139 lines
4.5 KiB
Python
139 lines
4.5 KiB
Python
# Copyright 2024 Bytedance Ltd. and/or its affiliates
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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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import re
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import string
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import random
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def normalize_answer(s):
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def remove_articles(text):
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return re.sub(r"\b(a|an|the)\b", " ", text)
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def white_space_fix(text):
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return " ".join(text.split())
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def remove_punc(text):
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exclude = set(string.punctuation)
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return "".join(ch for ch in text if ch not in exclude)
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def lower(text):
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return text.lower()
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return white_space_fix(remove_articles(remove_punc(lower(s))))
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def em_check(prediction, golden_answers):
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if isinstance(golden_answers, str):
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golden_answers = [golden_answers]
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normalized_prediction = normalize_answer(prediction)
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score = 0
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for golden_answer in golden_answers:
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golden_answer = normalize_answer(golden_answer)
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if golden_answer == normalized_prediction:
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score = 1
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break
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return score
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def subem_check(prediction, golden_answers):
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if isinstance(golden_answers, str):
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golden_answers = [golden_answers]
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normalized_prediction = normalize_answer(prediction)
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score = 0
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for golden_answer in golden_answers:
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golden_answer = normalize_answer(golden_answer)
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if golden_answer in normalized_prediction:
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score = 1
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break
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return score
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def extract_solution(solution_str):
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"""Extract the equation from the solution string."""
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# Remove everything before the first "Assistant:"
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# if "Assistant:" in solution_str:
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# solution_str = solution_str.split("Assistant:", 1)[1]
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# elif "<|im_start|>assistant" in solution_str:
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# solution_str = solution_str.split("<|im_start|>assistant", 1)[1]
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# else:
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# return None
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# solution_str = solution_str.split('\n')[-1]
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answer_pattern = r'<answer>(.*?)</answer>'
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match = re.finditer(answer_pattern, solution_str, re.DOTALL)
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matches = list(match)
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# If there are 0 or exactly 1 matches, return None
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if len(matches) <= 1:
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return None
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# If there are 2 or more matches, return the last one
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return matches[-1].group(1).strip()
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def compute_score_em(solution_str, ground_truth, method='strict', format_score=0., score=1.):
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"""The scoring function for exact match (EM).
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Args:
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solution_str: the solution text
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ground_truth: the ground truth
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method: the method to extract the solution, choices are 'strict' and 'flexible'
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format_score: the score for the format
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score: the score for the correct answer
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"""
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answer = extract_solution(solution_str=solution_str)
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do_print = random.randint(1, 64) == 1
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if do_print:
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print(f"--------------------------------")
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print(f"Golden answers: {ground_truth['target']}")
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print(f"Extracted answer: {answer}")
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print(f"Solution string: {solution_str}")
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if answer is None:
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return 0
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else:
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if em_check(answer, ground_truth['target']):
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return score
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else:
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return format_score
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def compute_score_subem(solution_str, ground_truth, method='strict', format_score=0., score=1.):
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"""The scoring function for substring exact match (EM).
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Args:
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solution_str: the solution text
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ground_truth: the ground truth
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method: the method to extract the solution, choices are 'strict' and 'flexible'
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format_score: the score for the format
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score: the score for the correct answer
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"""
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answer = extract_solution(solution_str=solution_str)
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do_print = random.randint(1, 64) == 1
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if do_print:
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print(f"--------------------------------")
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print(f"Golden answers: {ground_truth['target']}")
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print(f"Extracted answer: {answer}")
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print(f"Solution string: {solution_str}")
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if answer is None:
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return 0
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else:
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if subem_check(answer, ground_truth['target']):
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return score
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else:
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return format_score
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