Datasets:

zzhowe1207
/

tet-rl

# Copyright 2024 Bytedance Ltd. and/or its affiliates
#
# 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 re
from typing import Any, Dict, List

from mathruler.grader import extract_boxed_content, grade_answer


def format_reward(response: str) -> float:
    pattern = re.compile(r"<think>.*</think>.*\\boxed\{.*\}.*", re.DOTALL)
    format_match = re.fullmatch(pattern, response)
    return 1.0 if format_match else 0.0


def accuracy_reward(response: str, ground_truth: str) -> float:
    answer = extract_boxed_content(response)
    return 1.0 if grade_answer(answer, ground_truth) else 0.0


def compute_score(reward_inputs: List[Dict[str, Any]], format_weight: float = 0.1) -> List[Dict[str, float]]:
    if not isinstance(reward_inputs, list):
        raise ValueError("Please use `reward_type=batch` for math reward function.")

    scores = []
    for reward_input in reward_inputs:
        response = re.sub(r"\s*(<|>|/)\s*", r"\1", reward_input["response"])  # handle qwen2.5vl-32b format
        format_score = format_reward(response)
        accuracy_score = accuracy_reward(response, reward_input["ground_truth"])
        scores.append(
            {
                "overall": (1 - format_weight) * accuracy_score + format_weight * format_score,
                "format": format_score,
                "accuracy": accuracy_score,
            }
        )

    return scores

	# Copyright 2024 Bytedance Ltd. and/or its affiliates
	#
	# 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 re
	from typing import Any, Dict, List

	from mathruler.grader import extract_boxed_content, grade_answer


	def format_reward(response: str) -> float:
	pattern = re.compile(r"<think>.</think>.\\boxed\{.\}.", re.DOTALL)
	format_match = re.fullmatch(pattern, response)
	return 1.0 if format_match else 0.0


	def accuracy_reward(response: str, ground_truth: str) -> float:
	answer = extract_boxed_content(response)
	return 1.0 if grade_answer(answer, ground_truth) else 0.0


	def compute_score(reward_inputs: List[Dict[str, Any]], format_weight: float = 0.1) -> List[Dict[str, float]]:
	if not isinstance(reward_inputs, list):
	raise ValueError("Please use `reward_type=batch` for math reward function.")

	scores = []
	for reward_input in reward_inputs:
	response = re.sub(r"\s(<\|>\|/)\s", r"\1", reward_input["response"]) # handle qwen2.5vl-32b format
	format_score = format_reward(response)
	accuracy_score = accuracy_reward(response, reward_input["ground_truth"])
	scores.append(
	{
	"overall": (1 - format_weight) * accuracy_score + format_weight * format_score,
	"format": format_score,
	"accuracy": accuracy_score,
	}
	)

	return scores