import datasets

from .evaluate import evaluate


SCREAMING_SNAKE_CASE									=						'\\n@article{hendrycks2021cuad,\n      title={CUAD: An Expert-Annotated NLP Dataset for Legal Contract Review},\n      author={Dan Hendrycks and Collin Burns and Anya Chen and Spencer Ball},\n      journal={arXiv preprint arXiv:2103.06268},\n      year={2021}\n}\n'

SCREAMING_SNAKE_CASE									=						'\nThis metric wrap the official scoring script for version 1 of the Contract\nUnderstanding Atticus Dataset (CUAD).\nContract Understanding Atticus Dataset (CUAD) v1 is a corpus of more than 13,000 labels in 510\ncommercial legal contracts that have been manually labeled to identify 41 categories of important\nclauses that lawyers look for when reviewing contracts in connection with corporate transactions.\n'

SCREAMING_SNAKE_CASE									=						'\nComputes CUAD scores (EM, F1, AUPR, Precision@80%Recall, and Precision@90%Recall).\nArgs:\n    predictions: List of question-answers dictionaries with the following key-values:\n        - \'id\': id of the question-answer pair as given in the references (see below)\n        - \'prediction_text\': list of possible texts for the answer, as a list of strings\n        depending on a threshold on the confidence probability of each prediction.\n    references: List of question-answers dictionaries with the following key-values:\n        - \'id\': id of the question-answer pair (see above),\n        - \'answers\': a Dict in the CUAD dataset format\n            {\n                \'text\': list of possible texts for the answer, as a list of strings\n                \'answer_start\': list of start positions for the answer, as a list of ints\n            }\n            Note that answer_start values are not taken into account to compute the metric.\nReturns:\n    \'exact_match\': Exact match (the normalized answer exactly match the gold answer)\n    \'f1\': The F-score of predicted tokens versus the gold answer\n    \'aupr\': Area Under the Precision-Recall curve\n    \'prec_at_80_recall\': Precision at 80% recall\n    \'prec_at_90_recall\': Precision at 90% recall\nExamples:\n    >>> predictions = [{\'prediction_text\': [\'The seller:\', \'The buyer/End-User: Shenzhen LOHAS Supply Chain Management Co., Ltd.\'], \'id\': \'LohaCompanyltd_20191209_F-1_EX-10.16_11917878_EX-10.16_Supply Agreement__Parties\'}]\n    >>> references = [{\'answers\': {\'answer_start\': [143, 49], \'text\': [\'The seller:\', \'The buyer/End-User: Shenzhen LOHAS Supply Chain Management Co., Ltd.\']}, \'id\': \'LohaCompanyltd_20191209_F-1_EX-10.16_11917878_EX-10.16_Supply Agreement__Parties\'}]\n    >>> cuad_metric = datasets.load_metric("cuad")\n    >>> results = cuad_metric.compute(predictions=predictions, references=references)\n    >>> print(results)\n    {\'exact_match\': 100.0, \'f1\': 100.0, \'aupr\': 0.0, \'prec_at_80_recall\': 1.0, \'prec_at_90_recall\': 1.0}\n'



@datasets.utils.file_utils.add_start_docstrings(_DESCRIPTION						,							_KWARGS_DESCRIPTION     )
class  _lowerCamelCase			(datasets.Metric     ):







				def 							__UpperCAmelCase					( self    :       Tuple						):

					"""simple docstring"""






					return datasets.MetricInfo(
					    description=_DESCRIPTION			,					citation=_CITATION			,					inputs_description=_KWARGS_DESCRIPTION			,					features=datasets.Features(
					        {
					            'predictions': {
					                'id': datasets.Value('string'						),
					                'prediction_text': datasets.features.Sequence(datasets.Value('string'						)						),
					            },
					            'references': {
					                'id': datasets.Value('string'						),
					                'answers': datasets.features.Sequence(
					                    {
					                        'text': datasets.Value('string'						),
					                        'answer_start': datasets.Value('int32'						),
					                    }						),
					            },
					        }						)			,					codebase_urls=['https://www.atticusprojectai.org/cuad']			,					reference_urls=['https://www.atticusprojectai.org/cuad']			,					)







				def 							__UpperCAmelCase					( self    :       Dict			,					lowerCamelCase_    :       Optional[Any]			,					lowerCamelCase_    :       Optional[Any]						):

					"""simple docstring"""






					_lowercase :    Union[str, Any]							=							{prediction["""id"""]: prediction["""prediction_text"""] for prediction in predictions}
					_lowercase :    Tuple							=							[
					    {
					        """paragraphs""": [
					            {
					                """qas""": [
					                    {
					                        """answers""": [{"""text""": answer_text} for answer_text in ref["""answers"""]["""text"""]],
					                        """id""": ref["""id"""],
					                    }
					                    for ref in references
					                ]
					            }
					        ]
					    }
					]
					_lowercase :    Optional[int]							=							evaluate(dataset=lowerCamelCase_			,					predictions=lowerCamelCase_						)
					return score




"""simple docstring"""







from __future__ import annotations

import math
import random
from collections.abc import Collection
from typing import overload



class  _lowerCamelCase			:







				def __init__( self    :       str			,					lowerCamelCase_    :       Collection[float] | None = None						):

					"""simple docstring"""






					if components is None:
						_lowercase :    Any							=							[]
					_lowercase :    int							=							list(lowerCamelCase_						)







				def __len__( self    :       int						):

					"""simple docstring"""






					return len(self.__components						)







				def __str__( self    :       List[Any]						):

					"""simple docstring"""






					return "(" + ",".join(map(lowerCamelCase_			,					self.__components						)						) + ")"







				def __add__( self    :       Dict			,					lowerCamelCase_    :       Vector						):

					"""simple docstring"""






					_lowercase :    Union[str, Any]							=							len(self						)
					if size == len(lowerCamelCase_						):
						_lowercase :    int							=							[self.__components[i] + other.component(lowerCamelCase_						) for i in range(lowerCamelCase_						)]
						return Vector(lowerCamelCase_						)
					else:
						raise Exception('must have the same size'						)







				def __sub__( self    :       int			,					lowerCamelCase_    :       Vector						):

					"""simple docstring"""






					_lowercase :    Optional[int]							=							len(self						)
					if size == len(lowerCamelCase_						):
						_lowercase :    Optional[int]							=							[self.__components[i] - other.component(lowerCamelCase_						) for i in range(lowerCamelCase_						)]
						return Vector(lowerCamelCase_						)
					else:  # error case
						raise Exception('must have the same size'						)







				@overload
				def __mul__( self    :       Tuple			,					lowerCamelCase_    :       float						):

					"""simple docstring"""






					...







				@overload
				def __mul__( self    :       Tuple			,					lowerCamelCase_    :       Vector						):

					"""simple docstring"""






					...







				def __mul__( self    :       int			,					lowerCamelCase_    :       float | Vector						):

					"""simple docstring"""






					if isinstance(lowerCamelCase_			,					(float, int)						):
						_lowercase :    List[Any]							=							[c * other for c in self.__components]
						return Vector(lowerCamelCase_						)
					elif isinstance(lowerCamelCase_			,					lowerCamelCase_						) and len(self						) == len(lowerCamelCase_						):
						_lowercase :    Any							=							len(self						)
						_lowercase :    List[Any]							=							[self.__components[i] * other.component(lowerCamelCase_						) for i in range(lowerCamelCase_						)]
						return sum(lowerCamelCase_						)
					else:  # error case
						raise Exception('invalid operand!'						)







				def 							__UpperCAmelCase					( self    :       Dict						):

					"""simple docstring"""






					return Vector(self.__components						)







				def 							__UpperCAmelCase					( self    :       List[str]			,					lowerCamelCase_    :       int						):

					"""simple docstring"""






					if isinstance(lowerCamelCase_			,					lowerCamelCase_						) and -len(self.__components						) <= i < len(self.__components						):
						return self.__components[i]
					else:
						raise Exception('index out of range'						)







				def 							__UpperCAmelCase					( self    :       str			,					lowerCamelCase_    :       int			,					lowerCamelCase_    :       float						):

					"""simple docstring"""






					assert -len(self.__components						) <= pos < len(self.__components						)
					_lowercase :    Tuple							=							value







				def 							__UpperCAmelCase					( self    :       List[Any]						):

					"""simple docstring"""






					if len(self.__components						) == 0:
						raise Exception('Vector is empty'						)
					_lowercase :    Optional[int]							=							[c**2 for c in self.__components]
					return math.sqrt(sum(lowerCamelCase_						)						)







				def 							__UpperCAmelCase					( self    :       int			,					lowerCamelCase_    :       Vector			,					lowerCamelCase_    :       bool = False						):

					"""simple docstring"""






					_lowercase :    int							=							self * other
					_lowercase :    Any							=							self.euclidean_length() * other.euclidean_length()
					if deg:
						return math.degrees(math.acos(num / den						)						)
					else:
						return math.acos(num / den						)



def      __lowerCAmelCase(		__UpperCAmelCase			):






	"""simple docstring"""





	assert isinstance(__UpperCAmelCase     ,__UpperCAmelCase			)
	return Vector([0] * dimension			)


def      __lowerCAmelCase(		__UpperCAmelCase     ,__UpperCAmelCase			):






	"""simple docstring"""





	assert isinstance(__UpperCAmelCase     ,__UpperCAmelCase			) and (isinstance(__UpperCAmelCase     ,__UpperCAmelCase			))
	_lowercase :    str							=							[0] * dimension
	_lowercase :    List[Any]							=							1
	return Vector(__UpperCAmelCase			)


def      __lowerCAmelCase(		__UpperCAmelCase     ,__UpperCAmelCase     ,__UpperCAmelCase			):






	"""simple docstring"""





	assert (
	    isinstance(__UpperCAmelCase     ,__UpperCAmelCase			)
	    and isinstance(__UpperCAmelCase     ,__UpperCAmelCase			)
	    and (isinstance(__UpperCAmelCase     ,(int, float)			))
	)
	return x * scalar + y


def      __lowerCAmelCase(		__UpperCAmelCase     ,__UpperCAmelCase     ,__UpperCAmelCase			):






	"""simple docstring"""





	random.seed(__UpperCAmelCase			)
	_lowercase :    Tuple							=							[random.randint(__UpperCAmelCase     ,__UpperCAmelCase			) for _ in range(__UpperCAmelCase			)]
	return Vector(__UpperCAmelCase			)



class  _lowerCamelCase			:







				def __init__( self    :       Dict			,					lowerCamelCase_    :       list[list[float]]			,					lowerCamelCase_    :       int			,					lowerCamelCase_    :       int						):

					"""simple docstring"""






					_lowercase :    Tuple							=							matrix
					_lowercase :    str							=							w
					_lowercase :    Tuple							=							h







				def __str__( self    :       int						):

					"""simple docstring"""






					_lowercase :    Tuple							=							''
					for i in range(self.__height						):
						ans += "|"
						for j in range(self.__width						):
							if j < self.__width - 1:
								ans += str(self.__matrix[i][j]						) + ","
							else:
								ans += str(self.__matrix[i][j]						) + "|\n"
					return ans







				def __add__( self    :       Dict			,					lowerCamelCase_    :       Matrix						):

					"""simple docstring"""






					if self.__width == other.width() and self.__height == other.height():
						_lowercase :    Dict							=							[]
						for i in range(self.__height						):
							_lowercase :    Tuple							=							[
							    self.__matrix[i][j] + other.component(lowerCamelCase_			,					lowerCamelCase_						)
							    for j in range(self.__width						)
							]
							matrix.append(lowerCamelCase_						)
						return Matrix(lowerCamelCase_			,					self.__width			,					self.__height						)
					else:
						raise Exception('matrix must have the same dimension!'						)







				def __sub__( self    :       str			,					lowerCamelCase_    :       Matrix						):

					"""simple docstring"""






					if self.__width == other.width() and self.__height == other.height():
						_lowercase :    List[Any]							=							[]
						for i in range(self.__height						):
							_lowercase :    int							=							[
							    self.__matrix[i][j] - other.component(lowerCamelCase_			,					lowerCamelCase_						)
							    for j in range(self.__width						)
							]
							matrix.append(lowerCamelCase_						)
						return Matrix(lowerCamelCase_			,					self.__width			,					self.__height						)
					else:
						raise Exception('matrices must have the same dimension!'						)







				@overload
				def __mul__( self    :       Union[str, Any]			,					lowerCamelCase_    :       float						):

					"""simple docstring"""






					...







				@overload
				def __mul__( self    :       List[str]			,					lowerCamelCase_    :       Vector						):

					"""simple docstring"""






					...







				def __mul__( self    :       int			,					lowerCamelCase_    :       float | Vector						):

					"""simple docstring"""






					if isinstance(lowerCamelCase_			,					lowerCamelCase_						):  # matrix-vector
						if len(lowerCamelCase_						) == self.__width:
							_lowercase :    Optional[int]							=							zero_vector(self.__height						)
							for i in range(self.__height						):
								_lowercase :    Optional[Any]							=							[
								    self.__matrix[i][j] * other.component(lowerCamelCase_						)
								    for j in range(self.__width						)
								]
								ans.change_component(lowerCamelCase_			,					sum(lowerCamelCase_						)						)
							return ans
						else:
							raise Exception(
							    'vector must have the same size as the '
							    'number of columns of the matrix!'						)
					elif isinstance(lowerCamelCase_			,					(int, float)						):  # matrix-scalar
						_lowercase :    Optional[int]							=							[
						    [self.__matrix[i][j] * other for j in range(self.__width						)]
						    for i in range(self.__height						)
						]
						return Matrix(lowerCamelCase_			,					self.__width			,					self.__height						)
					return None







				def 							__UpperCAmelCase					( self    :       Union[str, Any]						):

					"""simple docstring"""






					return self.__height







				def 							__UpperCAmelCase					( self    :       List[Any]						):

					"""simple docstring"""






					return self.__width







				def 							__UpperCAmelCase					( self    :       Optional[Any]			,					lowerCamelCase_    :       int			,					lowerCamelCase_    :       int						):

					"""simple docstring"""






					if 0 <= x < self.__height and 0 <= y < self.__width:
						return self.__matrix[x][y]
					else:
						raise Exception('change_component: indices out of bounds'						)







				def 							__UpperCAmelCase					( self    :       Optional[Any]			,					lowerCamelCase_    :       int			,					lowerCamelCase_    :       int			,					lowerCamelCase_    :       float						):

					"""simple docstring"""






					if 0 <= x < self.__height and 0 <= y < self.__width:
						_lowercase :    int							=							value
					else:
						raise Exception('change_component: indices out of bounds'						)







				def 							__UpperCAmelCase					( self    :       int			,					lowerCamelCase_    :       int			,					lowerCamelCase_    :       int						):

					"""simple docstring"""






					if self.__height != self.__width:
						raise Exception('Matrix is not square'						)
					_lowercase :    Union[str, Any]							=							self.__matrix[:x] + self.__matrix[x + 1 :]
					for i in range(len(lowerCamelCase_						)						):
						_lowercase :    int							=							minor[i][:y] + minor[i][y + 1 :]
					return Matrix(lowerCamelCase_			,					self.__width - 1			,					self.__height - 1						).determinant()







				def 							__UpperCAmelCase					( self    :       List[str]			,					lowerCamelCase_    :       int			,					lowerCamelCase_    :       int						):

					"""simple docstring"""






					if self.__height != self.__width:
						raise Exception('Matrix is not square'						)
					if 0 <= x < self.__height and 0 <= y < self.__width:
						return (-1) ** (x + y) * self.minor(lowerCamelCase_			,					lowerCamelCase_						)
					else:
						raise Exception('Indices out of bounds'						)







				def 							__UpperCAmelCase					( self    :       Dict						):

					"""simple docstring"""






					if self.__height != self.__width:
						raise Exception('Matrix is not square'						)
					if self.__height < 1:
						raise Exception('Matrix has no element'						)
					elif self.__height == 1:
						return self.__matrix[0][0]
					elif self.__height == 2:
						return (
						    self.__matrix[0][0] * self.__matrix[1][1]
						    - self.__matrix[0][1] * self.__matrix[1][0]
						)
					else:
						_lowercase :    Union[str, Any]							=							[
						    self.__matrix[0][y] * self.cofactor(0			,					lowerCamelCase_						) for y in range(self.__width						)
						]
						return sum(lowerCamelCase_						)



def      __lowerCAmelCase(		__UpperCAmelCase			):






	"""simple docstring"""





	_lowercase :    list[list[float]]							=							[[0] * n for _ in range(__UpperCAmelCase			)]
	return Matrix(__UpperCAmelCase     ,__UpperCAmelCase     ,__UpperCAmelCase			)







def      __lowerCAmelCase(		__UpperCAmelCase     ,__UpperCAmelCase     ,__UpperCAmelCase     ,__UpperCAmelCase			):






	"""simple docstring"""





	random.seed(__UpperCAmelCase			)
	_lowercase :    list[list[float]]							=							[
	    [random.randint(__UpperCAmelCase     ,__UpperCAmelCase			) for _ in range(__UpperCAmelCase			)] for _ in range(__UpperCAmelCase			)
	]
	return Matrix(__UpperCAmelCase     ,__UpperCAmelCase     ,__UpperCAmelCase			)



