Convert to Parquet format and remove loading script

#4
by elie-mada - opened
README.md CHANGED
@@ -22,11 +22,20 @@ task_ids:
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  - masked-language-modeling
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  paperswithcode_id: null
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  pretty_name: Penn Treebank
 
 
 
 
 
 
 
 
 
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  dataset_info:
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  features:
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  - name: sentence
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  dtype: string
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- config_name: penn_treebank
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  splits:
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  - name: train
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  num_bytes: 5143706
@@ -80,7 +89,7 @@ dataset_info:
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  ### Dataset Summary
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- This is the Penn Treebank Project: Release 2 CDROM, featuring a million words of 1989 Wall Street Journal material.
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  The rare words in this version are already replaced with <unk> token. The numbers are replaced with <N> token.
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  ### Supported Tasks and Leaderboards
@@ -95,15 +104,23 @@ The text in the dataset is in American English
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  ### Data Instances
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- [Needs More Information]
 
 
 
 
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  ### Data Fields
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- [Needs More Information]
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  ### Data Splits
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- [Needs More Information]
 
 
 
 
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  ## Dataset Creation
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@@ -161,6 +178,7 @@ Dataset provided for research purposes only. Please check dataset license for ad
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  ### Citation Information
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  @article{marcus-etal-1993-building,
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  title = "Building a Large Annotated Corpus of {E}nglish: The {P}enn {T}reebank",
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  author = "Marcus, Mitchell P. and
@@ -173,6 +191,8 @@ Dataset provided for research purposes only. Please check dataset license for ad
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  url = "https://www.aclweb.org/anthology/J93-2004",
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  pages = "313--330",
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  }
 
 
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  ### Contributions
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- Thanks to [@harshalmittal4](https://github.com/harshalmittal4) for adding this dataset.
 
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  - masked-language-modeling
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  paperswithcode_id: null
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  pretty_name: Penn Treebank
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+ configs:
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+ - config_name: default
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+ data_files:
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+ - split: train
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+ path: data/train-*
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+ - split: test
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+ path: data/test-*
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+ - split: validation
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+ path: data/validation-*
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  dataset_info:
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  features:
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  - name: sentence
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  dtype: string
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+ config_name: default
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  splits:
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  - name: train
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  num_bytes: 5143706
 
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  ### Dataset Summary
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+ This is the Penn Treebank Project: Release 2 CDROM, featuring a million words of 1989 Wall Street Journal material.
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  The rare words in this version are already replaced with <unk> token. The numbers are replaced with <N> token.
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  ### Supported Tasks and Leaderboards
 
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  ### Data Instances
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+ An example instance:
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+
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+ ```json
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+ {"sentence": "pierre <unk> N years old will join the board as a nonexecutive director nov. N"}
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+ ```
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  ### Data Fields
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+ - `sentence` (string): A sentence from the Wall Street Journal corpus with rare words replaced by `<unk>` and numbers by `<N>`.
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  ### Data Splits
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+ | Split | Examples |
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+ |------------|----------|
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+ | train | 42,068 |
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+ | test | 3,761 |
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+ | validation | 3,370 |
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  ## Dataset Creation
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  ### Citation Information
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+ ```bibtex
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  @article{marcus-etal-1993-building,
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  title = "Building a Large Annotated Corpus of {E}nglish: The {P}enn {T}reebank",
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  author = "Marcus, Mitchell P. and
 
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  url = "https://www.aclweb.org/anthology/J93-2004",
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  pages = "313--330",
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  }
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+ ```
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+
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  ### Contributions
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+ Thanks to [@harshalmittal4](https://github.com/harshalmittal4) for adding this dataset.
data/test-00000-of-00001.parquet ADDED
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data/validation-00000-of-00001.parquet ADDED
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+ size 232009
ptb_text_only.py DELETED
@@ -1,146 +0,0 @@
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- # coding=utf-8
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- # Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
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- #
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- # Licensed under the Apache License, Version 2.0 (the "License");
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- # you may not use this file except in compliance with the License.
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- # You may obtain a copy of the License at
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- #
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- # http://www.apache.org/licenses/LICENSE-2.0
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- #
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- # Unless required by applicable law or agreed to in writing, software
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- # distributed under the License is distributed on an "AS IS" BASIS,
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- # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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- # See the License for the specific language governing permissions and
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- # limitations under the License.
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- """
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- Load the Penn Treebank dataset.
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-
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- This is the Penn Treebank Project: Release 2 CDROM, featuring a million words of 1989 Wall
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- Street Journal material.
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- """
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-
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-
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- import datasets
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-
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-
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- # TODO: Add BibTeX citation
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- # Find for instance the citation on arxiv or on the dataset repo/website
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- _CITATION = """\
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- @article{marcus-etal-1993-building,
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- title = "Building a Large Annotated Corpus of {E}nglish: The {P}enn {T}reebank",
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- author = "Marcus, Mitchell P. and
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- Santorini, Beatrice and
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- Marcinkiewicz, Mary Ann",
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- journal = "Computational Linguistics",
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- volume = "19",
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- number = "2",
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- year = "1993",
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- url = "https://www.aclweb.org/anthology/J93-2004",
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- pages = "313--330",
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- }
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- """
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-
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- # TODO: Add description of the dataset here
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- # You can copy an official description
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- _DESCRIPTION = """\
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- This is the Penn Treebank Project: Release 2 CDROM, featuring a million words of 1989 Wall Street Journal material. This corpus has been annotated for part-of-speech (POS) information. In addition, over half of it has been annotated for skeletal syntactic structure.
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- """
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-
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- # TODO: Add a link to an official homepage for the dataset here
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- _HOMEPAGE = "https://catalog.ldc.upenn.edu/LDC99T42"
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-
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- # TODO: Add the licence for the dataset here if you can find it
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- _LICENSE = "LDC User Agreement for Non-Members"
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-
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- # TODO: Add link to the official dataset URLs here
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- # The HuggingFace dataset library don't host the datasets but only point to the original files
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- # This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)
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- _URL = "https://raw.githubusercontent.com/wojzaremba/lstm/master/data/"
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- _TRAINING_FILE = "ptb.train.txt"
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- _DEV_FILE = "ptb.valid.txt"
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- _TEST_FILE = "ptb.test.txt"
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-
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-
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- class PtbTextOnlyConfig(datasets.BuilderConfig):
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- """BuilderConfig for PtbTextOnly"""
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-
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- def __init__(self, **kwargs):
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- """BuilderConfig PtbTextOnly.
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- Args:
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- **kwargs: keyword arguments forwarded to super.
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- """
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- super(PtbTextOnlyConfig, self).__init__(**kwargs)
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-
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-
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- class PtbTextOnly(datasets.GeneratorBasedBuilder):
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- """Load the Penn Treebank dataset."""
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-
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- VERSION = datasets.Version("1.1.0")
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-
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- # This is an example of a dataset with multiple configurations.
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- # If you don't want/need to define several sub-sets in your dataset,
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- # just remove the BUILDER_CONFIG_CLASS and the BUILDER_CONFIGS attributes.
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-
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- # If you need to make complex sub-parts in the datasets with configurable options
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- # You can create your own builder configuration class to store attribute, inheriting from datasets.BuilderConfig
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- # BUILDER_CONFIG_CLASS = MyBuilderConfig
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-
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- # You will be able to load one or the other configurations in the following list with
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- # data = datasets.load_dataset('my_dataset', 'first_domain')
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- # data = datasets.load_dataset('my_dataset', 'second_domain')
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- BUILDER_CONFIGS = [
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- PtbTextOnlyConfig(
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- name="penn_treebank",
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- version=VERSION,
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- description="Load the Penn Treebank dataset",
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- ),
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- ]
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-
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- def _info(self):
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- features = datasets.Features({"sentence": datasets.Value("string")})
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- return datasets.DatasetInfo(
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- # This is the description that will appear on the datasets page.
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- description=_DESCRIPTION,
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- # This defines the different columns of the dataset and their types
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- features=features, # Here we define them above because they are different between the two configurations
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- # If there's a common (input, target) tuple from the features,
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- # specify them here. They'll be used if as_supervised=True in
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- # builder.as_dataset.
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- supervised_keys=None,
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- # Homepage of the dataset for documentation
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- homepage=_HOMEPAGE,
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- # License for the dataset if available
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- license=_LICENSE,
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- # Citation for the dataset
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- citation=_CITATION,
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- )
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-
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- def _split_generators(self, dl_manager):
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- """Returns SplitGenerators."""
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- # TODO: This method is tasked with downloading/extracting the data and defining the splits depending on the configuration
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- # If several configurations are possible (listed in BUILDER_CONFIGS), the configuration selected by the user is in self.config.name
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-
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- # dl_manager is a datasets.download.DownloadManager that can be used to download and extract URLs
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- # It can accept any type or nested list/dict and will give back the same structure with the url replaced with path to local files.
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- # By default the archives will be extracted and a path to a cached folder where they are extracted is returned instead of the archive
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- my_urls = {
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- "train": f"{_URL}{_TRAINING_FILE}",
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- "dev": f"{_URL}{_DEV_FILE}",
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- "test": f"{_URL}{_TEST_FILE}",
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- }
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- data_dir = dl_manager.download_and_extract(my_urls)
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- return [
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- datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": data_dir["train"]}),
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- datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": data_dir["test"]}),
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- datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": data_dir["dev"]}),
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- ]
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-
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- def _generate_examples(self, filepath):
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- """Yields examples."""
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- # TODO: This method will receive as arguments the `gen_kwargs` defined in the previous `_split_generators` method.
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- # It is in charge of opening the given file and yielding (key, example) tuples from the dataset
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- # The key is not important, it's more here for legacy reason (legacy from tfds)
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- with open(filepath, encoding="utf-8") as f:
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- for id_, line in enumerate(f):
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- line = line.strip()
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- yield id_, {"sentence": line}