import math_equivalence  # From: git+https://github.com/hendrycks/math.git

import datasets


__SCREAMING_SNAKE_CASE						:   Any         =			'\\n@article{hendrycksmath2021,\n  title={Measuring Mathematical Problem Solving With the MATH Dataset},\n  author={Dan Hendrycks\n    and Collin Burns\n    and Saurav Kadavath\n    and Akul Arora\n    and Steven Basart\n    and Eric Tang\n    and Dawn Song\n    and Jacob Steinhardt},\n  journal={arXiv preprint arXiv:2103.03874},\n  year={2021}\n}\n'


__SCREAMING_SNAKE_CASE						:   int         =			'\\nThis metric is used to assess performance on the Mathematics Aptitude Test of Heuristics (MATH) dataset.\nIt first canonicalizes the inputs (e.g., converting "1/2" to "\\frac{1}{2}") and then computes accuracy.\n'


__SCREAMING_SNAKE_CASE						:   Optional[Any]         =			R'\nCalculates accuracy after canonicalizing inputs.\n\nArgs:\n    predictions: list of predictions to score. Each prediction\n        is a string that contains natural language and LaTex.\n    references: list of reference for each prediction. Each\n        reference is a string that contains natural language\n        and LaTex.\nReturns:\n    accuracy: accuracy after canonicalizing inputs\n        (e.g., converting "1/2" to "\\frac{1}{2}")\n\nExamples:\n    >>> metric = datasets.load_metric("competition_math")\n    >>> results = metric.compute(references=["\\frac{1}{2}"], predictions=["1/2"])\n    >>> print(results)\n    {\'accuracy\': 1.0}\n'



@datasets.utils.file_utils.add_end_docstrings(_DESCRIPTION						,			_KWARGS_DESCRIPTION		)
class        lowercase_   (					datasets.Metric		):



							def 	UpperCamelCase	(						self    ):
													return datasets.MetricInfo(
													    description=_DESCRIPTION				,    citation=_CITATION				,    inputs_description=_KWARGS_DESCRIPTION				,    features=datasets.Features(
													        {
													            "predictions": datasets.Value("string"    ),
													            "references": datasets.Value("string"    ),
													        }    )				,    homepage="https://github.com/hendrycks/math"				,    codebase_urls=["https://github.com/hendrycks/math"]				,    )



							def 	UpperCamelCase	(						self				,    lowercase_				,    lowercase_    ):
													_snake_case						:					Optional[Any]    =   0.0
													for i, j in zip(lowercase_				,    lowercase_    ):
																			n_correct += 1.0 if math_equivalence.is_equiv(lowercase_				,    lowercase_    ) else 0.0
													_snake_case						:					Dict    =   n_correct / len(lowercase_    )
													return {
													    "accuracy": accuracy,
													}
from __future__ import annotations

from collections import deque
from collections.abc import Iterator
from dataclasses import dataclass



@dataclass
class        lowercase_   :
							_lowerCamelCase						=		42
							_lowerCamelCase						=		42




class        lowercase_   :



							def __init__(						self				,    lowercase_    ):
													_snake_case						:					list[list[Edge]]    =   [[] for _ in range(lowercase_    )]
													_snake_case						:					Union[str, Any]    =   size



							def __getitem__(						self				,    lowercase_    ):
													return iter(self._graph[vertex]    )



							@property
							def 	UpperCamelCase	(						self    ):
													return self._size



							def 	UpperCamelCase	(						self				,    lowercase_				,    lowercase_				,    lowercase_    ):
													if weight not in (0, 1):
																			raise ValueError("Edge weight must be either 0 or 1."    )

													if to_vertex < 0 or to_vertex >= self.size:
																			raise ValueError("Vertex indexes must be in [0; size)."    )

													self._graph[from_vertex].append(Edge(lowercase_				,    lowercase_    )    )



							def 	UpperCamelCase	(						self				,    lowercase_				,    lowercase_    ):
													_snake_case						:					Optional[int]    =   deque([start_vertex]    )
													_snake_case						:					list[int | None]    =   [None] * self.size
													_snake_case						:					Tuple    =   0

													while queue:
																			_snake_case						:					List[Any]    =   queue.popleft()
																			_snake_case						:					Tuple    =   distances[current_vertex]
																			if current_distance is None:
																									continue

																			for edge in self[current_vertex]:
																									_snake_case						:					Dict    =   current_distance + edge.weight
																									_snake_case						:					str    =   distances[edge.destination_vertex]
																									if (
																									    isinstance(lowercase_				,    lowercase_    )
																									    and new_distance >= dest_vertex_distance
																									):
																															continue
																									_snake_case						:					List[Any]    =   new_distance
																									if edge.weight == 0:
																															queue.appendleft(edge.destination_vertex    )
																									else:
																															queue.append(edge.destination_vertex    )

													if distances[finish_vertex] is None:
																			raise ValueError("No path from start_vertex to finish_vertex."    )

													return distances[finish_vertex]


if __name__ == "__main__":
				import doctest

				doctest.testmod()