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https://api.github.com/repos/huggingface/datasets/issues/1856 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1856/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1856/comments | https://api.github.com/repos/huggingface/datasets/issues/1856/events | https://github.com/huggingface/datasets/issues/1856 | 805,360,200 | MDU6SXNzdWU4MDUzNjAyMDA= | 1,856 | load_dataset("amazon_polarity") NonMatchingChecksumError | [] | closed | false | null | 12 | 2021-02-10T10:00:56Z | 2022-03-15T13:55:24Z | 2022-03-15T13:55:23Z | null | Hi, it seems that loading the amazon_polarity dataset gives a NonMatchingChecksumError.
To reproduce:
```
load_dataset("amazon_polarity")
```
This will give the following error:
```
---------------------------------------------------------------------------
NonMatchingChecksumError Traceback (most recent call last)
<ipython-input-3-8559a03fe0f8> in <module>()
----> 1 dataset = load_dataset("amazon_polarity")
3 frames
/usr/local/lib/python3.6/dist-packages/datasets/utils/info_utils.py in verify_checksums(expected_checksums, recorded_checksums, verification_name)
37 if len(bad_urls) > 0:
38 error_msg = "Checksums didn't match" + for_verification_name + ":\n"
---> 39 raise NonMatchingChecksumError(error_msg + str(bad_urls))
40 logger.info("All the checksums matched successfully" + for_verification_name)
41
NonMatchingChecksumError: Checksums didn't match for dataset source files:
['https://drive.google.com/u/0/uc?id=0Bz8a_Dbh9QhbaW12WVVZS2drcnM&export=download']
``` | {
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} | https://api.github.com/repos/huggingface/datasets/issues/1856/timeline | null | completed | null | null | false | [
"Hi ! This issue may be related to #996 \r\nThis comes probably from the Quota Exceeded error from Google Drive.\r\nCan you try again tomorrow and see if you still have the error ?\r\n\r\nOn my side I didn't get any error today with `load_dataset(\"amazon_polarity\")`",
"+1 encountering this issue as well",
"@l... |
https://api.github.com/repos/huggingface/datasets/issues/1042 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1042/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1042/comments | https://api.github.com/repos/huggingface/datasets/issues/1042/events | https://github.com/huggingface/datasets/pull/1042 | 756,097,583 | MDExOlB1bGxSZXF1ZXN0NTMxNjk3NDU4 | 1,042 | Add Big Patent dataset | [] | closed | false | null | 2 | 2020-12-03T11:07:59Z | 2020-12-04T04:38:26Z | 2020-12-04T04:38:26Z | null | - More info on the dataset: https://evasharma.github.io/bigpatent/
- There's another raw version of the dataset available from tfds. However, they're quite large so I don't have the resources to fully test all the configs for that version yet. We'll try to add it later.
- ~Currently, there are no dummy data for this dataset yet as I'm facing some problems with generating them. I'm trying to add them later.~ | {
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"Looks like this PR include changes about many other files than the ones related to big patent.\r\nCould you create another branch and another PR ?",
"@lhoestq Just created a new PR here: https://github.com/huggingface/datasets/pull/1087"
] |
https://api.github.com/repos/huggingface/datasets/issues/3988 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3988/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3988/comments | https://api.github.com/repos/huggingface/datasets/issues/3988/events | https://github.com/huggingface/datasets/pull/3988 | 1,176,858,540 | PR_kwDODunzps400RGb | 3,988 | More consistent references in docs | [] | closed | false | null | 2 | 2022-03-22T14:18:41Z | 2022-03-22T17:06:32Z | 2022-03-22T16:50:44Z | null | Aligns the internal references with style discussed in https://github.com/huggingface/datasets/pull/3980.
cc @stevhliu | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"Looks good, thanks for working on this!"
] |
https://api.github.com/repos/huggingface/datasets/issues/5074 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5074/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5074/comments | https://api.github.com/repos/huggingface/datasets/issues/5074/events | https://github.com/huggingface/datasets/issues/5074 | 1,397,850,352 | I_kwDODunzps5TUYDw | 5,074 | Replace AssertionErrors with more meaningful errors | [
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"color": "7057ff",
"default": true,
"description": "Good for newcomers",
"id": 1935892877,
"name": "good first issue",
"node_id": "MDU6TGFiZWwxOTM1ODkyODc3",
"url": "https://api.github.com/repos/huggingface/datasets/labels/good%20first%20issue"
},
{
"color": "DF8D62",
"defa... | closed | false | null | 3 | 2022-10-05T14:03:55Z | 2022-10-07T14:33:11Z | 2022-10-07T14:33:11Z | null | Replace the AssertionErrors with more meaningful errors such as ValueError, TypeError, etc.
The files with AssertionErrors that need to be replaced:
```
src/datasets/arrow_reader.py
src/datasets/builder.py
src/datasets/utils/version.py
``` | {
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} | https://api.github.com/repos/huggingface/datasets/issues/5074/timeline | null | completed | null | null | false | [
"Hi, can I pick up this issue?",
"#self-assign",
"Looks like the top-level `datasource` directory was removed when https://github.com/huggingface/datasets/pull/4974 was merged, so there are 3 source files to fix."
] |
https://api.github.com/repos/huggingface/datasets/issues/3174 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3174/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3174/comments | https://api.github.com/repos/huggingface/datasets/issues/3174/events | https://github.com/huggingface/datasets/pull/3174 | 1,038,427,245 | PR_kwDODunzps4tyuQ_ | 3,174 | Asserts replaced by exceptions (huggingface#3171) | [] | closed | false | null | 1 | 2021-10-28T11:55:45Z | 2021-11-06T06:35:32Z | 2021-10-29T13:08:43Z | null | I've replaced two asserts with their proper exceptions following the guidelines described in issue #3171 by following the contributing guidelines.
PS: This is one of my first PRs, hoping I don't break anything! | {
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"Your first PR went smoothly, well done!\r\nYou are welcome to continue contributing to this project.\r\nGràcies, @joseporiolayats! 😉 "
] |
https://api.github.com/repos/huggingface/datasets/issues/3869 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3869/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3869/comments | https://api.github.com/repos/huggingface/datasets/issues/3869/events | https://github.com/huggingface/datasets/issues/3869 | 1,163,434,800 | I_kwDODunzps5FWJsw | 3,869 | Making the Hub the place for datasets in Portuguese | [
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"color": "e99695",
"default": false,
"description": "Requesting to add a new dataset",
"id": 2067376369,
"name": "dataset request",
"node_id": "MDU6TGFiZWwyMDY3Mzc2MzY5",
"url": "https://api.github.com/repos/huggingface/datasets/labels/dataset%20request"
}
] | open | false | null | 1 | 2022-03-09T03:06:18Z | 2022-03-09T09:04:09Z | null | null | Let's make Hugging Face Datasets the central hub for datasets in Portuguese :)
**Motivation**. Datasets are currently quite scattered and an open-source central point such as the Hugging Face Hub would be ideal to support the growth of the Portuguese speaking community.
What are some datasets in Portuguese worth integrating into the Hugging Face hub?
Special thanks to @augusnunes for his collaboration on identifying the first ones:
- [NILC - USP](http://www.nilc.icmc.usp.br/nilc/index.php/tools-and-resources).
Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
cc @osanseviero
| {
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} | https://api.github.com/repos/huggingface/datasets/issues/3869/timeline | null | null | null | null | false | [
"Hi @omarespejel! I think the philosophy for `datasets` issues is to create concrete issues with proposals to add a specific, individual dataset rather than umbrella issues for things such as datasets for a language, since we could end up with hundreds of issues (one per language). I see NILC - USP has many dataset... |
https://api.github.com/repos/huggingface/datasets/issues/2692 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2692/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2692/comments | https://api.github.com/repos/huggingface/datasets/issues/2692/events | https://github.com/huggingface/datasets/pull/2692 | 949,765,484 | MDExOlB1bGxSZXF1ZXN0Njk0NDE4MDg1 | 2,692 | Update BibTeX entry | [] | closed | false | null | 0 | 2021-07-21T14:23:35Z | 2021-07-21T15:31:41Z | 2021-07-21T15:31:40Z | null | Update BibTeX entry | {
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https://api.github.com/repos/huggingface/datasets/issues/3108 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3108/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3108/comments | https://api.github.com/repos/huggingface/datasets/issues/3108/events | https://github.com/huggingface/datasets/pull/3108 | 1,030,405,618 | PR_kwDODunzps4tY8ID | 3,108 | Add Google BLEU (aka GLEU) metric | [] | closed | false | null | 0 | 2021-10-19T14:48:38Z | 2021-10-25T14:07:04Z | 2021-10-25T14:07:04Z | null | This PR adds the NLTK implementation of Google BLEU metric. This is also a part of an effort to resolve an unfortunate naming collision between GLEU for machine translation and GLEU for grammatical error correction.
I used [this page](https://huggingface.co/docs/datasets/add_metric.html) for reference. Please, point me to the right direction if I missed anything. | {
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https://api.github.com/repos/huggingface/datasets/issues/4607 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4607/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4607/comments | https://api.github.com/repos/huggingface/datasets/issues/4607/events | https://github.com/huggingface/datasets/pull/4607 | 1,290,171,941 | PR_kwDODunzps46pLnd | 4,607 | Align more metadata with other repo types (models,spaces) | [] | closed | false | null | 5 | 2022-06-30T13:52:12Z | 2022-07-01T12:00:37Z | 2022-07-01T11:49:14Z | null | see also associated PR on the `datasets-tagging` Space: https://huggingface.co/spaces/huggingface/datasets-tagging/discussions/2 (to merge after this one is merged) | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"I just set a default value (None) for the deprecated licenses and languages fields, which should fix most of the CI failures.\r\n\r\nNote that the CI should still be red because you edited many dataset cards and they're still missing... |
https://api.github.com/repos/huggingface/datasets/issues/519 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/519/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/519/comments | https://api.github.com/repos/huggingface/datasets/issues/519/events | https://github.com/huggingface/datasets/issues/519 | 682,193,882 | MDU6SXNzdWU2ODIxOTM4ODI= | 519 | [BUG] Metrics throwing new error on master since 0.4.0 | [] | closed | false | null | 2 | 2020-08-19T21:29:15Z | 2022-06-02T16:41:01Z | 2020-08-19T22:04:40Z | null | The following error occurs when passing in references of type `List[List[str]]` to metrics like bleu.
Wasn't happening on 0.4.0 but happening now on master.
```
File "/usr/local/lib/python3.7/site-packages/nlp/metric.py", line 226, in compute
self.add_batch(predictions=predictions, references=references)
File "/usr/local/lib/python3.7/site-packages/nlp/metric.py", line 242, in add_batch
batch = self.info.features.encode_batch(batch)
File "/usr/local/lib/python3.7/site-packages/nlp/features.py", line 527, in encode_batch
encoded_batch[key] = [encode_nested_example(self[key], cast_to_python_objects(obj)) for obj in column]
File "/usr/local/lib/python3.7/site-packages/nlp/features.py", line 527, in <listcomp>
encoded_batch[key] = [encode_nested_example(self[key], cast_to_python_objects(obj)) for obj in column]
File "/usr/local/lib/python3.7/site-packages/nlp/features.py", line 456, in encode_nested_example
raise ValueError("Got a string but expected a list instead: '{}'".format(obj))
``` | {
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"Update - maybe this is only failing on bleu because I was not tokenizing inputs to the metric",
"Closing - seems to be just forgetting to tokenize. And found the helpful discussion in huggingface/evaluate#105 "
] |
https://api.github.com/repos/huggingface/datasets/issues/5870 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5870/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5870/comments | https://api.github.com/repos/huggingface/datasets/issues/5870/events | https://github.com/huggingface/datasets/issues/5870 | 1,712,156,282 | I_kwDODunzps5mDW56 | 5,870 | Behaviour difference between datasets.map and IterableDatasets.map | [] | open | false | null | 1 | 2023-05-16T14:32:57Z | 2023-05-16T14:36:05Z | null | null | ### Describe the bug
All the examples in all the docs mentioned throughout huggingface datasets correspond to datasets object, and not IterableDatasets object. At one point of time, they might have been in sync, but the code for datasets version >=2.9.0 is very different as compared to the docs.
I basically need to .map() a transform on images in an iterable dataset, which was made using a custom databuilder config.
This works very good in map-styles datasets, but the .map() fails in IterableDatasets, show behvaiour as such:
"pixel_values" key not found, KeyError in examples object/dict passed into transform function for map, which works fine with map style, even as batch.
In iterable style, the object/dict passed into map() paramter callable function is completely different as what is mentioned in all examples.
Please look into this. Thank you
My databuilder class is inherited as such:
def _info(self):
print ("Config: ",self.config.__dict__.keys())
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=datasets.Features(
{
"labels": datasets.Sequence(datasets.Value("uint16")),
# "labels_name": datasets.Value("string"),
# "pixel_values": datasets.Array3D(shape=(3, 1280, 960), dtype="float32"),
"pixel_values": datasets.Array3D(shape=(1280, 960, 3), dtype="uint8"),
"image_s3_path": datasets.Value("string"),
}
),
supervised_keys=None,
homepage="none",
citation="",
)
def _split_generators(self, dl_manager):
records_train = list(db.mini_set.find({'split':'train'},{'image_s3_path':1, 'ocwen_template_name':1}))[:10000]
records_val = list(db.mini_set.find({'split':'val'},{'image_s3_path':1, 'ocwen_template_name':1}))[:1000]
# print (len(records),self.config.num_shards)
# shard_size_train = len(records_train)//self.config.num_shards
# sharded_records_train = [records_train[i:i+shard_size_train] for i in range(0,len(records_train),shard_size_train)]
# shard_size_val = len(records_val)//self.config.num_shards
# sharded_records_val = [records_val[i:i+shard_size_val] for i in range(0,len(records_val),shard_size_val)]
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN, gen_kwargs={"records":records_train} # passing list of records, for sharding to take over
),
datasets.SplitGenerator(
name=datasets.Split.VALIDATION, gen_kwargs={"records":records_val} # passing list of records, for sharding to take over
),
]
def _generate_examples(self, records):
# print ("Generating examples for [{}] shards".format(len(shards)))
# initiate_db_connection()
# records = list(db.mini_set.find({'split':split},{'image_s3_path':1, 'ocwen_template_name':1}))[:10]
id_ = 0
# for records in shards:
for i,rec in enumerate(records):
img_local_path = fetch_file(rec['image_s3_path'],self.config.buffer_dir)
# t = self.config.processor(Image.open(img_local_path), random_padding=True, return_tensors="np").pixel_values.squeeze()
# print (t.shape, type(t),type(t[0][0][0]))
# sys.exit()
pvs = np.array(Image.open(img_local_path).resize((1280,960))) # image object is wxh, so resize as per that, numpy array of it is hxwxc, transposing to cxwxh
# pvs = self.config.processor(Image.open(img_local_path), random_padding=True, return_tensors="np").pixel_values.astype(np.float16).squeeze()
# print (type(pvs[0][0][0]))
lblids = self.config.processor.tokenizer('<s_class>'+rec['ocwen_template_name']+'</s_class>'+'</s>', add_special_tokens=False, padding=False, truncation=False, return_tensors="np")["input_ids"].squeeze(0) # take padding later, as per batch collating
# print (len(lblids),type(lblids[0]))
# print (type(pvs),pvs.shape,type(pvs[0][0][0]), type(lblids))
yield id_, {"labels":lblids,"pixel_values":pvs,"image_s3_path":rec['image_s3_path']}
id_+=1
os.remove(img_local_path)
and I load it inside my trainer script as such
`ds = load_dataset("/tmp/DonutDS/dataset/", split="train", streaming=True) # iterable dataset, where .map() falls`
or also as
`ds = load_from_disk('/tmp/DonutDS/dataset/') #map style dataset`
Thank you to the team for having such a great library, and for this bug fix in advance!
### Steps to reproduce the bug
Above config can allow one to reproduce the said bug
### Expected behavior
.map() should show some consistency b/w map-style and iterable-style datasets, or atleast the docs should address iterable-style datasets behaviour and examples. I honestly do not figure the use of such docs.
### Environment info
datasets==2.9.0
transformers==4.26.0 | {
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"PS - some work is definitely needed for 'special cases' docs, not explanations, just usages of 'functions' under mixture of special cases, like a combination of custom databuilder + iterable dataset for large size + dynamic .map() application."
] |
https://api.github.com/repos/huggingface/datasets/issues/4205 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4205/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4205/comments | https://api.github.com/repos/huggingface/datasets/issues/4205/events | https://github.com/huggingface/datasets/pull/4205 | 1,212,466,138 | PR_kwDODunzps42oVFE | 4,205 | Fix `convert_file_size_to_int` for kilobits and megabits | [] | closed | false | null | 1 | 2022-04-22T14:56:21Z | 2022-05-03T15:28:42Z | 2022-05-03T15:21:48Z | null | Minor change to fully align this function with the recent change in Transformers (https://github.com/huggingface/transformers/pull/16891) | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] |
https://api.github.com/repos/huggingface/datasets/issues/5444 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5444/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5444/comments | https://api.github.com/repos/huggingface/datasets/issues/5444/events | https://github.com/huggingface/datasets/issues/5444 | 1,550,185,071 | I_kwDODunzps5cZfJv | 5,444 | info messages logged as warnings | [] | closed | false | null | 7 | 2023-01-20T01:19:18Z | 2023-07-12T17:19:31Z | 2023-07-12T17:19:31Z | null | ### Describe the bug
Code in `datasets` is using `logger.warning` when it should be using `logger.info`.
Some of these are probably a matter of opinion, but I think anything starting with `logger.warning(f"Loading chached` clearly falls into the info category.
Definitions from the Python docs for reference:
* INFO: Confirmation that things are working as expected.
* WARNING: An indication that something unexpected happened, or indicative of some problem in the near future (e.g. ‘disk space low’). The software is still working as expected.
In theory, a user should be able to resolve things such that there are no warnings.
### Steps to reproduce the bug
Load any dataset that's already cached.
### Expected behavior
No output when log level is at the default WARNING level.
### Environment info
- `datasets` version: 2.8.0
- Platform: Linux-5.10.102.1-microsoft-standard-WSL2-x86_64-with-glibc2.31
- Python version: 3.10.8
- PyArrow version: 9.0.0
- Pandas version: 1.5.2 | {
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"Looks like a duplicate of https://github.com/huggingface/datasets/issues/1948. \r\n\r\nI also think these should be logged as INFO messages, but let's see what @lhoestq thinks.",
"It can be considered unexpected to see a `map` function return instantaneously. The warning is here to explain this case by mentionin... |
https://api.github.com/repos/huggingface/datasets/issues/114 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/114/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/114/comments | https://api.github.com/repos/huggingface/datasets/issues/114/events | https://github.com/huggingface/datasets/issues/114 | 618,611,310 | MDU6SXNzdWU2MTg2MTEzMTA= | 114 | Couldn't reach CNN/DM dataset | [] | closed | false | null | 1 | 2020-05-15T00:16:17Z | 2020-05-15T00:19:52Z | 2020-05-15T00:19:51Z | null | I can't get CNN / DailyMail dataset.
```python
import nlp
assert "cnn_dailymail" in [dataset.id for dataset in nlp.list_datasets()]
cnn_dm = nlp.load_dataset('cnn_dailymail')
```
[Colab notebook](https://colab.research.google.com/drive/1zQ3bYAVzm1h0mw0yWPqKAg_4EUlSx5Ex?usp=sharing)
gives following error :
```
ConnectionError: Couldn't reach https://s3.amazonaws.com/datasets.huggingface.co/nlp/cnn_dailymail/cnn_dailymail.py
``` | {
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} | https://api.github.com/repos/huggingface/datasets/issues/114/timeline | null | completed | null | null | false | [
"Installing from source (instead of Pypi package) solved the problem."
] |
https://api.github.com/repos/huggingface/datasets/issues/2417 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2417/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2417/comments | https://api.github.com/repos/huggingface/datasets/issues/2417/events | https://github.com/huggingface/datasets/pull/2417 | 903,956,071 | MDExOlB1bGxSZXF1ZXN0NjU1MTU3NTI4 | 2,417 | Make datasets PEP-561 compliant | [] | closed | false | null | 1 | 2021-05-27T16:16:17Z | 2021-05-28T13:10:10Z | 2021-05-28T13:09:16Z | null | Allows to type-check datasets with `mypy` when imported as a third-party library
PEP-561: https://www.python.org/dev/peps/pep-0561
MyPy doc on the subject: https://mypy.readthedocs.io/en/stable/installed_packages.html
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"This is super cool, I love that ❤️ "
] |
https://api.github.com/repos/huggingface/datasets/issues/4277 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4277/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4277/comments | https://api.github.com/repos/huggingface/datasets/issues/4277/events | https://github.com/huggingface/datasets/pull/4277 | 1,225,002,286 | PR_kwDODunzps43RZV9 | 4,277 | Enable label alignment for token classification datasets | [] | closed | false | null | 3 | 2022-05-04T07:15:16Z | 2022-05-06T15:42:15Z | 2022-05-06T15:36:31Z | null | This PR extends the `Dataset.align_labels_with_mapping()` method to support alignment of label mappings between datasets and models for token classification (e.g. NER).
Example of usage:
```python
from datasets import load_dataset
ner_ds = load_dataset("conll2003", split="train")
# returns [3, 0, 7, 0, 0, 0, 7, 0, 0]
ner_ds[0]["ner_tags"]
# hypothetical model mapping with O <--> B-LOC
label2id = {
"B-LOC": "0",
"B-MISC": "7",
"B-ORG": "3",
"B-PER": "1",
"I-LOC": "6",
"I-MISC": "8",
"I-ORG": "4",
"I-PER": "2",
"O": "5"
}
ner_aligned_ds = ner_ds.align_labels_with_mapping(label2id, "ner_tags")
# returns [3, 5, 7, 5, 5, 5, 7, 5, 5]
ner_aligned_ds[0]["ner_tags"]
```
Context: we need this in AutoTrain to automatically align datasets / models during evaluation. cc @abhishekkrthakur | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"Hmm, not sure why the Windows tests are failing with:\r\n\r\n```\r\nDid not find path entry C:\\tools\\miniconda3\\bin\r\nC:\\tools\\miniconda3\\envs\\py37\\python.exe: No module named pytest\r\n```\r\n\r\nEdit: running the CI again ... |
https://api.github.com/repos/huggingface/datasets/issues/712 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/712/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/712/comments | https://api.github.com/repos/huggingface/datasets/issues/712/events | https://github.com/huggingface/datasets/issues/712 | 714,242,316 | MDU6SXNzdWU3MTQyNDIzMTY= | 712 | Error in the notebooks/Overview.ipynb notebook | [] | closed | false | null | 2 | 2020-10-04T05:58:31Z | 2020-10-05T16:25:40Z | 2020-10-05T16:25:40Z | null | Hi,
I got the following error in **cell number 3** while exploring the **Overview.ipynb** notebook in google colab. I used the [link ](https://colab.research.google.com/github/huggingface/datasets/blob/master/notebooks/Overview.ipynb) provided in the main README file to open it in colab.
```python
# You can access various attributes of the datasets before downloading them
squad_dataset = list_datasets()[datasets.index('squad')]
pprint(squad_dataset.__dict__) # It's a simple python dataclass
```
Error message
```
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-5-8dc805c4949c> in <module>()
2 squad_dataset = list_datasets()[datasets.index('squad')]
3
----> 4 pprint(squad_dataset.__dict__) # It's a simple python dataclass
AttributeError: 'str' object has no attribute '__dict__'
```
The object `squad_dataset` is a `str` not a `dataclass` . | {
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"Do this:\r\n``` python\r\nsquad_dataset = list_datasets(with_details=True)[datasets.index('squad')]\r\npprint(squad_dataset.__dict__) # It's a simple python dataclass\r\n```",
"Thanks! This worked. I have created a PR to fix this in the notebook. "
] |
https://api.github.com/repos/huggingface/datasets/issues/3664 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3664/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3664/comments | https://api.github.com/repos/huggingface/datasets/issues/3664/events | https://github.com/huggingface/datasets/pull/3664 | 1,121,233,301 | PR_kwDODunzps4x7mg_ | 3,664 | [WIP] Return local paths to Common Voice | [] | closed | false | null | 19 | 2022-02-01T21:48:27Z | 2022-02-22T09:14:06Z | 2022-02-22T09:14:06Z | null | Fixes https://github.com/huggingface/datasets/issues/3663
This is a proposed way of returning the old local file-based generator while keeping the new streaming generator intact.
TODO:
- [ ] brainstorm a bit more on https://github.com/huggingface/datasets/issues/3663 to see if we can do better
- [ ] refactor the heck out of this PR to avoid completely copying the logic between the two generators | {
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"Cool thanks for giving it a try @anton-l ! \r\n\r\nWould be very much in favor of having \"real\" paths to the audio files again for non-streaming use cases. At the same time it would be nice to make the audio data loading script as understandable as possible so that the community can easily add audio datasets in ... |
https://api.github.com/repos/huggingface/datasets/issues/1189 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1189/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1189/comments | https://api.github.com/repos/huggingface/datasets/issues/1189/events | https://github.com/huggingface/datasets/pull/1189 | 757,831,035 | MDExOlB1bGxSZXF1ZXN0NTMzMTI4NjY1 | 1,189 | Add Dengue dataset in Filipino | [] | closed | false | null | 0 | 2020-12-06T02:50:47Z | 2020-12-07T15:38:58Z | 2020-12-07T15:38:58Z | null | This PR adds the Dengue Dataset, a benchmark dataset for low-resource multiclass classification, with 4,015 training, 500 testing, and 500 validation examples, each labeled as part of five classes. Each sample can be a part of multiple classes. Collected as tweets.
Link to the paper: https://ieeexplore.ieee.org/document/8459963
Link to the dataset/repo: https://github.com/jcblaisecruz02/Filipino-Text-Benchmarks
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https://api.github.com/repos/huggingface/datasets/issues/3776 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3776/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3776/comments | https://api.github.com/repos/huggingface/datasets/issues/3776/events | https://github.com/huggingface/datasets/issues/3776 | 1,146,932,871 | I_kwDODunzps5EXM6H | 3,776 | Allow download only some files from the Wikipedia dataset | [
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] | open | false | null | 1 | 2022-02-22T13:46:41Z | 2022-02-22T14:50:02Z | null | null | **Is your feature request related to a problem? Please describe.**
The Wikipedia dataset can be really big. This is a problem if you want to use it locally in a laptop with the Apache Beam `DirectRunner`. Even if your laptop have a considerable amount of memory (e.g. 32gb).
**Describe the solution you'd like**
I would like to use the `data_files` argument in the `load_dataset` function to define which file in the wikipedia dataset I would like to download. Thus, I can work with the dataset in a smaller machine using the Apache Beam `DirectRunner`.
**Describe alternatives you've considered**
I've tried to use the `simple` Wikipedia dataset. But it's in English and I would like to use Portuguese texts in my model.
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"Hi @jvanz, thank you for your proposal.\r\n\r\nIn fact, we are aware that it is very common the problem you mention. Because of that, we are currently working in implementing a new version of wikipedia on the Hub, with all data preprocessed (no need to use Apache Beam), from where you will be able to use `data_fil... |
https://api.github.com/repos/huggingface/datasets/issues/2540 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2540/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2540/comments | https://api.github.com/repos/huggingface/datasets/issues/2540/events | https://github.com/huggingface/datasets/pull/2540 | 928,433,892 | MDExOlB1bGxSZXF1ZXN0Njc2NDM5NTM1 | 2,540 | Remove task templates if required features are removed during `Dataset.map` | [] | closed | false | null | 0 | 2021-06-23T16:20:25Z | 2021-06-24T14:41:15Z | 2021-06-24T13:34:03Z | null | This PR fixes a bug reported by @craffel where removing a dataset's columns during `Dataset.map` triggered a `KeyError` because the `TextClassification` template tried to access the removed columns during `DatasetInfo.__post_init__`:
```python
from datasets import load_dataset
# `yelp_polarity` comes with a `TextClassification` template
ds = load_dataset("yelp_polarity", split="test")
ds
# Dataset({
# features: ['text', 'label'],
# num_rows: 38000
# })
# Triggers KeyError: 'label' - oh noes!
ds.map(lambda x: {"inputs": 0}, remove_columns=ds.column_names)
```
I wrote a unit test to make sure I could reproduce the error and then patched a fix. | {
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https://api.github.com/repos/huggingface/datasets/issues/5760 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5760/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5760/comments | https://api.github.com/repos/huggingface/datasets/issues/5760/events | https://github.com/huggingface/datasets/issues/5760 | 1,670,028,072 | I_kwDODunzps5jipso | 5,760 | Multi-image loading in Imagefolder dataset | [
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] | open | false | null | 2 | 2023-04-16T16:01:05Z | 2023-05-16T10:14:59Z | null | null | ### Feature request
Extend the `imagefolder` dataloading script to support loading multiple images per dataset entry.
This only really makes sense if a metadata file is present.
Currently you can use the following format (example `metadata.jsonl`:
```
{'file_name': 'path_to_image.png', 'metadata': ...}
...
```
which will return a batch with key `image` and any other metadata.
I would propose extending `file_name` to also accept a list of files, which would return a batch with key `images` and any other metadata.
### Motivation
This is useful for example in segmentation tasks in computer vision models, or in text-to-image models that also accept conditioning signals such as another image, feature map, or similar. Currently if I want to do this, I would need to write a custom dataset, rather than just use `imagefolder`.
### Your contribution
Would be open to doing a PR, but also happy for someone else to take it as I am not familiar with the datasets library. | {
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"Supporting this could be useful (I remember a use-case for this on the Hub). Do you agree @polinaeterna? \r\n\r\nImplementing this should be possible if we iterate over metadata files and build image/audio file paths instead of iterating over image/audio files and looking for the corresponding entries in metadata ... |
https://api.github.com/repos/huggingface/datasets/issues/5192 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5192/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5192/comments | https://api.github.com/repos/huggingface/datasets/issues/5192/events | https://github.com/huggingface/datasets/pull/5192 | 1,433,199,790 | PR_kwDODunzps5CD2BQ | 5,192 | Drop labels in Image and Audio folders if files are on different levels in directory or if there is only one label | [
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] | closed | false | null | 9 | 2022-11-02T14:01:41Z | 2022-11-15T16:32:53Z | 2022-11-15T16:31:07Z | null | Will close https://github.com/huggingface/datasets/issues/5153
Drop labels by default (`drop_labels=None`) when:
* there are files on different levels of directory hierarchy by checking their path depth
* all files are in the same directory (=only one label was inferred)
First one fixes cases like this:
```
repo
image3.jpg
image4.jpg
data
image1.jpg
image2.jpg
```
Second one fixes cases like this:
```
repo
image1.jpg
image2.jpg
image3.jpg
```
This is mostly to fix the viewer for people who just drop images in the Hub interface into the root dir.
I added tests for both of the cases on local and remote files. **I also changed data files for old test on drop_labels** (`test_generate_examples_drop_labels`). The files I provide to `test_generate_examples_drop_labels` now has "canonical" classification structure (two dirs) in order not to change the logic of the test (=not to check these two cases addressed in the PR).
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_5192). All of your documentation changes will be reflected on that endpoint.",
"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_5192). All of your documentation changes will be reflected on... |
https://api.github.com/repos/huggingface/datasets/issues/4069 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4069/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4069/comments | https://api.github.com/repos/huggingface/datasets/issues/4069/events | https://github.com/huggingface/datasets/pull/4069 | 1,186,790,578 | PR_kwDODunzps41VIMJ | 4,069 | Add support for metadata files to `imagefolder` | [] | closed | false | null | 7 | 2022-03-30T17:47:51Z | 2022-05-03T12:49:00Z | 2022-05-03T12:42:16Z | null | This PR adds support for metadata files to `imagefolder` to add an ability to specify image fields other than `image` and `label`, which are inferred from the directory structure in the loaded dataset.
To be parsed as an image metadata file, a file should be named `"info.csv"` and should have the following structure:
```
image_id,some_col1_name,some_col2_name
rel/path/to/image1.jpg,image1_col1_value,image1_col2_value
rel/path/to/image2.jpg,image2_col1_value,image2_col2_value
...
```
This is how the resolution works:
```
- path/to/imagefolder/directory
- info.csv
- 10.jpg # referenced as 10.jpg in "info.csv"
- Cat
- 0.jpg # referenced as Cat/0.jpg in "info.csv"
- 1.jpg # referenced as Cat/1.jpg in "info.csv"
- Dog
- 0.jpg # referenced as Dog/0.jpg in "info.csv"
- 1.jpg # referenced as Dog/1.jpg in "info.csv"
```
Open questions:
1. IMO it makes more sense to store image metadata as JSON Lines than CSV. CSV is sufficient for textual metadata but not the best for representing bounding boxes, for instance. Also, JSON Lines is more strict, which is good in this case (CSV supports various delimiters, the header line is optional, etc., so it's easier to enforce rules on JSON Lines that it's on CSV)
2. A better name for the `image_id` column, which contains image identifiers? Maybe `image_file` or `image_filename`?
3. WDYT about making `with_metadata=True` the default behavior if the loaded repo/directory contains an `info.csv` file?
An example repository: https://huggingface.co/datasets/mariosasko/PetImages. Can be loaded by installing `datasets` from the PR branch and running `load_dataset("mariosasko/PetImages", with_metadata=True)`.
cc: @abhishekkrthakur (this PR should address https://huggingface.slack.com/archives/C02JB9L6JKF/p1645450017434029?thread_ts=1645157416.389499&cid=C02JB9L6JKF)
TODOs:
- [x] Test
- [x] Metadata file nesting
```
- path/to/imagefolder/directory
- info.csv
- 10.jpg
- Cat
- info.csv # should have higher precedence in this directory than the top-level info.csv, but we choose the first "eligible" metadata file currently
- 0.jpg
- 1.jpg
``` | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"Love it !\r\n\r\n+1 to using JSON Lines rather than CSV. I've also seen image datasets for which JSON Lines was used.\r\n\r\nA `file_name` column sounds good as well, and it means we could reuse the same name for audio. And ok to che... |
https://api.github.com/repos/huggingface/datasets/issues/1900 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1900/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1900/comments | https://api.github.com/repos/huggingface/datasets/issues/1900/events | https://github.com/huggingface/datasets/pull/1900 | 810,512,488 | MDExOlB1bGxSZXF1ZXN0NTc1MTkxNTc3 | 1,900 | Issue #1895: Bugfix for string_to_arrow timestamp[ns] support | [] | closed | false | null | 1 | 2021-02-17T20:26:04Z | 2021-02-19T18:27:11Z | 2021-02-19T18:27:11Z | null | Should resolve https://github.com/huggingface/datasets/issues/1895
The main part of this PR adds additional parsing in `string_to_arrow` to convert the timestamp dtypes that result from `str(pa_type)` back into the pa.DataType TimestampType.
While adding unit-testing, I noticed that support for the double/float types also don't invert correctly, so I added them, which I believe would hypothetically make this section of `Value` redundant:
```
def __post_init__(self):
if self.dtype == "double": # fix inferred type
self.dtype = "float64"
if self.dtype == "float": # fix inferred type
self.dtype = "float32"
```
However, since I think Value.dtype is part of the public interface, removing that would result in a backward-incompatible change, so I didn't muck with that.
The rest of the PR consists of docstrings that I added while developing locally so I could keep track of which functions were supposed to be inverses of each other, and thought I'd include them initially in case you want to keep them around, but I'm happy to delete or remove any of them at your request! | {
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"OK! Thank you for the review - I will follow up with a separate PR for the comments here (https://github.com/huggingface/datasets/pull/1900#discussion_r578319725)!"
] |
https://api.github.com/repos/huggingface/datasets/issues/4997 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4997/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4997/comments | https://api.github.com/repos/huggingface/datasets/issues/4997/events | https://github.com/huggingface/datasets/pull/4997 | 1,379,430,711 | PR_kwDODunzps4_RrBU | 4,997 | Add support for parsing JSON files in array form | [] | closed | false | null | 1 | 2022-09-20T13:31:26Z | 2022-09-20T15:42:40Z | 2022-09-20T15:40:06Z | null | Support parsing JSON files in the array form (top-level object is an array). For simplicity, `json.load` is used for decoding. This means the entire file is loaded into memory. If requested, we can optimize this by introducing a param similar to `lines` in [`pandas.read_json`](https://pandas.pydata.org/docs/reference/api/pandas.read_json.html), which, if set to `True`, would allow us to read in chunks.
Fixes https://github.com/huggingface/datasets/issues/4963
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"_The documentation is not available anymore as the PR was closed or merged._"
] |
https://api.github.com/repos/huggingface/datasets/issues/5953 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5953/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5953/comments | https://api.github.com/repos/huggingface/datasets/issues/5953/events | https://github.com/huggingface/datasets/issues/5953 | 1,756,520,523 | I_kwDODunzps5osmBL | 5,953 | Bad error message when trying to download gated dataset | [] | closed | false | null | 8 | 2023-06-14T10:03:39Z | 2023-06-14T16:36:51Z | 2023-06-14T12:26:32Z | null | ### Describe the bug
When I attempt to download a model from the Hub that is gated without being logged in, I get a nice error message. E.g.:
E.g.
```sh
Repository Not Found for url: https://huggingface.co/api/models/DeepFloyd/IF-I-XL-v1.0.
Please make sure you specified the correct `repo_id` and `repo_type`.
If you are trying to access a private or gated repo, make sure you are authenticated.
Invalid username or password..
Will try to load from local cache.
```
If I do the same for a gated dataset on the Hub, I'm not gated a nice error message IMO:
```sh
File ~/hf/lib/python3.10/site-packages/fsspec/implementations/http.py:430, in HTTPFileSystem._info(self, url, **kwargs)
427 except Exception as exc:
428 if policy == "get":
429 # If get failed, then raise a FileNotFoundError
--> 430 raise FileNotFoundError(url) from exc
431 logger.debug(str(exc))
433 return {"name": url, "size": None, **info, "type": "file"}
FileNotFoundError: https://huggingface.co/datasets/mozilla-foundation/common_voice_13_0/resolve/main/n_shards.json
```
### Steps to reproduce the bug
```
huggingface-cli logout
```
and then:
```py
from datasets import load_dataset, Audio
# English
stream_data = load_dataset("mozilla-foundation/common_voice_13_0", "en", split="test", streaming=True)
stream_data = stream_data.cast_column("audio", Audio(sampling_rate=16000))
en_sample = next(iter(stream_data))["audio"]["array"]
# Swahili
stream_data = load_dataset("mozilla-foundation/common_voice_13_0", "sw", split="test", streaming=True)
stream_data = stream_data.cast_column("audio", Audio(sampling_rate=16000))
sw_sample = next(iter(stream_data))["audio"]["array"]
```
### Expected behavior
Better error message
### Environment info
Copy-and-paste the text below in your GitHub issue.
- `datasets` version: 2.12.0
- Platform: Linux-6.2.0-76060200-generic-x86_64-with-glibc2.35
- Python version: 3.10.6
- Huggingface_hub version: 0.16.0.dev0
- PyArrow version: 11.0.0
- Pandas version: 1.5.3
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"cc @sanchit-gandhi @Vaibhavs10 @lhoestq - this is mainly for demos that use Common Voice datasets as done here: https://github.com/facebookresearch/fairseq/tree/main/examples/mms#-transformers\r\n",
"Hi ! the error for me is\r\n\r\n```\r\nFileNotFoundError: Couldn't find a dataset script at /content/mozilla-foun... |
https://api.github.com/repos/huggingface/datasets/issues/145 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/145/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/145/comments | https://api.github.com/repos/huggingface/datasets/issues/145/events | https://github.com/huggingface/datasets/pull/145 | 619,480,549 | MDExOlB1bGxSZXF1ZXN0NDE4OTcxMjg0 | 145 | [AWS Tests] Follow-up PR from #144 | [] | closed | false | null | 0 | 2020-05-16T13:53:46Z | 2020-05-16T13:54:23Z | 2020-05-16T13:54:22Z | null | I forgot to add this line in PR #145 . | {
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https://api.github.com/repos/huggingface/datasets/issues/3001 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3001/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3001/comments | https://api.github.com/repos/huggingface/datasets/issues/3001/events | https://github.com/huggingface/datasets/pull/3001 | 1,014,024,982 | PR_kwDODunzps4sl0BY | 3,001 | Fix cast to Python scalar in Matthews Correlation metric | [] | closed | false | null | 0 | 2021-10-02T11:44:59Z | 2021-10-04T09:54:04Z | 2021-10-04T09:26:12Z | null | This PR is motivated by issue #2964.
The Matthews Correlation metric relies on sklearn's `matthews_corrcoef` function to compute the result. This function returns either `float` or `np.float64` (see the [source](https://github.com/scikit-learn/scikit-learn/blob/844b4be24d20fc42cc13b957374c718956a0db39/sklearn/metrics/_classification.py#L906-L909)). Obviously, calling `.item()` on the float value will fail, so I'm fixing this with the built-in `float()` function, which covers both cases. Surprisingly, on my machine, casting `np.float64` to a Python scalar with `float()` is even faster than with the `.item()` method. | {
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https://api.github.com/repos/huggingface/datasets/issues/5651 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5651/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5651/comments | https://api.github.com/repos/huggingface/datasets/issues/5651/events | https://github.com/huggingface/datasets/issues/5651 | 1,631,967,509 | I_kwDODunzps5hRdkV | 5,651 | expanduser in save_to_disk | [
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] | open | false | null | 4 | 2023-03-20T12:02:18Z | 2023-07-26T16:18:06Z | null | null | ### Describe the bug
save_to_disk() does not expand `~`
1. `dataset = load_datasets("any dataset")`
2. `dataset.save_to_disk("~/data")`
3. a folder named "~" created in current folder
4. FileNotFoundError is raised, because the expanded path does not exist (`/home/<user>/data`)
related issue https://github.com/huggingface/transformers/issues/10628
### Steps to reproduce the bug
As described above.
### Expected behavior
expanduser correctly
### Environment info
- datasets 2.10.1
- python 3.10 | {
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"`save_to_disk` should indeed expand `~`. Marking it as a \"good first issue\".",
"#self-assign\r\n\r\nFile path to code: \r\n\r\nhttps://github.com/huggingface/datasets/blob/2.13.0/src/datasets/arrow_dataset.py#L1364\r\n\r\n@RmZeta2718 I created a pull request for this issue. ",
"Hello, \r\nIt says `save_to_di... |
https://api.github.com/repos/huggingface/datasets/issues/5463 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5463/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5463/comments | https://api.github.com/repos/huggingface/datasets/issues/5463/events | https://github.com/huggingface/datasets/pull/5463 | 1,557,021,041 | PR_kwDODunzps5IiGWb | 5,463 | Imagefolder docs: mention support of CSV and ZIP | [] | closed | false | null | 3 | 2023-01-25T17:24:01Z | 2023-01-25T18:33:35Z | 2023-01-25T18:26:15Z | null | null | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==6.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | rea... |
https://api.github.com/repos/huggingface/datasets/issues/4562 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4562/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4562/comments | https://api.github.com/repos/huggingface/datasets/issues/4562/events | https://github.com/huggingface/datasets/issues/4562 | 1,283,779,557 | I_kwDODunzps5MhOvl | 4,562 | Dataset Viewer issue for allocine | [
{
"color": "E5583E",
"default": false,
"description": "Related to the dataset viewer on huggingface.co",
"id": 3470211881,
"name": "dataset-viewer",
"node_id": "LA_kwDODunzps7O1zsp",
"url": "https://api.github.com/repos/huggingface/datasets/labels/dataset-viewer"
}
] | closed | false | null | 5 | 2022-06-24T13:50:38Z | 2022-06-27T06:39:32Z | 2022-06-24T16:44:41Z | null | ### Link
https://huggingface.co/datasets/allocine
### Description
Not sure if this is a problem with `bz2` compression, but I thought these datasets could be streamed:
```
Status code: 400
Exception: AttributeError
Message: 'TarContainedFile' object has no attribute 'readable'
```
### Owner
No | {
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"I removed my assignment as @huggingface/datasets should be able to answer better than me\r\n",
"Let me have a look...",
"Thanks for the quick fix @albertvillanova ",
"Note that the underlying issue is that datasets containing TAR files are not streamable out of the box: they need being iterated with `dl_mana... |
https://api.github.com/repos/huggingface/datasets/issues/6006 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6006/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6006/comments | https://api.github.com/repos/huggingface/datasets/issues/6006/events | https://github.com/huggingface/datasets/issues/6006 | 1,788,855,582 | I_kwDODunzps5qn8Ue | 6,006 | NotADirectoryError when loading gigawords | [] | closed | false | null | 1 | 2023-07-05T06:23:41Z | 2023-07-05T06:31:02Z | 2023-07-05T06:31:01Z | null | ### Describe the bug
got `NotADirectoryError` whtn loading gigawords dataset
### Steps to reproduce the bug
When running
```
import datasets
datasets.load_dataset('gigaword')
```
Got the following exception:
```bash
Traceback (most recent call last): [0/1862]
File "/home/x/.conda/envs/dataproc/lib/python3.8/site-packages/datasets/builder.py", line 1629, in _prepare_split_single
for key, record in generator:
File "/home/x/.cache/huggingface/modules/datasets_modules/datasets/gigaword/ea83a8b819190acac5f2dae011fad51dccf269a0604ec5dd24795b
64efb424b6/gigaword.py", line 115, in _generate_examples
with open(src_path, encoding="utf-8") as f_d, open(tgt_path, encoding="utf-8") as f_s:
File "/home/x/.conda/envs/dataproc/lib/python3.8/site-packages/datasets/streaming.py", line 71, in wrapper
return function(*args, use_auth_token=use_auth_token, **kwargs)
File "/home/x/.conda/envs/dataproc/lib/python3.8/site-packages/datasets/download/streaming_download_manager.py", line 493, in xope
n
return open(main_hop, mode, *args, **kwargs)
NotADirectoryError: [Errno 20] Not a directory: '/home/x/.cache/huggingface/datasets/downloads/6da52431bb5124d90cf51a0187d2dbee9046e
89780c4be7599794a4f559048ec/org_data/train.src.txt'
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "gigaword.py", line 38, in <module>
main()
File "gigaword.py", line 35, in main
train, dev, test = dataset.generate_k_shot_data(k=32, seed=seed, path="../data/")
File "/home/x/MICL/preprocess/fewshot_gym_dataset.py", line 199, in generate_k_shot_data
dataset = self.load_dataset()
File "gigaword.py", line 29, in load_dataset
return datasets.load_dataset('gigaword')
File "/home/x/.conda/envs/dataproc/lib/python3.8/site-packages/datasets/load.py", line 1809, in load_dataset
builder_instance.download_and_prepare(
File "/home/x/.conda/envs/dataproc/lib/python3.8/site-packages/datasets/builder.py", line 909, in download_and_prepare
self._download_and_prepare(
File "/home/x/.conda/envs/dataproc/lib/python3.8/site-packages/datasets/builder.py", line 1670, in _download_and_prepare
super()._download_and_prepare(
File "/home/x/.conda/envs/dataproc/lib/python3.8/site-packages/datasets/builder.py", line 1004, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/home/x/.conda/envs/dataproc/lib/python3.8/site-packages/datasets/builder.py", line 1508, in _prepare_split
for job_id, done, content in self._prepare_split_single(
File "/home/x/.conda/envs/dataproc/lib/python3.8/site-packages/datasets/builder.py", line 1665, in _prepare_split_single
raise DatasetGenerationError("An error occurred while generating the dataset") from e
datasets.builder.DatasetGenerationError: An error occurred while generating the dataset
```
### Expected behavior
Download and process the dataset successfully
### Environment info
- `datasets` version: 2.13.1
- Platform: Linux-5.0.0-1032-azure-x86_64-with-glibc2.10
- Python version: 3.8.0
- Huggingface_hub version: 0.15.1
- PyArrow version: 12.0.1
- Pandas version: 2.0.3
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} | https://api.github.com/repos/huggingface/datasets/issues/6006/timeline | null | completed | null | null | false | [
"issue due to corrupted download files. resolved after cleaning download cache. sorry for any inconvinence."
] |
https://api.github.com/repos/huggingface/datasets/issues/4416 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4416/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4416/comments | https://api.github.com/repos/huggingface/datasets/issues/4416/events | https://github.com/huggingface/datasets/pull/4416 | 1,251,875,763 | PR_kwDODunzps44o7sF | 4,416 | Add LCCC dataset | [] | closed | false | null | 6 | 2022-05-29T12:27:19Z | 2022-06-15T10:28:59Z | 2022-06-02T09:13:46Z | null | Hi, I am trying to add a new dataset lccc.
All tests are passed. | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"Thank you very much for your help @albertvillanova .\r\n\r\nI think I have fixed all the comments.\r\n\r\nPlease let me know if this PR need further modification ;)",
"@albertvillanova Thank you very much for your kind help.\r\nThe... |
https://api.github.com/repos/huggingface/datasets/issues/1788 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1788/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1788/comments | https://api.github.com/repos/huggingface/datasets/issues/1788/events | https://github.com/huggingface/datasets/pull/1788 | 795,544,422 | MDExOlB1bGxSZXF1ZXN0NTYyODc1NzA2 | 1,788 | Doc2dial rc | [] | closed | false | null | 0 | 2021-01-27T23:51:00Z | 2021-01-28T18:46:13Z | 2021-01-28T18:46:13Z | null | {
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https://api.github.com/repos/huggingface/datasets/issues/2682 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2682/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2682/comments | https://api.github.com/repos/huggingface/datasets/issues/2682/events | https://github.com/huggingface/datasets/pull/2682 | 948,713,137 | MDExOlB1bGxSZXF1ZXN0NjkzNTE2NjU2 | 2,682 | Fix c4 expected files | [] | closed | false | null | 0 | 2021-07-20T14:29:31Z | 2021-07-20T14:38:11Z | 2021-07-20T14:38:10Z | null | Some files were not registered in the list of expected files to download
Fix https://github.com/huggingface/datasets/issues/2677 | {
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https://api.github.com/repos/huggingface/datasets/issues/2073 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2073/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2073/comments | https://api.github.com/repos/huggingface/datasets/issues/2073/events | https://github.com/huggingface/datasets/pull/2073 | 834,192,501 | MDExOlB1bGxSZXF1ZXN0NTk1MDYyMzQ2 | 2,073 | Fixes check of TF_AVAILABLE and TORCH_AVAILABLE | [] | closed | false | null | 0 | 2021-03-17T21:28:53Z | 2021-03-18T09:09:25Z | 2021-03-18T09:09:24Z | null | # What is this PR doing
This PR implements the checks if `Tensorflow` and `Pytorch` are available the same way as `transformers` does it. I added the additional checks for the different `Tensorflow` and `torch` versions. #2068 | {
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https://api.github.com/repos/huggingface/datasets/issues/1266 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1266/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1266/comments | https://api.github.com/repos/huggingface/datasets/issues/1266/events | https://github.com/huggingface/datasets/pull/1266 | 758,704,178 | MDExOlB1bGxSZXF1ZXN0NTMzODMyNTQ1 | 1,266 | removing unzipped hansards dummy data | [] | closed | false | null | 0 | 2020-12-07T17:31:16Z | 2020-12-07T17:32:29Z | 2020-12-07T17:32:29Z | null | which were added by mistake | {
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https://api.github.com/repos/huggingface/datasets/issues/1652 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1652/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1652/comments | https://api.github.com/repos/huggingface/datasets/issues/1652/events | https://github.com/huggingface/datasets/pull/1652 | 775,571,813 | MDExOlB1bGxSZXF1ZXN0NTQ2MjI1NTM1 | 1,652 | Update dataset cards from previous sprint | [] | closed | false | null | 0 | 2020-12-28T20:20:47Z | 2020-12-30T16:48:04Z | 2020-12-30T16:48:04Z | null | This PR updates the dataset cards/readmes for the 4 approved PRs I submitted in the previous sprint. | {
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https://api.github.com/repos/huggingface/datasets/issues/4006 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4006/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4006/comments | https://api.github.com/repos/huggingface/datasets/issues/4006/events | https://github.com/huggingface/datasets/pull/4006 | 1,179,367,195 | PR_kwDODunzps408YnW | 4,006 | Use audio feature in ASR task template | [] | closed | false | null | 1 | 2022-03-24T11:15:22Z | 2022-03-24T17:19:29Z | 2022-03-24T16:48:02Z | null | The AutomaticSpeechRecognition task template is outdated: it still uses the file path column as input instead of the audio column.
I changed that and updated all the datasets as well as the tests.
The only community dataset that will need to be updated is `facebook/multilingual_librispeech`. It has almost zero usage unfortunately (probably because users load the duplicate `multilingual_librispeech` directly instead), but it means we can update it.
(this makes me think that we should deprecate `multilingual_librispeech` it and redirect users to `facebook/multilingual_librispeech`).
This PR is also useful for the AudioFolder in https://github.com/huggingface/datasets/pull/3963 | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] |
https://api.github.com/repos/huggingface/datasets/issues/1465 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1465/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1465/comments | https://api.github.com/repos/huggingface/datasets/issues/1465/events | https://github.com/huggingface/datasets/pull/1465 | 761,538,931 | MDExOlB1bGxSZXF1ZXN0NTM2MTkxNjM1 | 1,465 | Add clean menyo20k data | [] | closed | false | null | 1 | 2020-12-10T19:22:00Z | 2020-12-14T10:30:21Z | 2020-12-14T10:30:21Z | null | New Clean PR for menyo20k_mt | {
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"@lhoestq rerun the tests "
] |
https://api.github.com/repos/huggingface/datasets/issues/2104 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2104/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2104/comments | https://api.github.com/repos/huggingface/datasets/issues/2104/events | https://github.com/huggingface/datasets/issues/2104 | 839,027,834 | MDU6SXNzdWU4MzkwMjc4MzQ= | 2,104 | Trouble loading wiki_movies | [] | closed | false | null | 2 | 2021-03-23T18:59:54Z | 2022-03-30T08:22:58Z | 2022-03-30T08:22:58Z | null | Hello,
I am trying to load_dataset("wiki_movies") and it gives me this error -
`FileNotFoundError: Couldn't find file locally at wiki_movies/wiki_movies.py, or remotely at https://raw.githubusercontent.com/huggingface/datasets/1.1.2/datasets/wiki_movies/wiki_movies.py or https://s3.amazonaws.com/datasets.huggingface.co/datasets/datasets/wiki_movies/wiki_movies.py`
Trying to do `python run_mlm.py \
--model_name_or_path roberta-base \
--dataset_name wiki_movies \` also gives the same error.
Is this something on my end? From what I can tell, this dataset was re-added by @lhoestq a few months ago.
Thank you! | {
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} | https://api.github.com/repos/huggingface/datasets/issues/2104/timeline | null | completed | null | null | false | [
"Hi ! `wiki_movies` was added in `datasets==1.2.0`. However it looks like you have `datasets==1.1.2`.\r\n\r\nTo use `wiki_movies`, please update `datasets` with\r\n```\r\npip install --upgrade datasets\r\n```",
"Thanks a lot! That solved it and I was able to upload a model trained on it as well :)"
] |
https://api.github.com/repos/huggingface/datasets/issues/66 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/66/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/66/comments | https://api.github.com/repos/huggingface/datasets/issues/66/events | https://github.com/huggingface/datasets/pull/66 | 614,748,552 | MDExOlB1bGxSZXF1ZXN0NDE1MjM5Njgy | 66 | [Datasets] ReadME | [] | closed | false | null | 0 | 2020-05-08T13:37:43Z | 2020-05-08T13:39:23Z | 2020-05-08T13:39:22Z | null | {
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https://api.github.com/repos/huggingface/datasets/issues/633 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/633/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/633/comments | https://api.github.com/repos/huggingface/datasets/issues/633/events | https://github.com/huggingface/datasets/issues/633 | 702,440,484 | MDU6SXNzdWU3MDI0NDA0ODQ= | 633 | Load large text file for LM pre-training resulting in OOM | [] | open | false | null | 27 | 2020-09-16T04:33:15Z | 2021-02-16T12:02:01Z | null | null | I tried to pretrain Longformer using transformers and datasets. But I got OOM issues with loading a large text file. My script is almost like this:
```python
from datasets import load_dataset
@dataclass
class DataCollatorForDatasetsLanguageModeling(DataCollatorForLanguageModeling):
"""
Data collator used for language modeling based on DataCollatorForLazyLanguageModeling
- collates batches of tensors, honoring their tokenizer's pad_token
- preprocesses batches for masked language modeling
"""
block_size: int = 512
def __call__(self, examples: List[dict]) -> Dict[str, torch.Tensor]:
examples = [example['text'] for example in examples]
batch, attention_mask = self._tensorize_batch(examples)
if self.mlm:
inputs, labels = self.mask_tokens(batch)
return {"input_ids": inputs, "labels": labels}
else:
labels = batch.clone().detach()
if self.tokenizer.pad_token_id is not None:
labels[labels == self.tokenizer.pad_token_id] = -100
return {"input_ids": batch, "labels": labels}
def _tensorize_batch(self, examples: List[str]) -> Tuple[torch.Tensor, torch.Tensor]:
if self.tokenizer._pad_token is None:
raise ValueError(
"You are attempting to pad samples but the tokenizer you are using"
f" ({self.tokenizer.__class__.__name__}) does not have one."
)
tensor_examples = self.tokenizer.batch_encode_plus(
[ex for ex in examples if ex],
max_length=self.block_size,
return_tensors="pt",
pad_to_max_length=True,
return_attention_mask=True,
truncation=True,
)
input_ids, attention_mask = tensor_examples["input_ids"], tensor_examples["attention_mask"]
return input_ids, attention_mask
dataset = load_dataset('text', data_files='train.txt',cache_dir="./", , split='train')
data_collator = DataCollatorForDatasetsLanguageModeling(tokenizer=tokenizer, mlm=True,
mlm_probability=0.15, block_size=tokenizer.max_len)
trainer = Trainer(model=model, args=args, data_collator=data_collator,
train_dataset=train_dataset, prediction_loss_only=True, )
trainer.train(model_path=model_path)
```
This train.txt is about 1.1GB and has 90k lines where each line is a sequence of 4k words.
During training, the memory usage increased fast as the following graph and resulted in OOM before the finish of training.
Could you please give me any suggestions on why this happened and how to fix it?
Thanks. | {
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"Not sure what could cause that on the `datasets` side. Could this be a `Trainer` issue ? cc @julien-c @sgugger ?",
"There was a memory leak issue fixed recently in master. You should install from source and see if it fixes your problem.",
"@lhoestq @sgugger Thanks for your comments. I have install from source ... |
https://api.github.com/repos/huggingface/datasets/issues/3621 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3621/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3621/comments | https://api.github.com/repos/huggingface/datasets/issues/3621/events | https://github.com/huggingface/datasets/issues/3621 | 1,112,720,434 | I_kwDODunzps5CUsQy | 3,621 | Consider adding `ipywidgets` as a dependency. | [
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] | closed | false | null | 4 | 2022-01-24T14:27:11Z | 2022-02-24T09:04:36Z | 2022-02-24T09:04:36Z | null | When I install `datasets` in a fresh virtualenv with jupyterlab I always see this error.
```
ImportError: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html
```
It's a bit of a nuisance, because I need to run shut down the jupyterlab server in order to install the required dependency. Might it be an option to just include it as a dependency here? | {
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"Hi! We use `tqdm` to display progress bars, so I suggest you open this issue in their repo.",
"It depends on how you use `tqdm`, no? \r\n\r\nDoesn't this library import via; \r\n\r\n```\r\nfrom tqdm.notebook import tqdm\r\n```",
"Hi! Sorry for the late reply. We import `tqdm` as `from tqdm.auto import tqdm`, w... |
https://api.github.com/repos/huggingface/datasets/issues/6026 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6026/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6026/comments | https://api.github.com/repos/huggingface/datasets/issues/6026/events | https://github.com/huggingface/datasets/pull/6026 | 1,802,929,222 | PR_kwDODunzps5VanI8 | 6,026 | Fix style with ruff 0.0.278 | [] | closed | false | null | 3 | 2023-07-13T12:34:24Z | 2023-07-13T12:46:26Z | 2023-07-13T12:37:01Z | null | null | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6026). All of your documentation changes will be reflected on that endpoint.",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchma... |
https://api.github.com/repos/huggingface/datasets/issues/3660 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3660/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3660/comments | https://api.github.com/repos/huggingface/datasets/issues/3660/events | https://github.com/huggingface/datasets/pull/3660 | 1,120,982,671 | PR_kwDODunzps4x6xr8 | 3,660 | Change HTTP links to HTTPS | [] | open | false | null | 0 | 2022-02-01T17:12:51Z | 2022-09-21T15:16:32Z | null | null | I tested the links. I also fixed some typos.
Originally from #3489 | {
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https://api.github.com/repos/huggingface/datasets/issues/1902 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1902/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1902/comments | https://api.github.com/repos/huggingface/datasets/issues/1902/events | https://github.com/huggingface/datasets/pull/1902 | 810,931,171 | MDExOlB1bGxSZXF1ZXN0NTc1NTQwMDM1 | 1,902 | Fix setimes_2 wmt urls | [] | closed | false | null | 0 | 2021-02-18T09:42:26Z | 2021-02-18T09:55:41Z | 2021-02-18T09:55:41Z | null | Continuation of #1901
Some other urls were missing https | {
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https://api.github.com/repos/huggingface/datasets/issues/4930 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4930/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4930/comments | https://api.github.com/repos/huggingface/datasets/issues/4930/events | https://github.com/huggingface/datasets/pull/4930 | 1,362,193,587 | PR_kwDODunzps4-Yflc | 4,930 | Add cc-by-nc-2.0 to list of licenses | [] | closed | false | null | 5 | 2022-09-05T15:37:32Z | 2022-09-06T16:43:32Z | 2022-09-05T17:01:04Z | null | This PR adds the `cc-by-nc-2.0` to the list of licenses because it is required by `scifact` dataset: https://github.com/allenai/scifact/blob/master/LICENSE.md | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"this list needs to be kept in sync with the ones in moon-landing and hub-docs :)",
"@julien-c don't you think it might be better to a have a single file (source of truth) in one of the repos and then use it in every other repo, ins... |
https://api.github.com/repos/huggingface/datasets/issues/3025 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3025/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3025/comments | https://api.github.com/repos/huggingface/datasets/issues/3025/events | https://github.com/huggingface/datasets/pull/3025 | 1,016,061,222 | PR_kwDODunzps4srsgG | 3,025 | Fix Windows test suite | [] | closed | false | null | 0 | 2021-10-05T08:55:22Z | 2021-10-05T09:58:28Z | 2021-10-05T09:58:27Z | null | Try a hotfix to restore Windows test suite.
Fix #3024. | {
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https://api.github.com/repos/huggingface/datasets/issues/2373 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2373/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2373/comments | https://api.github.com/repos/huggingface/datasets/issues/2373/events | https://github.com/huggingface/datasets/issues/2373 | 894,499,909 | MDU6SXNzdWU4OTQ0OTk5MDk= | 2,373 | Loading dataset from local path | [] | closed | false | null | 1 | 2021-05-18T15:20:50Z | 2021-05-18T15:36:36Z | 2021-05-18T15:36:35Z | null | I'm trying to load a local dataset with the code below
```
ds = datasets.load_dataset('my_script.py',
data_files='corpus.txt',
data_dir='/data/dir',
cache_dir='.')
```
But internally a BuilderConfig is created, which tries to use getmtime on the data_files string, without using data_dir. Is this a bug or am I not using the load_dataset correctly?
https://github.com/huggingface/datasets/blob/bc61954083f74e6460688202e9f77dde2475319c/src/datasets/builder.py#L153 | {
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"Version below works, checked again in the docs, and data_files should be a path.\r\n```\r\nds = datasets.load_dataset('my_script.py', \r\n data_files='/data/dir/corpus.txt', \r\n cache_dir='.')\r\n```"
] |
https://api.github.com/repos/huggingface/datasets/issues/2114 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2114/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2114/comments | https://api.github.com/repos/huggingface/datasets/issues/2114/events | https://github.com/huggingface/datasets/pull/2114 | 841,207,878 | MDExOlB1bGxSZXF1ZXN0NjAwOTc1MTA3 | 2,114 | Support for legal NLP datasets (EURLEX, ECtHR cases and EU-REG-IR) | [] | closed | false | null | 2 | 2021-03-25T18:40:17Z | 2021-03-31T10:38:50Z | 2021-03-31T10:38:50Z | null | Add support for two legal NLP datasets:
- EURLEX (https://www.aclweb.org/anthology/P19-1636/)
- ECtHR cases (https://arxiv.org/abs/2103.13084)
- EU-REG-IR (https://arxiv.org/abs/2101.10726) | {
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"> Awesome thank you :)\r\n> This is really cool\r\n> \r\n> I left a few comments.\r\n> \r\n> Also it looks like the dummy data are quite big (100-200KB each). Can you try to reduce their sizes please ? For example I noticed that all the jsonl files inside the `dummy_data.zip` files have 20 lines. Can you only keep... |
https://api.github.com/repos/huggingface/datasets/issues/1257 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1257/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1257/comments | https://api.github.com/repos/huggingface/datasets/issues/1257/events | https://github.com/huggingface/datasets/pull/1257 | 758,550,490 | MDExOlB1bGxSZXF1ZXN0NTMzNzA2NDQy | 1,257 | Add Swahili news classification dataset | [] | closed | false | null | 0 | 2020-12-07T14:15:13Z | 2020-12-08T14:44:19Z | 2020-12-08T14:44:19Z | null | Add Swahili news classification dataset | {
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https://api.github.com/repos/huggingface/datasets/issues/3840 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3840/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3840/comments | https://api.github.com/repos/huggingface/datasets/issues/3840/events | https://github.com/huggingface/datasets/pull/3840 | 1,161,183,773 | PR_kwDODunzps40B8eu | 3,840 | Pin responses to fix CI for Windows | [] | closed | false | null | 1 | 2022-03-07T10:06:53Z | 2022-03-07T10:12:36Z | 2022-03-07T10:07:24Z | null | Temporarily fix CI for Windows by pinning `responses`.
See: https://app.circleci.com/pipelines/github/huggingface/datasets/10292/workflows/83de4a55-bff7-43ec-96f7-0c335af5c050/jobs/63355
Fix: #3839 | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3840). All of your documentation changes will be reflected on that endpoint."
] |
https://api.github.com/repos/huggingface/datasets/issues/4533 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4533/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4533/comments | https://api.github.com/repos/huggingface/datasets/issues/4533/events | https://github.com/huggingface/datasets/issues/4533 | 1,277,211,490 | I_kwDODunzps5MILNi | 4,533 | Timestamp not returned as datetime objects in streaming mode | [
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] | closed | false | null | 0 | 2022-06-20T17:28:47Z | 2022-06-22T16:29:09Z | 2022-06-22T16:29:09Z | null | As reported in (internal) https://github.com/huggingface/datasets-server/issues/397
```python
>>> from datasets import load_dataset
>>> dataset = load_dataset("ett", name="h2", split="test", streaming=True)
>>> d = next(iter(dataset))
>>> d['start']
Timestamp('2016-07-01 00:00:00')
```
while loading in non-streaming mode it returns `datetime.datetime(2016, 7, 1, 0, 0)` | {
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https://api.github.com/repos/huggingface/datasets/issues/668 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/668/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/668/comments | https://api.github.com/repos/huggingface/datasets/issues/668/events | https://github.com/huggingface/datasets/issues/668 | 708,310,956 | MDU6SXNzdWU3MDgzMTA5NTY= | 668 | OverflowError when slicing with an array containing negative ids | [] | closed | false | null | 0 | 2020-09-24T16:27:14Z | 2020-09-28T14:42:19Z | 2020-09-28T14:42:19Z | null | ```python
from datasets import Dataset
d = ds.Dataset.from_dict({"a": range(10)})
print(d[0])
# {'a': 0}
print(d[-1])
# {'a': 9}
print(d[[0, -1]])
# OverflowError
```
results in
```
---------------------------------------------------------------------------
OverflowError Traceback (most recent call last)
<ipython-input-5-863dc3555598> in <module>
----> 1 d[[0, -1]]
~/Desktop/hf/nlp/src/datasets/arrow_dataset.py in __getitem__(self, key)
1070 format_columns=self._format_columns,
1071 output_all_columns=self._output_all_columns,
-> 1072 format_kwargs=self._format_kwargs,
1073 )
1074
~/Desktop/hf/nlp/src/datasets/arrow_dataset.py in _getitem(self, key, format_type, format_columns, output_all_columns, format_kwargs)
1025 indices = key
1026
-> 1027 indices_array = pa.array([int(i) for i in indices], type=pa.uint64())
1028
1029 # Check if we need to convert indices
~/.virtualenvs/hf-datasets/lib/python3.7/site-packages/pyarrow/array.pxi in pyarrow.lib.array()
~/.virtualenvs/hf-datasets/lib/python3.7/site-packages/pyarrow/array.pxi in pyarrow.lib._sequence_to_array()
OverflowError: can't convert negative value to unsigned int
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/576 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/576/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/576/comments | https://api.github.com/repos/huggingface/datasets/issues/576/events | https://github.com/huggingface/datasets/pull/576 | 694,348,645 | MDExOlB1bGxSZXF1ZXN0NDgwNzM3NDQ1 | 576 | Fix the code block in doc | [] | closed | false | null | 1 | 2020-09-06T11:40:55Z | 2020-09-07T07:37:32Z | 2020-09-07T07:37:18Z | null | {
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"thanks :)"
] | |
https://api.github.com/repos/huggingface/datasets/issues/5460 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5460/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5460/comments | https://api.github.com/repos/huggingface/datasets/issues/5460/events | https://github.com/huggingface/datasets/pull/5460 | 1,555,387,532 | PR_kwDODunzps5Icn9C | 5,460 | Document that removing all the columns returns an empty document and the num_row is lost | [] | closed | false | null | 4 | 2023-01-24T17:33:38Z | 2023-01-25T16:11:10Z | 2023-01-25T16:04:03Z | null | null | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==6.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | rea... |
https://api.github.com/repos/huggingface/datasets/issues/2532 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2532/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2532/comments | https://api.github.com/repos/huggingface/datasets/issues/2532/events | https://github.com/huggingface/datasets/issues/2532 | 927,063,196 | MDU6SXNzdWU5MjcwNjMxOTY= | 2,532 | Tokenizer's normalization preprocessor cause misalignment in return_offsets_mapping for tokenizer classification task | [
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}
] | closed | false | null | 2 | 2021-06-22T10:08:18Z | 2021-06-23T05:17:25Z | 2021-06-23T05:17:25Z | null | [This colab notebook](https://colab.research.google.com/drive/151gKyo0YIwnlznrOHst23oYH_a3mAe3Z?usp=sharing) implements a token classification input pipeline extending the logic from [this hugging example](https://huggingface.co/transformers/custom_datasets.html#tok-ner).
The pipeline works fine with most instance in different languages, but unfortunately, [the Japanese Kana ligature (a form of abbreviation? I don't know Japanese well)](https://en.wikipedia.org/wiki/Kana_ligature) break the alignment of `return_offsets_mapping`:
Without the try catch block, it riase `ValueError: NumPy boolean array indexing assignment cannot assign 88 input values to the 87 output values where the mask is true`, example shown here [(another colab notebook)](https://colab.research.google.com/drive/1MmOqf3ppzzdKKyMWkn0bJy6DqzOO0SSm?usp=sharing)
It is clear that the normalizer is the process that break the alignment, as it is observed that `tokenizer._tokenizer.normalizer.normalize_str('ヿ')` return 'コト'.
One workaround is to include `tokenizer._tokenizer.normalizer.normalize_str` before the tokenizer preprocessing pipeline, which is also provided in the [first colab notebook](https://colab.research.google.com/drive/151gKyo0YIwnlznrOHst23oYH_a3mAe3Z?usp=sharing) with the name `udposTestDatasetWorkaround`.
I guess similar logics should be included inside the tokenizer and the offsets_mapping generation process such that user don't need to include them in their code. But I don't understand the code of tokenizer well that I think I am not able to do this.
p.s.
**I am using my own dataset building script in the provided example, but the script should be equivalent to the changes made by this [update](https://github.com/huggingface/datasets/pull/2466)**
`get_dataset `is just a simple wrapping for `load_dataset`
and the `tokenizer` is just `XLMRobertaTokenizerFast.from_pretrained("xlm-roberta-large")` | {
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} | https://api.github.com/repos/huggingface/datasets/issues/2532/timeline | null | completed | null | null | false | [
"Hi @jerryIsHere, thanks for reporting the issue. But are you sure this is a bug in HuggingFace **Datasets**?",
"> Hi @jerryIsHere, thanks for reporting the issue. But are you sure this is a bug in HuggingFace **Datasets**?\r\n\r\nOh, I am sorry\r\nI would reopen the post on huggingface/transformers"
] |
https://api.github.com/repos/huggingface/datasets/issues/2695 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2695/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2695/comments | https://api.github.com/repos/huggingface/datasets/issues/2695/events | https://github.com/huggingface/datasets/issues/2695 | 949,864,823 | MDU6SXNzdWU5NDk4NjQ4MjM= | 2,695 | Cannot import load_dataset on Colab | [
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] | closed | false | null | 5 | 2021-07-21T15:52:51Z | 2021-07-22T07:26:25Z | 2021-07-22T07:09:07Z | null | ## Describe the bug
Got tqdm concurrent module not found error during importing load_dataset from datasets.
## Steps to reproduce the bug
Here [colab notebook](https://colab.research.google.com/drive/1pErWWnVP4P4mVHjSFUtkePd8Na_Qirg4?usp=sharing) to reproduce the error
On colab:
```python
!pip install datasets
from datasets import load_dataset
```
## Expected results
Works without error
## Actual results
Specify the actual results or traceback.
```
ModuleNotFoundError Traceback (most recent call last)
<ipython-input-2-8cc7de4c69eb> in <module>()
----> 1 from datasets import load_dataset, load_metric, Metric, MetricInfo, Features, Value
2 from sklearn.metrics import mean_squared_error
/usr/local/lib/python3.7/dist-packages/datasets/__init__.py in <module>()
31 )
32
---> 33 from .arrow_dataset import Dataset, concatenate_datasets
34 from .arrow_reader import ArrowReader, ReadInstruction
35 from .arrow_writer import ArrowWriter
/usr/local/lib/python3.7/dist-packages/datasets/arrow_dataset.py in <module>()
40 from tqdm.auto import tqdm
41
---> 42 from datasets.tasks.text_classification import TextClassification
43
44 from . import config, utils
/usr/local/lib/python3.7/dist-packages/datasets/tasks/__init__.py in <module>()
1 from typing import Optional
2
----> 3 from ..utils.logging import get_logger
4 from .automatic_speech_recognition import AutomaticSpeechRecognition
5 from .base import TaskTemplate
/usr/local/lib/python3.7/dist-packages/datasets/utils/__init__.py in <module>()
19
20 from . import logging
---> 21 from .download_manager import DownloadManager, GenerateMode
22 from .file_utils import DownloadConfig, cached_path, hf_bucket_url, is_remote_url, temp_seed
23 from .mock_download_manager import MockDownloadManager
/usr/local/lib/python3.7/dist-packages/datasets/utils/download_manager.py in <module>()
24
25 from .. import config
---> 26 from .file_utils import (
27 DownloadConfig,
28 cached_path,
/usr/local/lib/python3.7/dist-packages/datasets/utils/file_utils.py in <module>()
25 import posixpath
26 import requests
---> 27 from tqdm.contrib.concurrent import thread_map
28
29 from .. import __version__, config, utils
ModuleNotFoundError: No module named 'tqdm.contrib.concurrent'
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.10.0
- Platform: Colab
- Python version: 3.7.11
- PyArrow version: 3.0.0
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"I'm facing the same issue on Colab today too.\r\n\r\n```\r\nModuleNotFoundError Traceback (most recent call last)\r\n<ipython-input-4-5833ac0f5437> in <module>()\r\n 3 \r\n 4 from ray import tune\r\n----> 5 from datasets import DatasetDict, Dataset\r\n 6 from datasets import lo... |
https://api.github.com/repos/huggingface/datasets/issues/5056 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5056/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5056/comments | https://api.github.com/repos/huggingface/datasets/issues/5056/events | https://github.com/huggingface/datasets/pull/5056 | 1,394,713,173 | PR_kwDODunzps5ADfxN | 5,056 | Fix broken URL's (GEM) | [] | closed | false | null | 2 | 2022-10-03T13:13:22Z | 2022-10-04T13:49:00Z | 2022-10-04T13:48:59Z | null | This PR fixes the broken URL's in GEM. cc. @lhoestq, @albertvillanova | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_5056). All of your documentation changes will be reflected on that endpoint.",
"Thanks, @manandey. We have removed all dataset scripts from this repo. Subsequent PRs should be opened directly on the Hugging Face Hub."
] |
https://api.github.com/repos/huggingface/datasets/issues/4843 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4843/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4843/comments | https://api.github.com/repos/huggingface/datasets/issues/4843/events | https://github.com/huggingface/datasets/pull/4843 | 1,337,668,699 | PR_kwDODunzps49HaWT | 4,843 | Fix typo in streaming docs | [] | closed | false | null | 1 | 2022-08-12T20:18:21Z | 2022-08-14T11:43:30Z | 2022-08-14T11:02:09Z | null | null | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] |
https://api.github.com/repos/huggingface/datasets/issues/171 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/171/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/171/comments | https://api.github.com/repos/huggingface/datasets/issues/171/events | https://github.com/huggingface/datasets/pull/171 | 621,199,128 | MDExOlB1bGxSZXF1ZXN0NDIwMjk0ODM0 | 171 | fix squad metric format | [] | closed | false | null | 5 | 2020-05-19T18:37:36Z | 2020-05-22T13:36:50Z | 2020-05-22T13:36:48Z | null | The format of the squad metric was wrong.
This should fix #143
I tested with
```python3
predictions = [
{'id': '56be4db0acb8001400a502ec', 'prediction_text': 'Denver Broncos'}
]
references = [
{'answers': [{'text': 'Denver Broncos'}], 'id': '56be4db0acb8001400a502ec'}
]
``` | {
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"One thing for SQuAD is that I wanted to be able to use the SQuAD dataset directly in the metrics and I'm not sure it will be possible with this format.\r\n\r\n(maybe it's not really possible in general though)",
"This is kinda related to one thing I had in mind which is that we may want to be able to dump our mo... |
https://api.github.com/repos/huggingface/datasets/issues/1681 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1681/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1681/comments | https://api.github.com/repos/huggingface/datasets/issues/1681/events | https://github.com/huggingface/datasets/issues/1681 | 777,644,163 | MDU6SXNzdWU3Nzc2NDQxNjM= | 1,681 | Dataset "dane" missing | [] | closed | false | null | 3 | 2021-01-03T14:03:03Z | 2021-01-05T08:35:35Z | 2021-01-05T08:35:13Z | null | the `dane` dataset appear to be missing in the latest version (1.1.3).
```python
>>> import datasets
>>> datasets.__version__
'1.1.3'
>>> "dane" in datasets.list_datasets()
True
```
As we can see it should be present, but doesn't seem to be findable when using `load_dataset`.
```python
>>> datasets.load_dataset("dane")
Traceback (most recent call last):
File "/home/kenneth/.Envs/EDP/lib/python3.8/site-packages/datasets/load.py", line 267, in prepare_module
local_path = cached_path(file_path, download_config=download_config)
File "/home/kenneth/.Envs/EDP/lib/python3.8/site-packages/datasets/utils/file_utils.py", line 300, in cached_path
output_path = get_from_cache(
File "/home/kenneth/.Envs/EDP/lib/python3.8/site-packages/datasets/utils/file_utils.py", line 486, in get_from_cache
raise FileNotFoundError("Couldn't find file at {}".format(url))
FileNotFoundError: Couldn't find file at https://raw.githubusercontent.com/huggingface/datasets/1.1.3/datasets/dane/dane.py
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/home/kenneth/.Envs/EDP/lib/python3.8/site-packages/datasets/load.py", line 278, in prepare_module
local_path = cached_path(file_path, download_config=download_config)
File "/home/kenneth/.Envs/EDP/lib/python3.8/site-packages/datasets/utils/file_utils.py", line 300, in cached_path
output_path = get_from_cache(
File "/home/kenneth/.Envs/EDP/lib/python3.8/site-packages/datasets/utils/file_utils.py", line 486, in get_from_cache
raise FileNotFoundError("Couldn't find file at {}".format(url))
FileNotFoundError: Couldn't find file at https://s3.amazonaws.com/datasets.huggingface.co/datasets/datasets/dane/dane.py
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/kenneth/.Envs/EDP/lib/python3.8/site-packages/datasets/load.py", line 588, in load_dataset
module_path, hash = prepare_module(
File "/home/kenneth/.Envs/EDP/lib/python3.8/site-packages/datasets/load.py", line 280, in prepare_module
raise FileNotFoundError(
FileNotFoundError: Couldn't find file locally at dane/dane.py, or remotely at https://raw.githubusercontent.com/huggingface/datasets/1.1.3/datasets/dane/dane.py or https://s3.amazonaws.com/datasets.huggingface.co/datasets/datasets/dane/dane.py
```
This issue might be relevant to @ophelielacroix from the Alexandra Institut whom created the data. | {
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"Hi @KennethEnevoldsen ,\r\nI think the issue might be that this dataset was added during the community sprint and has not been released yet. It will be available with the v2 of datasets.\r\nFor now, you should be able to load the datasets after installing the latest (master) version of datasets using pip:\r\npip i... |
https://api.github.com/repos/huggingface/datasets/issues/1626 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1626/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1626/comments | https://api.github.com/repos/huggingface/datasets/issues/1626/events | https://github.com/huggingface/datasets/pull/1626 | 773,840,368 | MDExOlB1bGxSZXF1ZXN0NTQ0ODYxMDE4 | 1,626 | Fix dataset_dict.shuffle with single seed | [] | closed | false | null | 0 | 2020-12-23T14:33:36Z | 2021-01-04T10:00:04Z | 2021-01-04T10:00:03Z | null | Fix #1610
I added support for single integer used in `DatasetDict.shuffle`. Previously only a dictionary of seed was allowed.
Moreover I added the missing `seed` parameter. Previously only `seeds` was allowed. | {
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https://api.github.com/repos/huggingface/datasets/issues/2336 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2336/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2336/comments | https://api.github.com/repos/huggingface/datasets/issues/2336/events | https://github.com/huggingface/datasets/pull/2336 | 881,298,783 | MDExOlB1bGxSZXF1ZXN0NjM0ODk1OTU5 | 2,336 | Fix overflow issue in interpolation search | [] | closed | false | null | 3 | 2021-05-08T20:51:36Z | 2021-05-10T13:29:07Z | 2021-05-10T13:26:12Z | null | Fixes #2335
More info about this error can be found [here](https://stackoverflow.com/questions/53239890/why-do-i-keep-getting-this-error-runtimewarning-overflow-encountered-in-int-sc/53240100). | {
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"~~Seems like the CI failure is unrelated to this PR~~ (fixed with the merge). \r\n\r\n@lhoestq Can you please verify that everything is OK in terms of speed? Another solution is to change the offsets array dtype to np.int64 (but this doesn't scale in theory compared to Python integer which is unbound). I'm not sur... |
https://api.github.com/repos/huggingface/datasets/issues/5798 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5798/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5798/comments | https://api.github.com/repos/huggingface/datasets/issues/5798/events | https://github.com/huggingface/datasets/issues/5798 | 1,685,904,526 | I_kwDODunzps5kfNyO | 5,798 | Support parallelized downloading and processing in load_dataset with Spark | [
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] | open | false | null | 17 | 2023-04-27T00:16:11Z | 2023-05-25T14:11:41Z | null | null | ### Feature request
When calling `load_dataset` for datasets that have multiple files, support using Spark to distribute the downloading and processing job to worker nodes when `cache_dir` is a cloud file system shared among nodes.
```python
load_dataset(..., use_spark=True)
```
### Motivation
Further speed up `dl_manager.download` and `_prepare_split` by distributing the workloads to worker nodes.
### Your contribution
I can submit a PR to support this. | {
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"Hi ! We're using process pools for parallelism right now. I was wondering if there's a package that implements the same API as a process pool but runs with Spark under the hood ? That or something similar would be cool because users could use whatever distributed framework they want this way.\r\n\r\nFeel free to p... |
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More info : http://opus.nlpl.eu/Finlex.php | {
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https://api.github.com/repos/huggingface/datasets/issues/131 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/131/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/131/comments | https://api.github.com/repos/huggingface/datasets/issues/131/events | https://github.com/huggingface/datasets/issues/131 | 619,073,731 | MDU6SXNzdWU2MTkwNzM3MzE= | 131 | [Feature request] Add Toronto BookCorpus dataset | [
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] | closed | false | null | 2 | 2020-05-15T15:50:44Z | 2020-06-28T21:27:31Z | 2020-06-28T21:27:31Z | null | I know the copyright/distribution of this one is complex, but it would be great to have! That, combined with the existing `wikitext`, would provide a complete dataset for pretraining models like BERT. | {
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"As far as I understand, `wikitext` is refer to `WikiText-103` and `WikiText-2` that created by researchers in Salesforce, and mostly used in traditional language modeling.\r\n\r\nYou might want to say `wikipedia`, a dump from wikimedia foundation.\r\n\r\nAlso I would like to have Toronto BookCorpus too ! Though it... |
https://api.github.com/repos/huggingface/datasets/issues/3799 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3799/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3799/comments | https://api.github.com/repos/huggingface/datasets/issues/3799/events | https://github.com/huggingface/datasets/pull/3799 | 1,155,356,102 | PR_kwDODunzps4zus9R | 3,799 | Xtreme-S Metrics | [] | closed | false | null | 3 | 2022-03-01T13:42:28Z | 2022-03-16T14:40:29Z | 2022-03-16T14:40:26Z | null | **Added datasets (TODO)**:
- [x] MLS
- [x] Covost2
- [x] Minds-14
- [x] Voxpopuli
- [x] FLoRes (need data)
**Metrics**: Done | {
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"@lhoestq - if you could take a final review here this would be great (if you have 5min :-) ) ",
"Don't think the failures are related but not 100% sure",
"Yes the CI fail is unrelated - you can ignore it"
] |
https://api.github.com/repos/huggingface/datasets/issues/3788 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3788/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3788/comments | https://api.github.com/repos/huggingface/datasets/issues/3788/events | https://github.com/huggingface/datasets/issues/3788 | 1,150,375,720 | I_kwDODunzps5EkVco | 3,788 | Only-data dataset loaded unexpectedly as validation split | [
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] | open | false | null | 7 | 2022-02-25T12:11:39Z | 2022-02-28T11:22:22Z | null | null | ## Describe the bug
As reported by @thomasw21 and @lhoestq, a dataset containing only a data file whose name matches the pattern `*dev*` will be returned as VALIDATION split, even if this is not the desired behavior, e.g. a file named `datosdevision.jsonl.gz`. | {
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"I see two options:\r\n1. drop the \"dev\" keyword since it can be considered too generic\r\n2. improve the pattern to something more reasonable, e.g. asking for a separator before and after \"dev\"\r\n```python\r\n[\"*[ ._-]dev[ ._-]*\", \"dev[ ._-]*\"]\r\n```\r\n\r\nI think 2. is nice. If we agree on this one we ... |
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https://api.github.com/repos/huggingface/datasets/issues/684 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/684/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/684/comments | https://api.github.com/repos/huggingface/datasets/issues/684/events | https://github.com/huggingface/datasets/pull/684 | 711,080,947 | MDExOlB1bGxSZXF1ZXN0NDk0ODA2NjE1 | 684 | Fix column order issue in cast | [] | closed | false | null | 0 | 2020-09-29T12:49:13Z | 2020-09-29T15:56:46Z | 2020-09-29T15:56:45Z | null | Previously, the order of the columns in the features passes to `cast_` mattered.
However even though features passed to `cast_` had the same order as the dataset features, it could fail because the schema that was built was always in alphabetical order.
This issue was reported by @lewtun in #623
To fix that I fixed the schema to follow the order of the arrow table columns.
I also added the possibility to give features that are not ordered the same way as the dataset features. | {
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https://api.github.com/repos/huggingface/datasets/issues/5018 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5018/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5018/comments | https://api.github.com/repos/huggingface/datasets/issues/5018/events | https://github.com/huggingface/datasets/pull/5018 | 1,384,146,585 | PR_kwDODunzps4_hA0V | 5,018 | Create all YAML dataset_info | [
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] | closed | false | null | 2 | 2022-09-23T18:08:15Z | 2022-10-03T17:08:05Z | 2022-10-03T17:08:05Z | null | Following https://github.com/huggingface/datasets/pull/4926
Creates all the `dataset_info` YAML fields in the dataset cards
The JSON are also updated using the simplified backward compatible format added in https://github.com/huggingface/datasets/pull/4926
Needs https://github.com/huggingface/datasets/pull/4926 to be merged first | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_5018). All of your documentation changes will be reflected on that endpoint.",
"Closing since https://github.com/huggingface/datasets/pull/4974 removed all the datasets scripts.\r\n\r\nIndividual PRs must be opened on the Huggi... |
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] | open | false | null | 1 | 2023-04-25T16:14:18Z | 2023-05-05T16:22:50Z | null | null | ### Feature request
I currently have a dataset (with tiff and json files) where I have to do this:
`wget path_to_data/images.zip && unzip images.zip`
`wget path_to_data/annotations.zip && unzip annotations.zip`
Would it make sense a contribution that supports these type of files?
### Motivation
instead of using `load_dataset` have to use wget as these files are not supported for annotations with JSON and images with TIFF files.
Additionally to this, the PIL formatting from datasets does not read correctly the image channels with TIFF format, besides multichannel adaptation might be necessary as well (as my data e.g has more than 3 channels)
### Your contribution
1. Support TIFF images over multi channel format
2. Support JSON annotations | {
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"The issue with multichannel TIFF images has already been reported in Pillow (https://github.com/python-pillow/Pillow/issues/1888). We can't do much about it on our side.\r\n\r\nStill, to avoid the error, you can bypass the default Pillow decoding and define a custom one as follows:\r\n```python\r\nimport tifffile ... |
https://api.github.com/repos/huggingface/datasets/issues/2325 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2325/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2325/comments | https://api.github.com/repos/huggingface/datasets/issues/2325/events | https://github.com/huggingface/datasets/pull/2325 | 876,653,121 | MDExOlB1bGxSZXF1ZXN0NjMwNzU1MzIx | 2,325 | Added the HLGD dataset | [] | closed | false | null | 2 | 2021-05-05T16:53:29Z | 2021-05-12T14:55:13Z | 2021-05-12T14:16:38Z | null | Added the Headline Grouping Dataset (HLGD), from the NAACL2021 paper: News Headline Grouping as a Challenging NLU Task
Dataset Link: https://github.com/tingofurro/headline_grouping
Paper link: https://people.eecs.berkeley.edu/~phillab/pdfs/NAACL2021_HLG.pdf | {
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"Is there anything else needed from my end?",
"Thanks Bhavitvya and Quentin, this was very streamlined!"
] |
https://api.github.com/repos/huggingface/datasets/issues/1604 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1604/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1604/comments | https://api.github.com/repos/huggingface/datasets/issues/1604/events | https://github.com/huggingface/datasets/issues/1604 | 770,862,112 | MDU6SXNzdWU3NzA4NjIxMTI= | 1,604 | Add tests for the download functions ? | [
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] | closed | false | null | 1 | 2020-12-18T12:49:25Z | 2022-10-05T13:04:24Z | 2022-10-05T13:04:24Z | null | AFAIK the download functions in `DownloadManager` are not tested yet. It could be good to add some to ensure behavior is as expected. | {
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"We have some tests now for it under `tests/test_download_manager.py`."
] |
https://api.github.com/repos/huggingface/datasets/issues/2420 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2420/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2420/comments | https://api.github.com/repos/huggingface/datasets/issues/2420/events | https://github.com/huggingface/datasets/pull/2420 | 904,821,772 | MDExOlB1bGxSZXF1ZXN0NjU1OTQ1ODgw | 2,420 | Updated Dataset Description | [] | closed | false | null | 0 | 2021-05-28T07:10:51Z | 2021-06-10T12:11:35Z | 2021-06-10T12:11:35Z | null | Added Point of contact information and several other details about the dataset. | {
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https://api.github.com/repos/huggingface/datasets/issues/932 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/932/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/932/comments | https://api.github.com/repos/huggingface/datasets/issues/932/events | https://github.com/huggingface/datasets/pull/932 | 753,840,300 | MDExOlB1bGxSZXF1ZXN0NTI5ODQwNjQ3 | 932 | adding metooma dataset | [] | closed | false | null | 3 | 2020-11-30T22:09:49Z | 2020-12-02T00:37:54Z | 2020-12-02T00:37:54Z | null | {
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"This PR adds the #MeToo MA dataset. It presents multi-label data points for tweets mined in the backdrop of the #MeToo movement. The dataset includes data points in the form of Tweet ids and appropriate labels. Please refer to the accompanying paper for detailed information regarding annotation, collection, and gu... | |
https://api.github.com/repos/huggingface/datasets/issues/4461 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4461/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4461/comments | https://api.github.com/repos/huggingface/datasets/issues/4461/events | https://github.com/huggingface/datasets/issues/4461 | 1,264,800,451 | I_kwDODunzps5LY1LD | 4,461 | AttributeError: module 'datasets' has no attribute 'load_dataset' | [
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] | closed | false | null | 2 | 2022-06-08T13:59:20Z | 2023-07-28T08:12:22Z | 2022-06-08T14:41:00Z | null | ## Describe the bug
I have piped install datasets, but this package doesn't have these attributes: load_dataset, load_metric.
## Environment info
- `datasets` version: 1.9.0
- Platform: Linux-5.13.0-44-generic-x86_64-with-debian-bullseye-sid
- Python version: 3.6.13
- PyArrow version: 6.0.1
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"I'm having the same issue，Can you tell me how to solve it？",
"I have the same issue, can you tell me how to solve it? Thanks"
] |
https://api.github.com/repos/huggingface/datasets/issues/44 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/44/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/44/comments | https://api.github.com/repos/huggingface/datasets/issues/44/events | https://github.com/huggingface/datasets/pull/44 | 611,873,486 | MDExOlB1bGxSZXF1ZXN0NDEyOTUwMzU1 | 44 | [Tests] Fix tests for datasets with no config | [] | closed | false | null | 0 | 2020-05-04T13:25:38Z | 2020-05-04T13:28:04Z | 2020-05-04T13:28:03Z | null | Forgot to fix `None` problem for datasets that have no config this in PR: https://github.com/huggingface/nlp/pull/42 | {
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https://api.github.com/repos/huggingface/datasets/issues/2063 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2063/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2063/comments | https://api.github.com/repos/huggingface/datasets/issues/2063/events | https://github.com/huggingface/datasets/pull/2063 | 832,993,705 | MDExOlB1bGxSZXF1ZXN0NTk0MDY2NzI5 | 2,063 | [Common Voice] Adapt dataset script so that no manual data download is actually needed | [] | closed | false | null | 0 | 2021-03-16T16:33:44Z | 2021-03-17T09:42:52Z | 2021-03-17T09:42:37Z | null | This PR changes the dataset script so that no manual data dir is needed anymore. | {
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https://api.github.com/repos/huggingface/datasets/issues/1349 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1349/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1349/comments | https://api.github.com/repos/huggingface/datasets/issues/1349/events | https://github.com/huggingface/datasets/pull/1349 | 759,870,664 | MDExOlB1bGxSZXF1ZXN0NTM0Nzk4NDQ3 | 1,349 | initial commit for MultiReQA | [] | closed | false | null | 2 | 2020-12-08T23:44:34Z | 2020-12-09T16:46:37Z | 2020-12-09T16:46:37Z | null | Added MultiReQA, which is a dataset containing the sentence boundary annotation from eight publicly available QA datasets including SearchQA, TriviaQA, HotpotQA, NaturalQuestions, SQuAD, BioASQ, RelationExtraction, and TextbookQA. | {
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"looks like this dataset includes changes about many other files than the ones for multi_re_qa\r\n\r\nCan you create another branch and another PR please ?",
"> looks like this dataset includes changes about many other files than the ones for multi_re_qa\r\n> \r\n> Can you create another branch and another PR ple... |
https://api.github.com/repos/huggingface/datasets/issues/1229 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1229/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1229/comments | https://api.github.com/repos/huggingface/datasets/issues/1229/events | https://github.com/huggingface/datasets/pull/1229 | 758,100,707 | MDExOlB1bGxSZXF1ZXN0NTMzMzI2OTgw | 1,229 | Muchocine - Spanish movie reviews dataset | [] | closed | false | null | 4 | 2020-12-07T02:23:29Z | 2020-12-21T10:09:09Z | 2020-12-21T10:09:09Z | null | {
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"Hi @mapmeld !\r\nhave you had a chance to take a look at my suggestions ?\r\n\r\nFeel free to ping me if you have questions or when you're ready for a review",
"@lhoestq unfortunately I don't have any more information about where the dataset comes from",
"It's fine, you can just add the sections titles back an... | |
https://api.github.com/repos/huggingface/datasets/issues/5349 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5349/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5349/comments | https://api.github.com/repos/huggingface/datasets/issues/5349/events | https://github.com/huggingface/datasets/pull/5349 | 1,487,396,780 | PR_kwDODunzps5E8N6G | 5,349 | Clean up remaining Main Classes docstrings | [] | closed | false | null | 1 | 2022-12-09T20:17:15Z | 2022-12-12T17:27:17Z | 2022-12-12T17:24:13Z | null | This PR cleans up the remaining docstrings in Main Classes (`IterableDataset`, `IterableDatasetDict`, and `Features`). | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] |
https://api.github.com/repos/huggingface/datasets/issues/4160 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4160/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4160/comments | https://api.github.com/repos/huggingface/datasets/issues/4160/events | https://github.com/huggingface/datasets/issues/4160 | 1,202,845,874 | I_kwDODunzps5Hsfiy | 4,160 | RGBA images not showing | [
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"description": "Related to the dataset viewer on huggingface.co",
"id": 3470211881,
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{
"color": "6... | closed | false | null | 2 | 2022-04-13T06:59:23Z | 2022-06-21T16:43:11Z | 2022-06-21T16:43:11Z | null | ## Dataset viewer issue for ceyda/smithsonian_butterflies_transparent
[**Link:** *link to the dataset viewer page*](https://huggingface.co/datasets/ceyda/smithsonian_butterflies_transparent)
Am I the one who added this dataset ? Yes
👉 More of a general issue of 'RGBA' png images not being supported
(the dataset itself is just for the huggan sprint and not that important, consider it just an example) | {
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"Thanks for reporting. It's a known issue, and we hope to fix it soon.",
"Fixed, thanks!"
] |
https://api.github.com/repos/huggingface/datasets/issues/6003 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6003/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6003/comments | https://api.github.com/repos/huggingface/datasets/issues/6003/events | https://github.com/huggingface/datasets/issues/6003 | 1,786,554,110 | I_kwDODunzps5qfKb- | 6,003 | interleave_datasets & DataCollatorForLanguageModeling having a conflict ? | [] | open | false | null | 0 | 2023-07-03T17:15:31Z | 2023-07-03T17:15:31Z | null | null | ### Describe the bug
Hi everyone :)
I have two local & custom datasets (1 "sentence" per line) which I split along the 95/5 lines for pre-training a Bert model. I use a modified version of `run_mlm.py` in order to be able to make use of `interleave_dataset`:
- `tokenize()` runs fine
- `group_text()` runs fine
Everytime, on step 19, I get
```pytb
File "env/lib/python3.9/site-packages/transformers/data/data_collator.py", line 779, in torch_mask_tokens
inputs[indices_random] = random_words[indices_random]
RuntimeError: Index put requires the source and destination dtypes match, got Float for the destination and Long for the source.
```
I tried:
- training without interleave on dataset 1, it runs
- training without interleave on dataset 2, it runs
- training without `.to_iterable_dataset()`, it hangs then crash
- training without group_text() and padding to max_length seemed to fix the issue, but who knows if this was just because it was an issue that would come much later in terms of steps.
I might have coded something wrong, but I don't get what
### Steps to reproduce the bug
I have this function:
```py
def build_dataset(path: str, percent: str):
dataset = load_dataset(
"text",
data_files={"train": [path]},
split=f"train[{percent}]"
)
dataset = dataset.map(
lambda examples: tokenize(examples["text"]),
batched=True,
num_proc=num_proc,
)
dataset = dataset.map(
group_texts,
batched=True,
num_proc=num_proc,
desc=f"Grouping texts in chunks of {tokenizer.max_seq_length}",
remove_columns=["text"]
)
print(len(dataset))
return dataset.to_iterable_dataset()
```
I hardcoded group_text:
```py
def group_texts(examples):
# Concatenate all texts.
concatenated_examples = {k: list(chain(*examples[k])) for k in examples.keys()}
total_length = len(concatenated_examples[list(examples.keys())[0]])
# We drop the small remainder, and if the total_length < max_seq_length we exclude this batch and return an empty dict.
# We could add padding if the model supported it instead of this drop, you can customize this part to your needs.
total_length = (total_length // 512) * 512
# Split by chunks of max_len.
result = {
k: [t[i: i + 512] for i in range(0, total_length, 512)]
for k, t in concatenated_examples.items()
}
# result = {k: [el for el in elements if el] for k, elements in result.items()}
return result
```
And then I build datasets using the following code:
```py
train1 = build_dataset("d1.txt", ":95%")
train2 = build_dataset("d2.txt", ":95%")
dev1 = build_dataset("d1.txt", "95%:")
dev2 = build_dataset("d2.txt", "95%:")
```
and finally I run
```py
train_dataset = interleave_datasets(
[train1, train2],
probabilities=[0.8, 0.2],
seed=42
)
eval_dataset = interleave_datasets(
[dev1, dev2],
probabilities=[0.8, 0.2],
seed=42
)
```
Then I run the training part which remains mostly untouched:
> CUDA_VISIBLE_DEVICES=1 python custom_dataset.py --model_type bert --per_device_train_batch_size 32 --do_train --output_dir /var/mlm/training-bert/model --max_seq_length 512 --save_steps 10000 --save_total_limit 3 --auto_find_batch_size --logging_dir ./logs-bert --learning_rate 0.0001 --do_train --num_train_epochs 25 --warmup_steps 10000 --max_step 45000 --fp16
### Expected behavior
The model should then train normally, but fails every time at the same step (19).
printing the variables at `inputs[indices_random] = random_words[indices_random]` shows a magnificient empty tensor (, 32) [if I remember well]
### Environment info
transformers[torch] 4.30.2
Ubuntu
A100 0 CUDA 12
Driver Version: 525.116.04 | {
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https://api.github.com/repos/huggingface/datasets/issues/419 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/419/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/419/comments | https://api.github.com/repos/huggingface/datasets/issues/419/events | https://github.com/huggingface/datasets/pull/419 | 661,974,747 | MDExOlB1bGxSZXF1ZXN0NDUzNTgxNzQz | 419 | EmoContext dataset add | [] | closed | false | null | 0 | 2020-07-20T15:48:45Z | 2020-07-24T08:22:01Z | 2020-07-24T08:22:00Z | null | EmoContext Dataset add
Signed-off-by: lordtt13 <thakurtanmay72@yahoo.com> | {
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https://api.github.com/repos/huggingface/datasets/issues/3955 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3955/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3955/comments | https://api.github.com/repos/huggingface/datasets/issues/3955/events | https://github.com/huggingface/datasets/pull/3955 | 1,172,246,647 | PR_kwDODunzps40l5kG | 3,955 | Remove unncessary 'pylint disable' message in ReadMe | [] | closed | false | null | 0 | 2022-03-17T11:16:55Z | 2022-04-12T14:28:35Z | 2022-04-12T14:28:35Z | null | null | {
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https://api.github.com/repos/huggingface/datasets/issues/3769 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3769/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3769/comments | https://api.github.com/repos/huggingface/datasets/issues/3769/events | https://github.com/huggingface/datasets/issues/3769 | 1,146,258,023 | I_kwDODunzps5EUoJn | 3,769 | `dataset = dataset.map()` causes faiss index lost | [
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] | open | false | null | 3 | 2022-02-21T21:59:23Z | 2022-06-27T14:56:29Z | null | null | ## Describe the bug
assigning the resulted dataset to original dataset causes lost of the faiss index
## Steps to reproduce the bug
`my_dataset` is a regular loaded dataset. It's a part of a customed dataset structure
```python
self.dataset.add_faiss_index('embeddings')
self.dataset.list_indexes()
# ['embeddings']
dataset2 = my_dataset.map(
lambda x: self._get_nearest_examples_batch(x['text']), batch=True
)
# the unexpected result:
dataset2.list_indexes()
# []
self.dataset.list_indexes()
# ['embeddings']
```
in case something wrong with my `_get_nearest_examples_batch()`, it's like this
```python
def _get_nearest_examples_batch(self, examples, k=5):
queries = embed(examples)
scores_batch, retrievals_batch = self.dataset.get_nearest_examples_batch(self.faiss_column, queries, k)
return {
'neighbors': [batch['text'] for batch in retrievals_batch],
'scores': scores_batch
}
```
## Expected results
`map` shouldn't drop the indexes, in another word, indexes should be carried to the generated dataset
## Actual results
map drops the indexes
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.18.3
- Platform: Ubuntu 20.04.3 LTS
- Python version: 3.8.12
- PyArrow version: 7.0.0
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} | https://api.github.com/repos/huggingface/datasets/issues/3769/timeline | null | null | null | null | false | [
"Hi ! Indeed `map` is dropping the index right now, because one can create a dataset with more or fewer rows using `map` (and therefore the index might not be relevant anymore)\r\n\r\nI guess we could check the resulting dataset length, and if the user hasn't changed the dataset size we could keep the index, what d... |
https://api.github.com/repos/huggingface/datasets/issues/1369 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1369/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1369/comments | https://api.github.com/repos/huggingface/datasets/issues/1369/events | https://github.com/huggingface/datasets/pull/1369 | 760,227,776 | MDExOlB1bGxSZXF1ZXN0NTM1MDk0NDk1 | 1,369 | Use passed --cache_dir for modules cache | [] | open | false | null | 7 | 2020-12-09T10:59:59Z | 2022-07-06T15:19:47Z | null | null | When passed `--cache_dir` arg:
```shell
python datasets-cli test datasets/<my-dataset-folder> --save_infos --all_configs --cache_dir <my-cache-dir>
```
it is not used for caching the modules, which are cached in the default location at `.cache/huggingface/modules`.
With this fix, the modules will be cached at `<my-cache-dir>/modules`. | {
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"I have a question: why not using a tmp dir instead, like the DummyDataGeneratorDownloadManager does?",
"Hi @lhoestq, I am trying to understand better the logic...\r\n\r\nWhy do we have a `dynamic_module_path` besides the modules cache path?\r\n```python\r\nDYNAMIC_MODULES_PATH = os.path.join(HF_MODULES_CACHE, \"... |
https://api.github.com/repos/huggingface/datasets/issues/4669 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4669/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4669/comments | https://api.github.com/repos/huggingface/datasets/issues/4669/events | https://github.com/huggingface/datasets/issues/4669 | 1,299,848,003 | I_kwDODunzps5NehtD | 4,669 | loading oscar-corpus/OSCAR-2201 raises an error | [
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] | closed | false | null | 1 | 2022-07-10T07:09:30Z | 2022-07-11T09:27:49Z | 2022-07-11T09:27:49Z | null | ## Describe the bug
load_dataset('oscar-2201', 'af')
raises an error:
Traceback (most recent call last):
File "/usr/lib/python3.8/code.py", line 90, in runcode
exec(code, self.locals)
File "<input>", line 1, in <module>
File "..python3.8/site-packages/datasets/load.py", line 1656, in load_dataset
builder_instance = load_dataset_builder(
File ".../lib/python3.8/site-packages/datasets/load.py", line 1439, in load_dataset_builder
dataset_module = dataset_module_factory(
File ".../lib/python3.8/site-packages/datasets/load.py", line 1189, in dataset_module_factory
raise FileNotFoundError(
FileNotFoundError: Couldn't find a dataset script at .../oscar-2201/oscar-2201.py or any data file in the same directory. Couldn't find 'oscar-2201' on the Hugging Face Hub either: FileNotFoundError: Couldn't find file at https://raw.githubusercontent.com/huggingface/datasets/master/datasets/oscar-2201/oscar-2201.py
I've tried other permutations such as :
oscar_22 = load_dataset('oscar-2201', 'af',use_auth_token=True)
oscar_22 = load_dataset('oscar-corpus/OSCAR-2201', 'af',use_auth_token=True)
oscar_22 = load_dataset('oscar-2201', 'af')
oscar_22 = load_dataset('oscar-corpus/OSCAR-2201')
with the same unfortunate result.
## Steps to reproduce the bug
oscar_22 = load_dataset('oscar-2201', 'af',use_auth_token=True)
oscar_22 = load_dataset('oscar-corpus/OSCAR-2201', 'af',use_auth_token=True)
oscar_22 = load_dataset('oscar-2201', 'af')
oscar_22 = load_dataset('oscar-corpus/OSCAR-2201')
# Sample code to reproduce the bug
```
## Expected results
loaded data
## Actual results
Traceback (most recent call last):
File "/usr/lib/python3.8/code.py", line 90, in runcode
exec(code, self.locals)
File "<input>", line 1, in <module>
File "..python3.8/site-packages/datasets/load.py", line 1656, in load_dataset
builder_instance = load_dataset_builder(
File ".../lib/python3.8/site-packages/datasets/load.py", line 1439, in load_dataset_builder
dataset_module = dataset_module_factory(
File ".../lib/python3.8/site-packages/datasets/load.py", line 1189, in dataset_module_factory
raise FileNotFoundError(
FileNotFoundError: Couldn't find a dataset script at .../oscar-2201/oscar-2201.py or any data file in the same directory. Couldn't find 'oscar-2201' on the Hugging Face Hub either: FileNotFoundError: Couldn't find file at https://raw.githubusercontent.com/huggingface/datasets/master/datasets/oscar-2201/oscar-2201.py
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 2.3.2
- Platform: Linux-5.13.0-37-generic-x86_64-with-glibc2.29
- Python version: 3.8.10
- PyArrow version: 8.0.0
- Pandas version: 1.4.3
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"I had to use the appropriate token for use_auth_token. Thank you."
] |
https://api.github.com/repos/huggingface/datasets/issues/2709 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2709/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2709/comments | https://api.github.com/repos/huggingface/datasets/issues/2709/events | https://github.com/huggingface/datasets/issues/2709 | 951,534,757 | MDU6SXNzdWU5NTE1MzQ3NTc= | 2,709 | Missing documentation for wnut_17 (ner_tags) | [
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] | closed | false | null | 1 | 2021-07-23T12:25:32Z | 2021-07-26T09:30:55Z | 2021-07-26T09:30:55Z | null | On the info page of the wnut_17 data set (https://huggingface.co/datasets/wnut_17), the model output of ner-tags is only documented for these 5 cases:
`ner_tags: a list of classification labels, with possible values including O (0), B-corporation (1), I-corporation (2), B-creative-work (3), I-creative-work (4).`
I trained a model with the data and it gives me 13 classes:
```
"id2label": {
"0": 0,
"1": 1,
"2": 2,
"3": 3,
"4": 4,
"5": 5,
"6": 6,
"7": 7,
"8": 8,
"9": 9,
"10": 10,
"11": 11,
"12": 12
}
"label2id": {
"0": 0,
"1": 1,
"10": 10,
"11": 11,
"12": 12,
"2": 2,
"3": 3,
"4": 4,
"5": 5,
"6": 6,
"7": 7,
"8": 8,
"9": 9
}
```
The paper (https://www.aclweb.org/anthology/W17-4418.pdf) explains those 6 categories, but the ordering does not match:
```
1. person
2. location (including GPE, facility)
3. corporation
4. product (tangible goods, or well-defined
services)
5. creative-work (song, movie, book and
so on)
6. group (subsuming music band, sports team,
and non-corporate organisations)
```
I would be very helpful for me, if somebody could clarify the model ouputs and explain the "B-" and "I-" prefixes to me.
Really great work with that and the other packages, I couldn't believe that training the model with that data was basically a one-liner! | {
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} | https://api.github.com/repos/huggingface/datasets/issues/2709/timeline | null | completed | null | null | false | [
"Hi @maxpel, thanks for reporting this issue.\r\n\r\nIndeed, the documentation in the dataset card is not complete. I’m opening a Pull Request to fix it.\r\n\r\nAs the paper explains, there are 6 entity types and we have ordered them alphabetically: `corporation`, `creative-work`, `group`, `location`, `person` and ... |
https://api.github.com/repos/huggingface/datasets/issues/5961 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5961/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5961/comments | https://api.github.com/repos/huggingface/datasets/issues/5961/events | https://github.com/huggingface/datasets/issues/5961 | 1,758,525,111 | I_kwDODunzps5o0Pa3 | 5,961 | IterableDataset: split by node and map may preprocess samples that will be skipped anyway | [] | open | false | null | 7 | 2023-06-15T10:29:10Z | 2023-06-20T01:30:40Z | null | null | There are two ways an iterable dataset can be split by node:
1. if the number of shards is a factor of number of GPUs: in that case the shards are evenly distributed per GPU
2. otherwise, each GPU iterate on the data and at the end keeps 1 sample out of n(GPUs) - skipping the others.
In case 2. it's therefore possible to have the same examples passed to `prepare_dataset` for each GPU.
This doesn't sound optimized though, because it runs the preprocessing on samples that won't be used in the end.
Could you open a new issue so that we can discuss about this and find a solution ?
_Originally posted by @lhoestq in https://github.com/huggingface/datasets/issues/5360#issuecomment-1592729051_
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"Does \"number of shards\" refer to the total number of data?\r\n\r\nmy config:\r\nnproc_per_node=2\r\nds=ds['train'] = load_dataset(streaming=True).take(50000)\r\n\r\nI'm test again: in prepare_data(), data have the same for each GPU\r\n",
"The number of shards is `ds.n_shards`. It corresponds generally to the ... |
https://api.github.com/repos/huggingface/datasets/issues/5546 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5546/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5546/comments | https://api.github.com/repos/huggingface/datasets/issues/5546/events | https://github.com/huggingface/datasets/issues/5546 | 1,590,346,349 | I_kwDODunzps5eysJt | 5,546 | Downloaded datasets do not cache at $HF_HOME | [] | closed | false | null | 1 | 2023-02-18T13:30:35Z | 2023-07-24T14:22:43Z | 2023-07-24T14:22:43Z | null | ### Describe the bug
In the huggingface course (https://huggingface.co/course/chapter3/2?fw=pt) it said that if we set HF_HOME, downloaded datasets would be cached at specified address but it does not. downloaded models from checkpoint names are downloaded and cached at HF_HOME but this is not the case for datasets, they are still cached at ~/.cache/huggingface/datasets.
### Steps to reproduce the bug
Run the following code
```
from datasets import load_dataset
raw_datasets = load_dataset("glue", "mrpc")
raw_datasets
```
it downloads and store dataset at ~/.cache/huggingface/datasets
### Expected behavior
to cache dataset at HF_HOME.
### Environment info
python 3.10.6
Kubuntu 22.04
HF_HOME located on a separate partition | {
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"Hi ! Can you make sure you set `HF_HOME` before importing `datasets` ?\r\n\r\nThen you can print\r\n```python\r\nprint(datasets.config.HF_CACHE_HOME)\r\nprint(datasets.config.HF_DATASETS_CACHE)\r\n```"
] |
https://api.github.com/repos/huggingface/datasets/issues/4659 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4659/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4659/comments | https://api.github.com/repos/huggingface/datasets/issues/4659/events | https://github.com/huggingface/datasets/pull/4659 | 1,297,094,140 | PR_kwDODunzps47AQo9 | 4,659 | Transfer CI to GitHub Actions | [] | closed | false | null | 4 | 2022-07-07T09:29:47Z | 2022-07-12T11:30:20Z | 2022-07-12T11:18:25Z | null | This PR transfers CI from CircleCI to GitHub Actions. The implementation in GitHub Actions tries to be as faithful as possible to the implementation in CircleCI and get the same output results (exceptions below).
**IMPORTANT NOTE**: The fast-fail policy (described below) is not finally implemented, so that:
- we can continue merging PRs with CI in red because of some random error returned by the Hub
- it is not annoying for maintainers to have to relaunch failed CI jobs
See comments here: https://github.com/huggingface/datasets/pull/4659#discussion_r918802348
Differences in the implementation in GitHub Actions compared to the CircleCI one:
- This PR introduces some *fail-fast* mechanisms to significantly reduce the total time CI is running, both because of environmental impact and because CI in GitHub Actions billing depends on the minutes per month running time (see [About billing for GitHub Actions](https://docs.github.com/en/billing/managing-billing-for-github-actions/about-billing-for-github-actions)):
- All tests *depend* on `check_code_quality` job: only if `check_code_quality` passes, then the other test jobs are launched
- The tests are implemented with a matrix strategy (cross-product: OS and PyArrow versions) and fail-fast: if any of the 4 processes fails, the others are cancelled
- OS dependencies for Linux (see table below)
| OS dependencies | Passed tests | Skipped tests |
| --- | ---: | ---: |
| libsndfile1-dev | 4786 | 3119 |
| libsndfile1 | 4786 | 3119 |
| libsndfile1, sox | 4788 | 3117 |
- This PR replaces `libsndfile1-dev` with `libsndfile1`: the same number of passing tests but less packages installed
- This PR adds `sox`: required by MP3 tests (2 more tests are passed: 4788 instead of 4786)
- For tests using PyArrow 6, this PR uses 6.0.1 instead of 6.0.0
TO DO:
- [ ] Remove old CircleCI CI: kept for the moment to compare stability and performance
Close #4658.
## Comparison between CircleCI and GitHub Actions
| | | CircleCI | GitHub Actions |
| --- | --- | ---: | ---: |
| Ubuntu, pyarrow-latest ||||
|| Passed tests | 4786 | 4788 |
|| Duration | 11m 0s | 10m 10s |
| Windows, pyarrow-latest ||||
|| Passed tests | 4783 | 4783 |
|| Duration | 29m 59s | 22m 56s | | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"Thanks a lot @albertvillanova ! I hope we're finally done with flakiness on windows ^^\r\n\r\nAlso thanks for paying extra attention to billing and avoiding running unnecessary jobs. Though for certain aspects (see my comments), I th... |
https://api.github.com/repos/huggingface/datasets/issues/5448 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5448/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5448/comments | https://api.github.com/repos/huggingface/datasets/issues/5448/events | https://github.com/huggingface/datasets/issues/5448 | 1,550,618,514 | I_kwDODunzps5cbI-S | 5,448 | Support fsspec 2023.1.0 in CI | [
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] | closed | false | null | 0 | 2023-01-20T10:26:31Z | 2023-01-20T13:26:05Z | 2023-01-20T13:26:05Z | null | Once we find out the root cause of:
- #5445
we should revert the temporary pin on fsspec introduced by:
- #5447 | {
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https://api.github.com/repos/huggingface/datasets/issues/854 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/854/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/854/comments | https://api.github.com/repos/huggingface/datasets/issues/854/events | https://github.com/huggingface/datasets/issues/854 | 743,675,376 | MDU6SXNzdWU3NDM2NzUzNzY= | 854 | wmt16 does not download | [
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] | closed | false | null | 12 | 2020-11-16T09:31:51Z | 2022-10-05T12:27:42Z | 2022-10-05T12:27:42Z | null | Hi, I appreciate your help with the following error, thanks
>>> from datasets import load_dataset
>>> dataset = load_dataset("wmt16", "ro-en", split="train")
Downloading and preparing dataset wmt16/ro-en (download: Unknown size, generated: Unknown size, post-processed: Unknown size, total: Unknown size) to /root/.cache/huggingface/datasets/wmt16/ro-en/1.0.0/7b2c4443a7d34c2e13df267eaa8cab4c62dd82f6b62b0d9ecc2e3a673ce17308...
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/root/anaconda3/envs/pytorch/lib/python3.6/site-packages/datasets/load.py", line 611, in load_dataset
ignore_verifications=ignore_verifications,
File "/root/anaconda3/envs/pytorch/lib/python3.6/site-packages/datasets/builder.py", line 476, in download_and_prepare
dl_manager=dl_manager, verify_infos=verify_infos, **download_and_prepare_kwargs
File "/root/anaconda3/envs/pytorch/lib/python3.6/site-packages/datasets/builder.py", line 531, in _download_and_prepare
split_generators = self._split_generators(dl_manager, **split_generators_kwargs)
File "/root/.cache/huggingface/modules/datasets_modules/datasets/wmt16/7b2c4443a7d34c2e13df267eaa8cab4c62dd82f6b62b0d9ecc2e3a673ce17308/wmt_utils.py", line 755, in _split_generators
downloaded_files = dl_manager.download_and_extract(urls_to_download)
File "/root/anaconda3/envs/pytorch/lib/python3.6/site-packages/datasets/utils/download_manager.py", line 254, in download_and_extract
return self.extract(self.download(url_or_urls))
File "/root/anaconda3/envs/pytorch/lib/python3.6/site-packages/datasets/utils/download_manager.py", line 179, in download
num_proc=download_config.num_proc,
File "/root/anaconda3/envs/pytorch/lib/python3.6/site-packages/datasets/utils/py_utils.py", line 225, in map_nested
_single_map_nested((function, obj, types, None, True)) for obj in tqdm(iterable, disable=disable_tqdm)
File "/root/anaconda3/envs/pytorch/lib/python3.6/site-packages/datasets/utils/py_utils.py", line 225, in <listcomp>
_single_map_nested((function, obj, types, None, True)) for obj in tqdm(iterable, disable=disable_tqdm)
File "/root/anaconda3/envs/pytorch/lib/python3.6/site-packages/datasets/utils/py_utils.py", line 181, in _single_map_nested
mapped = [_single_map_nested((function, v, types, None, True)) for v in pbar]
File "/root/anaconda3/envs/pytorch/lib/python3.6/site-packages/datasets/utils/py_utils.py", line 181, in <listcomp>
mapped = [_single_map_nested((function, v, types, None, True)) for v in pbar]
File "/root/anaconda3/envs/pytorch/lib/python3.6/site-packages/datasets/utils/py_utils.py", line 163, in _single_map_nested
return function(data_struct)
File "/root/anaconda3/envs/pytorch/lib/python3.6/site-packages/datasets/utils/file_utils.py", line 308, in cached_path
use_etag=download_config.use_etag,
File "/root/anaconda3/envs/pytorch/lib/python3.6/site-packages/datasets/utils/file_utils.py", line 475, in get_from_cache
raise ConnectionError("Couldn't reach {}".format(url))
ConnectionError: Couldn't reach http://opus.nlpl.eu/download.php?f=SETIMES/v2/tmx/en-ro.tmx.gz | {
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"Hi,I also posted it to the forum, but this is a bug, perhaps it needs to be reported here? thanks ",
"It looks like the official OPUS server for WMT16 doesn't provide the data files anymore (503 error).\r\nI searched a bit and couldn't find a mirror except maybe http://nlp.ffzg.hr/resources/corpora/setimes/ (the... |
https://api.github.com/repos/huggingface/datasets/issues/5985 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5985/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5985/comments | https://api.github.com/repos/huggingface/datasets/issues/5985/events | https://github.com/huggingface/datasets/issues/5985 | 1,771,588,158 | I_kwDODunzps5pmEo- | 5,985 | Cannot reuse tokenizer object for dataset map | [
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] | closed | false | null | 2 | 2023-06-23T14:45:31Z | 2023-07-21T14:09:14Z | 2023-07-21T14:09:14Z | null | ### Describe the bug
Related to https://github.com/huggingface/transformers/issues/24441. Not sure if this is a tokenizer issue or caching issue, so filing in both.
Passing the tokenizer to the dataset map function causes the tokenizer to be fingerprinted weirdly. After calling the tokenizer with arguments like padding and truncation the tokenizer object changes interanally, even though the hash remains the same.
But dumps is able to detect that internal change which causes the tokenizer object's fingerprint to change.
### Steps to reproduce the bug
```python
from transformers import AutoTokenizer
from datasets.utils.py_utils import dumps # Huggingface datasets
t = AutoTokenizer.from_pretrained('bert-base-uncased')
t.save_pretrained("tok1")
th1 = hash(dumps(t))
text = "This is an example text"
ttext = t(text, max_length=512, padding="max_length", truncation=True)
t.save_pretrained("tok2")
th2 = hash(dumps(t))
assert th1 == th2 # Assertion Error
```
But if you use just the hash of the object without dumps, the hashes don't change
```python
from transformers import AutoTokenizer
from datasets.utils.py_utils import dumps # Huggingface datasets
t = AutoTokenizer.from_pretrained('bert-base-uncased')
th1 = hash(t) # Just hash no dumps
text = "This is an example text"
ttext = t(text, max_length=512, padding="max_length", truncation=True)
th2 = hash(t) # Just hash no dumps
assert th1 == th2 # This is OK
```
This causes situations such as the following
1. Create a text file like this `yes "This is an example text" | head -n 10000 > lines.txt`
```python
from transformers import AutoTokenizer
import datasets
class TokenizeMapper(object):
"""Mapper for tokenizer.
This is needed because the caching mechanism of HuggingFace does not work on
lambdas. Each time a new lambda will be created by a new process which will
lead to a different hash.
This way we can have a universal mapper object in init and reuse it with the same
hash for each process.
"""
def __init__(self, tokenizer):
"""Initialize the tokenizer."""
self.tokenizer = tokenizer
def __call__(self, examples, **kwargs):
"""Run the mapper."""
texts = examples["text"]
tt = self.tokenizer(texts, max_length=256, padding="max_length", truncation=True)
batch_outputs = {
"input_ids": tt.input_ids,
"attention_mask": tt.attention_mask,
}
return batch_outputs
t = AutoTokenizer.from_pretrained('bert-base-uncased')
mapper = TokenizeMapper(t)
ds = datasets.load_dataset("text", data_files="lines.txt")
mds1 = ds.map(
mapper,
batched=False,
remove_columns=["text"],
).with_format("torch")
mds2 = ds.map(
mapper,
batched=False,
remove_columns=["text"],
).with_format("torch")
```
The second call to map should reuse the cached processed dataset from mds1, but it instead it redoes the tokenization because of the behavior of dumps.
### Expected behavior
We should be able to initialize a tokenizer. And reusing it should let us reuse the same map computation for the same dataset.
The second call to map should reuse the cached processed dataset from mds1, but it instead it redoes the tokenization because of the behavior of dumps.
### Environment info
- `datasets` version: 2.13.0
- Platform: Linux-6.1.31_1-x86_64-with-glibc2.36
- Python version: 3.9.16
- Huggingface_hub version: 0.15.1
- PyArrow version: 12.0.1
- Pandas version: 2.0.2 | {
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"This is a known issue: https://github.com/huggingface/datasets/issues/3847.\r\n\r\nFixing this requires significant work - rewriting the `tokenizers` lib to make them immutable.\r\n\r\nThe current solution is to pass `cache_file_name` to `map` to use that file for caching or calling a tokenizer before `map` (with ... |
https://api.github.com/repos/huggingface/datasets/issues/5747 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5747/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5747/comments | https://api.github.com/repos/huggingface/datasets/issues/5747/events | https://github.com/huggingface/datasets/pull/5747 | 1,667,270,412 | PR_kwDODunzps5ORtBF | 5,747 | [WIP] Add Dataset.to_spark | [] | open | false | null | 0 | 2023-04-13T23:20:03Z | 2023-05-05T12:31:10Z | null | null | null | {
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