Datasets:

selfishark

/

hf-issues-dataset-with-comments

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I_kwDODunzps5FpdbI

NonMatchingChecksumError on Spider dataset

closed

NONE

## 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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https://github.com/huggingface/datasets/pull/3905

PR_kwDODunzps40ZJQJ

Perplexity Metric Card

closed

CONTRIBUTOR

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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I_kwDODunzps5FmiWv

CONLL2003 Dataset not available

closed

NONE

## Describe the bug [CONLL2003](https://huggingface.co/datasets/conll2003) Dataset can no longer reach 'https://data.deepai.org/conll2003.zip'  ## Steps to reproduce the bug ```python from datasets import load_dataset datasets = load_dataset("conll2003") ``` ## Expected results Download the conll2003 dataset. ## Actual results Error: `ConnectionError: Couldn't reach https://data.deepai.org/conll2003.zip (error 502)`

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PR_kwDODunzps40WnkI

Add Biwi Kinect Head Pose dataset.

open

CONTRIBUTOR

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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I_kwDODunzps5FlSlx

Can't import datasets: partially initialized module 'fsspec' has no attribute 'utils'

closed

NONE

## 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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I_kwDODunzps5FlDD9

Dataset viewer issue for IndicParaphrase- the preview doesn't show

closed

NONE

## 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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https://github.com/huggingface/datasets/pull/3900

PR_kwDODunzps40VxRh

Add MetaShift dataset

closed

CONTRIBUTOR

This PR adds the MetaShift dataset. Dataset Request : Add MetaShift dataset [#3813](https://github.com/huggingface/datasets/issues/3813) @lhoestq As discussed, - I have copied the preprocessing script and modified it as required to not create new directories and folders and instead yield the images. - I do the preprocessing in _split_generators to get the required data which is then passed to _generate_examples. - Beyond the generated MetaShift dataset, the original preprocess script also generates the meta-graphs for each class, I have currently not included this part. [ Ref : [Link](https://github.com/Weixin-Liang/MetaShift#generate-full-metashift) ] - There is a Bonus section, the authors share. I have currently not included this part. [ Ref : [Link](https://github.com/Weixin-Liang/MetaShift#bonus-generate-the-metashift-attributes-dataset-subsets-defined-by-subject-attributes) ] - I had a basic test script which downloaded the dataset and tested the basic functionality. Things seems fine. For real data, I performed the following test : ``` RUN_SLOW=1 pytest tests/test_dataset_common.py::LocalDatasetTest::test_load_real_dataset_metashift ============================================== test session starts =============================================== platform linux -- Python 3.7.11, pytest-7.0.1, pluggy-1.0.0 rootdir: ./datasets plugins: hydra-core-1.1.1, datadir-1.3.1, forked-1.4.0, xdist-2.5.0 collected 1 item tests/test_dataset_common.py . [100%] ========================================= 1 passed in 4821.25s (1:20:21) ========================================= ``` - I couldn't get the dummy dataset. Need some inputs here. Error as follows : ``` Using custom data configuration default Dataset metashift with config None seems to already open files in the method `_split_generators(...)`. You might consider to instead only open files in the method `_generate_examples(...)` instead. If this is not possible the dummy data has to be created with less guidance. Make sure you create the file dummy_data/full-candidate-subsets.pkl. for split in generator_splits: UnboundLocalError: local variable 'generator_splits' referenced before assignment ``` To-Do : - [x] Currently I am using the default _SELECTED_CLASSES. I need to use config option here as suggested - [x] Complete fields in the Dataset Card. - [x] Tagging the dataset using the Datasets Tagging app. Need your help and suggestions for improvement. Thank you

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https://github.com/huggingface/datasets/pull/3899

PR_kwDODunzps40UzR3

Add exact match metric

closed

CONTRIBUTOR

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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PR_kwDODunzps40UWG4

Create README.md for WER metric

closed

CONTRIBUTOR

Proposing a draft WER metric card, @lhoestq I'm not very certain about "Values from popular papers" -- I don't know ASR very well, what do you think of the examples I found?

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https://github.com/huggingface/datasets/pull/3897

PR_kwDODunzps40UJH4

Align tqdm control/cache control with Transformers

closed

CONTRIBUTOR

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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I_kwDODunzps5FiVWu

Missing google file for `multi_news` dataset

closed

CONTRIBUTOR

## 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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PR_kwDODunzps40T1C8

Fix code examples indentation

closed

MEMBER

Some code examples are currently not rendered correctly. I think this is because they are over-indented cc @mariosasko

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PR_kwDODunzps40TzXW

[docs] make dummy data creation optional

closed

MEMBER

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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PR_kwDODunzps40TmxB

Add default branch for doc building

closed

MEMBER

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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PR_kwDODunzps40ShYB

Fix CLI test checksums

closed

MEMBER

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

Fix race condition in doc build

closed

MEMBER

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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PR_kwDODunzps40QJ8V

Update beans download urls

closed

CONTRIBUTOR

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

Cannot load beans dataset (Couldn't reach the dataset)

closed

NONE

## 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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I_kwDODunzps5FdyKJ

IterableDataset columns and feature types

open

MEMBER

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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PR_kwDODunzps40PwqT

ImageFolder improvements

closed

CONTRIBUTOR

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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PR_kwDODunzps40PO6W

Retry HfApi call inside push_to_hub when 504 error

closed

MEMBER

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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PR_kwDODunzps40O00Z

Fix some shuffle docs

closed

MEMBER

Following #3842 some docs were still outdated (with `buffer_size` as the first argument)

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PR_kwDODunzps40OPM9

Fix bug in METEOR metric due to nltk version

closed

MEMBER

Fix #3883.

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I_kwDODunzps5Fa1m9

The metric Meteor doesn't work for nltk ==3.6.4

closed

NONE

## 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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PR_kwDODunzps40NKz7

Image process doc

closed

MEMBER

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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I_kwDODunzps5FaCCl

How to use Image folder

closed

NONE

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

Change the framework switches to the new syntax

closed

MEMBER

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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PR_kwDODunzps40MP7f

SQuAD v2 metric: create README.md

closed

CONTRIBUTOR

Proposing SQuAD v2 metric card

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PR_kwDODunzps40MOpn

Update cats_vs_dogs size

closed

CONTRIBUTOR

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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I_kwDODunzps5FY3aH

Align metadata to DCAT/DCAT-AP

open

NONE

**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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PR_kwDODunzps40LYC8

Fix download_mode in dataset_module_factory

closed

MEMBER

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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PR_kwDODunzps40LUuw

Module namespace cleanup for v2.0

closed

CONTRIBUTOR

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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PR_kwDODunzps40LRYD

add MSE and MAE metrics - V2

closed

CONTRIBUTOR

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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PR_kwDODunzps40LGoV

Create SQuAD metric README.md

closed

CONTRIBUTOR

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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I_kwDODunzps5FXvzi

HTTP error 504 Server Error: Gateway Time-out

closed

NONE

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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PR_kwDODunzps40KRcM

add pandas to env command

closed

MEMBER

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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PR_kwDODunzps40KAYy

Add wikitablequestions dataset

closed

CONTRIBUTOR

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I_kwDODunzps5FWJsw

Making the Hub the place for datasets in Portuguese

open

NONE

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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PR_kwDODunzps40HnWA

Ignore duplicate keys if `ignore_verifications=True`

closed

CONTRIBUTOR

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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PR_kwDODunzps40Hjrk

Update for the rename doc-builder -> hf-doc-utils

closed

MEMBER

This PR adapts the job to the upcoming change of name of `doc-builder`.

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PR_kwDODunzps40HWcu

Bring back imgs so that forsk dont get broken

closed

CONTRIBUTOR

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PR_kwDODunzps40HT9K

Add logo img

closed

CONTRIBUTOR

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PR_kwDODunzps40HQZ_

Update image dataset tags

closed

CONTRIBUTOR

Align the existing image datasets' tags with new tags introduced in #3800.

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PR_kwDODunzps40HP-A

Update code blocks

closed

MEMBER

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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PR_kwDODunzps40HFht

Manipulate columns on IterableDataset (rename columns, cast, etc.)

closed

MEMBER

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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I_kwDODunzps5FTWzc

big_patent cased version

open

NONE

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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PR_kwDODunzps40GpzZ

Small doc fixes

closed

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I_kwDODunzps5FSz9l

Unable to dowload big_patent (FileNotFoundError)

closed

NONE

## 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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PR_kwDODunzps40GVSq

Udpate index.mdx margins

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I_kwDODunzps5FSrqp

Order of dataset changes due to glob.glob.

open

MEMBER

## 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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PR_kwDODunzps40GUSf

Fix push_to_hub with null images

closed

MEMBER

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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I_kwDODunzps5FSY7N

Bad error message when loading private dataset

open

MEMBER

## 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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I_kwDODunzps5FSVaX

load only England English dataset from common voice english dataset

closed

NONE

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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PR_kwDODunzps40F3uN

add ontonotes_conll dataset

closed

CONTRIBUTOR

# 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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PR_kwDODunzps40Fb26

Redundant add dataset information and dead link.

closed

CONTRIBUTOR

> 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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I_kwDODunzps5FRNGO

Load audio dataset error

closed

NONE

## 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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PR_kwDODunzps40FBx9

[feat] Add tqdm arguments

open

NONE

In this PR, tqdm arguments can be passed to the map() function and such, in order to be more flexible.

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PR_kwDODunzps40E6sW

Add "Adversarial GLUE" dataset to datasets library

closed

CONTRIBUTOR

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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I_kwDODunzps5FQ-Lm

NonMatchingChecksumError when checksum is None

closed

CONTRIBUTOR

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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I_kwDODunzps5FQIWh

Datasets' cache not re-used

open

NONE

## 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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https://github.com/huggingface/datasets/pull/3846

PR_kwDODunzps40D-uh

Update faiss device docstring

closed

MEMBER

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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PR_kwDODunzps40DvqX

add RMSE and MAE metrics.

closed

CONTRIBUTOR

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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PR_kwDODunzps40DkYL

Add rmse and mae metrics.

closed

CONTRIBUTOR

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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PR_kwDODunzps40Cm0D

Fix Google Drive URL to avoid Virus scan warning in streaming mode

closed

CONTRIBUTOR

The streaming version of https://github.com/huggingface/datasets/pull/3787. Fix #3835 CC: @albertvillanova

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PR_kwDODunzps40CZvE

Align IterableDataset.shuffle with Dataset.shuffle

closed

MEMBER

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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I_kwDODunzps5FNpCC

Pyright reportPrivateImportUsage when `from datasets import load_dataset`

open

CONTRIBUTOR

## 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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https://github.com/huggingface/datasets/pull/3840

PR_kwDODunzps40B8eu

Pin responses to fix CI for Windows

closed

MEMBER

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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I_kwDODunzps5FNkD6

CI is broken for Windows

closed

MEMBER

## Describe the bug See: https://app.circleci.com/pipelines/github/huggingface/datasets/10292/workflows/83de4a55-bff7-43ec-96f7-0c335af5c050/jobs/63355

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I_kwDODunzps5FNYz-

Add a data type for labeled images (image segmentation)

open

CONTRIBUTOR

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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PR_kwDODunzps40BwE1

Release: 1.18.4

closed

MEMBER

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PR_kwDODunzps40Bobr

Logo float left

closed

CONTRIBUTOR

<img width="1000" alt="Screenshot 2022-03-07 at 09 35 29" src="https://user-images.githubusercontent.com/11827707/156996422-339ba43e-932b-4849-babf-9321cb99c922.png">

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I_kwDODunzps5FM-ZV

The link given on the gigaword does not work

closed

NONE

## 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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PR_kwDODunzps40ATVw

Fix dead dataset scripts creation link.

closed

CONTRIBUTOR

Previous link gives 404 error. Updated with a new dataset scripts creation link.

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