/huggingface/modules/datasets_modules/datasets/wiki_auto/5ffdd9fc62422d29bd02675fb9606f77c1251ee17169ac10b143ce07ef2f4db8/wiki_auto.py", line 193, in _split_generators
data_dir = dl_manager.download_and_extract(my_urls)
File "/opt/conda/lib/python3.8/site-packages/datasets/utils/download_manager.py", line 284, in download_and_extract
return self.extract(self.download(url_or_urls))
File "/opt/conda/lib/python3.8/site-packages/datasets/utils/download_manager.py", line 196, in download
downloaded_path_or_paths = map_nested(
File "/opt/conda/lib/python3.8/site-packages/datasets/utils/py_utils.py", line 216, in map_nested
mapped = [
File "/opt/conda/lib/python3.8/site-packages/datasets/utils/py_utils.py", line 217, in <listcomp>
_single_map_nested((function, obj, types, None, True))
File "/opt/conda/lib/python3.8/site-packages/datasets/utils/py_utils.py", line 152, in _single_map_nested
return function(data_struct)
File "/opt/conda/lib/python3.8/site-packages/datasets/utils/download_manager.py", line 217, in _download
return cached_path(url_or_filename, download_config=download_config)
File "/opt/conda/lib/python3.8/site-packages/datasets/utils/file_utils.py", line 295, in cached_path
output_path = get_from_cache(
File "/opt/conda/lib/python3.8/site-packages/datasets/utils/file_utils.py", line 592, in get_from_cache
raise FileNotFoundError("Couldn't find file at {}".format(url))
FileNotFoundError: Couldn't find file at https://github.com/chaojiang06/wiki-auto/raw/master/wiki-manual/train.tsv
```
- jeopardy
```
Using custom data configuration default
Downloading and preparing dataset jeopardy/default (download: 12.13 MiB, generated: 34.46 MiB, post-processed: Unknown size, total: 46.59 MiB) to /root/.cache/huggingface/datasets/jeopardy/default/0.1.0/25ee3e4a73755e637b8810f6493fd36e4523dea3ca8a540529d0a6e24c7f9810...
Traceback (most recent call last):
File "jeopardy.py", line 45, in <module>
main()
File "jeopardy.py", line 42, in main
train, dev, test = dataset.generate_k_shot_data(k=32, seed=seed, path="../data/")
File "/workspace/projects/CrossFit/tasks/fewshot_gym_dataset.py", line 79, in generate_k_shot_data
dataset = self.load_dataset()
File "jeopardy.py", line 36, in load_dataset
return datasets.load_dataset("jeopardy")
File "/opt/conda/lib/python3.8/site-packages/datasets/load.py", line 1632, in load_dataset
builder_instance.download_and_prepare(
File "/opt/conda/lib/python3.8/site-packages/datasets/builder.py", line 607, in download_and_prepare
self._download_and_prepare(
File "/opt/conda/lib/python3.8/site-packages/datasets/builder.py", line 675, in _download_and_prepare
split_generators = self._split_generators(dl_manager, **split_generators_kwargs)
File "/root/.cache/huggingface/modules/datasets_modules/datasets/jeopardy/25ee3e4a73755e637b8810f6493fd36e4523dea3ca8a540529d0a6e24c7f9810/jeopardy.py", line 72, in _split_generators
filepath = dl_manager.download_and_extract(_DATA_URL)
File "/opt/conda/lib/python3.8/site-packages/datasets/utils/download_manager.py", line 284, in download_and_extract
return self.extract(self.download(url_or_urls))
File "/opt/conda/lib/python3.8/site-packages/datasets/utils/download_manager.py", line 196, in download
downloaded_path_or_paths = map_nested(
File "/opt/conda/lib/python3.8/site-packages/datasets/utils/py_utils.py", line 206, in map_nested
return function(data_struct)
File "/opt/conda/lib/python3.8/site-packages/datasets/utils/download_manager.py", line 217, in _download
return cached_path(url_or_filename, download_config=download_config)
File "/opt/conda/lib/python3.8/site-packages/datasets/utils/file_utils.py", line 295, in cached_path
output_path = get_from_cache(
File "/opt/conda/lib/python3.8/site-packages/datasets/utils/file_utils.py", line 594, in get_from_cache
raise ConnectionError("Couldn't reach {}".format(url))
ConnectionError: Couldn't reach http://skeeto.s3.amazonaws.com/share/JEOPARDY_QUESTIONS1.json.gz
```
- definite_pronoun_resolution
```
Downloading and preparing dataset definite_pronoun_resolution/plain_text (download: 222.12 KiB, generated: 239.12 KiB, post-processed: Unknown size, total: 461.24 KiB) to /root/.cache/huggingface/datasets/definite_pronoun_resolution/plain_text/1.0.0/35a1dfd4fba4afb8ba226cbbb65ac7cef0dd3cf9302d8f803740f05d2f16ceff...
0%| | 0/2 [00:00<?, ?it/s]Traceback (most recent call last):
File "definite_pronoun_resolution.py", line 37, in <module>
main()
File "definite_pronoun_resolution.py", line 34, in main
train, dev, test = dataset.generate_k_shot_data(k=32, seed=seed, path="../data/")
File "/workspace/projects/CrossFit/tasks/fewshot_gym_dataset.py", line 79, in generate_k_shot_data
dataset = self.load_dataset()
File "definite_pronoun_resolution.py", line 28, in load_dataset
return datasets.load_dataset('definite_pronoun_resolution')
File "/opt/conda/lib/python3.8/site-packages/datasets/load.py", line 1632, in load_dataset
builder_instance.download_and_prepare(
File "/opt/conda/lib/python3.8/site-packages/datasets/builder.py", line 607, in download_and_prepare
self._download_and_prepare(
File "/opt/conda/lib/python3.8/site-packages/datasets/builder.py", line 675, in _download_and_prepare
split_generators = self._split_generators(dl_manager, **split_generators_kwargs)
File "/root/.cache/huggingface/modules/datasets_modules/datasets/definite_pronoun_resolution/35a1dfd4fba4afb8ba226cbbb65ac7cef0dd3cf9302d8f803740f05d2f16ceff/definite_pronoun_resolution.py", line 76, in _split_generators
files = dl_manager.download_and_extract(
File "/opt/conda/lib/python3.8/site-packages/datasets/utils/download_manager.py", line 284, in download_and_extract
return self.extract(self.download(url_or_urls))
File "/opt/conda/lib/python3.8/site-packages/datasets/utils/download_manager.py", line 196, in download
downloaded_path_or_paths = map_nested(
File "/opt/conda/lib/python3.8/site-packages/datasets/utils/py_utils.py", line 216, in map_nested
mapped = [
File "/opt/conda/lib/python3.8/site-packages/datasets/utils/py_utils.py", line 217, in <listcomp>
_single_map_nested((function, obj, types, None, True))
File "/opt/conda/lib/python3.8/site-packages/datasets/utils/py_utils.py", line 152, in _single_map_nested
return function(data_struct)
File "/opt/conda/lib/python3.8/site-packages/datasets/utils/download_manager.py", line 217, in _download
return cached_path(url_or_filename, download_config=download_config)
File "/opt/conda/lib/python3.8/site-packages/datasets/utils/file_utils.py", line 295, in cached_path
output_path = get_from_cache(
File "/opt/conda/lib/python3.8/site-packages/datasets/utils/file_utils.py", line 594, in get_from_cache
raise ConnectionError("Couldn't reach {}".format(url))
ConnectionError: Couldn't reach http://www.hlt.utdallas.edu/~vince/data/emnlp12/train.c.txt
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.15.1
- Platform: Linux-4.15.0-161-generic-x86_64-with-glibc2.10
- Python version: 3.8.3
- PyArrow version: 4.0.1
| false
|
1,052,552,516
|
https://api.github.com/repos/huggingface/datasets/issues/3263
|
https://github.com/huggingface/datasets/issues/3263
| 3,263
|
FET DATA
|
closed
| 0
| 2021-11-13T05:46:06
| 2021-11-13T13:31:47
| 2021-11-13T13:31:47
|
FStell01
|
[
"dataset request"
] |
## Adding a Dataset
- **Name:** *name of the dataset*
- **Description:** *short description of the dataset (or link to social media or blog post)*
- **Paper:** *link to the dataset paper if available*
- **Data:** *link to the Github repository or current dataset location*
- **Motivation:** *what are some good reasons to have this dataset*
Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
| false
|
1,052,455,082
|
https://api.github.com/repos/huggingface/datasets/issues/3262
|
https://github.com/huggingface/datasets/pull/3262
| 3,262
|
asserts replaced with exception for image classification task, csv, json
|
closed
| 0
| 2021-11-12T22:34:59
| 2021-11-15T11:08:37
| 2021-11-15T11:08:37
|
manisnesan
|
[] |
Fixes for csv, json in io module and image_classification task with tests referenced in https://github.com/huggingface/datasets/issues/3171
| true
|
1,052,346,381
|
https://api.github.com/repos/huggingface/datasets/issues/3261
|
https://github.com/huggingface/datasets/issues/3261
| 3,261
|
Scifi_TV_Shows: Having trouble getting viewer to find appropriate files
|
closed
| 2
| 2021-11-12T19:25:19
| 2021-12-21T10:24:10
| 2021-12-21T10:24:10
|
lara-martin
|
[
"dataset-viewer"
] |
## Dataset viewer issue for '*Science Fiction TV Show Plots Corpus (Scifi_TV_Shows)*'
**Link:** [link](https://huggingface.co/datasets/lara-martin/Scifi_TV_Shows)
I tried adding both a script (https://huggingface.co/datasets/lara-martin/Scifi_TV_Shows/blob/main/Scifi_TV_Shows.py) and some dummy examples (https://huggingface.co/datasets/lara-martin/Scifi_TV_Shows/tree/main/dummy), but the viewer still has a 404 error ("Not found. Maybe the cache is missing, or maybe the ressource does not exist."). I'm not sure what to try next. Thanks in advance!
Am I the one who added this dataset? Yes
| false
|
1,052,247,373
|
https://api.github.com/repos/huggingface/datasets/issues/3260
|
https://github.com/huggingface/datasets/pull/3260
| 3,260
|
Fix ConnectionError in Scielo dataset
|
closed
| 1
| 2021-11-12T18:02:37
| 2021-11-16T18:18:17
| 2021-11-16T17:55:22
|
mariosasko
|
[] |
This PR:
* allows 403 status code in HEAD requests to S3 buckets to fix the connection error in the Scielo dataset (instead of `url`, uses `response.url` to check the URL of the final endpoint)
* makes the Scielo dataset streamable
Fixes #3255.
| true
|
1,052,189,775
|
https://api.github.com/repos/huggingface/datasets/issues/3259
|
https://github.com/huggingface/datasets/pull/3259
| 3,259
|
Updating details of IRC disentanglement data
|
closed
| 1
| 2021-11-12T17:16:58
| 2021-11-18T17:19:33
| 2021-11-18T17:19:33
|
jkkummerfeld
|
[] |
I was pleasantly surprised to find that someone had already added my dataset to the huggingface library, but some details were missing or incorrect. This PR fixes the documentation.
| true
|
1,052,188,195
|
https://api.github.com/repos/huggingface/datasets/issues/3258
|
https://github.com/huggingface/datasets/issues/3258
| 3,258
|
Reload dataset that was already downloaded with `load_from_disk` from cloud storage
|
open
| 0
| 2021-11-12T17:14:59
| 2021-11-12T17:14:59
| null |
lhoestq
|
[
"enhancement"
] |
`load_from_disk` downloads the dataset to a temporary directory without checking if the dataset has already been downloaded once.
It would be nice to have some sort of caching for datasets downloaded this way. This could leverage the fingerprint of the dataset that was saved in the `state.json` file.
| false
|
1,052,118,365
|
https://api.github.com/repos/huggingface/datasets/issues/3257
|
https://github.com/huggingface/datasets/issues/3257
| 3,257
|
Use f-strings for string formatting
|
closed
| 5
| 2021-11-12T16:02:15
| 2021-11-17T16:18:38
| 2021-11-17T16:18:38
|
mariosasko
|
[
"good first issue"
] |
f-strings offer better readability/performance than `str.format` and `%`, so we should use them in all places in our codebase unless there is good reason to keep the older syntax.
> **NOTE FOR CONTRIBUTORS**: To avoid large PRs and possible merge conflicts, do 1-3 modules per PR. Also, feel free to ignore the files located under `datasets/*`.
| false
|
1,052,000,613
|
https://api.github.com/repos/huggingface/datasets/issues/3256
|
https://github.com/huggingface/datasets/pull/3256
| 3,256
|
asserts replaced by exception for text classification task with test.
|
closed
| 2
| 2021-11-12T14:05:36
| 2021-11-12T15:09:33
| 2021-11-12T14:59:32
|
manisnesan
|
[] |
I have replaced only a single assert in text_classification.py along with a unit test to verify an exception is raised based on https://github.com/huggingface/datasets/issues/3171 .
I would like to first understand the code contribution workflow. So keeping the change to a single file rather than making too many changes. Once this gets approved, I will look into the rest.
Thanks.
| true
|
1,051,783,129
|
https://api.github.com/repos/huggingface/datasets/issues/3255
|
https://github.com/huggingface/datasets/issues/3255
| 3,255
|
SciELO dataset ConnectionError
|
closed
| 0
| 2021-11-12T09:57:14
| 2021-11-16T17:55:22
| 2021-11-16T17:55:22
|
WojciechKusa
|
[
"bug"
] |
## Describe the bug
I get `ConnectionError` when I am trying to load the SciELO dataset.
When I try the URL with `requests` I get:
```
>>> requests.head("https://ndownloader.figstatic.com/files/14019287")
<Response [302]>
```
And as far as I understand redirections in `datasets` are not supported for downloads.
https://github.com/huggingface/datasets/blob/807341d0db0728073ab605c812c67f927d148f38/datasets/scielo/scielo.py#L45
## Steps to reproduce the bug
```python
from datasets import load_dataset
dataset = load_dataset("scielo", "en-es")
```
## Expected results
Download SciELO dataset and load Dataset object
## Actual results
```
Downloading and preparing dataset scielo/en-es (download: 21.90 MiB, generated: 68.45 MiB, post-processed: Unknown size, total: 90.35 MiB) to /Users/test/.cache/huggingface/datasets/scielo/en-es/1.0.0/7e05d55a20257efeb9925ff5de65bd4884fc6ddb6d765f1ea3e8860449d90e0e...
Traceback (most recent call last):
File "scielo.py", line 3, in <module>
dataset = load_dataset("scielo", "en-es")
File "../lib/python3.8/site-packages/datasets/load.py", line 1632, in load_dataset
builder_instance.download_and_prepare(
File "../lib/python3.8/site-packages/datasets/builder.py", line 607, in download_and_prepare
self._download_and_prepare(
File "../lib/python3.8/site-packages/datasets/builder.py", line 675, in _download_and_prepare
split_generators = self._split_generators(dl_manager, **split_generators_kwargs)
File "/Users/test/.cache/huggingface/modules/datasets_modules/datasets/scielo/7e05d55a20257efeb9925ff5de65bd4884fc6ddb6d765f1ea3e8860449d90e0e/scielo.py", line 77, in _split_generators
data_dir = dl_manager.download_and_extract(_URLS[self.config.name])
File "../lib/python3.8/site-packages/datasets/utils/download_manager.py", line 284, in download_and_extract
return self.extract(self.download(url_or_urls))
File "../lib/python3.8/site-packages/datasets/utils/download_manager.py", line 196, in download
downloaded_path_or_paths = map_nested(
File "../lib/python3.8/site-packages/datasets/utils/py_utils.py", line 206, in map_nested
return function(data_struct)
File "../lib/python3.8/site-packages/datasets/utils/download_manager.py", line 217, in _download
return cached_path(url_or_filename, download_config=download_config)
File "../lib/python3.8/site-packages/datasets/utils/file_utils.py", line 295, in cached_path
output_path = get_from_cache(
File "../lib/python3.8/site-packages/datasets/utils/file_utils.py", line 594, in get_from_cache
raise ConnectionError("Couldn't reach {}".format(url))
ConnectionError: Couldn't reach https://ndownloader.figstatic.com/files/14019287
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.15.1
- Platform: macOS-10.16-x86_64-i386-64bit
- Python version: 3.8.12
- PyArrow version: 6.0.0
| false
|
1,051,351,172
|
https://api.github.com/repos/huggingface/datasets/issues/3254
|
https://github.com/huggingface/datasets/pull/3254
| 3,254
|
Update xcopa dataset (fix checksum issues + add translated data)
|
closed
| 1
| 2021-11-11T20:51:33
| 2021-11-12T10:30:58
| 2021-11-12T10:30:57
|
mariosasko
|
[] |
This PR updates the checksums (as reported [here](https://discuss.huggingface.co/t/how-to-load-dataset-locally/11601/2)) of the `xcopa` dataset. Additionally, it adds new configs that hold the translated data of the original set of configs. This data was not available at the time of adding this dataset to the lib.
| true
|
1,051,308,972
|
https://api.github.com/repos/huggingface/datasets/issues/3253
|
https://github.com/huggingface/datasets/issues/3253
| 3,253
|
`GeneratorBasedBuilder` does not support `None` values
|
closed
| 1
| 2021-11-11T19:51:21
| 2021-12-09T14:26:58
| 2021-12-09T14:26:58
|
pavel-lexyr
|
[
"bug"
] |
## Describe the bug
`GeneratorBasedBuilder` does not support `None` values.
## Steps to reproduce the bug
See [this repository](https://github.com/pavel-lexyr/huggingface-datasets-bug-reproduction) for minimal reproduction.
## Expected results
Dataset is initialized with a `None` value in the `value` column.
## Actual results
```
Traceback (most recent call last):
File "main.py", line 3, in <module>
datasets.load_dataset("./bad-data")
File ".../datasets/load.py", line 1632, in load_dataset
builder_instance.download_and_prepare(
File ".../datasets/builder.py", line 607, in download_and_prepare
self._download_and_prepare(
File ".../datasets/builder.py", line 697, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File ".../datasets/builder.py", line 1103, in _prepare_split
example = self.info.features.encode_example(record)
File ".../datasets/features/features.py", line 1033, in encode_example
return encode_nested_example(self, example)
File ".../datasets/features/features.py", line 808, in encode_nested_example
return {
File ".../datasets/features/features.py", line 809, in <dictcomp>
k: encode_nested_example(sub_schema, sub_obj) for k, (sub_schema, sub_obj) in utils.zip_dict(schema, obj)
File ".../datasets/features/features.py", line 855, in encode_nested_example
return schema.encode_example(obj)
File ".../datasets/features/features.py", line 299, in encode_example
return float(value)
TypeError: float() argument must be a string or a number, not 'NoneType'
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.15.1
- Platform: Linux-5.4.0-81-generic-x86_64-with-glibc2.29
- Python version: 3.8.10
- PyArrow version: 6.0.0
| false
|
1,051,124,749
|
https://api.github.com/repos/huggingface/datasets/issues/3252
|
https://github.com/huggingface/datasets/pull/3252
| 3,252
|
Fix failing CER metric test in CI after update
|
closed
| 0
| 2021-11-11T15:57:16
| 2021-11-12T14:06:44
| 2021-11-12T14:06:43
|
mariosasko
|
[] |
Fixes the [failing CER metric test](https://app.circleci.com/pipelines/github/huggingface/datasets/8644/workflows/79816553-fa2f-4756-b022-d5937f00bf7b/jobs/53298) in CI by adding support for `jiwer==2.3.0`, which was released yesterday. Also, I verified that all the tests in `metrics/cer/test_cer.py` pass after the change, so the results should be the same irrespective of the `jiwer` version.
| true
|
1,050,541,348
|
https://api.github.com/repos/huggingface/datasets/issues/3250
|
https://github.com/huggingface/datasets/pull/3250
| 3,250
|
Add ETHICS dataset
|
closed
| 1
| 2021-11-11T03:45:34
| 2022-10-03T09:37:25
| 2022-10-03T09:37:25
|
ssss1029
|
[
"dataset contribution"
] |
This PR adds the ETHICS dataset, including all 5 sub-datasets.
From https://arxiv.org/abs/2008.02275
| true
|
1,050,193,138
|
https://api.github.com/repos/huggingface/datasets/issues/3249
|
https://github.com/huggingface/datasets/pull/3249
| 3,249
|
Fix streaming for id_newspapers_2018
|
closed
| 0
| 2021-11-10T18:55:30
| 2021-11-12T14:01:32
| 2021-11-12T14:01:31
|
lhoestq
|
[] |
To be compatible with streaming, this dataset must use `dl_manager.iter_archive` since the data are in a .tgz file
| true
|
1,050,171,082
|
https://api.github.com/repos/huggingface/datasets/issues/3248
|
https://github.com/huggingface/datasets/pull/3248
| 3,248
|
Stream from Google Drive and other hosts
|
closed
| 3
| 2021-11-10T18:32:32
| 2021-11-30T16:03:43
| 2021-11-12T17:18:11
|
lhoestq
|
[] |
Streaming from Google Drive is a bit more challenging than the other host we've been supporting:
- the download URL must be updated to add the confirm token obtained by HEAD request
- it requires to use cookies to keep the connection alive
- the URL doesn't tell any information about whether the file is compressed or not
Therefore I did two things:
- I added a step for URL and headers/cookies preparation in the StreamingDownloadManager
- I added automatic compression type inference by reading the [magic number](https://en.wikipedia.org/wiki/List_of_file_signatures)
This allows to do do fancy things like
```python
from datasets.utils.streaming_download_manager import StreamingDownloadManager, xopen, xjoin, xglob
# zip file containing a train.tsv file
url = "https://drive.google.com/uc?export=download&id=1k92sUfpHxKq8PXWRr7Y5aNHXwOCNUmqh"
extracted = StreamingDownloadManager().download_and_extract(url)
for inner_file in xglob(xjoin(extracted, "*.tsv")):
with xopen(inner_file) as f:
# streaming starts here
for line in f:
print(line)
```
This should make around 80 datasets streamable. It concerns those hosted on Google Drive but also any dataset for which the URL doesn't give any information about compression. Here is the full list:
```
amazon_polarity, ami, arabic_billion_words, ascent_kb, asset, big_patent, billsum, capes, cmrc2018, cnn_dailymail,
code_x_glue_cc_code_completion_token, code_x_glue_cc_code_refinement, code_x_glue_cc_code_to_code_trans,
code_x_glue_tt_text_to_text, conll2002, craigslist_bargains, dbpedia_14, docred, ehealth_kd, emo, euronews, germeval_14,
gigaword, grail_qa, great_code, has_part, head_qa, health_fact, hope_edi, id_newspapers_2018,
igbo_english_machine_translation, irc_disentangle, jfleg, jnlpba, journalists_questions, kor_ner, linnaeus, med_hop, mrqa,
mt_eng_vietnamese, multi_news, norwegian_ner, offcombr, offenseval_dravidian, para_pat, peoples_daily_ner, pn_summary,
poleval2019_mt, pubmed_qa, qangaroo, reddit_tifu, refresd, ro_sts_parallel, russian_super_glue, samsum, sberquad, scielo,
search_qa, species_800, spider, squad_adversarial, tamilmixsentiment, tashkeela, ted_talks_iwslt, trec, turk, turkish_ner,
twi_text_c3, universal_morphologies, web_of_science, weibo_ner, wiki_bio, wiki_hop, wiki_lingua, wiki_summary, wili_2018,
wisesight1000, wnut_17, yahoo_answers_topics, yelp_review_full, yoruba_text_c3
```
Some of them may not work if the host doesn't support HTTP range requests for example
Fix https://github.com/huggingface/datasets/issues/2742
Fix https://github.com/huggingface/datasets/issues/3188
| true
|
1,049,699,088
|
https://api.github.com/repos/huggingface/datasets/issues/3247
|
https://github.com/huggingface/datasets/issues/3247
| 3,247
|
Loading big json dataset raises pyarrow.lib.ArrowNotImplementedError
|
closed
| 3
| 2021-11-10T11:17:59
| 2022-04-10T14:05:57
| 2022-04-10T14:05:57
|
maxzirps
|
[
"bug"
] |
## Describe the bug
When trying to create a dataset from a json file with around 25MB, the following error is raised `pyarrow.lib.ArrowNotImplementedError: Unsupported cast from struct<b: int64, c: int64> to struct using function cast_struct`
Splitting the big file into smaller ones and then loading it with the `load_dataset` method did also not work.
Creating a pandas dataframe from it and then loading it with `Dataset.from_pandas` works
## Steps to reproduce the bug
```python
load_dataset("json", data_files="test.json")
```
test.json ~25MB
```json
{"a": {"c": 8, "b": 5}}
{"a": {"b": 7, "c": 6}}
{"a": {"c": 8, "b": 5}}
{"a": {"b": 7, "c": 6}}
{"a": {"c": 8, "b": 5}}
...
```
working.json ~160bytes
```json
{"a": {"c": 8, "b": 5}}
{"a": {"b": 7, "c": 6}}
{"a": {"c": 8, "b": 5}}
{"a": {"b": 7, "c": 6}}
{"a": {"c": 8, "b": 5}}
```
## Expected results
It should load the dataset from the json file without error.
## Actual results
It raises Exception `pyarrow.lib.ArrowNotImplementedError: Unsupported cast from struct<b: int64, c: int64> to struct using function cast_struct`
```
Traceback (most recent call last):
File "/Users/m/workspace/xxx/project/main.py", line 60, in <module>
dataset = load_dataset("json", data_files="result.json")
File "/opt/homebrew/Caskroom/miniforge/base/envs/xxx/lib/python3.9/site-packages/datasets/load.py", line 1627, in load_dataset
builder_instance.download_and_prepare(
File "/opt/homebrew/Caskroom/miniforge/base/envs/xxx/lib/python3.9/site-packages/datasets/builder.py", line 607, in download_and_prepare
self._download_and_prepare(
File "/opt/homebrew/Caskroom/miniforge/base/envs/xxx/lib/python3.9/site-packages/datasets/builder.py", line 697, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/opt/homebrew/Caskroom/miniforge/base/envs/xxx/lib/python3.9/site-packages/datasets/builder.py", line 1159, in _prepare_split
writer.write_table(table)
File "/opt/homebrew/Caskroom/miniforge/base/envs/xxx/lib/python3.9/site-packages/datasets/arrow_writer.py", line 428, in write_table
pa_table = pa.Table.from_arrays([pa_table[name] for name in self._schema.names], schema=self._schema)
File "pyarrow/table.pxi", line 1685, in pyarrow.lib.Table.from_arrays
File "pyarrow/table.pxi", line 630, in pyarrow.lib._sanitize_arrays
File "pyarrow/array.pxi", line 338, in pyarrow.lib.asarray
File "pyarrow/table.pxi", line 304, in pyarrow.lib.ChunkedArray.cast
File "/opt/homebrew/Caskroom/miniforge/base/envs/xxx/lib/python3.9/site-packages/pyarrow/compute.py", line 309, in cast
return call_function("cast", [arr], options)
File "pyarrow/_compute.pyx", line 528, in pyarrow._compute.call_function
File "pyarrow/_compute.pyx", line 327, in pyarrow._compute.Function.call
File "pyarrow/error.pxi", line 143, in pyarrow.lib.pyarrow_internal_check_status
File "pyarrow/error.pxi", line 120, in pyarrow.lib.check_status
pyarrow.lib.ArrowNotImplementedError: Unsupported cast from struct<b: int64, c: int64> to struct using function cast_struct
```
## Environment info
- `datasets` version: 1.14.0
- Platform: macOS-12.0.1-arm64-arm-64bit
- Python version: 3.9.7
- PyArrow version: 6.0.0
| false
|
1,049,662,746
|
https://api.github.com/repos/huggingface/datasets/issues/3246
|
https://github.com/huggingface/datasets/pull/3246
| 3,246
|
[tiny] fix typo in stream docs
|
closed
| 0
| 2021-11-10T10:40:02
| 2021-11-10T11:10:39
| 2021-11-10T11:10:39
|
verbiiyo
|
[] | null | true
|
1,048,726,062
|
https://api.github.com/repos/huggingface/datasets/issues/3245
|
https://github.com/huggingface/datasets/pull/3245
| 3,245
|
Fix load_from_disk temporary directory
|
closed
| 0
| 2021-11-09T15:15:15
| 2021-11-09T15:30:52
| 2021-11-09T15:30:51
|
lhoestq
|
[] |
`load_from_disk` uses `tempfile.TemporaryDirectory()` instead of our `get_temporary_cache_files_directory()` function. This can cause the temporary directory to be deleted before the dataset object is garbage collected.
In practice, it prevents anyone from using methods like `shuffle` on a dataset loaded this way, because it can't write the shuffled indices in a directory that doesn't exist anymore.
In this PR I switch to using `get_temporary_cache_files_directory()` and I update the tests.
cc @mariosasko since you worked on `get_temporary_cache_files_directory()`
| true
|
1,048,675,741
|
https://api.github.com/repos/huggingface/datasets/issues/3244
|
https://github.com/huggingface/datasets/pull/3244
| 3,244
|
Fix filter method for batched=True
|
closed
| 0
| 2021-11-09T14:30:59
| 2021-11-09T15:52:58
| 2021-11-09T15:52:57
|
thomasw21
|
[] | null | true
|
1,048,630,754
|
https://api.github.com/repos/huggingface/datasets/issues/3243
|
https://github.com/huggingface/datasets/pull/3243
| 3,243
|
Remove redundant isort module placement
|
closed
| 0
| 2021-11-09T13:50:30
| 2021-11-12T14:02:45
| 2021-11-12T14:02:45
|
mariosasko
|
[] |
`isort` can place modules by itself from [version 5.0.0](https://pycqa.github.io/isort/docs/upgrade_guides/5.0.0.html#module-placement-changes-known_third_party-known_first_party-default_section-etc) onwards, making the `known_first_party` and `known_third_party` fields in `setup.cfg` redundant (this is why our CI works, even though we haven't touched these options in a while).
| true
|
1,048,527,232
|
https://api.github.com/repos/huggingface/datasets/issues/3242
|
https://github.com/huggingface/datasets/issues/3242
| 3,242
|
Adding ANERcorp-CAMeLLab dataset
|
open
| 1
| 2021-11-09T12:04:04
| 2021-11-09T12:41:15
| null |
vitalyshalumov
|
[
"dataset request"
] | null | false
|
1,048,461,852
|
https://api.github.com/repos/huggingface/datasets/issues/3241
|
https://github.com/huggingface/datasets/pull/3241
| 3,241
|
Swap descriptions of v1 and raw-v1 configs of WikiText dataset and fix metadata
|
closed
| 0
| 2021-11-09T10:54:15
| 2022-02-14T15:46:00
| 2021-11-09T13:49:28
|
albertvillanova
|
[] |
Fix #3237, fix #795.
| true
|
1,048,376,021
|
https://api.github.com/repos/huggingface/datasets/issues/3240
|
https://github.com/huggingface/datasets/issues/3240
| 3,240
|
Couldn't reach data file for disaster_response_messages
|
closed
| 1
| 2021-11-09T09:26:42
| 2021-12-14T14:38:29
| 2021-12-14T14:38:29
|
pandya6988
|
[
"dataset bug"
] |
## Describe the bug
Following command gives an ConnectionError.
## Steps to reproduce the bug
```python
disaster = load_dataset('disaster_response_messages')
```
## Error
```
ConnectionError: Couldn't reach https://datasets.appen.com/appen_datasets/disaster_response_data/disaster_response_messages_training.csv
```
## Expected results
It should load dataset without an error
## 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:
- Platform: Google Colab
- Python version: 3.7
- PyArrow version:
| false
|
1,048,360,232
|
https://api.github.com/repos/huggingface/datasets/issues/3239
|
https://github.com/huggingface/datasets/issues/3239
| 3,239
|
Inconsistent performance of the "arabic_billion_words" dataset
|
open
| 0
| 2021-11-09T09:11:00
| 2021-11-09T09:11:00
| null |
vitalyshalumov
|
[
"bug"
] |
## Describe the bug
When downloaded from macine 1 the dataset is downloaded and parsed correctly.
When downloaded from machine two (which has a different cache directory),
the following script:
import datasets
from datasets import load_dataset
raw_dataset_elkhair_1 = load_dataset('arabic_billion_words', 'Alittihad', split="train",download_mode='force_redownload')
gives the following error:
**Downloading and preparing dataset arabic_billion_words/Alittihad (download: 332.13 MiB, generated: 1.49 GiB, post-processed: Unknown size, total: 1.82 GiB) to /root/.cache/huggingface/datasets/arabic_billion_words/Alittihad/1.1.0/687a1f963284c8a766558661375ea8f7ab3fa3633f8cd9c9f42a53ebe83bfe17...
Downloading: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 348M/348M [00:24<00:00, 14.0MB/s]
Traceback (most recent call last):
File ".../why_mismatch.py", line 3, in <module>
File "/opt/conda/lib/python3.8/site-packages/datasets/load.py", line 1632, in load_dataset
builder_instance.download_and_prepare(
File "/opt/conda/lib/python3.8/site-packages/datasets/builder.py", line 607, in download_and_prepare
self._download_and_prepare(
File "/opt/conda/lib/python3.8/site-packages/datasets/builder.py", line 709, in _download_and_prepare
verify_splits(self.info.splits, split_dict)
File "/opt/conda/lib/python3.8/site-packages/datasets/utils/info_utils.py", line 74, in verify_splits
raise NonMatchingSplitsSizesError(str(bad_splits))
datasets.utils.info_utils.NonMatchingSplitsSizesError: [{'expected': SplitInfo(name='train', num_bytes=1601790302, num_examples=349342, dataset_name='arabic_billion_words'), 'recorded': SplitInfo(name='train', num_bytes=0, num_examples=0, dataset_name='arabic_billion_words')}]**
Note that the package versions of datasets (1.15.1) and rarfile (4.0) are identical.
## Steps to reproduce the bug
import datasets
from datasets import load_dataset
raw_dataset_elkhair_1 = load_dataset('arabic_billion_words', 'Alittihad', split="train",download_mode='force_redownload')
# Sample code to reproduce the bug
## Expected results
Downloading and preparing dataset arabic_billion_words/Alittihad (download: 332.13 MiB, generated: 1.49 GiB, post-processed: Unknown size, total: 1.82 GiB) to .../.cache/huggingface/datasets/arabic_billion_words/Alittihad/1.1.0/687a1f963284c8a766558661375ea8f7ab3fa3633f8cd9c9f42a53ebe83bfe17...
Downloading: 100%|███████████████████████████| 348M/348M [00:22<00:00, 15.8MB/s]
Dataset arabic_billion_words downloaded and prepared to .../.cache/huggingface/datasets/arabic_billion_words/Alittihad/1.1.0/687a1f963284c8a766558661375ea8f7ab3fa3633f8cd9c9f42a53ebe83bfe17. Subsequent calls will reuse this data.
## 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. -->
Machine 1:
- `datasets` version: 1.15.1
- Platform: Linux-5.8.0-63-generic-x86_64-with-glibc2.29
- Python version: 3.8.10
- PyArrow version: 4.0.1
Machine 2 (the bugged one)
- `datasets` version: 1.15.1
- Platform: Linux-4.4.0-210-generic-x86_64-with-glibc2.10
- Python version: 3.8.8
- PyArrow version: 6.0.0
| false
|
1,048,226,086
|
https://api.github.com/repos/huggingface/datasets/issues/3238
|
https://github.com/huggingface/datasets/issues/3238
| 3,238
|
Reuters21578 Couldn't reach
|
closed
| 2
| 2021-11-09T06:08:56
| 2021-11-11T00:02:57
| 2021-11-11T00:02:57
|
TingNLP
|
[
"dataset bug"
] |
``## Adding a Dataset
- **Name:** *Reuters21578*
- **Description:** *ConnectionError: Couldn't reach https://kdd.ics.uci.edu/databases/reuters21578/reuters21578.tar.gz*
- **Data:** *https://huggingface.co/datasets/reuters21578*
`from datasets import load_dataset`
`dataset = load_dataset("reuters21578", 'ModLewis')`
ConnectionError: Couldn't reach https://kdd.ics.uci.edu/databases/reuters21578/reuters21578.tar.gz
And I try to request the link as follow:
`import requests`
`requests.head('https://kdd.ics.uci.edu/databases/reuters21578/reuters21578.tar.gz')`
SSLError: HTTPSConnectionPool(host='kdd.ics.uci.edu', port=443): Max retries exceeded with url: /databases/reuters21578/reuters21578.tar.gz (Caused by SSLError(SSLError(1, '[SSL: CERTIFICATE_VERIFY_FAILED] certificate verify failed (_ssl.c:852)'),))
This problem likes #575
What should I do ?
| false
|
1,048,165,525
|
https://api.github.com/repos/huggingface/datasets/issues/3237
|
https://github.com/huggingface/datasets/issues/3237
| 3,237
|
wikitext description wrong
|
closed
| 2
| 2021-11-09T04:06:52
| 2022-02-14T15:45:11
| 2021-11-09T13:49:28
|
hongyuanmei
|
[
"bug"
] |
## Describe the bug
Descriptions of the wikitext datasests are wrong.
## Steps to reproduce the bug
Please see: https://github.com/huggingface/datasets/blob/f6dcafce996f39b6a4bbe3a9833287346f4a4b68/datasets/wikitext/wikitext.py#L50
## Expected results
The descriptions for raw-v1 and v1 should be switched.
| false
|
1,048,026,358
|
https://api.github.com/repos/huggingface/datasets/issues/3236
|
https://github.com/huggingface/datasets/issues/3236
| 3,236
|
Loading of datasets changed in #3110 returns no examples
|
closed
| 7
| 2021-11-08T23:29:46
| 2021-11-09T16:46:05
| 2021-11-09T16:45:47
|
eladsegal
|
[
"bug"
] |
## Describe the bug
Loading of datasets changed in https://github.com/huggingface/datasets/pull/3110 returns no examples:
```python
DatasetDict({
train: Dataset({
features: ['id', 'title', 'abstract', 'full_text', 'qas'],
num_rows: 0
})
validation: Dataset({
features: ['id', 'title', 'abstract', 'full_text', 'qas'],
num_rows: 0
})
})
```
## Steps to reproduce the bug
Load any of the datasets that were changed in https://github.com/huggingface/datasets/pull/3110:
```python
from datasets import load_dataset
load_dataset("qasper")
# The problem only started with the commit of #3110
load_dataset("qasper", revision="b6469baa22c174b3906c631802a7016fedea6780")
```
## Expected results
```python
DatasetDict({
train: Dataset({
features: ['id', 'title', 'abstract', 'full_text', 'qas'],
num_rows: 888
})
validation: Dataset({
features: ['id', 'title', 'abstract', 'full_text', 'qas'],
num_rows: 281
})
})
```
Which can be received when specifying revision of the commit before https://github.com/huggingface/datasets/pull/3110:
```python
from datasets import load_dataset
load_dataset("qasper", revision="acfe2abda1ca79f0ce5c1896aa83b4b78af76b7d")
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.15.2.dev0 (master)
- Python version: 3.8.10
- PyArrow version: 3.0.0
| false
|
1,047,808,263
|
https://api.github.com/repos/huggingface/datasets/issues/3235
|
https://github.com/huggingface/datasets/pull/3235
| 3,235
|
Addd options to use updated bleurt checkpoints
|
closed
| 0
| 2021-11-08T18:53:54
| 2021-11-12T14:05:28
| 2021-11-12T14:05:28
|
jaehlee
|
[] |
Adds options to use newer recommended checkpoint (as of 2021/10/8) bleurt-20 and its distilled versions.
Updated checkpoints are described in https://github.com/google-research/bleurt/blob/master/checkpoints.md#the-recommended-checkpoint-bleurt-20
This change won't affect the default behavior of metrics/bleurt. It only adds option to load newer checkpoints as
`datasets.load_metric('bleurt', 'bleurt-20')`
`bluert-20` generates scores roughly between 0 and 1, which wasn't the case for the previous checkpoints.
| true
|
1,047,634,236
|
https://api.github.com/repos/huggingface/datasets/issues/3234
|
https://github.com/huggingface/datasets/pull/3234
| 3,234
|
Avoid PyArrow type optimization if it fails
|
closed
| 5
| 2021-11-08T16:10:27
| 2021-11-10T12:04:29
| 2021-11-10T12:04:28
|
mariosasko
|
[] |
Adds a new variable, `DISABLE_PYARROW_TYPES_OPTIMIZATION`, to `config.py` for easier control of the Arrow type optimization.
Fix #2206
| true
|
1,047,474,931
|
https://api.github.com/repos/huggingface/datasets/issues/3233
|
https://github.com/huggingface/datasets/pull/3233
| 3,233
|
Improve repository structure docs
|
closed
| 0
| 2021-11-08T13:51:35
| 2021-11-09T10:02:18
| 2021-11-09T10:02:17
|
lhoestq
|
[] |
Continuation of the documentation started in https://github.com/huggingface/datasets/pull/3221, taking into account @stevhliu 's comments
| true
|
1,047,361,573
|
https://api.github.com/repos/huggingface/datasets/issues/3232
|
https://github.com/huggingface/datasets/issues/3232
| 3,232
|
The Xsum datasets seems not able to download.
|
closed
| 4
| 2021-11-08T11:58:54
| 2021-11-09T15:07:16
| 2021-11-09T15:07:16
|
FYYFU
|
[
"bug"
] |
## Describe the bug
The download Link of the Xsum dataset provided in the repository is [Link](http://bollin.inf.ed.ac.uk/public/direct/XSUM-EMNLP18-Summary-Data-Original.tar.gz). It seems not able to download.
## Steps to reproduce the bug
```python
load_dataset('xsum')
```
## Actual results
``` python
raise ConnectionError("Couldn't reach {}".format(url))
ConnectionError: Couldn't reach http://bollin.inf.ed.ac.uk/public/direct/XSUM-EMNLP18-Summary-Data-Original.tar.gz
```
| false
|
1,047,170,906
|
https://api.github.com/repos/huggingface/datasets/issues/3231
|
https://github.com/huggingface/datasets/pull/3231
| 3,231
|
Group tests in multiprocessing workers by test file
|
closed
| 0
| 2021-11-08T08:46:03
| 2021-11-08T13:19:18
| 2021-11-08T08:59:44
|
albertvillanova
|
[] |
By grouping tests by test file, we make sure that all the tests in `test_load.py` are sent to the same worker.
Therefore, the fixture `hf_token` will be called only once (and from the same worker).
Related to: #3200.
Fix #3219.
| true
|
1,047,135,583
|
https://api.github.com/repos/huggingface/datasets/issues/3230
|
https://github.com/huggingface/datasets/pull/3230
| 3,230
|
Add full tagset to conll2003 README
|
closed
| 1
| 2021-11-08T08:06:04
| 2021-11-09T10:48:38
| 2021-11-09T10:40:58
|
BramVanroy
|
[] |
Even though it is possible to manually get the tagset list with
```python
dset.features[field_name].feature.names
```
I think it is useful to have an overview of the used tagset on the dataset card. This is particularly useful in light of the **dataset viewer**: the tags are encoded, so it is not immediately obvious what they are for a given sample. Adding a label-int mapping should make it easier for visitors to get a grasp of what they mean.
From user-experience perspective, I would urge the full tagsets to always be available in the README's but I understand that that would take a lot of work, probably. Perhaps it can be automated?
closes #3189
| true
|
1,046,706,425
|
https://api.github.com/repos/huggingface/datasets/issues/3229
|
https://github.com/huggingface/datasets/pull/3229
| 3,229
|
Fix URL in CITATION file
|
closed
| 0
| 2021-11-07T10:04:35
| 2021-11-07T10:04:46
| 2021-11-07T10:04:45
|
albertvillanova
|
[] |
Currently the BibTeX citation parsed from the CITATION file has wrong URL (it shows the repo URL instead of the proceedings paper URL):
```
@inproceedings{Lhoest_Datasets_A_Community_2021,
author = {Lhoest, Quentin and Villanova del Moral, Albert and von Platen, Patrick and Wolf, Thomas and Šaško, Mario and Jernite, Yacine and Thakur, Abhishek and Tunstall, Lewis and Patil, Suraj and Drame, Mariama and Chaumond, Julien and Plu, Julien and Davison, Joe and Brandeis, Simon and Sanh, Victor and Le Scao, Teven and Canwen Xu, Kevin and Patry, Nicolas and Liu, Steven and McMillan-Major, Angelina and Schmid, Philipp and Gugger, Sylvain and Raw, Nathan and Lesage, Sylvain and Lozhkov, Anton and Carrigan, Matthew and Matussière, Théo and von Werra, Leandro and Debut, Lysandre and Bekman, Stas and Delangue, Clément},
booktitle = {Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing: System Demonstrations},
month = {11},
pages = {175--184},
publisher = {Association for Computational Linguistics},
title = {{Datasets: A Community Library for Natural Language Processing}},
url = {https://github.com/huggingface/datasets},
year = {2021}
}
```
| true
|
1,046,702,143
|
https://api.github.com/repos/huggingface/datasets/issues/3228
|
https://github.com/huggingface/datasets/pull/3228
| 3,228
|
Add CITATION file
|
closed
| 0
| 2021-11-07T09:40:19
| 2021-11-07T09:51:47
| 2021-11-07T09:51:46
|
albertvillanova
|
[] |
Add CITATION file.
| true
|
1,046,667,845
|
https://api.github.com/repos/huggingface/datasets/issues/3227
|
https://github.com/huggingface/datasets/issues/3227
| 3,227
|
Error in `Json(datasets.ArrowBasedBuilder)` class
|
closed
| 3
| 2021-11-07T05:50:32
| 2021-11-09T19:09:15
| 2021-11-09T19:09:15
|
JunShern
|
[
"bug"
] |
## Describe the bug
When a json file contains a `text` field that is larger than the block_size, the JSON dataset builder fails.
## Steps to reproduce the bug
Create a folder that contains the following:
```
.
├── testdata
│ └── mydata.json
└── test.py
```
Please download [this file](https://github.com/huggingface/datasets/files/7491797/mydata.txt) as `mydata.json`. (The error does not occur in JSON files with shorter text, but it is reproducible when the text is long as in the file I provide)
:exclamation: :exclamation: GitHub doesn't allow me to upload JSON so this file is a TXT, and you should rename it to `.json`!
`test.py` simply contains:
```python
from datasets import load_dataset
my_dataset = load_dataset("testdata")
```
To reproduce the error, simply run
```
python test.py
```
## Expected results
The data should load correctly without error.
## Actual results
The dataset builder fails with:
```
Using custom data configuration testdata-d490389b8ab4fd82
Downloading and preparing dataset json/testdata to /home/junshern.chan/.cache/huggingface/datasets/json/testdata-d490389b8ab4fd82/0.0.0/3333a8af0db9764dfcff43a42ff26228f0f2e267f0d8a0a294452d188beadb34...
100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00, 2264.74it/s]
100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00, 447.01it/s]
Failed to read file '/home/junshern.chan/hf-json-bug/testdata/mydata.json' with error <class 'pyarrow.lib.ArrowInvalid'>: JSON parse error: Missing a name for object member. in row 0
Traceback (most recent call last):
File "test.py", line 28, in <module>
my_dataset = load_dataset("testdata")
File "/home/junshern.chan/.casio/miniconda/envs/hf-json-bug/lib/python3.8/site-packages/datasets/load.py", line 1632, in load_dataset
builder_instance.download_and_prepare(
File "/home/junshern.chan/.casio/miniconda/envs/hf-json-bug/lib/python3.8/site-packages/datasets/builder.py", line 607, in download_and_prepare
self._download_and_prepare(
File "/home/junshern.chan/.casio/miniconda/envs/hf-json-bug/lib/python3.8/site-packages/datasets/builder.py", line 697, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/home/junshern.chan/.casio/miniconda/envs/hf-json-bug/lib/python3.8/site-packages/datasets/builder.py", line 1156, in _prepare_split
for key, table in utils.tqdm(
File "/home/junshern.chan/.casio/miniconda/envs/hf-json-bug/lib/python3.8/site-packages/tqdm/std.py", line 1168, in __iter__
for obj in iterable:
File "/home/junshern.chan/.casio/miniconda/envs/hf-json-bug/lib/python3.8/site-packages/datasets/packaged_modules/json/json.py", line 146, in _generate_tables
raise ValueError(
ValueError: Not able to read records in the JSON file at /home/junshern.chan/hf-json-bug/testdata/mydata.json. You should probably indicate the field of the JSON file containing your records. This JSON file contain the following fields: ['text']. Select the correct one and provide it as `field='XXX'` to the dataset loading method.
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.15.1
- Platform: Linux-5.8.0-63-generic-x86_64-with-glibc2.17
- Python version: 3.8.12
- PyArrow version: 6.0.0
| false
|
1,046,584,518
|
https://api.github.com/repos/huggingface/datasets/issues/3226
|
https://github.com/huggingface/datasets/pull/3226
| 3,226
|
Fix paper BibTeX citation with proceedings reference
|
closed
| 0
| 2021-11-06T19:52:59
| 2021-11-07T07:05:28
| 2021-11-07T07:05:27
|
albertvillanova
|
[] |
Fix paper BibTeX citation with proceedings reference.
| true
|
1,046,530,493
|
https://api.github.com/repos/huggingface/datasets/issues/3225
|
https://github.com/huggingface/datasets/pull/3225
| 3,225
|
Update tatoeba to v2021-07-22
|
closed
| 4
| 2021-11-06T15:14:31
| 2021-11-12T11:13:13
| 2021-11-12T11:13:13
|
KoichiYasuoka
|
[] |
Tatoeba's latest version is v2021-07-22
| true
|
1,046,495,831
|
https://api.github.com/repos/huggingface/datasets/issues/3224
|
https://github.com/huggingface/datasets/pull/3224
| 3,224
|
User-pickling with dynamic sub-classing
|
closed
| 18
| 2021-11-06T12:08:24
| 2025-03-26T19:45:37
| 2025-03-26T19:45:36
|
BramVanroy
|
[] |
This is a continuation of the now closed PR in https://github.com/huggingface/datasets/pull/3206. The discussion there has shaped a new approach to do this.
In this PR, behavior of `pklregister` and `Pickler` is extended. Earlier, users were already able to register custom pickle functions. That is useful if they have objects that are not easily picklable with default methods. When one registers a custom function to a type, an object of that type will be pickled with the given function by `Pickler` which looks up the type in its `dispatch` table. The downside of this method, and of `pickle` in general, is that it is limited to direct type-matching and does not allow sub-classes. In many, default, cases that is not an issue. But when you are using external libraries where classes (e.g. parsers, models) are sub-classed this is not ideal.
```python
from datasets.fingerprint import Hasher
from datasets.utils.py_utils import pklregister
class BaseParser:
pass
class EnglishParser(BaseParser):
pass
@pklregister(BaseParser)
def custom_pkl_func(pickler, obj):
print(f"Called the custom pickle function for type {type(obj)}!")
# do something with the obj and ultimately save with the pickler
base = BaseParser()
en = EnglishParser()
# Hasher.hash uses the Pickler behind the scenes
# `custom_pkl_func` called for base
Hasher.hash(base)
# `custom_pkl_func` not called for en :-(
Hasher.hash(en)
```
In the example above we'd want to sub-class `EnglishParser` to be handled in the same way as its super-class `BaseParser`. This PR solves that by allowing for a keyword-argument `allow_subclasses` in `pklregister` (default: `False`).
```python
@pklregister(BaseParser, allow_subclasses=True)
```
When this option is enabled, we not only save the function in `Pickler.dispatch` but also save it in a custom table `Pickler.subclass_dispatch` **which allows us to dynamically add sub-classes of that class to the real dispatch table**. Then, if we want to pickle an object `obj` with `Pickler.dump()` (which ultimately will call `Pickler.save()`) we _first_ check whether any of the object's super-classes exist in `Pickler.sublcass_dispatch` and get the related custom pickle function. If we find one, we add the type of `obj` alongside the function to `Pickler.dispatch`. All of this happens at the start of the call to `Pickler.save()`. _Only then_ dill.Pickler's `save` will be called, which in turn will call `pickle._Pickler.save` which handles everything. Here, the `Pickler.dispatch` table will be used to look up custom pickler functions - and it now also includes the function for `obj`, which was copied from its super-class, which we added at the very start of our custom `Pickler.save()`.
For edge cases and, especially, for testing, a contextmanager class `TempPickleRegistry` is included that resets the pickle registry on exit to its previous state.
```python
with TempPickleRegistry():
@pklregister(MyObjClass)
def pickle_registry_test_false(pickler, obj):
pickler.save(obj.fancy_method())
some_obj = MyObjClass()
dumps(some_obj)
# `MyObjClass` is in Pickler.dispatch
# ... `MyObjClass` is _not_ in Pickler.dispatch anymore
```
closes https://github.com/huggingface/datasets/issues/3178
To Do
====
- [x] Write tests
- [ ] Write documentation/examples?
| true
|
1,046,445,507
|
https://api.github.com/repos/huggingface/datasets/issues/3223
|
https://github.com/huggingface/datasets/pull/3223
| 3,223
|
Update BibTeX entry
|
closed
| 0
| 2021-11-06T06:41:52
| 2021-11-06T07:06:38
| 2021-11-06T07:06:38
|
albertvillanova
|
[] |
Update BibTeX entry.
| true
|
1,046,299,725
|
https://api.github.com/repos/huggingface/datasets/issues/3222
|
https://github.com/huggingface/datasets/pull/3222
| 3,222
|
Add docs for audio processing
|
closed
| 2
| 2021-11-05T23:07:59
| 2021-11-24T16:32:08
| 2021-11-24T15:35:52
|
stevhliu
|
[
"documentation"
] |
This PR adds documentation for the `Audio` feature. It describes:
- The difference between loading `path` and `audio`, as well as use-cases/best practices for each of them.
- Resampling audio files with `cast_column`, and then calling `ds[0]["audio"]` to automatically decode and resample to the desired sampling rate.
- Resampling with `map`.
Preview [here](https://52969-250213286-gh.circle-artifacts.com/0/docs/_build/html/audio_process.html), let me know if I'm missing anything!
| true
|
1,045,890,512
|
https://api.github.com/repos/huggingface/datasets/issues/3221
|
https://github.com/huggingface/datasets/pull/3221
| 3,221
|
Resolve data_files by split name
|
closed
| 4
| 2021-11-05T14:07:35
| 2021-11-08T13:52:20
| 2021-11-05T17:49:58
|
lhoestq
|
[] |
As discussed in https://github.com/huggingface/datasets/issues/3027 we should automatically infer what file is supposed to go to what split automatically, based on filenames.
I added the support for different kinds of patterns, for both dataset repositories and local directories:
```
Input structure:
my_dataset_repository/
├── README.md
└── dataset.csv
Output patterns:
{"train": ["*"]}
```
```
Input structure:
my_dataset_repository/
├── README.md
├── train.csv
└── test.csv
my_dataset_repository/
├── README.md
└── data/
├── train.csv
└── test.csv
my_dataset_repository/
├── README.md
├── train_0.csv
├── train_1.csv
├── train_2.csv
├── train_3.csv
├── test_0.csv
└── test_1.csv
Output patterns:
{"train": ["*train*"], "test": ["*test*"]}
```
```
Input structure:
my_dataset_repository/
├── README.md
└── data/
├── train/
│ ├── shard_0.csv
│ ├── shard_1.csv
│ ├── shard_2.csv
│ └── shard_3.csv
└── test/
├── shard_0.csv
└── shard_1.csv
Output patterns:
{"train": ["*train*/*", "*train*/**/*"], "test": ["*test*/*", "*test*/**/*"]}
```
and also this pattern that allows to have custom split names, and that is the structure used by #3098 for `push_to_hub` (cc @LysandreJik ):
```
Input structure:
my_dataset_repository/
├── README.md
└── data/
├── train-00000-of-00003.csv
├── train-00001-of-00003.csv
├── train-00002-of-00003.csv
├── test-00000-of-00001.csv
├── random-00000-of-00003.csv
├── random-00001-of-00003.csv
└── random-00002-of-00003.csv
Output patterns:
{
"train": ["data/train-[0-9][0-9][0-9][0-9][0-9]-of-[0-9][0-9][0-9][0-9][0-9].*"],
"test": ["data/test-[0-9][0-9][0-9][0-9][0-9]-of-[0-9][0-9][0-9][0-9][0-9].*"],
"random": ["data/random-[0-9][0-9][0-9][0-9][0-9]-of-[0-9][0-9][0-9][0-9][0-9].*"],
}
```
You can check the documentation about structuring your repository [here](https://52640-250213286-gh.circle-artifacts.com/0/docs/_build/html/repository_structure.html). cc @stevhliu
Fix https://github.com/huggingface/datasets/issues/3027
Fix https://github.com/huggingface/datasets/issues/3212
In the future we can also add support for dataset configurations.
| true
|
1,045,549,029
|
https://api.github.com/repos/huggingface/datasets/issues/3220
|
https://github.com/huggingface/datasets/issues/3220
| 3,220
|
Add documentation about dataset viewer feature
|
open
| 1
| 2021-11-05T08:11:19
| 2023-09-25T11:48:38
| null |
albertvillanova
|
[
"enhancement",
"dataset-viewer"
] |
Add to the docs more details about the dataset viewer feature in the Hub.
CC: @julien-c
| false
|
1,045,095,000
|
https://api.github.com/repos/huggingface/datasets/issues/3219
|
https://github.com/huggingface/datasets/issues/3219
| 3,219
|
Eventual Invalid Token Error at setup of private datasets
|
closed
| 0
| 2021-11-04T18:50:45
| 2021-11-08T13:23:06
| 2021-11-08T08:59:43
|
albertvillanova
|
[
"bug"
] |
## Describe the bug
From time to time, there appear Invalid Token errors with private datasets:
- https://app.circleci.com/pipelines/github/huggingface/datasets/8520/workflows/d44629f2-4749-40f8-a657-50931d0b3434/jobs/52534
```
____________ ERROR at setup of test_load_streaming_private_dataset _____________
ValueError: Invalid token passed!
____ ERROR at setup of test_load_streaming_private_dataset_with_zipped_data ____
ValueError: Invalid token passed!
=========================== short test summary info ============================
ERROR tests/test_load.py::test_load_streaming_private_dataset - ValueError: I...
ERROR tests/test_load.py::test_load_streaming_private_dataset_with_zipped_data
```
- https://app.circleci.com/pipelines/github/huggingface/datasets/8557/workflows/a8383181-ba6d-4487-9d0a-f750b6dcb936/jobs/52763
```
____ ERROR at setup of test_load_streaming_private_dataset_with_zipped_data ____
[gw1] linux -- Python 3.6.15 /home/circleci/.pyenv/versions/3.6.15/bin/python3.6
hf_api = <huggingface_hub.hf_api.HfApi object at 0x7f4899bab908>
hf_token = 'vgNbyuaLNEBuGbgCEtSBCOcPjZnngJufHkTaZvHwkXKGkHpjBPwmLQuJVXRxBuaRzNlGjlMpYRPbthfHPFWXaaEDTLiqTTecYENxukRYVAAdpeApIUPxcgsowadkTkPj'
zip_csv_path = PosixPath('/tmp/pytest-of-circleci/pytest-0/popen-gw1/data16/dataset.csv.zip')
@pytest.fixture(scope="session")
def hf_private_dataset_repo_zipped_txt_data_(hf_api: HfApi, hf_token, zip_csv_path):
repo_name = "repo_zipped_txt_data-{}".format(int(time.time() * 10e3))
hf_api.create_repo(token=hf_token, name=repo_name, repo_type="dataset", private=True)
repo_id = f"{USER}/{repo_name}"
hf_api.upload_file(
token=hf_token,
path_or_fileobj=str(zip_csv_path),
path_in_repo="data.zip",
repo_id=repo_id,
> repo_type="dataset",
)
tests/hub_fixtures.py:68:
...
ValueError: Invalid token passed!
=========================== short test summary info ============================
ERROR tests/test_load.py::test_load_streaming_private_dataset_with_zipped_data
```
| false
|
1,045,032,313
|
https://api.github.com/repos/huggingface/datasets/issues/3218
|
https://github.com/huggingface/datasets/pull/3218
| 3,218
|
Fix code quality in riddle_sense dataset
|
closed
| 0
| 2021-11-04T17:43:20
| 2021-11-04T17:50:03
| 2021-11-04T17:50:02
|
albertvillanova
|
[] |
Fix trailing whitespace.
Fix #3217.
| true
|
1,045,029,710
|
https://api.github.com/repos/huggingface/datasets/issues/3217
|
https://github.com/huggingface/datasets/issues/3217
| 3,217
|
Fix code quality bug in riddle_sense dataset
|
closed
| 1
| 2021-11-04T17:40:32
| 2021-11-04T17:50:02
| 2021-11-04T17:50:02
|
albertvillanova
|
[
"bug"
] |
## Describe the bug
```
datasets/riddle_sense/riddle_sense.py:36:21: W291 trailing whitespace
```
| false
|
1,045,027,733
|
https://api.github.com/repos/huggingface/datasets/issues/3216
|
https://github.com/huggingface/datasets/pull/3216
| 3,216
|
Pin version exclusion for tensorflow incompatible with keras
|
closed
| 0
| 2021-11-04T17:38:06
| 2021-11-05T10:57:38
| 2021-11-05T10:57:37
|
albertvillanova
|
[] |
Once `tensorflow` version 2.6.2 is released:
- https://github.com/tensorflow/tensorflow/commit/c1867f3bfdd1042f694df7a9870be51ba80543cb
- https://pypi.org/project/tensorflow/2.6.2/
with the patch:
- tensorflow/tensorflow#52927
we can remove the temporary fix we introduced in:
- #3208
Fix #3209.
| true
|
1,045,011,207
|
https://api.github.com/repos/huggingface/datasets/issues/3215
|
https://github.com/huggingface/datasets/pull/3215
| 3,215
|
Small updates to to_tf_dataset documentation
|
closed
| 1
| 2021-11-04T17:22:01
| 2021-11-04T18:55:38
| 2021-11-04T18:55:37
|
Rocketknight1
|
[] |
I added a little more description about `to_tf_dataset` compared to just setting the format
| true
|
1,044,924,050
|
https://api.github.com/repos/huggingface/datasets/issues/3214
|
https://github.com/huggingface/datasets/issues/3214
| 3,214
|
Add ACAV100M Dataset
|
open
| 0
| 2021-11-04T15:59:58
| 2021-12-08T12:00:30
| null |
nateraw
|
[
"dataset request",
"vision"
] |
## Adding a Dataset
- **Name:** *ACAV100M*
- **Description:** *contains 100 million videos with high audio-visual correspondence, ideal for self-supervised video representation learning.*
- **Paper:** *https://arxiv.org/abs/2101.10803*
- **Data:** *https://github.com/sangho-vision/acav100m*
- **Motivation:** *The largest dataset (to date) for audio-visual learning.*
Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
| false
|
1,044,745,313
|
https://api.github.com/repos/huggingface/datasets/issues/3213
|
https://github.com/huggingface/datasets/pull/3213
| 3,213
|
Fix tuple_ie download url
|
closed
| 0
| 2021-11-04T13:09:07
| 2021-11-05T14:16:06
| 2021-11-05T14:16:05
|
mariosasko
|
[] |
Fix #3204
| true
|
1,044,640,967
|
https://api.github.com/repos/huggingface/datasets/issues/3212
|
https://github.com/huggingface/datasets/issues/3212
| 3,212
|
Sort files before loading
|
closed
| 1
| 2021-11-04T11:08:31
| 2021-11-05T17:49:58
| 2021-11-05T17:49:58
|
lvwerra
|
[
"enhancement"
] |
When loading a dataset that consists of several files (e.g. `my_data/data_001.json`, `my_data/data_002.json` etc.) they are not loaded in order when using `load_dataset("my_data")`.
This could lead to counter-intuitive results if, for example, the data files are sorted by date or similar since they would appear in different order in the `Dataset`.
The straightforward solution is to sort the list of files alphabetically before loading them.
cc @lhoestq
| false
|
1,044,617,913
|
https://api.github.com/repos/huggingface/datasets/issues/3211
|
https://github.com/huggingface/datasets/pull/3211
| 3,211
|
Fix disable_nullable default value to False
|
closed
| 0
| 2021-11-04T10:52:06
| 2021-11-04T11:08:21
| 2021-11-04T11:08:20
|
lhoestq
|
[] |
Currently the `disable_nullable` parameter is not consistent across all dataset transforms. For example it is `False` in `map` but `True` in `flatten_indices`.
This creates unexpected behaviors like this
```python
from datasets import Dataset, concatenate_datasets
d1 = Dataset.from_dict({"a": [0, 1, 2, 3]})
d2 = d1.filter(lambda x: x["a"] < 2).flatten_indices()
d1.data.schema == d2.data.schema # False
```
This can cause issues when concatenating datasets for example.
For consistency I set `disable_nullable` to `False` in `flatten_indices` and I fixed some docstrings
cc @SBrandeis
| true
|
1,044,611,471
|
https://api.github.com/repos/huggingface/datasets/issues/3210
|
https://github.com/huggingface/datasets/issues/3210
| 3,210
|
ConnectionError: Couldn't reach https://raw.githubusercontent.com/huggingface/datasets/1.15.1/datasets/wmt16/wmt16.py
|
closed
| 3
| 2021-11-04T10:47:26
| 2022-03-30T08:26:35
| 2022-03-30T08:26:35
|
xiuzhilu
|
[
"dataset bug"
] |
when I use python examples/pytorch/translation/run_translation.py --model_name_or_path examples/pytorch/translation/opus-mt-en-ro --do_train --do_eval --source_lang en --target_lang ro --dataset_name wmt16 --dataset_config_name ro-en --output_dir /tmp/tst-translation --per_device_train_batch_size=4 --per_device_eval_batch_size=4 --overwrite_output_dir --predict_with_generate to finetune translation model on huggingface, I get the issue"ConnectionError: Couldn't reach https://raw.githubusercontent.com/huggingface/datasets/1.15.1/datasets/wmt16/wmt16.py".But I can open the https://raw.githubusercontent.com/huggingface/datasets/1.15.1/datasets/wmt16/wmt16.py by using website. What should I do to solve the issue?
| false
|
1,044,505,771
|
https://api.github.com/repos/huggingface/datasets/issues/3209
|
https://github.com/huggingface/datasets/issues/3209
| 3,209
|
Unpin keras once TF fixes its release
|
closed
| 0
| 2021-11-04T09:15:32
| 2021-11-05T10:57:37
| 2021-11-05T10:57:37
|
albertvillanova
|
[] |
Related to:
- #3208
| false
|
1,044,504,093
|
https://api.github.com/repos/huggingface/datasets/issues/3208
|
https://github.com/huggingface/datasets/pull/3208
| 3,208
|
Pin keras version until TF fixes its release
|
closed
| 0
| 2021-11-04T09:13:32
| 2021-11-04T09:30:55
| 2021-11-04T09:30:54
|
albertvillanova
|
[] |
Fix #3207.
| true
|
1,044,496,389
|
https://api.github.com/repos/huggingface/datasets/issues/3207
|
https://github.com/huggingface/datasets/issues/3207
| 3,207
|
CI error: Another metric with the same name already exists in Keras 2.7.0
|
closed
| 0
| 2021-11-04T09:04:11
| 2021-11-04T09:30:54
| 2021-11-04T09:30:54
|
albertvillanova
|
[
"bug"
] |
## Describe the bug
Release of TensorFlow 2.7.0 contains an incompatibility with Keras. See:
- keras-team/keras#15579
This breaks our CI test suite: https://app.circleci.com/pipelines/github/huggingface/datasets/8493/workflows/055c7ae2-43bc-49b4-9f11-8fc71f35a25c/jobs/52363
| false
|
1,044,216,270
|
https://api.github.com/repos/huggingface/datasets/issues/3206
|
https://github.com/huggingface/datasets/pull/3206
| 3,206
|
[WIP] Allow user-defined hash functions via a registry
|
closed
| 13
| 2021-11-03T23:25:42
| 2021-11-05T12:38:11
| 2021-11-05T12:38:04
|
BramVanroy
|
[] |
Inspired by the discussion on hashing in https://github.com/huggingface/datasets/issues/3178#issuecomment-959016329, @lhoestq suggested that it would be neat to allow users more control over the hashing process. Specifically, it would be great if users can specify specific hashing functions depending on the **class** of the object.
As an example, we found in the linked topic that loaded spaCy models (`Language` objects) have different hashes when `dump`'d, but their byte representation with `Language.to_bytes()` _is_ deterministic. It would therefore be great if we could specify that for `Language` objects, the hasher should hash the objects `to_bytes()` return value instead of the object itself.
This PR adds a new, but tiny, dependency to manage the registry, namely [`catalogue`](https://github.com/explosion/catalogue).
Two files have been changed (apart from the added dependency in `setup.py`) and one file has been added.
**utils.registry** (added)
This file defines our custom Registry and builds a registry called "hashers". A Registry is basically dictionary from names (str) to functions. A function can be added to the registry by a decorator, e.g.
```python
@hashers.register(spacy.Language)
def hash_spacy_language(nlp):
return Hasher.hash(nlp.to_bytes())
```
You'll notice that `spacy.Language` is not a string, even though the registry holds a str->func mapping. To accomplish this with classes in a dynamic way, catalogue.Registry needed to be subclassed and modified as `DatasetsRegistry`. All methods that use a name as an input are now modified so that classes are deterministically converted in strings in such a way that we can later retrieve the actual class from the string (below).
**utils.py_utils** (modified)
Added two functions to deal with classes and their qualified names, that is, their full descriptive name including the module. On the one hand it allows us to retrieve a string from a given class, e.g. given `Module` class, return `torch.nn.Module` str. Conversly, a function is added to convert such a full qualified name into a class. For instance, given the string `torch.nn.Module`, return the `Module` class. These straightforward methods allow us to interchangeably use classes and strings without any needed user interaction - they can just register a class, and behind the scenes `DatasetsRegistry` converts these to deterministic strings.
**fingerprint** (modified)
Updated Hasher.hash so that if the object to hash is an instance of a class in the registry, the registered function is used to hash the object instead of the default behavior. To do so we iterate over the registry `hashers` and convert its keys (strings) into classes, and then we can use `isinstance`.
```python
# Check if the current object is an instance that is
# applicable to the user-defined hashers. If so, hash
# with the user-defined function
for full_module_name, func in hashers.get_all().items():
registered_cls = get_cls_from_qualname(full_module_name)
if isinstance(value, registered_cls):
return func(value)
```
**Putting it all together**
To test this, you can try the following example with spaCy. First install spaCy from source and checkout a specific commit.
```shell
git clone https://github.com/explosion/spaCy.git
cd spaCy/
git checkout cab9209c3dfcd1b75dfe5657f10e52c4d847a3cf
cd ..
git clone https://github.com/BramVanroy/datasets.git
cd datasets
git checkout registry
pip install -e .
pip install ../spaCy
spacy download en_core_web_sm
```
Now you can run the following script. By default it will use the custom hasher function for the Language object. You can enable the default behavior by commenting out `@hashers.register...`.
```python
import spacy
from datasets.fingerprint import Hasher
from datasets.utils.registry import hashers
# Register a function so that when the Hasher encounters a spacy.Language object
# it uses this custom function to hash instead of the default
@hashers.register(spacy.Language)
def hash_spacy_language(nlp):
return Hasher.hash(nlp.to_bytes())
def main():
print(hashers.get_all())
nlp = spacy.load("en_core_web_sm")
dump1 = Hasher.hash(nlp)
nlp = spacy.load("en_core_web_sm")
dump2 = Hasher.hash(nlp)
print(dump1)
# succeeds when using the registered custom function
# fails if using the default
assert dump1 == dump2
if __name__ == '__main__':
main()
```
To do
====
- The above is just a proof-of-concept. I am open to changes/suggestions
- Tests still need to be written
- We should consider whether we can make `DatasetsRegistry` very restrictive and ONLY allowing classes. That would make testing easier - otherwise we also need to test for other sorts of objects.
- Maybe the `hashers` definition is better suited in `fingerprint`?
- Documentation/examples need to be updated
- Not sure why the logger is not working in `hash()`
- `get_cls_from_qualname` might need a fail-safe: is it possible for a full_qualname to not have a module, and if so how do we deal with that?
| true
|
1,044,099,561
|
https://api.github.com/repos/huggingface/datasets/issues/3205
|
https://github.com/huggingface/datasets/pull/3205
| 3,205
|
Add Multidoc2dial Dataset
|
closed
| 4
| 2021-11-03T20:48:31
| 2021-11-24T17:32:49
| 2021-11-24T16:55:08
|
sivasankalpp
|
[] |
This PR adds the MultiDoc2Dial dataset introduced in this [paper](https://arxiv.org/pdf/2109.12595v1.pdf )
| true
|
1,043,707,307
|
https://api.github.com/repos/huggingface/datasets/issues/3204
|
https://github.com/huggingface/datasets/issues/3204
| 3,204
|
FileNotFoundError for TupleIE dataste
|
closed
| 3
| 2021-11-03T14:56:55
| 2021-11-05T15:51:15
| 2021-11-05T14:16:05
|
arda-vianai
|
[
"bug"
] |
Hi,
`dataset = datasets.load_dataset('tuple_ie', 'all')`
returns a FileNotFound error. Is the data not available?
Many thanks.
| false
|
1,043,552,766
|
https://api.github.com/repos/huggingface/datasets/issues/3203
|
https://github.com/huggingface/datasets/pull/3203
| 3,203
|
Updated: DaNE - updated URL for download
|
closed
| 3
| 2021-11-03T12:55:13
| 2021-11-04T13:14:36
| 2021-11-04T11:46:43
|
MalteHB
|
[] |
It seems that DaNLP has updated their download URLs and it therefore also needs to be updated in here...
| true
|
1,043,213,660
|
https://api.github.com/repos/huggingface/datasets/issues/3202
|
https://github.com/huggingface/datasets/issues/3202
| 3,202
|
Add mIoU metric
|
closed
| 1
| 2021-11-03T08:42:32
| 2022-06-01T17:39:05
| 2022-06-01T17:39:04
|
NielsRogge
|
[
"enhancement"
] |
**Is your feature request related to a problem? Please describe.**
Recently, some semantic segmentation models were added to HuggingFace Transformers, including [SegFormer](https://huggingface.co/transformers/model_doc/segformer.html) and [BEiT](https://huggingface.co/transformers/model_doc/beit.html).
Semantic segmentation (which is the task of labeling every pixel of an image with a corresponding class) is typically evaluated using the Mean Intersection and Union (mIoU). Together with the upcoming Image Feature, adding this metric could be very handy when creating example scripts to fine-tune any Transformer-based model on a semantic segmentation dataset.
An implementation can be found [here](https://github.com/open-mmlab/mmsegmentation/blob/504965184c3e6bc9ec43af54237129ef21981a5f/mmseg/core/evaluation/metrics.py#L132) for instance.
| false
|
1,043,209,142
|
https://api.github.com/repos/huggingface/datasets/issues/3201
|
https://github.com/huggingface/datasets/issues/3201
| 3,201
|
Add GSM8K dataset
|
closed
| 1
| 2021-11-03T08:36:44
| 2022-04-13T11:56:12
| 2022-04-13T11:56:11
|
NielsRogge
|
[
"dataset request"
] |
## Adding a Dataset
- **Name:** GSM8K (short for Grade School Math 8k)
- **Description:** GSM8K is a dataset of 8.5K high quality linguistically diverse grade school math word problems created by human problem writers.
- **Paper:** https://openai.com/blog/grade-school-math/
- **Data:** https://github.com/openai/grade-school-math
- **Motivation:** The dataset is useful to investigate the reasoning abilities of large Transformer models, such as GPT-3.
Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
| false
|
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