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https://api.github.com/repos/huggingface/datasets/issues/3931
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1,170,097,208
PR_kwDODunzps40fBjx
3,931
Add align_labels_with_mapping docs
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[ "_The documentation is not available anymore as the PR was closed or merged._" ]
2022-03-15T19:24:57
2022-03-18T16:28:31
2022-03-18T16:24:33
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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 🎉 ). 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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Create README.md
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2022-03-15T19:16:59
2022-04-04T15:23:15
2022-04-04T15:17:28
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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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Load a local dataset twice
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[ "Hi @caush, thanks for reporting:\r\n\r\nIn order to load local CSV files, you can use our \"csv\" loading script: https://huggingface.co/docs/datasets/loading#csv\r\n```python\r\ndataset = load_dataset(\"csv\", data_files=[\"data/file1.csv\", \"data/file2.csv\"])\r\n```\r\nOR:\r\n```python\r\ndataset = load_datase...
2022-03-15T18:59:26
2022-03-16T09:55:09
2022-03-16T09:54:06
NONE
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## 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 - Platform: Linux-5.4.0-65-generic-x86_64-with-glibc2.10 - Python version: 3.8.12 - PyArrow version: 7.0.0 - Pandas version: 1.4.1
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3,928
Frugal score deprecations
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[ "Hi @Ierezell, thanks for reporting.\r\n\r\nI'm making a PR to suppress those logs from the terminal. " ]
2022-03-15T18:10:42
2022-03-17T08:37:24
2022-03-17T08:37:24
NONE
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## 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%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 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%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 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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Update main readme
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[ "_The documentation is not available anymore as the PR was closed or merged._", "What do you think @albertvillanova ?" ]
2022-03-15T18:09:59
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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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Doc maintenance
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3926). All of your documentation changes will be reflected on that endpoint." ]
2022-03-15T17:00:46
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This PR adds some minor maintenance to the docs. The main fix is properly linking to pages in the callouts because some of the links would just redirect to a non-existent section on the same page.
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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![image](https://user-images.githubusercontent.com/42851186/158429361-e19ce25b-c259-4ded-8473-075deafdbb96.png)\r\n\r\nany idea what could cause this ?", "Ok fixed :)" ]
2022-03-15T16:33:46
2022-03-22T13:49:11
2022-03-22T13:44:04
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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 ![image](https://user-images.githubusercontent.com/42851186/158426345-2ee1ceef-ddf3-4a6f-a93e-d1a8f38a44f5.png)
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1,169,805,813
PR_kwDODunzps40eED5
3,924
Document cases for github datasets
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3924). All of your documentation changes will be reflected on that endpoint.", "Yay!" ]
2022-03-15T15:10:10
2022-04-05T18:33:15
2022-03-15T15:41:23
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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 there’s no clear org name / namespace that you can put the dataset under
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PR_kwDODunzps40d9YU
3,923
Add methods to IterableDatasetDict
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3923). All of your documentation changes will be reflected on that endpoint.", "Is this feature stale or needs any help to it ? If so I can quickly send a PR. Thanks\r\n\r\nCC : @lhoestq, @albertvillanova ", "These features h...
2022-03-15T14:46:03
2022-07-06T15:40:20
2022-03-15T16:45:06
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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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1,169,761,293
PR_kwDODunzps40d6vm
3,922
Fix NonMatchingChecksumError in MultiWOZ 2.2 dataset
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3922). All of your documentation changes will be reflected on that endpoint.", "Unrelated CI test failure. This PR can be merged." ]
2022-03-15T14:36:28
2022-03-15T16:07:04
2022-03-15T16:07:03
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Fix #2957
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3,921
Fix NonMatchingChecksumError in CRD3 dataset
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3921). All of your documentation changes will be reflected on that endpoint.", "Unrelated test failure. This PR can be merged." ]
2022-03-15T14:27:14
2022-03-15T15:54:27
2022-03-15T15:54:26
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Fix #3051
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'datasets.features' is not a package
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[ "Hi @Arij-Aladel,\r\n\r\nYou are using a very old version of our library `datasets`: 1.8.0\r\nCurrent version is 2.0.0 (and the previous one was 1.18.4)\r\n\r\nPlease, try to update `datasets` library and check if the problem persists:\r\n```shell\r\n/env/bin/pip install -U datasets", "The problem I can no I have...
2022-03-15T11:14:23
2022-03-16T09:17:12
2022-03-16T09:17:12
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@albertvillanova 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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AttributeError: 'DatasetDict' object has no attribute 'features'
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[ "You are likely trying to get the `features` from a `DatasetDict`, a dictionary containing `Datasets`. You probably first want to index into a particular split from your `DatasetDict` i.e. `dataset['train'].features`. \r\n\r\nFor example \r\n\r\n```python \r\nds = load_dataset('mnist')\r\nds.features\r\n```\r\nRetu...
2022-03-15T10:46:59
2022-03-17T04:16:14
2022-03-17T04:16:14
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## 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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datasets.utils.info_utils.NonMatchingChecksumError: Checksums didn't match for dataset source files
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[ "Hi @willowdong! These issues were fixed on master. We will have a new release of `datasets` later today. In the meantime, you can avoid these issues by installing `datasets` from master as follows:\r\n```bash\r\npip install git+https://github.com/huggingface/datasets.git\r\n```", "You should force redownload:\r\...
2022-03-15T08:53:45
2022-03-16T15:36:58
2022-03-15T14:01:25
NONE
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## 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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Create README.md
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3917). All of your documentation changes will be reflected on that endpoint." ]
2022-03-14T21:08:10
2022-03-17T17:45:39
2022-03-17T17:45:39
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This follows the same structure as the GLUE metric card, hope that works for everyone :)
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3916). All of your documentation changes will be reflected on that endpoint." ]
2022-03-14T20:27:22
2022-03-15T17:06:57
2022-03-15T17:06:56
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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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Metric card template
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[ "_The documentation is not available anymore as the PR was closed or merged._", "Looks like a great start! I have a general comment and a few specific comments.\r\n\r\nMy general comment is I wonder if we need a post for this template and the data and model card templates (or a combined one?) explaining why this ...
2022-03-14T20:07:08
2022-05-04T10:44:09
2022-05-04T10:37:06
CONTRIBUTOR
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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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Use templates for doc-builidng jobs
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3914). All of your documentation changes will be reflected on that endpoint.", "You can ignore the CI failures btw, they're unrelated to this PR" ]
2022-03-14T18:53:06
2022-03-17T15:02:59
2022-03-17T15:02:58
CONTRIBUTOR
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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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Deterministic split order in DatasetDict.map
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3913). All of your documentation changes will be reflected on that endpoint.", "I'm surprised this is needed because the order of the `dict` keys is deterministic as of Python 3.6 (documented in 3.7). Is there a reproducer for ...
2022-03-14T17:58:37
2023-09-24T09:55:10
2022-03-15T10:45:15
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The order in which the splits are processed by `map` is not deterministic in `DatasetDict.map`. This can cause caching issues when the processing function is stateful and sensible to the order in which examples are processed Close https://github.com/huggingface/datasets/issues/3847
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add draft of registering function for pandas
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3912). All of your documentation changes will be reflected on that endpoint.", "That's cool ! Though I would expect such an integration to only require `huggingface_hub`, not the full `datasets` library. \r\n Indeed if users wa...
2022-03-14T17:54:29
2023-09-24T09:55:01
2023-01-24T12:57:10
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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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Create README.md for CER metric
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[ "_The documentation is not available anymore as the PR was closed or merged._" ]
2022-03-14T16:54:51
2022-03-17T17:49:40
2022-03-17T17:45:54
NONE
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Initial proposal for a CER metric card cc @patrickvonplaten - wdyt this time around? :smile:
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PR_kwDODunzps40aAiX
3,910
Fix text loader to split only on universal newlines
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3910). All of your documentation changes will be reflected on that endpoint.", "Looks like the test needs to be updated for windows ^^'", "I don't think this is the same issue as in https://github.com/oscar-corpus/corpus/issu...
2022-03-14T15:54:58
2022-03-15T16:16:11
2022-03-15T16:16:09
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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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I_kwDODunzps5FpxYK
3,909
Error loading file audio when downloading the Common Voice dataset directly from the Hub
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[ "Hi ! It could an issue with torchaudio, which version of torchaudio are you using ? Can you also try updating `datasets` to 2.0.0 and see if it works ?", "I _might_ have a similar issue. I'm trying to use the librispeech_asr dataset and read it with soundfile.\r\n\r\n```python\r\nfrom datasets import load_datase...
2022-03-14T15:53:50
2023-03-02T15:31:27
2023-03-02T15:31:26
NONE
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## 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 = '[\,\?\.\!\-\;\:\"\“\'\�]' 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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Update README.md for SQuAD v2 metric
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3908). All of your documentation changes will be reflected on that endpoint." ]
2022-03-14T15:53:10
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Putting "Values from popular papers" as a subsection of "Output values"
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Update README.md for SQuAD metric
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3907). All of your documentation changes will be reflected on that endpoint." ]
2022-03-14T15:52:31
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Putting "Values from popular papers" as a subsection of "Output values"
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NonMatchingChecksumError on Spider dataset
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[ "Hi @kolk, thanks for reporting.\r\n\r\nIndeed, Google Drive service recently changed their service and we had to add a fix to our library to cope with that change:\r\n- #3787 \r\n\r\nWe just made patch release last week: 1.18.4 https://github.com/huggingface/datasets/releases/tag/1.18.4\r\n\r\nPlease, feel free to...
2022-03-14T14:54:53
2022-03-15T07:09:51
2022-03-15T07:09:51
NONE
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## 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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Perplexity Metric Card
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3905). All of your documentation changes will be reflected on that endpoint.", "I'm wondering if we should add that perplexity can be used for analyzing datasets as well", "Otherwise, looks good! Good job, @emibaylor !" ]
2022-03-14T12:39:40
2022-03-16T19:38:56
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CONTRIBUTOR
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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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3,904
CONLL2003 Dataset not available
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[ "Thanks for reporting, @omarespejel.\r\n\r\nI'm sorry but I can't reproduce the issue: the loading of the dataset works perfecto for me and I can reach the data URL: https://data.deepai.org/conll2003.zip\r\n\r\nMight it be due to a temporary problem in the data owner site (https://data.deepai.org/) that is fixed no...
2022-03-13T23:46:15
2023-06-28T18:08:16
2022-03-17T08:21:32
NONE
null
null
null
## Describe the bug [CONLL2003](https://huggingface.co/datasets/conll2003) Dataset can no longer reach 'https://data.deepai.org/conll2003.zip' ![image](https://user-images.githubusercontent.com/4755430/158084483-ff83631c-5154-4823-892d-577bf1166db0.png) ## 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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1,167,521,627
PR_kwDODunzps40WnkI
3,903
Add Biwi Kinect Head Pose dataset.
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[ "_The documentation is not available anymore as the PR was closed or merged._", "Thanks for the detailed explanation of the structure!\r\n\r\n1. IMO it makes the most sense to yield one example for each person (so the total of 24 examples), so the features dict should be similar to this:\r\n \r\n ```python\r\n ...
2022-03-13T08:59:21
2022-05-31T17:02:19
2022-05-31T12:15:58
CONTRIBUTOR
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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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Can't import datasets: partially initialized module 'fsspec' has no attribute 'utils'
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[ "Update: `\"python3 -c \"from from datasets import Dataset, DatasetDict\"` works, but not if I import without the `python3 -c`", "Hi @arunasank, thanks for reporting.\r\n\r\nIt seems that this can be caused because you are using an old version of `fsspec`: the reason why it works if you run `python3` seems to be ...
2022-03-12T21:22:03
2023-02-09T14:53:49
2022-03-22T07:10:41
NONE
null
null
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## 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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1,167,339,773
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Dataset viewer issue for IndicParaphrase- the preview doesn't show
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[ "It seems to have been fixed:\r\n\r\n<img width=\"1534\" alt=\"Capture d’écran 2022-04-12 à 14 10 07\" src=\"https://user-images.githubusercontent.com/1676121/162959599-6b7fef7c-8411-4e03-8f00-90040a658079.png\">\r\n" ]
2022-03-12T16:56:05
2022-04-12T12:10:50
2022-04-12T12:10:49
NONE
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## Dataset viewer issue for '*IndicParaphrase*' **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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3,900
Add MetaShift dataset
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[ "_The documentation is not available anymore as the PR was closed or merged._", "@lhoestq Please could you review this when you get time. Thank you.", "Thanks a lot for your inputs @mariosasko .\r\n> Maybe we can add the generated meta-graphs to the card as images (with attributions)?\r\n\r\nYes. We can do this...
2022-03-12T08:44:18
2022-04-01T16:59:48
2022-04-01T15:16:30
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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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3,899
Add exact match metric
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[ "_The documentation is not available anymore as the PR was closed or merged._" ]
2022-03-11T22:21:40
2022-03-21T16:10:03
2022-03-21T16:05:35
CONTRIBUTOR
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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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3,898
Create README.md for WER metric
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3898). All of your documentation changes will be reflected on that endpoint.", "For ASR you can probably ping @patrickvonplaten ", "Ah only noticed now that ` # Values from popular papers` is from a template. @lhoestq @sashav...
2022-03-11T19:29:09
2022-03-15T17:05:00
2022-03-15T17:04:59
NONE
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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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3,897
Align tqdm control/cache control with Transformers
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3897). All of your documentation changes will be reflected on that endpoint." ]
2022-03-11T18:12:22
2022-03-14T15:01:10
2022-03-14T15:01:08
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This PR: * 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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Missing google file for `multi_news` dataset
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[ "reported by @abidlabs ", "related to https://github.com/huggingface/datasets/pull/3843?", "`datasets` 1.18.4 fixes the issue when you load the dataset with `load_dataset`.\r\n\r\nWhen loading in streaming mode, the fix is indeed on https://github.com/huggingface/datasets/pull/3843 which will be merged soon :)"...
2022-03-11T16:38:10
2022-03-15T12:30:23
2022-03-15T12:30:23
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## Dataset viewer issue for '*multi_news*' **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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Fix code examples indentation
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3895). All of your documentation changes will be reflected on that endpoint.", "Still not rendered properly: https://moon-ci-docs.huggingface.co/docs/datasets/pr_3895/en/package_reference/main_classes#datasets.Dataset.align_lab...
2022-03-11T16:29:04
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Some code examples are currently not rendered correctly. I think this is because they are over-indented cc @mariosasko
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[docs] make dummy data creation optional
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3894). All of your documentation changes will be reflected on that endpoint.", "The dev doc build rendering doesn't seem to be updated with my last commit for some reason", "Merging it anyway since I'd like to share this page...
2022-03-11T16:21:34
2022-03-11T17:27:56
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Related to #3507 : dummy data for datasets created on the Hugging Face Hub are optional. We can discuss later to make them optional for datasets in this repository as well
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Add default branch for doc building
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3893). All of your documentation changes will be reflected on that endpoint.", "Yes! And when we discovered on the Transformers side that this check fails on the GitHub actions, we added a config attribute to have a default. Se...
2022-03-11T15:24:27
2022-03-11T15:34:35
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Since other libraries use `main` as their default branch and it's now the standard default, you have to specify a different name in the doc config if you're using `master` like datasets (`doc-builder` tries to guess it, but in the job, we have weird checkout of merge commits so it doesn't always manage to get it right). This PR makes sure it will always use master for the dev doc (until you decide to switchto main)
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Fix CLI test checksums
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3892). All of your documentation changes will be reflected on that endpoint.", "Feel free to merge if it's good for you :)", "I've added a test @lhoestq. Once all green, I'll merge. ", "Last failing tests do not have nothin...
2022-03-11T10:04:04
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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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PR_kwDODunzps40QKIG
3,891
Fix race condition in doc build
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3891). All of your documentation changes will be reflected on that endpoint." ]
2022-03-10T17:17:10
2022-03-10T17:23:00
2022-03-10T17:17:30
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Following https://github.com/huggingface/datasets/runs/5499386744 it seems that race conditions that create issues when updating the doc. I took the same approach as in `transformers` to fix race conditions
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3,890
Update beans download urls
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3890). All of your documentation changes will be reflected on that endpoint.", "@albertvillanova Thanks for investigating and fixing that issue. I regenerated the `dataset_infos.json` file." ]
2022-03-10T17:16:16
2022-03-15T16:47:30
2022-03-15T15:26:48
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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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I_kwDODunzps5Fd3LT
3,889
Cannot load beans dataset (Couldn't reach the dataset)
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[ "Hi ! A pull request is open to fix the dataset, we'll release a patch soon with a new release of `datasets` :)" ]
2022-03-10T16:34:08
2022-03-15T15:26:47
2022-03-15T15:26:47
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## Describe the bug 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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IterableDataset columns and feature types
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[ "#self-assign", "@alvarobartt I've assigned you the issue since I'm not actively working on it.", "Cool thanks @mariosasko I'll try to fix it in the upcoming days, thanks!", "@lhoestq so in order to address what’s not completed in this issue, do you think it makes sense to add a param `features` to `IterableD...
2022-03-10T16:19:12
2022-11-29T11:39:24
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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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ImageFolder improvements
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3887). All of your documentation changes will be reflected on that endpoint." ]
2022-03-10T15:34:46
2022-03-11T15:06:11
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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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Retry HfApi call inside push_to_hub when 504 error
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3886). All of your documentation changes will be reflected on that endpoint.", "I made it more robust by increasing the wait time, and I also added some logs when a request is retried. Let me know if it's ok for you", "At the...
2022-03-10T13:24:40
2022-03-16T09:00:56
2022-03-15T16:19:50
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Ass suggested by @lhoestq in #3872, this PR: - 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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Fix some shuffle docs
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3885). All of your documentation changes will be reflected on that endpoint." ]
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Following #3842 some docs were still outdated (with `buffer_size` as the first argument)
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Fix bug in METEOR metric due to nltk version
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3884). All of your documentation changes will be reflected on that endpoint." ]
2022-03-10T08:44:20
2022-03-10T09:03:40
2022-03-10T09:03:39
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Fix #3883.
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I_kwDODunzps5Fa1m9
3,883
The metric Meteor doesn't work for nltk ==3.6.4
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[ "Hi @zhaowei-wang98, thanks for reporting.\r\n\r\nWe are fixing it... " ]
2022-03-10T02:28:27
2022-03-10T09:03:39
2022-03-10T09:03:39
NONE
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## 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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Image process doc
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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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How to use Image folder
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[ "Even this from docs throw same error\r\n```\r\ndataset = load_dataset(\"imagefolder\", data_files=\"https://download.microsoft.com/download/3/E/1/3E1C3F21-ECDB-4869-8368-6DEBA77B919F/kagglecatsanddogs_3367a.zip\", split=\"train\")\r\n\r\n```", "Hi @INF800,\r\n\r\nPlease note that the `imagefolder` feature enhanc...
2022-03-09T21:18:52
2022-03-11T08:45:52
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Ran this code ``` 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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PR_kwDODunzps40MjM3
3,880
Change the framework switches to the new syntax
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3880). All of your documentation changes will be reflected on that endpoint.", "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3880). All of your documentation changes will be reflected on...
2022-03-09T20:29:10
2022-03-15T14:13:28
2022-03-15T14:13:27
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This PR updates the syntax of the framework-specific code samples. With this new syntax, you'll be able to: - 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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1,164,311,612
PR_kwDODunzps40MP7f
3,879
SQuAD v2 metric: create README.md
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3879). All of your documentation changes will be reflected on that endpoint." ]
2022-03-09T18:47:56
2022-03-10T16:48:59
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Proposing SQuAD v2 metric card
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Update cats_vs_dogs size
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3878). All of your documentation changes will be reflected on that endpoint.", "Maybe `NonMatchingSplitsSizesError` errors should also tell the user to try using a more recent version of the dataset to get the fixes ?", "@lho...
2022-03-09T18:40:56
2022-09-30T08:47:43
2022-03-10T14:21:23
CONTRIBUTOR
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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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1,164,146,311
I_kwDODunzps5FY3aH
3,877
Align metadata to DCAT/DCAT-AP
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2022-03-09T16:12:25
2022-03-09T16:33:42
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**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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Fix download_mode in dataset_module_factory
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3876). All of your documentation changes will be reflected on that endpoint." ]
2022-03-09T14:54:33
2022-03-10T08:47:00
2022-03-10T08:46:59
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Fix `download_mode` value set in `dataset_module_factory`. 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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1,164,029,673
PR_kwDODunzps40LUuw
3,875
Module namespace cleanup for v2.0
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[ "will it solve https://github.com/huggingface/datasets-preview-backend/blob/4c542a74244045929615640ccbba5a902c344c5a/pyproject.toml#L85-L89?", "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3875). All of your documentation changes will be reflected on that endpoint.", "@s...
2022-03-09T14:43:07
2022-03-11T15:42:06
2022-03-11T15:42:05
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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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1,164,013,511
PR_kwDODunzps40LRYD
3,874
add MSE and MAE metrics - V2
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[ "@mariosasko New PR here. I'm not sure how to add you as a co-author here. Also I see flake8 tests are failing, any inputs on how to resolve this ?\r\nAlso, let me know if any other changes are required. Thank you.", "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3874). Al...
2022-03-09T14:30:16
2022-03-09T17:20:42
2022-03-09T17:18:20
CONTRIBUTOR
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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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1,163,961,578
PR_kwDODunzps40LGoV
3,873
Create SQuAD metric README.md
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3873). All of your documentation changes will be reflected on that endpoint.", "Oh one last thing I almost forgot, I think I would add a section \"Examples\" with examples of inputs and outputs and in particular: an example giv...
2022-03-09T13:47:08
2022-03-10T16:45:57
2022-03-10T16:45:57
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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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HTTP error 504 Server Error: Gateway Time-out
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[ "is pushing directly with git (and git-lfs) an option for you?", "I have installed git-lfs and doing this push with that\r\n", "yes but is there any way you could try pushing with `git` command line directly instead of `push_to_hub`?", "Okay. I didnt saved the dataset to my local machine. So, I processed the ...
2022-03-09T12:03:37
2022-03-15T16:19:50
2022-03-15T16:19:50
NONE
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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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1,163,714,113
PR_kwDODunzps40KRcM
3,871
add pandas to env command
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3871). All of your documentation changes will be reflected on that endpoint.", "Think failures are unrelated - feel free to merge whenever you want :-)" ]
2022-03-09T09:48:51
2022-03-09T11:21:38
2022-03-09T11:21:37
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Pandas is a required packages and used quite a bit. I don't see any downside with adding its version to the `datasets-cli env` command.
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3,870
Add wikitablequestions dataset
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[ "@lhoestq Would you mind reviewing it when you're available? Thanks!\r\n", "> Awesome thanks for adding this dataset ! :) The dataset script and dataset cards look pretty good\r\n> \r\n> It looks like your `dummy_data.zip` files are quite big though (>1MB each), do you think we can reduce their sizes ? This way t...
2022-03-09T08:27:43
2022-03-14T11:19:24
2022-03-14T11:16:19
CONTRIBUTOR
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3,869
Making the Hub the place for datasets in Portuguese
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[ "Hi @omarespejel! I think the philosophy for `datasets` issues is to create concrete issues with proposals to add a specific, individual dataset rather than umbrella issues for things such as datasets for a language, since we could end up with hundreds of issues (one per language). I see NILC - USP has many dataset...
2022-03-09T03:06:18
2022-03-09T09:04:09
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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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3,868
Ignore duplicate keys if `ignore_verifications=True`
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3868). All of your documentation changes will be reflected on that endpoint.", "Cool thanks ! Could you add a test please ?" ]
2022-03-08T17:14:56
2022-03-09T13:50:45
2022-03-09T13:50:44
CONTRIBUTOR
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Currently, it's impossible to generate a dataset if some keys from `_generate_examples` are duplicated. This PR allows skipping the check for duplicate keys if `ignore_verifications` is set to `True`.
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Update for the rename doc-builder -> hf-doc-utils
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[ "why utils? it's a builder no?", "~~@julien-c there was a vote 🙂 https://huggingface.slack.com/archives/C021H1P1HKR/p1646405136644739~~\r\n\r\noh I see you already commeented in the thread as well", "Thanks ! It looks all good to me (provided `hf-doc-utils` is the name we keep in the end). I'm fine with this n...
2022-03-08T16:58:25
2023-09-24T09:54:44
2022-03-08T17:30:45
CONTRIBUTOR
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This PR adapts the job to the upcoming change of name of `doc-builder`.
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Bring back imgs so that forsk dont get broken
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3866). All of your documentation changes will be reflected on that endpoint.", "I think we just need to keep `datasets_logo_name.jpg` and `course_banner.png` because they appear in the README.md of the forks of `datasets`. The ...
2022-03-08T16:01:31
2022-03-08T17:37:02
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Add logo img
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3865). All of your documentation changes will be reflected on that endpoint.", "Superceded by https://github.com/huggingface/datasets/pull/3866" ]
2022-03-08T15:50:59
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Update image dataset tags
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3864). All of your documentation changes will be reflected on that endpoint." ]
2022-03-08T15:36:32
2022-03-08T17:04:47
2022-03-08T17:04:46
CONTRIBUTOR
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Align the existing image datasets' tags with new tags introduced in #3800.
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Update code blocks
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3863). All of your documentation changes will be reflected on that endpoint." ]
2022-03-08T15:34:43
2022-03-09T16:45:30
2022-03-09T16:45:29
MEMBER
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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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3,862
Manipulate columns on IterableDataset (rename columns, cast, etc.)
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3862). All of your documentation changes will be reflected on that endpoint.", "> IIUC we check if columns are present/not present directly in the yielded examples and not in info.features because info.features can be None (aft...
2022-03-08T14:53:57
2022-03-10T16:40:22
2022-03-10T16:40:21
MEMBER
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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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1,162,702,044
I_kwDODunzps5FTWzc
3,861
big_patent cased version
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[ "To follow up on this: the cased and uncased versions actually contain different content, and the cased one is easier since it contains a Summary of the Invention in the input.\r\n\r\nSee the paper describing the issue here:\r\nhttps://aclanthology.org/2022.gem-1.34/", "Thanks for proposing the addition of the ca...
2022-03-08T14:08:55
2023-04-21T14:32:03
2023-04-21T14:32:03
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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1,162,623,329
PR_kwDODunzps40GpzZ
3,860
Small doc fixes
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3860). All of your documentation changes will be reflected on that endpoint.", "There are still some `.. code-block:: python` (e.g. see [this](https://huggingface.co/docs/datasets/master/en/package_reference/main_classes#datase...
2022-03-08T12:55:39
2022-03-08T17:37:13
2022-03-08T17:37:13
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1,162,559,333
I_kwDODunzps5FSz9l
3,859
Unable to dowload big_patent (FileNotFoundError)
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[ "Hi @slvcsl, thanks for reporting.\r\n\r\nYesterday we just made a patch release of our `datasets` library that fixes this issue: version 1.18.4.\r\nhttps://pypi.org/project/datasets/#history\r\n\r\nPlease, feel free to update `datasets` library to the latest version: \r\n```shell\r\npip install -U datasets\r\n```\...
2022-03-08T11:47:12
2022-03-08T13:04:09
2022-03-08T13:04:04
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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Udpate index.mdx margins
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3858). All of your documentation changes will be reflected on that endpoint." ]
2022-03-08T11:11:52
2022-03-08T12:57:57
2022-03-08T12:57:56
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1,162,525,353
I_kwDODunzps5FSrqp
3,857
Order of dataset changes due to glob.glob.
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[ "I agree using `glob.glob` alone is bad practice because it's not deterministic. Using `sorted` is a nice solution.\r\n\r\nNote that the `xglob` function you are referring to in the `streaming_download_manager.py` code just extends `glob.glob` for URLs - we don't change its behavior. That's why it has no `sorted()`...
2022-03-08T11:10:30
2022-03-14T11:08:22
null
MEMBER
null
null
null
## Describe the bug 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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1,162,522,034
PR_kwDODunzps40GUSf
3,856
Fix push_to_hub with null images
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3856). All of your documentation changes will be reflected on that endpoint." ]
2022-03-08T11:07:09
2022-03-08T15:22:17
2022-03-08T15:22:16
MEMBER
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This code currently raises an error because of the null image: ```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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1,162,448,589
I_kwDODunzps5FSY7N
3,855
Bad error message when loading private dataset
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[ "We raise the error “ FileNotFoundError: can’t find the dataset” mainly to follow best practice in security (otherwise users could be able to guess what private repositories users/orgs may have)\r\n\r\nWe can indeed reformulate this and add the \"If this is a private repository,...\" part !", "Resolved via https:...
2022-03-08T09:55:17
2022-07-11T15:06:40
2022-07-11T15:06:40
MEMBER
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## 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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1,162,434,199
I_kwDODunzps5FSVaX
3,854
load only England English dataset from common voice english dataset
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[ "Hi @amanjaiswal777,\r\n\r\nFirst note that the dataset you are trying to load is deprecated: it was the Common Voice dataset release as of Dec 2020.\r\n\r\nCurrently, Common Voice dataset releases are directly hosted on the Hub, under the Mozilla Foundation organization: https://huggingface.co/mozilla-foundation\r...
2022-03-08T09:40:52
2022-03-09T08:13:33
2022-03-09T08:13:33
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 – 79
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1,162,386,592
PR_kwDODunzps40F3uN
3,853
add ontonotes_conll dataset
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3853). All of your documentation changes will be reflected on that endpoint.", "The CI fail is unrelated to this dataset, merging :)" ]
2022-03-08T08:53:42
2022-03-15T10:48:02
2022-03-15T10:48:02
CONTRIBUTOR
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# 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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1,162,252,337
PR_kwDODunzps40Fb26
3,852
Redundant add dataset information and dead link.
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3852). All of your documentation changes will be reflected on that endpoint." ]
2022-03-08T05:57:05
2022-03-08T16:54:36
2022-03-08T16:54:36
CONTRIBUTOR
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> 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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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...
2022-03-08T02:16:04
2022-09-27T12:13:55
2022-03-08T11:20:06
NONE
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null
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## 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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1,162,126,030
PR_kwDODunzps40FBx9
3,850
[feat] Add tqdm arguments
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2022-03-08T01:53:25
2022-12-16T05:34:07
2022-12-16T05:34:07
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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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3,849
Add "Adversarial GLUE" dataset to datasets library
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[ "_The documentation is not available anymore as the PR was closed or merged._", "@lhoestq can you review when you have some time?", "Hi @lhoestq -- thanks so much for your review! I just added the stuff you requested to the README.md, including an example from the dataset, the table of contents, and lots of sec...
2022-03-08T00:47:11
2022-03-28T11:17:14
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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%|███████████████████████████████████████████████████████████████████████████████████████████████████████████| 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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NonMatchingChecksumError when checksum is None
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[ "Hi @jxmorris12, thanks for reporting.\r\n\r\nThe objective of `verify_checksums` is to check that both checksums are equal. Therefore if one is None and the other is non-None, they are not equal, and the function accordingly raises a NonMatchingChecksumError. That behavior is expected.\r\n\r\nThe question is: how ...
2022-03-08T00:24:12
2022-03-15T14:37:26
2022-03-15T12:28:23
CONTRIBUTOR
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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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Datasets' cache not re-used
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[ "<s>I think this is because the tokenizer is stateful and because the order in which the splits are processed is not deterministic. Because of that, the hash of the tokenizer may change for certain splits, which causes issues with caching.\r\n\r\nTo fix this we can try making the order of the splits deterministic f...
2022-03-07T19:55:15
2023-11-20T18:14:37
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## Describe the bug For most tokenizers I have tested (e.g. the RoBERTa tokenizer), the data preprocessing cache are not fully reused in the first few runs, although their `.arrow` cache files are in the cache directory. ## Steps to reproduce the bug Here is a reproducer. The GPT2 tokenizer works perfectly with caching, but not the RoBERTa tokenizer in this example. ```python from datasets import load_dataset from transformers import AutoTokenizer raw_datasets = load_dataset("wikitext", "wikitext-2-raw-v1") # tokenizer = AutoTokenizer.from_pretrained("gpt2") tokenizer = AutoTokenizer.from_pretrained("roberta-base") text_column_name = "text" column_names = raw_datasets["train"].column_names def tokenize_function(examples): return tokenizer(examples[text_column_name], return_special_tokens_mask=True) tokenized_datasets = raw_datasets.map( tokenize_function, batched=True, remove_columns=column_names, load_from_cache_file=True, desc="Running tokenizer on every text in dataset", ) ``` ## Expected results No tokenization would be required after the 1st run. Everything should be loaded from the cache. ## Actual results Tokenization for some subsets are repeated at the 2nd and 3rd run. Starting from the 4th run, everything are loaded from cache. ## Environment info <!-- You can run the command `datasets-cli env` and copy-and-paste its output below. --> - `datasets` version: 1.18.3 - Platform: Ubuntu 18.04.6 LTS - Python version: 3.6.9 - PyArrow version: 6.0.1
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Update faiss device docstring
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3846). All of your documentation changes will be reflected on that endpoint." ]
2022-03-07T19:06:59
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Following https://github.com/huggingface/datasets/pull/3721 I updated the docstring of the `device` argument of the FAISS related methods of `Dataset`
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add RMSE and MAE metrics.
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3845). All of your documentation changes will be reflected on that endpoint.", "@mariosasko I've reopened it here. Please suggest any changes if required. Thank you.", "Thanks for suggestions. :) I have added update the KWARG...
2022-03-07T17:53:24
2022-03-09T16:50:03
2022-03-09T16:50:03
CONTRIBUTOR
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This PR adds RMSE - Root Mean Squared Error and MAE - Mean Absolute Error to the metrics API. Both implementations are based on usage of sciket-learn. Feature request here : Add support for continuous metrics (RMSE, MAE) [#3608](https://github.com/huggingface/datasets/issues/3608) Please suggest any changes if required. Thank you.
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Add rmse and mae metrics.
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3844). All of your documentation changes will be reflected on that endpoint.", "@dnaveenr This PR is in pretty good shape, so feel free to reopen it." ]
2022-03-07T17:06:38
2022-03-07T17:24:32
2022-03-07T17:15:06
CONTRIBUTOR
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This PR adds RMSE - Root Mean Squared Error and MAE - Mean Absolute Error to the metrics API. Both implementations are based on usage of sciket-learn. Feature request here : Add support for continuous metrics (RMSE, MAE) [#3608](https://github.com/huggingface/datasets/issues/3608) Any suggestions and changes required will be helpful.
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Fix Google Drive URL to avoid Virus scan warning in streaming mode
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3843). All of your documentation changes will be reflected on that endpoint.", "Cool ! Looks like it breaks `test_streaming_gg_drive_gzipped` for some reason..." ]
2022-03-07T13:09:19
2022-03-15T12:30:25
2022-03-15T12:30:23
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The streaming version of https://github.com/huggingface/datasets/pull/3787. Fix #3835 CC: @albertvillanova
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Align IterableDataset.shuffle with Dataset.shuffle
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3842). All of your documentation changes will be reflected on that endpoint.", "We should also add `generator` as a param to `shuffle` to fully align the APIs, no?", "I added the `generator` argument.\r\n\r\nI had to make a f...
2022-03-07T12:10:46
2022-03-07T19:03:43
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From #3444 , Dataset.shuffle can have the same API than IterableDataset.shuffle (i.e. in streaming mode). Currently you can pass an optional seed to both if you want, BUT currently IterableDataset.shuffle always requires a buffer_size, used for approximate shuffling. I propose using a reasonable default value (maybe 1000) instead. In this PR, I set the default `buffer_size` value to 1,000, and I reorder the `IterableDataset.shuffle` arguments to match `Dataset.shuffle`, i.e. making `seed` the first argument.
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Pyright reportPrivateImportUsage when `from datasets import load_dataset`
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[ "Hi! \r\n\r\nThis issue stems from `datasets` having `py.typed` defined (see https://github.com/microsoft/pyright/discussions/3764#discussioncomment-3282142) - to avoid it, we would either have to remove `py.typed` (added to be compliant with PEP-561) or export the names with `__all__`/`from .submodule import name ...
2022-03-07T10:24:04
2023-02-18T19:14:03
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CONTRIBUTOR
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## Describe the bug Pyright complains about module not exported. ## Steps to reproduce the bug Use an editor/IDE with Pyright Language server with default configuration: ```python from datasets import load_dataset ``` ## Expected results No complain from Pyright ## Actual results Pyright complain below: ``` `load_dataset` is not exported from module "datasets" Import from "datasets.load" instead [reportPrivateImportUsage] ``` Importing from `datasets.load` does indeed solves the problem but I believe importing directly from top level `datasets` is the intended usage per the documentation. ## Environment info - `datasets` version: 1.18.3 - Platform: macOS-12.2.1-arm64-arm-64bit - Python version: 3.9.10 - PyArrow version: 7.0.0
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Pin responses to fix CI for Windows
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3840). All of your documentation changes will be reflected on that endpoint." ]
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Temporarily fix CI for Windows by pinning `responses`. See: https://app.circleci.com/pipelines/github/huggingface/datasets/10292/workflows/83de4a55-bff7-43ec-96f7-0c335af5c050/jobs/63355 Fix: #3839
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CI is broken for Windows
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## Describe the bug See: https://app.circleci.com/pipelines/github/huggingface/datasets/10292/workflows/83de4a55-bff7-43ec-96f7-0c335af5c050/jobs/63355 ``` ___________________ test_datasetdict_from_text_split[test] ____________________ [gw0] win32 -- Python 3.7.11 C:\tools\miniconda3\envs\py37\python.exe split = 'test' text_path = 'C:\\Users\\circleci\\AppData\\Local\\Temp\\pytest-of-circleci\\pytest-0\\popen-gw0\\data6\\dataset.txt' tmp_path = WindowsPath('C:/Users/circleci/AppData/Local/Temp/pytest-of-circleci/pytest-0/popen-gw0/test_datasetdict_from_text_spl7') @pytest.mark.parametrize("split", [None, NamedSplit("train"), "train", "test"]) def test_datasetdict_from_text_split(split, text_path, tmp_path): if split: path = {split: text_path} else: split = "train" path = {"train": text_path, "test": text_path} cache_dir = tmp_path / "cache" expected_features = {"text": "string"} > dataset = TextDatasetReader(path, cache_dir=cache_dir).read() tests\io\test_text.py:118: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ C:\tools\miniconda3\envs\py37\lib\site-packages\datasets\io\text.py:43: in read use_auth_token=use_auth_token, C:\tools\miniconda3\envs\py37\lib\site-packages\datasets\builder.py:588: in download_and_prepare self._download_prepared_from_hf_gcs(dl_manager.download_config) C:\tools\miniconda3\envs\py37\lib\site-packages\datasets\builder.py:630: in _download_prepared_from_hf_gcs reader.download_from_hf_gcs(download_config, relative_data_dir) C:\tools\miniconda3\envs\py37\lib\site-packages\datasets\arrow_reader.py:260: in download_from_hf_gcs downloaded_dataset_info = cached_path(remote_dataset_info.replace(os.sep, "/")) C:\tools\miniconda3\envs\py37\lib\site-packages\datasets\utils\file_utils.py:301: in cached_path download_desc=download_config.download_desc, C:\tools\miniconda3\envs\py37\lib\site-packages\datasets\utils\file_utils.py:560: in get_from_cache headers=headers, C:\tools\miniconda3\envs\py37\lib\site-packages\datasets\utils\file_utils.py:476: in http_head max_retries=max_retries, C:\tools\miniconda3\envs\py37\lib\site-packages\datasets\utils\file_utils.py:397: in _request_with_retry response = requests.request(method=method.upper(), url=url, timeout=timeout, **params) C:\tools\miniconda3\envs\py37\lib\site-packages\requests\api.py:61: in request return session.request(method=method, url=url, **kwargs) C:\tools\miniconda3\envs\py37\lib\site-packages\requests\sessions.py:529: in request resp = self.send(prep, **send_kwargs) C:\tools\miniconda3\envs\py37\lib\site-packages\requests\sessions.py:645: in send r = adapter.send(request, **kwargs) C:\tools\miniconda3\envs\py37\lib\site-packages\responses\__init__.py:840: in unbound_on_send return self._on_request(adapter, request, *a, **kwargs) C:\tools\miniconda3\envs\py37\lib\site-packages\responses\__init__.py:780: in _on_request match, match_failed_reasons = self._find_match(request) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = <responses.RequestsMock object at 0x000002048AD70588> request = <PreparedRequest [HEAD]> def _find_first_match(self, request): match_failed_reasons = [] > for i, match in enumerate(self._matches): E AttributeError: 'RequestsMock' object has no attribute '_matches' C:\tools\miniconda3\envs\py37\lib\site-packages\moto\core\models.py:289: AttributeError ```
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Add a data type for labeled images (image segmentation)
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2022-03-07T09:38:15
2022-04-10T13:34:59
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CONTRIBUTOR
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It might be a mix of Image and ClassLabel, and the color palette might be generated automatically. --- ### Example every pixel in the images of the annotation column (in https://huggingface.co/datasets/scene_parse_150) has a value that gives its class, and the dataset itself is associated with a color palette (eg https://github.com/open-mmlab/mmsegmentation/blob/98a353b674c6052d319e7de4e5bcd65d670fcf84/mmseg/datasets/ade.py#L47) that maps every class with a color. So we might want to render the image as a colored image instead of a black and white one. <img width="785" alt="156741519-fbae6844-2606-4c28-837e-279d83d00865" src="https://user-images.githubusercontent.com/1676121/157005263-7058c584-2b70-465a-ad94-8a982f726cf4.png"> See https://github.com/tensorflow/datasets/blob/master/tensorflow_datasets/core/features/labeled_image.py for reference in Tensorflow
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Release: 1.18.4
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2022-03-07T09:13:29
2022-03-07T11:07:35
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Logo float left
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3836). All of your documentation changes will be reflected on that endpoint.", "Weird, the logo doesn't seem to be floating on my side (using Chrome) at https://huggingface.co/docs/datasets/master/en/index", "https://huggingf...
2022-03-07T08:38:34
2022-03-07T20:21:11
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The link given on the gigaword does not work
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2022-03-07T07:56:42
2022-03-15T12:30:23
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## Dataset viewer issue for '*name of the dataset*' **Link:** *link to the dataset viewer page* *short description of the issue* Am I the one who added this dataset ? Yes-No
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Fix dead dataset scripts creation link.
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2022-03-06T16:45:48
2022-03-07T12:12:07
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Previous link gives 404 error. Updated with a new dataset scripts creation link.
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Small typos in How-to-train tutorial.
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Making Hugging Face the place to go for Graph NNs datasets
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[ "It will be indeed really great to add support to GNN datasets. Big :+1: for this initiative.", "@napoles-uach identifies the [TUDatasets](https://chrsmrrs.github.io/datasets/) (A collection of benchmark datasets for graph classification and regression). \r\n\r\nAdded to the Tasks in the initial issue.", "Thank...
2022-03-06T03:02:58
2022-03-14T07:45:38
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Let's make Hugging Face Datasets the central hub for GNN datasets :) **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 GNN field. What are some datasets worth integrating into the Hugging Face hub? Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md). Special thanks to @napoles-uach for his collaboration on identifying the first ones: - [ ] [SNAP-Stanford OGB Datasets](https://github.com/snap-stanford/ogb). - [ ] [SNAP-Stanford Pretrained GNNs Chemistry and Biology Datasets](https://github.com/snap-stanford/pretrain-gnns). - [ ] [TUDatasets](https://chrsmrrs.github.io/datasets/) (A collection of benchmark datasets for graph classification and regression) cc @osanseviero
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https://api.github.com/repos/huggingface/datasets/issues/3832/timeline
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