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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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- """Children's Book Test Dataset."""
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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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- _CITATION = """\
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- @misc{hill2016goldilocks,
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- title={The Goldilocks Principle: Reading Children's Books with Explicit Memory Representations},
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- author={Felix Hill and Antoine Bordes and Sumit Chopra and Jason Weston},
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- year={2016},
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- eprint={1511.02301},
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- archivePrefix={arXiv},
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- primaryClass={cs.CL}
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- }
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- """
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-
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-
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- _DESCRIPTION = """\
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- The Children’s Book Test (CBT) is designed to measure directly
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- how well language models can exploit wider linguistic context.
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- The CBT is built from books that are freely available.
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- """
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-
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- _HOMEPAGE = "https://research.fb.com/downloads/babi/"
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-
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- _LICENSE = """GNU Free Documentation License v1.3"""
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-
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- ZIP_URL = "data/CBTest.tgz"
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- dir = "CBTest/data/"
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- paths = {
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- "raw": {"train": dir + "cbt_train.txt", "valid": dir + "cbt_valid.txt", "test": dir + "cbt_test.txt"},
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- "V": {
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- "train": dir + "cbtest_V_train.txt",
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- "valid": dir + "cbtest_V_valid_2000ex.txt",
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- "test": dir + "cbtest_V_test_2500ex.txt",
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- },
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- "P": {
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- "train": dir + "cbtest_P_train.txt",
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- "valid": dir + "cbtest_P_valid_2000ex.txt",
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- "test": dir + "cbtest_P_test_2500ex.txt",
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- },
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- "NE": {
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- "train": dir + "cbtest_NE_train.txt",
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- "valid": dir + "cbtest_NE_valid_2000ex.txt",
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- "test": dir + "cbtest_NE_test_2500ex.txt",
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- },
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- "CN": {
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- "train": dir + "cbtest_CN_train.txt",
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- "valid": dir + "cbtest_CN_valid_2000ex.txt",
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- "test": dir + "cbtest_CN_test_2500ex.txt",
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- },
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- }
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-
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-
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- class Cbt(datasets.GeneratorBasedBuilder):
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- """TODO: Short description of my dataset."""
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-
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- VERSION = datasets.Version("1.1.0")
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-
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- BUILDER_CONFIGS = [
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- datasets.BuilderConfig(
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- name="raw", version=VERSION, description="This part of my dataset covers the raw CBT books"
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- ),
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- datasets.BuilderConfig(
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- name="V", version=VERSION, description="This part of my dataset covers the verb answer CBT dataset"
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- ),
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- datasets.BuilderConfig(
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- name="P", version=VERSION, description="This part of my dataset covers the preposition answer CBT dataset"
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- ),
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- datasets.BuilderConfig(
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- name="NE",
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- version=VERSION,
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- description="This part of my dataset covers the named entity answer CBT dataset",
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- ),
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- datasets.BuilderConfig(
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- name="CN", version=VERSION, description="This part of my dataset covers the common noun answer CBT dataset"
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- ),
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- ]
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-
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- def _info(self):
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- if self.config.name in ["V", "P", "NE", "CN"]:
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- features = datasets.Features(
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- {
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- "sentences": datasets.Sequence(datasets.Value("string")), # There are 20 sentences
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- "question": datasets.Value("string"),
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- "answer": datasets.Value("string"),
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- "options": datasets.Sequence(datasets.Value("string")),
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- }
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- )
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- else: # This is an example to show how to have different features for "first_domain" and "second_domain"
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- features = datasets.Features({"title": datasets.Value("string"), "content": 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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- my_urls = ZIP_URL # Cannot download just one single type as it is a compressed file.
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- archive = dl_manager.download(my_urls)
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- return [
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- datasets.SplitGenerator(
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- name=datasets.Split.TRAIN,
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- # These kwargs will be passed to _generate_examples
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- gen_kwargs={"filepath": paths[self.config.name]["train"], "files": dl_manager.iter_archive(archive)},
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- ),
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- datasets.SplitGenerator(
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- name=datasets.Split.TEST,
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- # These kwargs will be passed to _generate_examples
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- gen_kwargs={"filepath": paths[self.config.name]["test"], "files": dl_manager.iter_archive(archive)},
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- ),
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- datasets.SplitGenerator(
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- name=datasets.Split.VALIDATION,
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- # These kwargs will be passed to _generate_examples
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- gen_kwargs={"filepath": paths[self.config.name]["valid"], "files": dl_manager.iter_archive(archive)},
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- ),
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- ]
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-
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- def _generate_examples(self, filepath, files):
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- """Yields examples as (key, example) tuples."""
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- for path, f in files:
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- if path == filepath:
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- if self.config.name != "raw":
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- sentences = []
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- example_idx = 0
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- for idx, line in enumerate(f):
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- line = line.decode("utf-8")
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- if line.strip() == "":
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- continue
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-
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- elif line.split()[0] == "21":
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- splitline = line.split("\t") # question, answer options are tab separated
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- question = splitline[0]
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- answer = splitline[1]
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- options = splitline[-1]
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- question = question[2:].strip() # The first two indices contain `21`.
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- answer = answer.strip()
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- options = options.strip().split("|")
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- yield example_idx, {
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- "sentences": sentences,
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- "question": question,
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- "options": options,
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- "answer": answer,
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- }
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-
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- sentences = []
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- example_idx += 1
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- else:
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- if len(line.split()[0]) == 1:
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- sentences.append(line[1:].strip())
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- else:
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- sentences.append(line[2:].strip())
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- # Text might contain double spaces.
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- else:
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- book_idx = 0
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- book_sentences = []
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- for idx, line in enumerate(f):
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- line = line.decode("utf-8")
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- if line[:12] == "_BOOK_TITLE_":
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- if idx == 0: # First line:
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- title = line.split(":")[1].strip()
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- else:
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- yield book_idx, {
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- "title": title,
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- "content": "".join(book_sentences),
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- }
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- title = line.split(":")[1].strip()
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- book_sentences = []
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- book_idx += 1
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- else:
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- book_sentences.append(line)
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- else:
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- yield book_idx, {
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- "title": title,
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- "content": "".join(book_sentences),
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- }
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- book_sentences = []
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- book_idx += 1
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- break