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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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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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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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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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**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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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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#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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Added a test to recognize import errors of all metrics | {
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#445 | {
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#445 | {
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When loading the metric "sacrebleu" there is an import error due to the wrong path
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```
dataset = load_dataset('csv', data_file='./a.csv')
```
And after a while, I tried to load another csv called 'b.csv'
```
dataset = load_dataset('csv', data_file='./b.csv')
```
However, the new dataset seems to remain the old 'a.csv' and not loading new csv file.
Even... | {
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https://api.github.com/repos/huggingface/datasets/issues/443 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/443/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/443/comments | https://api.github.com/repos/huggingface/datasets/issues/443/events | https://github.com/huggingface/datasets/issues/443 | 666,246,716 | MDU6SXNzdWU2NjYyNDY3MTY= | 443 | Cannot unpickle saved .pt dataset with torch.save()/load() | {
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} | Saving a formatted torch dataset to file using `torch.save()`. Loading the same file fails during unpickling:
```python
>>> import torch
>>> import nlp
>>> squad = nlp.load_dataset("squad.py", split="train")
>>> squad
Dataset(features: {'source_text': Value(dtype='string', id=None), 'target_text': Value(dtype... | {
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https://api.github.com/repos/huggingface/datasets/issues/442 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/442/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/442/comments | https://api.github.com/repos/huggingface/datasets/issues/442/events | https://github.com/huggingface/datasets/issues/442 | 666,201,810 | MDU6SXNzdWU2NjYyMDE4MTA= | 442 | [Suggestion] Glue Diagnostic Data with Labels | {
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} | Hello! First of all, thanks for setting up this useful project!
I've just realised you provide the the [Glue Diagnostics Data](https://huggingface.co/nlp/viewer/?dataset=glue&config=ax) without labels, indicating in the `GlueConfig` that you've only a test set.
Yet, the data with labels is available, too (see als... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/441 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/441/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/441/comments | https://api.github.com/repos/huggingface/datasets/issues/441/events | https://github.com/huggingface/datasets/pull/441 | 666,148,413 | MDExOlB1bGxSZXF1ZXN0NDU3MDQyMjY3 | 441 | Add features parameter in load dataset | {
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If they don't match the data type, it raises a `ValueError`.
It's a draft PR because #440 needs to be merged first. | {
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https://api.github.com/repos/huggingface/datasets/issues/440 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/440/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/440/comments | https://api.github.com/repos/huggingface/datasets/issues/440/events | https://github.com/huggingface/datasets/pull/440 | 666,116,823 | MDExOlB1bGxSZXF1ZXN0NDU3MDE2MjQy | 440 | Fix user specified features in map | {
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The writer used to overwrite the user specified features with inferred features.
I also added tests to make sure it doesn't happen again. | {
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https://api.github.com/repos/huggingface/datasets/issues/439 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/439/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/439/comments | https://api.github.com/repos/huggingface/datasets/issues/439/events | https://github.com/huggingface/datasets/issues/439 | 665,964,673 | MDU6SXNzdWU2NjU5NjQ2NzM= | 439 | Issues: Adding a FAISS or Elastic Search index to a Dataset | {
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} | It seems the DPRContextEncoder, DPRContextEncoderTokenizer cited[ in this documentation](https://huggingface.co/nlp/faiss_and_ea.html) is not implemented ? It didnot work with the standard nlp installation . Also, I couldn't find or use it with the latest nlp install from github in Colab. Is there any dependency on t... | {
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} | **Links:**
[iwslt](https://pytorchnlp.readthedocs.io/en/latest/_modules/torchnlp/datasets/iwslt.html)
Don't know if that link is up to date.
[ittb](http://www.cfilt.iitb.ac.in/iitb_parallel/)
**Motivation**: replicate mbart finetuning results (table below)
![image](https://user-images.githubusercontent.com/60450... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/437 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/437/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/437/comments | https://api.github.com/repos/huggingface/datasets/issues/437/events | https://github.com/huggingface/datasets/pull/437 | 665,597,176 | MDExOlB1bGxSZXF1ZXN0NDU2NjIzNjc3 | 437 | Fix XTREME PAN-X loading | {
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In response to the discussion in #425 @lewtun and I made some fixes to the repo. In the original XTREME implementation the PAN-X dataset for named entity recognition loaded each word/tag pair as a single row and the sentence relation was lost. With the fix each row contains the list of all words in a single sen... | {
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ImportWarning: To use `nlp`, the module `pyarrow>=0.16.0` is required, and the current version of `pyarrow` doesn't match this condition. If you are running this in a Google Colab, you should probably just rest... | {
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https://api.github.com/repos/huggingface/datasets/issues/435 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/435/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/435/comments | https://api.github.com/repos/huggingface/datasets/issues/435/events | https://github.com/huggingface/datasets/issues/435 | 665,507,141 | MDU6SXNzdWU2NjU1MDcxNDE= | 435 | ImportWarning for pyarrow 1.0.0 | {
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https://api.github.com/repos/huggingface/datasets/issues/434 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/434/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/434/comments | https://api.github.com/repos/huggingface/datasets/issues/434/events | https://github.com/huggingface/datasets/pull/434 | 665,477,638 | MDExOlB1bGxSZXF1ZXN0NDU2NTM3Njgz | 434 | Fixed check for pyarrow | {
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https://api.github.com/repos/huggingface/datasets/issues/433 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/433/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/433/comments | https://api.github.com/repos/huggingface/datasets/issues/433/events | https://github.com/huggingface/datasets/issues/433 | 665,311,025 | MDU6SXNzdWU2NjUzMTEwMjU= | 433 | How to reuse functionality of a (generic) dataset? | {
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} | I have written a generic dataset for corpora created with the Brat annotation tool ([specification](https://brat.nlplab.org/standoff.html), [dataset code](https://github.com/ArneBinder/nlp/blob/brat/datasets/brat/brat.py)). Now I wonder how to use that to create specific dataset instances. What's the recommended way to... | {
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https://api.github.com/repos/huggingface/datasets/issues/432 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/432/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/432/comments | https://api.github.com/repos/huggingface/datasets/issues/432/events | https://github.com/huggingface/datasets/pull/432 | 665,234,340 | MDExOlB1bGxSZXF1ZXN0NDU2MzQxNDk3 | 432 | Fix handling of config files while loading datasets from multiple processes | {
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https://api.github.com/repos/huggingface/datasets/issues/431 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/431/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/431/comments | https://api.github.com/repos/huggingface/datasets/issues/431/events | https://github.com/huggingface/datasets/pull/431 | 665,044,416 | MDExOlB1bGxSZXF1ZXN0NDU2MTgyNDE2 | 431 | Specify split post processing + Add post processing resources downloading | {
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```python
from nlp import load_dataset
wiki = load_dataset("wiki_dpr", "psgs_w100_with_nq_embeddings", split="train[:100]", with_index=True)
```
Then you'd get an error `Index size should match Dataset size...`
This was because it was trying to use the full index (21M elements).
... | {
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https://api.github.com/repos/huggingface/datasets/issues/430 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/430/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/430/comments | https://api.github.com/repos/huggingface/datasets/issues/430/events | https://github.com/huggingface/datasets/pull/430 | 664,583,837 | MDExOlB1bGxSZXF1ZXN0NDU1ODAxOTI2 | 430 | add DatasetDict | {
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### Overview
When you call `load_dataset` it can return a dictionary of datasets if there are several splits (train/test for example).
If you wanted to apply dataset transforms you had to iterate over each split and apply the transform.
Instead of returning a dict, it now returns a `nlp.Dat... | {
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https://api.github.com/repos/huggingface/datasets/issues/429 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/429/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/429/comments | https://api.github.com/repos/huggingface/datasets/issues/429/events | https://github.com/huggingface/datasets/pull/429 | 664,412,137 | MDExOlB1bGxSZXF1ZXN0NDU1NjU2MDk5 | 429 | mlsum | {
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The tests for the load_real_data fail, as there is no default language subset to download it looks for a file that does not exist. This bug does not happen when using the load_dataset function, as it asks you to specify a language if you do not, so I submit this PR anyway. The dataset is avalaible on : https... | {
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https://api.github.com/repos/huggingface/datasets/issues/428 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/428/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/428/comments | https://api.github.com/repos/huggingface/datasets/issues/428/events | https://github.com/huggingface/datasets/pull/428 | 664,367,086 | MDExOlB1bGxSZXF1ZXN0NDU1NjE3Nzcy | 428 | fix concatenate_datasets | {
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https://api.github.com/repos/huggingface/datasets/issues/427 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/427/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/427/comments | https://api.github.com/repos/huggingface/datasets/issues/427/events | https://github.com/huggingface/datasets/pull/427 | 664,341,623 | MDExOlB1bGxSZXF1ZXN0NDU1NTk1Nzc3 | 427 | Allow sequence features for beam + add processed Natural Questions | {
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### The issue
The steps of beam datasets processing is the following:
- download the source files and send them in a remote storage (gcs)
- process the files using a beam runner (dataflow)
- save output in remote storage (gcs)
- convert outp... | {
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https://api.github.com/repos/huggingface/datasets/issues/426 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/426/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/426/comments | https://api.github.com/repos/huggingface/datasets/issues/426/events | https://github.com/huggingface/datasets/issues/426 | 664,203,897 | MDU6SXNzdWU2NjQyMDM4OTc= | 426 | [FEATURE REQUEST] Multiprocessing with for dataset.map, dataset.filter | {
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} | It would be nice to be able to speed up `dataset.map` or `dataset.filter`. Perhaps this is as easy as sharding the dataset sending each shard to a process/thread/dask pool and using the new `nlp.concatenate_dataset()` function to join them all together? | {
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https://api.github.com/repos/huggingface/datasets/issues/425 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/425/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/425/comments | https://api.github.com/repos/huggingface/datasets/issues/425/events | https://github.com/huggingface/datasets/issues/425 | 664,029,848 | MDU6SXNzdWU2NjQwMjk4NDg= | 425 | Correct data structure for PAN-X task in XTREME dataset? | {
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## Description of the problem
Thanks to the fix from #416 I am now able to load the NER task in the XTREME dataset as follows:
```python
from nlp import load_dataset
# AmazonPhotos.zip is located in data/
dataset = load_dataset("xtreme", "PAN-X.en", data_dir='./data')
dataset_train = dataset['tr... | {
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https://api.github.com/repos/huggingface/datasets/issues/424 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/424/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/424/comments | https://api.github.com/repos/huggingface/datasets/issues/424/events | https://github.com/huggingface/datasets/pull/424 | 663,858,552 | MDExOlB1bGxSZXF1ZXN0NDU1MTk4MTY0 | 424 | Web of science | {
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#353 | {
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https://api.github.com/repos/huggingface/datasets/issues/423 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/423/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/423/comments | https://api.github.com/repos/huggingface/datasets/issues/423/events | https://github.com/huggingface/datasets/pull/423 | 663,079,359 | MDExOlB1bGxSZXF1ZXN0NDU0NTU4OTA0 | 423 | Change features vs schema logic | {
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Previously, it was confusing to have `features` and pyarrow's `schema` in `nlp.Dataset`.
However `features` is supposed to be the front-facing object to define the different fields of a dataset, while `schema` is only used to write arrow files.
Changes:
- Remove `sche... | {
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https://api.github.com/repos/huggingface/datasets/issues/422 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/422/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/422/comments | https://api.github.com/repos/huggingface/datasets/issues/422/events | https://github.com/huggingface/datasets/pull/422 | 663,028,497 | MDExOlB1bGxSZXF1ZXN0NDU0NTE3MDU2 | 422 | - Corrected encoding for IMDB. | {
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https://api.github.com/repos/huggingface/datasets/issues/421 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/421/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/421/comments | https://api.github.com/repos/huggingface/datasets/issues/421/events | https://github.com/huggingface/datasets/pull/421 | 662,213,864 | MDExOlB1bGxSZXF1ZXN0NDUzNzkzMzQ1 | 421 | Style change | {
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https://api.github.com/repos/huggingface/datasets/issues/420 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/420/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/420/comments | https://api.github.com/repos/huggingface/datasets/issues/420/events | https://github.com/huggingface/datasets/pull/420 | 662,029,782 | MDExOlB1bGxSZXF1ZXN0NDUzNjI5OTk2 | 420 | Better handle nested features | {
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- added arrow schema to features conversion (it's going to be useful to fix #342 )
- make flatten handle deep features (useful for tfrecords conversion in #339 )
- add tests for flatten and features conversions
- the reader now returns the kwargs to instantiate a Dataset (fix circular dependencies) | {
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Signed-off-by: lordtt13 <thakurtanmay72@yahoo.com> | {
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This is the script for me:
```python
class EmoConfig(nlp.BuilderConfig):
"""BuilderConfig ... | {
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https://api.github.com/repos/huggingface/datasets/issues/417 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/417/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/417/comments | https://api.github.com/repos/huggingface/datasets/issues/417/events | https://github.com/huggingface/datasets/pull/417 | 661,804,054 | MDExOlB1bGxSZXF1ZXN0NDUzNDMyODE5 | 417 | Fix docstrins multiple metrics instances | {
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This should fix #304 | {
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https://api.github.com/repos/huggingface/datasets/issues/416 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/416/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/416/comments | https://api.github.com/repos/huggingface/datasets/issues/416/events | https://github.com/huggingface/datasets/pull/416 | 661,635,393 | MDExOlB1bGxSZXF1ZXN0NDUzMjg1NTM4 | 416 | Fix xtreme panx directory | {
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https://api.github.com/repos/huggingface/datasets/issues/415 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/415/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/415/comments | https://api.github.com/repos/huggingface/datasets/issues/415/events | https://github.com/huggingface/datasets/issues/415 | 660,687,076 | MDU6SXNzdWU2NjA2ODcwNzY= | 415 | Something is wrong with WMT 19 kk-en dataset | {
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} | The translation in the `train` set does not look right:
```
>>>import nlp
>>>from nlp import load_dataset
>>>dataset = load_dataset('wmt19', 'kk-en')
>>>dataset["train"]["translation"][0]
{'kk': 'Trumpian Uncertainty', 'en': 'Трамптық белгісіздік'}
>>>dataset["validation"]["translation"][0]
{'kk': 'Ақша-несие... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/413 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/413/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/413/comments | https://api.github.com/repos/huggingface/datasets/issues/413/events | https://github.com/huggingface/datasets/issues/413 | 660,063,655 | MDU6SXNzdWU2NjAwNjM2NTU= | 413 | Is there a way to download only NQ dev? | {
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} | Maybe I missed that in the docs, but is there a way to only download the dev set of natural questions (~1 GB)?
As we want to benchmark QA models on different datasets, I would like to avoid downloading the 41GB of training data.
I tried
```
dataset = nlp.load_dataset('natural_questions', split="validation", bea... | {
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https://api.github.com/repos/huggingface/datasets/issues/412 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/412/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/412/comments | https://api.github.com/repos/huggingface/datasets/issues/412/events | https://github.com/huggingface/datasets/issues/412 | 660,047,139 | MDU6SXNzdWU2NjAwNDcxMzk= | 412 | Unable to load XTREME dataset from disk | {
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## Description of the problem
Following the [docs](https://huggingface.co/nlp/loading_datasets.html?highlight=xtreme#manually-downloading-files) I'm trying to load the `PAN-X.fr` dataset from the [XTREME](https://github.com/google-research/xtreme) benchmark.
I have manually downloaded the `AmazonPho... | {
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https://api.github.com/repos/huggingface/datasets/issues/411 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/411/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/411/comments | https://api.github.com/repos/huggingface/datasets/issues/411/events | https://github.com/huggingface/datasets/pull/411 | 659,393,398 | MDExOlB1bGxSZXF1ZXN0NDUxMjQxOTQy | 411 | Sbf | {
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"g... | [] | closed | false | [] | null | [] | 2020-07-17T16:19:45Z | 2020-07-21T09:13:46Z | 2020-07-21T09:13:45Z | null | CONTRIBUTOR | null | null | null | null | This PR adds the Social Bias Frames Dataset (ACL 2020) .
dataset homepage: https://homes.cs.washington.edu/~msap/social-bias-frames/ | {
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https://api.github.com/repos/huggingface/datasets/issues/410 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/410/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/410/comments | https://api.github.com/repos/huggingface/datasets/issues/410/events | https://github.com/huggingface/datasets/pull/410 | 659,242,871 | MDExOlB1bGxSZXF1ZXN0NDUxMTEzMTI3 | 410 | 20newsgroup | {
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#353 | {
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https://api.github.com/repos/huggingface/datasets/issues/409 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/409/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/409/comments | https://api.github.com/repos/huggingface/datasets/issues/409/events | https://github.com/huggingface/datasets/issues/409 | 659,128,611 | MDU6SXNzdWU2NTkxMjg2MTE= | 409 | train_test_split error: 'dict' object has no attribute 'deepcopy' | {
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} | `train_test_split` is giving me an error when I try and call it:
`'dict' object has no attribute 'deepcopy'`
## To reproduce
```
dataset = load_dataset('glue', 'mrpc', split='train')
dataset = dataset.train_test_split(test_size=0.2)
```
## Full Stacktrace
```
-------------------------------------------... | {
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These tests make sure that they're always available. It also makes sure that their scripts are in sync between S3 and the repo.
This should avoid future issues like #407 | {
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} | There may or may not be a regression for the pre-processed Wikipedia dataset. This was working fine 10 commits ago (without having Apache Beam available):
```
nlp.load_dataset('wikipedia', "20200501.en", split='train')
```
And now, having pulled master, I get:
```
Downloading and preparing dataset wikipedia... | {
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} | Consider shuffling bookcorpus:
```
dataset = nlp.load_dataset('bookcorpus', split='train')
dataset.shuffle()
```
According to tqdm, this will take around 2.5 hours on my machine to complete (even with the faster version of select from #405). I've also tried with `keep_in_memory=True` and `writer_batch_size=1000`... | {
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https://api.github.com/repos/huggingface/datasets/issues/405 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/405/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/405/comments | https://api.github.com/repos/huggingface/datasets/issues/405/events | https://github.com/huggingface/datasets/pull/405 | 658,580,192 | MDExOlB1bGxSZXF1ZXN0NDUwNTI1MTc3 | 405 | Make select() faster by batching reads | {
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```
dataset = nlp.load_dataset('bookcorpus', split='train')
start = time.time()
dataset.select(np.arange(1000), reader_batch_size=1, load_from_cache_file=False)
end = time.time()
print(f'{end - start}')
start = time.time()
dataset.select(np.arange(1000), reader_batch_size=1000, load_fr... | {
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https://api.github.com/repos/huggingface/datasets/issues/404 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/404/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/404/comments | https://api.github.com/repos/huggingface/datasets/issues/404/events | https://github.com/huggingface/datasets/pull/404 | 658,400,987 | MDExOlB1bGxSZXF1ZXN0NDUwMzY4Mjg4 | 404 | Add seed in metrics | {
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In this PR I allow the user to specify numpy's seed when instantiating a metric with `load_metric`.
The seed is set only when `compute` is called, and reset afterwards.
Moreover when calling `compute` with the same metric instance (i.e. same experiment... | {
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https://api.github.com/repos/huggingface/datasets/issues/403 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/403/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/403/comments | https://api.github.com/repos/huggingface/datasets/issues/403/events | https://github.com/huggingface/datasets/pull/403 | 658,325,756 | MDExOlB1bGxSZXF1ZXN0NDUwMzAzNjI2 | 403 | return python objects instead of arrays by default | {
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I fixed it by using to_pydict/to_pylist instead.
Fix #387
It was mentioned in https://github.com/huggingface/transformers/issues/5729
| {
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https://api.github.com/repos/huggingface/datasets/issues/402 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/402/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/402/comments | https://api.github.com/repos/huggingface/datasets/issues/402/events | https://github.com/huggingface/datasets/pull/402 | 658,001,288 | MDExOlB1bGxSZXF1ZXN0NDUwMDI2NTE0 | 402 | Search qa | {
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#336 | {
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https://api.github.com/repos/huggingface/datasets/issues/401 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/401/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/401/comments | https://api.github.com/repos/huggingface/datasets/issues/401/events | https://github.com/huggingface/datasets/pull/401 | 657,996,252 | MDExOlB1bGxSZXF1ZXN0NDUwMDIyNTc0 | 401 | add web_questions | {
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#336
Maybe @patrickvonplaten you can help with the dummy_data structure? it still broken | {
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https://api.github.com/repos/huggingface/datasets/issues/400 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/400/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/400/comments | https://api.github.com/repos/huggingface/datasets/issues/400/events | https://github.com/huggingface/datasets/pull/400 | 657,975,600 | MDExOlB1bGxSZXF1ZXN0NDUwMDA1MDU5 | 400 | Web questions | {
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#336 | {
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https://api.github.com/repos/huggingface/datasets/issues/399 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/399/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/399/comments | https://api.github.com/repos/huggingface/datasets/issues/399/events | https://github.com/huggingface/datasets/pull/399 | 657,841,433 | MDExOlB1bGxSZXF1ZXN0NDQ5ODkxNTEy | 399 | Spelling mistake | {
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https://api.github.com/repos/huggingface/datasets/issues/398 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/398/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/398/comments | https://api.github.com/repos/huggingface/datasets/issues/398/events | https://github.com/huggingface/datasets/pull/398 | 657,511,962 | MDExOlB1bGxSZXF1ZXN0NDQ5NjE1OTk1 | 398 | Add inline links | {
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https://api.github.com/repos/huggingface/datasets/issues/397 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/397/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/397/comments | https://api.github.com/repos/huggingface/datasets/issues/397/events | https://github.com/huggingface/datasets/pull/397 | 657,510,856 | MDExOlB1bGxSZXF1ZXN0NDQ5NjE1MDA4 | 397 | Add contiguous sharding | {
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"gists... | [] | closed | false | [] | null | [] | 2020-07-15T17:02:58Z | 2020-07-17T16:59:31Z | 2020-07-17T16:59:31Z | null | CONTRIBUTOR | null | null | null | null | This makes dset.shard() play nice with nlp.concatenate_datasets(). When I originally wrote the shard() method, I was thinking about a distributed training scenario, but https://github.com/huggingface/nlp/pull/389 also uses it for splitting the dataset for distributed preprocessing.
Usage:
```
nlp.concatenate_datas... | {
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Fix #395 | {
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https://api.github.com/repos/huggingface/datasets/issues/395 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/395/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/395/comments | https://api.github.com/repos/huggingface/datasets/issues/395/events | https://github.com/huggingface/datasets/issues/395 | 657,454,983 | MDU6SXNzdWU2NTc0NTQ5ODM= | 395 | Memory issue when doing select | {
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} | As noticed in #389, the following code loads the entire wikipedia in memory.
```python
import nlp
w = nlp.load_dataset("wikipedia", "20200501.en", split="train")
w.select([0])
```
This is caused by [this line](https://github.com/huggingface/nlp/blob/master/src/nlp/arrow_dataset.py#L626) for some reason, that ... | {
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https://api.github.com/repos/huggingface/datasets/issues/394 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/394/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/394/comments | https://api.github.com/repos/huggingface/datasets/issues/394/events | https://github.com/huggingface/datasets/pull/394 | 657,425,548 | MDExOlB1bGxSZXF1ZXN0NDQ5NTQzNTE0 | 394 | Remove remaining nested dict | {
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#378 | {
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https://api.github.com/repos/huggingface/datasets/issues/393 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/393/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/393/comments | https://api.github.com/repos/huggingface/datasets/issues/393/events | https://github.com/huggingface/datasets/pull/393 | 657,330,911 | MDExOlB1bGxSZXF1ZXN0NDQ5NDY1MTAz | 393 | Fix extracted files directory for the DownloadManager | {
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For downloaded files, we are using the `downloads` directory to make things easier to navigate, but extracted files were still placed at the root of the cache directory. To fix that I changed the directory for extracted files to ca... | {
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https://api.github.com/repos/huggingface/datasets/issues/392 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/392/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/392/comments | https://api.github.com/repos/huggingface/datasets/issues/392/events | https://github.com/huggingface/datasets/pull/392 | 657,313,738 | MDExOlB1bGxSZXF1ZXN0NDQ5NDUwOTkx | 392 | Style change detection | {
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- There's the possibility of adding the [PAN19](https://zenodo.org/record/3577602) and PAN18 style change detection tasks too (these are datasets whose labels... | {
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https://api.github.com/repos/huggingface/datasets/issues/390 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/390/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/390/comments | https://api.github.com/repos/huggingface/datasets/issues/390/events | https://github.com/huggingface/datasets/pull/390 | 656,956,384 | MDExOlB1bGxSZXF1ZXN0NDQ5MTYxMzY3 | 390 | Concatenate datasets | {
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This would also be useful if someone wants to pretrain on a large generic dataset + their own custom dataset. Not in... | {
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https://api.github.com/repos/huggingface/datasets/issues/389 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/389/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/389/comments | https://api.github.com/repos/huggingface/datasets/issues/389/events | https://github.com/huggingface/datasets/pull/389 | 656,921,768 | MDExOlB1bGxSZXF1ZXN0NDQ5MTMyOTU5 | 389 | Fix pickling of SplitDict | {
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```
wiki = nlp.load_dataset('wikipedia', split='train')
def sentencize(examples):
...
wiki = wiki.map(sentencize, batched=True)
torch.save(wiki, '... | {
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} | 1. I try downloading `wmt14`, `wmt15`, `wmt17`, `wmt19` with the following code:
```
nlp.load_dataset('wmt14','de-en')
nlp.load_dataset('wmt15','de-en')
nlp.load_dataset('wmt17','de-en')
nlp.load_dataset('wmt19','de-en')
```
The code runs but the download speed is **extremely slow**, the same behaviour is not ob... | {
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https://api.github.com/repos/huggingface/datasets/issues/387 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/387/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/387/comments | https://api.github.com/repos/huggingface/datasets/issues/387/events | https://github.com/huggingface/datasets/issues/387 | 656,361,357 | MDU6SXNzdWU2NTYzNjEzNTc= | 387 | Conversion through to_pandas output numpy arrays for lists instead of python objects | {
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} | In a related question, the conversion through to_pandas output numpy arrays for the lists instead of python objects.
Here is an example:
```python
>>> dataset._data.slice(key, 1).to_pandas().to_dict("list")
{'sentence1': ['Amrozi accused his brother , whom he called " the witness " , of deliberately distorting hi... | {
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https://api.github.com/repos/huggingface/datasets/issues/386 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/386/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/386/comments | https://api.github.com/repos/huggingface/datasets/issues/386/events | https://github.com/huggingface/datasets/pull/386 | 655,839,067 | MDExOlB1bGxSZXF1ZXN0NDQ4MjQ1NDI4 | 386 | Update dataset loading and features - Add TREC dataset | {
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- add a template for a new dataset script
- update the caching structure so that the path to the cached data files is also a function of the dataset loading script hash. This way when you update a loading script the data will be automatically updated instead of falling back to the previous version (which is ... | {
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https://api.github.com/repos/huggingface/datasets/issues/385 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/385/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/385/comments | https://api.github.com/repos/huggingface/datasets/issues/385/events | https://github.com/huggingface/datasets/pull/385 | 655,663,997 | MDExOlB1bGxSZXF1ZXN0NDQ4MTAzMjY5 | 385 | Remove unnecessary nested dict | {
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- MLQA
- RACE
Will be adding more if necessary.
#378 | {
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https://api.github.com/repos/huggingface/datasets/issues/383 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/383/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/383/comments | https://api.github.com/repos/huggingface/datasets/issues/383/events | https://github.com/huggingface/datasets/pull/383 | 655,291,201 | MDExOlB1bGxSZXF1ZXN0NDQ3ODI0OTky | 383 | Adding the Linguistic Code-switching Evaluation (LinCE) benchmark | {
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First of all, this library is really cool! Thanks for putting all of this together!
This PR contains the [Linguistic Code-switching Evaluation (LinCE) benchmark](https://ritual.uh.edu/lince). As described in the official website (FAQ):
> 1. Why do we need LinCE?
>LinCE brings 10 code-switching datasets t... | {
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https://api.github.com/repos/huggingface/datasets/issues/378 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/378/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/378/comments | https://api.github.com/repos/huggingface/datasets/issues/378/events | https://github.com/huggingface/datasets/issues/378 | 655,226,316 | MDU6SXNzdWU2NTUyMjYzMTY= | 378 | [dataset] Structure of MLQA seems unecessary nested | {
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} | The features of the MLQA dataset comprise several nested dictionaries with a single element inside (for `questions` and `ids`): https://github.com/huggingface/nlp/blob/master/datasets/mlqa/mlqa.py#L90-L97
Should we keep this @mariamabarham @patrickvonplaten? Was this added for compatibility with tfds?
```python
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https://api.github.com/repos/huggingface/datasets/issues/377 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/377/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/377/comments | https://api.github.com/repos/huggingface/datasets/issues/377/events | https://github.com/huggingface/datasets/issues/377 | 655,215,790 | MDU6SXNzdWU2NTUyMTU3OTA= | 377 | Iyy!!! | {
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https://api.github.com/repos/huggingface/datasets/issues/376 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/376/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/376/comments | https://api.github.com/repos/huggingface/datasets/issues/376/events | https://github.com/huggingface/datasets/issues/376 | 655,047,826 | MDU6SXNzdWU2NTUwNDc4MjY= | 376 | to_pandas conversion doesn't always work | {
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} | For some complex nested types, the conversion from Arrow to python dict through pandas doesn't seem to be possible.
Here is an example using the official SQUAD v2 JSON file.
This example was found while investigating #373.
```python
>>> squad = load_dataset('json', data_files={nlp.Split.TRAIN: ["./train-v2.0.... | {
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https://api.github.com/repos/huggingface/datasets/issues/375 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/375/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/375/comments | https://api.github.com/repos/huggingface/datasets/issues/375/events | https://github.com/huggingface/datasets/issues/375 | 655,023,307 | MDU6SXNzdWU2NTUwMjMzMDc= | 375 | TypeError when computing bertscore | {
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I installed nlp 0.3.0 via pip, and my python version is 3.7.
When I tried to compute bertscore with the code:
```
import nlp
bertscore = nlp.load_metric('bertscore')
# load hyps and refs
...
print (bertscore.compute(hyps, refs, lang='en'))
```
I got the following error.
```
Traceback (most rece... | {
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https://api.github.com/repos/huggingface/datasets/issues/374 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/374/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/374/comments | https://api.github.com/repos/huggingface/datasets/issues/374/events | https://github.com/huggingface/datasets/pull/374 | 654,895,066 | MDExOlB1bGxSZXF1ZXN0NDQ3NTMxMzUy | 374 | Add dataset post processing for faiss indexes | {
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Now that we can have datasets with embeddings (see `wiki_pr` for example), we can allow users to load the dataset + get the Faiss index that comes with it to do nearest neighbors queries.
## Implementation proposition
- Faiss indexes have to be added to the `nlp.... | {
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```
dataset = nlp.load_dataset('json', data_files={nlp.Split.TRAIN: ["./datasets/train-v2.0.json"]}, f... | {
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Fix https://github.com/huggingface/nlp/issues/369
JSON script now can accept JSON files containing a single dict with the records as a list in one attribute to the dict (previously it only accepted JSON files containing records as rows of dicts in the file).
In t... | {
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https://api.github.com/repos/huggingface/datasets/issues/371 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/371/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/371/comments | https://api.github.com/repos/huggingface/datasets/issues/371/events | https://github.com/huggingface/datasets/pull/371 | 654,668,242 | MDExOlB1bGxSZXF1ZXN0NDQ3MzQ4NDgw | 371 | Fix cached file path for metrics with different config names | {
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It should fix #368 | {
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https://api.github.com/repos/huggingface/datasets/issues/369 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/369/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/369/comments | https://api.github.com/repos/huggingface/datasets/issues/369/events | https://github.com/huggingface/datasets/issues/369 | 654,186,890 | MDU6SXNzdWU2NTQxODY4OTA= | 369 | can't load local dataset: pyarrow.lib.ArrowInvalid: straddling object straddles two block boundaries | {
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} | Trying to load a local SQuAD-formatted dataset (from a JSON file, about 60MB):
```
dataset = nlp.load_dataset(path='json', data_files={nlp.Split.TRAIN: ["./path/to/file.json"]})
```
causes
```
Traceback (most recent call last):
File "dataloader.py", line 9, in <module>
["./path/to/file.json"]})
File "/... | {
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https://api.github.com/repos/huggingface/datasets/issues/368 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/368/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/368/comments | https://api.github.com/repos/huggingface/datasets/issues/368/events | https://github.com/huggingface/datasets/issues/368 | 654,087,251 | MDU6SXNzdWU2NTQwODcyNTE= | 368 | load_metric can't acquire lock anymore | {
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} | I can't load metric (glue) anymore after an error in a previous run. I even removed the whole cache folder `/home/XXX/.cache/huggingface/`, and the issue persisted. What are the steps to fix this?
Traceback (most recent call last):
File "/home/XXX/miniconda3/envs/ML-DL-py-3.7/lib/python3.7/site-packages/n... | {
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Implementation Notes:
- I used the original version provided on the quora website. There's also a [Kaggle competition](https://www.kaggle.com/c/quora-question-pairs) which has a nice train/test sp... | {
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https://api.github.com/repos/huggingface/datasets/issues/365 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/365/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/365/comments | https://api.github.com/repos/huggingface/datasets/issues/365/events | https://github.com/huggingface/datasets/issues/365 | 653,845,964 | MDU6SXNzdWU2NTM4NDU5NjQ= | 365 | How to augment data ? | {
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For now my work-around is to use batched map, like this :
```python
def aug(samples):
# Simply copy the existing data to have x2 amount of data
for k, v in samples.items():
samples[k].extend(v)
return samples
dataset = dataset.map(aug, batched=T... | {
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- Passage and Document Retrieval
- Keyphrase Extraction
- QA and NLG
This PR only adds the 2 versions of the QA and NLG task dataset which was realeased with the original paper here https://arxiv.org/pd... | {
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https://api.github.com/repos/huggingface/datasets/issues/363 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/363/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/363/comments | https://api.github.com/repos/huggingface/datasets/issues/363/events | https://github.com/huggingface/datasets/pull/363 | 653,821,172 | MDExOlB1bGxSZXF1ZXN0NDQ2NjY0NDIy | 363 | Adding support for generic multi dimensional tensors and auxillary image data for multimodal datasets | {
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The main factory class is MultiArray, every single time this class is called, a corresponding pyarrow extension array and type class is generated (and added to the list of globals for future use) for a given root data type and set of dimensions/shape. I provide examples on working with this in datas... | {
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https://api.github.com/repos/huggingface/datasets/issues/362 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/362/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/362/comments | https://api.github.com/repos/huggingface/datasets/issues/362/events | https://github.com/huggingface/datasets/issues/362 | 653,766,245 | MDU6SXNzdWU2NTM3NjYyNDU= | 362 | [dateset subset missing] xtreme paws-x | {
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} | I tried nlp.load_dataset('xtreme', 'PAWS-X.es') but get the value error
It turns out that the subset for Spanish is missing
https://github.com/google-research-datasets/paws/tree/master/pawsx | {
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https://api.github.com/repos/huggingface/datasets/issues/361 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/361/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/361/comments | https://api.github.com/repos/huggingface/datasets/issues/361/events | https://github.com/huggingface/datasets/issues/361 | 653,757,376 | MDU6SXNzdWU2NTM3NTczNzY= | 361 | 🐛 [Metrics] ROUGE is non-deterministic | {
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} | If I run the ROUGE metric 2 times, with same predictions / references, the scores are slightly different.
Refer to [this Colab notebook](https://colab.research.google.com/drive/1wRssNXgb9ldcp4ulwj-hMJn0ywhDOiDy?usp=sharing) for reproducing the problem.
Example of F-score for ROUGE-1, ROUGE-2, ROUGE-L in 2 differe... | {
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