import datasets

from .evaluate import evaluate


A_      =      "\\n@inproceedings{Rajpurkar2016SQuAD10,\n  title={SQuAD: 100, 000+ Questions for Machine Comprehension of Text},\n  author={Pranav Rajpurkar and Jian Zhang and Konstantin Lopyrev and Percy Liang},\n  booktitle={EMNLP},\n  year={2016}\n}\n"

A_      =      "\nThis metric wrap the official scoring script for version 1 of the Stanford Question Answering Dataset (SQuAD).\n\nStanford Question Answering Dataset (SQuAD) is a reading comprehension dataset, consisting of questions posed by\ncrowdworkers on a set of Wikipedia articles, where the answer to every question is a segment of text, or span,\nfrom the corresponding reading passage, or the question might be unanswerable.\n"

A_      =      "\nComputes SQuAD scores (F1 and EM).\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': the text of the answer\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 SQuAD 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\nExamples:\n\n    >>> predictions = [{'prediction_text': '1976', 'id': '56e10a3be3433e1400422b22'}]\n    >>> references = [{'answers': {'answer_start': [97], 'text': ['1976']}, 'id': '56e10a3be3433e1400422b22'}]\n    >>> squad_metric = datasets.load_metric(\"squad\")\n    >>> results = squad_metric.compute(predictions=predictions, references=references)\n    >>> print(results)\n    {'exact_match': 100.0, 'f1': 100.0}\n"






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

						def        __a		(	self				:      int   )							->		Union[str, Any]:


									'''simple docstring'''

									return datasets.MetricInfo(
									    description=_DESCRIPTION							,							citation=_CITATION							,							inputs_description=_KWARGS_DESCRIPTION							,							features=datasets.Features(
									        {
									            '''predictions''': {'''id''': datasets.Value('''string'''   ), '''prediction_text''': datasets.Value('''string'''   )},
									            '''references''': {
									                '''id''': datasets.Value('''string'''   ),
									                '''answers''': datasets.features.Sequence(
									                    {
									                        '''text''': datasets.Value('''string'''   ),
									                        '''answer_start''': datasets.Value('''int32'''   ),
									                    }   ),
									            },
									        }   )							,							codebase_urls=['''https://rajpurkar.github.io/SQuAD-explorer/''']							,							reference_urls=['''https://rajpurkar.github.io/SQuAD-explorer/''']							,							)



						def        __a		(	self				:      Tuple							,							__lowerCamelCase				:      List[str]							,							__lowerCamelCase				:      str   )							->		Union[str, Any]:


									'''simple docstring'''

									lowercase							=		{prediction['''id''']: prediction['''prediction_text'''] for prediction in predictions}
									lowercase							=		[
									    {
									        '''paragraphs''': [
									            {
									                '''qas''': [
									                    {
									                        '''answers''': [{'''text''': answer_text} for answer_text in ref['''answers''']['''text''']],
									                        '''id''': ref['''id'''],
									                    }
									                    for ref in references
									                ]
									            }
									        ]
									    }
									]
									lowercase							=		evaluate(dataset=__lowerCamelCase							,							predictions=__lowerCamelCase   )
									return score






from __future__ import annotations

from collections.abc import MutableSequence






class      __lowercase					:

						def __init__(	self				:      Optional[Any]							,							__lowerCamelCase				:      int							,							__lowerCamelCase				:      MutableSequence[float]   )							->		None:


									'''simple docstring'''

									if len(__lowerCamelCase   ) != degree + 1:
												raise ValueError(
												    '''The number of coefficients should be equal to the degree + 1.'''   )

									lowercase							=		list(__lowerCamelCase   )
									lowercase							=		degree

						def __add__(	self				:      Any							,							__lowerCamelCase				:      Polynomial   )							->		Polynomial:


									'''simple docstring'''

									if self.degree > polynomial_a.degree:
												lowercase							=		self.coefficients[:]
												for i in range(polynomial_a.degree + 1   ):
															coefficients[i] += polynomial_a.coefficients[i]
												return Polynomial(self.degree							,							__lowerCamelCase   )
									else:
												lowercase							=		polynomial_a.coefficients[:]
												for i in range(self.degree + 1   ):
															coefficients[i] += self.coefficients[i]
												return Polynomial(polynomial_a.degree							,							__lowerCamelCase   )

						def __sub__(	self				:      str							,							__lowerCamelCase				:      Polynomial   )							->		Polynomial:


									'''simple docstring'''

									return self + polynomial_a * Polynomial(0							,							[-1]   )

						def __neg__(	self				:      str   )							->		Polynomial:


									'''simple docstring'''

									return Polynomial(self.degree							,							[-c for c in self.coefficients]   )

						def __mul__(	self				:      List[str]							,							__lowerCamelCase				:      Polynomial   )							->		Polynomial:


									'''simple docstring'''

									lowercase							=		[0] * (self.degree + polynomial_a.degree + 1)
									for i in range(self.degree + 1   ):
												for j in range(polynomial_a.degree + 1   ):
															coefficients[i + j] += (
															    self.coefficients[i] * polynomial_a.coefficients[j]
															)

									return Polynomial(self.degree + polynomial_a.degree							,							__lowerCamelCase   )

						def        __a		(	self				:      List[str]							,							__lowerCamelCase				:      int | float   )							->		int | float:


									'''simple docstring'''

									lowercase							=		0
									for i in range(self.degree + 1   ):
												result += self.coefficients[i] * (substitution**i)
									return result

						def __str__(	self				:      str   )							->		str:


									'''simple docstring'''

									lowercase							=		''''''
									for i in range(self.degree							,							-1							,							-1   ):
												if self.coefficients[i] == 0:
															continue
												elif self.coefficients[i] > 0:
															if polynomial:
																		polynomial += " + "
												else:
															polynomial += " - "

												if i == 0:
															polynomial += str(abs(self.coefficients[i]   )   )
												elif i == 1:
															polynomial += str(abs(self.coefficients[i]   )   ) + "x"
												else:
															polynomial += str(abs(self.coefficients[i]   )   ) + "x^" + str(__lowerCamelCase   )

									return polynomial

						def __repr__(	self				:      Tuple   )							->		str:


									'''simple docstring'''

									return self.__str__()

						def        __a		(	self				:      Union[str, Any]   )							->		Polynomial:


									'''simple docstring'''

									lowercase							=		[0] * self.degree
									for i in range(self.degree   ):
												lowercase							=		self.coefficients[i + 1] * (i + 1)
									return Polynomial(self.degree - 1							,							__lowerCamelCase   )

						def        __a		(	self				:      Union[str, Any]							,							__lowerCamelCase				:      int | float = 0   )							->		Polynomial:


									'''simple docstring'''

									lowercase							=		[0] * (self.degree + 2)
									lowercase							=		constant
									for i in range(self.degree + 1   ):
												lowercase							=		self.coefficients[i] / (i + 1)
									return Polynomial(self.degree + 1							,							__lowerCamelCase   )

						def __eq__(	self				:      Tuple							,							__lowerCamelCase				:      object   )							->		bool:


									'''simple docstring'''

									if not isinstance(__lowerCamelCase							,							__lowerCamelCase   ):
												return False

									if self.degree != polynomial_a.degree:
												return False

									for i in range(self.degree + 1   ):
												if self.coefficients[i] != polynomial_a.coefficients[i]:
															return False

									return True



						def __ne__(	self				:      Tuple							,							__lowerCamelCase				:      object   )							->		bool:


									'''simple docstring'''

									return not self.__eq__(__lowerCamelCase   )





