





import time
import unittest

from transformers import is_torch_available
from transformers.testing_utils import require_torch, torch_device

from ..test_modeling_common import ids_tensor


if is_torch_available():
     import torch

     from transformers.generation import (
         MaxLengthCriteria,
         MaxNewTokensCriteria,
         MaxTimeCriteria,
         StoppingCriteriaList,
         validate_stopping_criteria,
     )



@require_torch
class 				_UpperCAmelCase    (    unittest.TestCase    ):

  """simple docstring"""


  def 				lowercase		(				self :		List[str]					,  lowerCAmelCase_ :		List[Any]     )							->						Optional[Any]:
     __lowerCAmelCase								=	3
     __lowerCAmelCase								=	2_5_0

     __lowerCAmelCase								=	ids_tensor((batch_size, length)					,  lowerCAmelCase_     )
     __lowerCAmelCase								=	torch.ones((batch_size, length)					,  device=lowerCAmelCase_					,  dtype=torch.float     ) / length
     return input_ids, scores






  def 				lowercase		(				self :		List[Any]     )							->						Any:
     __lowerCAmelCase	,	__lowerCAmelCase								=	self._get_tensors(5     )

     __lowerCAmelCase								=	StoppingCriteriaList(
         [
             MaxLengthCriteria(max_length=1_0     ),
             MaxTimeCriteria(max_time=0.1     ),
         ]     )

     self.assertFalse(criteria(lowerCAmelCase_					,  lowerCAmelCase_     )     )

     __lowerCAmelCase	,	__lowerCAmelCase								=	self._get_tensors(9     )
     self.assertFalse(criteria(lowerCAmelCase_					,  lowerCAmelCase_     )     )

     __lowerCAmelCase	,	__lowerCAmelCase								=	self._get_tensors(1_0     )
     self.assertTrue(criteria(lowerCAmelCase_					,  lowerCAmelCase_     )     )






  def 				lowercase		(				self :		List[str]     )							->						Union[str, Any]:
     __lowerCAmelCase								=	MaxLengthCriteria(max_length=1_0     )

     __lowerCAmelCase	,	__lowerCAmelCase								=	self._get_tensors(5     )
     self.assertFalse(criteria(lowerCAmelCase_					,  lowerCAmelCase_     )     )

     __lowerCAmelCase	,	__lowerCAmelCase								=	self._get_tensors(9     )
     self.assertFalse(criteria(lowerCAmelCase_					,  lowerCAmelCase_     )     )

     __lowerCAmelCase	,	__lowerCAmelCase								=	self._get_tensors(1_0     )
     self.assertTrue(criteria(lowerCAmelCase_					,  lowerCAmelCase_     )     )






  def 				lowercase		(				self :		List[Any]     )							->						Optional[Any]:
     __lowerCAmelCase								=	MaxNewTokensCriteria(start_length=5					,  max_new_tokens=5     )

     __lowerCAmelCase	,	__lowerCAmelCase								=	self._get_tensors(5     )
     self.assertFalse(criteria(lowerCAmelCase_					,  lowerCAmelCase_     )     )

     __lowerCAmelCase	,	__lowerCAmelCase								=	self._get_tensors(9     )
     self.assertFalse(criteria(lowerCAmelCase_					,  lowerCAmelCase_     )     )

     __lowerCAmelCase	,	__lowerCAmelCase								=	self._get_tensors(1_0     )
     self.assertTrue(criteria(lowerCAmelCase_					,  lowerCAmelCase_     )     )

     __lowerCAmelCase								=	StoppingCriteriaList([criteria]     )
     self.assertEqual(criteria_list.max_length					,  1_0     )






  def 				lowercase		(				self :		Dict     )							->						int:
     __lowerCAmelCase	,	__lowerCAmelCase								=	self._get_tensors(5     )

     __lowerCAmelCase								=	MaxTimeCriteria(max_time=0.1     )
     self.assertFalse(criteria(lowerCAmelCase_					,  lowerCAmelCase_     )     )

     __lowerCAmelCase								=	MaxTimeCriteria(max_time=0.1					,  initial_timestamp=time.time() - 0.2     )
     self.assertTrue(criteria(lowerCAmelCase_					,  lowerCAmelCase_     )     )






  def 				lowercase		(				self :		List[str]     )							->						List[Any]:
     validate_stopping_criteria(StoppingCriteriaList([MaxLengthCriteria(1_0     )]     )					,  1_0     )

     with self.assertWarns(lowerCAmelCase_     ):
        validate_stopping_criteria(StoppingCriteriaList([MaxLengthCriteria(1_0     )]     )					,  1_1     )

     __lowerCAmelCase								=	validate_stopping_criteria(StoppingCriteriaList()					,  1_1     )

     self.assertEqual(len(lowerCAmelCase_     )					,  1     )








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

import datasets


_snake_case  :    Tuple						    =  '\\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'


_snake_case  :    str						    =  '\\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'


_snake_case  :    List[str]						    =  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 				_UpperCAmelCase    (    datasets.Metric    ):

  """simple docstring"""


  def 				lowercase		(				self :		str     )							->						int:
     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 				lowercase		(				self :		str					,  lowerCAmelCase_ :		Any					,  lowerCAmelCase_ :		Optional[int]     )							->						List[Any]:
     __lowerCAmelCase								=	0.0
     for i, j in zip(lowerCAmelCase_					,  lowerCAmelCase_     ):
        n_correct += 1.0 if math_equivalence.is_equiv(lowerCAmelCase_					,  lowerCAmelCase_     ) else 0.0
     __lowerCAmelCase								=	n_correct / len(lowerCAmelCase_     )
     return {
         "accuracy": accuracy,
     }

