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"#self-assign"
] | 2021-06-11T18:47:22 | 2021-07-05T10:45:57 | 2021-07-05T10:45:57 | MEMBER | null | null | null | As discussed with @stas00 and @lhoestq, this would allow things like:
```python
from datasets import load_dataset_builder
dataset_name = "openwebtext"
builder = load_dataset_builder(dataset_name)
print(builder.cache_dir)
``` | {
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"Hello, @lhoestq / @gaceladri : We have been seeing similar behavior with bigger datasets, where querying time increases. Are you folks aware of any solution that fixes this problem yet? ",
"Hi ! I'm pretty sure that it can be fixed by using the Arrow IPC file format instead of the raw streaming format but I ha... | 2021-02-01T11:08:23 | 2021-08-04T18:11:01 | 2021-08-04T18:10:42 | MEMBER | null | null | null | After some experiments with bookcorpus I noticed that querying examples from big datasets is slower than small datasets.
For example
```python
from datasets import load_dataset
b1 = load_dataset("bookcorpus", split="train[:1%]")
b50 = load_dataset("bookcorpus", split="train[:50%]")
b100 = load_dataset("bookcorpus", split="train[:100%]")
%timeit _ = b1[-1]
# 12.2 µs ± 70.4 ns per loop (mean ± std. dev. of 7 runs, 100000 loops each)
%timeit _ = b50[-1]
# 92.5 µs ± 1.24 µs per loop (mean ± std. dev. of 7 runs, 10000 loops each)
%timeit _ = b100[-1]
# 177 µs ± 3.13 µs per loop (mean ± std. dev. of 7 runs, 10000 loops each)
```
It looks like the time to fetch the example increases with the size of the dataset.
This is maybe due to the use of the Arrow streaming format to store the data on disk. I guess pyarrow needs to iterate through the file as a stream to find the queried sample.
Maybe switching to the Arrow IPC file format could help fixing this issue.
Indeed according to the [documentation](https://arrow.apache.org/docs/format/Columnar.html?highlight=arrow1#ipc-file-format), it's identical to the streaming format except that it contains the memory offsets of each sample, which could fix the issue:
> We define a “file format” supporting random access that is build with the stream format. The file starts and ends with a magic string ARROW1 (plus padding). What follows in the file is identical to the stream format. At the end of the file, we write a footer containing a redundant copy of the schema (which is a part of the streaming format) plus memory offsets and sizes for each of the data blocks in the file. This enables random access any record batch in the file. See File.fbs for the precise details of the file footer.
cc @gaceladri since it can help speed up your training when this one is fixed. | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"Currently the github datasets versioning is synced with the `datasets` lib versioning: when you load a github dataset using `datasets==x.y.z`, then the version of the dataset will be the one at the git tag `x.y.z`. This is for reprod... | 2022-03-30T09:21:56 | 2022-09-16T12:43:26 | 2022-09-16T12:40:43 | MEMBER | null | 0 | {
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} | We have recurrently had connection errors when requesting GitHub because sometimes the site is not available.
This PR requests the Hub instead, once all GitHub datasets are mirrored on the Hub.
Fix #2048
Related to:
- #4051
- #3210
- #2787
- #2075
- #2036 | {
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This was discussed in Issue #1762 where the docs didn't mention that keyword arguments to `datasets.Dataset.set_format()` are allowed.
To prevent people from having to check the code/method docs, I just added a couple of lines in the docs.
Please let me know your thoughts on this.
Thanks,
Gunjan
@lhoestq | {
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https://api.github.com/repos/huggingface/datasets/issues/2957 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2957/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2957/comments | https://api.github.com/repos/huggingface/datasets/issues/2957/events | https://github.com/huggingface/datasets/issues/2957 | 1,004,868,337 | I_kwDODunzps475RLx | 2,957 | MultiWOZ Dataset NonMatchingChecksumError | {
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"Hi Brady! I met the similar issue, it stuck in the downloading stage instead of download anything, maybe it is broken. After I change the downloading from URLs to one url of the [Multiwoz project](https://github.com/budzianowski/multiwoz/archive/44f0f8479f11721831c5591b839ad78827da197b.zip) and use dirs to get sep... | 2021-09-22T23:45:00 | 2022-03-15T16:07:02 | 2022-03-15T16:07:02 | NONE | null | null | null | ## Describe the bug
The checksums for the downloaded MultiWOZ dataset and source MultiWOZ dataset aren't matching.
## Steps to reproduce the bug
Both of the below dataset versions yield the checksum error:
```python
from datasets import load_dataset
dataset = load_dataset('multi_woz_v22', 'v2.2')
dataset = load_dataset('multi_woz_v22', 'v2.2_active_only')
```
## Expected results
For the above calls to `load_dataset` to work.
## Actual results
NonMatchingChecksumError. Traceback:
> Traceback (most recent call last):
File "/Users/brady/anaconda3/envs/elysium/lib/python3.8/site-packages/IPython/core/interactiveshell.py", line 3441, in run_code
exec(code_obj, self.user_global_ns, self.user_ns)
File "<ipython-input-15-4e91280e112e>", line 1, in <module>
dataset = load_dataset('multi_woz_v22', 'v2.2')
File "/Users/brady/anaconda3/envs/elysium/lib/python3.8/site-packages/datasets/load.py", line 847, in load_dataset
builder_instance.download_and_prepare(
File "/Users/brady/anaconda3/envs/elysium/lib/python3.8/site-packages/datasets/builder.py", line 615, in download_and_prepare
self._download_and_prepare(
File "/Users/brady/anaconda3/envs/elysium/lib/python3.8/site-packages/datasets/builder.py", line 675, in _download_and_prepare
verify_checksums(
File "/Users/brady/anaconda3/envs/elysium/lib/python3.8/site-packages/datasets/utils/info_utils.py", line 40, in verify_checksums
raise NonMatchingChecksumError(error_msg + str(bad_urls))
datasets.utils.info_utils.NonMatchingChecksumError: Checksums didn't match for dataset source files:
['https://github.com/budzianowski/multiwoz/raw/master/data/MultiWOZ_2.2/dialog_acts.json', 'https://github.com/budzianowski/multiwoz/raw/master/data/MultiWOZ_2.2/test/dialogues_001.json']
## Environment info
- `datasets` version: 1.11.0
- Platform: macOS-10.15.7-x86_64-i386-64bit
- Python version: 3.8.10
- PyArrow version: 5.0.0
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https://api.github.com/repos/huggingface/datasets/issues/2765 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2765/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2765/comments | https://api.github.com/repos/huggingface/datasets/issues/2765/events | https://github.com/huggingface/datasets/issues/2765 | 962,861,395 | MDU6SXNzdWU5NjI4NjEzOTU= | 2,765 | BERTScore Error | {
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"Hi,\r\n\r\nThe `use_fast_tokenizer` argument has been recently added to the bert-score lib. I've opened a PR with the fix. In the meantime, you can try to downgrade the version of bert-score with the following command to make the code work:\r\n```\r\npip uninstall bert-score\r\npip install \"bert-score<0.3.10\"\r\... | 2021-08-06T15:58:57 | 2021-08-09T11:16:25 | 2021-08-09T11:16:25 | NONE | null | null | null | ## Describe the bug
A clear and concise description of what the bug is.
## Steps to reproduce the bug
```python
predictions = ["hello there", "general kenobi"]
references = ["hello there", "general kenobi"]
bert = load_metric('bertscore')
bert.compute(predictions=predictions, references=references,lang='en')
```
# Bug
`TypeError: get_hash() missing 1 required positional argument: 'use_fast_tokenizer'`
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version:
- Platform: Colab
- Python version:
- PyArrow version:
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https://api.github.com/repos/huggingface/datasets/issues/4243 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4243/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4243/comments | https://api.github.com/repos/huggingface/datasets/issues/4243/events | https://github.com/huggingface/datasets/pull/4243 | 1,217,689,909 | PR_kwDODunzps425Gkn | 4,243 | WIP: Initial shades loading script and readme | {
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"Thanks for your contribution, @shayne-longpre.\r\n\r\nAre you still interested in adding this dataset? As we are transferring the dataset scripts from this GitHub repo, we would recommend you to add this to the Hugging Face Hub: https://huggingface.co/datasets"
] | 2022-04-27T17:45:43 | 2022-10-03T09:36:35 | 2022-10-03T09:36:35 | NONE | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/2225 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2225/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2225/comments | https://api.github.com/repos/huggingface/datasets/issues/2225/events | https://github.com/huggingface/datasets/pull/2225 | 858,469,561 | MDExOlB1bGxSZXF1ZXN0NjE1NzAzMTY4 | 2,225 | fixed one instance of 'train' to 'test' | {
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"Thanks ! good catch\r\n\r\nCould you also update the metadata of this dataset ?\r\nYou can do so by running\r\n```\r\ndatasets-cli test ./datasets/newsgroup --all_configs --save_infos --ignore_verifications\r\n```\r\nThis should update the dataset_infos.json file that contains the size of all the splits for exampl... | 2021-04-15T04:26:40 | 2021-04-15T22:09:50 | 2021-04-15T21:19:09 | CONTRIBUTOR | null | 0 | {
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} | I believe this should be 'test' instead of 'train' | {
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https://api.github.com/repos/huggingface/datasets/issues/1540 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1540/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1540/comments | https://api.github.com/repos/huggingface/datasets/issues/1540/events | https://github.com/huggingface/datasets/pull/1540 | 765,357,702 | MDExOlB1bGxSZXF1ZXN0NTM4OTQ1NDc2 | 1,540 | added TTC4900: A Benchmark Data for Turkish Text Categorization dataset | {
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"@lhoestq, can you help with creating dummy_data?\r\n",
"Hi @yavuzKomecoglu did you manage to build the dummy data ?",
"> Hi @yavuzKomecoglu did you manage to build the dummy data ?\r\n\r\nHi, sorry for the return. I've created dummy_data.zip manually.",
"> Nice thank you !\r\n> \r\n> Before we merge can you ... | 2020-12-13T12:43:33 | 2020-12-18T10:09:01 | 2020-12-18T10:09:01 | CONTRIBUTOR | null | 0 | {
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} | This PR adds the TTC4900 dataset which is a Turkish Text Categorization dataset by me and @basakbuluz.
Homepage: [https://www.kaggle.com/savasy/ttc4900](https://www.kaggle.com/savasy/ttc4900)
Point of Contact: [Savaş Yıldırım](mailto:savasy@gmail.com) / @savasy
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https://api.github.com/repos/huggingface/datasets/issues/1420 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1420/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1420/comments | https://api.github.com/repos/huggingface/datasets/issues/1420/events | https://github.com/huggingface/datasets/pull/1420 | 760,700,388 | MDExOlB1bGxSZXF1ZXN0NTM1NDg4MTM5 | 1,420 | Add dataset yoruba_wordsim353 | {
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"merging since the CI is fixed on master"
] | 2020-12-09T21:54:29 | 2020-12-11T13:34:04 | 2020-12-11T13:34:04 | CONTRIBUTOR | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/2248 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2248/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2248/comments | https://api.github.com/repos/huggingface/datasets/issues/2248/events | https://github.com/huggingface/datasets/pull/2248 | 864,853,447 | MDExOlB1bGxSZXF1ZXN0NjIxMDEyNzg5 | 2,248 | Implement Dataset to JSON | {
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} | [] | 2021-04-22T11:46:51 | 2021-04-27T15:29:21 | 2021-04-27T15:29:20 | MEMBER | null | 0 | {
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} | Implement `Dataset.to_json`. | {
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https://api.github.com/repos/huggingface/datasets/issues/3215 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3215/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3215/comments | https://api.github.com/repos/huggingface/datasets/issues/3215/events | https://github.com/huggingface/datasets/pull/3215 | 1,045,011,207 | PR_kwDODunzps4uGx4o | 3,215 | Small updates to to_tf_dataset documentation | {
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"@stevhliu Accepted both suggestions, thanks for the review!"
] | 2021-11-04T17:22:01 | 2021-11-04T18:55:38 | 2021-11-04T18:55:37 | MEMBER | null | 0 | {
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} | I added a little more description about `to_tf_dataset` compared to just setting the format | {
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https://api.github.com/repos/huggingface/datasets/issues/1809 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1809/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1809/comments | https://api.github.com/repos/huggingface/datasets/issues/1809/events | https://github.com/huggingface/datasets/pull/1809 | 799,059,141 | MDExOlB1bGxSZXF1ZXN0NTY1NzY4ODQz | 1,809 | Add FreebaseQA dataset | {
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"Hi ! It looks like this PR contains changes about other datasets than freebase_qa such as DuoRC.\r\n\r\nCan you remove these changes please ?",
"Hi @lhoestq,\r\n\r\nI think this happened because of rebasing. I'm unable to remove the duorc commit from the branch. GEM, Arabic sarcasm datasets are also there. I ca... | 2021-02-02T08:35:53 | 2021-02-03T17:15:05 | 2021-02-03T16:43:06 | CONTRIBUTOR | null | 0 | {
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} | Adding FreebaseQA dataset suggested in PR #1435 with minor edits. Also closes that PR.
Requesting @lhoestq to review. | {
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https://api.github.com/repos/huggingface/datasets/issues/1758 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1758/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1758/comments | https://api.github.com/repos/huggingface/datasets/issues/1758/events | https://github.com/huggingface/datasets/issues/1758 | 790,626,116 | MDU6SXNzdWU3OTA2MjYxMTY= | 1,758 | dataset.search() (elastic) cannot reliably retrieve search results | {
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"Hi !\r\nI tried your code on my side and I was able to workaround this issue by waiting a few seconds before querying the index.\r\nMaybe this is because the index is not updated yet on the ElasticSearch side ?",
"Thanks for the feedback! I added a 30 second \"sleep\" and that seemed to work well!"
] | 2021-01-21T02:26:37 | 2021-01-22T00:25:50 | 2021-01-22T00:25:50 | NONE | null | null | null | I am trying to use elastic search to retrieve the indices of items in the dataset in their precise order, given shuffled training indices.
The problem I have is that I cannot retrieve reliable results with my data on my first search. I have to run the search **twice** to get the right answer.
I am indexing data that looks like the following from the HF SQuAD 2.0 data set:
```
['57318658e6313a140071d02b',
'56f7165e3d8e2e1400e3733a',
'570e2f6e0b85d914000d7d21',
'5727e58aff5b5019007d97d0',
'5a3b5a503ff257001ab8441f',
'57262fab271a42140099d725']
```
To reproduce the issue, try:
```
from datasets import load_dataset, load_metric
from transformers import BertTokenizerFast, BertForQuestionAnswering
from elasticsearch import Elasticsearch
import numpy as np
import collections
from tqdm.auto import tqdm
import torch
# from https://colab.research.google.com/github/huggingface/notebooks/blob/master/examples/question_answering.ipynb#scrollTo=941LPhDWeYv-
tokenizer = BertTokenizerFast.from_pretrained('bert-base-uncased')
max_length = 384 # The maximum length of a feature (question and context)
doc_stride = 128 # The authorized overlap between two part of the context when splitting it is needed.
pad_on_right = tokenizer.padding_side == "right"
squad_v2 = True
# from https://colab.research.google.com/github/huggingface/notebooks/blob/master/examples/question_answering.ipynb#scrollTo=941LPhDWeYv-
def prepare_validation_features(examples):
# Tokenize our examples with truncation and maybe padding, but keep the overflows using a stride. This results
# in one example possible giving several features when a context is long, each of those features having a
# context that overlaps a bit the context of the previous feature.
tokenized_examples = tokenizer(
examples["question" if pad_on_right else "context"],
examples["context" if pad_on_right else "question"],
truncation="only_second" if pad_on_right else "only_first",
max_length=max_length,
stride=doc_stride,
return_overflowing_tokens=True,
return_offsets_mapping=True,
padding="max_length",
)
# Since one example might give us several features if it has a long context, we need a map from a feature to
# its corresponding example. This key gives us just that.
sample_mapping = tokenized_examples.pop("overflow_to_sample_mapping")
# We keep the example_id that gave us this feature and we will store the offset mappings.
tokenized_examples["example_id"] = []
for i in range(len(tokenized_examples["input_ids"])):
# Grab the sequence corresponding to that example (to know what is the context and what is the question).
sequence_ids = tokenized_examples.sequence_ids(i)
context_index = 1 if pad_on_right else 0
# One example can give several spans, this is the index of the example containing this span of text.
sample_index = sample_mapping[i]
tokenized_examples["example_id"].append(examples["id"][sample_index])
# Set to None the offset_mapping that are not part of the context so it's easy to determine if a token
# position is part of the context or not.
tokenized_examples["offset_mapping"][i] = [
(list(o) if sequence_ids[k] == context_index else None)
for k, o in enumerate(tokenized_examples["offset_mapping"][i])
]
return tokenized_examples
# build base examples, features set of training data
shuffled_idx = pd.read_csv('https://raw.githubusercontent.com/afogarty85/temp/main/idx.csv')['idx'].to_list()
examples = load_dataset("squad_v2").shuffle(seed=1)['train']
features = load_dataset("squad_v2").shuffle(seed=1)['train'].map(
prepare_validation_features,
batched=True,
remove_columns=['answers', 'context', 'id', 'question', 'title'])
# reorder features by the training process
features = features.select(indices=shuffled_idx)
# get the example ids to match with the "example" data; get unique entries
id_list = list(dict.fromkeys(features['example_id']))
# now search for their index positions in the examples data set; load elastic search
es = Elasticsearch([{'host': 'localhost'}]).ping()
# add an index to the id column for the examples
examples.add_elasticsearch_index(column='id')
# retrieve the example index
example_idx_k1 = [examples.search(index_name='id', query=i, k=1).indices for i in id_list]
example_idx_k1 = [item for sublist in example_idx_k1 for item in sublist]
example_idx_k2 = [examples.search(index_name='id', query=i, k=3).indices for i in id_list]
example_idx_k2 = [item for sublist in example_idx_k2 for item in sublist]
len(example_idx_k1) # should be 130319
len(example_idx_k2) # should be 130319
#trial 1 lengths:
# k=1: 130314
# k=3: 130319
# trial 2:
# just run k=3 first: 130310
# try k=1 after k=3: 130319
```
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https://api.github.com/repos/huggingface/datasets/issues/4752 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4752/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4752/comments | https://api.github.com/repos/huggingface/datasets/issues/4752/events | https://github.com/huggingface/datasets/issues/4752 | 1,319,464,409 | I_kwDODunzps5OpW3Z | 4,752 | DatasetInfo issue when testing multiple configs: mixed task_templates | {
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"I've narrowed down the issue to the `dataset_module_factory` which already creates a `dataset_infos.json` file down in the `.cache/modules/dataset_modules/..` folder. That JSON file already contains the wrong task_templates for `unfiltered`.",
"Ugh. Found the issue: apparently `datasets` was reusing the already ... | 2022-07-27T12:04:54 | 2022-08-08T18:20:50 | null | CONTRIBUTOR | null | null | null | ## Describe the bug
When running the `datasets-cli test` it would seem that some config properties in a DatasetInfo get mangled, leading to issues, e.g., about the ClassLabel.
## Steps to reproduce the bug
In summary, what I want to do is create three configs:
- unfiltered: no classlabel, no tasks. Gets data from unfiltered.json.gz (I'd want this without splits, just one chunk of data, but that does not seem possible?)
- filtered_sentiment: `review_sentiment` as ClassLabel, TextClassification task with `review_sentiment` as label. Gets train/test split from respective json.gz files
- filtered_rating: `review_rating0` as ClassLabel, TextClassification task with `review_rating0` as label. Gets train/test split from respective json.gz files
This might be a bit tedious to reproduce, so I am sorry, but these are the steps:
- Clone datasets -> `datasets/` and install it
- Clone `https://huggingface.co/datasets/BramVanroy/hebban-reviews` into `datasets/datasets` so that you have a new folder `datasets/datasets/hebban-reviews/`.
- Replace the HebbanReviews class with this new one:
```python
class HebbanReviews(datasets.GeneratorBasedBuilder):
"""The Hebban book reviews dataset."""
BUILDER_CONFIGS = [
HebbanReviewsConfig(
name="unfiltered",
description=_HEBBAN_REVIEWS_UNFILTERED_DESCRIPTION,
version=datasets.Version(_HEBBAN_VERSION)
),
HebbanReviewsConfig(
name="filtered_sentiment",
description=f"This config has the negative, neutral, and positive sentiment scores as ClassLabel in the 'review_sentiment' column.\n{_HEBBAN_REVIEWS_FILTERED_DESCRIPTION}",
version=datasets.Version(_HEBBAN_VERSION)
),
HebbanReviewsConfig(
name="filtered_rating",
description=f"This config has the 5-class ratings as ClassLabel in the 'review_rating0' column (which is a variant of 'review_rating' that starts counting from 0 instead of 1).\n{_HEBBAN_REVIEWS_FILTERED_DESCRIPTION}",
version=datasets.Version(_HEBBAN_VERSION)
)
]
DEFAULT_CONFIG_NAME = "filtered_sentiment"
_URLS = {
"train": "train.jsonl.gz",
"test": "test.jsonl.gz",
"unfiltered": "unfiltered.jsonl.gz",
}
def _info(self):
features = {
"review_title": datasets.Value("string"),
"review_text": datasets.Value("string"),
"review_text_without_quotes": datasets.Value("string"),
"review_n_quotes": datasets.Value("int32"),
"review_n_tokens": datasets.Value("int32"),
"review_rating": datasets.Value("int32"),
"review_rating0": datasets.Value("int32"),
"review_author_url": datasets.Value("string"),
"review_author_type": datasets.Value("string"),
"review_n_likes": datasets.Value("int32"),
"review_n_comments": datasets.Value("int32"),
"review_url": datasets.Value("string"),
"review_published_date": datasets.Value("string"),
"review_crawl_date": datasets.Value("string"),
"lid": datasets.Value("string"),
"lid_probability": datasets.Value("float32"),
"review_sentiment": datasets.features.ClassLabel(names=["negative", "neutral", "positive"]),
"review_sentiment_label": datasets.Value("string"),
"book_id": datasets.Value("int32"),
}
if self.config.name == "filtered_sentiment":
task_templates = [datasets.TextClassification(text_column="review_text_without_quotes", label_column="review_sentiment")]
elif self.config.name == "filtered_rating":
# For CrossEntropy, our classes need to start at index 0 -- not 1
features["review_rating0"] = datasets.features.ClassLabel(names=["1", "2", "3", "4", "5"])
features["review_sentiment"] = datasets.Value("int32")
task_templates = [datasets.TextClassification(text_column="review_text_without_quotes", label_column="review_rating0")]
elif self.config.name == "unfiltered": # no ClassLabels in unfiltered
features["review_sentiment"] = datasets.Value("int32")
task_templates = None
else:
raise ValueError(f"Unsupported config {self.config.name}. Expected one of 'filtered_sentiment' (default),"
f" 'filtered_rating', or 'unfiltered'")
print("AT INFO", self.config.name, task_templates)
return datasets.DatasetInfo(
description=self.config.description,
features=datasets.Features(features),
homepage="https://huggingface.co/datasets/BramVanroy/hebban-reviews",
citation=_HEBBAN_REVIEWS_CITATION,
task_templates=task_templates,
license="cc-by-4.0"
)
def _split_generators(self, dl_manager):
if self.config.name.startswith("filtered"):
files = dl_manager.download_and_extract({"train": "train.jsonl.gz",
"test": "test.jsonl.gz"})
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={
"data_file": files["train"]
},
),
datasets.SplitGenerator(
name=datasets.Split.TEST,
gen_kwargs={
"data_file": files["test"]
},
),
]
elif self.config.name == "unfiltered":
files = dl_manager.download_and_extract({"train": "unfiltered.jsonl.gz"})
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={
"data_file": files["train"]
},
),
]
else:
raise ValueError(f"Unsupported config {self.config.name}. Expected one of 'filtered_sentiment' (default),"
f" 'filtered_rating', or 'unfiltered'")
def _generate_examples(self, data_file):
lines = Path(data_file).open(encoding="utf-8").readlines()
for line_idx, line in enumerate(lines):
row = json.loads(line)
yield line_idx, row
```
- finally, run `datasets-cli test ./datasets/hebban-reviews/ --save_infos --all_configs` from within the topmost `datasets` directory
## Expected results
Succeeding tests for three different configs.
## Actual results
I printed out the values that are given to `DatasetInfo` for config name and task_templates, as you can see. There, as expected, I get `unfiltered None`. I also modified datasets/info.py and added this line [at L.170](https://github.com/huggingface/datasets/blob/f5847a304aa1b38b3a3c54a8318b4df60f1299bc/src/datasets/info.py#L170):
```python
print("INTERNALLY AT INFO.PY", self.config_name, self.task_templates)
```
to my surprise, here I get `unfiltered [TextClassification(task='text-classification', text_column='review_text_without_quotes', label_column='review_sentiment')]`. So one way or another, here I suddenly see that `unfiltered` now does have a task_template -- even though that is not what is written in the data loading script, as the first print statement correctly shows.
I do not quite understand how, but it seems that the config name and task_templates get mixed.
This ultimately leads to the following error, but this trace may not be very useful in itself:
```
Traceback (most recent call last):
File "C:\Users\bramv\.virtualenvs\hebban-U6poXNQd\Scripts\datasets-cli-script.py", line 33, in <module>
sys.exit(load_entry_point('datasets', 'console_scripts', 'datasets-cli')())
File "c:\dev\python\hebban\datasets\src\datasets\commands\datasets_cli.py", line 39, in main
service.run()
File "c:\dev\python\hebban\datasets\src\datasets\commands\test.py", line 144, in run
builder.as_dataset()
File "c:\dev\python\hebban\datasets\src\datasets\builder.py", line 899, in as_dataset
datasets = map_nested(
File "c:\dev\python\hebban\datasets\src\datasets\utils\py_utils.py", line 393, in map_nested
mapped = [
File "c:\dev\python\hebban\datasets\src\datasets\utils\py_utils.py", line 394, in <listcomp>
_single_map_nested((function, obj, types, None, True, None))
File "c:\dev\python\hebban\datasets\src\datasets\utils\py_utils.py", line 330, in _single_map_nested
return function(data_struct)
File "c:\dev\python\hebban\datasets\src\datasets\builder.py", line 930, in _build_single_dataset
ds = self._as_dataset(
File "c:\dev\python\hebban\datasets\src\datasets\builder.py", line 1006, in _as_dataset
return Dataset(fingerprint=fingerprint, **dataset_kwargs)
File "c:\dev\python\hebban\datasets\src\datasets\arrow_dataset.py", line 661, in __init__
info = info.copy() if info is not None else DatasetInfo()
File "c:\dev\python\hebban\datasets\src\datasets\info.py", line 286, in copy
return self.__class__(**{k: copy.deepcopy(v) for k, v in self.__dict__.items()})
File "<string>", line 20, in __init__
File "c:\dev\python\hebban\datasets\src\datasets\info.py", line 176, in __post_init__
self.task_templates = [
File "c:\dev\python\hebban\datasets\src\datasets\info.py", line 177, in <listcomp>
template.align_with_features(self.features) for template in (self.task_templates)
File "c:\dev\python\hebban\datasets\src\datasets\tasks\text_classification.py", line 22, in align_with_features
raise ValueError(f"Column {self.label_column} is not a ClassLabel.")
ValueError: Column review_sentiment is not a ClassLabel.
```
## Environment info
- `datasets` version: 2.4.1.dev0
- Platform: Windows-10-10.0.19041-SP0
- Python version: 3.8.8
- PyArrow version: 8.0.0
- Pandas version: 1.4.3 | {
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### Description
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### Owner
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https://api.github.com/repos/huggingface/datasets/issues/4780 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4780/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4780/comments | https://api.github.com/repos/huggingface/datasets/issues/4780/events | https://github.com/huggingface/datasets/pull/4780 | 1,326,034,767 | PR_kwDODunzps48g9oA | 4,780 | Remove apache_beam import from module level in natural_questions dataset | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-08-02T15:34:54 | 2022-08-02T16:16:33 | 2022-08-02T16:03:17 | MEMBER | null | 0 | {
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} | Instead of importing `apache_beam` at the module level, import it in the method `_build_pcollection`.
Fix #4779. | {
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https://api.github.com/repos/huggingface/datasets/issues/2486 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2486/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2486/comments | https://api.github.com/repos/huggingface/datasets/issues/2486/events | https://github.com/huggingface/datasets/pull/2486 | 919,174,898 | MDExOlB1bGxSZXF1ZXN0NjY4NTI2Njg3 | 2,486 | Add Rico Dataset | {
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"Hi ! Thanks for adding this dataset :)\r\n\r\nRegarding your questions:\r\n1. We can have them as different configuration of the `rico` dataset\r\n2. Yes please use the path to the image and not open the image directly, so that we can let users open the image one at at time during training if they want to for exam... | 2021-06-11T20:17:41 | 2022-10-03T09:38:18 | 2022-10-03T09:38:18 | NONE | null | 0 | {
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I'm wanting to add the Rico datasets for software engineering type data to y'alls awesome library. However, as I have started coding, I've ran into a few hiccups so I thought it best to open the PR early to get a bit of discussion on how the Rico datasets should be added to the `datasets` lib.
1) There are 7 different datasets under Rico and so I was wondering, should I make a folder for each or should I put them as different configurations of a single dataset?
You can see the datasets available for Rico here: http://interactionmining.org/rico
2) As of right now, I have a semi working version of the first dataset which has pairs of screenshots and hierarchies from android applications. However, these screenshots are very large (1440, 2560, 3) and there are 66,000 of them so I am not able to perform the processing that the `datasets` lib does after downloading and extracting the dataset since I run out of memory very fast. Is there a way to have `datasets` lib not put everything into memory while it is processing the dataset?
2.1) If there is not a way, would it be better to just return the path to the screenshots instead of the actual image?
3) The hierarchies are JSON objects and looking through the documentation of `datasets`, I didn't see any feature that I could use for this type of data. So, for now I just have it being read in as a string, is this okay or should I be doing it differently?
4) One of the Rico datasets is a bunch of animations (GIFs), is there a `datasets` feature that I can put this type of data into or should I just return the path as a string?
I appreciate any and all help I can get for this PR, I think the Rico datasets will be an awesome addition to the library :nerd_face: ! | {
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https://api.github.com/repos/huggingface/datasets/issues/5120 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5120/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5120/comments | https://api.github.com/repos/huggingface/datasets/issues/5120/events | https://github.com/huggingface/datasets/pull/5120 | 1,410,641,221 | PR_kwDODunzps5A4X10 | 5,120 | Fix `tqdm` zip bug | {
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"@albertvillanova Thanks for your comment. What do you think about creating 2 `pbar` for each case? I see the `pbar_iterable` is initialized differently. Maybe `pbar` can also be initialized like that.",
"@albertvillanova Another solution I implemented is to change `pbar_iterable` and add the `zip` to it. I updat... | 2022-10-16T22:19:18 | 2022-10-23T10:27:53 | 2022-10-19T08:53:17 | CONTRIBUTOR | null | 0 | {
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} | This PR solves #5117, by wrapping the entire `zip` clause in tqdm.
For more information, please checkout this Stack Overflow thread:
https://stackoverflow.com/questions/41171191/tqdm-progressbar-and-zip-built-in-do-not-work-together | {
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https://api.github.com/repos/huggingface/datasets/issues/5730 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5730/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5730/comments | https://api.github.com/repos/huggingface/datasets/issues/5730/events | https://github.com/huggingface/datasets/issues/5730 | 1,662,007,926 | I_kwDODunzps5jEDp2 | 5,730 | CI is broken: ValueError: Name (mock) already in the registry and clobber is False | {
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"following_url": "https://api.github.com/users/albertvillanova/following{/o... | null | [] | 2023-04-11T08:29:46 | 2023-04-11T08:47:56 | 2023-04-11T08:47:56 | MEMBER | null | null | null | CI is broken for `test_py310`.
See: https://github.com/huggingface/datasets/actions/runs/4665326892/jobs/8258580948
```
=========================== short test summary info ============================
ERROR tests/test_builder.py::test_builder_with_filesystem_download_and_prepare - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_builder.py::test_builder_with_filesystem_download_and_prepare_reload - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_dataset_dict.py::test_dummy_datasetdict_serialize_fs - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_file_utils.py::test_get_from_cache_fsspec - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_filesystem.py::test_is_remote_filesystem - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::test_xexists[tmp_path/file.txt-True] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::test_xexists[tmp_path/file_that_doesnt_exist.txt-False] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::test_xexists[mock://top_level/second_level/date=2019-10-01/a.parquet-True] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::test_xexists[mock://top_level/second_level/date=2019-10-01/file_that_doesnt_exist.parquet-False] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::test_xlistdir[tmp_path-expected_paths0] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::test_xlistdir[mock://-expected_paths1] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::test_xlistdir[mock://top_level-expected_paths2] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::test_xlistdir[mock://top_level/second_level/date=2019-10-01-expected_paths3] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::test_xisdir[tmp_path-True] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::test_xisdir[tmp_path/file.txt-False] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::test_xisdir[mock://-True] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::test_xisdir[mock://top_level-True] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::test_xisdir[mock://dir_that_doesnt_exist-False] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::test_xisfile[tmp_path/file.txt-True] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::test_xisfile[tmp_path/file_that_doesnt_exist.txt-False] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::test_xisfile[mock://-False] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::test_xisfile[mock://top_level/second_level/date=2019-10-01/a.parquet-True] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::test_xgetsize[tmp_path/file.txt-100] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::test_xgetsize[mock://-0] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::test_xgetsize[mock://top_level/second_level/date=2019-10-01/a.parquet-100] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::test_xglob[tmp_path/*.txt-expected_paths0] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::test_xglob[mock://*-expected_paths1] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::test_xglob[mock://top_*-expected_paths2] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::test_xglob[mock://top_level/second_level/date=2019-10-0[1-4]-expected_paths3] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::test_xglob[mock://top_level/second_level/date=2019-10-0[1-4]/*-expected_paths4] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::test_xwalk[tmp_path-expected_outputs0] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::test_xwalk[mock://top_level/second_level-expected_outputs1] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::TestxPath::test_xpath_exists[tmp_path/file.txt-True] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::TestxPath::test_xpath_exists[tmp_path/file_that_doesnt_exist.txt-False] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::TestxPath::test_xpath_exists[mock://top_level/second_level/date=2019-10-01/a.parquet-True] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::TestxPath::test_xpath_exists[mock://top_level/second_level/date=2019-10-01/file_that_doesnt_exist.parquet-False] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::TestxPath::test_xpath_glob[tmp_path-*.txt-expected_paths0] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::TestxPath::test_xpath_glob[mock://-*-expected_paths1] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::TestxPath::test_xpath_glob[mock://-top_*-expected_paths2] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::TestxPath::test_xpath_glob[mock://top_level/second_level-date=2019-10-0[1-4]-expected_paths3] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::TestxPath::test_xpath_glob[mock://top_level/second_level-date=2019-10-0[1-4]/*-expected_paths4] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::TestxPath::test_xpath_rglob[tmp_path-*.txt-expected_paths0] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::TestxPath::test_xpath_rglob[mock://-date=2019-10-0[1-4]-expected_paths1] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::TestxPath::test_xpath_rglob[mock://top_level-date=2019-10-0[1-4]-expected_paths2] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::TestxPath::test_xpath_rglob[mock://-date=2019-10-0[1-4]/*-expected_paths3] - ValueError: Name (mock) already in the registry and clobber is False
ERROR tests/test_streaming_download_manager.py::TestxPath::test_xpath_rglob[mock://top_level-date=2019-10-0[1-4]/*-expected_paths4] - ValueError: Name (mock) already in the registry and clobber is False
===== 2105 passed, 18 skipped, 38 warnings, 46 errors in 236.22s (0:03:56) =====
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/6054 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6054/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6054/comments | https://api.github.com/repos/huggingface/datasets/issues/6054/events | https://github.com/huggingface/datasets/issues/6054 | 1,813,271,304 | I_kwDODunzps5sFFMI | 6,054 | Multi-processed `Dataset.map` slows down a lot when `import torch` | {
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"A duplicate of https://github.com/huggingface/datasets/issues/5929"
] | 2023-07-20T06:36:14 | 2023-07-21T15:19:37 | 2023-07-21T15:19:37 | NONE | null | null | null | ### Describe the bug
When using `Dataset.map` with `num_proc > 1`, the speed slows down much if I add `import torch` to the start of the script even though I don't use it.
I'm not sure if it's `torch` only or if any other package that is "large" will also cause the same result.
BTW, `import lightning` also slows it down.
Below are the progress bars of `Dataset.map`, the only difference between them is with or without `import torch`, but the speed varies by 6-7 times.
- without `import torch` 
- with `import torch` 
### Steps to reproduce the bug
Below is the code I used, but I don't think the dataset and the mapping function have much to do with the phenomenon.
```python3
from datasets import load_from_disk, disable_caching
from transformers import AutoTokenizer
# import torch
# import lightning
def rearrange_datapoints(
batch,
tokenizer,
sequence_length,
):
datapoints = []
input_ids = []
for x in batch['input_ids']:
input_ids += x
while len(input_ids) >= sequence_length:
datapoint = input_ids[:sequence_length]
datapoints.append(datapoint)
input_ids[:sequence_length] = []
if input_ids:
paddings = [-1] * (sequence_length - len(input_ids))
datapoint = paddings + input_ids if tokenizer.padding_side == 'left' else input_ids + paddings
datapoints.append(datapoint)
batch['input_ids'] = datapoints
return batch
if __name__ == '__main__':
disable_caching()
tokenizer = AutoTokenizer.from_pretrained('...', use_fast=False)
dataset = load_from_disk('...')
dataset = dataset.map(
rearrange_datapoints,
fn_kwargs=dict(
tokenizer=tokenizer,
sequence_length=2048,
),
batched=True,
num_proc=8,
)
```
### Expected behavior
The multi-processed `Dataset.map` function speed between with and without `import torch` should be the same.
### Environment info
- `datasets` version: 2.13.1
- Platform: Linux-3.10.0-1127.el7.x86_64-x86_64-with-glibc2.31
- Python version: 3.10.11
- Huggingface_hub version: 0.14.1
- PyArrow version: 12.0.0
- Pandas version: 2.0.1 | {
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https://api.github.com/repos/huggingface/datasets/issues/2779 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2779/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2779/comments | https://api.github.com/repos/huggingface/datasets/issues/2779/events | https://github.com/huggingface/datasets/pull/2779 | 964,775,085 | MDExOlB1bGxSZXF1ZXN0NzA3MTgwNTgw | 2,779 | Fix sacrebleu tokenizers | {
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} | Last `sacrebleu` release (v2.0.0) has removed `sacrebleu.TOKENIZERS`: https://github.com/mjpost/sacrebleu/pull/152/files#diff-2553a315bb1f7e68c9c1b00d56eaeb74f5205aeb3a189bc3e527b122c6078795L17-R15
This PR makes a hot fix of the bug by using a private function in `sacrebleu`: `sacrebleu.metrics.bleu._get_tokenizer()`.
Eventually, this should be further fixed in order to use only public functions.
This is a partial hotfix of #2781. | {
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https://api.github.com/repos/huggingface/datasets/issues/4849 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4849/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4849/comments | https://api.github.com/repos/huggingface/datasets/issues/4849/events | https://github.com/huggingface/datasets/pull/4849 | 1,338,273,900 | PR_kwDODunzps49JN8d | 4,849 | 1.18.x | {
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https://api.github.com/repos/huggingface/datasets/issues/6074 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6074/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6074/comments | https://api.github.com/repos/huggingface/datasets/issues/6074/events | https://github.com/huggingface/datasets/pull/6074 | 1,822,299,128 | PR_kwDODunzps5Wb8O_ | 6,074 | Misc doc improvements | {
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"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_a... | 2023-07-26T12:20:54 | 2023-07-27T16:16:28 | 2023-07-27T16:16:02 | CONTRIBUTOR | null | 0 | {
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} | Removes the warning about requiring to write a dataset loading script to define multiple configurations, as the README YAML can be used instead (for simple cases). Also, deletes the section about using the `BatchSampler` in `torch<=1.12.1` to speed up loading, as `torch 1.12.1` is over a year old (and `torch 2.0` has been out for a while). | {
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https://api.github.com/repos/huggingface/datasets/issues/3274 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3274/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3274/comments | https://api.github.com/repos/huggingface/datasets/issues/3274/events | https://github.com/huggingface/datasets/pull/3274 | 1,053,689,140 | PR_kwDODunzps4uiL8- | 3,274 | Fix some contact information formats | {
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"The CI fail are caused by some missing sections or tags, which is unrelated to this PR. Merging !"
] | 2021-11-15T13:50:34 | 2021-11-15T14:43:55 | 2021-11-15T14:43:54 | MEMBER | null | 0 | {
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This PR fixes this for CoNLL-2002 and some other datasets with the same issue | {
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https://api.github.com/repos/huggingface/datasets/issues/3448 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3448/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3448/comments | https://api.github.com/repos/huggingface/datasets/issues/3448/events | https://github.com/huggingface/datasets/issues/3448 | 1,083,231,080 | I_kwDODunzps5AkMto | 3,448 | JSONDecodeError with HuggingFace dataset viewer | {
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"color": "E5583E",
"default": false,
"description": "Related to the dataset viewer on huggingface.co",
"id": 3470211881,
"name": "dataset-viewer",
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"Hi ! I think the issue comes from the dataset_infos.json file: it has the \"flat\" field twice.\r\n\r\nCan you try deleting this file and regenerating it please ?",
"Thanks! That fixed that, but now I am getting:\r\nServer Error\r\nStatus code: 400\r\nException: KeyError\r\nMessage: 'feature'\r\n\r\n... | 2021-12-17T12:52:41 | 2022-02-24T09:10:26 | 2022-02-24T09:10:26 | NONE | null | null | null | ## Dataset viewer issue for 'pubmed_neg'
**Link:** https://huggingface.co/datasets/IGESML/pubmed_neg
I am getting the error:
Status code: 400
Exception: JSONDecodeError
Message: Expecting property name enclosed in double quotes: line 61 column 2 (char 1202)
I have checked all files - I am not using single quotes anywhere. Not sure what is causing this issue.
Am I the one who added this dataset ? Yes
| {
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https://api.github.com/repos/huggingface/datasets/issues/3777 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3777/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3777/comments | https://api.github.com/repos/huggingface/datasets/issues/3777/events | https://github.com/huggingface/datasets/pull/3777 | 1,147,232,875 | PR_kwDODunzps4zTVrz | 3,777 | Start removing canonical datasets logic | {
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"I'm not sure if the documentation explains why the dataset identifiers might have a namespace or not (the user/org): 'glue' vs 'severo/glue'. Do you think we should explain it, and relate it to the GitHub/Hub distinction?",
"> I'm not sure if the documentation explains why the dataset identifiers might have a na... | 2022-02-22T18:23:30 | 2022-02-24T15:04:37 | 2022-02-24T15:04:36 | MEMBER | null | 0 | {
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} | I updated the source code and the documentation to start removing the "canonical datasets" logic.
Indeed this makes the documentation confusing and we don't want this distinction anymore in the future. Ideally users should share their datasets on the Hub directly.
### Changes
- the documentation about dataset loading mentions the datasets on the Hub (no difference between canonical and community, since they all have their own repository now)
- the documentation about adding a dataset doesn't explain the technical differences between canonical and community anymore, and only presents how to add a community dataset. There is still a small section at the bottom that mentions the datasets that are still on GitHub and redirects to the `ADD_NEW_DATASET.md` guide on GitHub about how to contribute a dataset to the `datasets` library
- the code source doesn't mention "canonical" anymore anywhere. There is still a `GitHubDatasetModuleFactory` class that is left, but I updated the docstring to say that it will be eventually removed in favor of the `HubDatasetModuleFactory` classes that already exist
Would love to have your feedbacks on this !
cc @julien-c @thomwolf @SBrandeis | {
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https://api.github.com/repos/huggingface/datasets/issues/6014 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6014/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6014/comments | https://api.github.com/repos/huggingface/datasets/issues/6014/events | https://github.com/huggingface/datasets/issues/6014 | 1,798,213,816 | I_kwDODunzps5rLpC4 | 6,014 | Request to Share/Update Dataset Viewer Code | {
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"Hi ! The huggingface/dataset-viewer code was not maintained anymore because we switched to a new dataset viewer that is deployed available for each dataset the Hugging Face website.\r\n\r\nWhat are you using this old repository for ?",
"I think these parts are outdated:\r\n\r\n* https://github.com/huggingface/da... | 2023-07-11T06:36:09 | 2023-09-25T12:01:27 | 2023-09-25T12:01:17 | NONE | null | null | null |
Overview:
The repository (huggingface/datasets-viewer) was recently archived and when I tried to run the code, there was the error message "AttributeError: module 'datasets.load' has no attribute 'prepare_module'". I could not resolve the issue myself due to lack of documentation of that attribute.
Request:
I kindly request the sharing of the code responsible for the dataset preview functionality or help with resolving the error. The dataset viewer on the Hugging Face website is incredibly useful since it is compatible with different types of inputs. It allows users to find datasets that meet their needs more efficiently. If needed, I am willing to contribute to the project by testing, documenting, and providing feedback on the dataset viewer code.
Thank you for considering this request, and I look forward to your response. | {
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https://api.github.com/repos/huggingface/datasets/issues/1804 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1804/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1804/comments | https://api.github.com/repos/huggingface/datasets/issues/1804/events | https://github.com/huggingface/datasets/pull/1804 | 798,483,881 | MDExOlB1bGxSZXF1ZXN0NTY1MjkzMTc3 | 1,804 | Add SICK dataset | {
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} | Adds the SICK dataset (http://marcobaroni.org/composes/sick.html).
Closes #1772.
Edit: also closes #1632, which is the original issue requesting the dataset. The newer one is a duplicate. | {
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https://api.github.com/repos/huggingface/datasets/issues/2340 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2340/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2340/comments | https://api.github.com/repos/huggingface/datasets/issues/2340/events | https://github.com/huggingface/datasets/pull/2340 | 882,370,824 | MDExOlB1bGxSZXF1ZXN0NjM1OTExNzIx | 2,340 | More consistent copy logic | {
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} | Use `info.copy()` instead of `copy.deepcopy(info)`.
`Features.copy` now creates a deep copy. | {
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https://api.github.com/repos/huggingface/datasets/issues/5266 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5266/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5266/comments | https://api.github.com/repos/huggingface/datasets/issues/5266/events | https://github.com/huggingface/datasets/pull/5266 | 1,455,281,310 | PR_kwDODunzps5DN9BT | 5,266 | Specify arguments as keywords in librosa.reshape to avoid future errors | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-11-18T14:58:47 | 2022-11-21T15:45:02 | 2022-11-21T15:41:57 | CONTRIBUTOR | null | 0 | {
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} | Fixes a warning and future deprecation from `librosa.reshape`:
```
FutureWarning: Pass orig_sr=16000, target_sr=48000 as keyword args. From version 0.10 passing these as positional arguments will result in an error
array = librosa.resample(array, sampling_rate, self.sampling_rate, res_type="kaiser_best")
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/3925 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3925/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3925/comments | https://api.github.com/repos/huggingface/datasets/issues/3925/events | https://github.com/huggingface/datasets/pull/3925 | 1,169,913,769 | PR_kwDODunzps40eaq8 | 3,925 | Fix main_classes docs index | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"Hmm it's still not good \r\n\r\n\r\nany idea what could cause this ?",
"Ok fixed :)"
] | 2022-03-15T16:33:46 | 2022-03-22T13:49:11 | 2022-03-22T13:44:04 | MEMBER | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/4728 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4728/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4728/comments | https://api.github.com/repos/huggingface/datasets/issues/4728/events | https://github.com/huggingface/datasets/issues/4728 | 1,312,897,454 | I_kwDODunzps5OQTmu | 4,728 | load_dataset gives "403" error when using Financial Phrasebank | {
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"Hi @rohitvincent, thanks for reporting.\r\n\r\nUnfortunately I'm not able to reproduce your issue:\r\n```python\r\nIn [2]: from datasets import load_dataset, DownloadMode\r\n ...: load_dataset(path='financial_phrasebank',name='sentences_allagree', download_mode=\"force_redownload\")\r\nDownloading builder script... | 2022-07-21T08:43:32 | 2022-08-04T08:32:35 | 2022-08-04T08:32:35 | NONE | null | null | null | I tried both codes below to download the financial phrasebank dataset (https://huggingface.co/datasets/financial_phrasebank) with the sentences_allagree subset. However, the code gives a 403 error when executed from multiple machines locally or on the cloud.
```
from datasets import load_dataset, DownloadMode
load_dataset(path='financial_phrasebank',name='sentences_allagree',download_mode=DownloadMode.FORCE_REDOWNLOAD)
```
```
from datasets import load_dataset, DownloadMode
load_dataset(path='financial_phrasebank',name='sentences_allagree')
```
**Error**
ConnectionError: Couldn't reach https://www.researchgate.net/profile/Pekka_Malo/publication/251231364_FinancialPhraseBank-v10/data/0c96051eee4fb1d56e000000/FinancialPhraseBank-v10.zip (error 403)
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https://api.github.com/repos/huggingface/datasets/issues/2452 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2452/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2452/comments | https://api.github.com/repos/huggingface/datasets/issues/2452/events | https://github.com/huggingface/datasets/issues/2452 | 913,603,877 | MDU6SXNzdWU5MTM2MDM4Nzc= | 2,452 | MRPC test set differences between torch and tensorflow datasets | {
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"color": "d73a4a",
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"id": 1935892857,
"name": "bug",
"node_id": "MDU6TGFiZWwxOTM1ODkyODU3",
"url": "https://api.github.com/repos/huggingface/datasets/labels/bug"
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] | closed | false | null | [] | null | [
"Realized that `tensorflow_datasets` is not provided by Huggingface and should therefore raise the issue there."
] | 2021-06-07T14:20:26 | 2021-06-07T14:34:32 | 2021-06-07T14:34:32 | NONE | null | null | null | ## Describe the bug
When using `load_dataset("glue", "mrpc")` to load the MRPC dataset, the test set includes the labels. When using `tensorflow_datasets.load('glue/{}'.format('mrpc'))` to load the dataset the test set does not contain the labels. There should be consistency between torch and tensorflow ways of importing the GLUE datasets.
## Steps to reproduce the bug
Minimal working code
```python
from datasets import load_dataset
import tensorflow as tf
import tensorflow_datasets
# torch
dataset = load_dataset("glue", "mrpc")
# tf
data = tensorflow_datasets.load('glue/{}'.format('mrpc'))
data = list(data['test'].as_numpy_iterator())
for i in range(40,50):
tf_sentence1 = data[i]['sentence1'].decode("utf-8")
tf_sentence2 = data[i]['sentence2'].decode("utf-8")
tf_label = data[i]['label']
index = data[i]['idx']
print('Index {}'.format(index))
torch_sentence1 = dataset['test']['sentence1'][index]
torch_sentence2 = dataset['test']['sentence2'][index]
torch_label = dataset['test']['label'][index]
print('Tensorflow: \n\tSentence1 {}\n\tSentence2 {}\n\tLabel {}'.format(tf_sentence1, tf_sentence2, tf_label))
print('Torch: \n\tSentence1 {}\n\tSentence2 {}\n\tLabel {}'.format(torch_sentence1, torch_sentence2, torch_label))
```
Sample output
```
Index 954
Tensorflow:
Sentence1 Sabri Yakou , an Iraqi native who is a legal U.S. resident , appeared before a federal magistrate yesterday on charges of violating U.S. arms-control laws .
Sentence2 The elder Yakou , an Iraqi native who is a legal U.S. resident , appeared before a federal magistrate Wednesday on charges of violating U.S. arms control laws .
Label -1
Torch:
Sentence1 Sabri Yakou , an Iraqi native who is a legal U.S. resident , appeared before a federal magistrate yesterday on charges of violating U.S. arms-control laws .
Sentence2 The elder Yakou , an Iraqi native who is a legal U.S. resident , appeared before a federal magistrate Wednesday on charges of violating U.S. arms control laws .
Label 1
Index 711
Tensorflow:
Sentence1 Others keep records sealed for as little as five years or as much as 30 .
Sentence2 Some states make them available immediately ; others keep them sealed for as much as 30 years .
Label -1
Torch:
Sentence1 Others keep records sealed for as little as five years or as much as 30 .
Sentence2 Some states make them available immediately ; others keep them sealed for as much as 30 years .
Label 0
```
## Expected results
I would expect the datasets to be independent of whether I am working with torch or tensorflow.
## Actual results
Test set labels are provided in the `datasets.load_datasets()` for MRPC. However MRPC is the only task where the test set labels are not -1.
## Environment info
- `datasets` version: 1.7.0
- Platform: Linux-5.4.109+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.7.10
- PyArrow version: 3.0.0
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https://api.github.com/repos/huggingface/datasets/issues/1363 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1363/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1363/comments | https://api.github.com/repos/huggingface/datasets/issues/1363/events | https://github.com/huggingface/datasets/pull/1363 | 760,160,944 | MDExOlB1bGxSZXF1ZXN0NTM1MDM4NjM0 | 1,363 | Adding OPUS MultiUN | {
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} | [] | closed | false | null | [] | null | [] | 2020-12-09T09:29:01 | 2020-12-09T17:54:20 | 2020-12-09T17:54:20 | MEMBER | null | 0 | {
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http://www.euromatrixplus.net/multi-un/ | {
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https://api.github.com/repos/huggingface/datasets/issues/5171 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5171/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5171/comments | https://api.github.com/repos/huggingface/datasets/issues/5171/events | https://github.com/huggingface/datasets/pull/5171 | 1,425,355,111 | PR_kwDODunzps5BpsXf | 5,171 | Add PB and TB in convert_file_size_to_int | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-10-27T09:50:31 | 2022-10-27T12:14:27 | 2022-10-27T12:12:30 | MEMBER | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/4516 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4516/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4516/comments | https://api.github.com/repos/huggingface/datasets/issues/4516/events | https://github.com/huggingface/datasets/pull/4516 | 1,273,825,640 | PR_kwDODunzps45ykYX | 4,516 | Fix hashing for python 3.9 | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"What do you think @albertvillanova ?"
] | 2022-06-16T16:42:31 | 2022-06-28T13:33:46 | 2022-06-28T13:23:06 | MEMBER | null | 0 | {
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} | In python 3.9, pickle hashes the `glob_ids` dictionary in addition to the `globs` of a function.
Therefore the test at `tests/test_fingerprint.py::RecurseDumpTest::test_recurse_dump_for_function_with_shuffled_globals` is currently failing for python 3.9
To make hashing deterministic when the globals are not in the same order, we also need to make the order of `glob_ids` deterministic.
Right now we don't have a CI to test python 3.9 but we should definitely have one. For this PR in particular I ran the tests locally using python 3.9 and they're passing now.
Fix https://github.com/huggingface/datasets/issues/4506 | {
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