Datasets:

safik

/

github-issues

like 0

https://api.github.com/repos/huggingface/datasets/issues/2700

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2700/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2700/comments

https://api.github.com/repos/huggingface/datasets/issues/2700/events

https://github.com/huggingface/datasets/issues/2700

MDU6SXNzdWU5NTAyNzYzMjU=

from datasets import Dataset is failing

closed

NONE

## Describe the bug A clear and concise description of what the bug is. ## Steps to reproduce the bug ```python # Sample code to reproduce the bug from datasets import Dataset ``` ## Expected results A clear and concise description of the expected results. ## Actual results Specify the actual results or traceback. /usr/local/lib/python3.7/dist-packages/datasets/utils/file_utils.py in <module>() 25 import posixpath 26 import requests ---> 27 from tqdm.contrib.concurrent import thread_map 28 29 from .. import __version__, config, utils ModuleNotFoundError: No module named 'tqdm.contrib.concurrent' --------------------------------------------------------------------------- NOTE: If your import is failing due to a missing package, you can manually install dependencies using either !pip or !apt. To view examples of installing some common dependencies, click the "Open Examples" button below. --------------------------------------------------------------------------- ## Environment info <!-- You can run the command `datasets-cli env` and copy-and-paste its output below. --> - `datasets` version: latest version as of 07/21/2021 - Platform: Google Colab - Python version: 3.7 - PyArrow version:

https://api.github.com/repos/huggingface/datasets/issues/2700/timeline

https://api.github.com/repos/huggingface/datasets/issues/2699

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2699/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2699/comments

https://api.github.com/repos/huggingface/datasets/issues/2699/events

https://github.com/huggingface/datasets/issues/2699

MDU6SXNzdWU5NTAyMjEyMjY=

cannot combine splits merging and streaming?

open

NONE

this does not work: `dataset = datasets.load_dataset('mc4','iw',split='train+validation',streaming=True)` with error: `ValueError: Bad split: train+validation. Available splits: ['train', 'validation']` these work: `dataset = datasets.load_dataset('mc4','iw',split='train+validation')` `dataset = datasets.load_dataset('mc4','iw',split='train',streaming=True)` `dataset = datasets.load_dataset('mc4','iw',split='validation',streaming=True)` i could not find a reference to this in the documentation and the error message is confusing. also would be nice to allow streaming for the merged splits

https://api.github.com/repos/huggingface/datasets/issues/2699/timeline

https://api.github.com/repos/huggingface/datasets/issues/2698

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2698/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2698/comments

https://api.github.com/repos/huggingface/datasets/issues/2698/events

https://github.com/huggingface/datasets/pull/2698

MDExOlB1bGxSZXF1ZXN0Njk0NzUxMzMw

Ignore empty batch when writing

closed

CONTRIBUTOR

This prevents an schema update with unknown column types, as reported in #2644. This is my first attempt at fixing the issue. I tested the following: - First batch returned by a batched map operation is empty. - An intermediate batch is empty. - `python -m unittest tests.test_arrow_writer` passes. However, `arrow_writer` looks like a pretty generic interface, I'm not sure if there are other uses I may have overlooked. Let me know if that's the case, or if a better approach would be preferable.

https://api.github.com/repos/huggingface/datasets/issues/2698/timeline

https://api.github.com/repos/huggingface/datasets/issues/2697

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2697/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2697/comments

https://api.github.com/repos/huggingface/datasets/issues/2697/events

https://github.com/huggingface/datasets/pull/2697

MDExOlB1bGxSZXF1ZXN0Njk0NjMyODg0

Fix import on Colab

closed

CONTRIBUTOR

Fix #2695, fix #2700.

https://api.github.com/repos/huggingface/datasets/issues/2697/timeline

https://api.github.com/repos/huggingface/datasets/issues/2696

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2696/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2696/comments

https://api.github.com/repos/huggingface/datasets/issues/2696/events

https://github.com/huggingface/datasets/pull/2696

MDExOlB1bGxSZXF1ZXN0Njk0NTMwODg3

Add support for disable_progress_bar on Windows

closed

CONTRIBUTOR

This PR is a continuation of #2667 and adds support for `utils.disable_progress_bar()` on Windows when using multiprocessing. This [answer](https://stackoverflow.com/a/6596695/14095927) on SO explains it nicely why the current approach (with calling `utils.is_progress_bar_enabled()` inside `Dataset._map_single`) would not work on Windows.

https://api.github.com/repos/huggingface/datasets/issues/2696/timeline

https://api.github.com/repos/huggingface/datasets/issues/2695

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2695/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2695/comments

https://api.github.com/repos/huggingface/datasets/issues/2695/events

https://github.com/huggingface/datasets/issues/2695

MDU6SXNzdWU5NDk4NjQ4MjM=

Cannot import load_dataset on Colab

closed

NONE

## Describe the bug Got tqdm concurrent module not found error during importing load_dataset from datasets. ## Steps to reproduce the bug Here [colab notebook](https://colab.research.google.com/drive/1pErWWnVP4P4mVHjSFUtkePd8Na_Qirg4?usp=sharing) to reproduce the error On colab: ```python !pip install datasets from datasets import load_dataset ``` ## Expected results Works without error ## Actual results Specify the actual results or traceback. ``` ModuleNotFoundError Traceback (most recent call last) <ipython-input-2-8cc7de4c69eb> in <module>() ----> 1 from datasets import load_dataset, load_metric, Metric, MetricInfo, Features, Value 2 from sklearn.metrics import mean_squared_error /usr/local/lib/python3.7/dist-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 /usr/local/lib/python3.7/dist-packages/datasets/arrow_dataset.py in <module>() 40 from tqdm.auto import tqdm 41 ---> 42 from datasets.tasks.text_classification import TextClassification 43 44 from . import config, utils /usr/local/lib/python3.7/dist-packages/datasets/tasks/__init__.py in <module>() 1 from typing import Optional 2 ----> 3 from ..utils.logging import get_logger 4 from .automatic_speech_recognition import AutomaticSpeechRecognition 5 from .base import TaskTemplate /usr/local/lib/python3.7/dist-packages/datasets/utils/__init__.py in <module>() 19 20 from . import logging ---> 21 from .download_manager import DownloadManager, GenerateMode 22 from .file_utils import DownloadConfig, cached_path, hf_bucket_url, is_remote_url, temp_seed 23 from .mock_download_manager import MockDownloadManager /usr/local/lib/python3.7/dist-packages/datasets/utils/download_manager.py in <module>() 24 25 from .. import config ---> 26 from .file_utils import ( 27 DownloadConfig, 28 cached_path, /usr/local/lib/python3.7/dist-packages/datasets/utils/file_utils.py in <module>() 25 import posixpath 26 import requests ---> 27 from tqdm.contrib.concurrent import thread_map 28 29 from .. import __version__, config, utils ModuleNotFoundError: No module named 'tqdm.contrib.concurrent' ``` ## Environment info <!-- You can run the command `datasets-cli env` and copy-and-paste its output below. --> - `datasets` version: 1.10.0 - Platform: Colab - Python version: 3.7.11 - PyArrow version: 3.0.0

https://api.github.com/repos/huggingface/datasets/issues/2695/timeline

https://api.github.com/repos/huggingface/datasets/issues/2694

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2694/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2694/comments

https://api.github.com/repos/huggingface/datasets/issues/2694/events

https://github.com/huggingface/datasets/pull/2694

MDExOlB1bGxSZXF1ZXN0Njk0NDg0NTcy

fix: 🐛 change string format to allow copy/paste to work in bash

closed

CONTRIBUTOR

Before: copy/paste resulted in an error because the square bracket characters `[]` are special characters in bash

https://api.github.com/repos/huggingface/datasets/issues/2694/timeline

https://api.github.com/repos/huggingface/datasets/issues/2693

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2693/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2693/comments

https://api.github.com/repos/huggingface/datasets/issues/2693/events

https://github.com/huggingface/datasets/pull/2693

MDExOlB1bGxSZXF1ZXN0Njk0NDQ1ODAz

Fix OSCAR Esperanto

closed

MEMBER

The Esperanto part (original) of OSCAR has the wrong number of examples: ```python from datasets import load_dataset raw_datasets = load_dataset("oscar", "unshuffled_original_eo") ``` raises ```python NonMatchingSplitsSizesError: [{'expected': SplitInfo(name='train', num_bytes=314188336, num_examples=121171, dataset_name='oscar'), 'recorded': SplitInfo(name='train', num_bytes=314064514, num_examples=121168, dataset_name='oscar')}] ``` I updated the number of expected examples in dataset_infos.json cc @sgugger

https://api.github.com/repos/huggingface/datasets/issues/2693/timeline

https://api.github.com/repos/huggingface/datasets/issues/2692

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2692/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2692/comments

https://api.github.com/repos/huggingface/datasets/issues/2692/events

https://github.com/huggingface/datasets/pull/2692

MDExOlB1bGxSZXF1ZXN0Njk0NDE4MDg1

Update BibTeX entry

closed

MEMBER

Update BibTeX entry

https://api.github.com/repos/huggingface/datasets/issues/2692/timeline

https://api.github.com/repos/huggingface/datasets/issues/2691

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2691/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2691/comments

https://api.github.com/repos/huggingface/datasets/issues/2691/events

https://github.com/huggingface/datasets/issues/2691

MDU6SXNzdWU5NDk3NTgzNzk=

xtreme / pan-x cannot be downloaded

closed

CONTRIBUTOR

## Describe the bug Dataset xtreme / pan-x cannot be loaded Seems related to https://github.com/huggingface/datasets/pull/2326 ## Steps to reproduce the bug ```python dataset = load_dataset("xtreme", "PAN-X.fr") ``` ## Expected results Load the dataset ## Actual results ``` FileNotFoundError: Couldn't find file at https://www.dropbox.com/s/12h3qqog6q4bjve/panx_dataset.tar?dl=1 ``` ## Environment info - `datasets` version: 1.9.0 - Platform: macOS-11.4-x86_64-i386-64bit - Python version: 3.8.11 - PyArrow version: 4.0.1

https://api.github.com/repos/huggingface/datasets/issues/2691/timeline

https://api.github.com/repos/huggingface/datasets/issues/2690

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2690/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2690/comments

https://api.github.com/repos/huggingface/datasets/issues/2690/events

https://github.com/huggingface/datasets/pull/2690

MDExOlB1bGxSZXF1ZXN0Njk0MjU5MDc1

Docs details

closed

CONTRIBUTOR

Some comments here: - the code samples assume the expected libraries have already been installed. Maybe add a section at start, or add it to every code sample. Something like `pip install datasets transformers torch 'datasets[streaming]'` (maybe just link to https://huggingface.co/docs/datasets/installation.html + a one-liner that installs all the requirements / alternatively a requirements.txt file) - "If you’d like to play with the examples, you must install it from source." in https://huggingface.co/docs/datasets/installation.html: it's not clear to me what this means (what are these "examples"?) - in https://huggingface.co/docs/datasets/loading_datasets.html: "or AWS bucket if it’s not already stored in the library". It's the only place in the doc (aside from the docstring https://huggingface.co/docs/datasets/package_reference/loading_methods.html?highlight=aws bucket#datasets.list_datasets) where the "AWS bucket" is mentioned. It's not easy to understand what this means. Maybe explain more, and link to https://s3.amazonaws.com/datasets.huggingface.co and/or https://huggingface.co/docs/datasets/filesystems.html. - example in https://huggingface.co/docs/datasets/loading_datasets.html#manually-downloading-files is obsoleted by https://github.com/huggingface/datasets/pull/2326. Also: see https://github.com/huggingface/datasets/issues/2691 for a bug on this specific dataset. - in https://huggingface.co/docs/datasets/loading_datasets.html#manually-downloading-files the doc says "After you’ve downloaded the files, you can point to the folder hosting them locally with the data_dir argument as follows:", but the following example does not show how to use `data_dir` - in https://huggingface.co/docs/datasets/loading_datasets.html#csv-files, it would be nice to have an URL to the csv loader reference (but I'm not sure there is one in the API reference). This comment applies in many places in the doc: I would want the API reference to contain doc for all the code/functions/classes... and I would want a lot more links inside the doc pointing to the API entries. - in the API reference (docstrings) I would prefer "SOURCE" to link to github instead of a copy of the code inside the docs site (eg. https://github.com/huggingface/datasets/blob/master/src/datasets/load.py#L711 instead of https://huggingface.co/docs/datasets/_modules/datasets/load.html#load_dataset) - it seems like not all the API is exposed in the doc. For example, there is no doc for [`disable_progress_bar`](https://github.com/huggingface/datasets/search?q=disable_progress_bar), see https://huggingface.co/docs/datasets/search.html?q=disable_progress_bar, even if the code contains docstrings. Does it mean that the function is not officially supported? (otherwise, maybe it also deserves a mention in https://huggingface.co/docs/datasets/package_reference/logging_methods.html) - in https://huggingface.co/docs/datasets/loading_datasets.html?highlight=most%20efficient%20format%20have%20json%20files%20consisting%20multiple%20json%20objects#json-files, "The most efficient format is to have JSON files consisting of multiple JSON objects, one per line, representing individual data rows:", maybe link to https://en.wikipedia.org/wiki/JSON_streaming#Line-delimited_JSON and give it a name ("line-delimited JSON"? "JSON Lines" as in https://huggingface.co/docs/datasets/processing.html#exporting-a-dataset-to-csv-json-parquet-or-to-python-objects ?) - in https://huggingface.co/docs/datasets/loading_datasets.html, for the local files sections, it would be nice to provide sample csv / json / text files to download, so that it's easier for the reader to try to load them (instead: they won't try) - the doc explains how to shard a dataset, but does not explain why and when a dataset should be sharded (I have no idea... for [parallelizing](https://huggingface.co/docs/datasets/processing.html#multiprocessing)?). It does neither give an idea of the number of shards a dataset typically should have and why. - the code example in https://huggingface.co/docs/datasets/processing.html#mapping-in-a-distributed-setting does not work, because `training_args` has not been defined before in the doc.

https://api.github.com/repos/huggingface/datasets/issues/2690/timeline

https://api.github.com/repos/huggingface/datasets/issues/2689

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2689/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2689/comments

https://api.github.com/repos/huggingface/datasets/issues/2689/events

https://github.com/huggingface/datasets/issues/2689

MDU6SXNzdWU5NDk0NDcxMDQ=

cannot save the dataset to disk after rename_column

closed

CONTRIBUTOR

## Describe the bug If you use `rename_column` and do no other modification, you will be unable to save the dataset using `save_to_disk` ## Steps to reproduce the bug ```python # Sample code to reproduce the bug In [1]: from datasets import Dataset, load_from_disk In [5]: dataset=Dataset.from_dict({'foo': [0]}) In [7]: dataset.save_to_disk('foo') In [8]: dataset=load_from_disk('foo') In [10]: dataset=dataset.rename_column('foo', 'bar') In [11]: dataset.save_to_disk('foo') --------------------------------------------------------------------------- PermissionError Traceback (most recent call last) <ipython-input-11-a3bc0d4fc339> in <module> ----> 1 dataset.save_to_disk('foo') /mnt/beegfs/projects/meerqat/anaconda3/envs/meerqat/lib/python3.7/site-packages/datasets/arrow_dataset.py in save_to_disk(self, dataset_path , fs) 597 if Path(dataset_path, config.DATASET_ARROW_FILENAME) in cache_files_paths: 598 raise PermissionError( --> 599 f"Tried to overwrite {Path(dataset_path, config.DATASET_ARROW_FILENAME)} but a dataset can't overwrite itself." 600 ) 601 if Path(dataset_path, config.DATASET_INDICES_FILENAME) in cache_files_paths: PermissionError: Tried to overwrite foo/dataset.arrow but a dataset can't overwrite itself. ``` N. B. I created the dataset from dict to enable easy reproduction but the same happens if you load an existing dataset (e.g. starting from `In [8]`) ## Environment info <!-- You can run the command `datasets-cli env` and copy-and-paste its output below. --> - `datasets` version: 1.8.0 - Platform: Linux-3.10.0-1160.11.1.el7.x86_64-x86_64-with-centos-7.9.2009-Core - Python version: 3.7.10 - PyArrow version: 3.0.0

https://api.github.com/repos/huggingface/datasets/issues/2689/timeline

https://api.github.com/repos/huggingface/datasets/issues/2688

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2688/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2688/comments

https://api.github.com/repos/huggingface/datasets/issues/2688/events

https://github.com/huggingface/datasets/issues/2688

MDU6SXNzdWU5NDkxODIwNzQ=

hebrew language codes he and iw should be treated as aliases

closed

NONE

https://huggingface.co/datasets/mc4 not listed when searching for hebrew datasets (he) as it uses the older language code iw, preventing discoverability.

https://api.github.com/repos/huggingface/datasets/issues/2688/timeline

https://api.github.com/repos/huggingface/datasets/issues/2687

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2687/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2687/comments

https://api.github.com/repos/huggingface/datasets/issues/2687/events

https://github.com/huggingface/datasets/pull/2687

MDExOlB1bGxSZXF1ZXN0NjkzNjY1NDI2

Minor documentation fix

closed

CONTRIBUTOR

Currently, [Writing a dataset loading script](https://huggingface.co/docs/datasets/add_dataset.html) page has a small error. A link to `matinf` dataset in [_Dataset scripts of reference_](https://huggingface.co/docs/datasets/add_dataset.html#dataset-scripts-of-reference) section actually leads to `xsquad`, instead. This PR fixes that.

https://api.github.com/repos/huggingface/datasets/issues/2687/timeline

https://api.github.com/repos/huggingface/datasets/issues/2686

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2686/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2686/comments

https://api.github.com/repos/huggingface/datasets/issues/2686/events

https://github.com/huggingface/datasets/pull/2686

MDExOlB1bGxSZXF1ZXN0NjkzNTk4OTE3

Fix bad config ids that name cache directories

closed

MEMBER

`data_dir=None` was considered a dataset config parameter, hence creating a special config_id for all dataset being loaded. Since the config_id is used to name the cache directories, this leaded to datasets being regenerated for users. I fixed this by ignoring the value of `data_dir` when it's `None` when computing the config_id. I also added a test to make sure the cache directories are not unexpectedly renamed in the future. Fix https://github.com/huggingface/datasets/issues/2683

https://api.github.com/repos/huggingface/datasets/issues/2686/timeline

https://api.github.com/repos/huggingface/datasets/issues/2685

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2685/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2685/comments

https://api.github.com/repos/huggingface/datasets/issues/2685/events

https://github.com/huggingface/datasets/pull/2685

MDExOlB1bGxSZXF1ZXN0NjkzNTgxNTk2

Fix Blog Authorship Corpus dataset

closed

MEMBER

This PR: - Update the JSON metadata file, which previously was raising a `NonMatchingSplitsSizesError` - Fix the codec of the data files (`latin_1` instead of `utf-8`), which previously was raising ` UnicodeDecodeError` for some files Close #2679.

https://api.github.com/repos/huggingface/datasets/issues/2685/timeline

https://api.github.com/repos/huggingface/datasets/issues/2684

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2684/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2684/comments

https://api.github.com/repos/huggingface/datasets/issues/2684/events

https://github.com/huggingface/datasets/pull/2684

MDExOlB1bGxSZXF1ZXN0NjkzNTY0MDY4

Print absolute local paths in load_dataset error messages

closed

CONTRIBUTOR

Use absolute local paths in the error messages of `load_dataset` as per @stas00's suggestion in https://github.com/huggingface/datasets/pull/2500#issuecomment-874891223

https://api.github.com/repos/huggingface/datasets/issues/2684/timeline

https://api.github.com/repos/huggingface/datasets/issues/2683

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2683/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2683/comments

https://api.github.com/repos/huggingface/datasets/issues/2683/events

https://github.com/huggingface/datasets/issues/2683

MDU6SXNzdWU5NDg3MjEzNzk=

Cache directories changed due to recent changes in how config kwargs are handled

closed

MEMBER

Since #2659 I can see weird cache directory names with hashes in the config id, even though no additional config kwargs are passed. For example: ```python from datasets import load_dataset_builder c4_builder = load_dataset_builder("c4", "en") print(c4_builder.cache_dir) # /Users/quentinlhoest/.cache/huggingface/datasets/c4/en-174d3b7155eb68db/0.0.0/... # instead of # /Users/quentinlhoest/.cache/huggingface/datasets/c4/en/0.0.0/... ``` This issue could be annoying since it would simply ignore old cache directories for users, and regenerate datasets cc @stas00 this is what you experienced a few days ago

https://api.github.com/repos/huggingface/datasets/issues/2683/timeline

https://api.github.com/repos/huggingface/datasets/issues/2682

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2682/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2682/comments

https://api.github.com/repos/huggingface/datasets/issues/2682/events

https://github.com/huggingface/datasets/pull/2682

MDExOlB1bGxSZXF1ZXN0NjkzNTE2NjU2

Fix c4 expected files

closed

MEMBER

Some files were not registered in the list of expected files to download Fix https://github.com/huggingface/datasets/issues/2677

https://api.github.com/repos/huggingface/datasets/issues/2682/timeline

https://api.github.com/repos/huggingface/datasets/issues/2681

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2681/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2681/comments

https://api.github.com/repos/huggingface/datasets/issues/2681/events

https://github.com/huggingface/datasets/issues/2681

MDU6SXNzdWU5NDg3MDg2NDU=

5 duplicate datasets

closed

CONTRIBUTOR

## Describe the bug In 5 cases, I could find a dataset on Paperswithcode which references two Hugging Face datasets as dataset loaders. They are: - https://paperswithcode.com/dataset/multinli -> https://huggingface.co/datasets/multi_nli and https://huggingface.co/datasets/multi_nli_mismatch <img width="838" alt="Capture d’écran 2021-07-20 à 16 33 58" src="https://user-images.githubusercontent.com/1676121/126342757-4625522a-f788-41a3-bd1f-2a8b9817bbf5.png"> - https://paperswithcode.com/dataset/squad -> https://huggingface.co/datasets/squad and https://huggingface.co/datasets/squad_v2 - https://paperswithcode.com/dataset/narrativeqa -> https://huggingface.co/datasets/narrativeqa and https://huggingface.co/datasets/narrativeqa_manual - https://paperswithcode.com/dataset/hate-speech-and-offensive-language -> https://huggingface.co/datasets/hate_offensive and https://huggingface.co/datasets/hate_speech_offensive - https://paperswithcode.com/dataset/newsph-nli -> https://huggingface.co/datasets/newsph and https://huggingface.co/datasets/newsph_nli Possible solutions: - don't fix (it works) - for each pair of duplicate datasets, remove one, and create an alias to the other. ## Steps to reproduce the bug Visit the Paperswithcode links, and look at the "Dataset Loaders" section ## Expected results There should only be one reference to a Hugging Face dataset loader ## Actual results Two Hugging Face dataset loaders

https://api.github.com/repos/huggingface/datasets/issues/2681/timeline

https://api.github.com/repos/huggingface/datasets/issues/2680

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2680/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2680/comments

https://api.github.com/repos/huggingface/datasets/issues/2680/events

https://github.com/huggingface/datasets/pull/2680

MDExOlB1bGxSZXF1ZXN0NjkzNDYyNzY3

feat: 🎸 add paperswithcode id for qasper dataset

closed

CONTRIBUTOR

The reverse reference exists on paperswithcode: https://paperswithcode.com/dataset/qasper

https://api.github.com/repos/huggingface/datasets/issues/2680/timeline

https://api.github.com/repos/huggingface/datasets/issues/2679

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2679/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2679/comments

https://api.github.com/repos/huggingface/datasets/issues/2679/events

https://github.com/huggingface/datasets/issues/2679

MDU6SXNzdWU5NDg1MDY2Mzg=

Cannot load the blog_authorship_corpus due to codec errors

closed

NONE

## Describe the bug A codec error is raised while loading the blog_authorship_corpus. ## Steps to reproduce the bug ``` from datasets import load_dataset raw_datasets = load_dataset("blog_authorship_corpus") ``` ## Expected results Loading the dataset without errors. ## Actual results An error similar to the one below was raised for (what seems like) every XML file. /home/izaskr/.cache/huggingface/datasets/downloads/extracted/7cf52524f6517e168604b41c6719292e8f97abbe8f731e638b13423f4212359a/blogs/788358.male.24.Arts.Libra.xml cannot be loaded. Error message: 'utf-8' codec can't decode byte 0xe7 in position 7551: invalid continuation byte Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/home/izaskr/anaconda3/envs/local_vae_older/lib/python3.8/site-packages/datasets/load.py", line 856, in load_dataset builder_instance.download_and_prepare( File "/home/izaskr/anaconda3/envs/local_vae_older/lib/python3.8/site-packages/datasets/builder.py", line 583, in download_and_prepare self._download_and_prepare( File "/home/izaskr/anaconda3/envs/local_vae_older/lib/python3.8/site-packages/datasets/builder.py", line 671, in _download_and_prepare verify_splits(self.info.splits, split_dict) File "/home/izaskr/anaconda3/envs/local_vae_older/lib/python3.8/site-packages/datasets/utils/info_utils.py", line 74, in verify_splits raise NonMatchingSplitsSizesError(str(bad_splits)) datasets.utils.info_utils.NonMatchingSplitsSizesError: [{'expected': SplitInfo(name='train', num_bytes=610252351, num_examples=532812, dataset_name='blog_authorship_corpus'), 'recorded': SplitInfo(name='train', num_bytes=614706451, num_examples=535568, dataset_name='blog_authorship_corpus')}, {'expected': SplitInfo(name='validation', num_bytes=37500394, num_examples=31277, dataset_name='blog_authorship_corpus'), 'recorded': SplitInfo(name='validation', num_bytes=32553710, num_examples=28521, dataset_name='blog_authorship_corpus')}] ## Environment info <!-- You can run the command `datasets-cli env` and copy-and-paste its output below. --> - `datasets` version: 1.9.0 - Platform: Linux-4.15.0-132-generic-x86_64-with-glibc2.10 - Python version: 3.8.8 - PyArrow version: 4.0.1

https://api.github.com/repos/huggingface/datasets/issues/2679/timeline

https://api.github.com/repos/huggingface/datasets/issues/2678

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2678/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2678/comments

https://api.github.com/repos/huggingface/datasets/issues/2678/events

https://github.com/huggingface/datasets/issues/2678

MDU6SXNzdWU5NDg0NzEyMjI=

Import Error in Kaggle notebook

closed

NONE

## Describe the bug Not able to import datasets library in kaggle notebooks ## Steps to reproduce the bug ```python !pip install datasets import datasets ``` ## Expected results No such error ## Actual results ``` ImportError Traceback (most recent call last) <ipython-input-9-652e886d387f> in <module> ----> 1 import datasets /opt/conda/lib/python3.7/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 /opt/conda/lib/python3.7/site-packages/datasets/arrow_dataset.py in <module> 36 import pandas as pd 37 import pyarrow as pa ---> 38 import pyarrow.compute as pc 39 from multiprocess import Pool, RLock 40 from tqdm.auto import tqdm /opt/conda/lib/python3.7/site-packages/pyarrow/compute.py in <module> 16 # under the License. 17 ---> 18 from pyarrow._compute import ( # noqa 19 Function, 20 FunctionOptions, ImportError: /opt/conda/lib/python3.7/site-packages/pyarrow/_compute.cpython-37m-x86_64-linux-gnu.so: undefined symbol: _ZNK5arrow7compute15KernelSignature8ToStringEv ``` ## Environment info <!-- You can run the command `datasets-cli env` and copy-and-paste its output below. --> - `datasets` version: 1.9.0 - Platform: Kaggle - Python version: 3.7.10 - PyArrow version: 4.0.1

https://api.github.com/repos/huggingface/datasets/issues/2678/timeline

https://api.github.com/repos/huggingface/datasets/issues/2677

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2677/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2677/comments

https://api.github.com/repos/huggingface/datasets/issues/2677/events

https://github.com/huggingface/datasets/issues/2677

MDU6SXNzdWU5NDg0Mjk3ODg=

Error when downloading C4

closed

NONE

Hi, I am trying to download `en` corpus from C4 dataset. However, I get an error caused by validation files download (see image). My code is very primitive: `datasets.load_dataset('c4', 'en')` Is this a bug or do I have some configurations missing on my server? Thanks! <img width="1014" alt="Снимок экрана 2021-07-20 в 11 37 17" src="https://user-images.githubusercontent.com/36672861/126289448-6e0db402-5f3f-485a-bf74-eb6e0271fc25.png">

https://api.github.com/repos/huggingface/datasets/issues/2677/timeline

https://api.github.com/repos/huggingface/datasets/issues/2676

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2676/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2676/comments

https://api.github.com/repos/huggingface/datasets/issues/2676/events

https://github.com/huggingface/datasets/pull/2676

MDExOlB1bGxSZXF1ZXN0NjkyNjc2NTg5

Increase json reader block_size automatically

closed

MEMBER

Currently some files can't be read with the default parameters of the JSON lines reader. For example this one: https://huggingface.co/datasets/thomwolf/codeparrot/resolve/main/file-000000000006.json.gz raises a pyarrow error: ```python ArrowInvalid: straddling object straddles two block boundaries (try to increase block size?) ``` The block size that is used is the default one by pyarrow (related to this [jira issue](https://issues.apache.org/jira/browse/ARROW-9612)). To fix this issue I changed the block_size to increase automatically if there is a straddling issue when parsing a batch of json lines. By default the value is `chunksize // 32` in order to leverage multithreading, and it doubles every time a straddling issue occurs. The block_size is then reset for each file. cc @thomwolf @albertvillanova

https://api.github.com/repos/huggingface/datasets/issues/2676/timeline

https://api.github.com/repos/huggingface/datasets/issues/2675

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2675/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2675/comments

https://api.github.com/repos/huggingface/datasets/issues/2675/events

https://github.com/huggingface/datasets/pull/2675

MDExOlB1bGxSZXF1ZXN0NjkyNjEwNTA1

Parallelize ETag requests

closed

MEMBER

Since https://github.com/huggingface/datasets/pull/2628 we use the ETag or the remote data files to compute the directory in the cache where a dataset is saved. This is useful in order to reload the dataset from the cache only if the remote files haven't changed. In this I made the ETag requests parallel using multithreading. There is also a tqdm progress bar that shows up if there are more than 16 data files.

https://api.github.com/repos/huggingface/datasets/issues/2675/timeline

https://api.github.com/repos/huggingface/datasets/issues/2674

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2674/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2674/comments

https://api.github.com/repos/huggingface/datasets/issues/2674/events

https://github.com/huggingface/datasets/pull/2674

MDExOlB1bGxSZXF1ZXN0NjkyMzMzODU3

Fix sacrebleu parameter name

closed

MEMBER

DONE: - Fix parameter name: `smooth` to `smooth_method`. - Improve kwargs description. - Align docs on using a metric. - Add example of passing additional arguments in using metrics. Related to #2669.

https://api.github.com/repos/huggingface/datasets/issues/2674/timeline

https://api.github.com/repos/huggingface/datasets/issues/2673

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2673/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2673/comments

https://api.github.com/repos/huggingface/datasets/issues/2673/events

https://github.com/huggingface/datasets/pull/2673

MDExOlB1bGxSZXF1ZXN0NjkyMzAxMTgw

Fix potential DuplicatedKeysError in SQuAD

closed

MEMBER

DONE: - Fix potential DiplicatedKeysError by ensuring keys are unique. - Align examples in the docs with SQuAD code. We should promote as a good practice, that the keys should be programmatically generated as unique, instead of read from data (which might be not unique).

https://api.github.com/repos/huggingface/datasets/issues/2673/timeline

https://api.github.com/repos/huggingface/datasets/issues/2672

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2672/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2672/comments

https://api.github.com/repos/huggingface/datasets/issues/2672/events

https://github.com/huggingface/datasets/pull/2672

MDExOlB1bGxSZXF1ZXN0NjkyMjk2NDQ4

Fix potential DuplicatedKeysError in LibriSpeech

closed

MEMBER

DONE: - Fix unnecessary path join. - Fix potential DiplicatedKeysError by ensuring keys are unique. We should promote as a good practice, that the keys should be programmatically generated as unique, instead of read from data (which might be not unique).

https://api.github.com/repos/huggingface/datasets/issues/2672/timeline

https://api.github.com/repos/huggingface/datasets/issues/2671

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2671/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2671/comments

https://api.github.com/repos/huggingface/datasets/issues/2671/events

https://github.com/huggingface/datasets/pull/2671

MDExOlB1bGxSZXF1ZXN0NjkyMjc5MTM0

Mesinesp development and training data sets have been added.

closed

NONE

https://zenodo.org/search?page=1&size=20&q=mesinesp, Mesinesp has Medical Semantic Indexed records in Spanish. Indexing is done using DeCS codes, a sort of Spanish equivalent to MeSH terms. The Mesinesp (Spanish BioASQ track, see https://temu.bsc.es/mesinesp) development set has a total of 750 records. The Mesinesp (Spanish BioASQ track, see https://temu.bsc.es/mesinesp) training set has a total of 369,368 records.

https://api.github.com/repos/huggingface/datasets/issues/2671/timeline

https://api.github.com/repos/huggingface/datasets/issues/2670

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2670/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2670/comments

https://api.github.com/repos/huggingface/datasets/issues/2670/events

https://github.com/huggingface/datasets/issues/2670

MDU6SXNzdWU5NDcxMjA3MDk=

Using sharding to parallelize indexing

open

CONTRIBUTOR

**Is your feature request related to a problem? Please describe.** Creating an elasticsearch index on large dataset could be quite long and cannot be parallelized on shard (the index creation is colliding) **Describe the solution you'd like** When working on dataset shards, if an index already exists, its mapping should be checked and if compatible, the indexing process should continue with the shard data. Additionally, at the end of the process, the `_indexes` dict should be send back to the original dataset object (from which the shards have been created) to allow to use the index for later filtering on the whole dataset. **Describe alternatives you've considered** Each dataset shard could created independent partial indices. then on the whole dataset level, indices should be all referred in `_indexes` dict and be used in querying through `get_nearest_examples()`. The drawback is that the scores will be computed independently on the partial indices leading to inconsistent values for most scoring based on corpus level statistics (tf/idf, BM25). **Additional context** The objectives is to parallelize the index creation to speed-up the process (ie surcharging the ES server which is fine to handle large load) while later enabling search on the whole dataset.

https://api.github.com/repos/huggingface/datasets/issues/2670/timeline

https://api.github.com/repos/huggingface/datasets/issues/2669

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2669/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2669/comments

https://api.github.com/repos/huggingface/datasets/issues/2669/events

https://github.com/huggingface/datasets/issues/2669

MDU6SXNzdWU5NDY5ODI5OTg=

Metric kwargs are not passed to underlying external metric f1_score

closed

CONTRIBUTOR

## Describe the bug When I want to use F1 score with average="min", this keyword argument does not seem to be passed through to the underlying sklearn metric. This is evident because [sklearn](https://scikit-learn.org/stable/modules/generated/sklearn.metrics.f1_score.html) throws an error telling me so. ## Steps to reproduce the bug ```python import datasets f1 = datasets.load_metric("f1", keep_in_memory=True, average="min") f1.add_batch(predictions=[0,2,3], references=[1, 2, 3]) f1.compute() ``` ## Expected results No error, because `average="min"` should be passed correctly to f1_score in sklearn. ## Actual results ``` Traceback (most recent call last): File "<stdin>", line 1, in <module> File "C:\Users\bramv\.virtualenvs\pipeline-TpEsXVex\lib\site-packages\datasets\metric.py", line 402, in compute output = self._compute(predictions=predictions, references=references, **kwargs) File "C:\Users\bramv\.cache\huggingface\modules\datasets_modules\metrics\f1\82177930a325d4c28342bba0f116d73f6d92fb0c44cd67be32a07c1262b61cfe\f1.py", line 97, in _compute "f1": f1_score( File "C:\Users\bramv\.virtualenvs\pipeline-TpEsXVex\lib\site-packages\sklearn\utils\validation.py", line 63, in inner_f return f(*args, **kwargs) File "C:\Users\bramv\.virtualenvs\pipeline-TpEsXVex\lib\site-packages\sklearn\metrics\_classification.py", line 1071, in f1_score return fbeta_score(y_true, y_pred, beta=1, labels=labels, File "C:\Users\bramv\.virtualenvs\pipeline-TpEsXVex\lib\site-packages\sklearn\utils\validation.py", line 63, in inner_f return f(*args, **kwargs) File "C:\Users\bramv\.virtualenvs\pipeline-TpEsXVex\lib\site-packages\sklearn\metrics\_classification.py", line 1195, in fbeta_score _, _, f, _ = precision_recall_fscore_support(y_true, y_pred, File "C:\Users\bramv\.virtualenvs\pipeline-TpEsXVex\lib\site-packages\sklearn\utils\validation.py", line 63, in inner_f return f(*args, **kwargs) File "C:\Users\bramv\.virtualenvs\pipeline-TpEsXVex\lib\site-packages\sklearn\metrics\_classification.py", line 1464, in precision_recall_fscore_support labels = _check_set_wise_labels(y_true, y_pred, average, labels, File "C:\Users\bramv\.virtualenvs\pipeline-TpEsXVex\lib\site-packages\sklearn\metrics\_classification.py", line 1294, in _check_set_wise_labels raise ValueError("Target is %s but average='binary'. Please " ValueError: Target is multiclass but average='binary'. Please choose another average setting, one of [None, 'micro', 'macro', 'weighted']. ``` ## Environment info <!-- You can run the command `datasets-cli env` and copy-and-paste its output below. --> - `datasets` version: 1.9.0 - Platform: Windows-10-10.0.19041-SP0 - Python version: 3.9.2 - PyArrow version: 4.0.1

https://api.github.com/repos/huggingface/datasets/issues/2669/timeline

https://api.github.com/repos/huggingface/datasets/issues/2668

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2668/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2668/comments

https://api.github.com/repos/huggingface/datasets/issues/2668/events

https://github.com/huggingface/datasets/pull/2668

MDExOlB1bGxSZXF1ZXN0NjkxOTY1MTY1

Add Russian SuperGLUE

closed

CONTRIBUTOR

Hi, This adds the [Russian SuperGLUE](https://russiansuperglue.com/) dataset. For the most part I reused the code for the original SuperGLUE, although there are some relatively minor differences in the structure that I accounted for.

https://api.github.com/repos/huggingface/datasets/issues/2668/timeline

https://api.github.com/repos/huggingface/datasets/issues/2667

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2667/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2667/comments

https://api.github.com/repos/huggingface/datasets/issues/2667/events

https://github.com/huggingface/datasets/pull/2667

MDExOlB1bGxSZXF1ZXN0NjkxOTYwNzc3

Use tqdm from tqdm_utils

closed

CONTRIBUTOR

This PR replaces `tqdm` from the `tqdm` lib with `tqdm` from `datasets.utils.tqdm_utils`. With this change, it's possible to disable progress bars just by calling `disable_progress_bar`. Note this doesn't work on Windows when using multiprocessing due to how global variables are shared between processes. Currently, there is no easy way to disable progress bars in a multiprocess setting on Windows (patching logging with `datasets.utils.logging.get_verbosity = lambda: datasets.utils.logging.NOTSET` doesn't seem to work as well), so adding support for this is a future goal. Additionally, this PR adds a unit ("ba" for batches) to the bar printed by `Dataset.to_json` (this change is motivated by https://github.com/huggingface/datasets/issues/2657).

https://api.github.com/repos/huggingface/datasets/issues/2667/timeline

https://api.github.com/repos/huggingface/datasets/issues/2666

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2666/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2666/comments

https://api.github.com/repos/huggingface/datasets/issues/2666/events

https://github.com/huggingface/datasets/pull/2666

MDExOlB1bGxSZXF1ZXN0NjkxOTMzMDM1

Adds CodeClippy dataset [WIP]

open

NONE

CodeClippy is an opensource code dataset scrapped from github during flax-jax-community-week https://the-eye.eu/public/AI/training_data/code_clippy_data/

https://api.github.com/repos/huggingface/datasets/issues/2666/timeline

https://api.github.com/repos/huggingface/datasets/issues/2665

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2665/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2665/comments

https://api.github.com/repos/huggingface/datasets/issues/2665/events

https://github.com/huggingface/datasets/pull/2665

MDExOlB1bGxSZXF1ZXN0NjkxOTMwNjky

Adds APPS dataset to the hub [WIP]

open

NONE

A loading script for [APPS dataset](https://github.com/hendrycks/apps)

https://api.github.com/repos/huggingface/datasets/issues/2665/timeline

https://api.github.com/repos/huggingface/datasets/issues/2663

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2663/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2663/comments

https://api.github.com/repos/huggingface/datasets/issues/2663/events

https://github.com/huggingface/datasets/issues/2663

MDU6SXNzdWU5NDY1NTIyNzM=

[`to_json`] add multi-proc sharding support

closed

MEMBER

As discussed on slack it appears that `to_json` is quite slow on huge datasets like OSCAR. I implemented sharded saving, which is much much faster - but the tqdm bars all overwrite each other, so it's hard to make sense of the progress, so if possible ideally this multi-proc support could be implemented internally in `to_json` via `num_proc` argument. I guess `num_proc` will be the number of shards? I think the user will need to use this feature wisely, since too many processes writing to say normal style HD is likely to be slower than one process. I'm not sure whether the user should be responsible to concatenate the shards at the end or `datasets`, either way works for my needs. The code I was using: ``` from multiprocessing import cpu_count, Process, Queue [...] filtered_dataset = concat_dataset.map(filter_short_documents, batched=True, batch_size=256, num_proc=cpu_count()) DATASET_NAME = "oscar" SHARDS = 10 def process_shard(idx): print(f"Sharding {idx}") ds_shard = filtered_dataset.shard(SHARDS, idx, contiguous=True) # ds_shard = ds_shard.shuffle() # remove contiguous=True above if shuffling print(f"Saving {DATASET_NAME}-{idx}.jsonl") ds_shard.to_json(f"{DATASET_NAME}-{idx}.jsonl", orient="records", lines=True, force_ascii=False) queue = Queue() processes = [Process(target=process_shard, args=(idx,)) for idx in range(SHARDS)] for p in processes: p.start() for p in processes: p.join() ``` Thank you! @lhoestq

https://api.github.com/repos/huggingface/datasets/issues/2663/timeline

https://api.github.com/repos/huggingface/datasets/issues/2662

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2662/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2662/comments

https://api.github.com/repos/huggingface/datasets/issues/2662/events

https://github.com/huggingface/datasets/pull/2662

MDExOlB1bGxSZXF1ZXN0NjkxNjM5MjU5

Load Dataset from the Hub (NO DATASET SCRIPT)

closed

MEMBER

## Load the data from any Dataset repository on the Hub This PR adds support for loading datasets from any dataset repository on the hub, without requiring any dataset script. As a user it's now possible to create a repo and upload some csv/json/text/parquet files, and then be able to load the data in one line. Here is an example with the `allenai/c4` repository that contains a lot of compressed json lines files: ```python from datasets import load_dataset data_files = {"train": "en/c4-train.*.json.gz"} c4 = load_dataset("allenai/c4", data_files=data_files, split="train", streaming=True) print(c4.n_shards) # 1024 print(next(iter(c4))) # {'text': 'Beginners BBQ Class Takin...'} ``` By default it loads all the files, but as shown in the example you can choose the ones you want with unix style patterns. Of course it's still possible to use dataset scripts since they offer the most flexibility. ## Implementation details It uses `huggingface_hub` to list the files in a dataset repository. If you provide a path to a local directory instead of a repository name, it works the same way but it uses `glob`. Depending on the data files available, or passed in the `data_files` parameter, one of the available builders will be used among the csv, json, text and parquet builders. Because of this, it's not possible to load both csv and json files at once. In this case you have to load them separately and then concatenate the two datasets for example. ## TODO - [x] tests - [x] docs - [x] when huggingface_hub gets a new release, update the CI and the setup.py Close https://github.com/huggingface/datasets/issues/2629

https://api.github.com/repos/huggingface/datasets/issues/2662/timeline

https://api.github.com/repos/huggingface/datasets/issues/2661

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2661/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2661/comments

https://api.github.com/repos/huggingface/datasets/issues/2661/events

https://github.com/huggingface/datasets/pull/2661

MDExOlB1bGxSZXF1ZXN0NjkxNjE5MzAz

Add SD task for SUPERB

closed

MEMBER

Include the SD (Speaker Diarization) task as described in the [SUPERB paper](https://arxiv.org/abs/2105.01051) and `s3prl` [instructions](https://github.com/s3prl/s3prl/tree/master/s3prl/downstream#sd-speaker-diarization). TODO: - [x] Generate the LibriMix corpus - [x] Prepare the corpus for diarization - [x] Upload these files to the superb-data repo - [x] Transcribe the corresponding s3prl processing of these files into our superb loading script - [x] README: tags + description sections - ~~Add DER metric~~ (we leave the DER metric for a follow-up PR) Related to #2619. Close #2653. cc: @lewtun

https://api.github.com/repos/huggingface/datasets/issues/2661/timeline

https://api.github.com/repos/huggingface/datasets/issues/2660

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2660/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2660/comments

https://api.github.com/repos/huggingface/datasets/issues/2660/events

https://github.com/huggingface/datasets/pull/2660

MDExOlB1bGxSZXF1ZXN0NjkxNTA4NzE0

Move checks from _map_single to map

closed

CONTRIBUTOR

The goal of this PR is to remove duplicated checks in the `map` logic to execute them only once whenever possible (`fn_kwargs`, `input_columns`, ...). Additionally, this PR improves the consistency (to align it with `input_columns`) of the `remove_columns` check by adding support for a single string value, which is then wrapped into a list.

https://api.github.com/repos/huggingface/datasets/issues/2660/timeline

https://api.github.com/repos/huggingface/datasets/issues/2659

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2659/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2659/comments

https://api.github.com/repos/huggingface/datasets/issues/2659/events

https://github.com/huggingface/datasets/pull/2659

MDExOlB1bGxSZXF1ZXN0NjkxMzcwNzU3

Allow dataset config kwargs to be None

closed

MEMBER

Close https://github.com/huggingface/datasets/issues/2658 The dataset config kwargs that were set to None we simply ignored. This was an issue when None has some meaning for certain parameters of certain builders, like the `sep` parameter of the "csv" builder that allows to infer to separator. cc @SBrandeis

https://api.github.com/repos/huggingface/datasets/issues/2659/timeline

https://api.github.com/repos/huggingface/datasets/issues/2658

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2658/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2658/comments

https://api.github.com/repos/huggingface/datasets/issues/2658/events

https://github.com/huggingface/datasets/issues/2658

MDU6SXNzdWU5NDYxMzk1MzI=

Can't pass `sep=None` to load_dataset("csv", ...) to infer the separator via pandas.read_csv

closed

MEMBER

When doing `load_dataset("csv", sep=None)`, the `sep` passed to `pd.read_csv` is still the default `sep=","` instead, which makes it impossible to make the csv loader infer the separator. Related to https://github.com/huggingface/datasets/pull/2656 cc @SBrandeis

https://api.github.com/repos/huggingface/datasets/issues/2658/timeline

https://api.github.com/repos/huggingface/datasets/issues/2657

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2657/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2657/comments

https://api.github.com/repos/huggingface/datasets/issues/2657/events

https://github.com/huggingface/datasets/issues/2657

MDU6SXNzdWU5NDU4MjI4Mjk=

`to_json` reporting enhancements

open

MEMBER

While using `to_json` 2 things came to mind that would have made the experience easier on the user: 1. Could we have a `desc` arg for the tqdm use and a fallback to just `to_json` so that it'd be clear to the user what's happening? Surely, one can just print the description before calling json, but I thought perhaps it'd help to have it self-identify like you did for other progress bars recently. 2. It took me a while to make sense of the reported numbers: ``` 22%|██▏ | 1536/7076 [12:30:57<44:09:42, 28.70s/it] ``` So iteration here happens to be 10K samples, and the total is 70M records. But the user does't know that, so the progress bar is perfect, but the numbers it reports are meaningless until one discovers that 1it=10K samples. And one still has to convert these in the head - so it's not quick. Not exactly sure what's the best way to approach this, perhaps it can be part of `desc`? or report M or K, so it'd be built-in if it were to print, e.g.: ``` 22%|██▏ | 15360K/70760K [12:30:57<44:09:42, 28.70s/it] ``` or ``` 22%|██▏ | 15.36M/70.76M [12:30:57<44:09:42, 28.70s/it] ``` (while of course remaining friendly to small datasets) I forget if tqdm lets you add a magnitude identifier to the running count. Thank you!

https://api.github.com/repos/huggingface/datasets/issues/2657/timeline

https://api.github.com/repos/huggingface/datasets/issues/2656

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2656/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2656/comments

https://api.github.com/repos/huggingface/datasets/issues/2656/events

https://github.com/huggingface/datasets/pull/2656

MDExOlB1bGxSZXF1ZXN0NjkwNzUzNjA3

Change `from_csv` default arguments

closed

CONTRIBUTOR

Passing `sep=None` to pandas's `read_csv` lets pandas guess the CSV file's separator This PR allows users to use this pandas's feature by passing `sep=None` to `Dataset.from_csv`: ```python Dataset.from_csv( ..., sep=None ) ```

https://api.github.com/repos/huggingface/datasets/issues/2656/timeline

https://api.github.com/repos/huggingface/datasets/issues/2655

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2655/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2655/comments

https://api.github.com/repos/huggingface/datasets/issues/2655/events

https://github.com/huggingface/datasets/issues/2655

MDU6SXNzdWU5NDUzODI3MjM=

Allow the selection of multiple columns at once

open

CONTRIBUTOR

**Is your feature request related to a problem? Please describe.** Similar to pandas, it would be great if we could select multiple columns at once. **Describe the solution you'd like** ```python my_dataset = ... # Has columns ['idx', 'sentence', 'label'] idx, label = my_dataset[['idx', 'label']] ``` **Describe alternatives you've considered** we can do `[dataset[col] for col in ('idx', 'label')]` **Additional context** This is of course very minor.

https://api.github.com/repos/huggingface/datasets/issues/2655/timeline

https://api.github.com/repos/huggingface/datasets/issues/2654

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2654/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2654/comments

https://api.github.com/repos/huggingface/datasets/issues/2654/events

https://github.com/huggingface/datasets/issues/2654

MDU6SXNzdWU5NDUxNjcyMzE=

Give a user feedback if the dataset he loads is streamable or not

open

MEMBER

**Is your feature request related to a problem? Please describe.** I would love to know if a `dataset` is with the current implementation streamable or not. **Describe the solution you'd like** We could show a warning when a dataset is loaded with `load_dataset('...',streaming=True)` when its lot streamable, e.g. if it is an archive. **Describe alternatives you've considered** Add a new metadata tag for "streaming"

https://api.github.com/repos/huggingface/datasets/issues/2654/timeline

https://api.github.com/repos/huggingface/datasets/issues/2653

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2653/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2653/comments

https://api.github.com/repos/huggingface/datasets/issues/2653/events

https://github.com/huggingface/datasets/issues/2653

MDU6SXNzdWU5NDUxMDIzMjE=

Add SD task for SUPERB

closed

MEMBER

Include the SD (Speaker Diarization) task as described in the [SUPERB paper](https://arxiv.org/abs/2105.01051) and `s3prl` [instructions](https://github.com/s3prl/s3prl/tree/master/s3prl/downstream#sd-speaker-diarization). Steps: - [x] Generate the LibriMix corpus - [x] Prepare the corpus for diarization - [x] Upload these files to the superb-data repo - [x] Transcribe the corresponding s3prl processing of these files into our superb loading script - [ ] README: tags + description sections Related to #2619. cc: @lewtun

https://api.github.com/repos/huggingface/datasets/issues/2653/timeline

https://api.github.com/repos/huggingface/datasets/issues/2652

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2652/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2652/comments

https://api.github.com/repos/huggingface/datasets/issues/2652/events

https://github.com/huggingface/datasets/pull/2652

MDExOlB1bGxSZXF1ZXN0NjkwMjg0MTI4

Fix logging docstring

closed

CONTRIBUTOR

Remove "no tqdm bars" from the docstring in the logging module to align it with the changes introduced in #2534.

https://api.github.com/repos/huggingface/datasets/issues/2652/timeline

https://api.github.com/repos/huggingface/datasets/issues/2651

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2651/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2651/comments

https://api.github.com/repos/huggingface/datasets/issues/2651/events

https://github.com/huggingface/datasets/issues/2651

MDU6SXNzdWU5NDQ3OTY5NjE=

Setting log level higher than warning does not suppress progress bar

closed

NONE

## Describe the bug I would like to disable progress bars for `.map` method (and other methods like `.filter` and `load_dataset` as well). According to #1627 one can suppress it by setting log level higher than `warning`, however doing so doesn't suppress it with version 1.9.0. I also tried to set `DATASETS_VERBOSITY` environment variable to `error` or `critical` but it also didn't work. ## Steps to reproduce the bug ```python import datasets from datasets.utils.logging import set_verbosity_error set_verbosity_error() def dummy_map(batch): return batch common_voice_train = datasets.load_dataset("common_voice", "de", split="train") common_voice_test = datasets.load_dataset("common_voice", "de", split="test") common_voice_train.map(dummy_map) ``` ## Expected results - The progress bar for `.map` call won't be shown ## Actual results - The progress bar for `.map` is still shown ## Environment info <!-- You can run the command `datasets-cli env` and copy-and-paste its output below. --> - `datasets` version: 1.9.0 - Platform: Linux-5.4.0-1045-aws-x86_64-with-Ubuntu-18.04-bionic - Python version: 3.7.5 - PyArrow version: 4.0.1

https://api.github.com/repos/huggingface/datasets/issues/2651/timeline

https://api.github.com/repos/huggingface/datasets/issues/2650

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2650/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2650/comments

https://api.github.com/repos/huggingface/datasets/issues/2650/events

https://github.com/huggingface/datasets/issues/2650

MDU6SXNzdWU5NDQ2NzI1NjU=

[load_dataset] shard and parallelize the process

open

MEMBER

- Some huge datasets take forever to build the first time. (e.g. oscar/en) as it's done in a single cpu core. - If the build crashes, everything done up to that point gets lost Request: Shard the build over multiple arrow files, which would enable: - much faster build by parallelizing the build process - if the process crashed, the completed arrow files don't need to be re-built again Thank you! @lhoestq

https://api.github.com/repos/huggingface/datasets/issues/2650/timeline

https://api.github.com/repos/huggingface/datasets/issues/2649

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2649/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2649/comments

https://api.github.com/repos/huggingface/datasets/issues/2649/events

https://github.com/huggingface/datasets/issues/2649

MDU6SXNzdWU5NDQ2NTEyMjk=

adding progress bar / ETA for `load_dataset`

open

MEMBER

Please consider: ``` Downloading and preparing dataset oscar/unshuffled_deduplicated_en (download: 462.40 GiB, generated: 1.18 TiB, post-processed: Unknown size, total: 1.63 TiB) to cache/oscar/unshuffled_deduplicated_en/1.0.0/84838bd49d2295f62008383b05620571535451d84545037bb94d6f3501651df2... HF google storage unreachable. Downloading and preparing it from source ``` and no indication whatsoever of whether things work well or when it'll be done. It's important to have an estimated completion time for when doing slurm jobs since some instances have a cap on run-time. I think for this particular job it sat for 30min in total silence and then after 30min it started generating: ``` 897850 examples [07:24, 10286.71 examples/s] ``` which is already great! Request: 1. ETA - knowing how many hours to allocate for a slurm job 2. progress bar - helps to know things are working and aren't stuck and where we are at. Thank you! @lhoestq

https://api.github.com/repos/huggingface/datasets/issues/2649/timeline

https://api.github.com/repos/huggingface/datasets/issues/2648

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2648/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2648/comments

https://api.github.com/repos/huggingface/datasets/issues/2648/events

https://github.com/huggingface/datasets/issues/2648

MDU6SXNzdWU5NDQ0ODQ1MjI=

Add web_split dataset for Paraphase and Rephrase benchmark

open

CONTRIBUTOR

## Describe: For getting simple sentences from complex sentence there are dataset and task like wiki_split that is available in hugging face datasets. This web_split is a very similar dataset. There some research paper which states that by combining these two datasets we if we train the model it will yield better results on both tests data. This dataset is made from web NLG data. All the dataset related details are provided in the below repository Github link: https://github.com/shashiongithub/Split-and-Rephrase

https://api.github.com/repos/huggingface/datasets/issues/2648/timeline

https://api.github.com/repos/huggingface/datasets/issues/2647

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2647/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2647/comments

https://api.github.com/repos/huggingface/datasets/issues/2647/events

https://github.com/huggingface/datasets/pull/2647

MDExOlB1bGxSZXF1ZXN0Njg5OTExMzky

Fix anchor in README

closed

CONTRIBUTOR

I forgot to push this fix in #2611, so I'm sending it now.

https://api.github.com/repos/huggingface/datasets/issues/2647/timeline

https://api.github.com/repos/huggingface/datasets/issues/2646

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2646/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2646/comments

https://api.github.com/repos/huggingface/datasets/issues/2646/events

https://github.com/huggingface/datasets/issues/2646

MDU6SXNzdWU5NDQzNzk5NTQ=

downloading of yahoo_answers_topics dataset failed

open

NONE

## Describe the bug I get an error datasets.utils.info_utils.NonMatchingChecksumError: Checksums didn't match for dataset source files when I try to download the yahoo_answers_topics dataset ## Steps to reproduce the bug self.dataset = load_dataset( 'yahoo_answers_topics', cache_dir=self.config['yahoo_cache_dir'], split='train[:90%]') # Sample code to reproduce the bug self.dataset = load_dataset( 'yahoo_answers_topics', cache_dir=self.config['yahoo_cache_dir'], split='train[:90%]') ## Expected results A clear and concise description of the expected results. ## Actual results Specify the actual results or traceback. datasets.utils.info_utils.NonMatchingChecksumError: Checksums didn't match for dataset source files

https://api.github.com/repos/huggingface/datasets/issues/2646/timeline

https://api.github.com/repos/huggingface/datasets/issues/2645

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2645/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2645/comments

https://api.github.com/repos/huggingface/datasets/issues/2645/events

https://github.com/huggingface/datasets/issues/2645

MDU6SXNzdWU5NDQzNzQyODQ=

load_dataset processing failed with OS error after downloading a dataset

closed

NONE

## Describe the bug After downloading a dataset like opus100, there is a bug that OSError: Cannot find data file. Original error: dlopen: cannot load any more object with static TLS ## Steps to reproduce the bug ```python from datasets import load_dataset this_dataset = load_dataset('opus100', 'af-en') ``` ## Expected results there is no error when running load_dataset. ## Actual results Specify the actual results or traceback. Traceback (most recent call last): File "/home/anaconda3/lib/python3.6/site-packages/datasets/builder.py", line 652, in _download_and_prep self._prepare_split(split_generator, **prepare_split_kwargs) File "/home/anaconda3/lib/python3.6/site-packages/datasets/builder.py", line 989, in _prepare_split example = self.info.features.encode_example(record) File "/home/anaconda3/lib/python3.6/site-packages/datasets/features.py", line 952, in encode_example example = cast_to_python_objects(example) File "/home/anaconda3/lib/python3.6/site-packages/datasets/features.py", line 219, in cast_to_python_ob return _cast_to_python_objects(obj)[0] File "/home/anaconda3/lib/python3.6/site-packages/datasets/features.py", line 165, in _cast_to_python_o import torch File "/home/anaconda3/lib/python3.6/site-packages/torch/__init__.py", line 188, in <module> _load_global_deps() File "/home/anaconda3/lib/python3.6/site-packages/torch/__init__.py", line 141, in _load_global_deps ctypes.CDLL(lib_path, mode=ctypes.RTLD_GLOBAL) File "/home/anaconda3/lib/python3.6/ctypes/__init__.py", line 348, in __init__ self._handle = _dlopen(self._name, mode) OSError: dlopen: cannot load any more object with static TLS During handling of the above exception, another exception occurred: Traceback (most recent call last): File "download_hub_opus100.py", line 9, in <module> this_dataset = load_dataset('opus100', language_pair) File "/home/anaconda3/lib/python3.6/site-packages/datasets/load.py", line 748, in load_dataset use_auth_token=use_auth_token, File "/home/anaconda3/lib/python3.6/site-packages/datasets/builder.py", line 575, in download_and_prepa dl_manager=dl_manager, verify_infos=verify_infos, **download_and_prepare_kwargs File "/home/anaconda3/lib/python3.6/site-packages/datasets/builder.py", line 658, in _download_and_prep + str(e) OSError: Cannot find data file. Original error: dlopen: cannot load any more object with static TLS ## Environment info - `datasets` version: 1.8.0 - Platform: Linux-3.13.0-32-generic-x86_64-with-debian-jessie-sid - Python version: 3.6.6 - PyArrow version: 3.0.0

https://api.github.com/repos/huggingface/datasets/issues/2645/timeline

https://api.github.com/repos/huggingface/datasets/issues/2644

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2644/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2644/comments

https://api.github.com/repos/huggingface/datasets/issues/2644/events

https://github.com/huggingface/datasets/issues/2644

MDU6SXNzdWU5NDQyNTQ3NDg=

Batched `map` not allowed to return 0 items

closed

CONTRIBUTOR

## Describe the bug I'm trying to use `map` to filter a large dataset by selecting rows that match an expensive condition (files referenced by one of the columns need to exist in the filesystem, so we have to `stat` them). According to [the documentation](https://huggingface.co/docs/datasets/processing.html#augmenting-the-dataset), `a batch mapped function can take as input a batch of size N and return a batch of size M where M can be greater or less than N and can even be zero`. However, when the returned batch has a size of zero (neither item in the batch fulfilled the condition), we get an `index out of bounds` error. I think that `arrow_writer.py` is [trying to infer the returned types using the first element returned](https://github.com/huggingface/datasets/blob/master/src/datasets/arrow_writer.py#L100), but no elements were returned in this case. For this error to happen, I'm returning a dictionary that contains empty lists for the keys I want to keep, see below. If I return an empty dictionary instead (no keys), then a different error eventually occurs. ## Steps to reproduce the bug ```python def select_rows(examples): # `key` is a column name that exists in the original dataset # The following line simulates no matches found, so we return an empty batch result = {'key': []} return result filtered_dataset = dataset.map( select_rows, remove_columns = dataset.column_names, batched = True, num_proc = 1, desc = "Selecting rows with images that exist" ) ``` The code above immediately triggers the exception. If we use the following instead: ```python def select_rows(examples): # `key` is a column name that exists in the original dataset result = {'key': []} # or defaultdict or whatever # code to check for condition and append elements to result # some_items_found will be set to True if there were any matching elements in the batch return result if some_items_found else {} ``` Then it _seems_ to work, but it eventually fails with some sort of schema error. I believe it may happen when an empty batch is followed by a non-empty one, but haven't set up a test to verify it. In my opinion, returning a dictionary with empty lists and valid column names should be accepted as a valid result with zero items. ## Expected results The dataset would be filtered and only the matching fields would be returned. ## Actual results An exception is encountered, as described. Using a workaround makes it fail further along the line. ## Environment info <!-- You can run the command `datasets-cli env` and copy-and-paste its output below. --> - `datasets` version: 1.9.1.dev0 - Platform: Linux-5.4.0-53-generic-x86_64-with-glibc2.17 - Python version: 3.8.10 - PyArrow version: 4.0.1

https://api.github.com/repos/huggingface/datasets/issues/2644/timeline

https://api.github.com/repos/huggingface/datasets/issues/2643

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2643/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2643/comments

https://api.github.com/repos/huggingface/datasets/issues/2643/events

https://github.com/huggingface/datasets/issues/2643

MDU6SXNzdWU5NDQyMjAyNzM=

Enum used in map functions will raise a RecursionError with dill.

open

NONE

## Describe the bug Enums used in functions pass to `map` will fail at pickling with a maximum recursion exception as described here: https://github.com/uqfoundation/dill/issues/250#issuecomment-852566284 In my particular case, I use an enum to define an argument with fixed options using the `TraininigArguments` dataclass as base class and the `HfArgumentParser`. In the same file I use a `ds.map` that tries to pickle the content of the module including the definition of the enum that runs into the dill bug described above. ## Steps to reproduce the bug ```python from datasets import load_dataset from enum import Enum class A(Enum): a = 'a' def main(): a = A.a def f(x): return {} if a == a.a else x ds = load_dataset('cnn_dailymail', '3.0.0')['test'] ds = ds.map(f, num_proc=15) if __name__ == "__main__": main() ``` ## Expected results The known problem with dill could be prevented as explained in the link above (workaround.) Since `HFArgumentParser` nicely uses the enum class for choices it makes sense to also deal with this bug under the hood. ## Actual results ```python File "/home/xxxx/miniconda3/lib/python3.8/site-packages/dill/_dill.py", line 1373, in save_type pickler.save_reduce(_create_type, (type(obj), obj.__name__, File "/home/xxxx/miniconda3/lib/python3.8/pickle.py", line 690, in save_reduce save(args) File "/home/xxxx/miniconda3/lib/python3.8/pickle.py", line 558, in save f(self, obj) # Call unbound method with explicit self File "/home/xxxx/miniconda3/lib/python3.8/pickle.py", line 899, in save_tuple save(element) File "/home/xxxx/miniconda3/lib/python3.8/pickle.py", line 534, in save self.framer.commit_frame() File "/home/xxxx/miniconda3/lib/python3.8/pickle.py", line 220, in commit_frame if f.tell() >= self._FRAME_SIZE_TARGET or force: RecursionError: maximum recursion depth exceeded while calling a Python object ``` ## Environment info - `datasets` version: 1.8.0 - Platform: Linux-5.9.0-4-amd64-x86_64-with-glibc2.10 - Python version: 3.8.5 - PyArrow version: 3.0.0

https://api.github.com/repos/huggingface/datasets/issues/2643/timeline

https://api.github.com/repos/huggingface/datasets/issues/2642

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2642/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2642/comments

https://api.github.com/repos/huggingface/datasets/issues/2642/events

https://github.com/huggingface/datasets/issues/2642

MDU6SXNzdWU5NDQxNzU2OTc=

Support multi-worker with streaming dataset (IterableDataset).

open

CONTRIBUTOR

**Is your feature request related to a problem? Please describe.** The current `.map` does not support multi-process, CPU can become bottleneck if the pre-processing is complex (e.g. t5 span masking). **Describe the solution you'd like** Ideally `.map` should support multi-worker like tfds, with `AUTOTUNE`. **Describe alternatives you've considered** A simpler solution is to shard the dataset and process it in parallel with pytorch dataloader. The shard does not need to be of equal size. * https://pytorch.org/docs/stable/data.html#torch.utils.data.IterableDataset **Additional context**

https://api.github.com/repos/huggingface/datasets/issues/2642/timeline

https://api.github.com/repos/huggingface/datasets/issues/2641

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2641/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2641/comments

https://api.github.com/repos/huggingface/datasets/issues/2641/events

https://github.com/huggingface/datasets/issues/2641

MDU6SXNzdWU5NDM4MzgwODU=

load_dataset("financial_phrasebank") NonMatchingChecksumError

open

NONE

## Describe the bug Attempting to download the financial_phrasebank dataset results in a NonMatchingChecksumError ## Steps to reproduce the bug ```python from datasets import load_dataset dataset = load_dataset("financial_phrasebank", 'sentences_allagree') ``` ## Expected results I expect to see the financial_phrasebank dataset downloaded successfully ## Actual results NonMatchingChecksumError: Checksums didn't match for dataset source files: ['https://www.researchgate.net/profile/Pekka_Malo/publication/251231364_FinancialPhraseBank-v10/data/0c96051eee4fb1d56e000000/FinancialPhraseBank-v10.zip'] ## Environment info - `datasets` version: 1.9.0 - Platform: Linux-4.14.232-177.418.amzn2.x86_64-x86_64-with-debian-10.6 - Python version: 3.7.10 - PyArrow version: 4.0.1

https://api.github.com/repos/huggingface/datasets/issues/2641/timeline

https://api.github.com/repos/huggingface/datasets/issues/2640

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2640/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2640/comments

https://api.github.com/repos/huggingface/datasets/issues/2640/events

https://github.com/huggingface/datasets/pull/2640

MDExOlB1bGxSZXF1ZXN0Njg5MjAxMDkw

Fix docstrings

closed

MEMBER

Fix rendering of some docstrings.

https://api.github.com/repos/huggingface/datasets/issues/2640/timeline

https://api.github.com/repos/huggingface/datasets/issues/2639

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2639/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2639/comments

https://api.github.com/repos/huggingface/datasets/issues/2639/events

https://github.com/huggingface/datasets/pull/2639

MDExOlB1bGxSZXF1ZXN0Njg5MTQ3NDE5

Refactor patching to specific submodule

closed

MEMBER

Minor reorganization of the code, so that additional patching functions (not related to streaming) might be created. In relation with the initial approach followed in #2631.

https://api.github.com/repos/huggingface/datasets/issues/2639/timeline

https://api.github.com/repos/huggingface/datasets/issues/2638

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2638/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2638/comments

https://api.github.com/repos/huggingface/datasets/issues/2638/events

https://github.com/huggingface/datasets/pull/2638

MDExOlB1bGxSZXF1ZXN0Njg5MTA5NTg1

Streaming for the Json loader

closed

MEMBER

It was not using `open` in the builder. Therefore `pyarrow.json.read_json` was downloading the full file to start yielding rows. Moreover, it appeared that `pyarrow.json.read_json` was not really suited for streaming as it was downloading too much data and failing if `block_size` was not properly configured (related to #2573). So I switched to using `open` which is extended to support reading from remote file progressively, and I removed the pyarrow json reader which was not practical. Instead, I'm using the classical `json.loads` from the standard library.

https://api.github.com/repos/huggingface/datasets/issues/2638/timeline

https://api.github.com/repos/huggingface/datasets/issues/2637

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2637/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2637/comments

https://api.github.com/repos/huggingface/datasets/issues/2637/events

https://github.com/huggingface/datasets/issues/2637

MDU6SXNzdWU5NDMyOTA3MzY=

Add the CIDEr metric?

open

NONE

Hi, I find the api in https://huggingface.co/metrics quite useful. I am playing around with video/image captioning task, where CIDEr is a popular metric. Do you plan to add this into the HF ```datasets``` library? Thanks.

https://api.github.com/repos/huggingface/datasets/issues/2637/timeline

https://api.github.com/repos/huggingface/datasets/issues/2636

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2636/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2636/comments

https://api.github.com/repos/huggingface/datasets/issues/2636/events

https://github.com/huggingface/datasets/pull/2636

MDExOlB1bGxSZXF1ZXN0Njg4NzEyMTY4

Streaming for the Pandas loader

closed

MEMBER

It was not using open in the builder. Therefore pd.read_pickle could fail when streaming from a private repo for example. Indeed, when streaming, open is extended to support reading from remote files and handles authentication to the HF Hub

https://api.github.com/repos/huggingface/datasets/issues/2636/timeline

https://api.github.com/repos/huggingface/datasets/issues/2635

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2635/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2635/comments

https://api.github.com/repos/huggingface/datasets/issues/2635/events

https://github.com/huggingface/datasets/pull/2635

MDExOlB1bGxSZXF1ZXN0Njg4Njk5OTM5

Streaming for the CSV loader

closed

MEMBER

It was not using `open` in the builder. Therefore `pd.read_csv` was downloading the full file to start yielding rows. Indeed, when streaming, `open` is extended to support reading from remote file progressively.

https://api.github.com/repos/huggingface/datasets/issues/2635/timeline

https://api.github.com/repos/huggingface/datasets/issues/2634

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2634/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2634/comments

https://api.github.com/repos/huggingface/datasets/issues/2634/events

https://github.com/huggingface/datasets/pull/2634

MDExOlB1bGxSZXF1ZXN0Njg4NDk2Mzc2

Inject ASR template for lj_speech dataset

closed

MEMBER

Related to: #2565, #2633. cc: @lewtun

https://api.github.com/repos/huggingface/datasets/issues/2634/timeline

https://api.github.com/repos/huggingface/datasets/issues/2633

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2633/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2633/comments

https://api.github.com/repos/huggingface/datasets/issues/2633/events

https://github.com/huggingface/datasets/pull/2633

MDExOlB1bGxSZXF1ZXN0Njg4MTMwOTA5

Update ASR tags

closed

MEMBER

This PR updates the ASR tags of the 5 datasets added in #2565 following the change of task categories in #2620

https://api.github.com/repos/huggingface/datasets/issues/2633/timeline

https://api.github.com/repos/huggingface/datasets/issues/2632

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2632/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2632/comments

https://api.github.com/repos/huggingface/datasets/issues/2632/events

https://github.com/huggingface/datasets/pull/2632

MDExOlB1bGxSZXF1ZXN0Njg4MDQyMjcw

add image-classification task template

closed

CONTRIBUTOR

Snippet below is the tl;dr, but you can try it out directly here: [](https://colab.research.google.com/gist/nateraw/005c025d41f0e48ae3d4ee61c0f20b70/image-classification-task-template-demo.ipynb) ```python from datasets import load_dataset ds = load_dataset('nateraw/image-folder', data_files='PetImages/') # DatasetDict({ # train: Dataset({ # features: ['file', 'labels'], # num_rows: 23410 # }) # }) ds = ds.prepare_for_task('image-classification') # DatasetDict({ # train: Dataset({ # features: ['image_file_path', 'labels'], # num_rows: 23410 # }) # }) ```

https://api.github.com/repos/huggingface/datasets/issues/2632/timeline

https://api.github.com/repos/huggingface/datasets/issues/2631

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2631/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2631/comments

https://api.github.com/repos/huggingface/datasets/issues/2631/events

https://github.com/huggingface/datasets/pull/2631

MDExOlB1bGxSZXF1ZXN0Njg3OTk3MzM2

Delete extracted files when loading dataset

closed

MEMBER

Close #2481, close #2604, close #2591. cc: @stas00, @thomwolf, @BirgerMoell

https://api.github.com/repos/huggingface/datasets/issues/2631/timeline

https://api.github.com/repos/huggingface/datasets/issues/2630

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2630/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2630/comments

https://api.github.com/repos/huggingface/datasets/issues/2630/events

https://github.com/huggingface/datasets/issues/2630

MDU6SXNzdWU5NDIxMDI5NTY=

Progress bars are not properly rendered in Jupyter notebook

closed

MEMBER

## Describe the bug The progress bars are not Jupyter widgets; regular progress bars appear (like in a terminal). ## Steps to reproduce the bug ```python ds.map(tokenize, num_proc=10) ``` ## Expected results Jupyter widgets displaying the progress bars. ## Actual results Simple plane progress bars. cc: Reported by @thomwolf

https://api.github.com/repos/huggingface/datasets/issues/2630/timeline

https://api.github.com/repos/huggingface/datasets/issues/2629

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2629/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2629/comments

https://api.github.com/repos/huggingface/datasets/issues/2629/events

https://github.com/huggingface/datasets/issues/2629

MDU6SXNzdWU5NDE4MTkyMDU=

Load datasets from the Hub without requiring a dataset script

closed

MEMBER

As a user I would like to be able to upload my csv/json/text/parquet/etc. files in a dataset repository on the Hugging Face Hub and be able to load this dataset with `load_dataset` without having to implement a dataset script. Moreover I would like to be able to specify which file goes into which split using the `data_files` argument. This feature should be compatible with private repositories and dataset streaming. This can be implemented by checking the extension of the files in the dataset repository and then by using the right dataset builder that is already packaged in the library (csv/json/text/parquet/etc.)

https://api.github.com/repos/huggingface/datasets/issues/2629/timeline

https://api.github.com/repos/huggingface/datasets/issues/2628

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2628/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2628/comments

https://api.github.com/repos/huggingface/datasets/issues/2628/events

https://github.com/huggingface/datasets/pull/2628

MDExOlB1bGxSZXF1ZXN0Njg3NTE0NzQz

Use ETag of remote data files

closed

MEMBER

Use ETag of remote data files to create config ID. Related to #2616.

https://api.github.com/repos/huggingface/datasets/issues/2628/timeline

https://api.github.com/repos/huggingface/datasets/issues/2627

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2627/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2627/comments

https://api.github.com/repos/huggingface/datasets/issues/2627/events

https://github.com/huggingface/datasets/pull/2627

MDExOlB1bGxSZXF1ZXN0Njg3MzczMDg1

Minor fix tests with Windows paths

closed

MEMBER

Minor fix tests with Windows paths.

https://api.github.com/repos/huggingface/datasets/issues/2627/timeline

https://api.github.com/repos/huggingface/datasets/issues/2626

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2626/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2626/comments

https://api.github.com/repos/huggingface/datasets/issues/2626/events

https://github.com/huggingface/datasets/pull/2626

MDExOlB1bGxSZXF1ZXN0Njg3MzY4OTMz

Use correct logger in metrics.py

closed

CONTRIBUTOR

Fixes #2624

https://api.github.com/repos/huggingface/datasets/issues/2626/timeline

https://api.github.com/repos/huggingface/datasets/issues/2625

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2625/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2625/comments

https://api.github.com/repos/huggingface/datasets/issues/2625/events

https://github.com/huggingface/datasets/issues/2625

MDU6SXNzdWU5NDE0Mzk5MjI=

⚛️😇⚙️🔑

closed

NONE

https://api.github.com/repos/huggingface/datasets/issues/2625/timeline

https://api.github.com/repos/huggingface/datasets/issues/2624

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2624/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2624/comments

https://api.github.com/repos/huggingface/datasets/issues/2624/events

https://github.com/huggingface/datasets/issues/2624

MDU6SXNzdWU5NDEzMTgyNDc=

can't set verbosity for `metric.py`

closed

NONE

## Describe the bug ``` [2021-07-10 20:13:11,528][datasets.utils.filelock][INFO] - Lock 139705371374976 acquired on /root/.cache/huggingface/metrics/seqeval/default/default_experiment-1-0.arrow.lock [2021-07-10 20:13:11,529][datasets.arrow_writer][INFO] - Done writing 32 examples in 6100 bytes /root/.cache/huggingface/metrics/seqeval/default/default_experiment-1-0.arrow. [2021-07-10 20:13:11,531][datasets.arrow_dataset][INFO] - Set __getitem__(key) output type to python objects for no columns (when key is int or slice) and don't output other (un-formatted) columns. [2021-07-10 20:13:11,543][/conda/envs/myenv/lib/python3.8/site-packages/datasets/metric.py][INFO] - Removing /root/.cache/huggingface/metrics/seqeval/default/default_experiment-1-0.arrow ``` As you can see, `datasets` logging come from different places. `filelock`, `arrow_writer` & `arrow_dataset` comes from `datasets.*` which are expected However, `metric.py` logging comes from `/conda/envs/myenv/lib/python3.8/site-packages/datasets/` So when setting `datasets.utils.logging.set_verbosity_error()`, it still logs the last message which is annoying during evaluation. I had to do ``` logging.getLogger("/conda/envs/myenv/lib/python3.8/site-packages/datasets/metric").setLevel(logging.ERROR) ``` to fully mute these messages ## Expected results it shouldn't log these messages when setting `datasets.utils.logging.set_verbosity_error()` ## Environment info <!-- You can run the command `datasets-cli env` and copy-and-paste its output below. --> - `datasets` version: tried both 1.8.0 & 1.9.0 - Platform: Ubuntu 18.04.5 LTS - Python version: 3.8.10 - PyArrow version: 3.0.0

https://api.github.com/repos/huggingface/datasets/issues/2624/timeline

https://api.github.com/repos/huggingface/datasets/issues/2623

https://api.github.com/repos/huggingface/datasets

https://api.github.com/repos/huggingface/datasets/issues/2623/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/2623/comments

https://api.github.com/repos/huggingface/datasets/issues/2623/events

https://github.com/huggingface/datasets/pull/2623

MDExOlB1bGxSZXF1ZXN0Njg3MTk0MjM3

[Metrics] added wiki_split metrics

closed