Datasets:

aidiary

/

github-issues

like 0

https://api.github.com/repos/huggingface/datasets/issues/1934

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

https://api.github.com/repos/huggingface/datasets/issues/1934/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/1934/comments

https://api.github.com/repos/huggingface/datasets/issues/1934/events

https://github.com/huggingface/datasets/issues/1934

MDU6SXNzdWU4MTQ0MzcxOTA=

Add Stanford Sentiment Treebank (SST)

closed

CONTRIBUTOR

I am going to add SST: - **Name:** The Stanford Sentiment Treebank - **Description:** The first corpus with fully labeled parse trees that allows for a complete analysis of the compositional effects of sentiment in language - **Paper:** [Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank](https://nlp.stanford.edu/~socherr/EMNLP2013_RNTN.pdf) - **Data:** https://nlp.stanford.edu/sentiment/index.html - **Motivation:** Already requested in #353, SST is a popular dataset for Sentiment Classification What's the difference with the [_SST-2_](https://huggingface.co/datasets/viewer/?dataset=glue&config=sst2) dataset included in GLUE? Essentially, SST-2 is a version of SST where: - the labels were mapped from real numbers in [0.0, 1.0] to a binary label: {0, 1} - the labels of the *sub-sentences* were included only in the training set - the labels in the test set are obfuscated So there is a lot more information in the original SST. The tricky bit is, the data is scattered into many text files and, for one in particular, I couldn't find the original encoding ([*but I'm not the only one*](https://groups.google.com/g/word2vec-toolkit/c/QIUjLw6RqFk/m/_iEeyt428wkJ) 🎵). The only solution I found was to manually replace all the è, ë, ç and so on into an `utf-8` copy of the text file. I uploaded the result in my Dropbox and I am using that as the main repo for the dataset. Also, the _sub-sentences_ are built at run-time from the information encoded in several text files, so generating the examples is a bit more cumbersome than usual. Luckily, the dataset is not enormous. I plan to divide the dataset in 2 configs: one with just whole sentences with their labels, the other with sentences _and their sub-sentences_ with their labels. Each config will be split in train, validation and test. Hopefully this makes sense, we may discuss it in the PR I'm going to submit.

https://api.github.com/repos/huggingface/datasets/issues/1934/timeline

completed

https://api.github.com/repos/huggingface/datasets/issues/1933

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

https://api.github.com/repos/huggingface/datasets/issues/1933/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/1933/comments

https://api.github.com/repos/huggingface/datasets/issues/1933/events

https://github.com/huggingface/datasets/pull/1933

MDExOlB1bGxSZXF1ZXN0NTc4MzQwMzk3

Use arrow ipc file format

closed

MEMBER

According to the [documentation](https://arrow.apache.org/docs/format/Columnar.html?highlight=arrow1#ipc-file-format), it's identical to the streaming format except that it contains the memory offsets of each sample: > We define a “file format” supporting random access that is build with the stream format. The file starts and ends with a magic string ARROW1 (plus padding). What follows in the file is identical to the stream format. At the end of the file, we write a footer containing a redundant copy of the schema (which is a part of the streaming format) plus memory offsets and sizes for each of the data blocks in the file. This enables random access any record batch in the file. See File.fbs for the precise details of the file footer. Since it stores more metadata regarding the positions of the examples in the file, it should enable better example retrieval performances. However from the discussion in https://github.com/huggingface/datasets/issues/1803 it looks like it's not the case unfortunately. Maybe in the future this will allow speed gains. I think it's still a good idea to start using it anyway for these reasons: - in the future we may have speed gains - it contains the arrow streaming format data - it's compatible with the pyarrow Dataset implementation (it allows to load remote dataframes for example) if we want to use it in the future - it's also the format used by arrow feather if we want to use it in the future - it's roughly the same size as the streaming format - it's easy to have backward compatibility with the streaming format

https://api.github.com/repos/huggingface/datasets/issues/1933/timeline

https://api.github.com/repos/huggingface/datasets/issues/1932

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

https://api.github.com/repos/huggingface/datasets/issues/1932/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/1932/comments

https://api.github.com/repos/huggingface/datasets/issues/1932/events

https://github.com/huggingface/datasets/pull/1932

MDExOlB1bGxSZXF1ZXN0NTc4MzMyMTQy

Fix builder config creation with data_dir

closed

MEMBER

The data_dir parameter wasn't taken into account to create the config_id, therefore the resulting builder config was considered not custom. However a builder config that is non-custom must not have a name that collides with the predefined builder config names. Therefore it resulted in a `ValueError("Cannot name a custom BuilderConfig the same as an available...")` I fixed that by commenting the line that used to ignore the data_dir when creating the config. It was previously ignored before the introduction of config id because we didn't want to change the config name. Now it's fine to take it into account for the config id. Now creating a config with a data_dir works again @patrickvonplaten

https://api.github.com/repos/huggingface/datasets/issues/1932/timeline

https://api.github.com/repos/huggingface/datasets/issues/1931

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

https://api.github.com/repos/huggingface/datasets/issues/1931/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/1931/comments

https://api.github.com/repos/huggingface/datasets/issues/1931/events

https://github.com/huggingface/datasets/pull/1931

MDExOlB1bGxSZXF1ZXN0NTc4MjQ4NTA5

add m_lama (multilingual lama) dataset

closed

CONTRIBUTOR

Add a multilingual (machine translated and automatically generated) version of the LAMA benchmark. For details see the paper https://arxiv.org/pdf/2102.00894.pdf

https://api.github.com/repos/huggingface/datasets/issues/1931/timeline

https://api.github.com/repos/huggingface/datasets/issues/1930

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

https://api.github.com/repos/huggingface/datasets/issues/1930/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/1930/comments

https://api.github.com/repos/huggingface/datasets/issues/1930/events

https://github.com/huggingface/datasets/pull/1930

MDExOlB1bGxSZXF1ZXN0NTc4MTAwNzI0

updated the wino_bias dataset

closed

CONTRIBUTOR

Updated the wino_bias.py script. - updated the data_url - added different configurations for different data splits - added the coreference_cluster to the data features

https://api.github.com/repos/huggingface/datasets/issues/1930/timeline

https://api.github.com/repos/huggingface/datasets/issues/1929

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

https://api.github.com/repos/huggingface/datasets/issues/1929/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/1929/comments

https://api.github.com/repos/huggingface/datasets/issues/1929/events

https://github.com/huggingface/datasets/pull/1929

MDExOlB1bGxSZXF1ZXN0NTc3OTk1MTE4

Improve typing and style and fix some inconsistencies

closed

CONTRIBUTOR

This PR: * improves typing (mostly more consistent use of `typing.Optional`) * `DatasetDict.cleanup_cache_files` now correctly returns a dict * replaces `dict()` with the corresponding literal * uses `dict_to_copy.copy()` instead of `dict(dict_to_copy)` for shallow copying

https://api.github.com/repos/huggingface/datasets/issues/1929/timeline

https://api.github.com/repos/huggingface/datasets/issues/1928

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

https://api.github.com/repos/huggingface/datasets/issues/1928/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/1928/comments

https://api.github.com/repos/huggingface/datasets/issues/1928/events

https://github.com/huggingface/datasets/pull/1928

MDExOlB1bGxSZXF1ZXN0NTc3ODgyMDM4

Updating old cards

closed

CONTRIBUTOR

Updated the cards for [Allocine](https://github.com/mcmillanmajora/datasets/tree/updating-old-cards/datasets/allocine), [CNN/DailyMail](https://github.com/mcmillanmajora/datasets/tree/updating-old-cards/datasets/cnn_dailymail), and [SNLI](https://github.com/mcmillanmajora/datasets/tree/updating-old-cards/datasets/snli). For the most part, the information was just rearranged or rephrased, but the social impact statements are new.

https://api.github.com/repos/huggingface/datasets/issues/1928/timeline

https://api.github.com/repos/huggingface/datasets/issues/1927

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

https://api.github.com/repos/huggingface/datasets/issues/1927/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/1927/comments

https://api.github.com/repos/huggingface/datasets/issues/1927/events

https://github.com/huggingface/datasets/pull/1927

MDExOlB1bGxSZXF1ZXN0NTc3ODYxODM5

Update dataset card of wino_bias

closed

CONTRIBUTOR

Updated the info for the wino_bias dataset.

https://api.github.com/repos/huggingface/datasets/issues/1927/timeline

https://api.github.com/repos/huggingface/datasets/issues/1926

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

https://api.github.com/repos/huggingface/datasets/issues/1926/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/1926/comments

https://api.github.com/repos/huggingface/datasets/issues/1926/events

https://github.com/huggingface/datasets/pull/1926

MDExOlB1bGxSZXF1ZXN0NTc3NzI4Mjgy

Fix: Wiki_dpr - add missing scalar quantizer

closed

MEMBER

All the prebuilt wiki_dpr indexes already use SQ8, I forgot to update the wiki_dpr script after building them. Now it's finally done. The scalar quantizer SQ8 doesn't reduce the performance of the index as shown in retrieval experiments on RAG. The quantizer reduces the size of the index a lot but increases index building time.

https://api.github.com/repos/huggingface/datasets/issues/1926/timeline

https://api.github.com/repos/huggingface/datasets/issues/1925

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

https://api.github.com/repos/huggingface/datasets/issues/1925/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/1925/comments

https://api.github.com/repos/huggingface/datasets/issues/1925/events

https://github.com/huggingface/datasets/pull/1925

MDExOlB1bGxSZXF1ZXN0NTc3NzIyMzc3

Fix: Wiki_dpr - fix when with_embeddings is False or index_name is "no_index"

closed

MEMBER

Fix the bugs noticed in #1915 There was a bug when `with_embeddings=False` where the configuration name was the same as if `with_embeddings=True`, which led the dataset builder to do bad verifications (for example it used to expect to download the embeddings for `with_embeddings=False`). Another issue was that setting `index_name="no_index"` didn't set `with_index` to False. I fixed both of them and added dummy data for those configurations for testing.

https://api.github.com/repos/huggingface/datasets/issues/1925/timeline

https://api.github.com/repos/huggingface/datasets/issues/1924

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

https://api.github.com/repos/huggingface/datasets/issues/1924/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/1924/comments

https://api.github.com/repos/huggingface/datasets/issues/1924/events

https://github.com/huggingface/datasets/issues/1924

MDU6SXNzdWU4MTM1OTk3MzM=

Anonymous Dataset Addition (i.e Anonymous PR?)

closed

CONTRIBUTOR

Hello, Thanks a lot for your librairy. We plan to submit a paper on OpenReview using the Anonymous setting. Is it possible to add a new dataset without breaking the anonimity, with a link to the paper ? Cheers @eusip

https://api.github.com/repos/huggingface/datasets/issues/1924/timeline

completed

https://api.github.com/repos/huggingface/datasets/issues/1923

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

https://api.github.com/repos/huggingface/datasets/issues/1923/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/1923/comments

https://api.github.com/repos/huggingface/datasets/issues/1923/events

https://github.com/huggingface/datasets/pull/1923

MDExOlB1bGxSZXF1ZXN0NTc3NTI0MTU0

Fix save_to_disk with relative path

closed

MEMBER

As noticed in #1919 and #1920 the target directory was not created using `makedirs` so saving to it raises `FileNotFoundError`. For absolute paths it works but not for the good reason. This is because the target path was the same as the temporary path where in-memory data are written as an intermediary step. I added the `makedirs` call using `fs.makedirs` in order to support remote filesystems. I also fixed the issue with the target path being the temporary path. I added a test case for relative paths as well for save_to_disk. Thanks to @M-Salti for reporting and investigating

https://api.github.com/repos/huggingface/datasets/issues/1923/timeline

https://api.github.com/repos/huggingface/datasets/issues/1922

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

https://api.github.com/repos/huggingface/datasets/issues/1922/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/1922/comments

https://api.github.com/repos/huggingface/datasets/issues/1922/events

https://github.com/huggingface/datasets/issues/1922

MDU6SXNzdWU4MTMxNDA4MDY=

How to update the "wino_bias" dataset

open

CONTRIBUTOR

Hi all, Thanks for the efforts to collect all the datasets! But I think there is a problem with the wino_bias dataset. The current link is not correct. How can I update that? Thanks!

https://api.github.com/repos/huggingface/datasets/issues/1922/timeline

https://api.github.com/repos/huggingface/datasets/issues/1921

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

https://api.github.com/repos/huggingface/datasets/issues/1921/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/1921/comments

https://api.github.com/repos/huggingface/datasets/issues/1921/events

https://github.com/huggingface/datasets/pull/1921

MDExOlB1bGxSZXF1ZXN0NTc3MDEzMDM4

Standardizing datasets dtypes

closed

CONTRIBUTOR

This PR follows up on discussion in #1900 to have an explicit set of basic dtypes for datasets. This moves away from str(pyarrow.DataType) as the method of choice for creating dtypes, favoring an explicit mapping to a list of supported Value dtypes. I believe in practice this should be backward compatible, since anyone previously using Value() would only have been able to use dtypes that had an identically named pyarrow factory function, which are all explicitly supported here, with `float32` and `float64` acting as the official datasets dtypes, which resolves the tension between `double` being the pyarrow dtype and `float64` being the pyarrow type factory function.

https://api.github.com/repos/huggingface/datasets/issues/1921/timeline

https://api.github.com/repos/huggingface/datasets/issues/1920

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

https://api.github.com/repos/huggingface/datasets/issues/1920/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/1920/comments

https://api.github.com/repos/huggingface/datasets/issues/1920/events

https://github.com/huggingface/datasets/pull/1920

MDExOlB1bGxSZXF1ZXN0NTc2OTQ5NzI2

Fix save_to_disk issue

closed

CONTRIBUTOR

Fixes #1919

https://api.github.com/repos/huggingface/datasets/issues/1920/timeline

https://api.github.com/repos/huggingface/datasets/issues/1919

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

https://api.github.com/repos/huggingface/datasets/issues/1919/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/1919/comments

https://api.github.com/repos/huggingface/datasets/issues/1919/events

https://github.com/huggingface/datasets/issues/1919

MDU6SXNzdWU4MTI2MjY4NzI=

Failure to save with save_to_disk

closed

CONTRIBUTOR

When I try to save a dataset locally using the `save_to_disk` method I get the error: ```bash FileNotFoundError: [Errno 2] No such file or directory: '/content/squad/train/squad-train.arrow' ``` To replicate: 1. Install `datasets` from master 2. Run this code: ```python from datasets import load_dataset squad = load_dataset("squad") # or any other dataset squad.save_to_disk("squad") # error here ``` The problem is that the method is not creating a directory with the name `dataset_path` for saving the dataset in (i.e. it's not creating the *train* and *validation* directories in this case). After creating the directory the problem resolves. I'll open a PR soon doing that and linking this issue.

https://api.github.com/repos/huggingface/datasets/issues/1919/timeline

completed

https://api.github.com/repos/huggingface/datasets/issues/1918

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

https://api.github.com/repos/huggingface/datasets/issues/1918/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/1918/comments

https://api.github.com/repos/huggingface/datasets/issues/1918/events

https://github.com/huggingface/datasets/pull/1918

MDExOlB1bGxSZXF1ZXN0NTc2ODg2OTQ0

Fix QA4MRE download URLs

closed

CONTRIBUTOR

The URLs in the `dataset_infos` and `README` are correct, only the ones in the download script needed updating.

https://api.github.com/repos/huggingface/datasets/issues/1918/timeline

https://api.github.com/repos/huggingface/datasets/issues/1917

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

https://api.github.com/repos/huggingface/datasets/issues/1917/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/1917/comments

https://api.github.com/repos/huggingface/datasets/issues/1917/events

https://github.com/huggingface/datasets/issues/1917

MDU6SXNzdWU4MTIzOTAxNzg=

UnicodeDecodeError: windows 10 machine

closed

NONE

Windows 10 Php 3.6.8 when running ``` import datasets oscar_am = datasets.load_dataset("oscar", "unshuffled_deduplicated_am") print(oscar_am["train"][0]) ``` I get the following error ``` file "C:\PYTHON\3.6.8\lib\encodings\cp1252.py", line 23, in decode return codecs.charmap_decode(input,self.errors,decoding_table)[0] UnicodeDecodeError: 'charmap' codec can't decode byte 0x9d in position 58: character maps to <undefined> ```

https://api.github.com/repos/huggingface/datasets/issues/1917/timeline

completed

https://api.github.com/repos/huggingface/datasets/issues/1916

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

https://api.github.com/repos/huggingface/datasets/issues/1916/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/1916/comments

https://api.github.com/repos/huggingface/datasets/issues/1916/events

https://github.com/huggingface/datasets/pull/1916

MDExOlB1bGxSZXF1ZXN0NTc2NjgwNjY5

Remove unused py_utils objects

closed

MEMBER

Remove unused/unnecessary py_utils functions/classes.

https://api.github.com/repos/huggingface/datasets/issues/1916/timeline

https://api.github.com/repos/huggingface/datasets/issues/1915

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

https://api.github.com/repos/huggingface/datasets/issues/1915/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/1915/comments

https://api.github.com/repos/huggingface/datasets/issues/1915/events

https://github.com/huggingface/datasets/issues/1915

MDU6SXNzdWU4MTIyMjk2NTQ=

Unable to download `wiki_dpr`

closed

NONE

I am trying to download the `wiki_dpr` dataset. Specifically, I want to download `psgs_w100.multiset.no_index` with no embeddings/no index. In order to do so, I ran: `curr_dataset = load_dataset("wiki_dpr", embeddings_name="multiset", index_name="no_index")` However, I got the following error: `datasets.utils.info_utils.UnexpectedDownloadedFile: {'embeddings_index'}` I tried adding in flags `with_embeddings=False` and `with_index=False`: `curr_dataset = load_dataset("wiki_dpr", with_embeddings=False, with_index=False, embeddings_name="multiset", index_name="no_index")` But I got the following error: `raise ExpectedMoreDownloadedFiles(str(set(expected_checksums) - set(recorded_checksums))) datasets.utils.info_utils.ExpectedMoreDownloadedFiles: {‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_5’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_15’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_30’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_36’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_18’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_41’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_13’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_48’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_10’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_23’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_14’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_34’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_43’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_40’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_47’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_3’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_24’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_7’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_33’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_46’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_42’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_27’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_29’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_26’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_22’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_4’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_20’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_39’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_6’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_16’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_8’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_35’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_49’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_17’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_25’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_0’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_38’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_12’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_44’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_1’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_32’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_19’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_31’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_37’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_9’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_11’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_21’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_28’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_45’, ‘https://dl.fbaipublicfiles.com/rag/rag_multiset_embeddings/wiki_passages_2’}` Is there anything else I need to set to download the dataset? **UPDATE**: just running `curr_dataset = load_dataset("wiki_dpr", with_embeddings=False, with_index=False)` gives me the same error.

https://api.github.com/repos/huggingface/datasets/issues/1915/timeline

completed

https://api.github.com/repos/huggingface/datasets/issues/1914

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

https://api.github.com/repos/huggingface/datasets/issues/1914/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/1914/comments

https://api.github.com/repos/huggingface/datasets/issues/1914/events

https://github.com/huggingface/datasets/pull/1914

MDExOlB1bGxSZXF1ZXN0NTc2NTYyNTkz

Fix logging imports and make all datasets use library logger

closed

MEMBER

Fix library relative logging imports and make all datasets use library logger.

https://api.github.com/repos/huggingface/datasets/issues/1914/timeline

https://api.github.com/repos/huggingface/datasets/issues/1913

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

https://api.github.com/repos/huggingface/datasets/issues/1913/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/1913/comments

https://api.github.com/repos/huggingface/datasets/issues/1913/events

https://github.com/huggingface/datasets/pull/1913

MDExOlB1bGxSZXF1ZXN0NTc2NTQ0NjQw

Add keep_linebreaks parameter to text loader

closed

MEMBER

As asked in #870 and https://github.com/huggingface/transformers/issues/10269 there should be a parameter to keep the linebreaks when loading a text dataset. cc @sgugger @jncasey

https://api.github.com/repos/huggingface/datasets/issues/1913/timeline

https://api.github.com/repos/huggingface/datasets/issues/1912

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

https://api.github.com/repos/huggingface/datasets/issues/1912/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/1912/comments

https://api.github.com/repos/huggingface/datasets/issues/1912/events

https://github.com/huggingface/datasets/pull/1912

MDExOlB1bGxSZXF1ZXN0NTc2NDY2ODQx

Update: WMT - use mirror links

closed

MEMBER

As asked in #1892 I created mirrors of the data hosted on statmt.org and updated the wmt scripts. Now downloading the wmt datasets is blazing fast :) cc @stas00 @patrickvonplaten

https://api.github.com/repos/huggingface/datasets/issues/1912/timeline

https://api.github.com/repos/huggingface/datasets/issues/1911

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

https://api.github.com/repos/huggingface/datasets/issues/1911/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/1911/comments

https://api.github.com/repos/huggingface/datasets/issues/1911/events

https://github.com/huggingface/datasets/issues/1911

MDU6SXNzdWU4MTIwMDk5NTY=

Saving processed dataset running infinitely

open

NONE

I have a text dataset of size 220M. For pre-processing, I need to tokenize this and filter rows with the large sequence. My tokenization took roughly 3hrs. I used map() with batch size 1024 and multi-process with 96 processes. filter() function was way to slow, so I used a hack to use pyarrow filter table function, which is damm fast. Mentioned [here](https://github.com/huggingface/datasets/issues/1796) ```dataset._data = dataset._data.filter(...)``` It took 1 hr for the filter. Then i use `save_to_disk()` on processed dataset and it is running forever. I have been waiting since 8 hrs, it has not written a single byte. Infact it has actually read from disk more than 100GB, screenshot below shows the stats using `iotop`. Second process is the one. <img width="1672" alt="Screenshot 2021-02-19 at 6 36 53 PM" src="https://user-images.githubusercontent.com/20911334/108508197-7325d780-72e1-11eb-8369-7c057d137d81.png"> I am not able to figure out, whether this is some issue with dataset library or that it is due to my hack for filter() function.

https://api.github.com/repos/huggingface/datasets/issues/1911/timeline

https://api.github.com/repos/huggingface/datasets/issues/1910

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

https://api.github.com/repos/huggingface/datasets/issues/1910/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/1910/comments

https://api.github.com/repos/huggingface/datasets/issues/1910/events

https://github.com/huggingface/datasets/pull/1910

MDExOlB1bGxSZXF1ZXN0NTc2MTg0MDQ3

Adding CoNLLpp dataset.

closed

CONTRIBUTOR

https://api.github.com/repos/huggingface/datasets/issues/1910/timeline

https://api.github.com/repos/huggingface/datasets/issues/1907

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

https://api.github.com/repos/huggingface/datasets/issues/1907/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/1907/comments

https://api.github.com/repos/huggingface/datasets/issues/1907/events

https://github.com/huggingface/datasets/issues/1907

MDU6SXNzdWU4MTE1MjA1Njk=

DBPedia14 Dataset Checksum bug?

closed

CONTRIBUTOR

Hi there!!! I've been using successfully the DBPedia dataset (https://huggingface.co/datasets/dbpedia_14) with my codebase in the last couple of weeks, but in the last couple of days now I get this error: ``` Traceback (most recent call last): File "./conditional_classification/basic_pipeline.py", line 178, in <module> main() File "./conditional_classification/basic_pipeline.py", line 128, in main corpus.load_data(limit_train_examples_per_class=args.data_args.train_examples_per_class, File "/home/fp/dev/conditional_classification/conditional_classification/datasets_base.py", line 83, in load_data datasets = load_dataset(self.name, split=dataset_split) File "/home/fp/anaconda3/envs/conditional/lib/python3.8/site-packages/datasets/load.py", line 609, in load_dataset builder_instance.download_and_prepare( File "/home/fp/anaconda3/envs/conditional/lib/python3.8/site-packages/datasets/builder.py", line 526, in download_and_prepare self._download_and_prepare( File "/home/fp/anaconda3/envs/conditional/lib/python3.8/site-packages/datasets/builder.py", line 586, in _download_and_prepare verify_checksums( File "/home/fp/anaconda3/envs/conditional/lib/python3.8/site-packages/datasets/utils/info_utils.py", line 39, in verify_checksums raise NonMatchingChecksumError(error_msg + str(bad_urls)) datasets.utils.info_utils.NonMatchingChecksumError: Checksums didn't match for dataset source files: ['https://drive.google.com/uc?export=download&id=0Bz8a_Dbh9QhbQ2Vic1kxMmZZQ1k'] ``` I've seen this has happened before in other datasets as reported in #537. I've tried clearing my cache and call again `load_dataset` but still is not working. My same codebase is successfully downloading and using other datasets (e.g. AGNews) without any problem, so I guess something has happened specifically to the DBPedia dataset in the last few days. Can you please check if there's a problem with the checksums? Or this is related to any other stuff? I've seen that the path in the cache for the dataset is `/home/fp/.cache/huggingface/datasets/d_bpedia14/dbpedia_14/2.0.0/a70413e39e7a716afd0e90c9e53cb053691f56f9ef5fe317bd07f2c368e8e897...` and includes `d_bpedia14` instead maybe of `dbpedia_14`. Was this maybe a bug introduced recently? Thanks!

https://api.github.com/repos/huggingface/datasets/issues/1907/timeline

completed

https://api.github.com/repos/huggingface/datasets/issues/1906

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

https://api.github.com/repos/huggingface/datasets/issues/1906/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/1906/comments

https://api.github.com/repos/huggingface/datasets/issues/1906/events

https://github.com/huggingface/datasets/issues/1906

MDU6SXNzdWU4MTE0MDUyNzQ=

Feature Request: Support for Pandas `Categorical`

open

CONTRIBUTOR

``` from datasets import Dataset import pandas as pd import pyarrow df = pd.DataFrame(pd.Series(["a", "b", "c", "a"], dtype="category")) pyarrow.Table.from_pandas(df) Dataset.from_pandas(df) # Throws NotImplementedError # TODO(thom) this will need access to the dictionary as well (for labels). I.e. to the py_table ``` I'm curious if https://github.com/huggingface/datasets/blob/master/src/datasets/features.py#L796 could be built out in a way similar to `Sequence`? e.g. a `Map` class (or whatever name the maintainers might prefer) that can accept: ``` index_type = generate_from_arrow_type(pa_type.index_type) value_type = generate_from_arrow_type(pa_type.value_type) ``` and then additional code points to modify: - FeatureType: https://github.com/huggingface/datasets/blob/master/src/datasets/features.py#L694 - A branch to handle Map in get_nested_type: https://github.com/huggingface/datasets/blob/master/src/datasets/features.py#L719 - I don't quite understand what `encode_nested_example` does but perhaps a branch there? https://github.com/huggingface/datasets/blob/master/src/datasets/features.py#L755 - Similarly, I don't quite understand why `Sequence` is used this way in `generate_from_dict`, but perhaps a branch here? https://github.com/huggingface/datasets/blob/master/src/datasets/features.py#L775 I couldn't find other usages of `Sequence` outside of defining specific datasets, so I'm not sure if that's a comprehensive set of touchpoints.

https://api.github.com/repos/huggingface/datasets/issues/1906/timeline

https://api.github.com/repos/huggingface/datasets/issues/1905

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

https://api.github.com/repos/huggingface/datasets/issues/1905/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/1905/comments

https://api.github.com/repos/huggingface/datasets/issues/1905/events

https://github.com/huggingface/datasets/pull/1905

MDExOlB1bGxSZXF1ZXN0NTc1OTIxMDk1

Standardizing datasets.dtypes

closed

CONTRIBUTOR

This PR was further branched off of jdy-str-to-pyarrow-parsing, so it depends on https://github.com/huggingface/datasets/pull/1900 going first for the diff to be up-to-date (I'm not sure if there's a way for me to use jdy-str-to-pyarrow-parsing as a base branch while having it appear in the pull requests here). This moves away from `str(pyarrow.DataType)` as the method of choice for creating dtypes, favoring an explicit mapping to a list of supported Value dtypes. I believe in practice this should be backward compatible, since anyone previously using Value() would only have been able to use dtypes that had an identically named pyarrow factory function, which are all explicitly supported here.

https://api.github.com/repos/huggingface/datasets/issues/1905/timeline

https://api.github.com/repos/huggingface/datasets/issues/1904

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

https://api.github.com/repos/huggingface/datasets/issues/1904/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/1904/comments

https://api.github.com/repos/huggingface/datasets/issues/1904/events

https://github.com/huggingface/datasets/pull/1904

MDExOlB1bGxSZXF1ZXN0NTc1ODE4MjA0

Fix to_pandas for boolean ArrayXD

closed

MEMBER

As noticed in #1887 the conversion of a dataset with a boolean ArrayXD feature types fails because of the underlying ListArray conversion to numpy requires `zero_copy_only=False`. zero copy is available for all primitive types except booleans see https://arrow.apache.org/docs/python/generated/pyarrow.Array.html#pyarrow.Array.to_numpy and https://issues.apache.org/jira/browse/ARROW-2871?jql=text%20~%20%22boolean%20to_numpy%22 cc @SBrandeis

https://api.github.com/repos/huggingface/datasets/issues/1904/timeline

https://api.github.com/repos/huggingface/datasets/issues/1903

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

https://api.github.com/repos/huggingface/datasets/issues/1903/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/1903/comments

https://api.github.com/repos/huggingface/datasets/issues/1903/events

https://github.com/huggingface/datasets/pull/1903

MDExOlB1bGxSZXF1ZXN0NTc1NzIwOTk2

Initial commit for the addition of TIMIT dataset

closed

CONTRIBUTOR

Below points needs to be addressed: - Creation of dummy dataset is failing - Need to check on the data representation - License is not creative commons. Copyright: Portions © 1993 Trustees of the University of Pennsylvania Also the links (_except the download_) point to the ami corpus! ;-) @patrickvonplaten Requesting your comments, will be happy to address them!

https://api.github.com/repos/huggingface/datasets/issues/1903/timeline

https://api.github.com/repos/huggingface/datasets/issues/1902

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

https://api.github.com/repos/huggingface/datasets/issues/1902/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/1902/comments

https://api.github.com/repos/huggingface/datasets/issues/1902/events

https://github.com/huggingface/datasets/pull/1902

MDExOlB1bGxSZXF1ZXN0NTc1NTQwMDM1

Fix setimes_2 wmt urls

closed

MEMBER

Continuation of #1901 Some other urls were missing https

https://api.github.com/repos/huggingface/datasets/issues/1902/timeline

https://api.github.com/repos/huggingface/datasets/issues/1901

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

https://api.github.com/repos/huggingface/datasets/issues/1901/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/1901/comments

https://api.github.com/repos/huggingface/datasets/issues/1901/events

https://github.com/huggingface/datasets/pull/1901

MDExOlB1bGxSZXF1ZXN0NTc1NDY5MDUy

Fix OPUS dataset download errors

closed

CONTRIBUTOR

Replace http to https. https://github.com/huggingface/datasets/issues/854 https://discuss.huggingface.co/t/cannot-download-wmt16/2081

https://api.github.com/repos/huggingface/datasets/issues/1901/timeline

https://api.github.com/repos/huggingface/datasets/issues/1900

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

https://api.github.com/repos/huggingface/datasets/issues/1900/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/1900/comments

https://api.github.com/repos/huggingface/datasets/issues/1900/events

https://github.com/huggingface/datasets/pull/1900

MDExOlB1bGxSZXF1ZXN0NTc1MTkxNTc3

Issue #1895: Bugfix for string_to_arrow timestamp[ns] support

closed

CONTRIBUTOR

Should resolve https://github.com/huggingface/datasets/issues/1895 The main part of this PR adds additional parsing in `string_to_arrow` to convert the timestamp dtypes that result from `str(pa_type)` back into the pa.DataType TimestampType. While adding unit-testing, I noticed that support for the double/float types also don't invert correctly, so I added them, which I believe would hypothetically make this section of `Value` redundant: ``` def __post_init__(self): if self.dtype == "double": # fix inferred type self.dtype = "float64" if self.dtype == "float": # fix inferred type self.dtype = "float32" ``` However, since I think Value.dtype is part of the public interface, removing that would result in a backward-incompatible change, so I didn't muck with that. The rest of the PR consists of docstrings that I added while developing locally so I could keep track of which functions were supposed to be inverses of each other, and thought I'd include them initially in case you want to keep them around, but I'm happy to delete or remove any of them at your request!

https://api.github.com/repos/huggingface/datasets/issues/1900/timeline

https://api.github.com/repos/huggingface/datasets/issues/1899

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

https://api.github.com/repos/huggingface/datasets/issues/1899/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/1899/comments

https://api.github.com/repos/huggingface/datasets/issues/1899/events

https://github.com/huggingface/datasets/pull/1899

MDExOlB1bGxSZXF1ZXN0NTc1MDIxMjc4

Fix: ALT - fix duplicated examples in alt-parallel

closed

MEMBER

As noticed in #1898 by @10-zin the examples of the `alt-paralel` configurations have all the same values for the `translation` field. This was due to a bad copy of a python dict. This PR fixes that.

https://api.github.com/repos/huggingface/datasets/issues/1899/timeline

https://api.github.com/repos/huggingface/datasets/issues/1898

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

https://api.github.com/repos/huggingface/datasets/issues/1898/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/1898/comments

https://api.github.com/repos/huggingface/datasets/issues/1898/events

https://github.com/huggingface/datasets/issues/1898

MDU6SXNzdWU4MTAxNTcyNTE=

ALT dataset has repeating instances in all splits

closed

NONE

The [ALT](https://huggingface.co/datasets/alt) dataset has all the same instances within each split :/ Seemed like a great dataset for some experiments I wanted to carry out, especially since its medium-sized, and has all splits. Would be great if this could be fixed :) Added a snapshot of the contents from `explore-datset` feature, for quick reference. 

https://api.github.com/repos/huggingface/datasets/issues/1898/timeline

completed

https://api.github.com/repos/huggingface/datasets/issues/1897

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

https://api.github.com/repos/huggingface/datasets/issues/1897/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/1897/comments

https://api.github.com/repos/huggingface/datasets/issues/1897/events

https://github.com/huggingface/datasets/pull/1897

MDExOlB1bGxSZXF1ZXN0NTc0ODU3MTIy

Fix PandasArrayExtensionArray conversion to native type

closed

MEMBER

To make the conversion to csv work in #1887 , we need PandasArrayExtensionArray used for multidimensional numpy arrays to be converted to pandas native types. However previously pandas.core.internals.ExtensionBlock.to_native_types would fail with an PandasExtensionArray because 1. the PandasExtensionArray.isna method was wrong 2. the conversion of a PandasExtensionArray to a numpy array with dtype=object was returning a multidimensional array while pandas excepts a 1D array in this case (more info [here](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.api.extensions.ExtensionArray.html#pandas.api.extensions.ExtensionArray)) I fixed these two issues and now the conversion to native types works, and so is the export to csv. cc @SBrandeis

https://api.github.com/repos/huggingface/datasets/issues/1897/timeline

https://api.github.com/repos/huggingface/datasets/issues/1895

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

https://api.github.com/repos/huggingface/datasets/issues/1895/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/1895/comments

https://api.github.com/repos/huggingface/datasets/issues/1895/events

https://github.com/huggingface/datasets/issues/1895

MDU6SXNzdWU4MDk2MzAyNzE=

Bug Report: timestamp[ns] not recognized

closed

CONTRIBUTOR

Repro: ``` from datasets import Dataset import pandas as pd import pyarrow df = pd.DataFrame(pd.date_range("2018-01-01", periods=3, freq="H")) pyarrow.Table.from_pandas(df) Dataset.from_pandas(df) # Throws ValueError: Neither timestamp[ns] nor timestamp[ns]_ seems to be a pyarrow data type. ``` The factory function seems to be just "timestamp": https://arrow.apache.org/docs/python/generated/pyarrow.timestamp.html#pyarrow.timestamp It seems like https://github.com/huggingface/datasets/blob/master/src/datasets/features.py#L36-L43 could have a little bit of additional structure for handling these cases? I'd be happy to take a shot at opening a PR if I could receive some guidance on whether parsing something like `timestamp[ns]` and resolving it to timestamp('ns') is the goal of this method. Alternatively, if I'm using this incorrectly (e.g. is the expectation that we always provide a schema when timestamps are involved?), that would be very helpful to know as well! ``` $ pip list # only the relevant libraries/versions datasets 1.2.1 pandas 1.0.3 pyarrow 3.0.0 ```

https://api.github.com/repos/huggingface/datasets/issues/1895/timeline

completed

https://api.github.com/repos/huggingface/datasets/issues/1894

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

https://api.github.com/repos/huggingface/datasets/issues/1894/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/1894/comments

https://api.github.com/repos/huggingface/datasets/issues/1894/events

https://github.com/huggingface/datasets/issues/1894

MDU6SXNzdWU4MDk2MDk2NTQ=

benchmarking against MMapIndexedDataset

open

CONTRIBUTOR

I am trying to benchmark my datasets based implementation against fairseq's [`MMapIndexedDataset`](https://github.com/pytorch/fairseq/blob/master/fairseq/data/indexed_dataset.py#L365) and finding that, according to psrecord, my `datasets` implem uses about 3% more CPU memory and runs 1% slower for `wikitext103` (~1GB of tokens). Questions: 1) Is this (basically identical) performance expected? 2) Is there a scenario where this library will outperform `MMapIndexedDataset`? (maybe more examples/larger examples?) 3) Should I be using different benchmarking tools than `psrecord`/how do you guys do benchmarks? Thanks in advance! Sam

https://api.github.com/repos/huggingface/datasets/issues/1894/timeline

https://api.github.com/repos/huggingface/datasets/issues/1893

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

https://api.github.com/repos/huggingface/datasets/issues/1893/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/1893/comments

https://api.github.com/repos/huggingface/datasets/issues/1893/events

https://github.com/huggingface/datasets/issues/1893

MDU6SXNzdWU4MDk1NTY1MDM=

wmt19 is broken

closed

CONTRIBUTOR

1. Check which lang pairs we have: `--dataset_name wmt19`: Please pick one among the available configs: ['cs-en', 'de-en', 'fi-en', 'gu-en', 'kk-en', 'lt-en', 'ru-en', 'zh-en', 'fr-de'] 2. OK, let's pick `ru-en`: `--dataset_name wmt19 --dataset_config "ru-en"` no cookies: ``` Traceback (most recent call last): File "./run_seq2seq.py", line 661, in <module> main() File "./run_seq2seq.py", line 317, in main datasets = load_dataset(data_args.dataset_name, data_args.dataset_config_name) File "/mnt/nvme1/code/huggingface/datasets-master/src/datasets/load.py", line 740, in load_dataset builder_instance.download_and_prepare( File "/mnt/nvme1/code/huggingface/datasets-master/src/datasets/builder.py", line 572, in download_and_prepare self._download_and_prepare( File "/mnt/nvme1/code/huggingface/datasets-master/src/datasets/builder.py", line 628, in _download_and_prepare split_generators = self._split_generators(dl_manager, **split_generators_kwargs) File "/home/stas/.cache/huggingface/modules/datasets_modules/datasets/wmt19/436092de5f3faaf0fc28bc84875475b384e90a5470fa6afaee11039ceddc5052/wmt_utils.py", line 755, in _split_generators downloaded_files = dl_manager.download_and_extract(urls_to_download) File "/mnt/nvme1/code/huggingface/datasets-master/src/datasets/utils/download_manager.py", line 276, in download_and_extract return self.extract(self.download(url_or_urls)) File "/mnt/nvme1/code/huggingface/datasets-master/src/datasets/utils/download_manager.py", line 191, in download downloaded_path_or_paths = map_nested( File "/mnt/nvme1/code/huggingface/datasets-master/src/datasets/utils/py_utils.py", line 233, in map_nested mapped = [ File "/mnt/nvme1/code/huggingface/datasets-master/src/datasets/utils/py_utils.py", line 234, in <listcomp> _single_map_nested((function, obj, types, None, True)) for obj in tqdm(iterable, disable=disable_tqdm) File "/mnt/nvme1/code/huggingface/datasets-master/src/datasets/utils/py_utils.py", line 190, in _single_map_nested mapped = [_single_map_nested((function, v, types, None, True)) for v in pbar] File "/mnt/nvme1/code/huggingface/datasets-master/src/datasets/utils/py_utils.py", line 190, in <listcomp> mapped = [_single_map_nested((function, v, types, None, True)) for v in pbar] File "/mnt/nvme1/code/huggingface/datasets-master/src/datasets/utils/py_utils.py", line 172, in _single_map_nested return function(data_struct) File "/mnt/nvme1/code/huggingface/datasets-master/src/datasets/utils/download_manager.py", line 211, in _download return cached_path(url_or_filename, download_config=download_config) File "/mnt/nvme1/code/huggingface/datasets-master/src/datasets/utils/file_utils.py", line 274, in cached_path output_path = get_from_cache( File "/mnt/nvme1/code/huggingface/datasets-master/src/datasets/utils/file_utils.py", line 584, in get_from_cache raise FileNotFoundError("Couldn't find file at {}".format(url)) FileNotFoundError: Couldn't find file at https://storage.googleapis.com/tfdataset-data/downloadataset/uncorpus/UNv1.0.en-ru.tar.gz ```

https://api.github.com/repos/huggingface/datasets/issues/1893/timeline

completed

https://api.github.com/repos/huggingface/datasets/issues/1892

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

https://api.github.com/repos/huggingface/datasets/issues/1892/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/1892/comments

https://api.github.com/repos/huggingface/datasets/issues/1892/events

https://github.com/huggingface/datasets/issues/1892

MDU6SXNzdWU4MDk1NTQxNzQ=

request to mirror wmt datasets, as they are really slow to download

closed

CONTRIBUTOR

Would it be possible to mirror the wmt data files under hf? Some of them take hours to download and not because of the local speed. They are all quite small datasets, just extremely slow to download. Thank you!

https://api.github.com/repos/huggingface/datasets/issues/1892/timeline

completed

https://api.github.com/repos/huggingface/datasets/issues/1891

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

https://api.github.com/repos/huggingface/datasets/issues/1891/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/1891/comments

https://api.github.com/repos/huggingface/datasets/issues/1891/events

https://github.com/huggingface/datasets/issues/1891

MDU6SXNzdWU4MDk1NTAwMDE=

suggestion to improve a missing dataset error

closed

CONTRIBUTOR

I was using `--dataset_name wmt19` all was good. Then thought perhaps wmt20 is out, so I tried to use `--dataset_name wmt20`, got 3 different errors (1 repeated twice), none telling me the real issue - that `wmt20` isn't in the `datasets`: ``` True, predict_with_generate=True) Traceback (most recent call last): File "/mnt/nvme1/code/huggingface/datasets-master/src/datasets/load.py", line 323, in prepare_module local_path = cached_path(file_path, download_config=download_config) File "/mnt/nvme1/code/huggingface/datasets-master/src/datasets/utils/file_utils.py", line 274, in cached_path output_path = get_from_cache( File "/mnt/nvme1/code/huggingface/datasets-master/src/datasets/utils/file_utils.py", line 584, in get_from_cache raise FileNotFoundError("Couldn't find file at {}".format(url)) FileNotFoundError: Couldn't find file at https://raw.githubusercontent.com/huggingface/datasets/master/datasets/wmt20/wmt20.py During handling of the above exception, another exception occurred: Traceback (most recent call last): File "/mnt/nvme1/code/huggingface/datasets-master/src/datasets/load.py", line 335, in prepare_module local_path = cached_path(file_path, download_config=download_config) File "/mnt/nvme1/code/huggingface/datasets-master/src/datasets/utils/file_utils.py", line 274, in cached_path output_path = get_from_cache( File "/mnt/nvme1/code/huggingface/datasets-master/src/datasets/utils/file_utils.py", line 584, in get_from_cache raise FileNotFoundError("Couldn't find file at {}".format(url)) FileNotFoundError: Couldn't find file at https://raw.githubusercontent.com/huggingface/datasets/master/datasets/wmt20/wmt20.py During handling of the above exception, another exception occurred: Traceback (most recent call last): File "./run_seq2seq.py", line 661, in <module> main() File "./run_seq2seq.py", line 317, in main datasets = load_dataset(data_args.dataset_name, data_args.dataset_config_name) File "/mnt/nvme1/code/huggingface/datasets-master/src/datasets/load.py", line 706, in load_dataset module_path, hash, resolved_file_path = prepare_module( File "/mnt/nvme1/code/huggingface/datasets-master/src/datasets/load.py", line 343, in prepare_module raise FileNotFoundError( FileNotFoundError: Couldn't find file locally at wmt20/wmt20.py, or remotely at https://raw.githubusercontent.com/huggingface/datasets/master/datasets/wmt20/wmt20.py. The file is also not present on the master branch on github. ``` Suggestion: if it is not in a local path, check that there is an actual `https://github.com/huggingface/datasets/tree/master/datasets/wmt20` first and assert "dataset `wmt20` doesn't exist in datasets", rather than trying to find a load script - since the whole repo is not there. The error occured when running: ``` cd examples/seq2seq export BS=16; rm -r output_dir; PYTHONPATH=../../src USE_TF=0 CUDA_VISIBLE_DEVICES=0 python ./run_seq2seq.py --model_name_or_path t5-small --output_dir output_dir --adam_eps 1e-06 --do_eval --evaluation_strategy=steps --label_smoothing 0.1 --learning_rate 3e-5 --logging_first_step --logging_steps 1000 --max_source_length 128 --max_target_length 128 --num_train_epochs 1 --overwrite_output_dir --per_device_eval_batch_size $BS --predict_with_generate --eval_steps 25000 --sortish_sampler --task translation_en_to_ro --val_max_target_length 128 --warmup_steps 500 --max_val_samples 500 --dataset_name wmt20 --dataset_config "ro-en" --source_prefix "translate English to Romanian: " ``` Thanks.

https://api.github.com/repos/huggingface/datasets/issues/1891/timeline

completed

https://api.github.com/repos/huggingface/datasets/issues/1890

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

https://api.github.com/repos/huggingface/datasets/issues/1890/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/1890/comments

https://api.github.com/repos/huggingface/datasets/issues/1890/events

https://github.com/huggingface/datasets/pull/1890

MDExOlB1bGxSZXF1ZXN0NTc0MjY0OTMx

Reformat dataset cards section titles

closed

MEMBER

Titles are formatted like [Foo](#foo) instead of just Foo

https://api.github.com/repos/huggingface/datasets/issues/1890/timeline

https://api.github.com/repos/huggingface/datasets/issues/1889

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

https://api.github.com/repos/huggingface/datasets/issues/1889/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/1889/comments

https://api.github.com/repos/huggingface/datasets/issues/1889/events

https://github.com/huggingface/datasets/pull/1889

MDExOlB1bGxSZXF1ZXN0NTc0MTY1NDAz

Implement to_dict and to_pandas for Dataset

closed

CONTRIBUTOR

With options to return a generator or the full dataset

https://api.github.com/repos/huggingface/datasets/issues/1889/timeline

https://api.github.com/repos/huggingface/datasets/issues/1888

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

https://api.github.com/repos/huggingface/datasets/issues/1888/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/1888/comments

https://api.github.com/repos/huggingface/datasets/issues/1888/events

https://github.com/huggingface/datasets/pull/1888

MDExOlB1bGxSZXF1ZXN0NTc0MTM2MDU4

Docs for adding new column on formatted dataset

closed

MEMBER

As mentioned in #1872 we should add in the documentation how the format gets updated when new columns are added Close #1872

https://api.github.com/repos/huggingface/datasets/issues/1888/timeline

https://api.github.com/repos/huggingface/datasets/issues/1887

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

https://api.github.com/repos/huggingface/datasets/issues/1887/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/1887/comments

https://api.github.com/repos/huggingface/datasets/issues/1887/events

https://github.com/huggingface/datasets/pull/1887

MDExOlB1bGxSZXF1ZXN0NTc0MTI2NTMy

Implement to_csv for Dataset

closed

CONTRIBUTOR

cc @thomwolf `to_csv` supports passing either a file path or a *binary* file object The writing is batched to avoid loading the whole table in memory

https://api.github.com/repos/huggingface/datasets/issues/1887/timeline

https://api.github.com/repos/huggingface/datasets/issues/1886

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

https://api.github.com/repos/huggingface/datasets/issues/1886/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/1886/comments

https://api.github.com/repos/huggingface/datasets/issues/1886/events

https://github.com/huggingface/datasets/pull/1886

MDExOlB1bGxSZXF1ZXN0NTc0MTE5ODcz

Common voice

closed

CONTRIBUTOR

Started filling out information about the dataset and a dataset card. To do Create tagging file Update the common_voice.py file with more information

https://api.github.com/repos/huggingface/datasets/issues/1886/timeline

https://api.github.com/repos/huggingface/datasets/issues/1885

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

https://api.github.com/repos/huggingface/datasets/issues/1885/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/1885/comments

https://api.github.com/repos/huggingface/datasets/issues/1885/events

https://github.com/huggingface/datasets/pull/1885

MDExOlB1bGxSZXF1ZXN0NTczODQyNzcz

add missing info on how to add large files

closed

CONTRIBUTOR

Thanks to @lhoestq's instructions I was able to add data files to a custom dataset repo. This PR is attempting to tell others how to do the same if they need to. @lhoestq

https://api.github.com/repos/huggingface/datasets/issues/1885/timeline

https://api.github.com/repos/huggingface/datasets/issues/1884

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

https://api.github.com/repos/huggingface/datasets/issues/1884/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/1884/comments

https://api.github.com/repos/huggingface/datasets/issues/1884/events

https://github.com/huggingface/datasets/pull/1884

MDExOlB1bGxSZXF1ZXN0NTczNzQwNzI5

dtype fix when using numpy arrays

closed

CONTRIBUTOR

As discussed in #625 this fix lets the user preserve the dtype of numpy array to pyarrow array which was getting lost due to conversion of numpy array -> list -> pyarrow array

https://api.github.com/repos/huggingface/datasets/issues/1884/timeline

https://api.github.com/repos/huggingface/datasets/issues/1883

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

https://api.github.com/repos/huggingface/datasets/issues/1883/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/1883/comments

https://api.github.com/repos/huggingface/datasets/issues/1883/events

https://github.com/huggingface/datasets/pull/1883

MDExOlB1bGxSZXF1ZXN0NTczNzM2NTIz

Add not-in-place implementations for several dataset transforms

closed

CONTRIBUTOR

Should we deprecate in-place versions of such methods?

https://api.github.com/repos/huggingface/datasets/issues/1883/timeline

https://api.github.com/repos/huggingface/datasets/issues/1882

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

https://api.github.com/repos/huggingface/datasets/issues/1882/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/1882/comments

https://api.github.com/repos/huggingface/datasets/issues/1882/events

https://github.com/huggingface/datasets/pull/1882

MDExOlB1bGxSZXF1ZXN0NTczNzA4OTEw

Create Remote Manager

open

MEMBER

Refactoring to separate the concern of remote (HTTP/FTP requests) management.

https://api.github.com/repos/huggingface/datasets/issues/1882/timeline

https://api.github.com/repos/huggingface/datasets/issues/1881

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

https://api.github.com/repos/huggingface/datasets/issues/1881/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/1881/comments

https://api.github.com/repos/huggingface/datasets/issues/1881/events

https://github.com/huggingface/datasets/pull/1881

MDExOlB1bGxSZXF1ZXN0NTczNTk1Nzkw

`list_datasets()` returns a list of strings, not objects

closed

CONTRIBUTOR

Here and there in the docs there is still stuff like this: ```python >>> datasets_list = list_datasets() >>> print(', '.join(dataset.id for dataset in datasets_list)) ``` However, my understanding is that `list_datasets()` returns a list of strings rather than a list of objects.

https://api.github.com/repos/huggingface/datasets/issues/1881/timeline

https://api.github.com/repos/huggingface/datasets/issues/1880

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

https://api.github.com/repos/huggingface/datasets/issues/1880/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/1880/comments

https://api.github.com/repos/huggingface/datasets/issues/1880/events

https://github.com/huggingface/datasets/pull/1880

MDExOlB1bGxSZXF1ZXN0NTczNTgzNjg0

Update multi_woz_v22 checksums

closed

MEMBER

As noticed in #1876 the checksums of this dataset are outdated. I updated them in this PR

https://api.github.com/repos/huggingface/datasets/issues/1880/timeline

https://api.github.com/repos/huggingface/datasets/issues/1879

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

https://api.github.com/repos/huggingface/datasets/issues/1879/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/1879/comments

https://api.github.com/repos/huggingface/datasets/issues/1879/events

https://github.com/huggingface/datasets/pull/1879

MDExOlB1bGxSZXF1ZXN0NTczNTY1NDAx

Replace flatten_nested

closed

MEMBER

Replace `flatten_nested` with `NestedDataStructure.flatten`. This is a first step towards having all NestedDataStructure logic as a separated concern, independent of the caller/user of the data structure. Eventually, all checks (whether the underlying data is list, dict, etc.) will be only inside this class. I have also generalized the flattening, and now it handles multiple levels of nesting.

https://api.github.com/repos/huggingface/datasets/issues/1879/timeline

https://api.github.com/repos/huggingface/datasets/issues/1878

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

https://api.github.com/repos/huggingface/datasets/issues/1878/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/1878/comments

https://api.github.com/repos/huggingface/datasets/issues/1878/events

https://github.com/huggingface/datasets/pull/1878

MDExOlB1bGxSZXF1ZXN0NTczNTUyODk3

Add LJ Speech dataset

closed

MEMBER

This PR adds the LJ Speech dataset (https://keithito.com/LJ-Speech-Dataset/) As requested by #1841 The ASR format is based on #1767 There are a couple of quirks that should be addressed: - I tagged this dataset as `other-other-automatic-speech-recognition` and `other-other-text-to-speech` (as classified by paperswithcode). Since the number of speech datasets is about to grow, maybe these categories should be added to the main list? - Similarly to #1767 this dataset uses only a single dummy sample to reduce the zip size (`wav`s are quite heavy). Is there a plan to allow LFS or S3 usage for dummy data in the repo? - The dataset is distributed under the Public Domain license, which is not used anywhere else in the repo, AFAIK. Do you think Public Domain is worth adding to the tagger app as well? Pinging @patrickvonplaten to review

https://api.github.com/repos/huggingface/datasets/issues/1878/timeline

https://api.github.com/repos/huggingface/datasets/issues/1877

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

https://api.github.com/repos/huggingface/datasets/issues/1877/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/1877/comments

https://api.github.com/repos/huggingface/datasets/issues/1877/events

https://github.com/huggingface/datasets/issues/1877

MDU6SXNzdWU4MDg0NjIyNzI=

Allow concatenation of both in-memory and on-disk datasets

closed

MEMBER

This is a prerequisite for the addition of the `add_item` feature (see #1870). Currently there is one assumption that we would need to change: a dataset is either fully in memory (dataset._data_files is empty), or the dataset can be reloaded from disk (using the dataset._data_files). This assumption is used for pickling for example: - in-memory dataset can just be pickled/unpickled in-memory - on-disk dataset can be unloaded to only keep the filepaths when pickling, and then reloaded from the disk when unpickling Maybe let's have a design that allows a Dataset to have a Table that can be rebuilt from heterogenous sources like in-memory tables or on-disk tables ? This could also be further extended in the future One idea would be to define a list of sources and each source implements a way to reload its corresponding pyarrow Table. Then the dataset would be the concatenation of all these tables. Depending on the source type, the serialization using pickle would be different. In-memory data would be copied while on-disk data would simply be replaced by the path to these data. If you have some ideas you would like to share about the design/API feel free to do so :) cc @albertvillanova

https://api.github.com/repos/huggingface/datasets/issues/1877/timeline

completed

https://api.github.com/repos/huggingface/datasets/issues/1876

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

https://api.github.com/repos/huggingface/datasets/issues/1876/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/1876/comments

https://api.github.com/repos/huggingface/datasets/issues/1876/events

https://github.com/huggingface/datasets/issues/1876

MDU6SXNzdWU4MDgwMjU4NTk=

load_dataset("multi_woz_v22") NonMatchingChecksumError

closed

NONE

Hi, it seems that loading the multi_woz_v22 dataset gives a NonMatchingChecksumError. To reproduce: `dataset = load_dataset('multi_woz_v22','v2.2_active_only',split='train')` This will give the following error: ``` raise NonMatchingChecksumError(error_msg + str(bad_urls)) datasets.utils.info_utils.NonMatchingChecksumError: Checksums didn't match for dataset source files: ['https://github.com/budzianowski/multiwoz/raw/master/data/MultiWOZ_2.2/dialog_acts.json', 'https://github.com/budzianowski/multiwoz/raw/master/data/MultiWOZ_2.2/train/dialogues_001.json', 'https://github.com/budzianowski/multiwoz/raw/master/data/MultiWOZ_2.2/train/dialogues_003.json', 'https://github.com/budzianowski/multiwoz/raw/master/data/MultiWOZ_2.2/train/dialogues_004.json', 'https://github.com/budzianowski/multiwoz/raw/master/data/MultiWOZ_2.2/train/dialogues_005.json', 'https://github.com/budzianowski/multiwoz/raw/master/data/MultiWOZ_2.2/train/dialogues_006.json', 'https://github.com/budzianowski/multiwoz/raw/master/data/MultiWOZ_2.2/train/dialogues_007.json', 'https://github.com/budzianowski/multiwoz/raw/master/data/MultiWOZ_2.2/train/dialogues_008.json', 'https://github.com/budzianowski/multiwoz/raw/master/data/MultiWOZ_2.2/train/dialogues_009.json', 'https://github.com/budzianowski/multiwoz/raw/master/data/MultiWOZ_2.2/train/dialogues_010.json', 'https://github.com/budzianowski/multiwoz/raw/master/data/MultiWOZ_2.2/train/dialogues_012.json', 'https://github.com/budzianowski/multiwoz/raw/master/data/MultiWOZ_2.2/train/dialogues_013.json', 'https://github.com/budzianowski/multiwoz/raw/master/data/MultiWOZ_2.2/train/dialogues_014.json', 'https://github.com/budzianowski/multiwoz/raw/master/data/MultiWOZ_2.2/train/dialogues_015.json', 'https://github.com/budzianowski/multiwoz/raw/master/data/MultiWOZ_2.2/train/dialogues_016.json', 'https://github.com/budzianowski/multiwoz/raw/master/data/MultiWOZ_2.2/train/dialogues_017.json', 'https://github.com/budzianowski/multiwoz/raw/master/data/MultiWOZ_2.2/dev/dialogues_001.json', 'https://github.com/budzianowski/multiwoz/raw/master/data/MultiWOZ_2.2/dev/dialogues_002.json', 'https://github.com/budzianowski/multiwoz/raw/master/data/MultiWOZ_2.2/test/dialogues_001.json', 'https://github.com/budzianowski/multiwoz/raw/master/data/MultiWOZ_2.2/test/dialogues_002.json'] ```

https://api.github.com/repos/huggingface/datasets/issues/1876/timeline

completed

https://api.github.com/repos/huggingface/datasets/issues/1875

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

https://api.github.com/repos/huggingface/datasets/issues/1875/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/1875/comments

https://api.github.com/repos/huggingface/datasets/issues/1875/events

https://github.com/huggingface/datasets/pull/1875

MDExOlB1bGxSZXF1ZXN0NTczMDM2NzE0

Adding sari metric

closed

CONTRIBUTOR

Adding SARI metric that is used in evaluation of text simplification. This is required as part of the GEM benchmark.

https://api.github.com/repos/huggingface/datasets/issues/1875/timeline

https://api.github.com/repos/huggingface/datasets/issues/1874

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

https://api.github.com/repos/huggingface/datasets/issues/1874/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/1874/comments

https://api.github.com/repos/huggingface/datasets/issues/1874/events

https://github.com/huggingface/datasets/pull/1874

MDExOlB1bGxSZXF1ZXN0NTcyOTYzMjAy

Adding Europarl Bilingual dataset

closed

CONTRIBUTOR

Implementation of Europarl bilingual dataset from described [here](https://opus.nlpl.eu/Europarl.php). This dataset allows to use every language pair detailed in the original dataset. The loading script manages also the small errors contained in the original dataset (in very rare cases (1 over 10M) there are some keys that references to inexistent sentences). I chose to follow the the style of a similar dataset available in this repository: `multi_para_crawl`.

https://api.github.com/repos/huggingface/datasets/issues/1874/timeline

https://api.github.com/repos/huggingface/datasets/issues/1873

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

https://api.github.com/repos/huggingface/datasets/issues/1873/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/1873/comments

https://api.github.com/repos/huggingface/datasets/issues/1873/events

https://github.com/huggingface/datasets/pull/1873

MDExOlB1bGxSZXF1ZXN0NTcyOTM4MTYy

add iapp_wiki_qa_squad

closed

CONTRIBUTOR

`iapp_wiki_qa_squad` is an extractive question answering dataset from Thai Wikipedia articles. It is adapted from [the original iapp-wiki-qa-dataset](https://github.com/iapp-technology/iapp-wiki-qa-dataset) to [SQuAD](https://rajpurkar.github.io/SQuAD-explorer/) format, resulting in 5761/742/739 questions from 1529/191/192 articles.

https://api.github.com/repos/huggingface/datasets/issues/1873/timeline

https://api.github.com/repos/huggingface/datasets/issues/1872

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

https://api.github.com/repos/huggingface/datasets/issues/1872/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/1872/comments

https://api.github.com/repos/huggingface/datasets/issues/1872/events

https://github.com/huggingface/datasets/issues/1872

MDU6SXNzdWU4MDc3MTE5MzU=

Adding a new column to the dataset after set_format was called

closed

NONE

Hi, thanks for the nice library. I'm in the process of creating a custom dataset, which has a mix of tensors and lists of strings. I stumbled upon an error and want to know if its a problem on my side. I load some lists of strings and integers, then call `data.set_format("torch", columns=["some_integer_column1", "some_integer_column2"], output_all_columns=True)`. This converts the integer columns into tensors, but keeps the lists of strings as they are. I then call `map` to add a new column to my dataset, which is a **list of strings**. Once I iterate through my dataset, I get an error that the new column can't be converted into a tensor (which is probably caused by `set_format`). Below some pseudo code: ```python def augment_func(sample: Dict) -> Dict: # do something return { "some_integer_column1" : augmented_data["some_integer_column1"], # <-- tensor "some_integer_column2" : augmented_data["some_integer_column2"], # <-- tensor "NEW_COLUMN": targets, # <-- list of strings } data = datasets.load_dataset(__file__, data_dir="...", split="train") data.set_format("torch", columns=["some_integer_column1", "some_integer_column2"], output_all_columns=True) augmented_dataset = data.map(augment_func, batched=False) for sample in augmented_dataset: print(sample) # fails ``` and the exception: ```python Traceback (most recent call last): File "dataset.py", line 487, in <module> main() File "dataset.py", line 471, in main for sample in augmented_dataset: File "lib/python3.8/site-packages/datasets/arrow_dataset.py", line 697, in __iter__ yield self._getitem( File "lib/python3.8/site-packages/datasets/arrow_dataset.py", line 1069, in _getitem outputs = self._convert_outputs( File "lib/python3.8/site-packages/datasets/arrow_dataset.py", line 890, in _convert_outputs v = map_nested(command, v, **map_nested_kwargs) File "lib/python3.8/site-packages/datasets/utils/py_utils.py", line 225, in map_nested return function(data_struct) File "lib/python3.8/site-packages/datasets/arrow_dataset.py", line 850, in command return [map_nested(command, i, **map_nested_kwargs) for i in x] File "lib/python3.8/site-packages/datasets/arrow_dataset.py", line 850, in <listcomp> return [map_nested(command, i, **map_nested_kwargs) for i in x] File "lib/python3.8/site-packages/datasets/utils/py_utils.py", line 225, in map_nested return function(data_struct) File "lib/python3.8/site-packages/datasets/arrow_dataset.py", line 850, in command return [map_nested(command, i, **map_nested_kwargs) for i in x] File "lib/python3.8/site-packages/datasets/arrow_dataset.py", line 850, in <listcomp> return [map_nested(command, i, **map_nested_kwargs) for i in x] File "lib/python3.8/site-packages/datasets/utils/py_utils.py", line 225, in map_nested return function(data_struct) File "lib/python3.8/site-packages/datasets/arrow_dataset.py", line 851, in command return torch.tensor(x, **format_kwargs) TypeError: new(): invalid data type 'str' ``` Thanks!

https://api.github.com/repos/huggingface/datasets/issues/1872/timeline

completed

https://api.github.com/repos/huggingface/datasets/issues/1871

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

https://api.github.com/repos/huggingface/datasets/issues/1871/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/1871/comments

https://api.github.com/repos/huggingface/datasets/issues/1871/events

https://github.com/huggingface/datasets/pull/1871

MDExOlB1bGxSZXF1ZXN0NTcyODk5Nzgz

Add newspop dataset

closed

CONTRIBUTOR

https://api.github.com/repos/huggingface/datasets/issues/1871/timeline

https://api.github.com/repos/huggingface/datasets/issues/1870

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

https://api.github.com/repos/huggingface/datasets/issues/1870/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/1870/comments

https://api.github.com/repos/huggingface/datasets/issues/1870/events

https://github.com/huggingface/datasets/pull/1870

MDExOlB1bGxSZXF1ZXN0NTcyNTc4Mjc4

Implement Dataset add_item

closed

MEMBER

Implement `Dataset.add_item`. Close #1854.

https://api.github.com/repos/huggingface/datasets/issues/1870/timeline

https://api.github.com/repos/huggingface/datasets/issues/1869

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

https://api.github.com/repos/huggingface/datasets/issues/1869/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/1869/comments

https://api.github.com/repos/huggingface/datasets/issues/1869/events

https://github.com/huggingface/datasets/pull/1869

MDExOlB1bGxSZXF1ZXN0NTcyNDU0NTMy

Remove outdated commands in favor of huggingface-cli

closed

MEMBER

Removing the old user commands since `huggingface_hub` is going to be used instead. cc @julien-c

https://api.github.com/repos/huggingface/datasets/issues/1869/timeline

https://api.github.com/repos/huggingface/datasets/issues/1868

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

https://api.github.com/repos/huggingface/datasets/issues/1868/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/1868/comments

https://api.github.com/repos/huggingface/datasets/issues/1868/events

https://github.com/huggingface/datasets/pull/1868

MDExOlB1bGxSZXF1ZXN0NTcyNDM2MjA0

Update oscar sizes

closed

MEMBER

This commit https://github.com/huggingface/datasets/commit/837a152e4724adc5308e2c4481908c00a8d93383 removed empty lines from the oscar deduplicated datasets. This PR updates the size of each deduplicated dataset to fix possible `NonMatchingSplitsSizesError` errors. cc @cahya-wirawan

https://api.github.com/repos/huggingface/datasets/issues/1868/timeline

https://api.github.com/repos/huggingface/datasets/issues/1867

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

https://api.github.com/repos/huggingface/datasets/issues/1867/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/1867/comments

https://api.github.com/repos/huggingface/datasets/issues/1867/events

https://github.com/huggingface/datasets/issues/1867

MDU6SXNzdWU4MDcxMjcxODE=

ERROR WHEN USING SET_TRANSFORM()

closed

NONE

Hi, I'm trying to use dataset.set_transform(encode) as @lhoestq told me in this issue: https://github.com/huggingface/datasets/issues/1825#issuecomment-774202797 However, when I try to use Trainer from transformers with such dataset, it throws an error: ``` TypeError: __init__() missing 1 required positional argument: 'transform' [INFO|trainer.py:357] 2021-02-12 10:18:09,893 >> The following columns in the training set don't have a corresponding argument in `AlbertForMaskedLM.forward` and have been ignored: text. Exception in device=TPU:0: __init__() missing 1 required positional argument: 'transform' Traceback (most recent call last): File "/anaconda3/envs/torch-xla-1.7/lib/python3.6/site-packages/torch_xla/distributed/xla_multiprocessing.py", line 330, in _mp_start_fn _start_fn(index, pf_cfg, fn, args) File "/anaconda3/envs/torch-xla-1.7/lib/python3.6/site-packages/torch_xla/distributed/xla_multiprocessing.py", line 324, in _start_fn fn(gindex, *args) File "/home/alejandro_vaca/transformers/examples/language-modeling/run_mlm_wwm.py", line 368, in _mp_fn main() File "/home/alejandro_vaca/transformers/examples/language-modeling/run_mlm_wwm.py", line 332, in main data_collator=data_collator, File "/anaconda3/envs/torch-xla-1.7/lib/python3.6/site-packages/transformers/trainer.py", line 286, in __init__ self._remove_unused_columns(self.train_dataset, description="training") File "/anaconda3/envs/torch-xla-1.7/lib/python3.6/site-packages/transformers/trainer.py", line 359, in _remove_unused_columns dataset.set_format(type=dataset.format["type"], columns=columns) File "/home/alejandro_vaca/datasets/src/datasets/fingerprint.py", line 312, in wrapper out = func(self, *args, **kwargs) File "/home/alejandro_vaca/datasets/src/datasets/arrow_dataset.py", line 818, in set_format _ = get_formatter(type, **format_kwargs) File "/home/alejandro_vaca/datasets/src/datasets/formatting/__init__.py", line 112, in get_formatter return _FORMAT_TYPES[format_type](**format_kwargs) TypeError: __init__() missing 1 required positional argument: 'transform' ``` The code I'm using: ```{python} def tokenize_function(examples): # Remove empty lines examples["text"] = [line for line in examples["text"] if len(line) > 0 and not line.isspace()] return tokenizer(examples["text"], padding=padding, truncation=True, max_length=data_args.max_seq_length) datasets.set_transform(tokenize_function) data_collator = DataCollatorForWholeWordMask(tokenizer=tokenizer, mlm_probability=data_args.mlm_probability) # Initialize our Trainer trainer = Trainer( model=model, args=training_args, train_dataset=datasets["train"] if training_args.do_train else None, eval_dataset=datasets["val"] if training_args.do_eval else None, tokenizer=tokenizer, data_collator=data_collator, ) ``` I've installed from source, master branch.

https://api.github.com/repos/huggingface/datasets/issues/1867/timeline

completed

https://api.github.com/repos/huggingface/datasets/issues/1866

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

https://api.github.com/repos/huggingface/datasets/issues/1866/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/1866/comments

https://api.github.com/repos/huggingface/datasets/issues/1866/events

https://github.com/huggingface/datasets/pull/1866

MDExOlB1bGxSZXF1ZXN0NTcyMzM3NDQ1

Add dataset for Financial PhraseBank

closed

CONTRIBUTOR

https://api.github.com/repos/huggingface/datasets/issues/1866/timeline

https://api.github.com/repos/huggingface/datasets/issues/1865

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

https://api.github.com/repos/huggingface/datasets/issues/1865/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/1865/comments

https://api.github.com/repos/huggingface/datasets/issues/1865/events

https://github.com/huggingface/datasets/pull/1865

MDExOlB1bGxSZXF1ZXN0NTcxODE2ODI2

Updated OPUS Open Subtitles Dataset with metadata information

closed

CONTRIBUTOR

Close #1844 Problems: - I ran `python datasets-cli test datasets/open_subtitles --save_infos --all_configs`, hence the change in `dataset_infos.json`, but it appears that the metadata features have not been added for all pairs. Any idea why that might be? - Possibly related to the above, I tried doing `pip uninstall datasets && pip install -e ".[dev]"` after the changes, and loading the dataset via `load_dataset("open_subtitles", lang1='hi', lang2='it')` to check if the update worked, but the loaded dataset did not contain the metadata fields (neither in the features nor doing `next(iter(dataset['train']))`). What step(s) did I miss? Questions: - Is it ok to have a `classmethod` in there? I have not seen any in the few other datasets I have checked. I could make it a local method of the `_generate_examples` method, but I'd rather not duplicate the logic...

https://api.github.com/repos/huggingface/datasets/issues/1865/timeline

https://api.github.com/repos/huggingface/datasets/issues/1864

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

https://api.github.com/repos/huggingface/datasets/issues/1864/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/1864/comments

https://api.github.com/repos/huggingface/datasets/issues/1864/events

https://github.com/huggingface/datasets/issues/1864

MDU6SXNzdWU4MDYxNzI4NDM=

Add Winogender Schemas

closed

CONTRIBUTOR

## Adding a Dataset - **Name:** Winogender Schemas - **Description:** Winogender Schemas (inspired by Winograd Schemas) are minimal pairs of sentences that differ only by the gender of one pronoun in the sentence, designed to test for the presence of gender bias in automated coreference resolution systems. - **Paper:** https://arxiv.org/abs/1804.09301 - **Data:** https://github.com/rudinger/winogender-schemas (see data directory) - **Motivation:** Testing gender bias in automated coreference resolution systems, improve coreference resolution in general. Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).

https://api.github.com/repos/huggingface/datasets/issues/1864/timeline

completed

https://api.github.com/repos/huggingface/datasets/issues/1863

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

https://api.github.com/repos/huggingface/datasets/issues/1863/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/1863/comments

https://api.github.com/repos/huggingface/datasets/issues/1863/events

https://github.com/huggingface/datasets/issues/1863

MDU6SXNzdWU4MDYxNzEzMTE=

Add WikiCREM

open

CONTRIBUTOR

## Adding a Dataset - **Name:** WikiCREM - **Description:** A large unsupervised corpus for coreference resolution. - **Paper:** https://arxiv.org/abs/1905.06290 - **Github repo:**: https://github.com/vid-koci/bert-commonsense - **Data:** https://ora.ox.ac.uk/objects/uuid:c83e94bb-7584-41a1-aef9-85b0e764d9e3 - **Motivation:** Coreference resolution, common sense reasoning Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).

https://api.github.com/repos/huggingface/datasets/issues/1863/timeline

https://api.github.com/repos/huggingface/datasets/issues/1862

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

https://api.github.com/repos/huggingface/datasets/issues/1862/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/1862/comments

https://api.github.com/repos/huggingface/datasets/issues/1862/events

https://github.com/huggingface/datasets/pull/1862

MDExOlB1bGxSZXF1ZXN0NTcxMjc2ODAx

Fix writing GPU Faiss index

closed

MEMBER

As reported in by @corticalstack there is currently an error when we try to save a faiss index on GPU. I fixed that by checking the index `getDevice()` method before calling `index_gpu_to_cpu` Close #1859

https://api.github.com/repos/huggingface/datasets/issues/1862/timeline

https://api.github.com/repos/huggingface/datasets/issues/1861

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

https://api.github.com/repos/huggingface/datasets/issues/1861/labels{/name}

https://api.github.com/repos/huggingface/datasets/issues/1861/comments

https://api.github.com/repos/huggingface/datasets/issues/1861/events

https://github.com/huggingface/datasets/pull/1861

MDExOlB1bGxSZXF1ZXN0NTcxMjAwNjA1