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One thing I noticed while writing this up is that, while this metric was made specifically to be better than BLEU at the sentence level instead of the corpus level, the current implementation only allows the calculation of the corpus-level statistic. I think changing this would be a good thing to put on the to do list for the future. | {
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} | The COMET metric has been broken for a while since big breaking changes happened. We did not catch them in the CI because the slow test mocks the download_model function that was changed.
This PR fixes the metric, updates the download_model mock and updates the doctest. | {
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When loading the reddit_tifu dataset, it throws the exception "Checksums didn't match for dataset source files"
## Steps to reproduce the bug
```python
import datasets
from datasets import load_dataset
print(datasets.__version__)
# load_dataset('billsum')
load_dataset('reddit_tifu', 'short')
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.17.0
- Platform: mac os
- Python version: Python 3.7.6
- PyArrow version: 3.0.0
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When loading the `billsum` dataset, it throws the exception "Checksums didn't match for dataset source files"
```
File "virtualenv_projects/codex/lib/python3.7/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://drive.google.com/uc?export=download&id=1g89WgFHMRbr4QrvA0ngh26PY081Nv3lx']
```
## Steps to reproduce the bug
```python
import datasets
from datasets import load_dataset
print(datasets.__version__)
load_dataset('billsum')
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.17.0
- Platform: mac os
- Python version: Python 3.7.6
- PyArrow version: 3.0.0
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] | closed | false | null | [] | null | [] | 2022-03-16T11:17:47Z | 2022-03-19T04:41:32Z | 2022-03-19T04:41:32Z | CONTRIBUTOR | null | null | null | ## Describe the bug
The source links of v2.0.0 docs are broken:
For exmaple, clicking the source button of this [class](https://huggingface.co/docs/datasets/v2.0.0/en/package_reference/main_classes#datasets.ClassLabel) will direct users to `https://github.com/huggingface/datasets/blob/v2.0.0/src/datasets/features/features.py#L747`
here, the `v2.0.0` should be `2.0.0`.
## Steps to reproduce the bug
```python
# Sample code to reproduce the bug
```
## Expected results
Redirecting to this link: `https://github.com/huggingface/datasets/blob/2.0.0/src/datasets/features/features.py#L747`
## Actual results
Described above.
## Environment info
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- `datasets` version:
- Platform:
- Python version:
- PyArrow version:
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] | null | [] | 2022-03-16T10:32:03Z | 2022-03-22T07:09:23Z | 2022-03-21T14:50:47Z | NONE | null | null | null | Hi,
I'm working with the github-code dataset. First of all, thank you for creating this amazing dataset!
I've noticed that two languages are missing from the dataset: TypeScript and Scala.
Looks like they're also omitted from the query you used to get the original code.
Are there any plans to add them in the future?
Thanks! | {
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- de
- en
- fr
- frr
- it
- simple
These pre-processed data can be accessed, e.g.:
```python
ds = load_dataset("wikipedia", "20220301.frr", split="train")
```
The next step will be to offer the pre-processed data for many other languages, but when loading using "wikimedia/wikipedia": https://huggingface.co/datasets/wikimedia/wikipedia | {
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} | This PR documents the `align_labels_with_mapping` function to ensure predicted labels are aligned with the dataset, or to assign a different mapping of labels to ids (requested by @mariosasko π ).
For this specific code sample, the current dataset has a `mixed` label that the original [dataset](https://huggingface.co/datasets/poem_sentiment#data-fields) didn't. Is there a way to remove this label so it is completely aligned with the original dataset mappings? Otherwise, I'll just leave it as it is. | {
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} | Creating a README for IndicGLUE
cc @mcmillanmajora for fact checking in terms of languages (also, are there any limitations of the dataset or eval metric that I'm not aware of?) | {
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] | null | [] | 2022-03-15T18:59:26Z | 2022-03-16T09:55:09Z | 2022-03-16T09:54:06Z | NONE | null | null | null | ## Describe the bug
Load a local "dataset" composed of two csv files twice.
## Steps to reproduce the bug
Put the two joined files in a repository named "Data".
Then in python:
import datasets as ds
ds.load_dataset('Data', data_files = {'file1.csv', 'file2.csv'})
## Expected results
Should give something like (because files have only one data row):
Title, clicks
Truc et astuce, 123
Machin, 12
## Actual results
Gives
Title, clicks
Truc et astuce, 123
Machin, 12
Truc et astuce, 123
Machin, 12
## Environment info
[file1.csv](https://github.com/huggingface/datasets/files/8256322/file1.csv)
[file2.csv](https://github.com/huggingface/datasets/files/8256323/file2.csv)
- `datasets` version: 2.0.0
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- Python version: 3.8.12
- PyArrow version: 7.0.0
- Pandas version: 1.4.1 | {
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] | null | [] | 2022-03-15T18:10:42Z | 2022-03-17T08:37:24Z | 2022-03-17T08:37:24Z | NONE | null | null | null | ## Describe the bug
The frugal score returns a really verbose output with warnings that can be easily changed.
## Steps to reproduce the bug
```python
# Sample code to reproduce the bug
from datasets.load import load_metric
frugal = load_metric("frugalscore")
frugal.compute(predictions=["Do you like spinachis"], references=["Do you like spinach"])
```
## Expected results
A clear and concise description of the expected results.
```
{'scores': [0.9946]}
```
## Actual results
Specify the actual results or traceback.
```
PyTorch: setting up devices
The default value for the training argument `--report_to` will change in v5 (from all installed integrations to none). In v5, you will need to use `--report_to all` to get the same behavior as now. You should start updating your code and make this info disappear :-).
100%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 1/1 [00:00<00:00, 864.09ba/s]
Using amp half precision backend
The following columns in the test set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: sentence2, sentence1. If sentence2, sentence1 are not expected by `BertForSequenceClassification.forward`, you can safely ignore this message.
***** Running Prediction *****
Num examples = 1
Batch size = 64
100%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 1/1 [00:00<00:00, 4644.85it/s]
{'scores': [0.9946]}
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.17.0
- Platform: Linux-5.13.0-30-generic-x86_64-with-glibc2.29
- Python version: 3.8.10
- PyArrow version: 7.0.0
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https://api.github.com/repos/huggingface/datasets/issues/3927 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3927/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3927/comments | https://api.github.com/repos/huggingface/datasets/issues/3927/events | https://github.com/huggingface/datasets/pull/3927 | 1,170,016,465 | PR_kwDODunzps40ewN2 | 3,927 | Update main readme | {
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} | The main readme was still focused on text datasets - I extended it by mentioning that we also support image and audio datasets | {
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} | Currently the `main_classes` documentation has a wrong index. I believe this comes from issues in the examples of the Translation feature types
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} | In general we recommend adding the new dataset under a username or organization in the Hugging Face Hub at [hf.co/datasets](hf.co/datasets), but users can still add a dataset on github in some cases.
I added a paragraph in the documentation to explain in which cases it can make more sense to open a PR on github:
- when you need the dataset to be reviewed
- when you need long-term maintenance from the HF team
- when thereβs no clear org name / namespace that you can put the dataset under | {
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https://api.github.com/repos/huggingface/datasets/issues/3923 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3923/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3923/comments | https://api.github.com/repos/huggingface/datasets/issues/3923/events | https://github.com/huggingface/datasets/pull/3923 | 1,169,773,869 | PR_kwDODunzps40d9YU | 3,923 | Add methods to IterableDatasetDict | {
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} | Following the new methods added in #3826 and https://github.com/huggingface/datasets/pull/3862 I added several methods to IterableDatasetDict:
- map
- filter
- shuffle
- with_format
- cast
- cast_column
- remove_columns
- rename_column
- rename_columns
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https://api.github.com/repos/huggingface/datasets/issues/3921 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3921/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3921/comments | https://api.github.com/repos/huggingface/datasets/issues/3921/events | https://github.com/huggingface/datasets/pull/3921 | 1,169,749,338 | PR_kwDODunzps40d4Mk | 3,921 | Fix NonMatchingChecksumError in CRD3 dataset | {
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https://api.github.com/repos/huggingface/datasets/issues/3920 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3920/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3920/comments | https://api.github.com/repos/huggingface/datasets/issues/3920/events | https://github.com/huggingface/datasets/issues/3920 | 1,169,532,807 | I_kwDODunzps5FtaeH | 3,920 | 'datasets.features' is not a package | {
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python 3.9
os: ubuntu 20.04
In conda environment
torch installed by
```/env/bin/pip install torch==1.9.0+cu111 torchvision==0.10.0+cu111 torchaudio==0.9.0 -f https://download.pytorch.org/whl/torch_stable.html```
datasets package is installed by
```
/env/bin/pip install datasets==1.8.0
```
During runing the code I have this error
```
[6]<stderr>: File "/home/arij/Memory-transformer-with-hierarchical-attention_MLM/env/lib/python3.9/site-packages/torch/serialization.py", line 875, in find_class
[6]<stderr>: return super().find_class(mod_name, name)
[6]<stderr>:ModuleNotFoundError: No module named 'datasets.features.features'; 'datasets.features' is not a package
```
precisely this error appears when
torch.load('data_file.pt')
```
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/arij/Memory-transformer-with-hierarchical-attention_MLM/env/lib/python3.9/site-packages/torch/serialization.py", line 607, in load
return _load(opened_zipfile, map_location, pickle_module, **pickle_load_args)
File "/home/arij/Memory-transformer-with-hierarchical-attention_MLM/env/lib/python3.9/site-packages/torch/serialization.py", line 882, in _load
result = unpickler.load()
File "/home/arij/Memory-transformer-with-hierarchical-attention_MLM/env/lib/python3.9/site-packages/torch/serialization.py", line 875, in find_class
return super().find_class(mod_name, name)
ModuleNotFoundError: No module named 'datasets.features.features'; 'datasets.features' is not a package
```
Why I am getting this error?
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https://api.github.com/repos/huggingface/datasets/issues/3919 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3919/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3919/comments | https://api.github.com/repos/huggingface/datasets/issues/3919/events | https://github.com/huggingface/datasets/issues/3919 | 1,169,497,210 | I_kwDODunzps5FtRx6 | 3,919 | AttributeError: 'DatasetDict' object has no attribute 'features' | {
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] | closed | false | null | [] | null | [] | 2022-03-15T10:46:59Z | 2022-03-17T04:16:14Z | 2022-03-17T04:16:14Z | NONE | null | null | null | ## Describe the bug
Receiving the error when trying to check for Dataset features
## Steps to reproduce the bug
from datasets import Dataset
dataset = Dataset.from_pandas(df[['id', 'words', 'bboxes', 'ner_tags', 'image_path']])
dataset.features
## Expected results
A clear and concise description of the expected results.
## Actual results
Getting the following errror
AttributeError: 'DatasetDict' object has no attribute 'features'
## Environment info
Copy-and-paste the text below in your GitHub issue.
- `datasets` version: 1.18.4
- Platform: Linux-4.14.252-131.483.amzn1.x86_64-x86_64-with-glibc2.9
- Python version: 3.6.13
- PyArrow version: 6.0.1
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] | closed | false | null | [] | null | [] | 2022-03-15T08:53:45Z | 2022-03-16T15:36:58Z | 2022-03-15T14:01:25Z | NONE | null | null | null | ## Describe the bug
Can't load the dataset
## Steps to reproduce the bug
```python
# Sample code to reproduce the bug
```
from datasets import load_dataset
dataset = load_dataset('multi_news')
dataset_2=load_dataset("reddit_tifu", "long")
## Actual results
raise NonMatchingChecksumError(error_msg + str(bad_urls))
datasets.utils.info_utils.NonMatchingChecksumError: Checksums didn't match for dataset source files:
['https://drive.google.com/uc?export=download&id=1ffWfITKFMJeqjT8loC8aiCLRNJpc_XnF']
## Environment info
- `datasets` version: 1.18.4
- Platform: macOS-10.16-x86_64-i386-64bit
- Python version: 3.8.0
- PyArrow version: 6.0.1
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} | I still have a hesitation regarding the format of inputs -- whether it's a list or a list of lists? -- hopefully @lhoestq will be able to clarify.
Also tagging @yjernite for the Limitations section. Happy to hear your thoughts! | {
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} | Adding a metric card template, based on ideas and edits from @sashavor and I, as well as from comments from @lhoestq and others (thank you!).
All feedback is welcome, but am especially curious about feedback in terms of:
- things that should be included but aren't
- things that are included but should be changed or removed
- the instructions I included, and whether they should be added to, clarified, or deleted altogether | {
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} | This PR updates the jobs for all doc-building related things by using the templates introduced on `doc-builder`. By putting those once there, we make sure every repo gets the latest fixes on the doc-building github actions :-)
Note: all libraries must share the same docker image for those doc-building jobs. For now, all the one used (`huggingface/transformers-doc-builder`) contains all extra steps of the datasets install for docbuling (mainly libsndfile) but if in the future some additional steps are necessary on top of `pip install -e .[dev]`, this docker image will need to be updated with the extra deps. | {
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Close https://github.com/huggingface/datasets/issues/3847 | {
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} | This PR adds a register function for `pandas`. It allows to directly push `DataFrame` objects to the hub and in return loading datasets on the hub from `DataFrame`. The motivation for this integration is to enable the vast number of `pandas` users to be able to easily push `DataFrames` to the hub.
Here is an example:
```python
import pandas as pd
from datasets import register_pandas
register_pandas()
# push to hub
df = pd.DataFrame.from_dict({"test": [1,2,3]})
df.push_to_hub("my_test")
# load from hub
df_retrieved = pd.DataFrame.load_from_hub("lvwerra/my_test")
```
It follows a similar philosophy as the `tqdm` [integration](https://github.com/tqdm/tqdm#pandas-integration). Also see [this issue](https://github.com/pandas-dev/pandas/issues/46000) on the `pandas` repository.
This is just a rough draft of what such integration could look like but I would like appreciate some feedback on this: is this something you would like to add the library and is this the way to go? cc @lhoestq @albertvillanova @julien-c | {
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https://api.github.com/repos/huggingface/datasets/issues/3911 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3911/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3911/comments | https://api.github.com/repos/huggingface/datasets/issues/3911/events | https://github.com/huggingface/datasets/pull/3911 | 1,168,652,374 | PR_kwDODunzps40aQHz | 3,911 | Create README.md for CER metric | {
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} | Initial proposal for a CER metric card
cc @patrickvonplaten - wdyt this time around? :smile: | {
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https://api.github.com/repos/huggingface/datasets/issues/3910 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3910/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3910/comments | https://api.github.com/repos/huggingface/datasets/issues/3910/events | https://github.com/huggingface/datasets/pull/3910 | 1,168,579,694 | PR_kwDODunzps40aAiX | 3,910 | Fix text loader to split only on universal newlines | {
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} | Currently, `text` loader breaks on a superset of universal newlines, which also contains Unicode line boundaries. See: https://docs.python.org/3/library/stdtypes.html#str.splitlines
However, the expected behavior is to get the lines splitted only on universal newlines: "\n", "\r\n" and "\r".
See: oscar-corpus/corpus#18
Fix #3729. | {
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https://api.github.com/repos/huggingface/datasets/issues/3909 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3909/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3909/comments | https://api.github.com/repos/huggingface/datasets/issues/3909/events | https://github.com/huggingface/datasets/issues/3909 | 1,168,578,058 | I_kwDODunzps5FpxYK | 3,909 | Error loading file audio when downloading the Common Voice dataset directly from the Hub | {
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] | open | false | null | [] | null | [] | 2022-03-14T15:53:50Z | 2022-04-05T16:36:58Z | null | NONE | null | null | null | ## Describe the bug
When loading the Common_Voice dataset, by downloading it directly from the Hugging Face hub, some files can not be opened.
## Steps to reproduce the bug
```python
import torch
import torchaudio
from datasets import load_dataset, load_metric
from transformers import Wav2Vec2ForCTC, Wav2Vec2Processor
import re
test_dataset = load_dataset("common_voice", "it", split="test")
#test_dataset = load_dataset('csv', data_files = {'test': '/workspace/Dataset/Common_Voice/cv-corpus80/it/test.csv'})
wer = load_metric("wer")
processor = Wav2Vec2Processor.from_pretrained("joorock12/wav2vec2-large-xlsr-italian")
model = Wav2Vec2ForCTC.from_pretrained("joorock12/wav2vec2-large-xlsr-italian")
model.to("cuda")
chars_to_ignore_regex = '[\,\?\.\!\-\;\:\"\β\'\οΏ½]'
resampler = torchaudio.transforms.Resample(48_000, 16_000)
```
## Expected results
The common voice dataset downloaded and correctly loaded whit the use of the hugging face datasets library.
## Actual results
The error is:
```python
0ex [00:00, ?ex/s]
---------------------------------------------------------------------------
RuntimeError Traceback (most recent call last)
<ipython-input-48-ef87f4129e6e> in <module>
7 return batch
8
----> 9 test_dataset = test_dataset.map(speech_file_to_array_fn)
/opt/conda/lib/python3.8/site-packages/datasets/arrow_dataset.py in map(self, function, with_indices, with_rank, input_columns, batched, batch_size, drop_last_batch, remove_columns, keep_in_memory, load_from_cache_file, cache_file_name, writer_batch_size, features, disable_nullable, fn_kwargs, num_proc, suffix_template, new_fingerprint, desc)
2107
2108 if num_proc is None or num_proc == 1:
-> 2109 return self._map_single(
2110 function=function,
2111 with_indices=with_indices,
/opt/conda/lib/python3.8/site-packages/datasets/arrow_dataset.py in wrapper(*args, **kwargs)
516 self: "Dataset" = kwargs.pop("self")
517 # apply actual function
--> 518 out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs)
519 datasets: List["Dataset"] = list(out.values()) if isinstance(out, dict) else [out]
520 for dataset in datasets:
/opt/conda/lib/python3.8/site-packages/datasets/arrow_dataset.py in wrapper(*args, **kwargs)
483 }
484 # apply actual function
--> 485 out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs)
486 datasets: List["Dataset"] = list(out.values()) if isinstance(out, dict) else [out]
487 # re-apply format to the output
/opt/conda/lib/python3.8/site-packages/datasets/fingerprint.py in wrapper(*args, **kwargs)
411 # Call actual function
412
--> 413 out = func(self, *args, **kwargs)
414
415 # Update fingerprint of in-place transforms + update in-place history of transforms
/opt/conda/lib/python3.8/site-packages/datasets/arrow_dataset.py in _map_single(self, function, with_indices, with_rank, input_columns, batched, batch_size, drop_last_batch, remove_columns, keep_in_memory, load_from_cache_file, cache_file_name, writer_batch_size, features, disable_nullable, fn_kwargs, new_fingerprint, rank, offset, disable_tqdm, desc, cache_only)
2465 if not batched:
2466 for i, example in enumerate(pbar):
-> 2467 example = apply_function_on_filtered_inputs(example, i, offset=offset)
2468 if update_data:
2469 if i == 0:
/opt/conda/lib/python3.8/site-packages/datasets/arrow_dataset.py in apply_function_on_filtered_inputs(inputs, indices, check_same_num_examples, offset)
2372 if with_rank:
2373 additional_args += (rank,)
-> 2374 processed_inputs = function(*fn_args, *additional_args, **fn_kwargs)
2375 if update_data is None:
2376 # Check if the function returns updated examples
/opt/conda/lib/python3.8/site-packages/datasets/arrow_dataset.py in decorated(item, *args, **kwargs)
2067 )
2068 # Use the LazyDict internally, while mapping the function
-> 2069 result = f(decorated_item, *args, **kwargs)
2070 # Return a standard dict
2071 return result.data if isinstance(result, LazyDict) else result
<ipython-input-48-ef87f4129e6e> in speech_file_to_array_fn(batch)
3 def speech_file_to_array_fn(batch):
4 batch["sentence"] = re.sub(chars_to_ignore_regex, '', batch["sentence"]).lower()
----> 5 speech_array, sampling_rate = torchaudio.load(batch["path"])
6 batch["speech"] = resampler(speech_array).squeeze().numpy()
7 return batch
/opt/conda/lib/python3.8/site-packages/torchaudio/backend/sox_io_backend.py in load(filepath, frame_offset, num_frames, normalize, channels_first, format)
150 filepath, frame_offset, num_frames, normalize, channels_first, format)
151 filepath = os.fspath(filepath)
--> 152 return torch.ops.torchaudio.sox_io_load_audio_file(
153 filepath, frame_offset, num_frames, normalize, channels_first, format)
154
RuntimeError: Error loading audio file: failed to open file common_voice_it_17415776.mp3 ```
## Environment info
- `datasets` version: 1.18.4
- Platform: Linux-5.4.0-x86_64-with-glibc2.10
- Python version: 3.8.5
- PyArrow version: 7.0.0 | {
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https://api.github.com/repos/huggingface/datasets/issues/3908 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3908/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3908/comments | https://api.github.com/repos/huggingface/datasets/issues/3908/events | https://github.com/huggingface/datasets/pull/3908 | 1,168,576,963 | PR_kwDODunzps40Z_9F | 3,908 | Update README.md for SQuAD v2 metric | {
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https://api.github.com/repos/huggingface/datasets/issues/3907 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3907/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3907/comments | https://api.github.com/repos/huggingface/datasets/issues/3907/events | https://github.com/huggingface/datasets/pull/3907 | 1,168,575,998 | PR_kwDODunzps40Z_vd | 3,907 | Update README.md for SQuAD metric | {
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https://api.github.com/repos/huggingface/datasets/issues/3906 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3906/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3906/comments | https://api.github.com/repos/huggingface/datasets/issues/3906/events | https://github.com/huggingface/datasets/issues/3906 | 1,168,496,328 | I_kwDODunzps5FpdbI | 3,906 | NonMatchingChecksumError on Spider dataset | {
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] | closed | false | null | [] | null | [] | 2022-03-14T14:54:53Z | 2022-03-15T07:09:51Z | 2022-03-15T07:09:51Z | NONE | null | null | null | ## Describe the bug
Failure to generate dataset ```spider``` because of checksums error for dataset source files.
## Steps to reproduce the bug
```
from datasets import load_dataset
spider = load_dataset("spider")
```
## Expected results
Checksums should match for files from url ['https://drive.google.com/uc?export=download&id=1_AckYkinAnhqmRQtGsQgUKAnTHxxX5J0']
## Actual results
```
>>> load_dataset("spider")
load_dataset("spider")
Downloading and preparing dataset spider/spider (download: 95.12 MiB, generated: 5.17 MiB, post-processed: Unknown size, total: 100.29 MiB) to /home/user/.cache/huggingface/datasets/spider/spider/1.0.0/79778ebea87c59b19411f1eb3eda317e9dd5f7788a556d837ef25c3ae6e5e8b7...
Traceback (most recent call last):
File "/home/user/py3_env/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-5-d4cb54197348>", line 1, in <module>
load_dataset("spider")
File "/home/user/py3_env/lib/python3.8/site-packages/datasets/load.py", line 1702, in load_dataset
builder_instance.download_and_prepare(
File "/home/user/py3_env/lib/python3.8/site-packages/datasets/builder.py", line 594, in download_and_prepare
self._download_and_prepare(
File "/home/user/py3_env/lib/python3.8/site-packages/datasets/builder.py", line 665, in _download_and_prepare
verify_checksums(
File "/home/user/py3_env/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://drive.google.com/uc?export=download&id=1_AckYkinAnhqmRQtGsQgUKAnTHxxX5J0']
```
## Environment info
datasets version: 1.18.3
Platform: Ubuntu 20 LTS
Python version: 3.8.10
PyArrow version: 6.0.1
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} | Add Perplexity metric card
Note that it is currently still missing the citation, but I plan to add it later today. | {
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] | null | [] | 2022-03-13T23:46:15Z | 2022-12-17T11:30:17Z | 2022-03-17T08:21:32Z | NONE | null | null | null | ## Describe the bug
[CONLL2003](https://huggingface.co/datasets/conll2003) Dataset can no longer reach 'https://data.deepai.org/conll2003.zip'
## Steps to reproduce the bug
```python
from datasets import load_dataset
datasets = load_dataset("conll2003")
```
## Expected results
Download the conll2003 dataset.
## Actual results
Error: `ConnectionError: Couldn't reach https://data.deepai.org/conll2003.zip (error 502)`
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https://api.github.com/repos/huggingface/datasets/issues/3903 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3903/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3903/comments | https://api.github.com/repos/huggingface/datasets/issues/3903/events | https://github.com/huggingface/datasets/pull/3903 | 1,167,521,627 | PR_kwDODunzps40WnkI | 3,903 | Add Biwi Kinect Head Pose dataset. | {
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} | This PR adds the Biwi Kinect Head Pose dataset.
Dataset Request : Add Biwi Kinect Head Pose Database [#3822](https://github.com/huggingface/datasets/issues/3822)
The Biwi Kinect Head Pose Database is acquired with the Microsoft Kinect sensor, a structured IR light device.It contains 15K images of 20 people with 6 females and 14 males where 4 people were recorded twice.
For each frame, there is :
- a depth image, (.bin file)
- a corresponding rgb image (both 640x480 pixels),
- annotation ( present inside a .txt file)
The ground truth is the 3D location of the head and its rotation.
The dataset structure is as follows :
```
- 01.obj
- 01
- frame_00003_depth.bin
- frame_00003_pose.txt
- frame_00003_rgb.png
.
.
.
- 02.obj
- 02
- frame_00003_depth.bin
- frame_00003_pose.txt
- frame_00003_rgb.png
.
.
.
```
Preview of frame_00003_pose.txt :
```
0.988397 0.0731349 0.133128
-0.0441539 0.976945 -0.208876
-0.145334 0.200575 0.968838
126.665 40.4515 876.198
```
I have used the following dataset features :
```
features=datasets.Features(
{
"person_id": datasets.Value("string"),
"frame_number": datasets.Value("string"),
"depth_image": datasets.Value("string"),
"rgb_image": datasets.Image(),
"3D_head_center": datasets.Array2D(shape=(3, 3), dtype="float"),
"3D_head_rotation": datasets.Value("float"),
}
```
I am giving the path to the depth_image here.
I need some inputs for the following :
1. For each person, the dataset has the following additional information :
```
For each sequence, the corresponding .obj file represents a head template deformed to match the neutral face of that specific person. [*.obj file]
In each folder, two .cal files contain calibration information for the depth and the color camera, e.g., the intrinsic camera matrix of the depth camera and the global rotation and translation to the rgb camera.
```
Wanted to know how we can represent these features ?
2. For _generate_examples , do I parse the directories and fetch the required information ? This would mean reading the .txt file to obtain the "3D_head_center" and "3D_head_rotation" details. We could precompute the features information and have a metadata file and use the metadata file to yield information in _generate_examples ? Wanted your thoughts for the best approach for this ?
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] | null | [] | 2022-03-12T21:22:03Z | 2022-03-22T07:10:42Z | 2022-03-22T07:10:41Z | NONE | null | null | null | ## Describe the bug
Unable to import datasets
## Steps to reproduce the bug
```python
from datasets import Dataset, DatasetDict
```
## Expected results
The import works without errors
## Actual results
```
AttributeError Traceback (most recent call last)
<ipython-input-37-c8cfcbe62127> in <module>
11 # from tqdm import tqdm
12 # import torch
---> 13 from datasets import Dataset
14 # from transformers import Trainer, TrainingArguments, AutoModel, AutoTokenizer, AutoModelForMaskedLM, DataCollatorForLanguageModeling
15 # from sentence_transformers import SentenceTransformer
~/.local/lib/python3.8/site-packages/datasets/__init__.py in <module>
31 )
32
---> 33 from .arrow_dataset import Dataset, concatenate_datasets
34 from .arrow_reader import ArrowReader, ReadInstruction
35 from .arrow_writer import ArrowWriter
~/.local/lib/python3.8/site-packages/datasets/arrow_dataset.py in <module>
46 )
47
---> 48 import fsspec
49 import numpy as np
50 import pandas as pd
~/.local/lib/python3.8/site-packages/fsspec/__init__.py in <module>
10 from . import _version, caching
11 from .callbacks import Callback
---> 12 from .core import get_fs_token_paths, open, open_files, open_local
13 from .exceptions import FSTimeoutError
14 from .mapping import FSMap, get_mapper
~/.local/lib/python3.8/site-packages/fsspec/core.py in <module>
16 caches,
17 )
---> 18 from .compression import compr
19 from .registry import filesystem, get_filesystem_class
20 from .utils import (
~/.local/lib/python3.8/site-packages/fsspec/compression.py in <module>
68
69
---> 70 register_compression("zip", unzip, "zip")
71 register_compression("bz2", BZ2File, "bz2")
72
~/.local/lib/python3.8/site-packages/fsspec/compression.py in register_compression(name, callback, extensions, force)
44
45 for ext in extensions:
---> 46 if ext in fsspec.utils.compressions and not force:
47 raise ValueError(
48 "Duplicate compression file extension: %s (%s)" % (ext, name)
AttributeError: partially initialized module 'fsspec' has no attribute 'utils' (most likely due to a circular import)
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.18.4
- Platform: Jupyter notebook
- Python version: 3.8.10
- PyArrow version: 7.0.0
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**Link:** *[IndicParaphrase](https://huggingface.co/datasets/ai4bharat/IndicParaphrase/viewer/hi/validation)*
*The preview of the dataset doesn't come up.
The error on the console is:
Status code: 400
Exception: FileNotFoundError
Message: [Errno 2] No such file or directory: '/home/hf/datasets-preview-backend/hi_IndicParaphrase_v1.0.tar'*
Am I the one who added this dataset ? Yes
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https://api.github.com/repos/huggingface/datasets/issues/3900 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3900/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3900/comments | https://api.github.com/repos/huggingface/datasets/issues/3900/events | https://github.com/huggingface/datasets/pull/3900 | 1,167,224,903 | PR_kwDODunzps40VxRh | 3,900 | Add MetaShift dataset | {
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} | This PR adds the MetaShift dataset.
Dataset Request : Add MetaShift dataset [#3813](https://github.com/huggingface/datasets/issues/3813)
@lhoestq As discussed,
- I have copied the preprocessing script and modified it as required to not create new directories and folders and instead yield the images.
- I do the preprocessing in _split_generators to get the required data which is then passed to _generate_examples.
- Beyond the generated MetaShift dataset, the original preprocess script also generates the meta-graphs for each class, I have currently not included this part. [ Ref : [Link](https://github.com/Weixin-Liang/MetaShift#generate-full-metashift) ]
- There is a Bonus section, the authors share. I have currently not included this part. [ Ref : [Link](https://github.com/Weixin-Liang/MetaShift#bonus-generate-the-metashift-attributes-dataset-subsets-defined-by-subject-attributes) ]
- I had a basic test script which downloaded the dataset and tested the basic functionality. Things seems fine.
For real data, I performed the following test :
```
RUN_SLOW=1 pytest tests/test_dataset_common.py::LocalDatasetTest::test_load_real_dataset_metashift
============================================== test session starts ===============================================
platform linux -- Python 3.7.11, pytest-7.0.1, pluggy-1.0.0
rootdir: ./datasets
plugins: hydra-core-1.1.1, datadir-1.3.1, forked-1.4.0, xdist-2.5.0
collected 1 item
tests/test_dataset_common.py . [100%]
========================================= 1 passed in 4821.25s (1:20:21) =========================================
```
- I couldn't get the dummy dataset. Need some inputs here.
Error as follows :
```
Using custom data configuration default
Dataset metashift with config None seems to already open files in the method `_split_generators(...)`. You might consider to instead only open files in the method `_generate_examples(...)` instead. If this is not possible the dummy data has to be created with less guidance. Make sure you create the file dummy_data/full-candidate-subsets.pkl.
for split in generator_splits:
UnboundLocalError: local variable 'generator_splits' referenced before assignment
```
To-Do :
- [x] Currently I am using the default _SELECTED_CLASSES. I need to use config option here as suggested
- [x] Complete fields in the Dataset Card.
- [x] Tagging the dataset using the Datasets Tagging app.
Need your help and suggestions for improvement. Thank you
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https://api.github.com/repos/huggingface/datasets/issues/3899 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3899/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3899/comments | https://api.github.com/repos/huggingface/datasets/issues/3899/events | https://github.com/huggingface/datasets/pull/3899 | 1,166,931,812 | PR_kwDODunzps40UzR3 | 3,899 | Add exact match metric | {
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} | Adding the exact match metric and its metric card.
Note: Some of the tests have failed, but I wanted to make a PR anyway so that the rest of the code can be reviewed if anyone has time. I'll look into + work on fixing the failed tests when I'm back online after the weekend | {
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} | Proposing a draft WER metric card, @lhoestq I'm not very certain about "Values from popular papers" -- I don't know ASR very well, what do you think of the examples I found? | {
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https://api.github.com/repos/huggingface/datasets/issues/3897 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3897/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3897/comments | https://api.github.com/repos/huggingface/datasets/issues/3897/events | https://github.com/huggingface/datasets/pull/3897 | 1,166,715,104 | PR_kwDODunzps40UJH4 | 3,897 | Align tqdm control/cache control with Transformers | {
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* aligns the `tqdm` logic with Transformers (follows https://github.com/huggingface/transformers/pull/15167) by moving the code to `utils/logging.py`, adding `enable_progres_bar`/`disable_progres_bar` and removing `set_progress_bar_enabled` (a note for @lhoestq: I'm not adding `logging.tqdm` to the public namespace in this PR to avoid the situation where `from datasets import *; tqdm` would overshadow the standard `tqdm`
* aligns the cache control with the new `tqdm` logic by adding `enable_caching`/`disable_caching` to the public namespace and deprecating `set_caching_enabled` (not fully removing it because it's used more often than `set_progress_bar_enabled` and has a dedicated example in the old docs)
Fix #3586 | {
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https://api.github.com/repos/huggingface/datasets/issues/3896 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3896/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3896/comments | https://api.github.com/repos/huggingface/datasets/issues/3896/events | https://github.com/huggingface/datasets/issues/3896 | 1,166,628,270 | I_kwDODunzps5FiVWu | 3,896 | Missing google file for `multi_news` dataset | {
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{
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"default": false,
"description": "Related to the dataset viewer on huggingface.co",
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**Link:** https://huggingface.co/datasets/multi_news
```
Server error
Status code: 400
Exception: FileNotFoundError
Message: https://drive.google.com/uc?export=download&id=1vRY2wM6rlOZrf9exGTm5pXj5ExlVwJ0C/multi-news-original/train.src
```
Am I the one who added this dataset ? No
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https://api.github.com/repos/huggingface/datasets/issues/3895 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3895/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3895/comments | https://api.github.com/repos/huggingface/datasets/issues/3895/events | https://github.com/huggingface/datasets/pull/3895 | 1,166,619,182 | PR_kwDODunzps40T1C8 | 3,895 | Fix code examples indentation | {
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cc @mariosasko | {
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We can discuss later to make them optional for datasets in this repository as well | {
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This PR makes sure it will always use master for the dev doc (until you decide to switchto main) | {
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} | Previous PR:
- #3796
introduced a side effect: `datasets-cli test` generates `dataset_infos.json` with `None` checksum values.
See:
- #3805
This PR introduces a way for `datasets-cli test` to force to record infos, even if `verify_infos=False`
Close #3848.
CC: @craffel | {
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} | Replace the old URLs with the Hub [URLs](https://huggingface.co/datasets/beans/tree/main/data).
Also reported by @stevhliu.
Fix #3889 | {
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The beans dataset is unavailable to download.
## Steps to reproduce the bug
```python
from datasets import load_dataset
ds = load_dataset('beans')
```
## Expected results
The dataset would be downloaded with no issue.
## Actual results
```
ConnectionError: Couldn't reach https://storage.googleapis.com/ibeans/train.zip (error 403)
```
[It looks like the billing of this project has been disabled because it is associated with a delinquent account.](https://storage.googleapis.com/ibeans/train.zip )
## Environment info
Google Colab
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] | null | [] | 2022-03-10T16:19:12Z | 2022-11-29T11:39:24Z | null | MEMBER | null | null | null | Right now, an IterableDataset (e.g. when streaming a dataset) doesn't require to know the list of columns it contains, nor their types: `my_iterable_dataset.features` may be `None`
However it's often interesting to know the column types and types. This helps knowing what's inside your dataset without having to manually check a few examples, and this is useful to prepare a processing pipeline or to train models.
Here are a few cases that lead to `features` being `None`:
1. when loading a dataset with `load_dataset` on CSV, JSON Lines, etc. files: type inference is only done when iterating over the dataset
2. when calling `map`, because we don't know in advance what's the output of the user's function passed to `map`
3. when calling `rename_columns`, `remove_columns`, etc. because they rely on `map`
Things we can consider, for each point above:
1.a infer the type automatically from the first samples on the dataset using prefetching, when the dataset builder doesn't provide the `features`
2.a allow the user to specify the `features` as an argument to `map` (this would be consistent with the non-streaming API)
2.b prefetch the first output value to infer the type
3.a don't rely on `map` directly and reuse the previous `features` and rename/remove the corresponding ones
The thing is that prefetching can take a few seconds, while the operations above are instantaneous since no data are downloaded. Therefore I'm not sure whether this solution may be worth it. Maybe prefetching could also be done when explicitly asked by the user
cc @mariosasko @albertvillanova | {
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} | This PR adds the following improvements to the `imagefolder` dataset:
* skip the extract step for image files (as discussed in https://github.com/huggingface/datasets/pull/2830#discussion_r816817919)
* option to drop labels by setting `drop_labels=True` (useful for image pretraining cc @NielsRogge). This is faster than loading a dataset and removing the `label` column because we don't need to iterate over the files to infer class labels. | {
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- Implements a retry function
- Retries HfApi call inside `push_to_hub` when 504 error. To be agreed:
- max_retries = 2 (at 0.5 and 1 seconds)
Fix #3872. | {
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] | null | [] | 2022-03-10T02:28:27Z | 2022-03-10T09:03:39Z | 2022-03-10T09:03:39Z | NONE | null | null | null | ## Describe the bug
Using the metric Meteor with nltk == 3.6.4 gives a TypeError:
TypeError: descriptor 'lower' for 'str' objects doesn't apply to a 'list' object
## Steps to reproduce the bug
```python
import datasets
metric = datasets.load_metric("meteor")
predictions = ["hello world"]
references = ["hello world"]
metric.compute(predictions=predictions, references=references)
```
## Expected results
TypeError: descriptor 'lower' for 'str' objects doesn't apply to a 'list' object
I think this TypeError exists because input sentences are tokenized into lists of tokens and the str.lower() is applied to this list of tokens.
## Actual results
No error but a meteor score
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.18.3
- Platform: linux
- Python version: 3.8.12
- PyArrow version: 7.0.0
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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 π 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` π₯². Working with @mariosasko on this! | {
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```
load_dataset("imagefolder", data_dir="./my-dataset")
```
`https://raw.githubusercontent.com/huggingface/datasets/master/datasets/imagefolder/imagefolder.py` missing
```
---------------------------------------------------------------------------
FileNotFoundError Traceback (most recent call last)
/tmp/ipykernel_33/1648737256.py in <module>
----> 1 load_dataset("imagefolder", data_dir="./my-dataset")
/opt/conda/lib/python3.7/site-packages/datasets/load.py in load_dataset(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, ignore_verifications, keep_in_memory, save_infos, revision, use_auth_token, task, streaming, script_version, **config_kwargs)
1684 revision=revision,
1685 use_auth_token=use_auth_token,
-> 1686 **config_kwargs,
1687 )
1688
/opt/conda/lib/python3.7/site-packages/datasets/load.py in load_dataset_builder(path, name, data_dir, data_files, cache_dir, features, download_config, download_mode, revision, use_auth_token, script_version, **config_kwargs)
1511 download_config.use_auth_token = use_auth_token
1512 dataset_module = dataset_module_factory(
-> 1513 path, revision=revision, download_config=download_config, download_mode=download_mode, data_files=data_files
1514 )
1515
/opt/conda/lib/python3.7/site-packages/datasets/load.py in dataset_module_factory(path, revision, download_config, download_mode, force_local_path, dynamic_modules_path, data_files, **download_kwargs)
1200 f"Couldn't find a dataset script at {relative_to_absolute_path(combined_path)} or any data file in the same directory. "
1201 f"Couldn't find '{path}' on the Hugging Face Hub either: {type(e1).__name__}: {e1}"
-> 1202 ) from None
1203 raise e1 from None
1204 else:
FileNotFoundError: Couldn't find a dataset script at /kaggle/working/imagefolder/imagefolder.py or any data file in the same directory. Couldn't find 'imagefolder' on the Hugging Face Hub either: FileNotFoundError: Couldn't find file at https://raw.githubusercontent.com/huggingface/datasets/master/datasets/imagefolder/imagefolder.py
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/3880 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3880/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3880/comments | https://api.github.com/repos/huggingface/datasets/issues/3880/events | https://github.com/huggingface/datasets/pull/3880 | 1,164,406,008 | PR_kwDODunzps40MjM3 | 3,880 | Change the framework switches to the new syntax | {
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- have paragraphs of text be framework-specific instead of just code samples
- have support for Flax code samples if you want.
This should be merged after https://github.com/huggingface/doc-builder/pull/63 and https://github.com/huggingface/doc-builder/pull/130 | {
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} | It seems like 12 new examples have been added to the `cats_vs_dogs`. This PR updates the size in the card and the info file to avoid a verification error (reported by @stevhliu). | {
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] | open | false | null | [] | null | [] | 2022-03-09T16:12:25Z | 2022-03-09T16:33:42Z | null | NONE | null | null | null | **Is your feature request related to a problem? Please describe.**
Align to DCAT metadata to describe datasets
**Describe the solution you'd like**
Reuse terms and structure from DCAT in the metadata file, ideally generate a json-ld file dcat compliant
**Describe alternatives you've considered**
**Additional context**
DCAT is a W3C standard extended in Europe with DCAT-AP, an example is data.europa.eu publishing datasets metadata in DCAT-AP
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Before the fix, it was set to `bool` (default to `False`).
Also set properly its default value in all public functions. | {
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} | This is an attempt to make the user-facing `datasets`' submodule namespace cleaner:
In particular, this PR does the following:
* removes the unused `zip_nested` and `flatten_nest_dict` and their accompanying tests
* removes `pyarrow` from the top-level namespace
* properly uses `__all__` and the `from <module> import *` syntax to avoid importing the `<module>`'s submodules
* cleans up the `utils` namespace
* moves the `temp_seed` context manage from `datasets/utils/file_utils.py` to `datasets/utils/py_utils.py` | {
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} | Created a new pull request to resolve unrelated changes in PR caused due to rebasing.
Ref Older PR : [#3845](https://github.com/huggingface/datasets/pull/3845)
Feature request here : Add support for continuous metrics (RMSE, MAE) [#3608](https://github.com/huggingface/datasets/issues/3608) | {
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} | Proposal for a metrics card structure (with an example based on the SQuAD metric).
@thomwolf @lhoestq @douwekiela @lewtun -- feel free to comment on structure or content (it's an initial draft, so I realize there's stuff missing!). | {
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} | [] | closed | false | null | [] | null | [] | 2022-03-09T12:03:37Z | 2022-03-15T16:19:50Z | 2022-03-15T16:19:50Z | NONE | null | null | null | I am trying to push a large dataset(450000+) records with the help of `push_to_hub()`
While pushing, it gives some error like this.
```
Traceback (most recent call last):
File "data_split_speech.py", line 159, in <module>
data_new_2.push_to_hub("user-name/dataset-name",private=True)
File "/opt/conda/lib/python3.8/site-packages/datasets/dataset_dict.py", line 951, in push_to_hub
repo_id, split, uploaded_size, dataset_nbytes = self[split]._push_parquet_shards_to_hub(
File "/opt/conda/lib/python3.8/site-packages/datasets/arrow_dataset.py", line 3556, in _push_parquet_shards_to_hub
api.upload_file(
File "/opt/conda/lib/python3.8/site-packages/huggingface_hub/hf_api.py", line 1017, in upload_file
raise err
File "/opt/conda/lib/python3.8/site-packages/huggingface_hub/hf_api.py", line 1008, in upload_file
r.raise_for_status()
File "/opt/conda/lib/python3.8/site-packages/requests/models.py", line 953, in raise_for_status
raise HTTPError(http_error_msg, response=self)
requests.exceptions.HTTPError: 504 Server Error: Gateway Time-out for url: https://huggingface.co/api/datasets/user-name/dataset-name/upload/main/data/train2-00041-of-00064.parquet
```
Can anyone help me to resolve this issue.
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] | open | false | null | [] | null | [] | 2022-03-09T03:06:18Z | 2022-03-09T09:04:09Z | null | NONE | null | null | null | Let's make Hugging Face Datasets the central hub for datasets in Portuguese :)
**Motivation**. Datasets are currently quite scattered and an open-source central point such as the Hugging Face Hub would be ideal to support the growth of the Portuguese speaking community.
What are some datasets in Portuguese worth integrating into the Hugging Face hub?
Special thanks to @augusnunes for his collaboration on identifying the first ones:
- [NILC - USP](http://www.nilc.icmc.usp.br/nilc/index.php/tools-and-resources).
Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
cc @osanseviero
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https://api.github.com/repos/huggingface/datasets/issues/3863 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3863/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3863/comments | https://api.github.com/repos/huggingface/datasets/issues/3863/events | https://github.com/huggingface/datasets/pull/3863 | 1,162,802,857 | PR_kwDODunzps40HP-A | 3,863 | Update code blocks | {
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} | Following https://github.com/huggingface/datasets/pull/3860#issuecomment-1061756712 and https://github.com/huggingface/datasets/pull/3690 we need to update the code blocks to use markdown instead of sphinx | {
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https://api.github.com/repos/huggingface/datasets/issues/3862 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3862/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3862/comments | https://api.github.com/repos/huggingface/datasets/issues/3862/events | https://github.com/huggingface/datasets/pull/3862 | 1,162,753,733 | PR_kwDODunzps40HFht | 3,862 | Manipulate columns on IterableDataset (rename columns, cast, etc.) | {
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} | I added:
- add_column
- cast
- rename_column
- rename_columns
related to https://github.com/huggingface/datasets/issues/3444
TODO:
- [x] docs
- [x] tests | {
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https://api.github.com/repos/huggingface/datasets/issues/3861 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3861/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3861/comments | https://api.github.com/repos/huggingface/datasets/issues/3861/events | https://github.com/huggingface/datasets/issues/3861 | 1,162,702,044 | I_kwDODunzps5FTWzc | 3,861 | big_patent cased version | {
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] | open | false | null | [] | null | [] | 2022-03-08T14:08:55Z | 2022-03-08T14:09:55Z | null | NONE | null | null | null | Hi! I am interested in working with the big_patent dataset.
In Tensorflow, there are a number of versions of the dataset:
- 1.0.0 : lower cased tokenized words
- 2.0.0 : Update to use cased raw strings
- 2.1.2 (default): Fix update to cased raw strings.
The version in the huggingface `datasets` library is the 1.0.0. I would be very interested in using the 2.1.2 cased version (used more, recently, for example in the Pegasus paper), but it does not seem to be supported (I tried using the `revision` parameter in `load_datasets`). Is there a way to already load it, or would it be possible to add that version? | {
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https://api.github.com/repos/huggingface/datasets/issues/3860 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3860/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3860/comments | https://api.github.com/repos/huggingface/datasets/issues/3860/events | https://github.com/huggingface/datasets/pull/3860 | 1,162,623,329 | PR_kwDODunzps40GpzZ | 3,860 | Small doc fixes | {
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https://api.github.com/repos/huggingface/datasets/issues/3859 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3859/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3859/comments | https://api.github.com/repos/huggingface/datasets/issues/3859/events | https://github.com/huggingface/datasets/issues/3859 | 1,162,559,333 | I_kwDODunzps5FSz9l | 3,859 | Unable to dowload big_patent (FileNotFoundError) | {
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] | null | [] | 2022-03-08T11:47:12Z | 2022-03-08T13:04:09Z | 2022-03-08T13:04:04Z | NONE | null | null | null | ## Describe the bug
I am trying to download some splits of the big_patent dataset, using the following code:
`ds = load_dataset("big_patent", "g", split="validation", download_mode="force_redownload")
`
However, this leads to a FileNotFoundError.
FileNotFoundError Traceback (most recent call last)
[<ipython-input-3-8d8a745706a9>](https://localhost:8080/#) in <module>()
1 from datasets import load_dataset
----> 2 ds = load_dataset("big_patent", "g", split="validation", download_mode="force_redownload")
8 frames
[/usr/local/lib/python3.7/dist-packages/datasets/load.py](https://localhost:8080/#) in load_dataset(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, ignore_verifications, keep_in_memory, save_infos, revision, use_auth_token, task, streaming, script_version, **config_kwargs)
1705 ignore_verifications=ignore_verifications,
1706 try_from_hf_gcs=try_from_hf_gcs,
-> 1707 use_auth_token=use_auth_token,
1708 )
1709
[/usr/local/lib/python3.7/dist-packages/datasets/builder.py](https://localhost:8080/#) in download_and_prepare(self, download_config, download_mode, ignore_verifications, try_from_hf_gcs, dl_manager, base_path, use_auth_token, **download_and_prepare_kwargs)
593 if not downloaded_from_gcs:
594 self._download_and_prepare(
--> 595 dl_manager=dl_manager, verify_infos=verify_infos, **download_and_prepare_kwargs
596 )
597 # Sync info
[/usr/local/lib/python3.7/dist-packages/datasets/builder.py](https://localhost:8080/#) in _download_and_prepare(self, dl_manager, verify_infos, **prepare_split_kwargs)
659 split_dict = SplitDict(dataset_name=self.name)
660 split_generators_kwargs = self._make_split_generators_kwargs(prepare_split_kwargs)
--> 661 split_generators = self._split_generators(dl_manager, **split_generators_kwargs)
662
663 # Checksums verification
[/root/.cache/huggingface/modules/datasets_modules/datasets/big_patent/bdefa7c0b39fba8bba1c6331b70b738e30d63c8ad4567f983ce315a5fef6131c/big_patent.py](https://localhost:8080/#) in _split_generators(self, dl_manager)
123 split_types = ["train", "val", "test"]
124 extract_paths = dl_manager.extract(
--> 125 {k: os.path.join(dl_path, "bigPatentData", k + ".tar.gz") for k in split_types}
126 )
127 extract_paths = {k: os.path.join(extract_paths[k], k) for k in split_types}
[/usr/local/lib/python3.7/dist-packages/datasets/utils/download_manager.py](https://localhost:8080/#) in extract(self, path_or_paths, num_proc)
282 download_config.extract_compressed_file = True
283 extracted_paths = map_nested(
--> 284 partial(cached_path, download_config=download_config), path_or_paths, num_proc=num_proc, disable_tqdm=False
285 )
286 path_or_paths = NestedDataStructure(path_or_paths)
[/usr/local/lib/python3.7/dist-packages/datasets/utils/py_utils.py](https://localhost:8080/#) in map_nested(function, data_struct, dict_only, map_list, map_tuple, map_numpy, num_proc, types, disable_tqdm)
260 mapped = [
261 _single_map_nested((function, obj, types, None, True))
--> 262 for obj in utils.tqdm(iterable, disable=disable_tqdm)
263 ]
264 else:
[/usr/local/lib/python3.7/dist-packages/datasets/utils/py_utils.py](https://localhost:8080/#) in <listcomp>(.0)
260 mapped = [
261 _single_map_nested((function, obj, types, None, True))
--> 262 for obj in utils.tqdm(iterable, disable=disable_tqdm)
263 ]
264 else:
[/usr/local/lib/python3.7/dist-packages/datasets/utils/py_utils.py](https://localhost:8080/#) in _single_map_nested(args)
194 # Singleton first to spare some computation
195 if not isinstance(data_struct, dict) and not isinstance(data_struct, types):
--> 196 return function(data_struct)
197
198 # Reduce logging to keep things readable in multiprocessing with tqdm
[/usr/local/lib/python3.7/dist-packages/datasets/utils/file_utils.py](https://localhost:8080/#) in cached_path(url_or_filename, download_config, **download_kwargs)
314 elif is_local_path(url_or_filename):
315 # File, but it doesn't exist.
--> 316 raise FileNotFoundError(f"Local file {url_or_filename} doesn't exist")
317 else:
318 # Something unknown
FileNotFoundError: Local file /root/.cache/huggingface/datasets/downloads/extracted/ad068abb3e11f9f2f5440b62e37eb2b03ee515df9de1637c55cd1793b68668b2/bigPatentData/train.tar.gz doesn't exist
I have tried this in a number of machines, including on Colab, so I think this is not environment dependent.
How do I load the bigPatent dataset? | {
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After discussion with @lhoestq, just want to mention here that `glob.glob(...)` should always be used in combination with `sorted(...)` to make sure the list of files returned by `glob.glob(...)` doesn't change depending on the OS system.
There are currently multiple datasets that use `glob.glob()` without making use of `sorted(...)` even the streaming download manager (if I'm not mistaken):
https://github.com/huggingface/datasets/blob/c14bfeb4af89da14f870de5ddaa584b08aa08eeb/src/datasets/utils/streaming_download_manager.py#L483 | {
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https://api.github.com/repos/huggingface/datasets/issues/3856 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3856/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3856/comments | https://api.github.com/repos/huggingface/datasets/issues/3856/events | https://github.com/huggingface/datasets/pull/3856 | 1,162,522,034 | PR_kwDODunzps40GUSf | 3,856 | Fix push_to_hub with null images | {
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```python
import datasets
dataset_dict = { 'name': ['image001.jpg', 'image002.jpg'], 'image': ['cat.jpg', None] }
features = datasets.Features({
'name': datasets.Value('string'),
'image': datasets.Image(),
})
dataset = datasets.Dataset.from_dict(dataset_dict, features)
dataset.push_to_hub("username/dataset") # this line produces an error: 'NoneType' object is not subscriptable
```
I fixed this in this PR
TODO:
- [x] add a test | {
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] | null | [] | 2022-03-08T09:55:17Z | 2022-07-11T15:06:40Z | 2022-07-11T15:06:40Z | MEMBER | null | null | null | ## Describe the bug
A pretty common behavior of an interaction between the Hub and datasets is the following.
An organization adds a dataset in private mode and wants to load it afterward.
```python
from transformers import load_dataset
ds = load_dataset("NewT5/dummy_data", "dummy")
```
This command then fails with:
```bash
FileNotFoundError: Couldn't find a dataset script at /home/patrick/NewT5/dummy_data/dummy_data.py or any data file in the same directory. Couldn't find 'NewT5/dummy_data' on the Hugging Face Hub either: FileNotFoundError: Dataset 'NewT5/dummy_data' doesn't exist on the Hub
```
**even though** the user has access to the website `NewT5/dummy_data` since she/he is part of the org.
We need to improve the error message here similar to how @sgugger, @LysandreJik and @julien-c have done it for transformers IMO.
## Steps to reproduce the bug
E.g. execute the following code to see the different error messages between `transformes` and `datasets`.
1. Transformers
```python
from transformers import BertModel
BertModel.from_pretrained("NewT5/dummy_model")
```
The error message is clearer here - it gives:
```
OSError: patrickvonplaten/gpt2-xl is not a local folder and is not a valid model identifier listed on 'https://huggingface.co/models'
If this is a private repository, make sure to pass a token having permission to this repo with `use_auth_token` or log in with `huggingface-cli login` and pass `use_auth_token=True`.
```
Let's maybe do the same for datasets? The PR was introduced to `transformers` here:
https://github.com/huggingface/transformers/pull/15261
## Expected results
Better error message
## 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: 1.18.4.dev0
- Platform: Linux-5.15.15-76051515-generic-x86_64-with-glibc2.34
- Python version: 3.9.7
- PyArrow version: 6.0.1
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] | null | [] | 2022-03-08T09:40:52Z | 2022-03-09T08:13:33Z | 2022-03-09T08:13:33Z | NONE | null | null | null | training_data = load_dataset("common_voice", "en",split='train[:250]+validation[:250]')
testing_data = load_dataset("common_voice", "en", split="test[:200]")
I'm trying to load only 8% of the English common voice data with accent == "England English." Can somebody assist me with this?
**Typical Voice Accent Proportions:**
- 24% United States English
- 8% England English
- 5% India and South Asia (India, Pakistan, Sri Lanka)
- 3% Australian English
- 3% Canadian English
- 2% Scottish English
- 1% Irish English
- 1% Southern African (South Africa, Zimbabwe, Namibia)
- 1% New Zealand English
Can we replicate this for Age as well?
**Age proportions of the common voice:-**
- 24% 19 - 29
- 14% 30 - 39
- 10% 40 - 49
- 6% < 19
- 4% 50 - 59
- 4% 60 - 69
- 1% 70 β 79 | {
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"url": "https://api.github.com/repos/huggingface/datasets/pulls/3853"
} | # Introduction of the dataset
OntoNotes v5.0 is the final version of OntoNotes corpus, and is a large-scale, multi-genre,
multilingual corpus manually annotated with syntactic, semantic and discourse information.
This dataset is the version of OntoNotes v5.0 extended and used in the CoNLL-2012 shared task
, includes v4 train/dev and v9 test data for English/Chinese/Arabic and corrected version v12 train/dev/test data (English only).
This dataset is widely used in name entity recognition, coreference resolution, and semantic role labeling.
In dataset loading script, I modify and use the code of [AllenNLP/Ontonotes](https://docs.allennlp.org/models/main/models/common/ontonotes/#ontonotes) to read the special conll files while don't get extra package dependency.
# Some workarounds I did
1. task ids
I add tasks that I can't find anywhere `semantic-role-labeling`, `lemmatization`, and `word-sense-disambiguation` to the task category `structure-prediction`, because they are related to "syntax". I feel there is another good name for the task category since some tasks mentioned aren't related to structure, but I have no good idea.
2. `dl_manage.extract`
Since we'll get another zip after unzip the downloaded zip data, I have to use `dl_manager.extract` directly inside `_generate_examples`. But when testing dummy data, `dl_manager.extract` do nothing. So I make a conditional such that it manually extract data when testing dummy data.
# Help
Don't know how to fix the building doc error. | {
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https://api.github.com/repos/huggingface/datasets/issues/3852 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3852/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3852/comments | https://api.github.com/repos/huggingface/datasets/issues/3852/events | https://github.com/huggingface/datasets/pull/3852 | 1,162,252,337 | PR_kwDODunzps40Fb26 | 3,852 | Redundant add dataset information and dead link. | {
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} | [] | closed | false | null | [] | null | [] | 2022-03-08T05:57:05Z | 2022-03-08T16:54:36Z | 2022-03-08T16:54:36Z | CONTRIBUTOR | null | false | {
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"url": "https://api.github.com/repos/huggingface/datasets/pulls/3852"
} | > Alternatively, you can follow the steps to [add a dataset](https://huggingface.co/docs/datasets/add_dataset.html) and [share a dataset](https://huggingface.co/docs/datasets/share_dataset.html) in the documentation.
The "add a dataset link" gives 404 Error, and the share_dataset link has changed. I feel this information is redundant/deprecated now since we have a more detailed guide for "How to add a dataset?". | {
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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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] | closed | false | null | [] | null | [] | 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/3850 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3850/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3850/comments | https://api.github.com/repos/huggingface/datasets/issues/3850/events | https://github.com/huggingface/datasets/pull/3850 | 1,162,126,030 | PR_kwDODunzps40FBx9 | 3,850 | [feat] Add tqdm arguments | {
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} | [] | closed | false | null | [] | null | [] | 2022-03-08T01:53:25Z | 2022-12-16T05:34:07Z | 2022-12-16T05:34:07Z | NONE | null | false | {
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} | In this PR, tqdm arguments can be passed to the map() function and such, in order to be more flexible. | {
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https://api.github.com/repos/huggingface/datasets/issues/3849 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3849/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3849/comments | https://api.github.com/repos/huggingface/datasets/issues/3849/events | https://github.com/huggingface/datasets/pull/3849 | 1,162,091,075 | PR_kwDODunzps40E6sW | 3,849 | Add "Adversarial GLUE" dataset to datasets library | {
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} | [] | closed | false | null | [] | null | [] | 2022-03-08T00:47:11Z | 2022-03-28T11:17:14Z | 2022-03-28T11:12:04Z | CONTRIBUTOR | null | false | {
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} | Adds the Adversarial GLUE dataset: https://adversarialglue.github.io/
```python
>>> import datasets
>>> >>> datasets.load_dataset('adv_glue')
Using the latest cached version of the module from /home/jxm3/.cache/huggingface/modules/datasets_modules/datasets/adv_glue/26709a83facad2830d72d4419dd179c0be092f4ad3303ad0ebe815d0cdba5cb4 (last modified on Mon Mar 7 19:19:48 2022) since it couldn't be found locally at adv_glue., or remotely on the Hugging Face Hub.
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/jxm3/random/datasets/src/datasets/load.py", line 1657, in load_dataset
builder_instance = load_dataset_builder(
File "/home/jxm3/random/datasets/src/datasets/load.py", line 1510, in load_dataset_builder
builder_instance: DatasetBuilder = builder_cls(
File "/home/jxm3/random/datasets/src/datasets/builder.py", line 1021, in __init__
super().__init__(*args, **kwargs)
File "/home/jxm3/random/datasets/src/datasets/builder.py", line 258, in __init__
self.config, self.config_id = self._create_builder_config(
File "/home/jxm3/random/datasets/src/datasets/builder.py", line 337, in _create_builder_config
raise ValueError(
ValueError: Config name is missing.
Please pick one among the available configs: ['adv_sst2', 'adv_qqp', 'adv_mnli', 'adv_mnli_mismatched', 'adv_qnli', 'adv_rte']
Example of usage:
`load_dataset('adv_glue', 'adv_sst2')`
>>> datasets.load_dataset('adv_glue', 'adv_sst2')['validation'][0]
Reusing dataset adv_glue (/home/jxm3/.cache/huggingface/datasets/adv_glue/adv_sst2/1.0.0/3719a903f606f2c96654d87b421bc01114c37084057cdccae65cd7bc24b10933)
100%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 1/1 [00:00<00:00, 604.11it/s]
{'sentence': "it 's an uneven treat that bores fun at the democratic exercise while also examining its significance for those who take part .", 'label': 1, 'idx': 0}
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/3848 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3848/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3848/comments | https://api.github.com/repos/huggingface/datasets/issues/3848/events | https://github.com/huggingface/datasets/issues/3848 | 1,162,076,902 | I_kwDODunzps5FQ-Lm | 3,848 | NonMatchingChecksumError when checksum is None | {
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] | null | [] | 2022-03-08T00:24:12Z | 2022-03-15T14:37:26Z | 2022-03-15T12:28:23Z | CONTRIBUTOR | null | null | null | I ran into the following error when adding a new dataset:
```bash
expected_checksums = {'https://adversarialglue.github.io/dataset/dev.zip': {'checksum': None, 'num_bytes': 40662}}
recorded_checksums = {'https://adversarialglue.github.io/dataset/dev.zip': {'checksum': 'efb4cbd3aa4a87bfaffc310ae951981cc0a36c6c71c6425dd74e5b55f2f325c9', 'num_bytes': 40662}}
verification_name = 'dataset source files'
def verify_checksums(expected_checksums: Optional[dict], recorded_checksums: dict, verification_name=None):
if expected_checksums is None:
logger.info("Unable to verify checksums.")
return
if len(set(expected_checksums) - set(recorded_checksums)) > 0:
raise ExpectedMoreDownloadedFiles(str(set(expected_checksums) - set(recorded_checksums)))
if len(set(recorded_checksums) - set(expected_checksums)) > 0:
raise UnexpectedDownloadedFile(str(set(recorded_checksums) - set(expected_checksums)))
bad_urls = [url for url in expected_checksums if expected_checksums[url] != recorded_checksums[url]]
for_verification_name = " for " + verification_name if verification_name is not None else ""
if len(bad_urls) > 0:
error_msg = "Checksums didn't match" + for_verification_name + ":\n"
> raise NonMatchingChecksumError(error_msg + str(bad_urls))
E datasets.utils.info_utils.NonMatchingChecksumError: Checksums didn't match for dataset source files:
E ['https://adversarialglue.github.io/dataset/dev.zip']
src/datasets/utils/info_utils.py:40: NonMatchingChecksumError
```
## Expected results
The dataset downloads correctly, and there is no error.
## Actual results
Datasets library is looking for a checksum of None, and it gets a non-None checksum, and throws an error. This is clearly a bug. | {
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