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https://api.github.com/repos/huggingface/datasets/issues/325 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/325/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/325/comments | https://api.github.com/repos/huggingface/datasets/issues/325/events | https://github.com/huggingface/datasets/pull/325 | 647,601,592 | MDExOlB1bGxSZXF1ZXN0NDQxNTk3NTgw | 325 | Add SQuADShifts dataset | {
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"Very cool to have this dataset, thank you for adding it :)"
] | 1,593,457,876,000 | 1,593,536,851,000 | 1,593,536,851,000 | CONTRIBUTOR | null | false | {
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"The glue metric for cola is a metric for classification. It expects label ids as integers as inputs.",
"I want to evaluate a sentence pair whether they are semantically equivalent, so I used MRPC and it gives the same error, does that mean we have to encode the sentences and parse as input?\r\n\r\nusing BertToke... | 1,593,449,628,000 | 1,594,286,014,000 | 1,594,286,014,000 | NONE | null | null | null | I was trying glue score along with other metrics here. But glue gives me this error;
```
import nlp
glue_metric = nlp.load_metric('glue',name="cola")
glue_score = glue_metric.compute(predictions, references)
```
```
---------------------------------------------------------------------------
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"Sorry for the long diff, everything after the imports comes from `black` for code quality :/ ",
" I think it's fine and I can't think of another way to make the import work anyways.\r\n\r\nMaybe we can have the `sys.path` behavior inside `prepare_module` instead ? Currently it seems to come out of nowhere in the... | 1,593,449,161,000 | 1,596,117,623,000 | 1,596,117,623,000 | MEMBER | null | false | {
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} | This fixes the `coval.py` metric so that imports within the downloaded module work correctly. We can use a similar trick to add the BLEURT metric (@ankparikh)
@thomwolf not sure how you feel about adding to the `PYTHONPATH` from the script. This is the only way I could make it work with my understanding of `importli... | {
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} | As we are using a columnar format like arrow as the backend for datasets, we expect to have a dictionary of columns when we slice a dataset like in this example:
```python
my_examples = dataset[0:10]
print(type(my_examples))
# >>> dict
print(my_examples["my_column"][0]
# >>> this is the first element of the colum... | {
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"It looks like it comes from `mwparserfromhell`.\r\n\r\nWould it be possible to get the bad `section` that causes this issue ? The `section` string is from `datasets/wikipedia.py:L548` ? You could just add a `try` statement and print the section if the line `section_text.append(section.strip_code().strip())` crashe... | 1,593,429,043,000 | 1,644,852,106,000 | 1,644,852,106,000 | NONE | null | null | null | Hi,
I am trying to download some wikipedia data but I got this error for spanish "es" (but there are maybe some others languages which have the same error I haven't tried all of them ).
`ERROR:root:mwparserfromhell ParseError: This is a bug and should be reported. Info: C tokenizer exited with non-empty token sta... | {
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"I wonder if this means downloading failed? That corpus has a really slow server.",
"This dataset seems to have a decoding problem that results in inconsistencies in the number of generated examples.\r\nSee #215.\r\nThat's why we end up with a `NonMatchingSplitsSizesError `."
] | 1,593,416,195,000 | 1,593,441,882,000 | 1,593,441,882,000 | CONTRIBUTOR | null | null | null | Selecting `blog_authorship_corpus` in the nlp viewer throws the following error:
```
NonMatchingSplitsSizesError: [{'expected': SplitInfo(name='train', num_bytes=610252351, num_examples=532812, dataset_name='blog_authorship_corpus'), 'recorded': SplitInfo(name='train', num_bytes=614706451, num_examples=535568, dat... | {
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"Oh yes, this is a backward compatibility feature with tensorflow_dataset in which a `Sequence` or `dict` is converted in a `dict` of `lists`, unfortunately it is not very intuitive, see here: https://github.com/huggingface/nlp/blob/master/src/nlp/features.py#L409\r\n\r\nTo avoid this behavior, you can just define ... | 1,593,301,517,000 | 1,593,771,720,000 | 1,593,771,720,000 | CONTRIBUTOR | null | null | null | Am pretty much finished [adding a dataset](https://github.com/ghomasHudson/nlp/blob/DocRED/datasets/docred/docred.py) for [DocRED](https://github.com/thunlp/DocRED), but am getting an error when trying to add a nested `nlp.features.sequence(nlp.features.sequence({key:value,...}))`.
The original data is in this form... | {
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"It's definitely going in the right direction ! Thanks for giving it a try\r\n\r\nI really like the API.\r\nIMO it's fine right now if we don't have all the dataset transforms (map, filter, etc.) as it can be done before building the multitask dataset, but it will be important to have them in the end.\r\nAll the fo... | 1,593,264,449,000 | 1,657,120,797,000 | 1,657,120,797,000 | CONTRIBUTOR | null | true | {
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} | Following our discussion in #217, I've implemented a first working version of `MultiDataset`.
There's a function `build_multitask()` which takes either individual `nlp.Dataset`s or `dicts` of splits and constructs `MultiDataset`(s). I've added a notebook with example usage.
I've implemented many of the `nlp.Datas... | {
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For example, in [QE 201... | {
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"Thanks @jxmorris12 for adding this adding. \r\nCan you please add a small description of the PR?"
] | 1,593,187,918,000 | 1,593,511,088,000 | 1,593,505,915,000 | CONTRIBUTOR | null | false | {
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"Update: I think I've found a solution.\r\n\r\n```python\r\noutput_types = {\"input_ids\": tf.int64, \"token_type_ids\": tf.int64, \"attention_mask\": tf.int64}\r\ndef train_dataset_gen():\r\n for i in range(len(train_dataset)):\r\n yield train_dataset[i]\r\ntf_dataset = tf.data.Dataset.from_generator(tra... | 1,593,124,220,000 | 1,603,813,097,000 | null | CONTRIBUTOR | null | null | null | I'm training on large datasets such as Wikipedia and BookCorpus. Following the instructions in [the tutorial notebook](https://colab.research.google.com/github/huggingface/nlp/blob/master/notebooks/Overview.ipynb), I see the following recommended for TensorFlow:
```python
train_tf_dataset = train_tf_dataset.filter(... | {
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"Thank you BatJeti! The storm-joker, aka the typo, finally got caught!"
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"Looks good to me"
] | 1,593,076,922,000 | 1,593,505,691,000 | 1,593,505,691,000 | CONTRIBUTOR | null | false | {
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Code is heavily bo... | {
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"Hi Jared,\r\nInteresting, thanks for raising this question. You can also do that after loading with `dataset.select()` or `dataset.filter()` which let you keep only a specific subset of rows in a dataset.\r\nWhat is your use-case for sharding?",
"Thanks for the pointer to those functions! It's still a little mor... | 1,593,038,913,000 | 1,594,038,936,000 | 1,594,038,936,000 | CONTRIBUTOR | null | null | null | Currently, to shard a dataset into 10 pieces on different ranks, you can run
```python
rank = 3 # for example
size = 10
dataset = nlp.load_dataset('wikitext', 'wikitext-2-raw-v1', split=f"train[{rank*10}%:{(rank+1)*10}%]")
```
However, this breaks down if you have a number of ranks that doesn't divide cleanly... | {
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A common processing step seems to be replacing the `XXX` placeholder with the `subject`. I've left this out as it's something you could easily do with `map`. | {
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"That's great work @ghomasHudson !"
] | 1,593,021,635,000 | 1,593,088,345,000 | 1,593,088,345,000 | CONTRIBUTOR | null | false | {
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Interesting things to note:
- Have copied the function (`_convert_to_human_readable`) which converts the SQL query to a human-readable (string) format as this is what most people will want when actually using this dataset for NLP applications.
- ... | {
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"Does it make sense to download the full stories? I remember attempting to implement this dataset a while ago and ended up with something like:\r\n```python\r\n def _split_generators(self, dl_manager):\r\n \"\"\"Returns SplitGenerators.\"\"\"\r\n\r\n dl_dir = dl_manager.download_and_extract(_DOWNLO... | 1,593,019,578,000 | 1,599,123,730,000 | 1,599,123,729,000 | NONE | null | false | {
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Only contains data for summaries (not whole story) | {
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```python
dataset = nlp.load_dataset('glue', 'mrpc')
```
```python
Downloading and preparing dataset glue/mrpc (download: Unknown size, generated: Unknown size, total: Unknown size) to C:\Users\Python\.cache... | {
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"@lucidrains - Thanks a lot for making the PR - PG19 is a super important dataset! Thanks for making it. Many people are asking for PG-19, so it would be great to have that in the library as soon as possible @thomwolf .",
"@mariamabarham yup! around 11GB!",
"I'm looking forward to our first deep learning writte... | 1,592,949,832,000 | 1,594,022,159,000 | 1,594,022,159,000 | CONTRIBUTOR | null | false | {
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Add functioning PG19 dataset with dummy data
`cos_e.py` was just auto-linted by `make style` | {
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Currently however, the code seems to... | {
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}
] | closed | false | null | [] | null | [] | 1,592,940,725,000 | 1,595,411,458,000 | 1,595,411,458,000 | CONTRIBUTOR | null | null | null | When I load more than one metric and try to print doc string of a particular metric,. It shows the doc strings of all imported metric one after the other which looks quite confusing and clumsy.
Attached [Colab](https://colab.research.google.com/drive/13H0ZgyQ2se0mqJ2yyew0bNEgJuHaJ8H3?usp=sharing) Notebook for problem ... | {
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Therefore it can happen that we try to move files across filesystems.
We were using `os.rename` that doesn't allow that, so I changed some of them to `shutil.move`.
This should fix #301 | {
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"Even more complicating - \r\n\r\nAs I see it, datasets can have \"addons\".\r\nFor example, the WebNLG dataset is a dataset for data-to-text. However, a work of mine and other works enriched this dataset with text plans / underlying text structures. In that case, I see a need to load the dataset \"WebNLG\" with \"... | 1,592,924,020,000 | 1,606,303,533,000 | 1,606,303,533,000 | CONTRIBUTOR | null | null | null | An emerging field in NLP is SLP - sign language processing.
I was wondering about adding datasets here, specifically because it's shaping up to be large and easily usable.
The metrics for sign language to text translation are the same.
So, what do you think about (me, or others) adding datasets here?
An exa... | {
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"Whoops didn't mean to close this one.\r\nI did some changes, could you try to run it from the master branch ?",
"Now it works, thanks!"
] | 1,592,911,904,000 | 1,592,982,307,000 | 1,592,982,307,000 | NONE | null | null | null | First of all thank you for a super handy library! I'd like to download large files to a specific drive so I set `cache_dir=my_path`. This works fine with e.g. imdb and squad. But on wikipedia I get an error:
```
nlp.load_dataset('wikipedia', '20200501.de', split = 'train', cache_dir=my_path)
```
```
OSError ... | {
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} | I added some type checking for metrics. There was an issue where a metric could interpret a string a a list. A `ValueError` is raised if a string is given instead of a list.
Moreover I added support for both strings and lists of strings for `references` in `bertscore`, as it is the case in the original code.
Both... | {
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"I guess you can just rebase from master to fix the CI"
] | 1,592,898,366,000 | 1,592,899,846,000 | 1,592,899,844,000 | CONTRIBUTOR | null | false | {
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"Looks very cool! Only looked at it superficially though",
"Alright I think I've checked all your comments, thanks :)\r\n\r\nMoreover I just added a way to serialize faiss indexes.\r\nThis is important because for big datasets the index construction can take some time.\r\n\r\nExamples:\r\n\r\n```python\r\nds = nl... | 1,592,897,583,000 | 1,593,157,844,000 | 1,593,157,843,000 | MEMBER | null | false | {
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} | # Better support for Numpy format + Add Indexed Datasets
I was working on adding Indexed Datasets but in the meantime I had to also add more support for Numpy arrays in the lib.
## Better support for Numpy format
New features:
- New fast method to convert Numpy arrays from Arrow structure (up to x100 speed up... | {
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"Thanks for reporting these errors :)\r\n\r\nI can actually see two issues here.\r\n\r\nFirst, datasets like `natural_questions` require apache_beam to be processed. Right now the import is not at the right place so we have this error message. However, even the imports are fixed, the nlp viewer doesn't actually hav... | 1,592,872,722,000 | 1,595,007,786,000 | 1,595,007,786,000 | NONE | null | null | null | Selecting `natural_questions` or `newsroom` dataset in the online demo results in an error similar to the following.
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"@jxmorris12 , we use `-1` to label examples for which `gold label` is missing (`gold label = -` in the original dataset). ",
"Thanks @mariamabarham! so the original dataset is missing some labels? That is weird. Is standard practice just to discard those examples training/eval?",
"Yes the original dataset is... | 1,592,868,810,000 | 1,592,923,319,000 | 1,592,923,318,000 | CONTRIBUTOR | null | null | null | I'm trying to train a model on the SNLI dataset. Why does it have so many -1 labels?
```
import nlp
from collections import Counter
data = nlp.load_dataset('snli')['train']
print(Counter(data['label']))
Counter({0: 183416, 2: 183187, 1: 182764, -1: 785})
```
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I am the author of `bert_score`. Recently, we received [ an issue ](https://github.com/Tiiiger/bert_score/issues/62) reporting a problem in using `bert_score` from the `nlp` package (also see #238 in this repo). After looking into this, I realized that the problem arises from the format `nlp.Metric` takes inpu... | {
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"I couldn't replicate this issue on my macbook :/\r\nCould you try to play with different encodings in `with open(path, encoding=...) as f` in scientific_papers.py:L108 ?",
"I was able to track down the file causing the problem by adding the following to `scientific_papers.py` (starting at line 116):\r\n\r\n```py... | 1,592,840,815,000 | 1,593,530,710,000 | 1,593,530,710,000 | CONTRIBUTOR | null | null | null | I am having trouble loading the `"arxiv"` config from the `"scientific_papers"` dataset on MacOS. When I try loading the dataset with:
```python
arxiv = nlp.load_dataset("scientific_papers", "arxiv")
```
I get the following stack trace:
```bash
JSONDecodeError Traceback (most recen... | {
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It should fix the CI that is currently failing. | {
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https://api.github.com/repos/huggingface/datasets/issues/292 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/292/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/292/comments | https://api.github.com/repos/huggingface/datasets/issues/292/events | https://github.com/huggingface/datasets/pull/292 | 642,897,797 | MDExOlB1bGxSZXF1ZXN0NDM3Nzk4NTM2 | 292 | Update metadata for x_stance dataset | {
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"Great! Thanks @jvamvas for these updates.\r\n",
"I have fixed a warning. The remaining test failure is due to an unrelated dataset.",
"We just fixed the other dataset on master. Could you rebase from master and push to rerun the CI ?"
] | 1,592,817,206,000 | 1,592,899,644,000 | 1,592,899,644,000 | CONTRIBUTOR | null | false | {
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} | Thank you for featuring the x_stance dataset in your library. This PR updates some metadata:
- Citation: Replace preprint with proceedings
- URL: Use a URL with long-term availability
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"I guess,test failing due to connection error?",
"We just fixed the other dataset on master. Could you rebase from master and push to rerun the CI ?",
"If I'm not wrong this function returns None if no main class was found.\r\nI think it makes things less clear not to have a return at the end of the function.\r... | 1,592,790,055,000 | 1,592,935,078,000 | 1,592,905,022,000 | NONE | null | false | {
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"It should ne fixed now, thanks for reporting this one :)\r\nIt was an issue on our google storage.\r\n\r\nLet me now if you're still facing this issue.",
"It works now, thanks for prompt help!"
] | 1,592,574,033,000 | 1,592,659,344,000 | 1,592,659,344,000 | NONE | null | null | null | Hi, I have a problem with downloading Eli5 dataset. When typing `nlp.load_dataset('eli5')`, I get ConnectionError: Couldn't reach https://storage.googleapis.com/huggingface-nlp/cache/datasets/eli5/LFQA_reddit/1.0.0/explain_like_im_five-train_eli5.arrow
I would appreciate if you could help me with this issue. | {
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"Looks cool!\r\n@mariamabarham can you add a detailed description here what exactly is changed and how the user can load xsum now?",
"And a rebase should solve the conflicts",
"This is a super useful PR :-) @sshleifer - maybe you can take a look at the updated version of xsum if you can use it for your use case... | 1,592,569,712,000 | 1,592,832,446,000 | 1,592,810,407,000 | CONTRIBUTOR | null | false | {
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} | This PR makes the following update to the xsum dataset:
- Manual download is not required anymore
- dataset can be loaded as follow: `nlp.load_dataset('xsum')`
**Important**
Instead of using on outdated url to download the data: "https://raw.githubusercontent.com/EdinburghNLP/XSum/master/XSum-Dataset/XSum... | {
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https://api.github.com/repos/huggingface/datasets/issues/288 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/288/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/288/comments | https://api.github.com/repos/huggingface/datasets/issues/288/events | https://github.com/huggingface/datasets/issues/288 | 641,888,610 | MDU6SXNzdWU2NDE4ODg2MTA= | 288 | Error at the first example in README: AttributeError: module 'dill' has no attribute '_dill' | {
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"It looks like the bug comes from `dill`. Which version of `dill` are you using ?",
"Thank you. It is version 0.2.6, which version is better?",
"0.2.6 is three years old now, maybe try a more recent one, e.g. the current 0.3.2 if you can?",
"Thanks guys! I upgraded dill and it works.",
"Awesome"
] | 1,592,564,482,000 | 1,592,730,311,000 | 1,592,730,311,000 | NONE | null | null | null | /Users/parasol_tree/anaconda3/lib/python3.6/site-packages/tensorflow/python/framework/dtypes.py:469: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_qint8 = np.dtype([("qint8", np.int8, 1)])
/Users/... | {
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The imports were wrong | {
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"Awesome!! Thanks @easonnie.\r\nLet's wait for additional reviews maybe from @lhoestq @patrickvonplaten @jplu"
] | 1,592,519,250,000 | 1,592,828,607,000 | 1,592,828,607,000 | CONTRIBUTOR | null | false | {
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} | I completed all the steps in https://github.com/huggingface/nlp/blob/master/CONTRIBUTING.md#how-to-add-a-dataset and push the code for ANLI. Please let me know if there are any errors. | {
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"Circle CI shuold be green :-) "
] | 1,592,497,523,000 | 1,592,813,365,000 | 1,592,813,364,000 | CONTRIBUTOR | null | false | {
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"Verified that this works, thanks!",
"But I get\r\n```python\r\nConnectionError: Couldn't reach https://s3.amazonaws.com/datasets.huggingface.co/nlp/datasets/./datasets/wmt16/wmt16.py\r\n```\r\nWhen I try from jupyter on brutasse or my mac. (the jupyter server is run from transformers).\r\n\r\n\r\nBoth machines c... | 1,592,495,997,000 | 1,592,555,061,000 | 1,592,555,059,000 | MEMBER | null | false | {
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} | This PR replaces the static `DatasetBulider` variable `MANUAL_DOWNLOAD_INSTRUCTIONS` by a property function `manual_download_instructions()`.
Some datasets like XTREME and all WMT need the manual data dir only for a small fraction of the possible configs.
After some brainstorming with @mariamabarham and @lhoestq... | {
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Can we make it so that they all are proper citations, i.e. parse by the bibtex spec:
https://bibtexparser.readthedocs.io/en/master/ | {
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} | Some datasets are hosted on gcs (wikipedia for example). In this PR I make sure that, when a user loads such datasets, the file_instructions are built using the dataset_info.json from gcs and not from the info extracted from the local `dataset_infos.json` (the one that contain the info for each config). Indeed local fi... | {
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https://api.github.com/repos/huggingface/datasets/issues/281 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/281/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/281/comments | https://api.github.com/repos/huggingface/datasets/issues/281/events | https://github.com/huggingface/datasets/issues/281 | 641,067,856 | MDU6SXNzdWU2NDEwNjc4NTY= | 281 | Private/sensitive data | {
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"Hi @MFreidank, you should already be able to load a dataset from local sources, indeed. (ping @lhoestq and @jplu)\r\n\r\nWe're also thinking about the ability to host private datasets on a hosted bucket with permission management, but that's further down the road.",
"Hi @MFreidank, it is possible to load a datas... | 1,592,473,647,000 | 1,592,658,912,000 | 1,592,658,912,000 | CONTRIBUTOR | null | null | null | Hi all,
Thanks for this fantastic library, it makes it very easy to do prototyping for NLP projects interchangeably between TF/Pytorch.
Unfortunately, there is data that cannot easily be shared publicly as it may contain sensitive information.
Is there support/a plan to support such data with NLP, e.g. by readin... | {
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https://api.github.com/repos/huggingface/datasets/issues/280 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/280/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/280/comments | https://api.github.com/repos/huggingface/datasets/issues/280/events | https://github.com/huggingface/datasets/issues/280 | 640,677,615 | MDU6SXNzdWU2NDA2Nzc2MTU= | 280 | Error with SquadV2 Metrics | {
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**squad_metric = nlp.load_metric('squad_v2')**
**This throws me an error.:**
```
ImportError Traceback (most recent call last)
<ipython-input-8-170b6a170555> in <module>
----> 1 squad_metric = nlp.load_metric('squad_v2')
~/env/lib6... | {
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https://api.github.com/repos/huggingface/datasets/issues/279 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/279/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/279/comments | https://api.github.com/repos/huggingface/datasets/issues/279/events | https://github.com/huggingface/datasets/issues/279 | 640,611,692 | MDU6SXNzdWU2NDA2MTE2OTI= | 279 | Dataset Preprocessing Cache with .map() function not working as expected | {
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"When you're processing a dataset with `.map`, it checks whether it has already done this computation using a hash based on the function and the input (using some fancy serialization with `dill`). If you found that it doesn't work as expected in some cases, let us know !\r\n\r\nGiven that, you can still force to re... | 1,592,414,241,000 | 1,625,607,808,000 | 1,618,789,429,000 | NONE | null | null | null | I've been having issues with reproducibility when loading and processing datasets with the `.map` function. I was only able to resolve them by clearing all of the cache files on my system.
Is there a way to disable using the cache when processing a dataset? As I make minor processing changes on the same dataset, I ... | {
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"Hi !\r\n\r\nAs you noticed, \"big\" datasets like Wikipedia require apache beam to be processed.\r\nHowever users usually don't have an apache beam runtime available (spark, dataflow, etc.) so our goal for this library is to also make available processed versions of these datasets, so that users can just download ... | 1,592,406,381,000 | 1,592,571,182,000 | 1,592,571,182,000 | NONE | null | null | null | Hi, first off let me say thank you for all the awesome work you're doing at Hugging Face across all your projects (NLP, Transformers, Tokenizers) - they're all amazing contributions to us working with NLP models :)
I'm trying to download the German Wikipedia dataset as follows:
```
wiki = nlp.load_dataset("wikip... | {
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"We are only wrapping the original dataset.\r\n\r\nMaybe try to ask on the GLUE mailing list or reach out to the original authors?",
"Tanks for the suggestion, I'll try to ask GLUE benchmark.\r\nI'll first close the issue, post the following up here afterwards, and reopen the issue if needed. "
] | 1,592,373,292,000 | 1,592,698,905,000 | 1,592,698,905,000 | CONTRIBUTOR | null | null | null | ```
qqp = nlp.load_dataset('glue', 'qqp')
print(qqp['train'][310121])
print(qqp['train'][362225])
```
```
{'question1': 'How can I create an Android app?', 'question2': '', 'label': 0, 'idx': 310137}
{'question1': 'How can I develop android app?', 'question2': '', 'label': 0, 'idx': 362246}
```
Notice that que... | {
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https://api.github.com/repos/huggingface/datasets/issues/276 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/276/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/276/comments | https://api.github.com/repos/huggingface/datasets/issues/276/events | https://github.com/huggingface/datasets/pull/276 | 639,490,858 | MDExOlB1bGxSZXF1ZXN0NDM1MDY5Nzg5 | 276 | Fix metric compute (original_instructions missing) | {
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"Awesome! This is working now:\r\n\r\n```python\r\nimport nlp \r\nseqeval = nlp.load_metric(\"seqeval\") \r\ny_true = [['O', 'O', 'O', 'B-MISC', 'I-MISC', 'I-MISC', 'O'], ['B-PER', 'I-PER', 'O']] \r\ny_pred = [['O', 'O', 'B-MISC', 'I-MISC', 'I-MISC', 'I-MISC', 'O'], ['B-PER', 'I-PER', 'O']] ... | 1,592,297,521,000 | 1,592,466,105,000 | 1,592,466,104,000 | MEMBER | null | false | {
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} | When loading arrow data we added in cc8d250 a way to specify the instructions that were used to store them with the loaded dataset.
However metrics load data the same way but don't need instructions (we use one single file).
In this PR I just make `original_instructions` optional when reading files to load a `Datas... | {
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The error is:
```
---------------------------------------------------------------------------
NonMatchingChecksumError Traceback (most recent call last)
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"Sounds good! Do you want to give it a try?",
"Ok, I'll see if I can figure it out tomorrow!",
"Got around to this today, and so far so good, I'm able to download and load pg19 locally. However, I think there may be an issue with the dummy data, and testing in general.\r\n\r\nThe problem lies in the fact that e... | 1,592,254,946,000 | 1,594,049,702,000 | 1,594,049,702,000 | CONTRIBUTOR | null | null | null | Hi, and thanks for all your open-sourced work, as always!
I was wondering if you would be open to adding PG-19 to your collection of datasets. https://github.com/deepmind/pg19 It is often used for benchmarking long-range language modeling. | {
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https://api.github.com/repos/huggingface/datasets/issues/273 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/273/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/273/comments | https://api.github.com/repos/huggingface/datasets/issues/273/events | https://github.com/huggingface/datasets/pull/273 | 638,968,054 | MDExOlB1bGxSZXF1ZXN0NDM0NjM0MzU4 | 273 | update cos_e to add cos_e v1.0 | {
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} | This PR updates the cos_e dataset to add v1.0 as requested here #163
@nazneenrajani | {
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https://api.github.com/repos/huggingface/datasets/issues/271 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/271/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/271/comments | https://api.github.com/repos/huggingface/datasets/issues/271/events | https://github.com/huggingface/datasets/pull/271 | 638,135,754 | MDExOlB1bGxSZXF1ZXN0NDMzOTg3NDkw | 271 | Fix allociné dataset configuration | {
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"Actually when there is only one configuration, then you don't need to specify the configuration in `load_dataset`. You can run:\r\n```python\r\ndataset = load_dataset('allocine')\r\n```\r\nand it works.\r\n\r\nMaybe we should take that into account in the nlp viewer @srush ?",
"@lhoestq Just to understand the ex... | 1,592,043,130,000 | 1,592,466,081,000 | 1,592,466,080,000 | CONTRIBUTOR | null | false | {
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} | This is a patch for #244. According to the [live nlp viewer](url), the Allociné dataset must be loaded with :
```python
dataset = load_dataset('allocine', 'allocine')
```
This is redundant, as there is only one "dataset configuration", and should only be:
```python
dataset = load_dataset('allocine')
```
This ... | {
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"C4 is too large to be shown in the viewer"
] | 1,592,036,776,000 | 1,603,812,929,000 | 1,603,812,913,000 | NONE | null | null | null | I get the following error when I try to view the c4 dataset in [nlpviewer](https://huggingface.co/nlp/viewer/)
```python
ModuleNotFoundError: No module named 'langdetect'
Traceback:
File "/home/sasha/.local/lib/python3.7/site-packages/streamlit/ScriptRunner.py", line 322, in _run_script
exec(code, module.__d... | {
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https://api.github.com/repos/huggingface/datasets/issues/269 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/269/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/269/comments | https://api.github.com/repos/huggingface/datasets/issues/269/events | https://github.com/huggingface/datasets/issues/269 | 638,106,774 | MDU6SXNzdWU2MzgxMDY3NzQ= | 269 | Error in metric.compute: missing `original_instructions` argument | {
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"name": "metric bug",
"color": "25b21e",
"default": false,
"description": "A bug in a metric script"
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"followers_url": "https://api.git... | null | [] | 1,592,029,614,000 | 1,592,466,104,000 | 1,592,466,104,000 | NONE | null | null | null | I'm running into an error using metrics for computation in the latest master as well as version 0.2.1. Here is a minimal example:
```python
import nlp
rte_metric = nlp.load_metric('glue', name="rte")
rte_metric.compute(
[0, 0, 1, 1],
[0, 1, 0, 1],
)
```
```
181 # Read the predictio... | {
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https://api.github.com/repos/huggingface/datasets/issues/268 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/268/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/268/comments | https://api.github.com/repos/huggingface/datasets/issues/268/events | https://github.com/huggingface/datasets/pull/268 | 637,848,056 | MDExOlB1bGxSZXF1ZXN0NDMzNzU5NzQ1 | 268 | add Rotten Tomatoes Movie Review sentences sentiment dataset | {
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"@jplu @thomwolf @patrickvonplaten @lhoestq -- How do I request reviewers? Thanks."
] | 1,591,977,239,000 | 1,592,466,384,000 | 1,592,466,383,000 | CONTRIBUTOR | null | false | {
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} | Sentence-level movie reviews v1.0 from here: http://www.cs.cornell.edu/people/pabo/movie-review-data/ | {
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https://api.github.com/repos/huggingface/datasets/issues/267 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/267/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/267/comments | https://api.github.com/repos/huggingface/datasets/issues/267/events | https://github.com/huggingface/datasets/issues/267 | 637,415,545 | MDU6SXNzdWU2Mzc0MTU1NDU= | 267 | How can I load/find WMT en-romanian? | {
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"I will take a look :-) "
] | 1,591,924,177,000 | 1,592,555,059,000 | 1,592,555,059,000 | CONTRIBUTOR | null | null | null | I believe it is from `wmt16`
When I run
```python
wmt = nlp.load_dataset('wmt16')
```
I get:
```python
AssertionError: The dataset wmt16 with config cs-en requires manual data.
Please follow the manual download instructions: Some of the wmt configs here, require a manual download.
Please look into wm... | {
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https://api.github.com/repos/huggingface/datasets/issues/266 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/266/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/266/comments | https://api.github.com/repos/huggingface/datasets/issues/266/events | https://github.com/huggingface/datasets/pull/266 | 637,156,392 | MDExOlB1bGxSZXF1ZXN0NDMzMTk1NDgw | 266 | Add sort, shuffle, test_train_split and select methods | {
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"Nice !\r\n\r\nAlso it looks like we can have a train_test_split method for free:\r\n```python\r\ntrain_indices, test_indices = train_test_split(range(len(dataset)))\r\ntrain = dataset.sort(indices=train_indices)\r\ntest = dataset.sort(indices=test_indices)\r\n```\r\n\r\nand a shuffling method for free:\r\n```pytho... | 1,591,892,540,000 | 1,592,497,405,000 | 1,592,497,404,000 | MEMBER | null | false | {
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} | Add a bunch of methods to reorder/split/select rows in a dataset:
- `dataset.select(indices)`: Create a new dataset with rows selected following the list/array of indices (which can have a different size than the dataset and contain duplicated indices, the only constrain is that all the integers in the list must be sm... | {
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https://api.github.com/repos/huggingface/datasets/issues/265 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/265/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/265/comments | https://api.github.com/repos/huggingface/datasets/issues/265/events | https://github.com/huggingface/datasets/pull/265 | 637,139,220 | MDExOlB1bGxSZXF1ZXN0NDMzMTgxNDMz | 265 | Add pyarrow warning colab | {
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} | When a user installs `nlp` on google colab, then google colab doesn't update pyarrow, and the runtime needs to be restarted to use the updated version of pyarrow.
This is an issue because `nlp` requires the updated version to work correctly.
In this PR I added en error that is shown to the user in google colab if... | {
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https://api.github.com/repos/huggingface/datasets/issues/264 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/264/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/264/comments | https://api.github.com/repos/huggingface/datasets/issues/264/events | https://github.com/huggingface/datasets/pull/264 | 637,106,170 | MDExOlB1bGxSZXF1ZXN0NDMzMTU0ODQ4 | 264 | Fix small issues creating dataset | {
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} | Fix many small issues mentioned in #249:
- don't force to install apache beam for commands
- fix None cache dir when using `dl_manager.download_custom`
- added new extras in `setup.py` named `dev` that contains tests and quality dependencies
- mock dataset sizes when running tests with dummy data
- add a note abou... | {
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https://api.github.com/repos/huggingface/datasets/issues/263 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/263/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/263/comments | https://api.github.com/repos/huggingface/datasets/issues/263/events | https://github.com/huggingface/datasets/issues/263 | 637,028,015 | MDU6SXNzdWU2MzcwMjgwMTU= | 263 | [Feature request] Support for external modality for language datasets | {
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"Thanks a lot, @aleSuglia for the very detailed and introductive feature request.\r\nIt seems like we could build something pretty useful here indeed.\r\n\r\nOne of the questions here is that Arrow doesn't have built-in support for generic \"tensors\" in records but there might be ways to do that in a clean way. We... | 1,591,882,938,000 | 1,644,499,595,000 | 1,644,499,595,000 | CONTRIBUTOR | null | null | null | # Background
In recent years many researchers have advocated that learning meanings from text-based only datasets is just like asking a human to "learn to speak by listening to the radio" [[E. Bender and A. Koller,2020](https://openreview.net/forum?id=GKTvAcb12b), [Y. Bisk et. al, 2020](https://arxiv.org/abs/2004.10... | {
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https://api.github.com/repos/huggingface/datasets/issues/262 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/262/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/262/comments | https://api.github.com/repos/huggingface/datasets/issues/262/events | https://github.com/huggingface/datasets/pull/262 | 636,702,849 | MDExOlB1bGxSZXF1ZXN0NDMyODI3Mzcz | 262 | Add new dataset ANLI Round 1 | {
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"Hello ! Thanks for adding this one :)\r\n\r\nThis looks great, you just have to do the last steps to make the CI pass.\r\nI can see that two things are missing:\r\n1. the dummy data that is used to test that the script is working as expected\r\n2. the json file with all the infos about the dataset\r\n\r\nYou can s... | 1,591,848,897,000 | 1,591,999,383,000 | 1,591,999,383,000 | CONTRIBUTOR | null | false | {
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} | Adding new dataset [ANLI](https://github.com/facebookresearch/anli/).
I'm not familiar with how to add new dataset. Let me know if there is any issue. I only include round 1 data here. There will be round 2, round 3 and more in the future with potentially different format. I think it will be better to separate them. | {
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https://api.github.com/repos/huggingface/datasets/issues/261 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/261/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/261/comments | https://api.github.com/repos/huggingface/datasets/issues/261/events | https://github.com/huggingface/datasets/issues/261 | 636,372,380 | MDU6SXNzdWU2MzYzNzIzODA= | 261 | Downloading dataset error with pyarrow.lib.RecordBatch | {
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"When you install `nlp` for the first time on a Colab runtime, it updates the `pyarrow` library that was already on colab. This update shows this message on colab:\r\n```\r\nWARNING: The following packages were previously imported in this runtime:\r\n [pyarrow]\r\nYou must restart the runtime in order to use newly... | 1,591,805,059,000 | 1,591,886,112,000 | 1,591,886,112,000 | NONE | null | null | null | I am trying to download `sentiment140` and I have the following error
```
/usr/local/lib/python3.6/dist-packages/nlp/load.py in load_dataset(path, name, version, data_dir, data_files, split, cache_dir, download_config, download_mode, ignore_verifications, save_infos, **config_kwargs)
518 download_mode=... | {
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https://api.github.com/repos/huggingface/datasets/issues/260 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/260/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/260/comments | https://api.github.com/repos/huggingface/datasets/issues/260/events | https://github.com/huggingface/datasets/pull/260 | 636,261,118 | MDExOlB1bGxSZXF1ZXN0NDMyNDY3NDM5 | 260 | Consistency fixes | {
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https://api.github.com/repos/huggingface/datasets/issues/259 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/259/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/259/comments | https://api.github.com/repos/huggingface/datasets/issues/259/events | https://github.com/huggingface/datasets/issues/259 | 636,239,529 | MDU6SXNzdWU2MzYyMzk1Mjk= | 259 | documentation missing how to split a dataset | {
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"this seems to work for my specific problem:\r\n\r\n`self.train_ds, self.test_ds, self.val_ds = map(_prepare_ds, ('train', 'test[:25%]+test[50%:75%]', 'test[75%:]'))`",
"Currently you can indeed split a dataset using `ds_test = nlp.load_dataset('imdb, split='test[:5000]')` (works also with percentages).\r\n\r\nHo... | 1,591,795,093,000 | 1,678,802,167,000 | 1,592,518,824,000 | NONE | null | null | null | I am trying to understand how to split a dataset ( as arrow_dataset).
I know I can do something like this to access a split which is already in the original dataset :
`ds_test = nlp.load_dataset('imdb, split='test') `
But how can I split ds_test into a test and a validation set (without reading the data into m... | {
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https://api.github.com/repos/huggingface/datasets/issues/258 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/258/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/258/comments | https://api.github.com/repos/huggingface/datasets/issues/258/events | https://github.com/huggingface/datasets/issues/258 | 635,859,525 | MDU6SXNzdWU2MzU4NTk1MjU= | 258 | Why is dataset after tokenization far more larger than the orginal one ? | {
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"Hi ! This is because `.map` added the new column `input_ids` to the dataset, and so all the other columns were kept. Therefore the dataset size increased a lot.\r\n If you want to only keep the `input_ids` column, you can stash the other ones by specifying `remove_columns=[\"title\", \"text\"]` in the arguments of... | 1,591,752,427,000 | 1,591,793,194,000 | 1,591,793,194,000 | CONTRIBUTOR | null | null | null | I tokenize wiki dataset by `map` and cache the results.
```
def tokenize_tfm(example):
example['input_ids'] = hf_fast_tokenizer.convert_tokens_to_ids(hf_fast_tokenizer.tokenize(example['text']))
return example
wiki = nlp.load_dataset('wikipedia', '20200501.en', cache_dir=cache_dir)['train']
wiki.map(token... | {
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https://api.github.com/repos/huggingface/datasets/issues/257 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/257/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/257/comments | https://api.github.com/repos/huggingface/datasets/issues/257/events | https://github.com/huggingface/datasets/issues/257 | 635,620,979 | MDU6SXNzdWU2MzU2MjA5Nzk= | 257 | Tokenizer pickling issue fix not landed in `nlp` yet? | {
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"Yes, the new release of tokenizers solves this and should be out soon.\r\nIn the meantime, you can install it with `pip install tokenizers==0.8.0-dev2`",
"If others run into this issue, a quick fix is to use python 3.6 instead of 3.7+. Serialization differences between the 3rd party `dataclasses` package for 3.6... | 1,591,722,754,000 | 1,591,825,532,000 | 1,591,723,613,000 | NONE | null | null | null | Unless I recreate an arrow_dataset from my loaded nlp dataset myself (which I think does not use the cache by default), I get the following error when applying the map function:
```
dataset = nlp.load_dataset('cos_e')
tokenizer = GPT2TokenizerFast.from_pretrained('gpt2', cache_dir=cache_dir)
for split in datase... | {
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https://api.github.com/repos/huggingface/datasets/issues/256 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/256/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/256/comments | https://api.github.com/repos/huggingface/datasets/issues/256/events | https://github.com/huggingface/datasets/issues/256 | 635,596,295 | MDU6SXNzdWU2MzU1OTYyOTU= | 256 | [Feature request] Add a feature to dataset | {
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"Do you have an example of what you would like to do? (you can just add a field in the output of the unction you give to map and this will add this field in the output table)",
"Given another source of data loaded in, I want to pre-add it to the dataset so that it aligns with the indices of the arrow dataset prio... | 1,591,720,692,000 | 1,591,721,502,000 | 1,591,721,502,000 | NONE | null | null | null | Is there a straightforward way to add a field to the arrow_dataset, prior to performing map? | {
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https://api.github.com/repos/huggingface/datasets/issues/255 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/255/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/255/comments | https://api.github.com/repos/huggingface/datasets/issues/255/events | https://github.com/huggingface/datasets/pull/255 | 635,300,822 | MDExOlB1bGxSZXF1ZXN0NDMxNjg3MDM0 | 255 | Add dataset/piaf | {
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"Very nice !"
] | 1,591,697,761,000 | 1,591,950,687,000 | 1,591,950,687,000 | CONTRIBUTOR | null | false | {
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https://api.github.com/repos/huggingface/datasets/issues/254 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/254/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/254/comments | https://api.github.com/repos/huggingface/datasets/issues/254/events | https://github.com/huggingface/datasets/issues/254 | 635,057,568 | MDU6SXNzdWU2MzUwNTc1Njg= | 254 | [Feature request] Be able to remove a specific sample of the dataset | {
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"Oh yes you can now do that with the `dataset.filter()` method that was added in #214 "
] | 1,591,669,333,000 | 1,591,692,098,000 | 1,591,692,098,000 | NONE | null | null | null | As mentioned in #117, it's currently not possible to remove a sample of the dataset.
But it is a important use case : After applying some preprocessing, some samples might be empty for example. We should be able to remove these samples from the dataset, or at least mark them as `removed` so when iterating the datase... | {
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https://api.github.com/repos/huggingface/datasets/issues/253 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/253/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/253/comments | https://api.github.com/repos/huggingface/datasets/issues/253/events | https://github.com/huggingface/datasets/pull/253 | 634,791,939 | MDExOlB1bGxSZXF1ZXN0NDMxMjgwOTYz | 253 | add flue dataset | {
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"The dummy data file was wrong. I only fixed it for the book config. Even though the tests are all green here, this should also be fixed for all other configs. Could you take a look there @mariamabarham ? ",
"Hi @mariamabarham \r\n\r\nFLUE can indeed become a very interesting benchmark for french NLP !\r\nUnfortu... | 1,591,636,269,000 | 1,594,885,859,000 | 1,594,885,859,000 | CONTRIBUTOR | null | false | {
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} | This PR add the Flue dataset as requested in this issue #223 . @lbourdois made a detailed description in that issue.
| {
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https://api.github.com/repos/huggingface/datasets/issues/252 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/252/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/252/comments | https://api.github.com/repos/huggingface/datasets/issues/252/events | https://github.com/huggingface/datasets/issues/252 | 634,563,239 | MDU6SXNzdWU2MzQ1NjMyMzk= | 252 | NonMatchingSplitsSizesError error when reading the IMDB dataset | {
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"I just tried on my side and I didn't encounter your problem.\r\nApparently the script doesn't generate all the examples on your side.\r\n\r\nCan you provide the version of `nlp` you're using ?\r\nCan you try to clear your cache and re-run the code ?",
"I updated it, that was it, thanks!",
"Hello, I am facing t... | 1,591,619,184,000 | 1,630,077,658,000 | 1,591,624,886,000 | NONE | null | null | null | Hi!
I am trying to load the `imdb` dataset with this line:
`dataset = nlp.load_dataset('imdb', data_dir='/A/PATH', cache_dir='/A/PATH')`
but I am getting the following error:
```
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/mounts/Users/cisintern/antmarakis/anaconda3/... | {
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https://api.github.com/repos/huggingface/datasets/issues/251 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/251/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/251/comments | https://api.github.com/repos/huggingface/datasets/issues/251/events | https://github.com/huggingface/datasets/pull/251 | 634,544,977 | MDExOlB1bGxSZXF1ZXN0NDMxMDgwMDkw | 251 | Better access to all dataset information | {
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} | Moves all the dataset info down one level from `dataset.info.XXX` to `dataset.XXX`
This way it's easier to access `dataset.feature['label']` for instance
Also, add the original split instructions used to create the dataset in `dataset.split`
Ex:
```
from nlp import load_dataset
stsb = load_dataset('glue', name=... | {
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https://api.github.com/repos/huggingface/datasets/issues/250 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/250/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/250/comments | https://api.github.com/repos/huggingface/datasets/issues/250/events | https://github.com/huggingface/datasets/pull/250 | 634,416,751 | MDExOlB1bGxSZXF1ZXN0NDMwOTcyMzg4 | 250 | Remove checksum download in c4 | {
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"Commenting again in case [previous thread](https://github.com/huggingface/nlp/pull/233) was inactive.\r\n\r\n@lhoestq I am facing `IsADirectoryError` while downloading with this command.\r\nCan you pls look into it & help me.\r\nI'm using version 0.4.0 of `nlp`.\r\n\r\n```\r\ndataset = load_dataset(\"c4\", 'en', d... | 1,591,607,580,000 | 1,598,339,096,000 | 1,591,607,819,000 | MEMBER | null | false | {
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} | There was a line from the original tfds script that was still there and causing issues when loading the c4 script. This one should fix #233 and allow anyone to load the c4 script to generate the dataset | {
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https://api.github.com/repos/huggingface/datasets/issues/249 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/249/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/249/comments | https://api.github.com/repos/huggingface/datasets/issues/249/events | https://github.com/huggingface/datasets/issues/249 | 633,393,443 | MDU6SXNzdWU2MzMzOTM0NDM= | 249 | [Dataset created] some critical small issues when I was creating a dataset | {
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"Thanks for noticing all these :) They should be easy to fix indeed",
"Alright I think I fixed all the problems you mentioned. Thanks again, that will be useful for many people.\r\nThere is still more work needed for point 7. but we plan to have some nice docs soon."
] | 1,591,534,734,000 | 1,591,950,531,000 | 1,591,950,531,000 | CONTRIBUTOR | null | null | null | Hi, I successfully created a dataset and has made a pr #248.
But I have encountered several problems when I was creating it, and those should be easy to fix.
1. Not found dataset_info.json
should be fixed by #241 , eager to wait it be merged.
2. Forced to install `apach_beam`
If we should install it, then it m... | {
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https://api.github.com/repos/huggingface/datasets/issues/248 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/248/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/248/comments | https://api.github.com/repos/huggingface/datasets/issues/248/events | https://github.com/huggingface/datasets/pull/248 | 633,390,427 | MDExOlB1bGxSZXF1ZXN0NDMwMDQ0MzU0 | 248 | add Toronto BooksCorpus | {
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"Thanks for adding this one !\r\n\r\nAbout the three points you mentioned:\r\n1. I think the `toronto_books_corpus` branch can be removed @mariamabarham ? \r\n2. You can use the download manager to download from google drive. For you case you can just do something like \r\n```python\r\nURL = \"https://drive.google.... | 1,591,534,496,000 | 1,591,951,503,000 | 1,591,951,502,000 | CONTRIBUTOR | null | false | {
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} | 1. I knew there is a branch `toronto_books_corpus`
- After I downloaded it, I found it is all non-english, and only have one row.
- It seems that it cites the wrong paper
- according to papar using it, it is called `BooksCorpus` but not `TornotoBooksCorpus`
2. It use a text mirror in google drive
- `bookscorpu... | {
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https://api.github.com/repos/huggingface/datasets/issues/247 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/247/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/247/comments | https://api.github.com/repos/huggingface/datasets/issues/247/events | https://github.com/huggingface/datasets/pull/247 | 632,380,078 | MDExOlB1bGxSZXF1ZXN0NDI5MTMwMzQ2 | 247 | Make all dataset downloads deterministic by applying `sorted` to glob and os.listdir | {
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"That's great!\r\n\r\nI think it would be nice to test \"deterministic-ness\" of datasets in CI if we can do it (should be left for future PR of course)\r\n\r\nHere is a possibility (maybe there are other ways to do it): given that we may soon have efficient and large-scale hashing (cf our discussion on versioning/... | 1,591,441,330,000 | 1,591,607,896,000 | 1,591,607,894,000 | MEMBER | null | false | {
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} | This PR makes all datasets loading deterministic by applying `sorted()` to all `glob.glob` and `os.listdir` statements.
Are there other "non-deterministic" functions apart from `glob.glob()` and `os.listdir()` that you can think of @thomwolf @lhoestq @mariamabarham @jplu ?
**Important**
It does break backward c... | {
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https://api.github.com/repos/huggingface/datasets/issues/246 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/246/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/246/comments | https://api.github.com/repos/huggingface/datasets/issues/246/events | https://github.com/huggingface/datasets/issues/246 | 632,380,054 | MDU6SXNzdWU2MzIzODAwNTQ= | 246 | What is the best way to cache a dataset? | {
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"Everything is already cached by default in 🤗nlp (in particular dataset\nloading and all the “map()” operations) so I don’t think you need to do any\nspecific caching in streamlit.\n\nTell us if you feel like it’s not the case.\n\nOn Sat, 6 Jun 2020 at 13:02, Fabrizio Milo <notifications@github.com> wrote:\n\n> Fo... | 1,591,441,327,000 | 1,594,286,107,000 | 1,594,286,107,000 | NONE | null | null | null | For example if I want to use streamlit with a nlp dataset:
```
@st.cache
def load_data():
return nlp.load_dataset('squad')
```
This code raises the error "uncachable object"
Right now I just fixed with a constant for my specific case:
```
@st.cache(hash_funcs={pyarrow.lib.Buffer: lambda b: 0})
```... | {
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https://api.github.com/repos/huggingface/datasets/issues/245 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/245/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/245/comments | https://api.github.com/repos/huggingface/datasets/issues/245/events | https://github.com/huggingface/datasets/issues/245 | 631,985,108 | MDU6SXNzdWU2MzE5ODUxMDg= | 245 | SST-2 test labels are all -1 | {
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"this also happened to me with `nlp.load_dataset('glue', 'mnli')`",
"Yes, this is because the test sets for glue are hidden so the labels are\nnot publicly available. You can read the glue paper for more details.\n\nOn Sat, 6 Jun 2020 at 18:16, Jack Morris <notifications@github.com> wrote:\n\n> this also happened... | 1,591,393,302,000 | 1,638,924,452,000 | 1,591,462,601,000 | CONTRIBUTOR | null | null | null | I'm trying to test a model on the SST-2 task, but all the labels I see in the test set are -1.
```
>>> import nlp
>>> glue = nlp.load_dataset('glue', 'sst2')
>>> glue
{'train': Dataset(schema: {'sentence': 'string', 'label': 'int64', 'idx': 'int32'}, num_rows: 67349), 'validation': Dataset(schema: {'sentence': 'st... | {
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https://api.github.com/repos/huggingface/datasets/issues/244 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/244/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/244/comments | https://api.github.com/repos/huggingface/datasets/issues/244/events | https://github.com/huggingface/datasets/pull/244 | 631,869,155 | MDExOlB1bGxSZXF1ZXN0NDI4NjgxMTcx | 244 | Add Allociné Dataset | {
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"great work @TheophileBlard ",
"LGTM, thanks a lot for adding dummy data tests :-) Was it difficult to create the correct dummy data folder? ",
"It was pretty easy actually. Documentation is on point !"
] | 1,591,384,766,000 | 1,591,861,646,000 | 1,591,861,646,000 | CONTRIBUTOR | null | false | {
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} | This is a french binary sentiment classification dataset, which was used to train this model: https://huggingface.co/tblard/tf-allocine.
Basically, it's a french "IMDB" dataset, with more reviews.
More info on [this repo](https://github.com/TheophileBlard/french-sentiment-analysis-with-bert). | {
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https://api.github.com/repos/huggingface/datasets/issues/243 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/243/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/243/comments | https://api.github.com/repos/huggingface/datasets/issues/243/events | https://github.com/huggingface/datasets/pull/243 | 631,735,848 | MDExOlB1bGxSZXF1ZXN0NDI4NTY2MTEy | 243 | Specify utf-8 encoding for GLUE | {
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"Thanks for fixing the encoding :)"
] | 1,591,374,780,000 | 1,592,428,566,000 | 1,591,605,721,000 | CONTRIBUTOR | null | false | {
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} | #242
This makes the GLUE-MNLI dataset readable on my machine, not sure if it's a Windows-only bug. | {
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https://api.github.com/repos/huggingface/datasets/issues/242 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/242/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/242/comments | https://api.github.com/repos/huggingface/datasets/issues/242/events | https://github.com/huggingface/datasets/issues/242 | 631,733,683 | MDU6SXNzdWU2MzE3MzM2ODM= | 242 | UnicodeDecodeError when downloading GLUE-MNLI | {
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"It should be good now, thanks for noticing and fixing it ! I would say that it was because you are on windows but not 100% sure",
"On Windows Python supports Unicode almost everywhere, but one of the notable exceptions is open() where it uses the locale encoding schema. So platform independent python scripts wou... | 1,591,374,601,000 | 1,591,718,807,000 | 1,591,605,903,000 | CONTRIBUTOR | null | null | null | When I run
```python
dataset = nlp.load_dataset('glue', 'mnli')
```
I get an encoding error (could it be because I'm using Windows?) :
```python
# Lots of error log lines later...
~\Miniconda3\envs\nlp\lib\site-packages\tqdm\std.py in __iter__(self)
1128 try:
-> 1129 for obj in iterable:... | {
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https://api.github.com/repos/huggingface/datasets/issues/241 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/241/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/241/comments | https://api.github.com/repos/huggingface/datasets/issues/241/events | https://github.com/huggingface/datasets/pull/241 | 631,703,079 | MDExOlB1bGxSZXF1ZXN0NDI4NTQwMDM0 | 241 | Fix empty cache dir | {
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"Looks great! Will this change force all cached datasets to be redownloaded? But even if it does, it shoud not be a big problem, I think",
"> Looks great! Will this change force all cached datasets to be redownloaded? But even if it does, it shoud not be a big problem, I think\r\n\r\nNo it shouldn't force to redo... | 1,591,371,922,000 | 1,591,605,333,000 | 1,591,605,331,000 | MEMBER | null | false | {
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} | If the cache dir of a dataset is empty, the dataset fails to load and throws a FileNotFounfError. We could end up with empty cache dir because there was a line in the code that created the cache dir without using a temp dir. Using a temp dir is useful as it gets renamed to the real cache dir only if the full process is... | {
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https://api.github.com/repos/huggingface/datasets/issues/240 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/240/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/240/comments | https://api.github.com/repos/huggingface/datasets/issues/240/events | https://github.com/huggingface/datasets/issues/240 | 631,434,677 | MDU6SXNzdWU2MzE0MzQ2Nzc= | 240 | Deterministic dataset loading | {
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"Yes good point !",
"I think using `sorted(glob.glob())` would actually solve this problem. Can you think of other reasons why dataset loading might not be deterministic? @mariamabarham @yjernite @lhoestq @thomwolf . \r\n\r\nI can do a sweep through the dataset scripts and fix the glob.glob() if you guys are ok w... | 1,591,347,806,000 | 1,591,607,894,000 | 1,591,607,894,000 | MEMBER | null | null | null | When calling:
```python
import nlp
dataset = nlp.load_dataset("trivia_qa", split="validation[:1%]")
```
the resulting dataset is not deterministic over different google colabs.
After talking to @thomwolf, I suspect the reason to be the use of `glob.glob` in line:
https://github.com/huggingface/nlp/blob/2e0... | {
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https://api.github.com/repos/huggingface/datasets/issues/239 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/239/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/239/comments | https://api.github.com/repos/huggingface/datasets/issues/239/events | https://github.com/huggingface/datasets/issues/239 | 631,340,440 | MDU6SXNzdWU2MzEzNDA0NDA= | 239 | [Creating new dataset] Not found dataset_info.json | {
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"I think you can just `rm` this directory and it should be good :)",
"@lhoestq - this seems to happen quite often (already the 2nd issue). Can we maybe delete this automatically?",
"Yes I have an idea of what's going on. I'm sure I can fix that",
"Hi, I rebase my local copy to `fix-empty-cache-dir`, and try t... | 1,591,337,704,000 | 1,591,534,864,000 | 1,591,534,864,000 | CONTRIBUTOR | null | null | null | Hi, I am trying to create Toronto Book Corpus. #131
I ran
`~/nlp % python nlp-cli test datasets/bookcorpus --save_infos --all_configs`
but this doesn't create `dataset_info.json` and try to use it
```
INFO:nlp.load:Checking datasets/bookcorpus/bookcorpus.py for additional imports.
INFO:filelock:Lock 1397953257... | {
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https://api.github.com/repos/huggingface/datasets/issues/238 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/238/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/238/comments | https://api.github.com/repos/huggingface/datasets/issues/238/events | https://github.com/huggingface/datasets/issues/238 | 631,260,143 | MDU6SXNzdWU2MzEyNjAxNDM= | 238 | [Metric] Bertscore : Warning : Empty candidate sentence; Setting recall to be 0. | {
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"This print statement comes from the official implementation of bert_score (see [here](https://github.com/Tiiiger/bert_score/blob/master/bert_score/utils.py#L343)). The warning shows up only if the attention mask outputs no candidate.\r\nRight now we want to only use official code for metrics to have fair evaluatio... | 1,591,323,287,000 | 1,593,450,619,000 | 1,593,450,619,000 | NONE | null | null | null | When running BERT-Score, I'm meeting this warning :
> Warning: Empty candidate sentence; Setting recall to be 0.
Code :
```
import nlp
metric = nlp.load_metric("bertscore")
scores = metric.compute(["swag", "swags"], ["swags", "totally something different"], lang="en", device=0)
```
---
**What am I do... | {
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"You should use `load_dataset('glue', 'mnli')`",
"Thanks! I thought I had to use the same code displayed in the live viewer:\r\n```python\r\n!pip install nlp\r\nfrom nlp import load_dataset\r\ndataset = load_dataset('multi_nli', 'plain_text')\r\n```\r\nYour suggestion works, even if then I got a different issue (... | 1,591,311,921,000 | 1,591,440,694,000 | 1,591,440,694,000 | CONTRIBUTOR | null | null | null | When I try to download MultiNLI with
```python
dataset = load_dataset('multi_nli')
```
I get this long error:
```python
---------------------------------------------------------------------------
OSError Traceback (most recent call last)
<ipython-input-13-3b11f6be4cb9> in <m... | {
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https://api.github.com/repos/huggingface/datasets/issues/236 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/236/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/236/comments | https://api.github.com/repos/huggingface/datasets/issues/236/events | https://github.com/huggingface/datasets/pull/236 | 631,099,875 | MDExOlB1bGxSZXF1ZXN0NDI4MDUwNzI4 | 236 | CompGuessWhat?! dataset | {
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"Hi @aleSuglia, thanks for this great PR. Indeed you can have both datasets in one file. You need to add a config class which will allows you to specify the different subdataset names and then you will be able to load them as follow.\r\nnlp.load_dataset(\"compguesswhat\", \"compguesswhat-gameplay\") \r\nnlp.load_d... | 1,591,299,950,000 | 1,591,868,622,000 | 1,591,861,521,000 | CONTRIBUTOR | null | false | {
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Thanks for the amazing library that you put together. I'm Alessandro Suglia, the first author of CompGuessWhat?!, a recently released dataset for grounded language learning accepted to ACL 2020 ([https://compguesswhat.github.io](https://compguesswhat.github.io)).
This pull-request adds the CompGuessWhat?! ... | {
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"I think it would be nicer to not create a new folder `datasets_experimental` , but just put your datasets also into the folder `datasets` for the following reasons:\r\n\r\n- From my point of view, the datasets are not very different from the other datasets (assuming that we soon have C4, and the beam datasets) so ... | 1,591,286,096,000 | 1,591,976,335,000 | 1,591,976,335,000 | MEMBER | null | false | {
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} | ## Adding an *experimental datasets* folder
After using the 🤗nlp library for some time, I find that while it makes it super easy to create new memory-mapped datasets with lots of cool utilities, a lot of what I want to do doesn't work well with the current `MockDownloader` based testing paradigm, making it hard to ... | {
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"What do you mean 'custom' ? You may want to elaborate on it when ask a question.\r\n\r\nAnyway, there are two things you may interested\r\n`nlp.Dataset.from_file` and `load_dataset(..., cache_dir=)`",
"To load a dataset you need to have a script that defines the format of the examples, the splits and the way to ... | 1,591,250,346,000 | 1,594,028,006,000 | 1,594,028,006,000 | NONE | null | null | null | Hello,
Does anyone know how we can call our custom dataset using the nlp.load command? Let's say that I have a dataset based on the same format as that of squad-v1.1, how am I supposed to load it using huggingface nlp.
Thank you! | {
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"Hello ! Thanks for noticing this bug, let me fix that.\r\n\r\nAlso for information, as specified in the changelog of the latest release, C4 currently needs to have a runtime for apache beam to work on. Apache beam is used to process this very big dataset and it can work on dataflow, spark, flink, apex, etc. You ca... | 1,591,232,798,000 | 1,610,090,252,000 | 1,591,607,819,000 | NONE | null | null | null | i run following code to download c4 English corpus.
```
dataset = nlp.load_dataset('c4', 'en', beam_runner='DirectRunner'
, data_dir='/mypath')
```
and i met failure as follows
```
Downloading and preparing dataset c4/en (download: Unknown size, generated: Unknown size, total: Unknown size) to /home/adam/.... | {
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"LGTM 👍 "
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} | With this PR users will be able to upload their own datasets and metrics.
As mentioned in #181, I had to use the new endpoints and revert the use of dataclasses (just in case we have changes in the API in the future).
We now distinguish commands for datasets and commands for metrics:
```bash
nlp-cli upload_data... | {
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@yjernite | {
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"\r\nThis was actually the right name. `dataset_infos.json` is used to have the infos of all the dataset configurations.\r\n\r\nOn the other hand `dataset_info.json` (without 's') is a cache file with the info of one specific configuration.\r\n\r\nTo fix #228, we probably just have to clear and reload the nlp-viewe... | 1,591,187,504,000 | 1,591,188,774,000 | 1,591,188,513,000 | NONE | null | false | {
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"Added pull request to change the name of the file from dataset_infos.json to dataset_info.json",
"Thanks for reporting this bug !\r\nAs it seems to be just a cache problem, I closed your PR.\r\nI think we might just need to clear and reload the `xnli` cache @srush ? ",
"Update: The dataset_info.json error is g... | 1,591,187,114,000 | 1,595,007,862,000 | 1,595,007,862,000 | NONE | null | null | null | When I try to access the XNLI dataset, I get the following error. The option of plain_text get selected automatically and then I get the following error.
```
FileNotFoundError: [Errno 2] No such file or directory: '/home/sasha/.cache/huggingface/datasets/xnli/plain_text/1.0.0/dataset_info.json'
Traceback:
File "/... | {
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"Thanks for your message 😊 \r\nIndeed users shouldn't have to install those dependencies",
"Got it, feel free to close this issue when you think it’s resolved.",
"It should be good now :)"
] | 1,591,176,800,000 | 1,591,197,941,000 | 1,591,197,941,000 | CONTRIBUTOR | null | null | null | Hi, first thanks to @lhoestq 's revolutionary work, I successfully downloaded processed wikipedia according to the doc. 😍😍😍
But at the first try, it tell me to install `apache_beam` and `mwparserfromhell`, which I thought wouldn't be used according to #204 , it was kind of confusing me at that time.
Maybe we s... | {
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"Awesome :D"
] | 1,591,008,885,000 | 1,591,195,043,000 | 1,591,195,042,000 | CONTRIBUTOR | null | false | {
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