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"#self-assign"
] | 2021-06-11T18:47:22Z | 2021-07-05T10:45:57Z | 2021-07-05T10:45:57Z | 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... | 2021-02-01T11:08:23Z | 2021-08-04T18:11:01Z | 2021-08-04T18:10:42Z | 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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https://api.github.com/repos/huggingface/datasets/issues/2574 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2574/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2574/comments | https://api.github.com/repos/huggingface/datasets/issues/2574/events | https://github.com/huggingface/datasets/pull/2574 | 934,632,378 | MDExOlB1bGxSZXF1ZXN0NjgxNjczMzYy | 2,574 | Add streaming in load a dataset docs | {
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https://api.github.com/repos/huggingface/datasets/issues/4059 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4059/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4059/comments | https://api.github.com/repos/huggingface/datasets/issues/4059/events | https://github.com/huggingface/datasets/pull/4059 | 1,186,149,949 | PR_kwDODunzps41TC-o | 4,059 | Load GitHub datasets from Hub | {
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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... | 2022-03-30T09:21:56Z | 2022-09-16T12:43:26Z | 2022-09-16T12:40:43Z | 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... | 2021-09-22T23:45:00Z | 2022-03-15T16:07:02Z | 2022-03-15T16:07:02Z | 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\... | 2021-08-06T15:58:57Z | 2021-08-09T11:16:25Z | 2021-08-09T11:16:25Z | 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"
] | 2022-04-27T17:45:43Z | 2022-10-03T09:36:35Z | 2022-10-03T09:36:35Z | 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... | 2021-04-15T04:26:40Z | 2021-04-15T22:09:50Z | 2021-04-15T21:19:09Z | 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 ... | 2020-12-13T12:43:33Z | 2020-12-18T10:09:01Z | 2020-12-18T10:09:01Z | 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"
] | 2020-12-09T21:54:29Z | 2020-12-11T13:34:04Z | 2020-12-11T13:34:04Z | 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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} | [] | 2021-04-22T11:46:51Z | 2021-04-27T15:29:21Z | 2021-04-27T15:29:20Z | 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!"
] | 2021-11-04T17:22:01Z | 2021-11-04T18:55:38Z | 2021-11-04T18:55:37Z | 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... | 2021-02-02T08:35:53Z | 2021-02-03T17:15:05Z | 2021-02-03T16:43:06Z | 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!"
] | 2021-01-21T02:26:37Z | 2021-01-22T00:25:50Z | 2021-01-22T00:25:50Z | 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 ... | 2022-07-27T12:04:54Z | 2022-08-08T18:20:50Z | 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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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._"
] | 2022-08-02T15:34:54Z | 2022-08-02T16:16:33Z | 2022-08-02T16:03:17Z | 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... | 2021-06-11T20:17:41Z | 2022-10-03T09:38:18Z | 2022-10-03T09:38:18Z | NONE | null | 0 | {
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} | Hi there!
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... | 2022-10-16T22:19:18Z | 2022-10-23T10:27:53Z | 2022-10-19T08:53:17Z | 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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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"
] | 2023-07-20T06:36:14Z | 2023-07-21T15:19:37Z | 2023-07-21T15:19:37Z | 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... | 2023-07-26T12:20:54Z | 2023-07-27T16:16:28Z | 2023-07-27T16:16:02Z | 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 !"
] | 2021-11-15T13:50:34Z | 2021-11-15T14:43:55Z | 2021-11-15T14:43:54Z | MEMBER | null | 0 | {
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} | As reported in https://github.com/huggingface/datasets/issues/3188 some contact information are not displayed correctly.
This PR fixes this for CoNLL-2002 and some other datasets with the same issue | {
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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... | 2021-12-17T12:52:41Z | 2022-02-24T09:10:26Z | 2022-02-24T09:10:26Z | 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... | 2022-02-22T18:23:30Z | 2022-02-24T15:04:37Z | 2022-02-24T15:04:36Z | 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... | 2023-07-11T06:36:09Z | 2023-09-25T12:01:27Z | 2023-09-25T12:01:17Z | 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._"
] | 2022-11-18T14:58:47Z | 2022-11-21T15:45:02Z | 2022-11-21T15:41:57Z | CONTRIBUTOR | null | 0 | {
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```
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 :)"
] | 2022-03-15T16:33:46Z | 2022-03-22T13:49:11Z | 2022-03-22T13:44:04Z | 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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} | [] | closed | false | null | [] | null | [
"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... | 2022-07-21T08:43:32Z | 2022-08-04T08:32:35Z | 2022-08-04T08:32:35Z | 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",
"default": true,
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"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."
] | 2021-06-07T14:20:26Z | 2021-06-07T14:34:32Z | 2021-06-07T14:34:32Z | 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 | [] | 2020-12-09T09:29:01Z | 2020-12-09T17:54:20Z | 2020-12-09T17:54:20Z | MEMBER | null | 0 | {
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} | Adding UnMulti
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._"
] | 2022-10-27T09:50:31Z | 2022-10-27T12:14:27Z | 2022-10-27T12:12:30Z | 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 ?"
] | 2022-06-16T16:42:31Z | 2022-06-28T13:33:46Z | 2022-06-28T13:23:06Z | 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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https://api.github.com/repos/huggingface/datasets/issues/5451 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5451/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5451/comments | https://api.github.com/repos/huggingface/datasets/issues/5451/events | https://github.com/huggingface/datasets/issues/5451 | 1,552,336,300 | I_kwDODunzps5chsWs | 5,451 | ImageFolder BadZipFile: Bad offset for central directory | {
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"Hi ! Could you share the full stack trace ? Which dataset did you try to load ?\r\n\r\nit may be related to https://github.com/huggingface/datasets/pull/5640",
"The `BadZipFile` error means the ZIP file is corrupted, so I'm closing this issue as it's not directly related to `datasets`.",
"For others that find ... | 2023-01-22T23:50:12Z | 2023-05-23T10:35:48Z | 2023-02-10T16:31:36Z | NONE | null | null | null | ### Describe the bug
I'm getting the following exception:
```
lib/python3.10/zipfile.py:1353 in _RealGetContents │
│ │
│ 1350 │ │ # self.start_dir: Position of start of central directory │
│ 1351 │ │ self.start_dir = offset_cd + concat │
│ 1352 │ │ if self.start_dir < 0: │
│ ❱ 1353 │ │ │ raise BadZipFile("Bad offset for central directory") │
│ 1354 │ │ fp.seek(self.start_dir, 0) │
│ 1355 │ │ data = fp.read(size_cd) │
│ 1356 │ │ fp = io.BytesIO(data) │
╰──────────────────────────────────────────────────────────────────────────────────────────────────╯
BadZipFile: Bad offset for central directory
Extracting data files: 35%|█████████████████▊ | 38572/110812 [00:10<00:20, 3576.26it/s]
```
### Steps to reproduce the bug
```
load_dataset(
args.dataset_name,
args.dataset_config_name,
cache_dir=args.cache_dir,
),
```
### Expected behavior
loads the dataset
### Environment info
datasets==2.8.0
Python 3.10.8
Linux 129-146-3-202 5.15.0-52-generic #58~20.04.1-Ubuntu SMP Thu Oct 13 13:09:46 UTC 2022 x86_64 x86_64 x86_64 GNU/Linux | {
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https://api.github.com/repos/huggingface/datasets/issues/1609 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1609/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1609/comments | https://api.github.com/repos/huggingface/datasets/issues/1609/events | https://github.com/huggingface/datasets/issues/1609 | 771,421,881 | MDU6SXNzdWU3NzE0MjE4ODE= | 1,609 | Not able to use 'jigsaw_toxicity_pred' dataset | {
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"Hi @jassimran,\r\nThe `jigsaw_toxicity_pred` dataset has not been released yet, it will be available with version 2 of `datasets`, coming soon.\r\nYou can still access it by installing the master (unreleased) version of datasets directly :\r\n`pip install git+https://github.com/huggingface/datasets.git@master`\r\n... | 2020-12-19T17:35:48Z | 2020-12-22T16:42:24Z | 2020-12-22T16:42:23Z | NONE | null | null | null | When trying to use jigsaw_toxicity_pred dataset, like this in a [colab](https://colab.research.google.com/drive/1LwO2A5M2X5dvhkAFYE4D2CUT3WUdWnkn?usp=sharing):
```
from datasets import list_datasets, list_metrics, load_dataset, load_metric
ds = load_dataset("jigsaw_toxicity_pred")
```
I see below error:
> FileNotFoundError: Couldn't find file at https://raw.githubusercontent.com/huggingface/datasets/1.1.3/datasets/jigsaw_toxicity_pred/jigsaw_toxicity_pred.py
During handling of the above exception, another exception occurred:
FileNotFoundError Traceback (most recent call last)
FileNotFoundError: Couldn't find file at https://s3.amazonaws.com/datasets.huggingface.co/datasets/datasets/jigsaw_toxicity_pred/jigsaw_toxicity_pred.py
During handling of the above exception, another exception occurred:
FileNotFoundError Traceback (most recent call last)
/usr/local/lib/python3.6/dist-packages/datasets/load.py in prepare_module(path, script_version, download_config, download_mode, dataset, force_local_path, **download_kwargs)
280 raise FileNotFoundError(
281 "Couldn't find file locally at {}, or remotely at {} or {}".format(
--> 282 combined_path, github_file_path, file_path
283 )
284 )
FileNotFoundError: Couldn't find file locally at jigsaw_toxicity_pred/jigsaw_toxicity_pred.py, or remotely at https://raw.githubusercontent.com/huggingface/datasets/1.1.3/datasets/jigsaw_toxicity_pred/jigsaw_toxicity_pred.py or https://s3.amazonaws.com/datasets.huggingface.co/datasets/datasets/jigsaw_toxicity_pred/jigsaw_toxicity_pred.py | {
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https://api.github.com/repos/huggingface/datasets/issues/2140 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2140/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2140/comments | https://api.github.com/repos/huggingface/datasets/issues/2140/events | https://github.com/huggingface/datasets/pull/2140 | 843,830,451 | MDExOlB1bGxSZXF1ZXN0NjAzMTYxMjYx | 2,140 | add banking77 dataset | {
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"@lhoestq I updated files"
] | 2021-03-29T21:32:23Z | 2021-04-09T09:32:18Z | 2021-04-09T09:32:18Z | CONTRIBUTOR | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/5346 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5346/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5346/comments | https://api.github.com/repos/huggingface/datasets/issues/5346/events | https://github.com/huggingface/datasets/issues/5346 | 1,486,884,983 | I_kwDODunzps5YoBB3 | 5,346 | [Quick poll] Give your opinion on the future of the Hugging Face Open Source ecosystem! | {
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"As the survey is finished, can we close this issue, @LysandreJik ?",
"Yes! I'll post a public summary on the forums shortly.",
"Is the summary available? I would be interested in reading your findings."
] | 2022-12-09T14:48:02Z | 2023-06-02T20:24:44Z | 2023-01-25T19:35:40Z | MEMBER | null | null | null | Thanks to all of you, Datasets is just about to pass 15k stars!
Since the last survey, a lot has happened: the [diffusers](https://github.com/huggingface/diffusers), [evaluate](https://github.com/huggingface/evaluate) and [skops](https://github.com/skops-dev/skops) libraries were born. `timm` joined the Hugging Face ecosystem. There were 25 new releases of `transformers`, 21 new releases of `datasets`, 13 new releases of `accelerate`.
If you have a couple of minutes and want to participate in shaping the future of the ecosystem, please share your thoughts:
[**hf.co/oss-survey**](https://docs.google.com/forms/d/e/1FAIpQLSf4xFQKtpjr6I_l7OfNofqiR8s-WG6tcNbkchDJJf5gYD72zQ/viewform?usp=sf_link)
(please reply in the above feedback form rather than to this thread)
Thank you all on behalf of the HuggingFace team! 🤗 | {
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"<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 | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_a... | 2023-02-28T15:37:46Z | 2023-02-28T17:28:35Z | 2023-02-28T17:21:17Z | CONTRIBUTOR | null | 0 | {
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} | Flatten a dataset on the fly in `save_to_disk` instead of doing it with `flatten_indices` to avoid creating an additional cache file.
(this is one of the sub-tasks in https://github.com/huggingface/datasets/issues/5507) | {
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https://api.github.com/repos/huggingface/datasets/issues/5201 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5201/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5201/comments | https://api.github.com/repos/huggingface/datasets/issues/5201/events | https://github.com/huggingface/datasets/pull/5201 | 1,435,881,554 | PR_kwDODunzps5CM0zn | 5,201 | Do not sort splits in dataset info | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"It would be coherent with https://github.com/huggingface/datasets-server/issues/614#issuecomment-1290534153",
"I think we started working on this issue nearly at the same time... :sweat_smile: \r\n- CI was fixed with this: https://... | 2022-11-04T10:47:21Z | 2022-11-04T14:47:37Z | 2022-11-04T14:45:09Z | CONTRIBUTOR | null | 0 | {
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} | I suggest not to sort splits by their names in dataset_info in README so that they are displayed in the order specified in the loading script. Otherwise `test` split is displayed first, see this repo: https://huggingface.co/datasets/paws
What do you think?
But I added sorting in tests to fix CI (for the same dataset). | {
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https://api.github.com/repos/huggingface/datasets/issues/3882 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3882/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3882/comments | https://api.github.com/repos/huggingface/datasets/issues/3882/events | https://github.com/huggingface/datasets/pull/3882 | 1,164,595,388 | PR_kwDODunzps40NKz7 | 3,882 | Image process doc | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3882). All of your documentation changes will be reflected on that endpoint."
] | 2022-03-10T00:32:10Z | 2022-03-15T15:24:16Z | 2022-03-15T15:24:09Z | MEMBER | null | 0 | {
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} | This PR is a first draft of how to process image data. It adds:
- Load an image dataset with `image` and `path` (adds tip about `decode=False` param to access the path and bytes, thanks to @mariosasko).
- Load an image using the `ImageFolder` builder. I know there is an [example](https://huggingface.co/docs/datasets/master/en/loading#image-folders) of this already, but I also wanted to add it here so users don't miss it. This doc seems important for centralizing all of the image-related things so far. Datasets has grown so quickly 🚀 now that I think maybe splitting up the How-to guides by modality may be better since working with vision/audio data is slightly different from what users have seen up until now. This way we can continue to scale the docs to better accommodate vision/audio things.
- Add a data augmentation with `set_transform`. There is only 1 example here so far, but we can certainly add more.
Todo:
- [x] Couldn't figure out why my augmentation function works with `set_transform` but not `map` 🥲. Working with @mariosasko on this! | {
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} | Example format is a little different from SQuAD since `thaiqa` always have one answer per question so I added a check to convert answers to lists if they are not already one to future-proof additional questions that might have multiple answers.
`thaiqa_squad` is an open-domain, extractive question answering dataset (4,000 questions in `train` and 74 questions in `dev`) in [SQuAD](https://rajpurkar.github.io/SQuAD-explorer/) format, originally created by [NECTEC](https://www.nectec.or.th/en/) from Wikipedia articles and adapted to [SQuAD](https://rajpurkar.github.io/SQuAD-explorer/) format by [PyThaiNLP](https://github.com/PyThaiNLP/). | {
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} | Related to #2743. | {
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https://api.github.com/repos/huggingface/datasets/issues/4388 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4388/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4388/comments | https://api.github.com/repos/huggingface/datasets/issues/4388/events | https://github.com/huggingface/datasets/pull/4388 | 1,244,645,158 | PR_kwDODunzps44RAG1 | 4,388 | Set builder name from module instead of class | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-05-23T06:26:35Z | 2022-05-25T05:24:43Z | 2022-05-25T05:16:15Z | MEMBER | null | 0 | {
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} | Now the builder name attribute is set from from the builder class name.
This PR sets the builder name attribute from the module name instead. Some motivating reasons:
- The dataset ID is relevant and unique among all datasets and this is directly related to the repository name, i.e., the name of the directory containing the dataset
- The name of the module (i.e. the file containing the loading loading script) is already relevant for loading: it must have the same name as its containing directory (related to the dataset ID), as we search for it using its directory name
- On the other hand, the name of the builder class is not relevant for loading: in our code, we just search for a class which is subclass of `DatasetBuilder` (independently of its name). We do not put any constraint on the naming of the builder class and indeed it can have a name completely different from its module/direcotry/dataset_id
IMO it makes more sense to align the caching directory name with the dataset_id/directory/module name instead of the builder class name.
Fix #4381. | {
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https://api.github.com/repos/huggingface/datasets/issues/2950 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2950/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2950/comments | https://api.github.com/repos/huggingface/datasets/issues/2950/events | https://github.com/huggingface/datasets/pull/2950 | 1,001,085,353 | PR_kwDODunzps4r-AKu | 2,950 | Fix fn kwargs in filter | {
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} | #2836 broke the `fn_kwargs` parameter of `filter`, as mentioned in https://github.com/huggingface/datasets/issues/2927
I fixed that and added a test to make sure it doesn't happen again (for either map or filter)
Fix #2927 | {
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https://api.github.com/repos/huggingface/datasets/issues/2943 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2943/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2943/comments | https://api.github.com/repos/huggingface/datasets/issues/2943/events | https://github.com/huggingface/datasets/issues/2943 | 1,000,355,115 | I_kwDODunzps47oDUr | 2,943 | Backwards compatibility broken for cached datasets that use `.filter()` | {
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"Hi ! I guess the caching mechanism should have considered the new `filter` to be different from the old one, and don't use cached results from the old `filter`.\r\nTo avoid other users from having this issue we could make the caching differentiate the two, what do you think ?",
"If it's easy enough to implement,... | 2021-09-19T16:16:37Z | 2021-09-20T16:25:43Z | 2021-09-20T16:25:42Z | MEMBER | null | null | null | ## Describe the bug
After upgrading to datasets `1.12.0`, some cached `.filter()` steps from `1.11.0` started failing with
`ValueError: Keys mismatch: between {'indices': Value(dtype='uint64', id=None)} and {'file': Value(dtype='string', id=None), 'text': Value(dtype='string', id=None), 'speaker_id': Value(dtype='int64', id=None), 'chapter_id': Value(dtype='int64', id=None), 'id': Value(dtype='string', id=None)}`
Related feature: https://github.com/huggingface/datasets/pull/2836
:question: This is probably a `wontfix` bug, since it can be solved by simply cleaning the related cache dirs, but the workaround could be useful for someone googling the error :)
## Workaround
Remove the cache for the given dataset, e.g. `rm -rf ~/.cache/huggingface/datasets/librispeech_asr`.
## Steps to reproduce the bug
1. Delete `~/.cache/huggingface/datasets/librispeech_asr` if it exists.
2. `pip install datasets==1.11.0` and run the following snippet:
```python
from datasets import load_dataset
ids = ["1272-141231-0000"]
ds = load_dataset("patrickvonplaten/librispeech_asr_dummy", "clean", split="validation")
ds = ds.filter(lambda x: x["id"] in ids)
```
3. `pip install datasets==1.12.1` and re-run the code again
## Expected results
Same result as with the previous `datasets` version.
## Actual results
```bash
Reusing dataset librispeech_asr (./.cache/huggingface/datasets/librispeech_asr/clean/2.1.0/468ec03677f46a8714ac6b5b64dba02d246a228d92cbbad7f3dc190fa039eab1)
Loading cached processed dataset at ./.cache/huggingface/datasets/librispeech_asr/clean/2.1.0/468ec03677f46a8714ac6b5b64dba02d246a228d92cbbad7f3dc190fa039eab1/cache-cd1c29844fdbc87a.arrow
Traceback (most recent call last):
File "./repos/transformers/src/transformers/models/wav2vec2/try_dataset.py", line 5, in <module>
ds = ds.filter(lambda x: x["id"] in ids)
File "./envs/transformers/lib/python3.8/site-packages/datasets/arrow_dataset.py", line 185, in wrapper
out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs)
File "./envs/transformers/lib/python3.8/site-packages/datasets/fingerprint.py", line 398, in wrapper
out = func(self, *args, **kwargs)
File "./envs/transformers/lib/python3.8/site-packages/datasets/arrow_dataset.py", line 2169, in filter
indices = self.map(
File "./envs/transformers/lib/python3.8/site-packages/datasets/arrow_dataset.py", line 1686, in map
return self._map_single(
File "./envs/transformers/lib/python3.8/site-packages/datasets/arrow_dataset.py", line 185, in wrapper
out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs)
File "./envs/transformers/lib/python3.8/site-packages/datasets/fingerprint.py", line 398, in wrapper
out = func(self, *args, **kwargs)
File "./envs/transformers/lib/python3.8/site-packages/datasets/arrow_dataset.py", line 1896, in _map_single
return Dataset.from_file(cache_file_name, info=info, split=self.split)
File "./envs/transformers/lib/python3.8/site-packages/datasets/arrow_dataset.py", line 343, in from_file
return cls(
File "./envs/transformers/lib/python3.8/site-packages/datasets/arrow_dataset.py", line 282, in __init__
self.info.features = self.info.features.reorder_fields_as(inferred_features)
File "./envs/transformers/lib/python3.8/site-packages/datasets/features.py", line 1151, in reorder_fields_as
return Features(recursive_reorder(self, other))
File "./envs/transformers/lib/python3.8/site-packages/datasets/features.py", line 1140, in recursive_reorder
raise ValueError(f"Keys mismatch: between {source} and {target}" + stack_position)
ValueError: Keys mismatch: between {'indices': Value(dtype='uint64', id=None)} and {'file': Value(dtype='string', id=None), 'text': Value(dtype='string', id=None), 'speaker_id': Value(dtype='int64', id=None), 'chapter_id': Value(dtype='int64', id=None), 'id': Value(dtype='string', id=None)}
Process finished with exit code 1
```
## Environment info
- `datasets` version: 1.12.1
- Platform: Linux-5.11.0-34-generic-x86_64-with-glibc2.17
- Python version: 3.8.10
- PyArrow version: 5.0.0
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https://api.github.com/repos/huggingface/datasets/issues/3714 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3714/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3714/comments | https://api.github.com/repos/huggingface/datasets/issues/3714/events | https://github.com/huggingface/datasets/issues/3714 | 1,136,105,530 | I_kwDODunzps5Dt5g6 | 3,714 | tatoeba_mt: File not found error and key error | {
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"Looks like I solved my problems ..."
] | 2022-02-13T16:35:45Z | 2022-02-13T20:44:04Z | 2022-02-13T20:44:04Z | NONE | null | null | null | ## Dataset viewer issue for 'tatoeba_mt'
**Link:** https://huggingface.co/datasets/Helsinki-NLP/tatoeba_mt
My data loader script does not seem to work.
The files are part of the local repository but cannot be found. An example where it should work is the subset for "afr-eng".
Another problem is that I do not have validation data for all subsets and I don't know how to properly check whether validation exists in the configuration before I try to download it. An example is the subset for "afr-deu".
Am I the one who added this dataset ? Yes
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https://api.github.com/repos/huggingface/datasets/issues/5912 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5912/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5912/comments | https://api.github.com/repos/huggingface/datasets/issues/5912/events | https://github.com/huggingface/datasets/issues/5912 | 1,730,299,852 | I_kwDODunzps5nIkfM | 5,912 | Missing elements in `map` a batched dataset | {
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"Hi ! in your code batching is **only used within** `map`, to process examples in batch. The dataset itself however is not batched and returns elements one by one.\r\n\r\nTo iterate on batches, you can do\r\n```python\r\nfor batch in dataset.iter(batch_size=8):\r\n ...\r\n```"
] | 2023-05-29T08:09:19Z | 2023-07-26T15:48:15Z | 2023-07-26T15:48:15Z | NONE | null | null | null | ### Describe the bug
As outlined [here](https://discuss.huggingface.co/t/length-error-using-map-with-datasets/40969/3?u=sachin), the following collate function drops 5 out of possible 6 elements in the batch (it is 6 because out of the eight, two are bad links in laion). A reproducible [kaggle kernel ](https://www.kaggle.com/sachin/laion-hf-dataset/edit) can be found here.
The weirdest part is when inspecting the sizes of the tensors as shown below, both `tokenized_captions["input_ids"]` and `image_features` show the correct shapes. Simply the output only has one element (with the batch dimension squeezed out).
```python
class CollateFn:
def get_image(self, url):
try:
response = requests.get(url)
return Image.open(io.BytesIO(response.content)).convert("RGB")
except PIL.UnidentifiedImageError:
logger.info(f"Reading error: Could not transform f{url}")
return None
except requests.exceptions.ConnectionError:
logger.info(f"Connection error: Could not transform f{url}")
return None
def __call__(self, batch):
images = [self.get_image(url) for url in batch["url"]]
captions = [caption for caption, image in zip(batch["caption"], images) if image is not None]
images = [image for image in images if image is not None]
tokenized_captions = tokenizer(
captions,
padding="max_length",
truncation=True,
max_length=tokenizer.model_max_length,
return_tensors="pt",
)
image_features = torch.stack([torch.Tensor(feature_extractor(image)["pixel_values"][0]) for image in images])
# import pdb; pdb.set_trace()
return {"input_ids": tokenized_captions["input_ids"], "images": image_features}
collate_fn = CollateFn()
laion_ds = datasets.load_dataset("laion/laion400m", split="train", streaming=True)
laion_ds_batched = laion_ds.map(collate_fn, batched=True, batch_size=8, remove_columns=next(iter(laion_ds)).keys())
```
### Steps to reproduce the bug
A reproducible [kaggle kernel ](https://www.kaggle.com/sachin/laion-hf-dataset/edit) can be found here.
### Expected behavior
Would expect `next(iter(laion_ds_batched))` to produce two tensors of shape `(batch_size, 77)` and `batch_size, image_shape`.
### Environment info
datasets==2.12.0
python==3.10 | {
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https://api.github.com/repos/huggingface/datasets/issues/1935 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1935/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1935/comments | https://api.github.com/repos/huggingface/datasets/issues/1935/events | https://github.com/huggingface/datasets/pull/1935 | 814,623,827 | MDExOlB1bGxSZXF1ZXN0NTc4NTgyMzk1 | 1,935 | add CoVoST2 | {
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"@patrickvonplaten \r\nI removed the mp3 files, dummy_data is much smaller now!"
] | 2021-02-23T16:28:16Z | 2021-02-24T18:09:32Z | 2021-02-24T18:05:09Z | MEMBER | null | 0 | {
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} | This PR adds the CoVoST2 dataset for speech translation and ASR.
https://github.com/facebookresearch/covost#covost-2
The dataset requires manual download as the download page requests an email address and the URLs are temporary.
The dummy data is a bit bigger because of the mp3 files and 36 configs. | {
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https://api.github.com/repos/huggingface/datasets/issues/2088 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2088/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2088/comments | https://api.github.com/repos/huggingface/datasets/issues/2088/events | https://github.com/huggingface/datasets/pull/2088 | 836,763,733 | MDExOlB1bGxSZXF1ZXN0NTk3MjQ4Mzk1 | 2,088 | change bibtex template to author instead of authors | {
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"Trailing whitespace was removed. So more changes in diff than just this fix."
] | 2021-03-20T09:23:44Z | 2021-03-23T15:40:12Z | 2021-03-23T15:40:12Z | CONTRIBUTOR | null | 0 | {
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} | Hi,
IMO when using BibTex Author should be used instead of Authors.
See here: http://www.bibtex.org/Using/de/
Thanks
Philip | {
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https://api.github.com/repos/huggingface/datasets/issues/2960 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2960/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2960/comments | https://api.github.com/repos/huggingface/datasets/issues/2960/events | https://github.com/huggingface/datasets/pull/2960 | 1,006,222,850 | PR_kwDODunzps4sOl0Y | 2,960 | Support pandas 1.3 new `read_csv` parameters | {
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} | [] | closed | false | null | [] | null | [] | 2021-09-24T08:37:24Z | 2021-09-24T11:22:31Z | 2021-09-24T11:22:30Z | CONTRIBUTOR | null | 0 | {
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} | Support two new arguments introduced in pandas v1.3.0:
- `encoding_errors`
- `on_bad_lines`
`read_csv` reference: https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.read_csv.html | {
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https://api.github.com/repos/huggingface/datasets/issues/2004 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2004/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2004/comments | https://api.github.com/repos/huggingface/datasets/issues/2004/events | https://github.com/huggingface/datasets/pull/2004 | 824,080,760 | MDExOlB1bGxSZXF1ZXN0NTg2MzcyODY1 | 2,004 | LaRoSeDa | {
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"@lhoestq all the changes requested are implemented. Thank you for your time and feedback :)"
] | 2021-03-08T01:06:32Z | 2021-03-17T10:43:20Z | 2021-03-17T10:43:20Z | CONTRIBUTOR | null | 0 | {
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} | Add LaRoSeDa to huggingface datasets. | {
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https://api.github.com/repos/huggingface/datasets/issues/2211 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2211/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2211/comments | https://api.github.com/repos/huggingface/datasets/issues/2211/events | https://github.com/huggingface/datasets/issues/2211 | 855,988,410 | MDU6SXNzdWU4NTU5ODg0MTA= | 2,211 | Getting checksum error when trying to load lc_quad dataset | {
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"Hi,\r\n\r\nI've already opened a PR with the fix. If you are in a hurry, just build the project from source and run:\r\n```bash\r\ndatasets-cli test datasets/lc_quad --save_infos --all_configs --ignore_verifications\r\n```\r\n\r\n",
"Ah sorry, I tried searching but couldn't find any related PR. \r\n\r\nThank you... | 2021-04-12T13:38:58Z | 2021-04-14T13:42:25Z | 2021-04-14T13:42:25Z | NONE | null | null | null | I'm having issues loading the [lc_quad](https://huggingface.co/datasets/fquad) dataset by running:
```Python
lc_quad = load_dataset("lc_quad")
```
which is giving me the following error:
```
Using custom data configuration default
Downloading and preparing dataset lc_quad/default (download: 3.69 MiB, generated: 19.77 MiB, post-processed: Unknown size, total: 23.46 MiB) to /root/.cache/huggingface/datasets/lc_quad/default/2.0.0/5a98fe174603f5dec6df07edf1c2b4d2317210d2ad61f5a393839bca4d64e5a7...
---------------------------------------------------------------------------
NonMatchingChecksumError Traceback (most recent call last)
<ipython-input-42-404ace83f73c> in <module>()
----> 1 lc_quad = load_dataset("lc_quad")
3 frames
/usr/local/lib/python3.7/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://github.com/AskNowQA/LC-QuAD2.0/archive/master.zip']
```
Does anyone know why this could be and how I fix it? | {
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https://api.github.com/repos/huggingface/datasets/issues/3111 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3111/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3111/comments | https://api.github.com/repos/huggingface/datasets/issues/3111/events | https://github.com/huggingface/datasets/issues/3111 | 1,030,598,983 | I_kwDODunzps49bbFH | 3,111 | concatenate_datasets removes ClassLabel typing. | {
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"Something like this would fix it I think: https://github.com/huggingface/datasets/compare/master...Dref360:HF-3111/concatenate_types?expand=1"
] | 2021-10-19T18:05:31Z | 2021-10-21T14:50:21Z | 2021-10-21T14:50:21Z | CONTRIBUTOR | null | null | null | ## Describe the bug
When concatenating two datasets, we lose typing of ClassLabel columns.
I can work on this if this is a legitimate bug,
## Steps to reproduce the bug
```python
import datasets
from datasets import Dataset, ClassLabel, Value, concatenate_datasets
DS_LEN = 100
my_dataset = Dataset.from_dict(
{
"sentence": [f"{chr(i % 10)}" for i in range(DS_LEN)],
"label": [i % 2 for i in range(DS_LEN)]
}
)
my_predictions = Dataset.from_dict(
{
"pred": [(i + 1) % 2 for i in range(DS_LEN)]
}
)
my_dataset = my_dataset.cast(datasets.Features({"sentence": Value("string"), "label": ClassLabel(2, names=["POS", "NEG"])}))
print("Original")
print(my_dataset)
print(my_dataset.features)
concat_ds = concatenate_datasets([my_dataset, my_predictions], axis=1)
print("Concatenated")
print(concat_ds)
print(concat_ds.features)
```
## Expected results
The features of `concat_ds` should contain ClassLabel.
## Actual results
On master, I get:
```
{'sentence': Value(dtype='string', id=None), 'label': Value(dtype='int64', id=None), 'pred': Value(dtype='int64', id=None)}
```
## Environment info
- `datasets` version: 1.14.1.dev0
- Platform: macOS-10.15.7-x86_64-i386-64bit
- Python version: 3.8.11
- PyArrow version: 4.0.1
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https://api.github.com/repos/huggingface/datasets/issues/4642 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4642/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4642/comments | https://api.github.com/repos/huggingface/datasets/issues/4642/events | https://github.com/huggingface/datasets/issues/4642 | 1,295,748,083 | I_kwDODunzps5NO4vz | 4,642 | Streaming issue for ccdv/pubmed-summarization | {
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"Thanks for reporting @lewtun.\r\n\r\nI confirm there is an issue with streaming: it does not stream locally. ",
"Oh, after investigation, the source of the issue is in the Hub dataset loading script.\r\n\r\nI'm opening a PR on the Hub dataset.",
"I've opened a PR on their Hub dataset to support streaming: http... | 2022-07-06T12:13:07Z | 2022-07-06T14:17:34Z | 2022-07-06T14:17:34Z | MEMBER | null | null | null | ### Link
https://huggingface.co/datasets/ccdv/pubmed-summarization
### Description
This was reported by a [user of AutoTrain Evaluate](https://huggingface.co/spaces/autoevaluate/model-evaluator/discussions/7). It seems like streaming doesn't work due to the way the dataset loading script is defined?
```
Status code: 400
Exception: FileNotFoundError
Message: https://huggingface.co/datasets/ccdv/pubmed-summarization/resolve/main/train.zip/train.txt
```
### Owner
No | {
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https://api.github.com/repos/huggingface/datasets/issues/2593 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2593/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2593/comments | https://api.github.com/repos/huggingface/datasets/issues/2593/events | https://github.com/huggingface/datasets/pull/2593 | 937,242,137 | MDExOlB1bGxSZXF1ZXN0NjgzODMwMjcy | 2,593 | Support pandas 1.3.0 read_csv | {
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} | Workaround for this issue in pandas 1.3.0 : https://github.com/pandas-dev/pandas/issues/42387
The csv reader raises an error:
```python
/usr/local/lib/python3.7/dist-packages/pandas/io/parsers/readers.py in _refine_defaults_read(dialect, delimiter, delim_whitespace, engine, sep, error_bad_lines, warn_bad_lines, on_bad_lines, names, prefix, defaults)
1304
1305 if names is not lib.no_default and prefix is not lib.no_default:
-> 1306 raise ValueError("Specified named and prefix; you can only specify one.")
1307
1308 kwds["names"] = None if names is lib.no_default else names
ValueError: Specified named and prefix; you can only specify one.
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/5237 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5237/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5237/comments | https://api.github.com/repos/huggingface/datasets/issues/5237/events | https://github.com/huggingface/datasets/pull/5237 | 1,448,202,491 | PR_kwDODunzps5C2KGz | 5,237 | Encode path only for old versions of hfh | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-11-14T14:46:57Z | 2022-11-14T17:38:18Z | 2022-11-14T17:35:59Z | MEMBER | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/5750 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5750/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5750/comments | https://api.github.com/repos/huggingface/datasets/issues/5750/events | https://github.com/huggingface/datasets/issues/5750 | 1,668,289,067 | I_kwDODunzps5jcBIr | 5,750 | Fail to create datasets from a generator when using Google Big Query | {
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"`from_generator` expects a generator function, not a generator object, so this should work:\r\n```python\r\nfrom datasets import Dataset\r\nfrom google.cloud import bigquery\r\n\r\nclient = bigquery.Client()\r\n\r\ndef gen()\r\n # Perform a query.\r\n QUERY = (\r\n 'SELECT name FROM `bigquery-public-d... | 2023-04-14T13:50:59Z | 2023-04-17T12:20:43Z | 2023-04-17T12:20:43Z | NONE | null | null | null | ### Describe the bug
Creating a dataset from a generator using `Dataset.from_generator()` fails if the generator is the [Google Big Query Python client](https://cloud.google.com/python/docs/reference/bigquery/latest). The problem is that the Big Query client is not pickable. And the function `create_config_id` tries to get a hash of the generator by pickling it. So the following error is generated:
```
_pickle.PicklingError: Pickling client objects is explicitly not supported.
Clients have non-trivial state that is local and unpickleable.
```
### Steps to reproduce the bug
1. Install the big query client and datasets `pip install google-cloud-bigquery datasets`
2. Run the following code:
```py
from datasets import Dataset
from google.cloud import bigquery
client = bigquery.Client()
# Perform a query.
QUERY = (
'SELECT name FROM `bigquery-public-data.usa_names.usa_1910_2013` '
'WHERE state = "TX" '
'LIMIT 100')
query_job = client.query(QUERY) # API request
rows = query_job.result() # Waits for query to finish
ds = Dataset.from_generator(rows)
for r in ds:
print(r)
```
### Expected behavior
Two options:
1. Ignore the pickle errors when computing the hash
2. Provide a scape hutch so that we can avoid calculating the hash for the generator. For example, allowing to provide a hash from the user.
### Environment info
python 3.9
google-cloud-bigquery 3.9.0
datasets 2.11.0
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"Yes, I agree this feature is much needed. We could do something similar to what TF does (https://www.tensorflow.org/api_docs/python/tf/data/Dataset#cache). \r\n\r\nIdeally, if the entire streamed dataset is consumed/cached, the generated cache should be reusable for the Arrow dataset."
] | 2021-10-22T13:09:53Z | 2021-10-29T11:14:39Z | null | CONTRIBUTOR | null | null | null | **Is your feature request related to a problem? Please describe.**
The streaming mode allows to get the 100 first rows of a dataset very quickly. But it does not cache the answer, so a posterior call to get the same 100 rows will send a request to the server again and again.
**Describe the solution you'd like**
Provide a way to write the streamed rows of a dataset on the disk, and to load from it later.
**Describe alternatives you've considered**
Provide a third mode: `lazy`, which would use the local cache for the data that have already been fetched previously, and use streaming to get the rest of the requested data.
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https://api.github.com/repos/huggingface/datasets/issues/4046 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4046/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4046/comments | https://api.github.com/repos/huggingface/datasets/issues/4046/events | https://github.com/huggingface/datasets/pull/4046 | 1,183,723,360 | PR_kwDODunzps41K6_H | 4,046 | Create metric card for XNLI | {
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"_The documentation is not available anymore as the PR was closed or merged._"
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https://api.github.com/repos/huggingface/datasets/issues/5902 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5902/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5902/comments | https://api.github.com/repos/huggingface/datasets/issues/5902/events | https://github.com/huggingface/datasets/pull/5902 | 1,727,342,194 | PR_kwDODunzps5RbPS9 | 5,902 | Fix `Overview.ipynb` & detach Jupyter Notebooks from `datasets` repository | {
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"Random fact: previous run was showing that the Hub was hosting 13336 datasets, while the most recent run shows 36662 👀🎉",
"_The documentation is not available anymore as the PR was closed or merged._",
"Thanks! \r\n\r\nHowever, I think we should stop linking this notebook and use the notebook version of the ... | 2023-05-26T10:25:01Z | 2023-07-25T13:50:06Z | 2023-07-25T13:38:33Z | CONTRIBUTOR | null | 0 | {
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} | ## What's in this PR?
This PR solves #5887 since there was a mismatch between the tokenizer and the model used, since the tokenizer was `bert-base-cased` while the model was `distilbert-base-case` both for the PyTorch and TensorFlow alternatives. Since DistilBERT doesn't use/need the `token_type_ids`, the `**batch` was failing, as the batch contained `input_ids`, `attention_mask`, `token_type_ids`, `start_positions` and `end_positions`, and `token_type_ids` was not required.
Besides that, at the end `seqeval` was being used to evaluate the model predictions, and just `evaluate` was being installed, so I've also included the `seqeval` installation.
Finally, I've re-run everything in Google Colab, and every cell was successfully executed!
## What was done on top of the original PR?
Based on the comments from @mariosasko and @stevhliu, I've updated the contents of this PR to also review the `quickstart.mdx` and update what was needed, besides that, we may eventually move the `Overview.ipynb` dataset to `huggingface/notebooks` following @stevhliu suggestions. | {
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https://api.github.com/repos/huggingface/datasets/issues/3540 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3540/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3540/comments | https://api.github.com/repos/huggingface/datasets/issues/3540/events | https://github.com/huggingface/datasets/issues/3540 | 1,094,900,336 | I_kwDODunzps5BQtpw | 3,540 | How to convert torch.utils.data.Dataset to datasets.arrow_dataset.Dataset? | {
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] | open | false | null | [] | null | [] | 2022-01-06T02:13:42Z | 2022-01-06T02:17:39Z | null | NONE | null | null | null | Hi,
I use torch.utils.data.Dataset to define my own data, but I need to use the 'map' function of datasets.arrow_dataset.Dataset later, so I hope to convert torch.utils.data.Dataset to datasets.arrow_dataset.Dataset.
Here is an example.
```
from torch.utils.data import Dataset
from datasets.arrow_dataset import Dataset as HFDataset
class ADataset(Dataset):
def __init__(self, data):
super().__init__()
self.data = data
def __getitem__(self, index):
return self.data[index]
def __len__(self):
return self.len
class MDataset():
def __init__(self, tokenizer: AutoTokenizer, data_args, training_args):
self.train_dataset = ADataset(data_args)
self.tokenizer = tokenizer
self.data_args = data_args
self.train_dataset = self.train_dataset.map(
self.process_function,
batched=True,
remove_columns=column_names,
load_from_cache_file=True,
desc="Running tokenizer on train dataset",
)
def process_function(self, examples):
sentences = [" ".join(sample[0][3]) for sample in examples]
tokenized = self.tokenizer(
sentences,
max_length=self.max_seq_len,
padding=self.padding,
truncation=True)
```
But it would raise an ERROR, AttributeError: 'ADataset' object has no attribute 'map'.
so how to convert torch.utils.data.Dataset to datasets.arrow_dataset.Dataset?
Thanks in advance!
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https://api.github.com/repos/huggingface/datasets/issues/2110 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2110/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2110/comments | https://api.github.com/repos/huggingface/datasets/issues/2110/events | https://github.com/huggingface/datasets/pull/2110 | 840,794,995 | MDExOlB1bGxSZXF1ZXN0NjAwNjI1NDQ5 | 2,110 | Fix incorrect assertion in builder.py | {
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"Hi ! The SplitInfo is not always available. By default you would get `split_info.num_examples == 0`\r\nSo unfortunately we can't use this assertion you suggested",
"> Hi ! The SplitInfo is not always available. By default you would get `split_info.num_examples == 0`\r\n> So unfortunately we can't use this assert... | 2021-03-25T10:39:20Z | 2021-04-12T13:33:03Z | 2021-04-12T13:33:03Z | CONTRIBUTOR | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/3933 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3933/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3933/comments | https://api.github.com/repos/huggingface/datasets/issues/3933/events | https://github.com/huggingface/datasets/pull/3933 | 1,170,253,605 | PR_kwDODunzps40flNM | 3,933 | Update README.md | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-03-15T20:52:05Z | 2022-03-17T17:51:24Z | 2022-03-17T17:47:37Z | NONE | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/5946 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5946/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5946/comments | https://api.github.com/repos/huggingface/datasets/issues/5946/events | https://github.com/huggingface/datasets/issues/5946 | 1,754,234,469 | I_kwDODunzps5oj35l | 5,946 | IndexError Not Solving -> IndexError: Invalid key: ?? is out of bounds for size 0 or ?? | {
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"https://colab.research.google.com/#scrollTo=AQ_HCYruWIHU&fileId=https%3A//huggingface.co/dfurman/falcon-40b-chat-oasst1/blob/main/finetune_falcon40b_oasst1_with_bnb_peft.ipynb\r\n\r\nI ran the same administration exactly the same but got the same error",
"Looks related to https://discuss.huggingface.co/t/indexer... | 2023-06-13T07:34:15Z | 2023-07-14T12:04:48Z | null | NONE | null | null | null | ### Describe the bug
in <cell line: 1>:1 │
│ │
│ /usr/local/lib/python3.10/dist-packages/transformers/trainer.py:1537 in train │
│ │
│ 1534 │ │ inner_training_loop = find_executable_batch_size( │
│ 1535 │ │ │ self._inner_training_loop, self._train_batch_size, args.auto_find_batch_size │
│ 1536 │ │ ) │
│ ❱ 1537 │ │ return inner_training_loop( │
│ 1538 │ │ │ args=args, │
│ 1539 │ │ │ resume_from_checkpoint=resume_from_checkpoint, │
│ 1540 │ │ │ trial=trial, │
│ │
│ /usr/local/lib/python3.10/dist-packages/transformers/trainer.py:1789 in _inner_training_loop │
│ │
│ 1786 │ │ │ │ rng_to_sync = True │
│ 1787 │ │ │ │
│ 1788 │ │ │ step = -1 │
│ ❱ 1789 │ │ │ for step, inputs in enumerate(epoch_iterator): │
│ 1790 │ │ │ │ total_batched_samples += 1 │
│ 1791 │ │ │ │ if rng_to_sync: │
│ 1792 │ │ │ │ │ self._load_rng_state(resume_from_checkpoint) │
│ │
│ /usr/local/lib/python3.10/dist-packages/accelerate/data_loader.py:377 in __iter__ │
│ │
│ 374 │ │ dataloader_iter = super().__iter__() │
│ 375 │ │ # We iterate one batch ahead to check when we are at the end │
│ 376 │ │ try: │
│ ❱ 377 │ │ │ current_batch = next(dataloader_iter) │
│ 378 │ │ except StopIteration: │
│ 379 │ │ │ yield │
│ 380 │
│ │
│ /usr/local/lib/python3.10/dist-packages/torch/utils/data/dataloader.py:633 in __next__ │
│ │
│ 630 │ │ │ if self._sampler_iter is None: │
│ 631 │ │ │ │ # TODO(https://github.com/pytorch/pytorch/issues/76750) │
│ 632 │ │ │ │ self._reset() # type: ignore[call-arg] │
│ ❱ 633 │ │ │ data = self._next_data() │
│ 634 │ │ │ self._num_yielded += 1 │
│ 635 │ │ │ if self._dataset_kind == _DatasetKind.Iterable and \ │
│ 636 │ │ │ │ │ self._IterableDataset_len_called is not None and \ │
│ │
│ /usr/local/lib/python3.10/dist-packages/torch/utils/data/dataloader.py:677 in _next_data │
│ │
│ 674 │ │
│ 675 │ def _next_data(self): │
│ 676 │ │ index = self._next_index() # may raise StopIteration │
│ ❱ 677 │ │ data = self._dataset_fetcher.fetch(index) # may raise StopIteration │
│ 678 │ │ if self._pin_memory: │
│ 679 │ │ │ data = _utils.pin_memory.pin_memory(data, self._pin_memory_device) │
│ 680 │ │ return data │
│ │
│ /usr/local/lib/python3.10/dist-packages/torch/utils/data/_utils/fetch.py:49 in fetch │
│ │
│ 46 │ def fetch(self, possibly_batched_index): │
│ 47 │ │ if self.auto_collation: │
│ 48 │ │ │ if hasattr(self.dataset, "__getitems__") and self.dataset.__getitems__: │
│ ❱ 49 │ │ │ │ data = self.dataset.__getitems__(possibly_batched_index) │
│ 50 │ │ │ else: │
│ 51 │ │ │ │ data = [self.dataset[idx] for idx in possibly_batched_index] │
│ 52 │ │ else: │
│ │
│ /usr/local/lib/python3.10/dist-packages/datasets/arrow_dataset.py:2782 in __getitems__ │
│ │
│ 2779 │ │
│ 2780 │ def __getitems__(self, keys: List) -> List: │
│ 2781 │ │ """Can be used to get a batch using a list of integers indices.""" │
│ ❱ 2782 │ │ batch = self.__getitem__(keys) │
│ 2783 │ │ n_examples = len(batch[next(iter(batch))]) │
│ 2784 │ │ return [{col: array[i] for col, array in batch.items()} for i in range(n_example │
│ 2785 │
│ │
│ /usr/local/lib/python3.10/dist-packages/datasets/arrow_dataset.py:2778 in __getitem__ │
│ │
│ 2775 │ │
│ 2776 │ def __getitem__(self, key): # noqa: F811 │
│ 2777 │ │ """Can be used to index columns (by string names) or rows (by integer index or i │
│ ❱ 2778 │ │ return self._getitem(key) │
│ 2779 │ │
│ 2780 │ def __getitems__(self, keys: List) -> List: │
│ 2781 │ │ """Can be used to get a batch using a list of integers indices.""" │
│ │
│ /usr/local/lib/python3.10/dist-packages/datasets/arrow_dataset.py:2762 in _getitem │
│ │
│ 2759 │ │ format_kwargs = kwargs["format_kwargs"] if "format_kwargs" in kwargs else self._ │
│ 2760 │ │ format_kwargs = format_kwargs if format_kwargs is not None else {} │
│ 2761 │ │ formatter = get_formatter(format_type, features=self._info.features, **format_kw │
│ ❱ 2762 │ │ pa_subtable = query_table(self._data, key, indices=self._indices if self._indice │
│ 2763 │ │ formatted_output = format_table( │
│ 2764 │ │ │ pa_subtable, key, formatter=formatter, format_columns=format_columns, output │
│ 2765 │ │ ) │
│ │
│ /usr/local/lib/python3.10/dist-packages/datasets/formatting/formatting.py:578 in query_table │
│ │
│ 575 │ │ _check_valid_column_key(key, table.column_names) │
│ 576 │ else: │
│ 577 │ │ size = indices.num_rows if indices is not None else table.num_rows │
│ ❱ 578 │ │ _check_valid_index_key(key, size) │
│ 579 │ # Query the main table │
│ 580 │ if indices is None: │
│ 581 │ │ pa_subtable = _query_table(table, key) │
│ │
│ /usr/local/lib/python3.10/dist-packages/datasets/formatting/formatting.py:531 in │
│ _check_valid_index_key │
│ │
│ 528 │ │ │ _check_valid_index_key(min(key), size=size) │
│ 529 │ elif isinstance(key, Iterable): │
│ 530 │ │ if len(key) > 0: │
│ ❱ 531 │ │ │ _check_valid_index_key(int(max(key)), size=size) │
│ 532 │ │ │ _check_valid_index_key(int(min(key)), size=size) │
│ 533 │ else: │
│ 534 │ │ _raise_bad_key_type(key) │
│ │
│ /usr/local/lib/python3.10/dist-packages/datasets/formatting/formatting.py:521 in │
│ _check_valid_index_key │
│ │
│ 518 def _check_valid_index_key(key: Union[int, slice, range, Iterable], size: int) -> None: │
│ 519 │ if isinstance(key, int): │
│ 520 │ │ if (key < 0 and key + size < 0) or (key >= size): │
│ ❱ 521 │ │ │ raise IndexError(f"Invalid key: {key} is out of bounds for size {size}") │
│ 522 │ │ return │
│ 523 │ elif isinstance(key, slice): │
│ 524 │ │ pass
### Steps to reproduce the bug
``
import json
import os
from pprint import pprint
import bitsandbytes as bnb
import pandas as pd
import torch
import torch.nn as nn
import transformers
from datasets import Dataset,load_dataset
from peft import (
LoraConfig,
PeftConfig,
PeftModel,
get_peft_model,
prepare_model_for_kbit_training
)
from transformers import (
AutoConfig,
AutoModelForCausalLM,
AutoTokenizer,
BitsAndBytesConfig,
)
os.environ["CUDA_VISIBLE_DEVICES"] = "0"
def print_trainable_parameters(model):
"""
Prints the number of trainable parameters in the model.
"""
trainable_params = 0
all_param = 0
for _, param in model.named_parameters():
all_param += param.numel()
if param.requires_grad:
trainable_params += param.numel()
print(
f"trainable params: {trainable_params} || all params: {all_param} || trainable%: {100 * trainable_params / all_param}"
)
MODEL_NAME = "tiiuae/falcon-7b"
bnb_config = BitsAndBytesConfig(
load_in_4bit = True,
bnb_4bit_use_double_quant=True,
bnb_4bit_quant_type="nf4",
bnb_4bit_compute_dtype=torch.bfloat16,
)
model = AutoModelForCausalLM.from_pretrained(
MODEL_NAME,
device_map = "auto",
trust_remote_code = True,
quantization_config = bnb_config
)
tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
tokenizer.pad_token = tokenizer.eos_token
model.gradient_checkpointing_enable()
model = prepare_model_for_kbit_training(model)
config = LoraConfig(
r = 16,
lora_alpha = 32,
target_modules = ["query_key_value"],
lora_dropout = 0.05,
bias = "none",
task_type = "CASUAL_LM"
)
model = get_peft_model(model,config)
print_trainable_parameters(model)
def generate_prompt(data_point):
return f"""
<human>: {data_point["question"]}
<assistant>: {data_point["answer"]}
""".strip()
def generate_and_tokenize_prompt(data_point):
full_prompt = generate_prompt(data_point)
tokenized_full_prompt = tokenizer(full_prompt, padding = True, truncation = True,return_tensors = None)
return dict({
"input_ids" : tokenized_full_prompt["input_ids"],
"attention_mask" : tokenized_full_prompt["attention_mask"]
})
data = data["train"].shuffle().map(generate_and_tokenize_prompt, batched = False)
OUTPUT_DIR = "experiments"
trainings_args = transformers.TrainingArguments(
per_device_train_batch_size = 1,
gradient_accumulation_steps = 4,
num_train_epochs = 1,
learning_rate = 2e-4,
fp16 = True,
save_total_limit = 3,
logging_steps = 1,
output_dir = OUTPUT_DIR,
max_steps = 80,
optim = "paged_adamw_8bit",
lr_scheduler_type = "cosine",
warmup_ratio = 0.05,
#remove_unused_columns=True
)
trainer = transformers.Trainer(
model = model,
train_dataset = data,
args = trainings_args,
data_collator = transformers.DataCollatorForLanguageModeling(tokenizer, mlm=False),
)
model.config.use_cache = False
trainer.train()
IndexError: Invalid key: 32 is out of bounds for size 0
DataSet Format is like :
[{"question": "How can I create an account?", "answer": "To create an account, click on the 'Sign Up' button on the top right corner of our website and follow the instructions to complete the registration process."}, .... ]
### Expected behavior
-
### Environment info
!pip install -q pip
!pip install -q bitsandbytes==0.39.0
!pip install -q torch==2.0.1
!pip install -q git+https://github.com/huggingface/transformers.git
!pip install -q git+https://github.com/huggingface/peft.git
!pip install -q git+https://github.com/huggingface/accelerate.git
!pip install -q datasets
!pip install -q loralib==0.1.1
!pip install -q einops==0.6.1
import json
import os
from pprint import pprint
import bitsandbytes as bnb
import pandas as pd
import torch
import torch.nn as nn
import transformers
from datasets import Dataset,load_dataset
from peft import (
LoraConfig,
PeftConfig,
PeftModel,
get_peft_model,
prepare_model_for_kbit_training
)
from transformers import (
AutoConfig,
AutoModelForCausalLM,
AutoTokenizer,
BitsAndBytesConfig,
)
os.environ["CUDA_VISIBLE_DEVICES"] = "0"
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https://api.github.com/repos/huggingface/datasets/issues/2677 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2677/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2677/comments | https://api.github.com/repos/huggingface/datasets/issues/2677/events | https://github.com/huggingface/datasets/issues/2677 | 948,429,788 | MDU6SXNzdWU5NDg0Mjk3ODg= | 2,677 | Error when downloading C4 | {
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"Hi Thanks for reporting !\r\nIt looks like these files are not correctly reported in the list of expected files to download, let me fix that ;)",
"Alright this is fixed now. We'll do a new release soon to make the fix available.\r\n\r\nIn the meantime feel free to simply pass `ignore_verifications=True` to `load... | 2021-07-20T08:37:30Z | 2021-07-20T14:41:31Z | 2021-07-20T14:38:10Z | NONE | null | null | null | Hi,
I am trying to download `en` corpus from C4 dataset. However, I get an error caused by validation files download (see image). My code is very primitive:
`datasets.load_dataset('c4', 'en')`
Is this a bug or do I have some configurations missing on my server?
Thanks!
<img width="1014" alt="Снимок экрана 2021-07-20 в 11 37 17" src="https://user-images.githubusercontent.com/36672861/126289448-6e0db402-5f3f-485a-bf74-eb6e0271fc25.png"> | {
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https://api.github.com/repos/huggingface/datasets/issues/4116 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4116/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4116/comments | https://api.github.com/repos/huggingface/datasets/issues/4116/events | https://github.com/huggingface/datasets/pull/4116 | 1,194,926,459 | PR_kwDODunzps41wCEO | 4,116 | Pretty print dataset info files | {
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"maybe just do it from now on no? (i.e. not for existing `dataset_infos.json` files)",
"_The documentation is not available anymore as the PR was closed or merged._",
"> maybe just do it from now on no? (i.e. not for existing dataset_infos.json files)\r\n\r\nYes, or do this only for datasets created with `push_... | 2022-04-06T17:40:48Z | 2022-04-08T11:28:01Z | 2022-04-08T11:21:53Z | CONTRIBUTOR | null | 0 | {
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} | Adds indentation to the `dataset_infos.json` file when saving for nicer diffs.
(suggested by @julien-c)
This PR also updates the info files of the GH datasets. Note that this change adds more than **10 MB** to the repo size (the total file size before the change: 29.672298 MB, after: 41.666475 MB), so I'm not sure this change is a good idea.
`src/datasets/info.py` is the only relevant file for reviewers.
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https://api.github.com/repos/huggingface/datasets/issues/4064 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4064/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4064/comments | https://api.github.com/repos/huggingface/datasets/issues/4064/events | https://github.com/huggingface/datasets/pull/4064 | 1,186,650,321 | PR_kwDODunzps41UqXS | 4,064 | Contributing MedMCQA dataset | {
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"@lhoestq Could you please take a look?\r\nThank you!!",
"Hi, thank you for the modifications and suggestions. Please check the changes.",
"Can you run `make style` to fix the code formatting please ?\r\n\r\nOh and was wrong with the dummy_data.zip file, it must actually be placed at `datasets/medmcqa/dummy/1.1... | 2022-03-30T15:42:47Z | 2022-05-06T09:40:40Z | 2022-05-06T08:42:56Z | CONTRIBUTOR | null | 0 | {
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} | Adding MedMCQA dataset ( https://paperswithcode.com/dataset/medmcqa )
**Name**: MedMCQA
**Description**: MedMCQA is a large-scale, Multiple-Choice Question Answering (MCQA) dataset designed to address real-world medical entrance exam questions.
MedMCQA has more than 194k high-quality AIIMS & NEET PG entrance exam MCQs covering 2.4k healthcare topics and 21 medical subjects are collected with an average token length of 12.77 and high topical diversity.
The dataset contains questions about the following topics: Anesthesia, Anatomy, Biochemistry, Dental, ENT, Forensic Medicine (FM), Obstetrics and Gynecology (O&G), Medicine, Microbiology, Ophthalmology, Orthopedics Pathology, Pediatrics, Pharmacology, Physiology,
Psychiatry, Radiology Skin, Preventive & Social Medicine (PSM), and Surgery
**Code**: https://github.com/medmcqa/medmcqa
All files are at place :
**a dataset script** : medmcqa.py
**a dataset card with tags and information** : README.md.
**a metadata file** : dataset_infos.json
**a dummy-data file** : Please help to generate this file, I was facing
` raise JSONDecodeError("Extra data", s, end)` error | {
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https://api.github.com/repos/huggingface/datasets/issues/3040 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3040/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3040/comments | https://api.github.com/repos/huggingface/datasets/issues/3040/events | https://github.com/huggingface/datasets/issues/3040 | 1,018,782,475 | I_kwDODunzps48uWML | 3,040 | [save_to_disk] Using `select()` followed by `save_to_disk` saves complete dataset making it hard to create dummy dataset | {
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"Hi,\r\n\r\nthe `save_to_disk` docstring explains that `flatten_indices` has to be called on a dataset before saving it to save only the shard/slice of the dataset.",
"That works! Thansk!\r\n\r\nMight be worth doing that automatically actually in case the `save_to_disk` is called on a dataset that has an indices ... | 2021-10-06T17:08:47Z | 2021-11-02T15:41:08Z | 2021-11-02T15:41:08Z | MEMBER | null | null | null | ## Describe the bug
When only keeping a dummy size of a dataset (say the first 100 samples), and then saving it to disk to upload it in the following to the hub for easy demo/use - not just the small dataset is saved but the whole dataset with an indices file. The problem with this is that the dataset is still very big.
## Steps to reproduce the bug
E.g. run the following:
```python
from datasets import load_dataset, save_to_disk
nlp = load_dataset("glue", "mnli", split="train")
nlp.save_to_disk("full")
nlp = nlp.select(range(100))
nlp.save_to_disk("dummy")
```
Now one can see that both `"dummy"` and `"full"` have the same size. This shouldn't be the case IMO.
## Expected results
IMO `"dummy"` should be much smaller so that one can easily play around with the dataset on the hub.
## Actual results
Specify the actual results or traceback.
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.12.2.dev0
- Platform: Linux-5.11.0-34-generic-x86_64-with-glibc2.10
- Python version: 3.8.5
- PyArrow version: 5.0.0
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https://api.github.com/repos/huggingface/datasets/issues/6178 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6178/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6178/comments | https://api.github.com/repos/huggingface/datasets/issues/6178/events | https://github.com/huggingface/datasets/issues/6178 | 1,866,610,102 | I_kwDODunzps5vQjW2 | 6,178 | 'import datasets' throws "invalid syntax error" | {
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"This seems to be related to your environment and not the `datasets` code (e.g., this could happen when exposing the Python 3.9 site packages to a lower Python version (interpreter))"
] | 2023-08-25T08:35:14Z | 2023-09-27T17:33:39Z | 2023-09-27T17:33:39Z | NONE | null | null | null | ### Describe the bug
Hi,
I have been trying to import the datasets library but I keep gtting this error.
`Traceback (most recent call last):
File /opt/local/jupyterhub/lib64/python3.9/site-packages/IPython/core/interactiveshell.py:3508 in run_code
exec(code_obj, self.user_global_ns, self.user_ns)
Cell In[2], line 1
import datasets
File /opt/local/jupyterhub/lib64/python3.9/site-packages/datasets/__init__.py:22
from .arrow_dataset import Dataset
File /opt/local/jupyterhub/lib64/python3.9/site-packages/datasets/arrow_dataset.py:67
from .arrow_writer import ArrowWriter, OptimizedTypedSequence
File /opt/local/jupyterhub/lib64/python3.9/site-packages/datasets/arrow_writer.py:27
from .features import Features, Image, Value
File /opt/local/jupyterhub/lib64/python3.9/site-packages/datasets/features/__init__.py:17
from .audio import Audio
File /opt/local/jupyterhub/lib64/python3.9/site-packages/datasets/features/audio.py:11
from ..download.streaming_download_manager import xopen, xsplitext
File /opt/local/jupyterhub/lib64/python3.9/site-packages/datasets/download/__init__.py:10
from .streaming_download_manager import StreamingDownloadManager
File /opt/local/jupyterhub/lib64/python3.9/site-packages/datasets/download/streaming_download_manager.py:18
from aiohttp.client_exceptions import ClientError
File /opt/local/jupyterhub/lib64/python3.9/site-packages/aiohttp/__init__.py:7
from .connector import * # noqa
File /opt/local/jupyterhub/lib64/python3.9/site-packages/aiohttp/connector.py:12
from .client import ClientRequest
File /opt/local/jupyterhub/lib64/python3.9/site-packages/aiohttp/client.py:144
yield from asyncio.async(resp.release(), loop=loop)
^
SyntaxError: invalid syntax`
I have simply used these commands:
`import datasets`
and
`from datasets import load_dataset`
### Environment info
The library has been installed a virtual machine on JupyterHub. Although I have used this library multiple times (on the same VM) before, to train/test an ASR or other ML models, I had never encountered this error. | {
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https://api.github.com/repos/huggingface/datasets/issues/5412 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5412/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5412/comments | https://api.github.com/repos/huggingface/datasets/issues/5412/events | https://github.com/huggingface/datasets/issues/5412 | 1,524,250,269 | I_kwDODunzps5a2jad | 5,412 | load_dataset() cannot find dataset_info.json with multiple training runs in parallel | {
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"Hi ! It fails because the dataset is already being prepared by your first run. I'd encourage you to prepare your dataset before using it for multiple trainings.\r\n\r\nYou can also specify another cache directory by passing `cache_dir=` to `load_dataset()`.",
"Thank you! What do you mean by prepare it beforehand... | 2023-01-08T00:44:32Z | 2023-01-19T20:28:43Z | 2023-01-19T20:28:43Z | NONE | null | null | null | ### Describe the bug
I have a custom local dataset in JSON form. I am trying to do multiple training runs in parallel. The first training run runs with no issue. However, when I start another run on another GPU, the following code throws this error.
If there is a workaround to ignore the cache I think that would solve my problem too.
I am using datasets version 2.8.0.
### Steps to reproduce the bug
1. Start training run of GPU 0 loading dataset from
```
load_dataset(
"json",
data_files=tr_dataset_path,
split=f"train",
download_mode="force_redownload",
)
```
2. While GPU 0 is training, start an identical run on GPU 1. GPU 1 will produce the following error:
```
Traceback (most recent call last):
File "/local-scratch1/data/mt/code/qq/train.py", line 198, in <module>
main()
File "/home/username/.local/lib/python3.8/site-packages/click/core.py", line 1130, in __call__
return self.main(*args, **kwargs)
File "/home/username/.local/lib/python3.8/site-packages/click/core.py", line 1055, in main
rv = self.invoke(ctx)
File "/home/username/.local/lib/python3.8/site-packages/click/core.py", line 1404, in invoke
return ctx.invoke(self.callback, **ctx.params)
File "/home/username/.local/lib/python3.8/site-packages/click/core.py", line 760, in invoke
return __callback(*args, **kwargs)
File "/local-scratch1/data/mt/code/qq/train.py", line 113, in main
load_dataset(
File "/home/username/miniconda3/envs/qq3/lib/python3.8/site-packages/datasets/load.py", line 1734, in load_dataset
builder_instance = load_dataset_builder(
File "/home/username/miniconda3/envs/qq3/lib/python3.8/site-packages/datasets/load.py", line 1518, in load_dataset_builder
builder_instance: DatasetBuilder = builder_cls(
File "/home/username/miniconda3/envs/qq3/lib/python3.8/site-packages/datasets/builder.py", line 366, in __init__
self.info = DatasetInfo.from_directory(self._cache_dir)
File "/home/username/miniconda3/envs/qq3/lib/python3.8/site-packages/datasets/info.py", line 313, in from_directory
with fs.open(path_join(dataset_info_dir, config.DATASET_INFO_FILENAME), "r", encoding="utf-8") as f:
File "/home/username/miniconda3/envs/qq3/lib/python3.8/site-packages/fsspec/spec.py", line 1094, in open
self.open(
File "/home/username/miniconda3/envs/qq3/lib/python3.8/site-packages/fsspec/spec.py", line 1106, in open
f = self._open(
File "/home/username/miniconda3/envs/qq3/lib/python3.8/site-packages/fsspec/implementations/local.py", line 175, in _open
return LocalFileOpener(path, mode, fs=self, **kwargs)
File "/home/username/miniconda3/envs/qq3/lib/python3.8/site-packages/fsspec/implementations/local.py", line 273, in __init__
self._open()
File "/home/username/miniconda3/envs/qq3/lib/python3.8/site-packages/fsspec/implementations/local.py", line 278, in _open
self.f = open(self.path, mode=self.mode)
FileNotFoundError: [Errno 2] No such file or directory: '/home/username/.cache/huggingface/datasets/json/default-43d06a4aedb25e6d/0.0.0/0f7e3662623656454fcd2b650f34e886a7db4b9104504885bd462096cc7a9f51/dataset_info.json'
```
### Expected behavior
Expected behavior: 2nd GPU training run should run the same as 1st GPU training run.
### Environment info
Copy-and-paste the text below in your GitHub issue.
- `datasets` version: 2.8.0
- Platform: Linux-5.4.0-120-generic-x86_64-with-glibc2.10
- Python version: 3.8.15
- PyArrow version: 9.0.0
- Pandas version: 1.5.2 | {
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https://api.github.com/repos/huggingface/datasets/issues/4485 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4485/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4485/comments | https://api.github.com/repos/huggingface/datasets/issues/4485/events | https://github.com/huggingface/datasets/pull/4485 | 1,269,463,054 | PR_kwDODunzps45kD7A | 4,485 | Fix cast to null | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-06-13T13:44:32Z | 2022-06-14T13:43:54Z | 2022-06-14T13:34:14Z | MEMBER | null | 0 | {
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} | It currently fails with `ArrowNotImplementedError` instead of `TypeError` when one tries to cast integer to null type.
Because if this, type inference breaks when one replaces null values with integers in `map` (it first tries to cast to the previous type before inferring the new type).
Fix https://github.com/huggingface/datasets/issues/4483 | {
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https://api.github.com/repos/huggingface/datasets/issues/5594 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5594/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5594/comments | https://api.github.com/repos/huggingface/datasets/issues/5594/events | https://github.com/huggingface/datasets/issues/5594 | 1,603,980,995 | I_kwDODunzps5fms7D | 5,594 | Error while downloading the xtreme udpos dataset | {
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"Hi! I cannot reproduce this error on my machine.\r\n\r\nThe raised error could mean that one of the downloaded files is corrupted. To verify this is not the case, you can run `load_dataset` as follows:\r\n```python\r\ntrain_dataset = load_dataset('xtreme', 'udpos.English', split=\"train\", cache_dir=args.cache_dir... | 2023-02-28T23:40:53Z | 2023-10-10T01:03:46Z | 2023-07-24T14:22:18Z | NONE | null | null | null | ### Describe the bug
Hi,
I am facing an error while downloading the xtreme udpos dataset using load_dataset. I have datasets 2.10.1 installed
```Downloading and preparing dataset xtreme/udpos.Arabic to /compute/tir-1-18/skhanuja/multilingual_ft/cache/data/xtreme/udpos.Arabic/1.0.0/29f5d57a48779f37ccb75cb8708d1095448aad0713b425bdc1ff9a4a128a56e4...
Downloading data: 16%|██████████████▏ | 56.9M/355M [03:11<16:43, 297kB/s]
Generating train split: 0%| | 0/6075 [00:00<?, ? examples/s]Traceback (most recent call last):
File "/home/skhanuja/miniconda3/envs/multilingual_ft/lib/python3.10/site-packages/datasets/builder.py", line 1608, in _prepare_split_single
for key, record in generator:
File "/home/skhanuja/.cache/huggingface/modules/datasets_modules/datasets/xtreme/29f5d57a48779f37ccb75cb8708d1095448aad0713b425bdc1ff9a4a128a56e4/xtreme.py", line 732, in _generate_examples
yield from UdposParser.generate_examples(config=self.config, filepath=filepath, **kwargs)
File "/home/skhanuja/.cache/huggingface/modules/datasets_modules/datasets/xtreme/29f5d57a48779f37ccb75cb8708d1095448aad0713b425bdc1ff9a4a128a56e4/xtreme.py", line 921, in generate_examples
for path, file in filepath:
File "/home/skhanuja/miniconda3/envs/multilingual_ft/lib/python3.10/site-packages/datasets/download/download_manager.py", line 158, in __iter__
yield from self.generator(*self.args, **self.kwargs)
File "/home/skhanuja/miniconda3/envs/multilingual_ft/lib/python3.10/site-packages/datasets/download/download_manager.py", line 211, in _iter_from_path
yield from cls._iter_tar(f)
File "/home/skhanuja/miniconda3/envs/multilingual_ft/lib/python3.10/site-packages/datasets/download/download_manager.py", line 167, in _iter_tar
for tarinfo in stream:
File "/home/skhanuja/miniconda3/envs/multilingual_ft/lib/python3.10/tarfile.py", line 2475, in __iter__
tarinfo = self.next()
File "/home/skhanuja/miniconda3/envs/multilingual_ft/lib/python3.10/tarfile.py", line 2344, in next
raise ReadError("unexpected end of data")
tarfile.ReadError: unexpected end of data
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/home/skhanuja/Optimal-Resource-Allocation-for-Multilingual-Finetuning/src/train_al.py", line 855, in <module>
main()
File "/home/skhanuja/Optimal-Resource-Allocation-for-Multilingual-Finetuning/src/train_al.py", line 487, in main
train_dataset = load_dataset(dataset_name, source_language, split="train", cache_dir=args.cache_dir, download_mode="force_redownload")
File "/home/skhanuja/miniconda3/envs/multilingual_ft/lib/python3.10/site-packages/datasets/load.py", line 1782, in load_dataset
builder_instance.download_and_prepare(
File "/home/skhanuja/miniconda3/envs/multilingual_ft/lib/python3.10/site-packages/datasets/builder.py", line 872, in download_and_prepare
self._download_and_prepare(
File "/home/skhanuja/miniconda3/envs/multilingual_ft/lib/python3.10/site-packages/datasets/builder.py", line 1649, in _download_and_prepare
super()._download_and_prepare(
File "/home/skhanuja/miniconda3/envs/multilingual_ft/lib/python3.10/site-packages/datasets/builder.py", line 967, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/home/skhanuja/miniconda3/envs/multilingual_ft/lib/python3.10/site-packages/datasets/builder.py", line 1488, in _prepare_split
for job_id, done, content in self._prepare_split_single(
File "/home/skhanuja/miniconda3/envs/multilingual_ft/lib/python3.10/site-packages/datasets/builder.py", line 1644, 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
```
### Steps to reproduce the bug
```
train_dataset = load_dataset('xtreme', 'udpos.English', split="train", cache_dir=args.cache_dir, download_mode="force_redownload")
```
### Expected behavior
Download the udpos dataset
### Environment info
- `datasets` version: 2.10.1
- Platform: Linux-3.10.0-957.1.3.el7.x86_64-x86_64-with-glibc2.17
- Python version: 3.10.8
- PyArrow version: 10.0.1
- Pandas version: 1.5.2 | {
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"gi... | null | [] | 2022-07-28T08:46:27Z | 2022-08-25T18:34:24Z | 2022-08-25T18:34:24Z | MEMBER | null | null | null | As discussed with @ydshieh, when passing a relative path as `data_dir` to `load_dataset` of a dataset hosted on the Hub, the relative path is transformed to the corresponding URL of the Hub dataset.
Currently, we mention this in our docs here: [Create a dataset loading script > Download data files and organize splits](https://huggingface.co/docs/datasets/v2.4.0/en/dataset_script#download-data-files-and-organize-splits)
> If the data files live in the same folder or repository of the dataset script, you can just pass the relative paths to the files instead of URLs.
Maybe we should document better how relative paths are handled, not only when creating a dataset loading script, but also when passing to `load_dataset`:
- `data_dir`
- `data_files`
CC: @stevhliu | {
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https://api.github.com/repos/huggingface/datasets/issues/3038 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3038/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3038/comments | https://api.github.com/repos/huggingface/datasets/issues/3038/events | https://github.com/huggingface/datasets/pull/3038 | 1,018,113,499 | PR_kwDODunzps4syno_ | 3,038 | add sberquad dataset | {
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"This PR is already working (although not very beautiful; see below): the idea was to have the `DatasetModule.builder_kwargs` accessible from the `builder_cls`, so that this can generate the default builder config (at the class level, without requiring the builder to be instantiated).\r\n\r\nI have a plan for a fol... | 2021-10-25T13:59:43Z | 2021-10-29T13:14:37Z | 2021-10-28T05:44:49Z | MEMBER | null | 0 | {
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Fix #3135. | {
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"Hi! Our versioning is based on Git revisions (the `revision` param in `load_dataset`), so you can just replace the old URL with the new one and open a PR :). I can also give you some pointers if needed.",
"@mariosasko Awesome thanks! I will do that. Looks like this new version of the data is not available as a z... | 2022-05-31T21:00:44Z | 2022-06-07T17:14:44Z | 2022-06-07T17:14:44Z | CONTRIBUTOR | null | null | null | **Is your feature request related to a problem? Please describe.**
The [Multi-News dataloader points to the original version of the Multi-News dataset](https://github.com/huggingface/datasets/blob/12540dd75015678ec6019f258d811ee107439a73/datasets/multi_news/multi_news.py#L47), but this has [known errors in it](https://github.com/Alex-Fabbri/Multi-News/issues/11). There exists a [newer version which fixes some of these issues](https://drive.google.com/open?id=1jwBzXBVv8sfnFrlzPnSUBHEEAbpIUnFq).
Unfortunately I don't think you can just replace this old URL with the new one, otherwise this could lead to issues with reproducibility.
**Describe the solution you'd like**
Add a new version to the Multi-News dataloader that points to the updated dataset which has fixes for some known issues.
**Describe alternatives you've considered**
Replace the current URL to the original version to the dataset with the URL to the version with fixes.
**Additional context**
Would be happy to make a PR for this, could someone maybe point me to another dataloader that has multiple versions so I can see how this is handled in `datasets`?
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https://api.github.com/repos/huggingface/datasets/issues/6219 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6219/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6219/comments | https://api.github.com/repos/huggingface/datasets/issues/6219/events | https://github.com/huggingface/datasets/pull/6219 | 1,884,244,334 | PR_kwDODunzps5ZsgPK | 6,219 | Release: 2.14.5 | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6219). 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... | 2023-09-06T15:17:10Z | 2023-09-06T15:46:20Z | 2023-09-06T15:18:51Z | MEMBER | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/2937 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2937/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2937/comments | https://api.github.com/repos/huggingface/datasets/issues/2937/events | https://github.com/huggingface/datasets/issues/2937 | 999,548,277 | I_kwDODunzps47k-V1 | 2,937 | load_dataset using default cache on Windows causes PermissionError: [WinError 5] Access is denied | {
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"Hi @daqieq, thanks for reporting.\r\n\r\nUnfortunately, I was not able to reproduce this bug:\r\n```ipython\r\nIn [1]: from datasets import load_dataset\r\n ...: ds = load_dataset('wiki_bio')\r\nDownloading: 7.58kB [00:00, 26.3kB/s]\r\nDownloading: 2.71kB [00:00, ?B/s]\r\nUsing custom data configuration default\... | 2021-09-17T16:52:10Z | 2022-08-24T13:09:08Z | 2022-08-24T13:09:08Z | NONE | null | null | null | ## Describe the bug
Standard process to download and load the wiki_bio dataset causes PermissionError in Windows 10 and 11.
## Steps to reproduce the bug
```python
from datasets import load_dataset
ds = load_dataset('wiki_bio')
```
## Expected results
It is expected that the dataset downloads without any errors.
## Actual results
PermissionError see trace below:
```
Using custom data configuration default
Downloading and preparing dataset wiki_bio/default (download: 318.53 MiB, generated: 736.94 MiB, post-processed: Unknown size, total: 1.03 GiB) to C:\Users\username\.cache\huggingface\datasets\wiki_bio\default\1.1.0\5293ce565954ba965dada626f1e79684e98172d950371d266bf3caaf87e911c9...
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "C:\Users\username\.conda\envs\hf\lib\site-packages\datasets\load.py", line 1112, in load_dataset
builder_instance.download_and_prepare(
File "C:\Users\username\.conda\envs\hf\lib\site-packages\datasets\builder.py", line 644, in download_and_prepare
self._save_info()
File "C:\Users\username\.conda\envs\hf\lib\contextlib.py", line 120, in __exit__
next(self.gen)
File "C:\Users\username\.conda\envs\hf\lib\site-packages\datasets\builder.py", line 598, in incomplete_dir
os.rename(tmp_dir, dirname)
PermissionError: [WinError 5] Access is denied: 'C:\\Users\\username\\.cache\\huggingface\\datasets\\wiki_bio\\default\\1.1.0\\5293ce565954ba965dada626f1e79684e98172d950371d266bf3caaf87e911c9.incomplete' -> 'C:\\Users\\username\\.cache\\huggingface\\datasets\\wiki_bio\\default\\1.1.0\\5293ce565954ba965dada626f1e79684e98172d950371d266bf3caaf87e911c9'
```
By commenting out the os.rename() [L604](https://github.com/huggingface/datasets/blob/master/src/datasets/builder.py#L604) and the shutil.rmtree() [L607](https://github.com/huggingface/datasets/blob/master/src/datasets/builder.py#L607) lines, in my virtual environment, I was able to get the load process to complete, rename the directory manually and then rerun the `load_dataset('wiki_bio')` to get what I needed.
It seems that os.rename() in the `incomplete_dir` content manager is the culprit. Here's another project [Conan](https://github.com/conan-io/conan/issues/6560) with similar issue with os.rename() if it helps debug this issue.
## Environment info
- `datasets` version: 1.12.1
- Platform: Windows-10-10.0.22449-SP0
- Python version: 3.8.12
- PyArrow version: 5.0.0
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https://api.github.com/repos/huggingface/datasets/issues/3851 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3851/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3851/comments | https://api.github.com/repos/huggingface/datasets/issues/3851/events | https://github.com/huggingface/datasets/issues/3851 | 1,162,137,998 | I_kwDODunzps5FRNGO | 3,851 | Load audio dataset error | {
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"Hi @lemoner20, thanks for reporting.\r\n\r\nI'm sorry but I cannot reproduce your problem:\r\n```python\r\nIn [1]: from datasets import load_dataset, load_metric, Audio\r\n ...: raw_datasets = load_dataset(\"superb\", \"ks\", split=\"train\")\r\n ...: print(raw_datasets[0][\"audio\"])\r\nDownloading builder sc... | 2022-03-08T02:16:04Z | 2022-09-27T12:13:55Z | 2022-03-08T11:20:06Z | NONE | null | null | null | ## Load audio dataset error
Hi, when I load audio dataset following https://huggingface.co/docs/datasets/audio_process and https://github.com/huggingface/datasets/tree/master/datasets/superb,
```
from datasets import load_dataset, load_metric, Audio
raw_datasets = load_dataset("superb", "ks", split="train")
print(raw_datasets[0]["audio"])
```
following errors occur
```
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-169-3f8253239fa0> in <module>
----> 1 raw_datasets[0]["audio"]
/usr/lib/python3.6/site-packages/datasets/arrow_dataset.py in __getitem__(self, key)
1924 """Can be used to index columns (by string names) or rows (by integer index or iterable of indices or bools)."""
1925 return self._getitem(
-> 1926 key,
1927 )
1928
/usr/lib/python3.6/site-packages/datasets/arrow_dataset.py in _getitem(self, key, decoded, **kwargs)
1909 pa_subtable = query_table(self._data, key, indices=self._indices if self._indices is not None else None)
1910 formatted_output = format_table(
-> 1911 pa_subtable, key, formatter=formatter, format_columns=format_columns, output_all_columns=output_all_columns
1912 )
1913 return formatted_output
/usr/lib/python3.6/site-packages/datasets/formatting/formatting.py in format_table(table, key, formatter, format_columns, output_all_columns)
530 python_formatter = PythonFormatter(features=None)
531 if format_columns is None:
--> 532 return formatter(pa_table, query_type=query_type)
533 elif query_type == "column":
534 if key in format_columns:
/usr/lib/python3.6/site-packages/datasets/formatting/formatting.py in __call__(self, pa_table, query_type)
279 def __call__(self, pa_table: pa.Table, query_type: str) -> Union[RowFormat, ColumnFormat, BatchFormat]:
280 if query_type == "row":
--> 281 return self.format_row(pa_table)
282 elif query_type == "column":
283 return self.format_column(pa_table)
/usr/lib/python3.6/site-packages/datasets/formatting/formatting.py in format_row(self, pa_table)
310 row = self.python_arrow_extractor().extract_row(pa_table)
311 if self.decoded:
--> 312 row = self.python_features_decoder.decode_row(row)
313 return row
314
/usr/lib/python3.6/site-packages/datasets/formatting/formatting.py in decode_row(self, row)
219
220 def decode_row(self, row: dict) -> dict:
--> 221 return self.features.decode_example(row) if self.features else row
222
223 def decode_column(self, column: list, column_name: str) -> list:
/usr/lib/python3.6/site-packages/datasets/features/features.py in decode_example(self, example)
1320 else value
1321 for column_name, (feature, value) in utils.zip_dict(
-> 1322 {key: value for key, value in self.items() if key in example}, example
1323 )
1324 }
/usr/lib/python3.6/site-packages/datasets/features/features.py in <dictcomp>(.0)
1319 if self._column_requires_decoding[column_name]
1320 else value
-> 1321 for column_name, (feature, value) in utils.zip_dict(
1322 {key: value for key, value in self.items() if key in example}, example
1323 )
/usr/lib/python3.6/site-packages/datasets/features/features.py in decode_nested_example(schema, obj)
1053 # Object with special decoding:
1054 elif isinstance(schema, (Audio, Image)):
-> 1055 return schema.decode_example(obj) if obj is not None else None
1056 return obj
1057
/usr/lib/python3.6/site-packages/datasets/features/audio.py in decode_example(self, value)
100 array, sampling_rate = self._decode_non_mp3_file_like(file)
101 else:
--> 102 array, sampling_rate = self._decode_non_mp3_path_like(path)
103 return {"path": path, "array": array, "sampling_rate": sampling_rate}
104
/usr/lib/python3.6/site-packages/datasets/features/audio.py in _decode_non_mp3_path_like(self, path)
143
144 with xopen(path, "rb") as f:
--> 145 array, sampling_rate = librosa.load(f, sr=self.sampling_rate, mono=self.mono)
146 return array, sampling_rate
147
/usr/lib/python3.6/site-packages/librosa/core/audio.py in load(path, sr, mono, offset, duration, dtype, res_type)
110
111 y = []
--> 112 with audioread.audio_open(os.path.realpath(path)) as input_file:
113 sr_native = input_file.samplerate
114 n_channels = input_file.channels
/usr/lib/python3.6/posixpath.py in realpath(filename)
392 """Return the canonical path of the specified filename, eliminating any
393 symbolic links encountered in the path."""
--> 394 filename = os.fspath(filename)
395 path, ok = _joinrealpath(filename[:0], filename, {})
396 return abspath(path)
TypeError: expected str, bytes or os.PathLike object, not _io.BufferedReader
```
## Expected results
```
>>> raw_datasets[0]["audio"]
{'array': array([-0.0005188 , -0.00109863, 0.00030518, ..., 0.01730347,
0.01623535, 0.01724243]),
'path': '/root/.cache/huggingface/datasets/downloads/extracted/bb3a06b491a64aff422f307cd8116820b4f61d6f32fcadcfc554617e84383cb7/bed/026290a7_nohash_0.wav',
'sampling_rate': 16000}
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/6148 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6148/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6148/comments | https://api.github.com/repos/huggingface/datasets/issues/6148/events | https://github.com/huggingface/datasets/pull/6148 | 1,849,524,683 | PR_kwDODunzps5X3oqv | 6,148 | Ignore parallel warning in map_nested | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | rea... | 2023-08-14T10:43:41Z | 2023-08-17T08:54:06Z | 2023-08-17T08:43:58Z | MEMBER | null | 0 | {
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} | This warning message was shown every time you pass num_proc to `load_dataset` because of `map_nested`
```
parallel_map is experimental and might be subject to breaking changes in the future
```
This PR removes it for `map_nested`. If someone uses another parallel backend they're already warned when `parallel_backend` is called anyway | {
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https://api.github.com/repos/huggingface/datasets/issues/4336 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4336/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4336/comments | https://api.github.com/repos/huggingface/datasets/issues/4336/events | https://github.com/huggingface/datasets/pull/4336 | 1,234,446,174 | PR_kwDODunzps43vpqG | 4,336 | Eval metadata batch 2 : Health Fact, Jigsaw Toxicity, LIAR, LJ Speech, MSRA NER, Multi News, NCBI Disease, Poem Sentiment | {
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"Summary of CircleCI errors:\r\n- **Jjigsaw_toxicity_pred**: `Citation Information` but it is empty.\r\n- **LIAR** : `Data Instances`,`Data Fields`, `Data Splits`, `Citation Information` are empty.\r\n- **MSRA NER** : Dataset Summary`, `Data Instances`, `Data Fields`, `Data Splits`, `Citation Information` are ... | 2022-05-12T20:24:45Z | 2022-05-16T16:25:00Z | 2022-05-16T16:24:59Z | NONE | null | 0 | {
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} | Adding evaluation metadata for :
- Health Fact
- Jigsaw Toxicity
- LIAR
- LJ Speech
- MSRA NER
- Multi News
- NCBI Diseas
- Poem Sentiment | {
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"Hi! Yes, the docs are outdated. Expect this to be fixed soon. \r\n\r\nIn the meantime, you can try to fix the issue yourself.\r\n\r\nThese are the configs/language pairs supported by `wmt15` from which you can choose:\r\n* `cs-en` (Czech - English)\r\n* `de-en` (German - English)\r\n* `fi-en` (Finnish- English)\r\... | 2022-05-15T20:58:26Z | 2022-07-11T14:54:02Z | 2022-07-11T14:54:01Z | NONE | null | null | null | ## Describe the bug
I am trying to load WMT15 dataset and to define which data-sources to use for train/validation/test splits, but unfortunately it seems that the official documentation at [https://huggingface.co/datasets/wmt15#:~:text=Versions%20exists%20for,wmt_translate%22%2C%20config%3Dconfig)](https://huggingface.co/datasets/wmt15#:~:text=Versions%20exists%20for,wmt_translate%22%2C%20config%3Dconfig)) doesn't work anymore.
## Steps to reproduce the bug
```shell
>>> import datasets
>>> a = datasets.translate.wmt.WmtConfig()
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
AttributeError: module 'datasets' has no attribute 'translate'
>>> a = datasets.wmt.WmtConfig()
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
AttributeError: module 'datasets' has no attribute 'wmt'
```
## Expected results
To load WMT15 with given data-sources.
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 2.0.0
- Platform: Linux-5.10.0-10-amd64-x86_64-with-glibc2.17
- Python version: 3.8.12
- PyArrow version: 7.0.0
- Pandas version: 1.4.1
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} | UPDATE2: PR passed all tests. Now waiting for review.
UPDATE: pushed a new version. cross fingers that it should complete all the tests! :)
If it passes all tests then it's not a draft version.
This is a draft version | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"@lhoestq I've been refactoring a little the code:\r\n- Use less RAM by loading only the required samples: only if its index is in the splits file\r\n- Start yielding \"earlier\" in streaming mode: for each `split_idx`:\r\n - either ... | 2022-06-27T17:11:23Z | 2022-07-04T19:35:01Z | 2022-07-04T19:23:57Z | MEMBER | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/1270 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1270/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1270/comments | https://api.github.com/repos/huggingface/datasets/issues/1270/events | https://github.com/huggingface/datasets/pull/1270 | 758,917,216 | MDExOlB1bGxSZXF1ZXN0NTM0MDAyODIz | 1,270 | add DFKI SmartData Corpus | {
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} | - **Name:** DFKI SmartData Corpus
- **Description:** DFKI SmartData Corpus is a dataset of 2598 German-language documents which has been annotated with fine-grained geo-entities, such as streets, stops and routes, as well as standard named entity types.
- **Paper:** https://www.dfki.de/fileadmin/user_upload/import/9427_lrec_smartdata_corpus.pdf
- **Data:** https://github.com/DFKI-NLP/smartdata-corpus
- **Motivation:** Contains fine-grained NER labels for German.
### Checkbox
- [X] Create the dataset script `/datasets/my_dataset/my_dataset.py` using the template
- [X] Fill the `_DESCRIPTION` and `_CITATION` variables
- [X] Implement `_infos()`, `_split_generators()` and `_generate_examples()`
- [X] Make sure that the `BUILDER_CONFIGS` class attribute is filled with the different configurations of the dataset and that the `BUILDER_CONFIG_CLASS` is specified if there is a custom config class.
- [X] Generate the metadata file `dataset_infos.json` for all configurations
- [X] Generate the dummy data `dummy_data.zip` files to have the dataset script tested and that they don't weigh too much (<50KB)
- [X] Add the dataset card `README.md` using the template : fill the tags and the various paragraphs
- [X] Both tests for the real data and the dummy data pass.
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"Hi ! It looks like the issue comes from pyarrow. What version of pyarrow are you using ? How did you install it ?",
"Thank you for the quick reply! I have `pyarrow==4.0.0`, and I am installing with `pip`. It's not one of my explicit dependencies, so I assume it came along with something else.",
"Could you tryi... | 2021-06-09T22:40:22Z | 2021-07-01T09:34:54Z | 2021-07-01T09:11:13Z | NONE | null | null | null | ## Describe the bug
Crash if when using `num_proc` > 1 (I used 16) for `map()` on a `datasets.Dataset`.
I believe I've had cases where `num_proc` > 1 works before, but now it seems either inconsistent, or depends on my data. I'm not sure whether the issue is on my end, because it's difficult for me to debug! Any tips greatly appreciated, I'm happy to provide more info if it would helps us diagnose.
## Steps to reproduce the bug
```python
# this function will be applied with map()
def tokenize_function(examples):
return tokenizer(
examples["text"],
padding=PaddingStrategy.DO_NOT_PAD,
truncation=True,
)
# data_files is a Dict[str, str] mapping name -> path
datasets = load_dataset("text", data_files={...})
# this is where the error happens if num_proc = 16,
# but is fine if num_proc = 1
tokenized_datasets = datasets.map(
tokenize_function,
batched=True,
num_proc=num_workers,
)
```
## Expected results
The `map()` function succeeds with `num_proc` > 1.
## Actual results
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.6.2
- Platform: Linux-5.4.0-73-generic-x86_64-with-glibc2.31
- Python version: 3.9.5
- PyTorch version (GPU?): 1.8.1+cu111 (True)
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in script?: Yes, but I think N/A for this issue
- Using distributed or parallel set-up in script?: Multi-GPU on one machine, but I think also N/A for this issue
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"@lhoestq @abhishekkrthakur what happened here ?\r\n",
"@lhoestq everything alright here ?",
"@tanmoyio please have patience. @lhoestq has to look at 150+ PRs and it may take time. The PR looks good to me but we wait for his confirmation :) 🤗 "
] | 2020-12-11T18:12:38Z | 2020-12-14T18:08:08Z | 2020-12-14T18:08:08Z | CONTRIBUTOR | null | 0 | {
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link: https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/DPQMQH | {
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"Hi, thanks for reporting! This line should be replaced with \r\n```python\r\ndataset = dataset.map(lambda examples: tokenizer(examples[\"text\"], return_tensors=\"np\"), batched=True)\r\n```\r\nfor it to work (the `return_tensors` part inside the `tokenizer` call).",
"Can I work on this?",
"Fixed in https://gi... | 2022-10-10T10:23:53Z | 2022-10-10T17:51:15Z | 2022-10-10T17:51:14Z | CONTRIBUTOR | null | null | null | ## Describe the bug
In the "Process text data" tutorial, [`map` has `return_tensors` as kwarg](https://huggingface.co/docs/datasets/main/en/nlp_process#map). It does not seem to appear in the [function documentation](https://huggingface.co/docs/datasets/main/en/package_reference/main_classes#datasets.Dataset.map), nor to work.
## Steps to reproduce the bug
MWE:
```python
from transformers import AutoTokenizer
tokenizer = AutoTokenizer.from_pretrained("bert-base-cased")
from datasets import load_dataset
dataset = load_dataset("lhoestq/demo1", split="train")
dataset = dataset.map(lambda examples: tokenizer(examples["review"]), batched=True, return_tensors="pt")
```
## Expected results
return_tensors to be a valid kwarg :smiley:
## Actual results
```python
>> TypeError: map() got an unexpected keyword argument 'return_tensors'
```
## Environment info
- `datasets` version: 2.3.2
- Platform: Linux-5.14.0-1052-oem-x86_64-with-glibc2.29
- Python version: 3.8.10
- PyArrow version: 8.0.0
- Pandas version: 1.4.3
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"Hi ! You're completely right, this must be mentioned in the dataset card.\r\nIf you're interesting in contributing, feel free to open a pull request to mention this in the `trivia_qa` dataset card in the \"Licensing Information\" section at https://github.com/huggingface/datasets/blob/master/datasets/trivia_qa/REA... | 2021-11-23T08:00:15Z | 2021-11-29T11:24:21Z | 2021-11-29T11:24:21Z | NONE | null | null | null | ## Describe the bug
TriviaQA Webpage at http://nlp.cs.washington.edu/triviaqa/ says they do not own the copyright to the data. However, Huggingface datasets at https://huggingface.co/datasets/trivia_qa mentions that the dataset is released under Apache License
Is the License Information on HuggingFace correct? | {
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"Hi @thomas-happify, please note that the preview may take some time before rendering the data.\r\n\r\nI've seen it is already working.\r\n\r\nI close this issue. Please feel free to reopen it if the problem arises again."
] | 2022-02-01T16:23:57Z | 2022-02-09T08:00:37Z | 2022-02-09T08:00:37Z | NONE | null | null | null | ## Dataset viewer issue for '*happifyhealth/twitter_pnn*'
**Link:** *[link to the dataset viewer page](https://huggingface.co/datasets/happifyhealth/twitter_pnn)*
I used
```
dataset.push_to_hub("happifyhealth/twitter_pnn")
```
but the preview is not working.
Am I the one who added this dataset ? Yes
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"_The documentation is not available anymore as the PR was closed or merged._"
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Fix #4815. | {
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"Yes, the dataset viewer is based on `datasets`, and the following does not work:\r\n\r\n```\r\n>>> from datasets import get_dataset_split_names\r\n>>> get_dataset_split_names('timit_asr')\r\nDownloading builder script: 7.48kB [00:00, 6.69MB/s]\r\nTraceback (most recent call last):\r\n File \"/home/slesage/hf/data... | 2022-08-26T07:12:05Z | 2022-10-03T12:40:28Z | 2022-10-03T12:40:27Z | NONE | null | null | null | ### Link
_No response_
### Description
_No response_
### Owner
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