# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # # NOTE: This is a modified version of https://github.com/huggingface/datasets/blob/master/datasets/wikitext/wikitext.py # that returns Wiki pages instead of Wiki text line-by-line. """WikiText Dataset.""" import os import datasets _CITATION = """\ @misc{merity2016pointer, title={Pointer Sentinel Mixture Models}, author={Stephen Merity and Caiming Xiong and James Bradbury and Richard Socher}, year={2016}, eprint={1609.07843}, archivePrefix={arXiv}, primaryClass={cs.CL} } """ _DESCRIPTION = """\ The WikiText language modeling dataset is a collection of over 100 million tokens extracted from the set of verified Good and Featured articles on Wikipedia. The dataset is available under the Creative Commons Attribution-ShareAlike License. """ _HOMEPAGE = "https://blog.einstein.ai/the-wikitext-long-term-dependency-language-modeling-dataset/" _LICENSE = "Creative Commons Attribution-ShareAlike 4.0 International (CC BY-SA 4.0)" _DATA_URL = "https://wikitext.smerity.com" class WikitextConfig(datasets.BuilderConfig): """BuilderConfig for GLUE.""" def __init__(self, data_url, **kwargs): """BuilderConfig for Wikitext Args: data_url: `string`, url to the dataset (word or raw level) **kwargs: keyword arguments forwarded to super. """ super(WikitextConfig, self).__init__( version=datasets.Version( "1.0.0", ), **kwargs, ) self.data_url = data_url class Wikitext(datasets.GeneratorBasedBuilder): """TODO(wikitext_103): Short description of my dataset.""" # TODO(wikitext_103): Set up version. VERSION = datasets.Version("0.1.0") BUILDER_CONFIGS = [ WikitextConfig( name="wikitext-103-v1", data_url=_DATA_URL + "/" + "wikitext-103-v1.zip", description="Word level dataset. No processing is needed other than replacing newlines with tokens.", ), WikitextConfig( name="wikitext-2-v1", data_url=_DATA_URL + "/" + "wikitext-2-v1.zip", description="Word level dataset. No processing is needed other than replacing newlines with tokens.", ), WikitextConfig( name="wikitext-103-raw-v1", data_url=_DATA_URL + "/" + "wikitext-103-raw-v1.zip", description="Raw level dataset: the raw tokens before the addition of tokens. " "They should only be used for character level work or for creating newly derived datasets.", ), WikitextConfig( name="wikitext-2-raw-v1", data_url=_DATA_URL + "/" + "wikitext-2-raw-v1.zip", description="Raw level dataset: the raw tokens before the addition of tokens. " "They should only be used for character level work or for creating newly derived datasets.", ), ] def _info(self): # TODO(wikitext): Specifies the datasets.DatasetInfo object return datasets.DatasetInfo( # This is the description that will appear on the datasets page. description=_DESCRIPTION, # datasets.features.FeatureConnectors features=datasets.Features( { "page": datasets.Value("string") # These are the features of your dataset like images, labels ... } ), # If there's a common (input, target) tuple from the features, # specify them here. They'll be used if as_supervised=True in # builder.as_dataset. supervised_keys=None, homepage=_HOMEPAGE, license=_LICENSE, citation=_CITATION, ) def _split_generators(self, dl_manager): """Returns SplitGenerators.""" # TODO(wikitext): Downloads the data and defines the splits # dl_manager is a datasets.download.DownloadManager that can be used to # download and extract URLs if self.config.name == "wikitext-103-v1": data_file = dl_manager.download_and_extract(self.config.data_url) data_dir = os.path.join(data_file, "wikitext-103") return [ datasets.SplitGenerator( name=datasets.Split.TEST, gen_kwargs={ "data_file": os.path.join(data_dir, "wiki.test.tokens"), "split": "test", }, ), datasets.SplitGenerator( name=datasets.Split.TRAIN, gen_kwargs={ "data_file": os.path.join(data_dir, "wiki.train.tokens"), "split": "train", }, ), datasets.SplitGenerator( name=datasets.Split.VALIDATION, gen_kwargs={ "data_file": os.path.join(data_dir, "wiki.valid.tokens"), "split": "valid", }, ), ] else: if self.config.name == "wikitext-103-raw-v1": data_file = dl_manager.download_and_extract(self.config.data_url) data_dir = os.path.join(data_file, "wikitext-103-raw") return [ datasets.SplitGenerator( name=datasets.Split.TEST, gen_kwargs={ "data_file": os.path.join(data_dir, "wiki.test.raw"), "split": "test", }, ), datasets.SplitGenerator( name=datasets.Split.TRAIN, gen_kwargs={ "data_file": os.path.join(data_dir, "wiki.train.raw"), "split": "train", }, ), datasets.SplitGenerator( name=datasets.Split.VALIDATION, gen_kwargs={ "data_file": os.path.join(data_dir, "wiki.valid.raw"), "split": "valid", }, ), ] else: if self.config.name == "wikitext-2-raw-v1": data_file = dl_manager.download_and_extract(self.config.data_url) data_dir = os.path.join(data_file, "wikitext-2-raw") return [ datasets.SplitGenerator( name=datasets.Split.TEST, gen_kwargs={ "data_file": os.path.join(data_dir, "wiki.test.raw"), "split": "test", }, ), datasets.SplitGenerator( name=datasets.Split.TRAIN, gen_kwargs={ "data_file": os.path.join(data_dir, "wiki.train.raw"), "split": "train", }, ), datasets.SplitGenerator( name=datasets.Split.VALIDATION, gen_kwargs={ "data_file": os.path.join(data_dir, "wiki.valid.raw"), "split": "valid", }, ), ] else: if self.config.name == "wikitext-2-v1": data_file = dl_manager.download_and_extract( self.config.data_url ) data_dir = os.path.join(data_file, "wikitext-2") return [ datasets.SplitGenerator( name=datasets.Split.TEST, gen_kwargs={ "data_file": os.path.join( data_dir, "wiki.test.tokens" ), "split": "test", }, ), datasets.SplitGenerator( name=datasets.Split.TRAIN, gen_kwargs={ "data_file": os.path.join( data_dir, "wiki.train.tokens" ), "split": "train", }, ), datasets.SplitGenerator( name=datasets.Split.VALIDATION, gen_kwargs={ "data_file": os.path.join( data_dir, "wiki.valid.tokens" ), "split": "valid", }, ), ] def _generate_examples(self, data_file, split): """Yields examples.""" with open(data_file, encoding="utf-8") as f: key = 0 ret = [] data = f.read().split("\n") for line in data: rline = line.replace("= = =", "===").replace("= =", "==").strip() if rline.startswith("= ") and rline.strip().endswith(" ="): page = "\n".join(ret) if page.strip(): yield key, {"page": page} key += 1 ret = [] ret.append(line) page = "\n".join(ret) yield key, {"page": page}