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childes_data_no_tags / childes_data_no_tags.py

w-nicole

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	# The majority of this file was taken and adapted from this file, on 6/3/21: https://github.com/huggingface/datasets/blob/master/datasets/snli/snli.py
	# License reproduced from the original code:
	# coding=utf-8
	# Copyright 2020 The TensorFlow Datasets Authors and the HuggingFace Datasets Authors.
	#
	# 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.
	# The changes to the file include:
	# Changing all of the parameters to reflect childes data and information
	# Changing the dl_manager to be essentially unused in split_generators and loading from text files instead
	# Changing generate_examples to load directly from text files and clean the lines of text.
	import datasets
	import os
	class Childes(datasets.GeneratorBasedBuilder):

	BUILDER_CONFIGS = [
	datasets.BuilderConfig(
	name="childes_data_no_tags",
	version=datasets.Version("1.0.0", ""),
	description="Childes language modeling dataset without speaker tags.",
	)
	]


	def _info(self):

	citation_text = """\\
	@article{sanchez2019childes,
	title={childes-db: A flexible and reproducible interface to the child language data exchange system},
	author={Sanchez, Alessandro and Meylan, Stephan C and Braginsky, Mika and MacDonald, Kyle E and Yurovsky, Daniel and Frank, Michael C},
	journal={Behavior research methods},
	volume={51},
	number={4},
	pages={1928--1941},
	year={2019},
	publisher={Springer}}
	"""


	return datasets.DatasetInfo(
	description = "CHILDES data for language modeling",
	citation = citation_text,
	# 6/3 Citation info is directly taken from Google Scholar
	features=datasets.Features(
	{
	"text": datasets.Value("string"),
	}
	),
	# No default supervised_keys (as we have to pass both premise
	# and hypothesis as input).
	homepage="https://childes-db.stanford.edu/",
	)


	def _split_generators(self, download_helper):

	paths = download_helper.download_and_extract({
	'train' : 'https://www.dropbox.com/s/dl/i282barrzlari08/train.txt?dl=1',
	'val' : 'https://www.dropbox.com/s/gx0rngo3v5mvlcf/validation.txt?dl=1',
	})

	list_datasets = []

	phases = ['train', 'val']
	dataset_names = [
	datasets.Split.TRAIN,
	datasets.Split.VALIDATION,
	]

	for phase, phase_name in zip(phases, dataset_names):

	this_dataset = datasets.SplitGenerator(
	name=phase_name, gen_kwargs={"file_path": paths[phase]}
	)

	list_datasets.append(this_dataset)


	return list_datasets

	def _generate_examples(self, file_path):

	# Remove the speaker tags
	clean_text = lambda text : text.strip('[CGV] ').strip('[CHI] ').strip('\n')

	# 6/17: https://stackoverflow.com/questions/10406135/unicodedecodeerror-ascii-codec-cant-decode-byte-0xd1-in-position-2-ordinal
	with open(file_path, 'r', encoding="utf-8") as f:
	for idx, line in enumerate(f.readlines()):
	yield idx, {"text" : clean_text(line)}