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https://api.github.com/repos/huggingface/datasets/issues/548 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/548/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/548/comments | https://api.github.com/repos/huggingface/datasets/issues/548/events | https://github.com/huggingface/datasets/pull/548 | 689,285,996 | MDExOlB1bGxSZXF1ZXN0NDc2MzYzMjU1 | 548 | [Breaking] Switch text loading to multi-threaded PyArrow loading | {
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"Awesome !\r\nAlso I was wondering if we should try to make the hashing of the `data_files` faster (it is used to build the cache directory of datasets like `text` or `json`). Right now it reads each file and hashes all of its data. We could simply hash the path and some metadata including the `time last modified` ... | 1,598,886,941,000 | 1,599,560,398,000 | 1,599,560,397,000 | MEMBER | null | Test if we can get better performances for large-scale text datasets by using multi-threaded text file loading based on Apache Arrow multi-threaded CSV loader.
If it works ok, it would fix #546.
**Breaking change**:
The text lines now do not include final line-breaks anymore. | {
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"When you load a text file for the first time with `nlp`, the file is converted into Apache Arrow format. Arrow allows to use memory-mapping, which means that you can load an arbitrary large dataset.\r\n\r\nNote that as soon as the conversion has been done once, the next time you'll load the dataset it will be much... | 1,598,878,643,000 | 1,633,705,937,000 | 1,599,560,397,000 | NONE | null | I made a simple python script to check the NLP library speed, which loads 1.1 TB of textual data.
It has been 8 hours and still, it is on the loading steps.
It does work when the text dataset size is small about 1 GB, but it doesn't scale.
It also uses a single thread during the data loading step.
```
train_fil... | {
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https://api.github.com/repos/huggingface/datasets/issues/545 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/545/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/545/comments | https://api.github.com/repos/huggingface/datasets/issues/545/events | https://github.com/huggingface/datasets/issues/545 | 689,138,878 | MDU6SXNzdWU2ODkxMzg4Nzg= | 545 | New release coming up for this library | {
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"Update: release is planed mid-next week."
] | 1,598,873,858,000 | 1,610,535,544,000 | 1,610,535,544,000 | MEMBER | null | Hi all,
A few words on the roadmap for this library.
The next release will be a big one and is planed at the end of this week.
In addition to the support for indexed datasets (useful for non-parametric models like REALM, RAG, DPR, knn-LM and many other fast dataset retrieval technics), it will:
- have support f... | {
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"I'll take a look!"
] | 1,598,757,634,000 | 1,598,872,510,000 | 1,598,872,510,000 | NONE | null | Loading from local files, e.g., `dataset = nlp.load_dataset('csv', data_files=['file_1.csv', 'file_2.csv'])`
concurrently from multiple processes, will raise `FileExistsError` from builder's line 430, https://github.com/huggingface/nlp/blob/6655008c738cb613c522deb3bd18e35a67b2a7e5/src/nlp/builder.py#L423-L438
Likel... | {
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https://api.github.com/repos/huggingface/datasets/issues/542 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/542/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/542/comments | https://api.github.com/repos/huggingface/datasets/issues/542/events | https://github.com/huggingface/datasets/pull/542 | 688,555,036 | MDExOlB1bGxSZXF1ZXN0NDc1NzkyNTY0 | 542 | Add TensorFlow example | {
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https://api.github.com/repos/huggingface/datasets/issues/541 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/541/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/541/comments | https://api.github.com/repos/huggingface/datasets/issues/541/events | https://github.com/huggingface/datasets/issues/541 | 688,521,224 | MDU6SXNzdWU2ODg1MjEyMjQ= | 541 | Best practices for training tokenizers with nlp | {
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What do you think are the best practices for training tokenizers using `nlp`? In the document and examples, I could only find pre-trained tokenizers used. | {
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"I'm not sure this would fix #537 .\r\nHowever your point about the missing `middle` data is right and we probably want to include these data as well.\r\nDo you think it would we worth having different configurations for this dataset for users who want to only load part of it (`high school` or `middle` or `all`) ?"... | 1,598,684,410,000 | 1,600,429,340,000 | 1,600,429,340,000 | CONTRIBUTOR | null | In #537 I noticed that there was a bug in checksum checking when I have tried to download the race dataset. The reason for this is that the current preprocessing was just considering the `high school` data and it was ignoring the `middle` one. This PR just fixes it :)
Moreover, I have added some descriptions. | {
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"Hi @gaguilar \r\n\r\nIf you want to take care of this, it very simple, you just need to regenerate the `dataset_infos.json` file as indicated [in the doc](https://huggingface.co/nlp/share_dataset.html#adding-metadata) by [installing from source](https://huggingface.co/nlp/installation.html#installing-from-source) ... | 1,598,644,551,000 | 1,599,150,842,000 | 1,599,150,841,000 | CONTRIBUTOR | null | Hi,
There is a `NonMatchingChecksumError` error for the `lid_msaea` (language identification for Modern Standard Arabic - Egyptian Arabic) dataset from the LinCE benchmark due to a minor update on that dataset.
How can I update the checksum of the library to solve this issue? The error is below and it also appea... | {
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You can use:
```
nlp.logging.set_verbosity(verbosity: int)
nlp.logging.set_verbosity_info()
nlp.logging.set_verbosity_warning()
nlp.logging.set_verbosity_debug... | {
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"`NonMatchingChecksumError` means that the checksum of the downloaded file is not the expected one.\r\nEither the file you downloaded was corrupted along the way, or the host updated the file.\r\nCould you try to clear your cache and run `load_dataset` again ? If the error is still there, it means that there was an... | 1,598,572,696,000 | 1,600,430,824,000 | 1,600,430,824,000 | CONTRIBUTOR | null | Hi there, I just would like to use this awesome lib to perform a dataset fine-tuning on RACE dataset. I have performed the following steps:
```
dataset = nlp.load_dataset("race")
len(dataset["train"]), len(dataset["validation"])
```
But then I got the following error:
```
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"I changed the way I implemented fingerprint updates to use decorator functions.\r\n\r\nI also added a new attribute called `_inplace_history` that stores the in-place history of transforms (like cast_, rename_columns, etc.). This history is useful to replay the changes that were done in-place when unpickling a dat... | 1,598,545,629,000 | 1,598,883,640,000 | 1,598,883,639,000 | MEMBER | null | This PR is a continuation of #513 , in which many in-place functions were introduced or updated (cast_, flatten_) etc.
However the caching didn't handle these changes. Indeed the caching took into account only the previous cache file name of the table, and not the possible in-place transforms of the table.
To fix t... | {
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To add a new tracked benchmark:
- create a new python benchmarking script in `./benchmarks/`. The script can use the utilities in `./benchmarks/utils.py` and should output a JSON file with results in `./benchmarks/results/`.
- add a new pipeline stage in [dvc.yaml](./dvc.yaml) w... | {
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"Thanks for reporting !\r\nThis has been fixed in #475 and the fix will be available in the next release",
"What you can do instead to get the list of the datasets is call\r\n\r\n```python\r\nprint([dataset.id for dataset in nlp.list_datasets()])\r\n```",
"Thanks @lhoestq . "
] | 1,598,429,941,000 | 1,598,509,871,000 | 1,598,509,871,000 | NONE | null | version = '0.4.0'
`list_datasets()` is broken. It results in the following error :
```
In [3]: nlp.list_datasets()
Out[3]: ---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
~/.virtualenvs/san-lgUCsFg_/lib/py... | {
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"I am facing probably facing similar issues with \r\n\r\n`wiki40b_en_100_0`",
"Could you try to run `dataset = load_dataset(\"text\", data_files=file_path, split=\"train\")` once before calling the script ?\r\n\r\nIt looks like several processes try to create the dataset in arrow format at the same time. If the d... | 1,598,366,198,000 | 1,598,962,496,000 | null | NONE | null | Hi,
I'm getting a "File exists" error when I use [text dataset](https://github.com/huggingface/nlp/tree/master/datasets/text) for pre-training a RoBERTa model using `transformers` (3.0.2) and `nlp`(0.4.0) on a VM with TPU (v3-8).
I modified [line 131 in the original `run_language_modeling.py`](https://github.com/... | {
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"Yes I agree. Maybe something that lets specify different format depending on the column ? Especially to better control dtype and shape (and ragged for tf)\r\n\r\nOh and I forgot: this one should also fix the second issue found in #477 for the next release",
"I am running into the same issue with the error messag... | 1,598,288,775,000 | 1,634,931,520,000 | 1,598,296,945,000 | MEMBER | null | I think it's better if it's clear whether the returned tensor is ragged or not when the type is set to tensorflow.
Previously it was a tensor (not ragged) if numpy could stack the output (which can change depending on the batch of example you take), which make things difficult to handle, as it may sometimes return a r... | {
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"Could you test to run the test using the changes in #527 and let me know if it fixes the issue ? If so I'll merge it and we'll be good to go :)",
"Hello, it does work on the fixing real dataset branch. Merci Quentin :)",
"Nice, glad to hear that :)\r\nde rien !"
] | 1,598,285,915,000 | 1,598,429,051,000 | 1,598,429,051,000 | CONTRIBUTOR | null | Hello (again :) !),
So, I started a new branch because of a [rebase issue](https://github.com/huggingface/nlp/pull/463), sorry for the mess.
However, the command `pytest tests/test_dataset_common.py::LocalDatasetTest::test_load_real_dataset_mlsum` still fails because there is no default language dataset : the s... | {
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"The problem came from `default: ` that is rendered differently and hides the parameter names. I changed `default: ...` to `defaults to ...`"
] | 1,598,275,908,000 | 1,598,346,244,000 | 1,598,346,243,000 | MEMBER | null | fix #524 | {
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To fix that I replaced it with one test with the first config of BUILDER_CONFIGS `test_load_real_dataset`, and another test that runs all of the configs in BUILDER_CONFIGS `test_load... | {
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"We have to change the tests to expect `None` instead of `python` then",
"Merging!"
] | 1,598,271,035,000 | 1,598,273,443,000 | 1,598,273,442,000 | MEMBER | null | Following the discussion on Slack, this small fix ensures that calling `dataset.set_format(type=dataset.format["type"])` works properly. Slightly breaking as calling `dataset.format` when the dataset is unformatted will return `None` instead of `python`. | {
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https://api.github.com/repos/huggingface/datasets/issues/525 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/525/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/525/comments | https://api.github.com/repos/huggingface/datasets/issues/525/events | https://github.com/huggingface/datasets/issues/525 | 683,875,483 | MDU6SXNzdWU2ODM4NzU0ODM= | 525 | wmt download speed example | {
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"Thanks for creating the issue :)\r\nThe download link for wmt-en-de raw looks like a mirror. We should use that instead of the current url.\r\nIs this mirror official ?\r\n\r\nAlso it looks like for `ro-en` it tried to download other languages. If we manage to only download the one that is asked it'd be cool\r\n\r... | 1,598,052,546,000 | 1,613,664,967,000 | null | CONTRIBUTOR | null | Continuing from the slack 1.0 roadmap thread w @lhoestq , I realized the slow downloads is only a thing sometimes. Here are a few examples, I suspect there are multiple issues. All commands were run from the same gcp us-central-1f machine.
```
import nlp
nlp.load_dataset('wmt16', 'de-en')
```
Downloads at 49.1 K... | {
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"Indeed, good catch!"
] | 1,598,028,454,000 | 1,598,346,243,000 | 1,598,346,243,000 | CONTRIBUTOR | null | See https://huggingface.co/nlp/master/package_reference/main_classes.html#nlp.Dataset.map. I believe this is because the parameter names are enclosed in backticks in the docstrings, maybe it's an old docstring format that doesn't work with the current Sphinx version. | {
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"I took your comments into account and added tests for `cast_to_python_objects`"
] | 1,597,916,522,000 | 1,598,259,255,000 | 1,598,259,254,000 | MEMBER | null | I changed how `cast_to_python_objects` works to make it faster.
It is used to cast numpy/pytorch/tensorflow/pandas objects to python lists, and it works recursively.
To avoid iterating over possibly long lists, it first checks if the first element that is not None has to be casted.
If the first element needs to be... | {
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"Thanks!"
] | 1,597,907,465,000 | 1,597,909,934,000 | 1,597,909,933,000 | CONTRIBUTOR | null | Many places dictionary is spelled dictionnary, not sure if its on purpose or not.
Fixed in this pr:
https://github.com/huggingface/nlp/pull/521 | {
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"Hahah thanks Yonatan. It was not on purpose, we are just not very good at spelling :)"
] | 1,597,907,342,000 | 1,597,909,924,000 | 1,597,909,924,000 | CONTRIBUTOR | null | This error happens many times I'm thinking maybe its spelled like this on purpose? | {
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https://api.github.com/repos/huggingface/datasets/issues/520 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/520/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/520/comments | https://api.github.com/repos/huggingface/datasets/issues/520/events | https://github.com/huggingface/datasets/pull/520 | 682,264,839 | MDExOlB1bGxSZXF1ZXN0NDcwNTI4MDE0 | 520 | Transform references for sacrebleu | {
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"I think I agree @lhoestq so I pushed a change.\r\nThanks for your work on the library!"
] | 1,597,883,215,000 | 1,597,915,854,000 | 1,597,915,853,000 | CONTRIBUTOR | null | Currently it is impossible to use sacrebleu when len(predictions) != the number of references per prediction (very uncommon), due to a strange format expected by sacrebleu. If one passes in the data to `nlp.metric.compute()` in sacrebleu format, `nlp` throws an error due to mismatching lengths between predictions and r... | {
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"Update - maybe this is only failing on bleu because I was not tokenizing inputs to the metric",
"Closing - seems to be just forgetting to tokenize. And found the helpful discussion in #137 "
] | 1,597,872,555,000 | 1,597,874,680,000 | 1,597,874,680,000 | CONTRIBUTOR | null | The following error occurs when passing in references of type `List[List[str]]` to metrics like bleu.
Wasn't happening on 0.4.0 but happening now on master.
```
File "/usr/local/lib/python3.7/site-packages/nlp/metric.py", line 226, in compute
self.add_batch(predictions=predictions, references=references)
... | {
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"(test failure is unrelated)",
"As discussed with @thomwolf merging since the hyperparameter-search has been merged in transformers."
] | 1,597,866,188,000 | 1,598,284,900,000 | 1,598,284,899,000 | MEMBER | null | Move the acquisition of the filelock at a later stage during metrics processing so it can be pickled/cloudpickled after instantiation.
Also add some tests on pickling, concurrent but separate metric instances and concurrent and distributed metric instances.
Changes significantly the caching behavior for the metri... | {
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"Any updates on this?",
"This request is still an open issue waiting to be addressed by any community member, @GuillemGSubies."
] | 1,597,848,119,000 | 1,627,970,373,000 | null | CONTRIBUTOR | null | Hi,
I am recommending that someone add MLDoc, a multilingual news topic classification dataset.
- Here's a link to the Github: https://github.com/facebookresearch/MLDoc
- and the paper: http://www.lrec-conf.org/proceedings/lrec2018/pdf/658.pdf
Looks like the dataset contains news stories in multiple languages... | {
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The happened during the creation of the `pa.Table`, since columns had different lengths. | {
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"This seems to be fixed in #513 for the filter function, replacing `cache_file_name` with `indices_cache_file_name` in the assert. Although not for the `map()` function @thomwolf ",
"Maybe I'm a bit tired but I fail to see the issue here.\r\n\r\nSince `cache_file_name` is `None` by default, if you set `keep_in_me... | 1,597,776,460,000 | 1,627,063,631,000 | null | CONTRIBUTOR | null | As of commit ef4aac2, the usage of the parameter `keep_in_memory=True` is never possible: `dataset.select(keep_in_memory=True)`
The commit added the lines
```python
# lines 994-996 in src/nlp/arrow_dataset.py
assert (
not keep_in_memory or cache_file_name is None
), "Please use either... | {
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"Ok I fixed `concatenate_datasets` and added tests\r\nFeel free to merge if it's good for you @thomwolf ",
"Ok, adding some benchmarks for map/filters and then I'll merge",
"Warning from pytorch that we should maybe consider at some point @lhoestq:\r\n```\r\n/__w/nlp/nlp/src/nlp/arrow_dataset.py:648: UserWarnin... | 1,597,772,162,000 | 1,598,604,111,000 | 1,598,604,110,000 | MEMBER | null | Use an indices mapping instead of rewriting the dataset for all the samples re-ordering/selection methods (`select`, `sort`, `shuffle`, `shard`, `train_test_split`).
Added a `flatten_indices` method which copy the dataset to a new table to remove the indices mapping with tests.
All the samples re-ordering/selecti... | {
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"😱",
"Yeah, this is spammy behavior. I've reported the user handle."
] | 1,597,764,805,000 | 1,597,765,701,000 | 1,597,765,147,000 | NONE | null | {
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https://api.github.com/repos/huggingface/datasets/issues/511 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/511/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/511/comments | https://api.github.com/repos/huggingface/datasets/issues/511/events | https://github.com/huggingface/datasets/issues/511 | 681,055,553 | MDU6SXNzdWU2ODEwNTU1NTM= | 511 | dataset.shuffle() and select() resets format. Intended? | {
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"Hi @vegarab yes feel free to open a discussion here.\r\n\r\nThis design choice was not very much thought about.\r\n\r\nSince `dataset.select()` (like all the method without a trailing underscore) is non-destructive and returns a new dataset it has most of its properties initialized from scratch (except the table a... | 1,597,758,361,000 | 1,600,073,138,000 | 1,600,073,138,000 | CONTRIBUTOR | null | Calling `dataset.shuffle()` or `dataset.select()` on a dataset resets its format set by `dataset.set_format()`. Is this intended or an oversight?
When working on quite large datasets that require a lot of preprocessing I find it convenient to save the processed dataset to file using `torch.save("dataset.pt")`. Later... | {
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"Seems like this method was added in 1.17. I'll add a requirement on this.",
"Thank you so much. After upgrading the numpy library, it worked."
] | 1,597,741,153,000 | 1,597,862,156,000 | 1,597,862,156,000 | NONE | null | Thank you so much for your excellent work! I would like to use nlp library in my project. While importing nlp, I am receiving the following error `AttributeError: module 'numpy.random' has no attribute 'Generator'` Numpy version in my project is 1.16.0. May I learn which numpy version is used for the nlp library.
Th... | {
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"Do you want to convert a dataset script to the tfds format ?\r\nIf so, we currently have a comversion script nlp/commands/convert.py but it is a conversion script that goes from tfds to nlp.\r\nI think it shouldn't be too hard to do the changes in reverse (at some manual adjustments).\r\nIf you manage to make it w... | 1,597,565,120,000 | 1,627,970,478,000 | 1,627,970,477,000 | NONE | null | Hi,
I want to use TensorFlow datasets with this repo, I noticed you made some conversion script,
can you give a simple example of using it?
Thanks
| {
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"Which version of Apache Beam do you have (can you copy your full environment info here)?",
"apache-beam==2.23.0\r\nnlp==0.4.0\r\n\r\nFor me this was resolved by running the same python script on Linux (or really WSL). ",
"Do you manage to run a dummy beam pipeline with python on windows ? \r\nYou can test a du... | 1,597,562,296,000 | 1,598,972,013,000 | 1,598,971,743,000 | NONE | null | I am trying to load a wikipedia data set
```
import nlp
from nlp import load_dataset
dataset = load_dataset("wikipedia", "20200501.en", split="train", cache_dir=data_path, beam_runner='DirectRunner')
#dataset = load_dataset('wikipedia', '20200501.sv', cache_dir=data_path, beam_runner='DirectRunner')
```
Th... | {
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"Looks like an issue with 3.0.2 transformers version. Works fine when I use \"master\" version of transformers."
] | 1,597,439,037,000 | 1,597,441,150,000 | 1,597,441,150,000 | NONE | null | I tried the following example code from https://huggingface.co/deepset/roberta-base-squad2 and got errors
I am using **transformers 3.0.2** code .
from transformers.pipelines import pipeline
from transformers.modeling_auto import AutoModelForQuestionAnswering
from transformers.tokenization_auto import AutoToke... | {
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I fixed that and added tests.
Thanks @avloss for reporting | {
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"Thanks for reporting the issue ! I'm creating a new PR to fix it and add tests.\r\n(I'm doing a new PR because I know there's some other place where it needs to be fixed)",
"I'm closing this one as I created the other PR."
] | 1,597,361,253,000 | 1,597,412,566,000 | 1,597,412,566,000 | NONE | null | Just learning about this library - so might've not set up all the flags correctly, but was getting this error about "tmp_file". | {
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"Thank you @ghomasHudson for making our dataset available! This is great!",
"The test passes since #527 :)"
] | 1,597,355,626,000 | 1,598,516,321,000 | 1,598,516,321,000 | CONTRIBUTOR | null | Following the discussion on Slack and #349, I've updated the hyperpartisan dataset to pull directly from Zenodo rather than manual install, which should make this dataset much more accessible. Many thanks to @johanneskiesel !
Currently doesn't pass `test_load_real_dataset` - I'm using `self.config.name` which is `de... | {
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"I don't see any significant change in the dataset script (except the version value update), can you check that again please ?",
"Hi @aleSuglia , can you check that all the changes you wanted to do are in the dataset script ?",
"Hey sorry but I'm in the middle of a conference deadline. I'll let you know asap!",... | 1,597,351,886,000 | 1,603,263,269,000 | 1,603,263,269,000 | CONTRIBUTOR | null | We updated some metadata information associated with the dataset. In addition, we've updated the `create_dummy_data.py` script to generate data samples for the dataset. | {
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https://api.github.com/repos/huggingface/datasets/issues/502 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/502/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/502/comments | https://api.github.com/repos/huggingface/datasets/issues/502/events | https://github.com/huggingface/datasets/pull/502 | 678,546,070 | MDExOlB1bGxSZXF1ZXN0NDY3NDc1MDg0 | 502 | Fix tokenizers caching | {
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"This should fix #501 and also the issue you sent me on slack @sgugger ."
] | 1,597,334,017,000 | 1,597,844,239,000 | 1,597,844,238,000 | MEMBER | null | I've found some cases where the caching didn't work properly for tokenizers:
1. if a tokenizer has a regex pattern, then the caching would be inconsistent across sessions
2. if a tokenizer has a cache attribute that changes after some calls, the the caching would not work after cache updates
3. if a tokenizer is u... | {
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"Thanks for reporting !\r\n\r\nTo store the cache file, we compute a hash of the function given in `.map`, using our own hashing function.\r\nThe hash doesn't seem to stay the same over sessions for the tokenizer.\r\nApparently this is because of the regex at `tokenizer.pat` is not well supported by our hashing fun... | 1,597,263,607,000 | 1,598,286,900,000 | 1,598,286,875,000 | NONE | null | The caching functionality doesn't work reliably when tokenizing a dataset. Here's a small example to reproduce it.
```python
import nlp
import transformers
def main():
ds = nlp.load_dataset("reddit", split="train[:500]")
tokenizer = transformers.AutoTokenizer.from_pretrained("gpt2")
def conv... | {
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"I took a look at the dummy data creation for this dataset.\r\n\r\nMaybe it didn't work on your side might be because `master.zip` and `narrativeqa_full_text.zip` are supposed to be directories and not acutal zip files in the dummy data folder.\r\n\r\nI managed to make it work with this `dummy_data.zip` file:\r\nht... | 1,597,240,183,000 | 1,607,512,862,000 | 1,607,512,862,000 | CONTRIBUTOR | null | Following the uploading of the full text data in #309, I've added the full text to the narrativeqa dataset.
Few notes:
- Had some encoding issues using the default `open` so am using `open(encoding="latin-1"...` which seems to fix it. Looks fine.
- Can't get the dummy data to work. Currently putting stuff at:
... | {
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Fix #490
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https://api.github.com/repos/huggingface/datasets/issues/497 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/497/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/497/comments | https://api.github.com/repos/huggingface/datasets/issues/497/events | https://github.com/huggingface/datasets/pull/497 | 677,057,116 | MDExOlB1bGxSZXF1ZXN0NDY2MjQ2NDQ3 | 497 | skip header in PAWS-X | {
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I also updated the `dataset_infos.json` file that is used to verify the integrity of the generated splits (the number of examples was reduced by one).
Note that there are new fields in `dataset_infos.json` introduced in the latest release 0.4.0 corresponding to post processing info. I remove... | {
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https://api.github.com/repos/huggingface/datasets/issues/496 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/496/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/496/comments | https://api.github.com/repos/huggingface/datasets/issues/496/events | https://github.com/huggingface/datasets/pull/496 | 677,016,998 | MDExOlB1bGxSZXF1ZXN0NDY2MjE1Mjg1 | 496 | fix bad type in overflow check | {
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This is because we were not using the inferred features to do this check, and we could end up with arrays that don't match because of a type mismatch (`null` vs `string` for example).
This s... | {
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I added support for stacked tensors for both pytorch and tensorflow.
For ragged tensors, they are stack... | {
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"This PR also fixed a bug where numpy arrays were returned instead of pytorch tensors when getting with a clumn as a key."
] | 1,597,153,230,000 | 1,597,157,810,000 | 1,597,153,792,000 | MEMBER | null | When getting items using a column name as a key, numpy arrays were not stacked.
I fixed that and added some tests.
There is another issue that still needs to be fixed though: when getting items using a column name as a key, pytorch tensors are not stacked (it outputs a list of tensors). This PR should help with the... | {
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"this doesn't work. I can decompress the file after download locally."
] | 1,597,112,092,000 | 1,597,112,548,000 | 1,597,112,532,000 | CONTRIBUTOR | null | I verified that
```
wget https://stuncorpusprod.blob.core.windows.net/corpusfiles/UNv1.0.en-zh.tar.gz.00
```
runs in 2 minutes. | {
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"In 0.4.0, the assertion in `concatenate_datasets ` is on the features, and not the schema.\r\nCould you try to update `nlp` ?\r\n\r\nAlso, since 0.4.0, you can use `dset_wikipedia.cast_(dset_books.features)` to avoid the schema cast hack.",
"Or maybe the assertion comes from elsewhere ?",
"I'm using the master... | 1,597,105,666,000 | 1,598,458,639,000 | 1,598,458,639,000 | CONTRIBUTOR | null | Here's the code I'm trying to run:
```python
dset_wikipedia = nlp.load_dataset("wikipedia", "20200501.en", split="train", cache_dir=args.cache_dir)
dset_wikipedia.drop(columns=["title"])
dset_wikipedia.features.pop("title")
dset_books = nlp.load_dataset("bookcorpus", split="train", cache_dir=args.cache_dir)
dse... | {
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"I did the release on github, and updated the doc :)\r\nSorry for the delay",
"Thanks!"
] | 1,597,103,997,000 | 1,597,164,607,000 | 1,597,164,607,000 | CONTRIBUTOR | null | 0.4.0 was released on PyPi, but not on GitHub. This means [the documentation](https://huggingface.co/nlp/) is still displaying from 0.3.0, and that there's no tag to easily clone the 0.4.0 version of the repo. | {
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https://api.github.com/repos/huggingface/datasets/issues/490 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/490/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/490/comments | https://api.github.com/repos/huggingface/datasets/issues/490/events | https://github.com/huggingface/datasets/issues/490 | 676,482,242 | MDU6SXNzdWU2NzY0ODIyNDI= | 490 | Loading preprocessed Wikipedia dataset requires apache_beam | {
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`nlp.load_dataset("wikipedia", "20200501.en", split="train", dir="/tmp/wikipedia")`
gives an error if apache_beam is not installed, stemming from
https://github.com/huggingface/nlp/blob/38eb2413de54ee804b0be81781bd65ac4a748ced/src/nlp/builder.py#L981-L988
This succeeded without the dependency in ve... | {
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"whoops",
"please delete this"
] | 1,597,098,783,000 | 1,597,100,114,000 | 1,597,098,820,000 | NONE | null | {
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https://api.github.com/repos/huggingface/datasets/issues/488 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/488/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/488/comments | https://api.github.com/repos/huggingface/datasets/issues/488/events | https://github.com/huggingface/datasets/issues/488 | 676,299,993 | MDU6SXNzdWU2NzYyOTk5OTM= | 488 | issues with downloading datasets for wmt16 and wmt19 | {
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"I found `UNv1.0.en-ru.tar.gz` here: https://conferences.unite.un.org/uncorpus/en/downloadoverview, so it can be reconstructed with:\r\n```\r\nwget -c https://stuncorpusprod.blob.core.windows.net/corpusfiles/UNv1.0.en-ru.tar.gz.00\r\nwget -c https://stuncorpusprod.blob.core.windows.net/corpusfiles/UNv1.0.en-ru.tar.... | 1,597,080,771,000 | 1,597,122,454,000 | null | CONTRIBUTOR | null | I have encountered multiple issues while trying to:
```
import nlp
dataset = nlp.load_dataset('wmt16', 'ru-en')
metric = nlp.load_metric('wmt16')
```
1. I had to do `pip install -e ".[dev]" ` on master, currently released nlp didn't work (sorry, didn't save the error) - I went back to the released version and no... | {
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https://api.github.com/repos/huggingface/datasets/issues/487 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/487/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/487/comments | https://api.github.com/repos/huggingface/datasets/issues/487/events | https://github.com/huggingface/datasets/pull/487 | 676,143,029 | MDExOlB1bGxSZXF1ZXN0NDY1NTA1NjQy | 487 | Fix elasticsearch result ids returning as strings | {
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"It looks like you need to rebase from master to fix the CI. Could you do that please ?"
] | 1,597,066,631,000 | 1,598,870,566,000 | 1,598,870,566,000 | CONTRIBUTOR | null | I am using the latest elasticsearch binary and master of nlp. For me elasticsearch searches failed because the resultant "id_" returned for searches are strings, but our library assumes them to be integers. | {
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https://api.github.com/repos/huggingface/datasets/issues/486 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/486/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/486/comments | https://api.github.com/repos/huggingface/datasets/issues/486/events | https://github.com/huggingface/datasets/issues/486 | 675,649,034 | MDU6SXNzdWU2NzU2NDkwMzQ= | 486 | Bookcorpus data contains pretokenized text | {
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"Yes indeed it looks like some `'` and spaces are missing (for example in `dont` or `didnt`).\r\nDo you know if there exist some copies without this issue ?\r\nHow would you fix this issue on the current data exactly ? I can see that the data is raw text (not tokenized) so I'm not sure I understand how you would do... | 1,596,956,004,000 | 1,601,467,264,000 | null | CONTRIBUTOR | null | It seem that the bookcoprus data downloaded through the library was pretokenized with NLTK's Treebank tokenizer, which changes the text in incompatible ways to how, for instance, BERT's wordpiece tokenizer works. For example, "didn't" becomes "did" + "n't", and double quotes are changed to `` and '' for start and end q... | {
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https://api.github.com/repos/huggingface/datasets/issues/485 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/485/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/485/comments | https://api.github.com/repos/huggingface/datasets/issues/485/events | https://github.com/huggingface/datasets/issues/485 | 675,595,393 | MDU6SXNzdWU2NzU1OTUzOTM= | 485 | PAWS dataset first item is header | {
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import nlp
dataset = nlp.load_dataset('xtreme', 'PAWS-X.en')
dataset['test'][0]
```
prints the following
```
{'label': 'label', 'sentence1': 'sentence1', 'sentence2': 'sentence2'}
```
dataset['test'][0] should probably be the first item in the dataset, not just a dictionary mapping the column names t... | {
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https://api.github.com/repos/huggingface/datasets/issues/484 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/484/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/484/comments | https://api.github.com/repos/huggingface/datasets/issues/484/events | https://github.com/huggingface/datasets/pull/484 | 675,088,983 | MDExOlB1bGxSZXF1ZXN0NDY0NjY1NTU4 | 484 | update mirror for RT dataset | {
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"Thanks for adding this mirror link :)\r\n\r\nCould you run the following command to update the json file `dataset_infos.json` used to verify the integrity of the downloaded file ?\r\n\r\n```\r\nnlp-cli test ./datasets/rotten_tomatoes --save_infos --ignore_verifications\r\n```",
"done! @lhoestq ",
"the build_do... | 1,596,813,945,000 | 1,598,276,017,000 | 1,598,276,017,000 | CONTRIBUTOR | null | {
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https://api.github.com/repos/huggingface/datasets/issues/483 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/483/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/483/comments | https://api.github.com/repos/huggingface/datasets/issues/483/events | https://github.com/huggingface/datasets/issues/483 | 675,080,694 | MDU6SXNzdWU2NzUwODA2OTQ= | 483 | rotten tomatoes movie review dataset taken down | {
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"found a mirror: https://storage.googleapis.com/seldon-datasets/sentence_polarity_v1/rt-polaritydata.tar.gz",
"fixed in #484 ",
"Closing this one. Thanks again @jxmorris12 for taking care of this :)"
] | 1,596,813,121,000 | 1,599,557,794,000 | 1,599,557,793,000 | CONTRIBUTOR | null | In an interesting twist of events, the individual who created the movie review seems to have left Cornell, and their webpage has been removed, along with the movie review dataset (http://www.cs.cornell.edu/people/pabo/movie-review-data/rt-polaritydata.tar.gz). It's not downloadable anymore. | {
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"This comes from an overflow in pyarrow's array.\r\nIt is stuck inside the loop that reduces the batch size to avoid the overflow.\r\nI'll take a look",
"I created a PR to fix the issue.\r\nIt was due to an overflow check that handled badly an empty list.\r\n\r\nYou can try the changes by using \r\n```\r\n!pip in... | 1,596,788,615,000 | 1,597,241,626,000 | 1,597,190,115,000 | NONE | null | Hi Huggingface Team!
Thank you guys once again for this amazing repo.
I have tried to prepare ELI5 to train with T5, based on [this wonderful notebook of Suraj Patil](https://github.com/patil-suraj/exploring-T5/blob/master/T5_on_TPU.ipynb)
However, when I run `dataset.map()` on ELI5 to prepare `input_text, ta... | {
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https://api.github.com/repos/huggingface/datasets/issues/481 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/481/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/481/comments | https://api.github.com/repos/huggingface/datasets/issues/481/events | https://github.com/huggingface/datasets/pull/481 | 674,567,389 | MDExOlB1bGxSZXF1ZXN0NDY0MjM2MTA1 | 481 | Apply utf-8 encoding to all datasets | {
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"Not sure why the AWS test is failing - perhaps I made too many concurrent CI builds 😢. Can someone please rerun the CI to check the error is not on my end?",
"I pushed an improved docstring and the unit tests now pass, which suggests the previous failure on AWS was simply a timeout error. \r\n\r\nFor some reaso... | 1,596,744,129,000 | 1,597,911,368,000 | 1,597,911,368,000 | MEMBER | null | ## Description
This PR applies utf-8 encoding for all instances of `with open(...) as f` to all Python files in `datasets/`. As suggested by @thomwolf in #468 , we use regular expressions and the following function
```python
def apply_encoding_on_file_open(filepath: str):
"""Apply UTF-8 encoding for all insta... | {
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https://api.github.com/repos/huggingface/datasets/issues/480 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/480/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/480/comments | https://api.github.com/repos/huggingface/datasets/issues/480/events | https://github.com/huggingface/datasets/pull/480 | 674,245,959 | MDExOlB1bGxSZXF1ZXN0NDYzOTcwNjQ2 | 480 | Column indexing hotfix | {
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"Looks good to me as well but we'll want to add a test indeed.\r\nYou can add one if you have time @TevenLeScao.\r\nOtherwise, we'll do it when we are back with Quentin. ",
"I fixed it in #494 "
] | 1,596,713,825,000 | 1,597,221,370,000 | 1,597,221,370,000 | MEMBER | null | As observed for example in #469 , currently `__getitem__` does not convert the data to the dataset format when indexing by column. This is a hotfix that imitates functional 0.3.0. code. In the future it'd probably be nice to have a test there. | {
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https://api.github.com/repos/huggingface/datasets/issues/479 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/479/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/479/comments | https://api.github.com/repos/huggingface/datasets/issues/479/events | https://github.com/huggingface/datasets/pull/479 | 673,905,407 | MDExOlB1bGxSZXF1ZXN0NDYzNjkxMjA0 | 479 | add METEOR metric | {
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"Really nice !\r\nThanks for adding this one.\r\n\r\nI noticed that there are some '-' that are left in the description in the middle of some workds. It migh come from copy-pasting the pdf paper. ex: `im-provement`. Could you fix that please ?",
"@lhoestq \r\nLinebreaks have been removed! Note that there are stil... | 1,596,669,180,000 | 1,597,844,349,000 | 1,597,844,349,000 | CONTRIBUTOR | null | Added the METEOR metric. Can be used like this:
```python
import nlp
meteor = nlp.load_metric('metrics/meteor')
meteor.compute(["some string", "some string"], ["some string", "some similar string"])
# {'meteor': 0.6411637931034483}
meteor.add("some string", "some string")
meteor.add('some string", "some simila... | {
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"Nevermind, I restarted my python session and it worked fine...\r\n\r\n---\r\n\r\nI had an authentification error, and I authenticated from another terminal. After that, no more error but it was not working. Restarting the sessions makes it work :)"
] | 1,596,589,712,000 | 1,596,590,497,000 | 1,596,590,496,000 | NONE | null | Previously, I was writing TFRecords manually to GCP bucket with : `with tf.io.TFRecordWriter('gs://my_bucket/x.tfrecord')`
Since `0.4.0` is out with the `export()` function, I tried it. But it seems TFRecords cannot be directly written to GCP bucket.
`dataset.export('local.tfrecord')` works fine,
but `dataset.... | {
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"Thanks for reporting this issue\r\n\r\nThere was a bug where numpy arrays would get returned instead of tensorflow tensors.\r\nThis is fixed on master.\r\n\r\nI tried to re-run the colab and encountered this error instead:\r\n\r\n```\r\nAttributeError: 'tensorflow.python.framework.ops.EagerTensor' object has no at... | 1,596,583,095,000 | 1,627,970,535,000 | 1,627,970,535,000 | NONE | null | with nlp 0.4.0, the TensorFlow example in Overview.ipynb throws the following exceptions:
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-5-48907f2ad433> in <module>
----> 1 features = {x: trai... | {
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"> Also, a little out of my depth there, but would there be a way to have the default pip install checklist command not require mysql and mariadb to be installed? Feels like that might be a source of confusion for users.\r\n\r\nI removed the pattern dependency, mysql is not a requirement anymore. I'm not sure where... | 1,596,565,925,000 | 1,599,161,648,000 | null | NONE | null | Sorry for the large pull request.
- Added checklists as datasets. I can't run `test_load_real_dataset` (see #474), but I can load the datasets successfully as shown in the example notebook
- Added a checklist wrapper | {
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"Cool thanks, I made those changes. LMK if you think it's ready for merge.",
"Ok to merge for me"
] | 1,596,555,149,000 | 1,597,698,848,000 | 1,597,698,847,000 | CONTRIBUTOR | null | A few misc. bugs and QOL improvements that I've come across in using the library. Let me know if you don't like any of them and I can adjust/remove them.
1. Printing datasets without a description field throws an error when formatting the `single_line_description`. This fixes that, and also adds some formatting to t... | {
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"The `data_dir` parameter has been removed. Now the error is `ValueError: Config name is missing`\r\n\r\nAs mentioned in #470 I think we can have one test with the first config of BUILDER_CONFIGS, and another test that runs all of the configs in BUILDER_CONFIGS",
"This was fixed in #527 \r\n\r\nClosing this one, ... | 1,596,498,396,000 | 1,599,490,393,000 | 1,599,490,393,000 | NONE | null | It a dataset has custom `BUILDER_CONFIGS` with non-keyword arguments (or keyword arguments with non default values), the config is not loaded during the test and causes an error.
I think the problem is that `test_load_real_dataset` calls `load_dataset` with `data_dir=temp_data_dir` ([here](https://github.com/huggingfa... | {
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"This PR was already approved by @lhoestq in #456 . This one just make style to remove some typos"
] | 1,596,453,302,000 | 1,596,453,730,000 | 1,596,453,729,000 | CONTRIBUTOR | null | opening new PR for CRD3 dataset (ACL2020) to fix the circle CI problems | {
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"Ok I tried to add the dummy dataset (I actually modified the dummy_data command to generate them for me because it was too painful to do that manually).\r\n\r\nThe dummy_data test seems to work:\r\n```bash\r\nRUN_SLOW=1 pytest tests/test_dataset_common.py::LocalDatasetTest::test_load_dataset_all_configs_iwslt2017\... | 1,596,448,359,000 | 1,599,482,010,000 | 1,599,482,010,000 | CONTRIBUTOR | null | Created a [IWSLT 2017](https://sites.google.com/site/iwsltevaluation2017/TED-tasks) dataset script for the *multilingual data*.
```
Bilingual data: {Arabic, German, French, Japanese, Korean, Chinese} <-> English
Multilingual data: German, English, Italian, Dutch, Romanian. (Any pair)
```
I'm unsure how to h... | {
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https://api.github.com/repos/huggingface/datasets/issues/469 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/469/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/469/comments | https://api.github.com/repos/huggingface/datasets/issues/469/events | https://github.com/huggingface/datasets/issues/469 | 671,876,963 | MDU6SXNzdWU2NzE4NzY5NjM= | 469 | invalid data type 'str' at _convert_outputs in arrow_dataset.py | {
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"Hi ! Did you try to set the output format to pytorch ? (or tensorflow if you're using tensorflow)\r\nIt can be done with `dataset.set_format(\"torch\", columns=columns)` (or \"tensorflow\").\r\n\r\nNote that for pytorch, string columns can't be converted to `torch.Tensor`, so you have to specify in `columns=` the... | 1,596,440,909,000 | 1,603,357,466,000 | null | NONE | null | I trying to build multi label text classifier model using Transformers lib.
I'm using Transformers NLP to load the data set, while calling trainer.train() method. It throws the following error
File "C:\***\arrow_dataset.py", line 343, in _convert_outputs
v = command(v)
TypeError: new(): invalid data type ... | {
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https://api.github.com/repos/huggingface/datasets/issues/468 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/468/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/468/comments | https://api.github.com/repos/huggingface/datasets/issues/468/events | https://github.com/huggingface/datasets/issues/468 | 671,622,441 | MDU6SXNzdWU2NzE2MjI0NDE= | 468 | UnicodeDecodeError while loading PAN-X task of XTREME dataset | {
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"Indeed. Solution 1 is the simplest.\r\n\r\nThis is actually a recurring problem.\r\nI think we should scan all the datasets with regexpr to fix the use of `open()` without encodings.\r\nAnd probably add a test in the CI to forbid using this in the future.",
"I'm happy to tackle the broader problem - will open a ... | 1,596,377,110,000 | 1,597,911,368,000 | 1,597,911,368,000 | MEMBER | null | Hi 🤗 team!
## Description of the problem
I'm running into a `UnicodeDecodeError` while trying to load the PAN-X subset the XTREME dataset:
```
---------------------------------------------------------------------------
UnicodeDecodeError Traceback (most recent call last)
<ipython-inp... | {
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"Thanks!"
] | 1,596,358,777,000 | 1,596,376,347,000 | 1,596,359,934,000 | CONTRIBUTOR | null | Fix typo from dictionnary -> dictionary | {
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"The cast function is now called inside `features.encode_example`.\r\nI also added `encode_batch` that was missing.\r\n\r\nMoreover I used the cast function in `Dataset.map` to support torch/tensorflow tensors or numpy arrays inputs.\r\n\r\nThere are tests for tensors inputs in metrics and in .map",
"I think we c... | 1,596,279,825,000 | 1,597,677,300,000 | 1,597,677,299,000 | MEMBER | null | - Disallow the use of positional arguments to avoid `predictions` vs `references` mistakes
- Allow to directly feed numpy/pytorch/tensorflow/pandas objects in metrics | {
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"One note on features inference:\r\n\r\nif an arrow type is `struct of items` where each item is a `list`, then we return a `dict` in which each item is a `Sequence`.\r\nIt means that we don't use the Sequence <-> dict swap when we infer features.\r\n\r\nIt's fine because the swap is generally used in dataset scrip... | 1,596,206,601,000 | 1,596,220,053,000 | 1,596,220,052,000 | MEMBER | null | When applying a transform like `map`, some features were lost (and inferred features were used).
It was the case for ClassLabel, Translation, etc.
To fix that, I did some modifications in the `ArrowWriter`:
- added the `update_features` parameter. When it's `True`, then the features specified by the user (if any... | {
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These methods are added to `Dataset` as well as `DatasetDict`.
Added tests for these new methods and add the methods to the doc.
Naming follows th... | {
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"I think the problem is related to `wiki_dpr` dataset which is making the circle CI failed as you can see:\r\n```\r\nFAILED tests/test_dataset_common.py::AWSDatasetTest::test_load_dataset_wiki_dpr\r\nFAILED tests/test_hf_gcp.py::TestDatasetOnHfGcp::test_script_synced_with_s3_wiki_dpr/dummy_psgs_w100_no_embeddings\r... | 1,596,196,252,000 | 1,598,280,882,000 | 1,598,280,882,000 | CONTRIBUTOR | null | New pull request that should correct the previous errors.
The load_real_data stills fails because it is looking for a default dataset URL that does not exists, this does not happen when loading the dataset with load_dataset | {
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"Thanks @TevenLeScao for finding this issue",
"Thanks @lhoestq for catching this ❤️"
] | 1,596,185,835,000 | 1,596,195,139,000 | 1,596,195,138,000 | MEMBER | null | If you interrupted a map function while it was writing, the cached file was not discarded.
Therefore the next time you called map, it was loading an incomplete arrow file.
We had the same issue with select if there was a bad indice at one point.
To fix that I used temporary files that are renamed once everything... | {
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- rename the `flatten`, `drop` and `dictionary_encode_column` methods in `flatten_`, `drop_` and `dictionary_encode_column_` to indicate that these methods have in-place effects as discussed in #166. From now on we s... | {
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Also changed the function call to use named rather than positional argum... | {
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Add tests to these for `Dataset` and `DatasetDict`.
Fix some bugs uncovered by the tests for `pandas` formating. | {
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"Sorry one nit: Could we use named arguments for the call to BLEURT?\r\n\r\ni.e. \r\n scores = self.scorer.score(references=references, candidates=predictions)\r\n\r\n(i.e. so it is less bug prone)\r\n",
"Following up on Ankur's comment---we are going to drop support for\npositional (not named) arguments i... | 1,596,046,112,000 | 1,596,203,774,000 | 1,596,203,774,000 | MEMBER | null | This PR adds the BLEURT metric to the library.
The BLEURT `Metric` downloads a TF checkpoint corresponding to its `config_name` at creation (in the `_info` function). Default is set to `bleurt-base-128`.
Note that the default in the original package is `bleurt-tiny-128`, but they throw a warning and recommend usi... | {
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"Hi ! Glad you managed to fix the version issue.\r\n\r\nThe command `\r\npython nlp-cli dummy_data datasets/guardian_authorship --save_infos --all_configs` is supposed to generate a json file `dataset_infos.json` next to your dataset script, but I can't see it in the PR.\r\nCan you make sure you have the json file ... | 1,595,989,437,000 | 1,597,936,197,000 | 1,597,936,076,000 | CONTRIBUTOR | null | A new dataset: Guardian news articles for authorship attribution
**tests passed:**
python nlp-cli dummy_data datasets/guardian_authorship --save_infos --all_configs
RUN_SLOW=1 pytest tests/test_dataset_common.py::LocalDatasetTest::test_load_dataset_all_configs_guardian_authorship
**Tests failed:**
Real data:... | {
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"I think this is the way to go but I’m afraid this might be a little slow. I was thinking that we could use a high quality very fast non crypto hash like xxhash for these stuff (hashing data files)",
"Yep good idea, I'll take a look",
"I tested the hashing speed [here](https://colab.research.google.com/drive/1h... | 1,595,953,851,000 | 1,596,031,043,000 | 1,596,031,042,000 | MEMBER | null | The cache dir for csv/json/txt datasets was always the same. This is an issue because it should be different depending on the data files provided by the user.
To fix that, I added a line that use the hash of the data files provided by the user to define the cache dir.
This should fix #444 | {
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#353 | {
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"> Awesome !\r\n> Good job on parsing these files :O\r\n> \r\n> Do you think it would be hard to get the two other split configurations ?\r\n\r\nIt shouldn't be that hard, I think I can consider different config names for each split ",
"> > Awesome !\r\n> > Good job on parsing these files :O\r\n> > Do you think i... | 1,595,926,692,000 | 1,596,453,031,000 | 1,596,453,031,000 | CONTRIBUTOR | null | This PR adds the `Reuters_21578` dataset https://kdd.ics.uci.edu/databases/reuters21578/reuters21578.html
#353
The datasets is a lit of `.sgm` files which are a bit different from xml file indeed `xml.etree` couldn't be used to read files. I consider them as text file (to avoid using external library) and read ... | {
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