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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))}
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