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https://api.github.com/repos/huggingface/datasets/issues/2539 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2539/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2539/comments | https://api.github.com/repos/huggingface/datasets/issues/2539/events | https://github.com/huggingface/datasets/pull/2539 | 927,952,429 | MDExOlB1bGxSZXF1ZXN0Njc2MDI5MDY5 | 2,539 | remove wi_locness dataset due to licensing issues | {
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"Hi ! I'm sorry to hear that.\r\nThough we are not redistributing the dataset, we just provide a python script that downloads and process the dataset from its original source hosted at https://www.cl.cam.ac.uk\r\n\r\nTherefore I'm not sure what's the issue with licensing. What do you mean exactly ?",
"I think tha... | 1,624,433,732,000 | 1,624,632,762,000 | 1,624,632,762,000 | CONTRIBUTOR | null | It was brought to my attention that this dataset's license is not only missing, but also prohibits redistribution. I contacted the original author to apologize for this oversight and asked if we could still use it, but unfortunately we can't and the author kindly asked to take down this dataset. | {
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https://api.github.com/repos/huggingface/datasets/issues/2537 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2537/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2537/comments | https://api.github.com/repos/huggingface/datasets/issues/2537/events | https://github.com/huggingface/datasets/pull/2537 | 927,472,659 | MDExOlB1bGxSZXF1ZXN0Njc1NjI1OTY3 | 2,537 | Add Parquet loader + from_parquet and to_parquet | {
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"`pyarrow` 1.0.0 doesn't support some types in parquet, we'll have to bump its minimum version.\r\n\r\nAlso I still need to add dummy data to test the parquet builder.",
"I had to bump the minimum pyarrow version to 3.0.0 to properly support parquet.\r\n\r\nEverything is ready for review now :)\r\nI reused pretty... | 1,624,382,903,000 | 1,625,070,663,000 | 1,625,070,658,000 | MEMBER | null | Continuation of #2247
I added a "parquet" dataset builder, as well as the methods `Dataset.from_parquet` and `Dataset.to_parquet`.
As usual, the data are converted to arrow in a batched way to avoid loading everything in memory. | {
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https://api.github.com/repos/huggingface/datasets/issues/2535 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2535/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2535/comments | https://api.github.com/repos/huggingface/datasets/issues/2535/events | https://github.com/huggingface/datasets/pull/2535 | 927,334,349 | MDExOlB1bGxSZXF1ZXN0Njc1NTA3MTAw | 2,535 | Improve Features docs | {
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} | [] | closed | false | null | [] | null | [] | 1,624,374,207,000 | 1,624,455,643,000 | 1,624,455,643,000 | MEMBER | null | - Fix rendering and cross-references in Features docs
- Add docstrings to Features methods | {
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https://api.github.com/repos/huggingface/datasets/issues/2534 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2534/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2534/comments | https://api.github.com/repos/huggingface/datasets/issues/2534/events | https://github.com/huggingface/datasets/pull/2534 | 927,201,435 | MDExOlB1bGxSZXF1ZXN0Njc1MzkzODg0 | 2,534 | Sync with transformers disabling NOTSET | {
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"Nice thanks ! I think there are other places with\r\n```python\r\nnot_verbose = bool(logger.getEffectiveLevel() > WARNING)\r\n```\r\n\r\nCould you replace them as well ?",
"Sure @lhoestq! I was not sure if this change should only be circumscribed to `http_get`..."
] | 1,624,366,461,000 | 1,624,545,767,000 | 1,624,545,767,000 | MEMBER | null | Close #2528. | {
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https://api.github.com/repos/huggingface/datasets/issues/2533 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2533/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2533/comments | https://api.github.com/repos/huggingface/datasets/issues/2533/events | https://github.com/huggingface/datasets/pull/2533 | 927,193,264 | MDExOlB1bGxSZXF1ZXN0Njc1Mzg2OTMw | 2,533 | Add task template for automatic speech recognition | {
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"@SBrandeis @lhoestq i've integrated your suggestions, so this is ready for another review :)",
"Merging if it's good for you @lewtun :)"
] | 1,624,365,902,000 | 1,624,464,886,000 | 1,624,463,817,000 | MEMBER | null | This PR adds a task template for automatic speech recognition. In this task, the input is a path to an audio file which the model consumes to produce a transcription.
Usage:
```python
from datasets import load_dataset
from datasets.tasks import AutomaticSpeechRecognition
ds = load_dataset("timit_asr", split="train[:10]")
# Dataset({
# features: ['file', 'text', 'phonetic_detail', 'word_detail', 'dialect_region', 'sentence_type', 'speaker_id', 'id'],
# num_rows: 10
# })
task = AutomaticSpeechRecognition(audio_file_column="file", transcription_column="text")
ds.prepare_for_task(task)
# Dataset({
# features: ['audio_file', 'transcription'],
# num_rows: 10
# })
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/2532 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2532/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2532/comments | https://api.github.com/repos/huggingface/datasets/issues/2532/events | https://github.com/huggingface/datasets/issues/2532 | 927,063,196 | MDU6SXNzdWU5MjcwNjMxOTY= | 2,532 | Tokenizer's normalization preprocessor cause misalignment in return_offsets_mapping for tokenizer classification task | {
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"Hi @jerryIsHere, thanks for reporting the issue. But are you sure this is a bug in HuggingFace **Datasets**?",
"> Hi @jerryIsHere, thanks for reporting the issue. But are you sure this is a bug in HuggingFace **Datasets**?\r\n\r\nOh, I am sorry\r\nI would reopen the post on huggingface/transformers"
] | 1,624,356,498,000 | 1,624,425,445,000 | 1,624,425,445,000 | CONTRIBUTOR | null | [This colab notebook](https://colab.research.google.com/drive/151gKyo0YIwnlznrOHst23oYH_a3mAe3Z?usp=sharing) implements a token classification input pipeline extending the logic from [this hugging example](https://huggingface.co/transformers/custom_datasets.html#tok-ner).
The pipeline works fine with most instance in different languages, but unfortunately, [the Japanese Kana ligature (a form of abbreviation? I don't know Japanese well)](https://en.wikipedia.org/wiki/Kana_ligature) break the alignment of `return_offsets_mapping`:

Without the try catch block, it riase `ValueError: NumPy boolean array indexing assignment cannot assign 88 input values to the 87 output values where the mask is true`, example shown here [(another colab notebook)](https://colab.research.google.com/drive/1MmOqf3ppzzdKKyMWkn0bJy6DqzOO0SSm?usp=sharing)
It is clear that the normalizer is the process that break the alignment, as it is observed that `tokenizer._tokenizer.normalizer.normalize_str('ヿ')` return 'コト'.
One workaround is to include `tokenizer._tokenizer.normalizer.normalize_str` before the tokenizer preprocessing pipeline, which is also provided in the [first colab notebook](https://colab.research.google.com/drive/151gKyo0YIwnlznrOHst23oYH_a3mAe3Z?usp=sharing) with the name `udposTestDatasetWorkaround`.
I guess similar logics should be included inside the tokenizer and the offsets_mapping generation process such that user don't need to include them in their code. But I don't understand the code of tokenizer well that I think I am not able to do this.
p.s.
**I am using my own dataset building script in the provided example, but the script should be equivalent to the changes made by this [update](https://github.com/huggingface/datasets/pull/2466)**
`get_dataset `is just a simple wrapping for `load_dataset`
and the `tokenizer` is just `XLMRobertaTokenizerFast.from_pretrained("xlm-roberta-large")` | {
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https://api.github.com/repos/huggingface/datasets/issues/2531 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2531/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2531/comments | https://api.github.com/repos/huggingface/datasets/issues/2531/events | https://github.com/huggingface/datasets/pull/2531 | 927,017,924 | MDExOlB1bGxSZXF1ZXN0Njc1MjM2MDYz | 2,531 | Fix dev version | {
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However it happens that `1.8.0 > 1.8.0.dev0` for example.
Therefore we need to use `1.8.1.dev0` for example in this case.
I updated the dev version to use `1.8.1.dev0`, and I also added a comment in the setup.py in the release steps about this. | {
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https://api.github.com/repos/huggingface/datasets/issues/2530 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2530/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2530/comments | https://api.github.com/repos/huggingface/datasets/issues/2530/events | https://github.com/huggingface/datasets/pull/2530 | 927,013,773 | MDExOlB1bGxSZXF1ZXN0Njc1MjMyNDk0 | 2,530 | Fixed label parsing in the ProductReviews dataset | {
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"@lhoestq, can you please review this PR?\r\nWhat exactly is the problem in the test case? Should it matter?",
"Hi ! Thanks for fixing this :)\r\n\r\nThe CI fails for two reasons:\r\n- the `pretty_name` tag is missing in yaml tags in ./datasets/turkish_product_reviews/README.md. You can fix that by adding this in... | 1,624,353,165,000 | 1,624,366,520,000 | 1,624,366,360,000 | CONTRIBUTOR | null | Fixed issue with parsing dataset labels. | {
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https://api.github.com/repos/huggingface/datasets/issues/2529 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2529/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2529/comments | https://api.github.com/repos/huggingface/datasets/issues/2529/events | https://github.com/huggingface/datasets/pull/2529 | 926,378,812 | MDExOlB1bGxSZXF1ZXN0Njc0NjkxNjA5 | 2,529 | Add summarization template | {
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"> Nice thanks !\r\n> Could you just move the test outside of the BaseDatasetTest class please ? Otherwise it will unnecessarily be run twice.\r\n\r\nsure, on it! thanks for the explanations about the `self._to` method :)",
"@lhoestq i've moved all the task template tests outside of `BaseDatasetTest` and collecte... | 1,624,291,711,000 | 1,624,458,131,000 | 1,624,455,010,000 | MEMBER | null | This PR adds a task template for text summarization. As far as I can tell, we do not need to distinguish between "extractive" or "abstractive" summarization - both can be handled with this template.
Usage:
```python
from datasets import load_dataset
from datasets.tasks import Summarization
ds = load_dataset("xsum", split="train")
# Dataset({
# features: ['document', 'summary', 'id'],
# num_rows: 204045
# })
summarization = Summarization(text_column="document", summary_column="summary")
ds.prepare_for_task(summarization)
# Dataset({
# features: ['text', 'summary'],
# num_rows: 204045
# })
```
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https://api.github.com/repos/huggingface/datasets/issues/2528 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2528/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2528/comments | https://api.github.com/repos/huggingface/datasets/issues/2528/events | https://github.com/huggingface/datasets/issues/2528 | 926,314,656 | MDU6SXNzdWU5MjYzMTQ2NTY= | 2,528 | Logging cannot be set to NOTSET similar to transformers | {
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"Hi @joshzwiebel, thanks for reporting. We are going to align with `transformers`."
] | 1,624,287,894,000 | 1,624,545,767,000 | 1,624,545,767,000 | NONE | null | ## Describe the bug
In the transformers library you can set the verbosity level to logging.NOTSET to work around the usage of tqdm and IPywidgets, however in Datasets this is no longer possible. This is because transformers set the verbosity level of tqdm with [this](https://github.com/huggingface/transformers/blob/b53bc55ba9bb10d5ee279eab51a2f0acc5af2a6b/src/transformers/file_utils.py#L1449)
`disable=bool(logging.get_verbosity() == logging.NOTSET)`
and datasets accomplishes this like [so](https://github.com/huggingface/datasets/blob/83554e410e1ab8c6f705cfbb2df7953638ad3ac1/src/datasets/utils/file_utils.py#L493)
`not_verbose = bool(logger.getEffectiveLevel() > WARNING)`
## Steps to reproduce the bug
```python
import datasets
import logging
datasets.logging.get_verbosity = lambda : logging.NOTSET
datasets.load_dataset("patrickvonplaten/librispeech_asr_dummy")
```
## Expected results
The code should download and load the dataset as normal without displaying progress bars
## Actual results
```ImportError Traceback (most recent call last)
<ipython-input-4-aec65c0509c6> in <module>
----> 1 datasets.load_dataset("patrickvonplaten/librispeech_asr_dummy")
~/venv/lib/python3.7/site-packages/datasets/load.py in load_dataset(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, ignore_verifications, keep_in_memory, save_infos, script_version, use_auth_token, task, **config_kwargs)
713 dataset=True,
714 return_resolved_file_path=True,
--> 715 use_auth_token=use_auth_token,
716 )
717 # Set the base path for downloads as the parent of the script location
~/venv/lib/python3.7/site-packages/datasets/load.py in prepare_module(path, script_version, download_config, download_mode, dataset, force_local_path, dynamic_modules_path, return_resolved_file_path, **download_kwargs)
350 file_path = hf_bucket_url(path, filename=name, dataset=False)
351 try:
--> 352 local_path = cached_path(file_path, download_config=download_config)
353 except FileNotFoundError:
354 raise FileNotFoundError(
~/venv/lib/python3.7/site-packages/datasets/utils/file_utils.py in cached_path(url_or_filename, download_config, **download_kwargs)
289 use_etag=download_config.use_etag,
290 max_retries=download_config.max_retries,
--> 291 use_auth_token=download_config.use_auth_token,
292 )
293 elif os.path.exists(url_or_filename):
~/venv/lib/python3.7/site-packages/datasets/utils/file_utils.py in get_from_cache(url, cache_dir, force_download, proxies, etag_timeout, resume_download, user_agent, local_files_only, use_etag, max_retries, use_auth_token)
668 headers=headers,
669 cookies=cookies,
--> 670 max_retries=max_retries,
671 )
672
~/venv/lib/python3.7/site-packages/datasets/utils/file_utils.py in http_get(url, temp_file, proxies, resume_size, headers, cookies, timeout, max_retries)
493 initial=resume_size,
494 desc="Downloading",
--> 495 disable=not_verbose,
496 )
497 for chunk in response.iter_content(chunk_size=1024):
~/venv/lib/python3.7/site-packages/tqdm/notebook.py in __init__(self, *args, **kwargs)
217 total = self.total * unit_scale if self.total else self.total
218 self.container = self.status_printer(
--> 219 self.fp, total, self.desc, self.ncols)
220 self.sp = self.display
221
~/venv/lib/python3.7/site-packages/tqdm/notebook.py in status_printer(_, total, desc, ncols)
95 if IProgress is None: # #187 #451 #558 #872
96 raise ImportError(
---> 97 "IProgress not found. Please update jupyter and ipywidgets."
98 " See https://ipywidgets.readthedocs.io/en/stable"
99 "/user_install.html")
ImportError: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.8.0
- Platform: Linux-5.4.95-42.163.amzn2.x86_64-x86_64-with-debian-10.8
- Python version: 3.7.10
- PyArrow version: 3.0.0
I am running this code on Deepnote and which important to this issue **does not** support IPywidgets
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https://api.github.com/repos/huggingface/datasets/issues/2527 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2527/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2527/comments | https://api.github.com/repos/huggingface/datasets/issues/2527/events | https://github.com/huggingface/datasets/pull/2527 | 926,031,525 | MDExOlB1bGxSZXF1ZXN0Njc0MzkzNjQ5 | 2,527 | Replace bad `n>1M` size tag | {
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} | [] | closed | false | null | [] | null | [] | 1,624,268,555,000 | 1,624,288,010,000 | 1,624,288,009,000 | MEMBER | null | Some datasets were still using the old `n>1M` tag which has been replaced with tags `1M<n<10M`, etc.
This resulted in unexpected results when searching for datasets bigger than 1M on the hub, since it was only showing the ones with the tag `n>1M`. | {
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https://api.github.com/repos/huggingface/datasets/issues/2525 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2525/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2525/comments | https://api.github.com/repos/huggingface/datasets/issues/2525/events | https://github.com/huggingface/datasets/pull/2525 | 925,896,358 | MDExOlB1bGxSZXF1ZXN0Njc0Mjc5MTgy | 2,525 | Use scikit-learn package rather than sklearn in setup.py | {
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} | [] | closed | false | null | [] | null | [] | 1,624,259,065,000 | 1,624,269,673,000 | 1,624,265,853,000 | CONTRIBUTOR | null | The sklearn package is an historical thing and should probably not be used by anyone, see https://github.com/scikit-learn/scikit-learn/issues/8215#issuecomment-344679114 for some caveats.
Note: this affects only TESTS_REQUIRE so I guess only developers not end users. | {
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https://api.github.com/repos/huggingface/datasets/issues/2524 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2524/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2524/comments | https://api.github.com/repos/huggingface/datasets/issues/2524/events | https://github.com/huggingface/datasets/pull/2524 | 925,610,934 | MDExOlB1bGxSZXF1ZXN0Njc0MDQzNzk1 | 2,524 | Raise FileNotFoundError in WindowsFileLock | {
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"Hi ! Could you clarify what it fixes exactly and give more details please ? Especially why this is related to the windows hanging error ?",
"This has already been merged, but I'll clarify the idea of this PR. Before this merge, FileLock was the only component affected by the max path limit on Windows (that came ... | 1,624,199,111,000 | 1,624,874,182,000 | 1,624,870,059,000 | CONTRIBUTOR | null | Closes #2443 | {
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https://api.github.com/repos/huggingface/datasets/issues/2523 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2523/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2523/comments | https://api.github.com/repos/huggingface/datasets/issues/2523/events | https://github.com/huggingface/datasets/issues/2523 | 925,421,008 | MDU6SXNzdWU5MjU0MjEwMDg= | 2,523 | Fr | {
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https://api.github.com/repos/huggingface/datasets/issues/2521 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2521/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2521/comments | https://api.github.com/repos/huggingface/datasets/issues/2521/events | https://github.com/huggingface/datasets/pull/2521 | 925,030,685 | MDExOlB1bGxSZXF1ZXN0NjczNTgxNzQ4 | 2,521 | Insert text classification template for Emotion dataset | {
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https://api.github.com/repos/huggingface/datasets/issues/2519 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2519/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2519/comments | https://api.github.com/repos/huggingface/datasets/issues/2519/events | https://github.com/huggingface/datasets/pull/2519 | 924,903,240 | MDExOlB1bGxSZXF1ZXN0NjczNDcyMzYy | 2,519 | Improve performance of pandas arrow extractor | {
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"Looks like this change\r\n```\r\npa_table[pa_table.column_names[0]].to_pandas(types_mapper=pandas_types_mapper)\r\n```\r\ndoesn't return a Series with the correct type.\r\nThis is related to https://issues.apache.org/jira/browse/ARROW-9664\r\n\r\nSince the types_mapper isn't taken into account, the ArrayXD types a... | 1,624,022,681,000 | 1,624,266,366,000 | 1,624,266,366,000 | MEMBER | null | While reviewing PR #2505, I noticed that pandas arrow extractor could be refactored to be faster. | {
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https://api.github.com/repos/huggingface/datasets/issues/2518 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2518/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2518/comments | https://api.github.com/repos/huggingface/datasets/issues/2518/events | https://github.com/huggingface/datasets/pull/2518 | 924,654,100 | MDExOlB1bGxSZXF1ZXN0NjczMjU5Nzg1 | 2,518 | Add task templates for tydiqa and xquad | {
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"Just tested TydiQA and it works fine :)"
] | 1,624,003,594,000 | 1,624,028,477,000 | 1,624,027,833,000 | MEMBER | null | This PR adds question-answering templates to the remaining datasets that are linked to a model on the Hub.
Notes:
* I could not test the tydiqa implementation since I don't have enough disk space 😢 . But I am confident the template works :)
* there exist other datasets like `fquad` and `mlqa` which are candidates for question-answering templates, but some work is needed to handle the ordering of nested column described in #2434
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https://api.github.com/repos/huggingface/datasets/issues/2517 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2517/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2517/comments | https://api.github.com/repos/huggingface/datasets/issues/2517/events | https://github.com/huggingface/datasets/pull/2517 | 924,643,345 | MDExOlB1bGxSZXF1ZXN0NjczMjUwODk1 | 2,517 | Fix typo in MatthewsCorrelation class name | {
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https://api.github.com/repos/huggingface/datasets/issues/2515 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2515/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2515/comments | https://api.github.com/repos/huggingface/datasets/issues/2515/events | https://github.com/huggingface/datasets/pull/2515 | 924,435,447 | MDExOlB1bGxSZXF1ZXN0NjczMDc3NTIx | 2,515 | CRD3 dataset card | {
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https://api.github.com/repos/huggingface/datasets/issues/2513 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2513/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2513/comments | https://api.github.com/repos/huggingface/datasets/issues/2513/events | https://github.com/huggingface/datasets/issues/2513 | 924,174,413 | MDU6SXNzdWU5MjQxNzQ0MTM= | 2,513 | Corelation should be Correlation | {
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"Hi @colbym-MM, thanks for reporting. We are fixing it."
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https://api.github.com/repos/huggingface/datasets/issues/2512 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2512/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2512/comments | https://api.github.com/repos/huggingface/datasets/issues/2512/events | https://github.com/huggingface/datasets/issues/2512 | 924,069,353 | MDU6SXNzdWU5MjQwNjkzNTM= | 2,512 | seqeval metric does not work with a recent version of sklearn: classification_report() got an unexpected keyword argument 'output_dict' | {
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"Sorry, I was using an old version of sequeval"
] | 1,623,944,162,000 | 1,623,944,767,000 | 1,623,944,767,000 | NONE | null | ## Describe the bug
A clear and concise description of what the bug is.
## Steps to reproduce the bug
```python
from datasets import load_dataset, load_metric
seqeval = load_metric("seqeval")
seqeval.compute(predictions=[['A']], references=[['A']])
```
## Expected results
The function computes a dict with metrics
## Actual results
```
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-39-69a57f5cf06f> in <module>
1 from datasets import load_dataset, load_metric
2 seqeval = load_metric("seqeval")
----> 3 seqeval.compute(predictions=[['A']], references=[['A']])
~/p3/lib/python3.7/site-packages/datasets/metric.py in compute(self, *args, **kwargs)
396 references = self.data["references"]
397 with temp_seed(self.seed):
--> 398 output = self._compute(predictions=predictions, references=references, **kwargs)
399
400 if self.buf_writer is not None:
~/.cache/huggingface/modules/datasets_modules/metrics/seqeval/81eda1ff004361d4fa48754a446ec69bb7aa9cf4d14c7215f407d1475941c5ff/seqeval.py in _compute(self, predictions, references, suffix)
95
96 def _compute(self, predictions, references, suffix=False):
---> 97 report = classification_report(y_true=references, y_pred=predictions, suffix=suffix, output_dict=True)
98 report.pop("macro avg")
99 report.pop("weighted avg")
TypeError: classification_report() got an unexpected keyword argument 'output_dict'
```
## Environment info
sklearn=0.24
datasets=1.1.3
| {
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"Update on this: I'm computing the checksums of the data files. It will be available soon",
"Added in #2575 :)"
] | 1,623,925,864,000 | 1,625,488,618,000 | 1,625,488,617,000 | MEMBER | null | ## Adding a Dataset
- **Name:** *C4*
- **Description:** *https://github.com/allenai/allennlp/discussions/5056*
- **Paper:** *https://arxiv.org/abs/1910.10683*
- **Data:** *https://huggingface.co/datasets/allenai/c4*
- **Motivation:** *Used a lot for pretraining*
Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
Should fix https://github.com/huggingface/datasets/issues/1710 | {
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https://api.github.com/repos/huggingface/datasets/issues/2510 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2510/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2510/comments | https://api.github.com/repos/huggingface/datasets/issues/2510/events | https://github.com/huggingface/datasets/pull/2510 | 923,735,485 | MDExOlB1bGxSZXF1ZXN0NjcyNDY3MzY3 | 2,510 | Add align_labels_with_mapping to DatasetDict | {
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} | [] | closed | false | null | [] | null | [] | 1,623,924,215,000 | 1,623,926,725,000 | 1,623,926,724,000 | MEMBER | null | https://github.com/huggingface/datasets/pull/2457 added the `Dataset.align_labels_with_mapping` method.
In this PR I also added `DatasetDict.align_labels_with_mapping` | {
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https://api.github.com/repos/huggingface/datasets/issues/2509 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2509/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2509/comments | https://api.github.com/repos/huggingface/datasets/issues/2509/events | https://github.com/huggingface/datasets/pull/2509 | 922,846,035 | MDExOlB1bGxSZXF1ZXN0NjcxNjcyMzU5 | 2,509 | Fix fingerprint when moving cache dir | {
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"Windows, why are you doing this to me ?",
"Thanks @lhoestq, I'm starting reviewing this PR.",
"Yea issues on windows are about long paths, not long filenames.\r\nWe can make sure the lock filenames are not too long, but not for the paths",
"Took your suggestions into account @albertvillanova :)"
] | 1,623,861,909,000 | 1,624,287,904,000 | 1,624,287,903,000 | MEMBER | null | The fingerprint of a dataset changes if the cache directory is moved.
I fixed that by setting the fingerprint to be the hash of:
- the relative cache dir (dataset_name/version/config_id)
- the requested split
Close #2496
I had to fix an issue with the filelock filename that was too long (>255). It prevented the tests to run on my machine. I just added `hash_filename_if_too_long` in case this happens, to not get filenames longer than 255.
We usually have long filenames for filelocks because they are named after the path that is being locked. In case the path is a cache directory that has long directory names, then the filelock filename could en up being very long. | {
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https://api.github.com/repos/huggingface/datasets/issues/2507 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2507/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2507/comments | https://api.github.com/repos/huggingface/datasets/issues/2507/events | https://github.com/huggingface/datasets/pull/2507 | 921,441,962 | MDExOlB1bGxSZXF1ZXN0NjcwNDQ0MDgz | 2,507 | Rearrange JSON field names to match passed features schema field names | {
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Close #2366. | {
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https://api.github.com/repos/huggingface/datasets/issues/2506 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2506/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2506/comments | https://api.github.com/repos/huggingface/datasets/issues/2506/events | https://github.com/huggingface/datasets/pull/2506 | 921,435,598 | MDExOlB1bGxSZXF1ZXN0NjcwNDM4NTgx | 2,506 | Add course banner | {
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https://api.github.com/repos/huggingface/datasets/issues/2505 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2505/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2505/comments | https://api.github.com/repos/huggingface/datasets/issues/2505/events | https://github.com/huggingface/datasets/pull/2505 | 921,234,797 | MDExOlB1bGxSZXF1ZXN0NjcwMjY2NjQy | 2,505 | Make numpy arrow extractor faster | {
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"Looks like we have a nice speed up in some benchmarks. For example:\r\n- `read_formatted numpy 5000`: 4.584777 sec -> 0.487113 sec\r\n- `read_formatted torch 5000`: 4.565676 sec -> 1.289514 sec",
"Can we convert this draft to PR @lhoestq ?",
"Ready for review ! cc @vblagoje",
"@lhoestq I tried the branch a... | 1,623,751,892,000 | 1,624,874,019,000 | 1,624,874,018,000 | MEMBER | null | I changed the NumpyArrowExtractor to call directly to_numpy and see if it can lead to speed-ups as discussed in https://github.com/huggingface/datasets/issues/2498
This could make the numpy/torch/tf/jax formatting faster | {
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https://api.github.com/repos/huggingface/datasets/issues/2502 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2502/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2502/comments | https://api.github.com/repos/huggingface/datasets/issues/2502/events | https://github.com/huggingface/datasets/pull/2502 | 920,623,572 | MDExOlB1bGxSZXF1ZXN0NjY5NzQ1MDA5 | 2,502 | JAX integration | {
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I just added the "jax" formatting, as we already have for pytorch, tensorflow, numpy (and also pandas and arrow).
It does pretty much the same thing as the pytorch formatter except it creates jax.numpy.ndarray objects.
```python
from datasets import Dataset
d = Dataset.from_dict({"foo": [[0., 1., 2.]]})
d = d.with_format("jax")
d[0]
# {'foo': DeviceArray([0., 1., 2.], dtype=float32)}
```
A few details:
- The default integer precision for jax depends on the jax configuration `jax_enable_x64` (see [here](https://jax.readthedocs.io/en/latest/notebooks/Common_Gotchas_in_JAX.html#double-64bit-precision)), I took that into account. Unless `jax_enable_x64` is specified, it is int32 by default
- AFAIK it's not possible to do a full conversion from arrow data to jax data. We are doing arrow -> numpy -> jax but the numpy -> jax part doesn't do zero copy unfortutanely (see [here](https://github.com/google/jax/issues/4486))
- the env var for disabling JAX is `USE_JAX`. However I noticed that in `transformers` it is `USE_FLAX`. This is not an issue though IMO
I also updated `convert_to_python_objects` to allow users to pass jax.numpy.ndarray objects to build a dataset.
Since the `convert_to_python_objects` method became slow because it's the time when pytorch, tf (and now jax) are imported, I fixed it by checking the `sys.modules` to avoid unecessary import of pytorch, tf or jax.
Close #2495 | {
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Close #2472. | {
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"Hi @mariosasko, thanks for taking on this issue.\r\n\r\nJust a few logistic suggestions, as you are one of our most active contributors ❤️ :\r\n- When you start working on an issue, you can self-assign it to you by commenting on the issue page with the keyword: `#self-assign`; we have implemented a GitHub Action t... | 1,623,680,865,000 | 1,625,789,296,000 | 1,625,481,958,000 | CONTRIBUTOR | null | Adds the `load_dataset_builder` function. The good thing is that we can reuse this function to load the dataset info without downloading the dataset itself.
TODOs:
- [x] Add docstring and entry in the docs
- [x] Add tests
Closes #2484
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"I believe we don't use PyArrow >= 4.0.0 because of some segfault issues:\r\nhttps://github.com/huggingface/datasets/blob/1206ffbcd42dda415f6bfb3d5040708f50413c93/setup.py#L78\r\nCan you confirm @lhoestq ?",
"@SBrandeis pyarrow version 4.0.1 has fixed that issue: #2489 😉 "
] | 1,623,664,967,000 | 1,623,780,378,000 | 1,623,680,677,000 | MEMBER | null | From pyarrow version 4, it is supported to cast sliced lists.
This PR uses default pyarrow cast in Datasets to cast sliced list arrays if pyarrow version is >= 4.
In relation with PR #2461 and #2490.
cc: @lhoestq, @abhi1thakur, @SBrandeis | {
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However the fingerprint seems to change when someone moves the cache directory of the dataset.
This is because it uses the default fingerprint generation:
1. the dataset path is used to get the fingerprint
2. the modification times of the arrow file is also used to get the fingerprint
To fix that we could set the fingerprint of the dataset to be a hash of (<dataset_name>, <config_name>, <version>, <script_hash>), i.e. a hash of the the cache path relative to the cache directory. | {
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"@albertvillanova done!"
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Here is my PR for the text classification dataset in Mongolian.
Please do let me know in case you have anything to clarify.
Thanks & Regards,
Enod | {
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"Closing this PR as I'll submit a new one - bug free"
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Close #2489. | {
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"Let me push a small fix... 😉 ",
"Thanks !"
] | 1,623,476,849,000 | 1,623,663,017,000 | 1,623,661,376,000 | MEMBER | null | Part of #2480. | {
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https://api.github.com/repos/huggingface/datasets/issues/2484 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2484/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2484/comments | https://api.github.com/repos/huggingface/datasets/issues/2484/events | https://github.com/huggingface/datasets/issues/2484 | 919,092,635 | MDU6SXNzdWU5MTkwOTI2MzU= | 2,484 | Implement loading a dataset builder | {
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"#self-assign"
] | 1,623,437,242,000 | 1,625,481,957,000 | 1,625,481,957,000 | MEMBER | null | As discussed with @stas00 and @lhoestq, this would allow things like:
```python
from datasets import load_dataset_builder
dataset_name = "openwebtext"
builder = load_dataset_builder(dataset_name)
print(builder.cache_dir)
``` | {
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"I continue thinking that the origin of the issue has to do with tqdm (and not with Arrow): this issue only arises for version 4.50.0 (and later) of tqdm, not for previous versions of tqdm.\r\n\r\nMy guess is that tqdm made a change from version 4.50.0 that does not properly release the iterable. ",
"FR"
] | 1,623,424,170,000 | 1,624,044,306,000 | 1,623,425,496,000 | MEMBER | null | In https://github.com/huggingface/datasets/commit/42320a110d9d072703814e1f630a0d90d626a1e6 we added a call to gc.collect to resolve some issues on windows (see https://github.com/huggingface/datasets/pull/2482)
However calling gc.collect too often causes significant slow downs (the CI run time doubled).
So I just moved the gc.collect call to the exact place where it's actually needed: when post-processing a dataset | {
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https://api.github.com/repos/huggingface/datasets/issues/2482 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2482/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2482/comments | https://api.github.com/repos/huggingface/datasets/issues/2482/events | https://github.com/huggingface/datasets/pull/2482 | 918,846,027 | MDExOlB1bGxSZXF1ZXN0NjY4MjMyMzI5 | 2,482 | Allow to use tqdm>=4.50.0 | {
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They were due to open arrow files not properly closed by pyarrow.
Since https://github.com/huggingface/datasets/commit/42320a110d9d072703814e1f630a0d90d626a1e6 gc.collect is called each time we don't need an arrow file to make sure that the files are closed.
close https://github.com/huggingface/datasets/issues/2471
cc @lewtun | {
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"My suggestion for this would be to have this enabled by default.\r\n\r\nPlus I don't know if there should be a dedicated issue to that is another functionality. But I propose layered building rather than all at once. That is:\r\n\r\n1. uncompress a handful of files via a generator enough to generate one arrow file... | 1,623,414,112,000 | 1,626,685,698,000 | 1,626,685,698,000 | MEMBER | null | As discussed with @stas00 and @lhoestq, allowing the deletion of extracted files would save a great amount of disk space to typical user. | {
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https://api.github.com/repos/huggingface/datasets/issues/2477 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2477/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2477/comments | https://api.github.com/repos/huggingface/datasets/issues/2477/events | https://github.com/huggingface/datasets/pull/2477 | 918,334,431 | MDExOlB1bGxSZXF1ZXN0NjY3NzczMTY0 | 2,477 | Fix docs custom stable version | {
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"I see that @lhoestq overlooked this PR with his commit 07e2b05. 😢 \r\n\r\nI'm adding a script so that this issue does not happen again.\r\n",
"For the moment, the script only includes `update_custom_js`, but in a follow-up PR I will include all the required steps to make a package release.",
"I think we just ... | 1,623,396,363,000 | 1,623,662,060,000 | 1,623,658,818,000 | MEMBER | null | Currently docs default version is 1.5.0. This PR fixes this and sets the latest version instead. | {
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https://api.github.com/repos/huggingface/datasets/issues/2476 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2476/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2476/comments | https://api.github.com/repos/huggingface/datasets/issues/2476/events | https://github.com/huggingface/datasets/pull/2476 | 917,686,662 | MDExOlB1bGxSZXF1ZXN0NjY3MTg3OTk1 | 2,476 | Add TimeDial | {
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"Hi @lhoestq,\r\nI've pushed the updated README and tags. Let me know if anything is missing/needs some improvement!\r\n\r\n~PS. I don't know why it's not triggering the build~"
] | 1,623,349,987,000 | 1,627,649,874,000 | 1,627,649,874,000 | CONTRIBUTOR | null | Dataset: https://github.com/google-research-datasets/TimeDial
To-Do: Update README.md and add YAML tags | {
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https://api.github.com/repos/huggingface/datasets/issues/2475 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2475/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2475/comments | https://api.github.com/repos/huggingface/datasets/issues/2475/events | https://github.com/huggingface/datasets/issues/2475 | 917,650,882 | MDU6SXNzdWU5MTc2NTA4ODI= | 2,475 | Issue in timit_asr database | {
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"This bug was fixed in #1995. Upgrading datasets to version 1.6 fixes the issue!",
"Indeed was a fixed bug.\r\nWorks on version 1.8\r\nThanks "
] | 1,623,348,329,000 | 1,623,572,030,000 | 1,623,571,993,000 | NONE | null | ## Describe the bug
I am trying to load the timit_asr dataset however only the first record is shown (duplicated over all the rows).
I am using the next code line
dataset = load_dataset(“timit_asr”, split=“test”).shuffle().select(range(10))
The above code result with the same sentence duplicated ten times.
It also happens when I use the dataset viewer at Streamlit .
## Steps to reproduce the bug
from datasets import load_dataset
dataset = load_dataset(“timit_asr”, split=“test”).shuffle().select(range(10))
data = dataset.to_pandas()
# Sample code to reproduce the bug
```
## Expected results
table with different row information
## Actual results
Specify the actual results or traceback.
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.4.1 (also occur in the latest version)
- Platform: Linux-4.15.0-143-generic-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.6.9
- PyTorch version (GPU?): 1.8.1+cu102 (False)
- Tensorflow version (GPU?): 1.15.3 (False)
- Using GPU in script?: No
- Using distributed or parallel set-up in script?: No
- `datasets` version:
- Platform:
- Python version:
- PyArrow version:
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"Sounds great! It'll make things easier for the user while accessing the dataset. I'll make some changes to the current file then.",
"I've updated with the suggested changes. Updated the README, YAML tags as well (not sure of Size category tag as I couldn't pass the path of `dataset_infos.json` for this dataset)\... | 1,623,341,880,000 | 1,627,559,779,000 | 1,627,559,778,000 | CONTRIBUTOR | null | Dataset: https://github.com/google-research-datasets/disfl-qa
To-Do: Update README.md and add YAML tags | {
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"I have received a reply from Zenodo support:\r\n> We are currently investigating and fixing this issue related to GitHub releases. As soon as we have solved it we will reach back to you.",
"Other repo maintainers had the same problem with Zenodo. \r\n\r\nThere is an open issue on their GitHub repo: zenodo/zenodo... | 1,623,338,146,000 | 1,623,689,382,000 | 1,623,689,382,000 | MEMBER | null | After the last release of Datasets (1.8.0), the automatic generation of the Zenodo DOI failed: it appears in yellow as "Received", instead of in green as "Published".
I have contacted Zenodo support to fix this issue.
TODO:
- [x] Check with Zenodo to fix the issue
- [x] Check BibTeX entry is right | {
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```
PermissionError: [WinError 32] The process cannot access the file because it is being used by another process
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/2470 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2470/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2470/comments | https://api.github.com/repos/huggingface/datasets/issues/2470/events | https://github.com/huggingface/datasets/issues/2470 | 916,724,260 | MDU6SXNzdWU5MTY3MjQyNjA= | 2,470 | Crash when `num_proc` > dataset length for `map()` on a `datasets.Dataset`. | {
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"Hi ! It looks like the issue comes from pyarrow. What version of pyarrow are you using ? How did you install it ?",
"Thank you for the quick reply! I have `pyarrow==4.0.0`, and I am installing with `pip`. It's not one of my explicit dependencies, so I assume it came along with something else.",
"Could you tryi... | 1,623,278,422,000 | 1,625,132,094,000 | 1,625,130,673,000 | NONE | null | ## Describe the bug
Crash if when using `num_proc` > 1 (I used 16) for `map()` on a `datasets.Dataset`.
I believe I've had cases where `num_proc` > 1 works before, but now it seems either inconsistent, or depends on my data. I'm not sure whether the issue is on my end, because it's difficult for me to debug! Any tips greatly appreciated, I'm happy to provide more info if it would helps us diagnose.
## Steps to reproduce the bug
```python
# this function will be applied with map()
def tokenize_function(examples):
return tokenizer(
examples["text"],
padding=PaddingStrategy.DO_NOT_PAD,
truncation=True,
)
# data_files is a Dict[str, str] mapping name -> path
datasets = load_dataset("text", data_files={...})
# this is where the error happens if num_proc = 16,
# but is fine if num_proc = 1
tokenized_datasets = datasets.map(
tokenize_function,
batched=True,
num_proc=num_workers,
)
```
## Expected results
The `map()` function succeeds with `num_proc` > 1.
## Actual results


## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.6.2
- Platform: Linux-5.4.0-73-generic-x86_64-with-glibc2.31
- Python version: 3.9.5
- PyTorch version (GPU?): 1.8.1+cu111 (True)
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in script?: Yes, but I think N/A for this issue
- Using distributed or parallel set-up in script?: Multi-GPU on one machine, but I think also N/A for this issue
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https://api.github.com/repos/huggingface/datasets/issues/2469 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2469/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2469/comments | https://api.github.com/repos/huggingface/datasets/issues/2469/events | https://github.com/huggingface/datasets/pull/2469 | 916,440,418 | MDExOlB1bGxSZXF1ZXN0NjY2MTA1OTk1 | 2,469 | Bump tqdm version | {
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"i tried both the latest version of `tqdm` and the version required by `autonlp` - no luck with windows 😞 \r\n\r\nit's very weird that a progress bar would trigger these kind of errors, so i'll have a look to see if it's something unique to `datasets`",
"Closing since this is now fixed in #2482 "
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"No, nevermind @lhoestq. Thanks to you for your reviews!"
] | 1,623,258,534,000 | 1,624,894,794,000 | 1,624,892,735,000 | MEMBER | null | Close #2365. | {
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https://api.github.com/repos/huggingface/datasets/issues/2466 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2466/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2466/comments | https://api.github.com/repos/huggingface/datasets/issues/2466/events | https://github.com/huggingface/datasets/pull/2466 | 915,914,098 | MDExOlB1bGxSZXF1ZXN0NjY1NjY1MjQy | 2,466 | change udpos features structure | {
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"Let's add the tags in another PR. Thanks again !",
"Close #2061 , close #2444."
] | 1,623,225,811,000 | 1,624,017,309,000 | 1,623,840,097,000 | CONTRIBUTOR | null | The structure is change such that each example is a sentence
The change is done for issues:
#2061
#2444
Close #2061 , close #2444. | {
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"Thank you for the review. ",
"Thanks a lot for the corrections and comments. \r\n\r\nI have resolved point 2. The make style still throws some errors, please see below\r\n\r\nblack --line-length 119 --target-version py36 tests src benchmarks datasets/**/*.py metrics\r\n/bin/sh: 1: black: not found\r\nMakefile:13... | 1,623,187,225,000 | 1,623,682,745,000 | 1,623,682,745,000 | CONTRIBUTOR | null | Adding Masakhane dataset https://github.com/masakhane-io/masakhane-ner
@lhoestq , can you please review | {
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"> Good catch ! Thanks for fixing it\r\n\r\nMy pleasure🙏"
] | 1,623,185,245,000 | 1,623,233,746,000 | 1,623,229,828,000 | CONTRIBUTOR | null | The labels index were mismatching the actual ones used in the dataset. Specifically `0` is used for `SUPPORTS` and `1` is used for `REFUTES`
After this change, the `README.md` now reflects the content of `dataset_infos.json`.
Signed-off-by: Matteo Manica <drugilsberg@gmail.com> | {
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Instead of updating the path, this PR fixes a commit hash as suggested by @lhoestq. | {
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https://api.github.com/repos/huggingface/datasets/issues/2461 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2461/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2461/comments | https://api.github.com/repos/huggingface/datasets/issues/2461/events | https://github.com/huggingface/datasets/pull/2461 | 915,286,150 | MDExOlB1bGxSZXF1ZXN0NjY1MTE3MTY4 | 2,461 | Support sliced list arrays in cast | {
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} | [] | closed | false | null | [] | null | [] | 1,623,173,927,000 | 1,623,174,984,000 | 1,623,174,983,000 | MEMBER | null | There is this issue in pyarrow:
```python
import pyarrow as pa
arr = pa.array([[i * 10] for i in range(4)])
arr.cast(pa.list_(pa.int32())) # works
arr = arr.slice(1)
arr.cast(pa.list_(pa.int32())) # fails
# ArrowNotImplementedError("Casting sliced lists (non-zero offset) not yet implemented")
```
However in `Dataset.cast` we slice tables to cast their types (it's memory intensive), so we have the same issue.
Because of this it is currently not possible to cast a Dataset with a Sequence feature type (unless the table is small enough to not be sliced).
In this PR I fixed this by resetting the offset of `pyarrow.ListArray` arrays to zero in the table before casting.
I used `pyarrow.compute.subtract` function to update the offsets of the ListArray.
cc @abhi1thakur @SBrandeis | {
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https://api.github.com/repos/huggingface/datasets/issues/2460 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2460/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2460/comments | https://api.github.com/repos/huggingface/datasets/issues/2460/events | https://github.com/huggingface/datasets/pull/2460 | 915,268,536 | MDExOlB1bGxSZXF1ZXN0NjY1MTAyMjA4 | 2,460 | Revert default in-memory for small datasets | {
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"Thank you for this welcome change guys!"
] | 1,623,172,463,000 | 1,623,175,454,000 | 1,623,174,943,000 | MEMBER | null | Close #2458 | {
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https://api.github.com/repos/huggingface/datasets/issues/2459 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2459/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2459/comments | https://api.github.com/repos/huggingface/datasets/issues/2459/events | https://github.com/huggingface/datasets/issues/2459 | 915,222,015 | MDU6SXNzdWU5MTUyMjIwMTU= | 2,459 | `Proto_qa` hosting seems to be broken | {
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"@VictorSanh , I think @mariosasko is already working on it. "
] | 1,623,168,992,000 | 1,623,313,869,000 | 1,623,313,869,000 | MEMBER | null | ## Describe the bug
The hosting (on Github) of the `proto_qa` dataset seems broken. I haven't investigated more yet, just flagging it for now.
@zaidalyafeai if you want to dive into it, I think it's just a matter of changing the links in `proto_qa.py`
## Steps to reproduce the bug
```python
from datasets import load_dataset
dataset = load_dataset("proto_qa")
```
## Actual results
```
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/hf/dev/promptsource/.venv/lib/python3.7/site-packages/datasets/load.py", line 751, in load_dataset
use_auth_token=use_auth_token,
File "/home/hf/dev/promptsource/.venv/lib/python3.7/site-packages/datasets/builder.py", line 575, in download_and_prepare
dl_manager=dl_manager, verify_infos=verify_infos, **download_and_prepare_kwargs
File "/home/hf/dev/promptsource/.venv/lib/python3.7/site-packages/datasets/builder.py", line 630, in _download_and_prepare
split_generators = self._split_generators(dl_manager, **split_generators_kwargs)
File "/home/hf/.cache/huggingface/modules/datasets_modules/datasets/proto_qa/445346efaad5c5f200ecda4aa7f0fb50ff1b55edde3003be424a2112c3e8102e/proto_qa.py", line 131, in _split_generators
train_fpath = dl_manager.download(_URLs[self.config.name]["train"])
File "/home/hf/dev/promptsource/.venv/lib/python3.7/site-packages/datasets/utils/download_manager.py", line 199, in download
num_proc=download_config.num_proc,
File "/home/hf/dev/promptsource/.venv/lib/python3.7/site-packages/datasets/utils/py_utils.py", line 195, in map_nested
return function(data_struct)
File "/home/hf/dev/promptsource/.venv/lib/python3.7/site-packages/datasets/utils/download_manager.py", line 218, in _download
return cached_path(url_or_filename, download_config=download_config)
File "/home/hf/dev/promptsource/.venv/lib/python3.7/site-packages/datasets/utils/file_utils.py", line 291, in cached_path
use_auth_token=download_config.use_auth_token,
File "/home/hf/dev/promptsource/.venv/lib/python3.7/site-packages/datasets/utils/file_utils.py", line 621, in get_from_cache
raise FileNotFoundError("Couldn't find file at {}".format(url))
FileNotFoundError: Couldn't find file at https://raw.githubusercontent.com/iesl/protoqa-data/master/data/train/protoqa_train.jsonl
``` | {
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"cc: @krandiash (pinged in reverted PR)."
] | 1,623,167,501,000 | 1,623,178,631,000 | 1,623,174,943,000 | MEMBER | null | Users are reporting issues and confusion about setting default in-memory to True for small datasets.
We see 2 clear use cases of Datasets:
- the "canonical" way, where you can work with very large datasets, as they are memory-mapped and cached (after every transformation)
- some edge cases (speed benchmarks, interactive/exploratory analysis,...), where default in-memory can explicitly be enabled, and no caching will be done
After discussing with @lhoestq we have agreed to:
- revert this feature (implemented in #2182)
- explain in the docs how to optimize speed/performance by setting default in-memory
cc: @stas00 https://github.com/huggingface/datasets/pull/2409#issuecomment-856210552 | {
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https://api.github.com/repos/huggingface/datasets/issues/2457 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2457/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2457/comments | https://api.github.com/repos/huggingface/datasets/issues/2457/events | https://github.com/huggingface/datasets/pull/2457 | 915,079,441 | MDExOlB1bGxSZXF1ZXN0NjY0OTQwMzQ0 | 2,457 | Add align_labels_with_mapping function | {
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"@lhoestq i think this is ready for another review 🙂 ",
"@lhoestq thanks for the feedback - it's now integrated :) \r\n\r\ni also added a comment about sorting the input label IDs",
"Created the PR here: https://github.com/huggingface/datasets/pull/2510",
"> Thanks ! Looks all good now :)\r\n> \r\n> We will ... | 1,623,160,440,000 | 1,623,925,026,000 | 1,623,923,812,000 | MEMBER | null | This PR adds a helper function to align the `label2id` mapping between a `datasets.Dataset` and a classifier (e.g. a transformer with a `PretrainedConfig.label2id` dict), with the alignment performed on the dataset itself.
This will help us with the Hub evaluation, where we won't know in advance whether a model that is fine-tuned on say MNLI has the same mappings as the MNLI dataset we load from `datasets`.
An example where this is needed is if we naively try to evaluate `microsoft/deberta-base-mnli` on `mnli` because the model config has the following mappings:
```python
"id2label": {
"0": "CONTRADICTION",
"1": "NEUTRAL",
"2": "ENTAILMENT"
},
"label2id": {
"CONTRADICTION": 0,
"ENTAILMENT": 2,
"NEUTRAL": 1
}
```
while the `mnli` dataset has the `contradiction` and `neutral` labels swapped:
```python
id2label = {0: 'entailment', 1: 'neutral', 2: 'contradiction'}
label2id = {'contradiction': 2, 'entailment': 0, 'neutral': 1}
```
As a result, we get a much lower accuracy during evaluation:
```python
from datasets import load_dataset
from transformers.trainer_utils import EvalPrediction
from transformers import AutoModelForSequenceClassification, Trainer
# load dataset for evaluation
mnli = load_dataset("glue", "mnli", split="test")
# load model
model_ckpt = "microsoft/deberta-base-mnli"
model = AutoModelForSequenceClassification.from_pretrained(checkpoint)
# preprocess, create trainer ...
mnli_enc = ...
trainer = Trainer(model, args=args, tokenizer=tokenizer)
# generate preds
preds = trainer.predict(mnli_enc)
# preds.label_ids misalinged with model.config => returns wrong accuracy (too low)!
compute_metrics(EvalPrediction(preds.predictions, preds.label_ids))
```
The fix is to use the helper function before running the evaluation to make sure the label IDs are aligned:
```python
mnli_enc_aligned = mnli_enc.align_labels_with_mapping(label2id=config.label2id, label_column="label")
# preds now aligned and everyone is happy :)
preds = trainer.predict(mnli_enc_aligned)
```
cc @thomwolf @lhoestq | {
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https://api.github.com/repos/huggingface/datasets/issues/2456 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2456/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2456/comments | https://api.github.com/repos/huggingface/datasets/issues/2456/events | https://github.com/huggingface/datasets/pull/2456 | 914,709,293 | MDExOlB1bGxSZXF1ZXN0NjY0NjAwOTk1 | 2,456 | Fix cross-reference typos in documentation | {
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} | [] | closed | false | null | [] | null | [] | 1,623,145,514,000 | 1,623,174,097,000 | 1,623,174,096,000 | MEMBER | null | Fix some minor typos in docs that avoid the creation of cross-reference links. | {
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https://api.github.com/repos/huggingface/datasets/issues/2455 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2455/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2455/comments | https://api.github.com/repos/huggingface/datasets/issues/2455/events | https://github.com/huggingface/datasets/pull/2455 | 914,177,468 | MDExOlB1bGxSZXF1ZXN0NjY0MTEzNjg2 | 2,455 | Update version in xor_tydi_qa.py | {
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"Hi ! Thanks for updating the version\r\n\r\n> Should I revert to the old dummy/1.0.0 or delete it and keep only dummy/1.1.0?\r\n\r\nFeel free to delete the old dummy data files\r\n"
] | 1,623,119,025,000 | 1,623,684,925,000 | 1,623,684,925,000 | CONTRIBUTOR | null | Fix #2449
@lhoestq Should I revert to the old `dummy/1.0.0` or delete it and keep only `dummy/1.1.0`? | {
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https://api.github.com/repos/huggingface/datasets/issues/2454 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2454/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2454/comments | https://api.github.com/repos/huggingface/datasets/issues/2454/events | https://github.com/huggingface/datasets/pull/2454 | 913,883,631 | MDExOlB1bGxSZXF1ZXN0NjYzODUyODU1 | 2,454 | Rename config and environment variable for in memory max size | {
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"Thank you for the rename, @albertvillanova!"
] | 1,623,093,668,000 | 1,623,098,626,000 | 1,623,098,626,000 | MEMBER | null | As discussed in #2409, both config and environment variable have been renamed.
cc: @stas00, huggingface/transformers#12056 | {
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"The arrow writer was supposing that the columns were always in the sorted order. I just pushed a fix to reorder the arrays accordingly to the schema. It was failing for many datasets like squad",
"and obviously it broke everything",
"Feel free to revert my commit. I can investigate this in the coming days",
... | 1,623,083,198,000 | 1,623,780,336,000 | 1,623,771,828,000 | MEMBER | null | When loading a Dataset from a JSON file whose column names are not sorted alphabetically, we should get the same column name order, whether we pass features (in the same order as in the file) or not.
I found this issue while working on #2366. | {
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https://api.github.com/repos/huggingface/datasets/issues/2452 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2452/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2452/comments | https://api.github.com/repos/huggingface/datasets/issues/2452/events | https://github.com/huggingface/datasets/issues/2452 | 913,603,877 | MDU6SXNzdWU5MTM2MDM4Nzc= | 2,452 | MRPC test set differences between torch and tensorflow datasets | {
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"Realized that `tensorflow_datasets` is not provided by Huggingface and should therefore raise the issue there."
] | 1,623,075,626,000 | 1,623,076,472,000 | 1,623,076,472,000 | NONE | null | ## Describe the bug
When using `load_dataset("glue", "mrpc")` to load the MRPC dataset, the test set includes the labels. When using `tensorflow_datasets.load('glue/{}'.format('mrpc'))` to load the dataset the test set does not contain the labels. There should be consistency between torch and tensorflow ways of importing the GLUE datasets.
## Steps to reproduce the bug
Minimal working code
```python
from datasets import load_dataset
import tensorflow as tf
import tensorflow_datasets
# torch
dataset = load_dataset("glue", "mrpc")
# tf
data = tensorflow_datasets.load('glue/{}'.format('mrpc'))
data = list(data['test'].as_numpy_iterator())
for i in range(40,50):
tf_sentence1 = data[i]['sentence1'].decode("utf-8")
tf_sentence2 = data[i]['sentence2'].decode("utf-8")
tf_label = data[i]['label']
index = data[i]['idx']
print('Index {}'.format(index))
torch_sentence1 = dataset['test']['sentence1'][index]
torch_sentence2 = dataset['test']['sentence2'][index]
torch_label = dataset['test']['label'][index]
print('Tensorflow: \n\tSentence1 {}\n\tSentence2 {}\n\tLabel {}'.format(tf_sentence1, tf_sentence2, tf_label))
print('Torch: \n\tSentence1 {}\n\tSentence2 {}\n\tLabel {}'.format(torch_sentence1, torch_sentence2, torch_label))
```
Sample output
```
Index 954
Tensorflow:
Sentence1 Sabri Yakou , an Iraqi native who is a legal U.S. resident , appeared before a federal magistrate yesterday on charges of violating U.S. arms-control laws .
Sentence2 The elder Yakou , an Iraqi native who is a legal U.S. resident , appeared before a federal magistrate Wednesday on charges of violating U.S. arms control laws .
Label -1
Torch:
Sentence1 Sabri Yakou , an Iraqi native who is a legal U.S. resident , appeared before a federal magistrate yesterday on charges of violating U.S. arms-control laws .
Sentence2 The elder Yakou , an Iraqi native who is a legal U.S. resident , appeared before a federal magistrate Wednesday on charges of violating U.S. arms control laws .
Label 1
Index 711
Tensorflow:
Sentence1 Others keep records sealed for as little as five years or as much as 30 .
Sentence2 Some states make them available immediately ; others keep them sealed for as much as 30 years .
Label -1
Torch:
Sentence1 Others keep records sealed for as little as five years or as much as 30 .
Sentence2 Some states make them available immediately ; others keep them sealed for as much as 30 years .
Label 0
```
## Expected results
I would expect the datasets to be independent of whether I am working with torch or tensorflow.
## Actual results
Test set labels are provided in the `datasets.load_datasets()` for MRPC. However MRPC is the only task where the test set labels are not -1.
## Environment info
- `datasets` version: 1.7.0
- Platform: Linux-5.4.109+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.7.10
- PyArrow version: 3.0.0
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https://api.github.com/repos/huggingface/datasets/issues/2450 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2450/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2450/comments | https://api.github.com/repos/huggingface/datasets/issues/2450/events | https://github.com/huggingface/datasets/issues/2450 | 912,890,291 | MDU6SXNzdWU5MTI4OTAyOTE= | 2,450 | BLUE file not found | {
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"Hi ! The `blue` metric doesn't exist, but the `bleu` metric does.\r\nYou can get the full list of metrics [here](https://github.com/huggingface/datasets/tree/master/metrics) or by running\r\n```python\r\nfrom datasets import list_metrics\r\n\r\nprint(list_metrics())\r\n```",
"Ah, my mistake. Thanks for correctin... | 1,622,998,914,000 | 1,623,062,775,000 | 1,623,062,775,000 | NONE | null | Hi, I'm having the following issue when I try to load the `blue` metric.
```shell
import datasets
metric = datasets.load_metric('blue')
Traceback (most recent call last):
File "/home/irfan/environments/Perplexity_Transformers/lib/python3.6/site-packages/datasets/load.py", line 320, in prepare_module
local_path = cached_path(file_path, download_config=download_config)
File "/home/irfan/environments/Perplexity_Transformers/lib/python3.6/site-packages/datasets/utils/file_utils.py", line 291, in cached_path
use_auth_token=download_config.use_auth_token,
File "/home/irfan/environments/Perplexity_Transformers/lib/python3.6/site-packages/datasets/utils/file_utils.py", line 621, 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/1.7.0/metrics/blue/blue.py
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/home/irfan/environments/Perplexity_Transformers/lib/python3.6/site-packages/datasets/load.py", line 332, in prepare_module
local_path = cached_path(file_path, download_config=download_config)
File "/home/irfan/environments/Perplexity_Transformers/lib/python3.6/site-packages/datasets/utils/file_utils.py", line 291, in cached_path
use_auth_token=download_config.use_auth_token,
File "/home/irfan/environments/Perplexity_Transformers/lib/python3.6/site-packages/datasets/utils/file_utils.py", line 621, 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/metrics/blue/blue.py
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "<input>", line 1, in <module>
File "/home/irfan/environments/Perplexity_Transformers/lib/python3.6/site-packages/datasets/load.py", line 605, in load_metric
dataset=False,
File "/home/irfan/environments/Perplexity_Transformers/lib/python3.6/site-packages/datasets/load.py", line 343, in prepare_module
combined_path, github_file_path
FileNotFoundError: Couldn't find file locally at blue/blue.py, or remotely at https://raw.githubusercontent.com/huggingface/datasets/1.7.0/metrics/blue/blue.py.
The file is also not present on the master branch on github.
```
Here is dataset installed version info
```shell
pip freeze | grep datasets
datasets==1.7.0
```
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https://api.github.com/repos/huggingface/datasets/issues/2449 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2449/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2449/comments | https://api.github.com/repos/huggingface/datasets/issues/2449/events | https://github.com/huggingface/datasets/pull/2449 | 912,751,752 | MDExOlB1bGxSZXF1ZXN0NjYyODg1ODUz | 2,449 | Update `xor_tydi_qa` url to v1.1 | {
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"Just noticed while \r\n```load_dataset('local_path/datastes/xor_tydi_qa')``` works,\r\n```load_dataset('xor_tydi_qa')``` \r\noutputs an error: \r\n`\r\nFileNotFoundError: Couldn't find file at https://nlp.cs.washington.edu/xorqa/XORQA_site/data/xor_dev_retrieve_eng_span.jsonl\r\n`\r\n(the old url)\r\n\r\nI tired c... | 1,622,972,698,000 | 1,623,078,981,000 | 1,623,054,664,000 | CONTRIBUTOR | null | The dataset is updated and the old url no longer works. So I updated it.
I faced a bug while trying to fix this. Documenting the solution here. Maybe we can add it to the doc (`CONTRIBUTING.md` and `ADD_NEW_DATASET.md`).
> And to make the command work without the ExpectedMoreDownloadedFiles error, you just need to use the --ignore_verifications flag.
https://github.com/huggingface/datasets/issues/2076#issuecomment-803904366 | {
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https://api.github.com/repos/huggingface/datasets/issues/2448 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2448/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2448/comments | https://api.github.com/repos/huggingface/datasets/issues/2448/events | https://github.com/huggingface/datasets/pull/2448 | 912,360,109 | MDExOlB1bGxSZXF1ZXN0NjYyNTI2NjA3 | 2,448 | Fix flores download link | {
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https://api.github.com/repos/huggingface/datasets/issues/2447 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2447/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2447/comments | https://api.github.com/repos/huggingface/datasets/issues/2447/events | https://github.com/huggingface/datasets/issues/2447 | 912,299,527 | MDU6SXNzdWU5MTIyOTk1Mjc= | 2,447 | dataset adversarial_qa has no answers in the "test" set | {
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"Hi ! I'm pretty sure that the answers are not made available for the test set on purpose because it is part of the DynaBench benchmark, for which you can submit your predictions on the website.\r\nIn any case we should mention this in the dataset card of this dataset.",
"Makes sense, but not intuitive for someon... | 1,622,905,058,000 | 1,623,064,387,000 | 1,623,064,387,000 | NONE | null | ## Describe the bug
When loading the adversarial_qa dataset the 'test' portion has no answers. Only the 'train' and 'validation' portions do. This occurs with all four of the configs ('adversarialQA', 'dbidaf', 'dbert', 'droberta')
## Steps to reproduce the bug
```
from datasets import load_dataset
examples = load_dataset('adversarial_qa', 'adversarialQA', script_version="master")['test']
print('Loaded {:,} examples'.format(len(examples)))
has_answers = 0
for e in examples:
if e['answers']['text']:
has_answers += 1
print('{:,} have answers'.format(has_answers))
>>> Loaded 3,000 examples
>>> 0 have answers
examples = load_dataset('adversarial_qa', 'adversarialQA', script_version="master")['validation']
<...code above...>
>>> Loaded 3,000 examples
>>> 3,000 have answers
```
## Expected results
If 'test' is a valid dataset, it should have answers. Also note that all of the 'train' and 'validation' sets have answers, there are no "no answer" questions with this set (not sure if this is correct or not).
## Environment info
- `datasets` version: 1.7.0
- Platform: Linux-5.8.0-53-generic-x86_64-with-glibc2.29
- Python version: 3.8.5
- PyArrow version: 1.0.0
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https://api.github.com/repos/huggingface/datasets/issues/2446 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2446/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2446/comments | https://api.github.com/repos/huggingface/datasets/issues/2446/events | https://github.com/huggingface/datasets/issues/2446 | 911,635,399 | MDU6SXNzdWU5MTE2MzUzOTk= | 2,446 | `yelp_polarity` is broken | {
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"```\r\nFile \"/home/sasha/.local/share/virtualenvs/lib-ogGKnCK_/lib/python3.7/site-packages/streamlit/script_runner.py\", line 332, in _run_script\r\n exec(code, module.__dict__)\r\nFile \"/home/sasha/nlp-viewer/run.py\", line 233, in <module>\r\n configs = get_confs(option)\r\nFile \"/home/sasha/.local/shar... | 1,622,821,469,000 | 1,622,833,007,000 | 1,622,833,007,000 | MEMBER | null | 
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https://api.github.com/repos/huggingface/datasets/issues/2445 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2445/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2445/comments | https://api.github.com/repos/huggingface/datasets/issues/2445/events | https://github.com/huggingface/datasets/pull/2445 | 911,577,578 | MDExOlB1bGxSZXF1ZXN0NjYxODMzMTky | 2,445 | Fix broken URLs for bn_hate_speech and covid_tweets_japanese | {
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"Thanks ! To fix the CI you just have to rename the dummy data file in the dummy_data.zip files",
"thanks for the tip with the dummy data - all fixed now!"
] | 1,622,818,415,000 | 1,622,828,386,000 | 1,622,828,385,000 | MEMBER | null | Closes #2388 | {
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"Hi,\r\n\r\nThis is a known issue. More info on this issue can be found in #2061. If you are looking for an open-source contribution, there are step-by-step instructions in the linked issue that you can follow to fix it.",
"Closed by #2466."
] | 1,622,797,826,000 | 1,624,017,223,000 | 1,624,017,223,000 | CONTRIBUTOR | null | I was browsing through annotation guidelines, as suggested by the datasets introduction.
The guidlines saids "There must be exactly one blank line after every sentence, including the last sentence in the file. Empty sentences are not allowed." in the [Sentence Boundaries and Comments section](https://universaldependencies.org/format.html#sentence-boundaries-and-comments)
But the sentence boundaries seems not to be represented by huggingface datasets features well. I found out that multiple sentence are concatenated together as a 1D array, without any delimiter.
PAN-x, which is another token classification subset from xtreme do represent the sentence boundary using a 2D array.
You may compare in PAN-x.en and udpos.English in the explorer:
https://huggingface.co/datasets/viewer/?dataset=xtreme | {
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https://api.github.com/repos/huggingface/datasets/issues/2443 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2443/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2443/comments | https://api.github.com/repos/huggingface/datasets/issues/2443/events | https://github.com/huggingface/datasets/issues/2443 | 909,983,574 | MDU6SXNzdWU5MDk5ODM1NzQ= | 2,443 | Some tests hang on Windows | {
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"Hi ! That would be nice indeed to at least have a warning, since we don't handle the max path length limit.\r\nAlso if we could have an error instead of an infinite loop I'm sure windows users will appreciate that",
"Unfortunately, I know this problem very well... 😅 \r\n\r\nI remember having proposed to throw a... | 1,622,680,050,000 | 1,624,870,059,000 | 1,624,870,059,000 | CONTRIBUTOR | null | Currently, several tests hang on Windows if the max path limit of 260 characters is not disabled. This happens due to the changes introduced by #2223 that cause an infinite loop in `WindowsFileLock` described in #2220. This can be very tricky to debug, so I think now is a good time to address these issues/PRs. IMO throwing an error is too harsh, but maybe we can emit a warning in the top-level `__init__.py ` on startup if long paths are not enabled.
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https://api.github.com/repos/huggingface/datasets/issues/2442 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2442/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2442/comments | https://api.github.com/repos/huggingface/datasets/issues/2442/events | https://github.com/huggingface/datasets/pull/2442 | 909,677,029 | MDExOlB1bGxSZXF1ZXN0NjYwMjE1ODY1 | 2,442 | add english language tags for ~100 datasets | {
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"Fixing the tags of all the datasets is out of scope for this PR so I'm merging even though the CI fails because of the missing tags"
] | 1,622,651,096,000 | 1,622,800,300,000 | 1,622,800,299,000 | MEMBER | null | As discussed on Slack, I have manually checked for ~100 datasets that they have at least one subset in English. This information was missing so adding into the READMEs.
Note that I didn't check all the subsets so it's possible that some of the datasets have subsets in other languages than English... | {
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https://api.github.com/repos/huggingface/datasets/issues/2441 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2441/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2441/comments | https://api.github.com/repos/huggingface/datasets/issues/2441/events | https://github.com/huggingface/datasets/issues/2441 | 908,554,713 | MDU6SXNzdWU5MDg1NTQ3MTM= | 2,441 | DuplicatedKeysError on personal dataset | {
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"Hi ! In your dataset script you must be yielding examples like\r\n```python\r\nfor line in file:\r\n ...\r\n yield key, {...}\r\n```\r\n\r\nSince `datasets` 1.7.0 we enforce the keys to be unique.\r\nHowever it looks like your examples generator creates duplicate keys: at least two examples have key 0.\r\n\r... | 1,622,570,381,000 | 1,622,850,603,000 | 1,622,850,603,000 | NONE | null | ## Describe the bug
Ever since today, I have been getting a DuplicatedKeysError while trying to load my dataset from my own script.
Error returned when running this line: `dataset = load_dataset('/content/drive/MyDrive/Thesis/Datasets/book_preprocessing/goodreads_maharjan_trimmed_and_nered/goodreadsnered.py')`
Note that my script was working fine with earlier versions of the Datasets library. Cannot say with 100% certainty if I have been doing something wrong with my dataset script this whole time or if this is simply a bug with the new version of datasets.
## Steps to reproduce the bug
I cannot provide code to reproduce the error as I am working with my own dataset. I can however provide my script if requested.
## Expected results
For my data to be loaded.
## Actual results
**DuplicatedKeysError** exception is raised
```
Downloading and preparing dataset good_reads_practice_dataset/main_domain (download: Unknown size, generated: Unknown size, post-processed: Unknown size, total: Unknown size) to /root/.cache/huggingface/datasets/good_reads_practice_dataset/main_domain/1.1.0/64ff7c3fee2693afdddea75002eb6887d4fedc3d812ae3622128c8504ab21655...
---------------------------------------------------------------------------
DuplicatedKeysError Traceback (most recent call last)
<ipython-input-6-c342ea0dae9d> in <module>()
----> 1 dataset = load_dataset('/content/drive/MyDrive/Thesis/Datasets/book_preprocessing/goodreads_maharjan_trimmed_and_nered/goodreadsnered.py')
5 frames
/usr/local/lib/python3.7/dist-packages/datasets/load.py in load_dataset(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, ignore_verifications, keep_in_memory, save_infos, script_version, use_auth_token, task, **config_kwargs)
749 try_from_hf_gcs=try_from_hf_gcs,
750 base_path=base_path,
--> 751 use_auth_token=use_auth_token,
752 )
753
/usr/local/lib/python3.7/dist-packages/datasets/builder.py in download_and_prepare(self, download_config, download_mode, ignore_verifications, try_from_hf_gcs, dl_manager, base_path, use_auth_token, **download_and_prepare_kwargs)
573 if not downloaded_from_gcs:
574 self._download_and_prepare(
--> 575 dl_manager=dl_manager, verify_infos=verify_infos, **download_and_prepare_kwargs
576 )
577 # Sync info
/usr/local/lib/python3.7/dist-packages/datasets/builder.py in _download_and_prepare(self, dl_manager, verify_infos, **prepare_split_kwargs)
650 try:
651 # Prepare split will record examples associated to the split
--> 652 self._prepare_split(split_generator, **prepare_split_kwargs)
653 except OSError as e:
654 raise OSError(
/usr/local/lib/python3.7/dist-packages/datasets/builder.py in _prepare_split(self, split_generator)
990 writer.write(example, key)
991 finally:
--> 992 num_examples, num_bytes = writer.finalize()
993
994 split_generator.split_info.num_examples = num_examples
/usr/local/lib/python3.7/dist-packages/datasets/arrow_writer.py in finalize(self, close_stream)
407 # In case current_examples < writer_batch_size, but user uses finalize()
408 if self._check_duplicates:
--> 409 self.check_duplicate_keys()
410 # Re-intializing to empty list for next batch
411 self.hkey_record = []
/usr/local/lib/python3.7/dist-packages/datasets/arrow_writer.py in check_duplicate_keys(self)
347 for hash, key in self.hkey_record:
348 if hash in tmp_record:
--> 349 raise DuplicatedKeysError(key)
350 else:
351 tmp_record.add(hash)
DuplicatedKeysError: FAILURE TO GENERATE DATASET !
Found duplicate Key: 0
Keys should be unique and deterministic in nature
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.7.0
- Platform: Windows-10-10.0.19041-SP0
- Python version: 3.7.9
- PyArrow version: 3.0.0
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https://api.github.com/repos/huggingface/datasets/issues/2440 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2440/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2440/comments | https://api.github.com/repos/huggingface/datasets/issues/2440/events | https://github.com/huggingface/datasets/issues/2440 | 908,521,954 | MDU6SXNzdWU5MDg1MjE5NTQ= | 2,440 | Remove `extended` field from dataset tagger | {
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"The tagger also doesn't insert the value for the `size_categories` field automatically, so this should be fixed too",
"Thanks for reporting. Indeed the `extended` tag doesn't exist. Not sure why we had that in the tagger.\r\nThe repo of the tagger is here if someone wants to give this a try: https://github.com/h... | 1,622,567,922,000 | 1,623,229,591,000 | 1,623,229,590,000 | MEMBER | null | ## Describe the bug
While working on #2435 I used the [dataset tagger](https://huggingface.co/datasets/tagging/) to generate the missing tags for the YAML metadata of each README.md file. However, it seems that our CI raises an error when the `extended` field is included:
```
dataset_name = 'arcd'
@pytest.mark.parametrize("dataset_name", get_changed_datasets(repo_path))
def test_changed_dataset_card(dataset_name):
card_path = repo_path / "datasets" / dataset_name / "README.md"
assert card_path.exists()
error_messages = []
try:
ReadMe.from_readme(card_path)
except Exception as readme_error:
error_messages.append(f"The following issues have been found in the dataset cards:\nREADME:\n{readme_error}")
try:
DatasetMetadata.from_readme(card_path)
except Exception as metadata_error:
error_messages.append(
f"The following issues have been found in the dataset cards:\nYAML tags:\n{metadata_error}"
)
if error_messages:
> raise ValueError("\n".join(error_messages))
E ValueError: The following issues have been found in the dataset cards:
E YAML tags:
E __init__() got an unexpected keyword argument 'extended'
tests/test_dataset_cards.py:70: ValueError
```
Consider either removing this tag from the tagger or including it as part of the validation step in the CI.
cc @yjernite | {
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https://api.github.com/repos/huggingface/datasets/issues/2439 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2439/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2439/comments | https://api.github.com/repos/huggingface/datasets/issues/2439/events | https://github.com/huggingface/datasets/pull/2439 | 908,511,983 | MDExOlB1bGxSZXF1ZXN0NjU5MTkzMDE3 | 2,439 | Better error message when trying to access elements of a DatasetDict without specifying the split | {
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cc @thomwolf | {
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https://api.github.com/repos/huggingface/datasets/issues/2438 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2438/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2438/comments | https://api.github.com/repos/huggingface/datasets/issues/2438/events | https://github.com/huggingface/datasets/pull/2438 | 908,461,914 | MDExOlB1bGxSZXF1ZXN0NjU5MTQ5Njg0 | 2,438 | Fix NQ features loading: reorder fields of features to match nested fields order in arrow data | {
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} | [] | closed | false | null | [] | null | [] | 1,622,563,770,000 | 1,622,797,351,000 | 1,622,797,351,000 | MEMBER | null | As mentioned in #2401, there is an issue when loading the features of `natural_questions` since the order of the nested fields in the features don't match. The order is important since it matters for the underlying arrow schema.
To fix that I re-order the features based on the arrow schema:
```python
inferred_features = Features.from_arrow_schema(arrow_table.schema)
self.info.features = self.info.features.reorder_fields_as(inferred_features)
assert self.info.features.type == inferred_features.type
```
The re-ordering is a recursive function. It takes into account that the `Sequence` feature type is a struct of list and not a list of struct.
Now it's possible to load `natural_questions` again :) | {
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https://api.github.com/repos/huggingface/datasets/issues/2437 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2437/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2437/comments | https://api.github.com/repos/huggingface/datasets/issues/2437/events | https://github.com/huggingface/datasets/pull/2437 | 908,108,882 | MDExOlB1bGxSZXF1ZXN0NjU4ODUwNTkw | 2,437 | Better error message when using the wrong load_from_disk | {
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"We also have other cases where people are lost between Dataset and DatasetDict, maybe let's gather and solve them all here?\r\n\r\nFor instance, I remember that some people thought they would request a single element of a split but are calling this on a DatasetDict. Maybe here also a better error message when the ... | 1,622,540,602,000 | 1,623,175,430,000 | 1,623,175,430,000 | MEMBER | null | As mentioned in #2424, the error message when one tries to use `Dataset.load_from_disk` to load a DatasetDict object (or _vice versa_) can be improved. I added a suggestion in the error message to let users know that they should use the other one. | {
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https://api.github.com/repos/huggingface/datasets/issues/2436 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2436/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2436/comments | https://api.github.com/repos/huggingface/datasets/issues/2436/events | https://github.com/huggingface/datasets/pull/2436 | 908,100,211 | MDExOlB1bGxSZXF1ZXN0NjU4ODQzMzQy | 2,436 | Update DatasetMetadata and ReadMe | {
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} | [] | closed | false | null | [] | null | [] | 1,622,539,957,000 | 1,623,677,007,000 | 1,623,677,006,000 | CONTRIBUTOR | null | This PR contains the changes discussed in #2395.
**Edit**:
In addition to those changes, I'll be updating the `ReadMe` as follows:
Currently, `Section` has separate parsing and validation error lists. In `.validate()`, we add these lists to the final lists and throw errors.
One way to make `ReadMe` consistent with `DatasetMetadata` and add a separate `.validate()` method is to throw separate parsing and validation errors.
This way, we don't have to throw validation errors, but only parsing errors in `__init__ ()`. We can have an option in `__init__()` to suppress parsing errors so that an object is created for validation. Doing this will allow the user to get all the errors in one go.
In `test_dataset_cards` , we are already catching error messages and appending to a list. This can be done for `ReadMe()` for parsing errors, and `ReadMe(...,suppress_errors=True); readme.validate()` for validation, separately.
**Edit 2**:
The only parsing issue we have as of now is multiple headings at the same level with the same name. I assume this will happen very rarely, but it is still better to throw an error than silently pick one of them. It should be okay to separate it this way.
Wdyt @lhoestq ?
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https://api.github.com/repos/huggingface/datasets/issues/2435 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2435/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2435/comments | https://api.github.com/repos/huggingface/datasets/issues/2435/events | https://github.com/huggingface/datasets/pull/2435 | 907,505,531 | MDExOlB1bGxSZXF1ZXN0NjU4MzQzNDE2 | 2,435 | Insert Extractive QA templates for SQuAD-like datasets | {
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"hi @lhoestq @SBrandeis i've now added the missing YAML tags, so this PR should be good to go :)",
"urgh, the windows tests are failing because of encoding issues 😢 \r\n\r\n```\r\ndataset_name = 'squad_kor_v1'\r\n\r\n @pytest.mark.parametrize(\"dataset_name\", get_changed_datasets(repo_path))\r\n def test_... | 1,622,470,151,000 | 1,622,730,870,000 | 1,622,730,747,000 | MEMBER | null | This PR adds task templates for 9 SQuAD-like templates with the following properties:
* 1 config
* A schema that matches the `squad` one (i.e. same column names, especially for the nested `answers` column because the current implementation does not support casting with mismatched columns. see #2434)
* Less than 20GB (my laptop can't handle more right now)
The aim of this PR is to provide a few datasets to experiment with the task template integration in other libraries / services.
PR #2429 should be merged before this one.
cc @abhi1thakur | {
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https://api.github.com/repos/huggingface/datasets/issues/2433 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2433/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2433/comments | https://api.github.com/repos/huggingface/datasets/issues/2433/events | https://github.com/huggingface/datasets/pull/2433 | 907,488,711 | MDExOlB1bGxSZXF1ZXN0NjU4MzI5MDQ4 | 2,433 | Fix DuplicatedKeysError in adversarial_qa | {
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} | [] | closed | false | null | [] | null | [] | 1,622,468,927,000 | 1,622,537,531,000 | 1,622,537,531,000 | CONTRIBUTOR | null | Fixes #2431 | {
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https://api.github.com/repos/huggingface/datasets/issues/2432 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2432/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2432/comments | https://api.github.com/repos/huggingface/datasets/issues/2432/events | https://github.com/huggingface/datasets/pull/2432 | 907,462,881 | MDExOlB1bGxSZXF1ZXN0NjU4MzA3MTE1 | 2,432 | Fix CI six installation on linux | {
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```
pip._vendor.resolvelib.resolvers.InconsistentCandidate: Provided candidate AlreadyInstalledCandidate(six 1.16.0 (/usr/local/lib/python3.6/site-packages)) does not satisfy SpecifierRequirement('six>1.9'), SpecifierRequirement('six>1.9'), SpecifierRequirement('six>=1.11'), SpecifierRequirement('six~=1.15'), SpecifierRequirement('six'), SpecifierRequirement('six>=1.5.2'), SpecifierRequirement('six>=1.9.0'), SpecifierRequirement('six>=1.11.0'), SpecifierRequirement('six'), SpecifierRequirement('six>=1.6.1'), SpecifierRequirement('six>=1.9'), SpecifierRequirement('six>=1.5'), SpecifierRequirement('six<2.0'), SpecifierRequirement('six<2.0'), SpecifierRequirement('six'), SpecifierRequirement('six'), SpecifierRequirement('six~=1.15.0'), SpecifierRequirement('six'), SpecifierRequirement('six<2.0,>=1.6.1'), SpecifierRequirement('six'), SpecifierRequirement('six>=1.5.2'), SpecifierRequirement('six>=1.9.0')
```
example CI failure here:
https://app.circleci.com/pipelines/github/huggingface/datasets/6200/workflows/b64fdec9-f9e6-431c-acd7-e9f2c440c568/jobs/38247
The main version requirement comes from tensorflow: `six~=1.15.0`
So I pinned the six version to this. | {
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"Thanks for reporting !\r\n#2433 fixed the issue, thanks @mariosasko :)\r\n\r\nWe'll do a patch release soon of the library.\r\nIn the meantime, you can use the fixed version of adversarial_qa by adding `script_version=\"master\"` in `load_dataset`"
] | 1,622,463,079,000 | 1,622,537,643,000 | 1,622,537,531,000 | NONE | null | ## Describe the bug
A clear and concise description of what the bug is.
## Steps to reproduce the bug
```python
dataset = load_dataset('adversarial_qa', 'adversarialQA')
```
## Expected results
The dataset should be loaded into memory
## Actual results
>DuplicatedKeysError: FAILURE TO GENERATE DATASET !
>Found duplicate Key: 4d3cb5677211ee32895ca9c66dad04d7152254d4
>Keys should be unique and deterministic in nature
>
>
>During handling of the above exception, another exception occurred:
>
>DuplicatedKeysError Traceback (most recent call last)
>
>/usr/local/lib/python3.7/dist-packages/datasets/arrow_writer.py in check_duplicate_keys(self)
> 347 for hash, key in self.hkey_record:
> 348 if hash in tmp_record:
>--> 349 raise DuplicatedKeysError(key)
> 350 else:
> 351 tmp_record.add(hash)
>
>DuplicatedKeysError: FAILURE TO GENERATE DATASET !
>Found duplicate Key: 4d3cb5677211ee32895ca9c66dad04d7152254d4
>Keys should be unique and deterministic in nature
## Environment info
- `datasets` version: 1.7.0
- Platform: Linux-5.4.109+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.7.10
- PyArrow version: 3.0.0
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https://api.github.com/repos/huggingface/datasets/issues/2430 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2430/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2430/comments | https://api.github.com/repos/huggingface/datasets/issues/2430/events | https://github.com/huggingface/datasets/pull/2430 | 907,322,595 | MDExOlB1bGxSZXF1ZXN0NjU4MTg3Njkw | 2,430 | Add version-specific BibTeX | {
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"Maybe we should only keep one citation ?\r\ncc @thomwolf @yjernite ",
"For info:\r\n- The one automatically generated by Zenodo is version-specific, and a new one will be generated after each release.\r\n- Zenodo has also generated a project-specific DOI (they call it *Concept DOI* as opposed to *Version DOI*), ... | 1,622,455,542,000 | 1,623,138,802,000 | 1,623,138,802,000 | MEMBER | null | As pointed out by @lhoestq in #2411, after the creation of the Zenodo DOI for Datasets, a new BibTeX entry is created with each release.
This PR adds a version-specific BibTeX entry, besides the existing one which is generic for the project.
See version-specific BibTeX entry here: https://zenodo.org/record/4817769/export/hx#.YLSyd6j7RPY | {
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https://api.github.com/repos/huggingface/datasets/issues/2429 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2429/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2429/comments | https://api.github.com/repos/huggingface/datasets/issues/2429/events | https://github.com/huggingface/datasets/pull/2429 | 907,321,665 | MDExOlB1bGxSZXF1ZXN0NjU4MTg2ODc0 | 2,429 | Rename QuestionAnswering template to QuestionAnsweringExtractive | {
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"> I like having \"extractive\" in the name to make things explicit. However this creates an inconsistency with transformers.\r\n> \r\n> See\r\n> https://huggingface.co/transformers/task_summary.html#extractive-question-answering\r\n> \r\n> But this is minor IMO and I'm ok with this renaming\r\n\r\nyes i chose this... | 1,622,455,482,000 | 1,622,476,646,000 | 1,622,476,644,000 | MEMBER | null | Following the discussion with @thomwolf in #2255, this PR renames the QA template to distinguish extractive vs abstractive QA. The abstractive template will be added in a future PR. | {
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https://api.github.com/repos/huggingface/datasets/issues/2428 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2428/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2428/comments | https://api.github.com/repos/huggingface/datasets/issues/2428/events | https://github.com/huggingface/datasets/pull/2428 | 907,169,746 | MDExOlB1bGxSZXF1ZXN0NjU4MDU2MjI3 | 2,428 | Add copyright info for wiki_lingua dataset | {
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"Build fails but this change should not be the reason...",
"rebased on master",
"rebased on master"
] | 1,622,445,772,000 | 1,622,802,153,000 | 1,622,802,153,000 | CONTRIBUTOR | null | {
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https://api.github.com/repos/huggingface/datasets/issues/2427 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2427/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2427/comments | https://api.github.com/repos/huggingface/datasets/issues/2427/events | https://github.com/huggingface/datasets/pull/2427 | 907,162,923 | MDExOlB1bGxSZXF1ZXN0NjU4MDUwMjAx | 2,427 | Add copyright info to MLSUM dataset | {
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"Build fails but this change should not be the reason...",
"rebased on master"
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https://api.github.com/repos/huggingface/datasets/issues/2426 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2426/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2426/comments | https://api.github.com/repos/huggingface/datasets/issues/2426/events | https://github.com/huggingface/datasets/issues/2426 | 906,473,546 | MDU6SXNzdWU5MDY0NzM1NDY= | 2,426 | Saving Graph/Structured Data in Datasets | {
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"It should probably work out of the box to save structured data. If you want to show an example we can help you.",
"An example of a toy dataset is like:\r\n```json\r\n[\r\n {\r\n \"name\": \"mike\",\r\n \"friends\": [\r\n \"tom\",\r\n \"lily\"\r\n ],\r\n \"arti... | 1,622,295,321,000 | 1,622,596,863,000 | 1,622,596,863,000 | NONE | null | Thanks for this amazing library! And my question is I have structured data that is organized with a graph. For example, a dataset with users' friendship relations and user's articles. When I try to save a python dict in the dataset, an error occurred ``did not recognize Python value type when inferring an Arrow data type''.
Although I also know that storing a python dict in pyarrow datasets is not the best practice, but I have no idea about how to save structured data in the Datasets.
Thank you very much for your help. | {
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https://api.github.com/repos/huggingface/datasets/issues/2425 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2425/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2425/comments | https://api.github.com/repos/huggingface/datasets/issues/2425/events | https://github.com/huggingface/datasets/pull/2425 | 906,385,457 | MDExOlB1bGxSZXF1ZXN0NjU3NDAwMjM3 | 2,425 | Fix Docstring Mistake: dataset vs. metric | {
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"IMO this PR is ready for review. I do not know why tests fail...",
"The CI fail is unrelated to this PR, and it has been fixed on master, merging :)",
"> I just have one comment: we use rouge, not rogue :p\r\n\r\nOops!",
"rebased on master"
] | 1,622,268,593,000 | 1,622,535,484,000 | 1,622,535,484,000 | CONTRIBUTOR | null | PR to fix #2412 | {
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https://api.github.com/repos/huggingface/datasets/issues/2424 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2424/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2424/comments | https://api.github.com/repos/huggingface/datasets/issues/2424/events | https://github.com/huggingface/datasets/issues/2424 | 906,193,679 | MDU6SXNzdWU5MDYxOTM2Nzk= | 2,424 | load_from_disk and save_to_disk are not compatible with each other | {
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"Hi,\r\n\r\n`load_dataset` returns an instance of `DatasetDict` if `split` is not specified, so instead of `Dataset.load_from_disk`, use `DatasetDict.load_from_disk` to load the dataset from disk.",
"Thanks it worked!",
"Though I see a stream of issues open by people lost between datasets and datasets dicts so ... | 1,622,243,230,000 | 1,623,180,152,000 | 1,623,180,152,000 | NONE | null | ## Describe the bug
load_from_disk and save_to_disk are not compatible. When I use save_to_disk to save a dataset to disk it works perfectly but given the same directory load_from_disk throws an error that it can't find state.json. looks like the load_from_disk only works on one split
## Steps to reproduce the bug
```python
from datasets import load_dataset
dataset = load_dataset("art")
dataset.save_to_disk("mydir")
d = Dataset.load_from_disk("mydir")
```
## Expected results
It is expected that these two functions be the reverse of each other without more manipulation
## Actual results
FileNotFoundError: [Errno 2] No such file or directory: 'mydir/art/state.json'
## Environment info
- `datasets` version: 1.6.2
- Platform: Linux-5.4.0-73-generic-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.7.10
- PyTorch version (GPU?): 1.8.1+cu102 (True)
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in script?: <fill in>
- Using distributed or parallel set-up in script?: <fill in>
| {
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https://api.github.com/repos/huggingface/datasets/issues/2423 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2423/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2423/comments | https://api.github.com/repos/huggingface/datasets/issues/2423/events | https://github.com/huggingface/datasets/pull/2423 | 905,935,753 | MDExOlB1bGxSZXF1ZXN0NjU2OTc5MjA5 | 2,423 | add `desc` in `map` for `DatasetDict` object | {
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"The CI error is unrelated to the PR, merging",
"@lhoestq, can we release this feature if you guys are planning for any patch release for Datasets. It'll slow down [#11927](https://github.com/huggingface/transformers/pull/11927) otherwise :/ ",
"Sure definitely, having a discrepancy between Dataset.map and Data... | 1,622,230,124,000 | 1,622,472,683,000 | 1,622,466,484,000 | CONTRIBUTOR | null | `desc` in `map` currently only works with `Dataset` objects. This PR adds support for `DatasetDict` objects as well | {
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https://api.github.com/repos/huggingface/datasets/issues/2422 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2422/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2422/comments | https://api.github.com/repos/huggingface/datasets/issues/2422/events | https://github.com/huggingface/datasets/pull/2422 | 905,568,548 | MDExOlB1bGxSZXF1ZXN0NjU2NjM3MzY1 | 2,422 | Fix save_to_disk nested features order in dataset_info.json | {
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The order of the nested features matters (pyarrow limitation), but the save_to_disk method was saving the features types as JSON with `sort_keys=True`, which was breaking the order of the nested features. | {
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https://api.github.com/repos/huggingface/datasets/issues/2421 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2421/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2421/comments | https://api.github.com/repos/huggingface/datasets/issues/2421/events | https://github.com/huggingface/datasets/pull/2421 | 905,549,756 | MDExOlB1bGxSZXF1ZXN0NjU2NjIwMTM3 | 2,421 | doc: fix typo HF_MAX_IN_MEMORY_DATASET_SIZE_IN_BYTES | {
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https://api.github.com/repos/huggingface/datasets/issues/2420 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2420/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2420/comments | https://api.github.com/repos/huggingface/datasets/issues/2420/events | https://github.com/huggingface/datasets/pull/2420 | 904,821,772 | MDExOlB1bGxSZXF1ZXN0NjU1OTQ1ODgw | 2,420 | Updated Dataset Description | {
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} | [] | closed | false | null | [] | null | [] | 1,622,185,851,000 | 1,623,327,095,000 | 1,623,327,095,000 | CONTRIBUTOR | null | Added Point of contact information and several other details about the dataset. | {
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https://api.github.com/repos/huggingface/datasets/issues/2419 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2419/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2419/comments | https://api.github.com/repos/huggingface/datasets/issues/2419/events | https://github.com/huggingface/datasets/pull/2419 | 904,347,339 | MDExOlB1bGxSZXF1ZXN0NjU1NTA1OTM1 | 2,419 | adds license information for DailyDialog. | {
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"Thanks! Can you also add it as metadata in the YAML block at the top of the file?\r\n\r\nShould be in the form:\r\n\r\n```\r\nlicenses:\r\n- cc-by-sa-4.0\r\n```",
"seems like we need to add all the other tags ? \r\n``` \r\nif error_messages:\r\n> raise ValueError(\"\\n\".join(error_messages))\r\n... | 1,622,156,622,000 | 1,622,467,012,000 | 1,622,467,012,000 | CONTRIBUTOR | null | {
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