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text_duplicates / text_duplicates.py

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	# Copyright 2022 The HuggingFace Team. All rights reserved.
	#
	# 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.

	import hashlib
	from collections import Counter

	import datasets

	import evaluate


	logger = evaluate.logging.get_logger(__name__)

	_DESCRIPTION = """
	Returns the duplicate fraction of duplicate strings in the input.
	"""

	_KWARGS_DESCRIPTION = """
	Args:
	`data`: a list of `str` to be checked for duplicates.

	Returns:
	`duplicate_fraction` (`float`) : the fraction of strings that are duplicated.
	`duplicates_dict` (`dict`) (optional) : a dictionary containing tuples with the duplicate strings and the number of times they are repeated.

	Examples:
	>>> data = ["hello sun","hello moon", "hello sun"]
	>>> duplicates = evaluate.load("text_duplicates")
	>>> results = duplicates.compute(data=data)
	>>> print(results)
	{'duplicate_fraction': 0.33333333333333337}

	>>> data = ["hello sun","hello moon", "hello sun"]
	>>> duplicates = evaluate.load("text_duplicates")
	>>> results = duplicates.compute(data=data, list_duplicates=True)
	>>> print(results)
	{'duplicate_fraction': 0.33333333333333337, 'duplicates_dict': {'hello sun': 2}}
	"""

	# TODO: Add BibTeX citation
	_CITATION = ""


	def get_hash(example):
	"""Get the hash of a string"""
	return hashlib.md5(example.strip().encode("utf-8")).hexdigest()


	@evaluate.utils.file_utils.add_start_docstrings(_DESCRIPTION, _KWARGS_DESCRIPTION)
	class TextDuplicates(evaluate.Measurement):
	"""This measurement returns the duplicate strings contained in the input(s)."""

	def _info(self):
	# TODO: Specifies the evaluate.MeasurementInfo object
	return evaluate.MeasurementInfo(
	# This is the description that will appear on the modules page.
	module_type="measurement",
	description=_DESCRIPTION,
	citation=_CITATION,
	inputs_description=_KWARGS_DESCRIPTION,
	# This defines the format of each prediction and reference
	features=datasets.Features(
	{
	"data": datasets.Value("string"),
	}
	),
	)

	def _compute(self, data, list_duplicates=False):
	"""Returns the duplicates contained in the input data and the number of times they are repeated."""
	if list_duplicates == True:
	logger.warning("This functionality can be memory-intensive for large datasets!")
	n_dedup = len(set([get_hash(d) for d in data]))
	c = Counter(data)
	duplicates = {k: v for k, v in c.items() if v > 1}
	return {"duplicate_fraction": 1 - (n_dedup / len(data)), "duplicates_dict": duplicates}
	else:
	n_dedup = len(set([get_hash(d) for d in data]))
	return {"duplicate_fraction": 1 - (n_dedup / len(data))}