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https://api.github.com/repos/huggingface/datasets/issues/574 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/574/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/574/comments | https://api.github.com/repos/huggingface/datasets/issues/574/events | https://github.com/huggingface/datasets/pull/574 | 693,364,853 | MDExOlB1bGxSZXF1ZXN0NDc5ODU5NzQy | 574 | Add modules cache | {
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"merged_at": "2020-09-07T09:01:35"... | As discusses in #554 , we should use a module cache directory outside of the python packages directory since we may not have write permissions.
I added a new HF_MODULES_PATH directory that is added to the python path when doing `import nlp`.
In this directory, a module `nlp_modules` is created so that datasets can ... | {
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"merged_at": "2020-09-04T12:53:23"... | As mentioned in #546 and #548 , hashing `data_files` contents to get the cache directory name for a text dataset can take a long time.
To make it faster I changed the hashing so that it takes into account the `path` and the `last modified timestamp` of each data file, instead of iterating through the content of each... | {
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"merged_at": "2020-09-07T07:46:07"... | I added `save` and `load` method to serialize/deserialize a dataset object in a folder.
It moves the arrow files there (or write them if the tables were in memory), and saves the pickle state in a json file `state.json`, except the info that are in a separate file `dataset_info.json`.
Example:
```python
import ... | {
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"merged_at": "2020-09-03T10:07:12"... | Reverts huggingface/nlp#471 | {
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https://api.github.com/repos/huggingface/datasets/issues/568 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/568/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/568/comments | https://api.github.com/repos/huggingface/datasets/issues/568/events | https://github.com/huggingface/datasets/issues/568 | 691,638,656 | MDU6SXNzdWU2OTE2Mzg2NTY= | 568 | `metric.compute` throws `ArrowInvalid` error | {
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```
File "/home/beltagy/trainer.py", line 92, in validation_step
rouge_scores = rouge.compute(predictions=generated_str, references=gold_st... | {
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"merged_at": "2020-09-03T16:31:52"... | A `logger` objects are not picklable in google colab, contrary to `logger` objects in jupyter notebooks or in python shells.
It creates some issues in google colab right now.
Indeed by calling any `Dataset` method, the fingerprint update pickles the transform function, and as the logger comes with it, it results in... | {
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```
>>> import nlp
2020-09-02 13:47:09.210310: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic l... | {
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"merged_at": "2020-09-09T09:13:22"... | There were CI bugs where a distributed metric would try to read all the files in process 0 while the other processes haven't started writing.
To fix that I added a custom locking mechanism that waits for the file to exist before trying to read it | {
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"merged_at": "2020-09-09T09:03:32"... | Various improvements to speed-up creation and processing of large scale datasets.
Currently:
- distributed downloads
- remove etag from datafiles hashes to spare a request when restarting a failed download | {
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} | Repurpose the `version` attribute in datasets and metrics to let the user pin a specific version of datasets and metric scripts:
```
dataset = nlp.load_dataset('squad', version='1.0.0')
metric = nlp.load_metric('squad', version='1.0.0')
```
Notes:
- version number are the release version of the library
- curre... | {
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Ubuntu 18.04
Python 3.6.8
nlp 0.4.0
## Description
Loading `imdb` dataset works fine when when I don't specify any `download_config` argument. When I create a custom `DownloadConfig` object and pass it to the `nlp.load_dataset` function, this results in an error.
## How to reprodu... | {
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"merged_at": "2020-09-04T18:05:47"... | This adds Wikipedia pre-processed for KILT, as well as the task data. Only the question IDs are provided for TriviaQA, but they can easily be mapped back with:
```
import nlp
kilt_wikipedia = nlp.load_dataset('kilt_wikipedia')
kilt_tasks = nlp.load_dataset('kilt_tasks')
triviaqa = nlp.load_dataset('trivia_qa',... | {
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"merged_at": "2020-09-01T17:24:50"... | Hopefully it fixes the github actions | {
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"merged_at": "2020-09-03T15:38:39"... | http://yanran.li/dailydialog.html
https://arxiv.org/pdf/1710.03957.pdf
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```>>> import nlp
>>> squad_dataset = nlp.load_dataset('squad')
... | {
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"merged_at": "2020-09-02T10:01:25"... | Adding multiprocessing to `.map`
It works in 3 steps:
- shard the dataset in `num_proc` shards
- spawn one process per shard and call `map` on them
- concatenate the resulting datasets
Example of usage:
```python
from nlp import load_dataset
dataset = load_dataset("squad", split="train")
def function... | {
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"merged_at": "2020-09-03T09:06:01"... | Hi,
I have added the updated `dataset_infos.json` file for the LinCE benchmark. This update is to fix the mismatched checksum bug #539 for one of the datasets in the LinCE benchmark. To update the file, I run this command from the nlp root directory:
```
python nlp-cli test ./datasets/lince --save_infos --all_co... | {
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} | Bleurt started throwing an error in some code we have.
This looks like the fix but...
It's also unnerving that even a prebuilt docker image with pinned versions can be working 1 day and then fail the next (especially for production systems).
Any way for us to pin your metrics code so that they are guaranteed not... | {
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"merged_at": "2020-09-08T10:19:57"... | 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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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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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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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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"merged_at": "2020-08-31T09:49:19"... | Update the Quick Tour documentation in order to add the TensorFlow equivalent source code for the classification example. Now it is possible to select either the code in PyTorch or in TensorFlow in the Quick tour. | {
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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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"merged_at": "2020-09-18T11:42:20"... | 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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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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"merged_at": "2020-08-31T11:42:50"... | Add a `nlp.logging` module to set the global logging level easily. The verbosity level also controls the tqdm bars (disabled when set higher than INFO).
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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] | closed | false | null | [] | null | 9 | 2020-08-27T23:58:16 | 2020-09-18T12:07:04 | 2020-09-18T12:07:04 | CONTRIBUTOR | null | null | 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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"merged_at": "2020-08-31T14:20:39"... | 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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"merged_at": "2020-08-27T08:39:59"... | Adding some benchmarks with DVC/CML
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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`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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"merged_at": "2020-08-26T08:02:23"... | It should fix the CI problems in #513 | {
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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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"merged_at": "2020-08-24T19:22:25"... | 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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"merged_at": "2020-08-26T08:04:10"... | 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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"merged_at": "2020-08-25T09:04:03"... | fix #524 | {
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"merged_at": "2020-08-25T09:20:44"... | As noticed in #470, #474, #476, #504 , the slow test `test_load_real_dataset` couldn't run on datasets that require config parameters.
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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```
import nlp
nlp.load_dataset('wmt16', 'de-en')
```
Downloads at 49.1 K... | {
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"merged_at": "2020-08-24T08:54:14"... | 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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Fixed in this pr:
https://github.com/huggingface/nlp/pull/521 | {
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"merged_at": "2020-08-20T07:52:04"... | This error happens many times I'm thinking maybe its spelled like this on purpose? | {
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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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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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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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"merged_at": "2020-08-20T20:30:42"... | If you had a dataset formatted as numpy for example, and tried to do a batched map, then it would crash because one of the elements from the inputs was missing for unchanged columns (ex: batch of length 999 instead of 1000).
The happened during the creation of the `pa.Table`, since columns had different lengths. | {
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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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"merged_at": "2020-08-28T08:41:50"... | 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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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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Th... | {
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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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```
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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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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"merged_at": "2020-08-17T11:24:38"... | As noticed in #505 , giving a function that doesn't return anything in `.map` raises an error because of an unreferenced variable.
I fixed that and added tests.
Thanks @avloss for reporting | {
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"merged_at": "2020-08-27T08:18:41"... | 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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"merged_at": "2020-08-19T13:37:17"... | 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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```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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} | 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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"merged_at": "2020-08-14T13:17:20"... | If the cache dir is local, then we shouldn't use beam's filesystem to save the dataset info
Fix #490
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"merged_at": "2020-08-19T09:50:01"... | This should fix #485
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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"merged_at": "2020-08-14T13:29:34"... | When writing an arrow file and inferring the features, the overflow check could fail if the first example had a `null` field.
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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"merged_at": "2020-08-12T09:30:48"... | When the format of a dataset is set to pytorch or tensorflow, and if the dataset has vectors in it, they were not stacked together as tensors when calling `dataset[i:i + batch_size][column]` or `dataset[column]`.
I added support for stacked tensors for both pytorch and tensorflow.
For ragged tensors, they are stack... | {
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"merged_at": "2020-08-11T13:49:52"... | 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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```
wget https://stuncorpusprod.blob.core.windows.net/corpusfiles/UNv1.0.en-zh.tar.gz.00
```
runs in 2 minutes. | {
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```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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`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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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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```
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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"merged_at": "2020-08-31T10:42:46"... | 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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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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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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"merged_at": "2020-08-20T08:16:08"... | ## 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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} | 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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"merged_at": "2020-08-19T13:39:09"... | 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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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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---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-5-48907f2ad433> in <module>
----> 1 features = {x: trai... | {
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https://api.github.com/repos/huggingface/datasets/issues/476 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/476/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/476/comments | https://api.github.com/repos/huggingface/datasets/issues/476/events | https://github.com/huggingface/datasets/pull/476 | 672,991,854 | MDExOlB1bGxSZXF1ZXN0NDYyOTMyMTgx | 476 | CheckList | {
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} | 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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https://api.github.com/repos/huggingface/datasets/issues/475 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/475/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/475/comments | https://api.github.com/repos/huggingface/datasets/issues/475/events | https://github.com/huggingface/datasets/pull/475 | 672,884,595 | MDExOlB1bGxSZXF1ZXN0NDYyODQzMzQz | 475 | misc. bugs and quality of life | {
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"merged_at": "2020-08-17T21:14:07"... | 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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