



import torch

from transformers import AutoTokenizer



class     __snake_case						(					lowerCAmelCase__						):




							def __init__(	self					:	Tuple    ,    A_					:	Tuple):
									lowerCAmelCase_      :					Dict     =			AutoTokenizer.from_pretrained(_UpperCAmelCase)




							def        UpperCAmelCase__      (	self					:	int    ,    A_					:	Tuple):


									if isinstance(_UpperCAmelCase    ,    _UpperCAmelCase) and all(isinstance(_x    ,    _UpperCAmelCase) for _x in x):
											lowerCAmelCase_      :					Optional[int]     =			None
											for l in x:
													lowerCAmelCase_      :					int     =			self.tokenizer(
													    _UpperCAmelCase    ,    padding='''max_length'''    ,    max_length=3_8_4    ,    truncation=_UpperCAmelCase    ,    return_tensors='''pt'''    ,    )
													lowerCAmelCase_      :					int     =			torch.tensor([len(_UpperCAmelCase)])
													if d is not None:
															for k in d.keys():
																	lowerCAmelCase_      :					List[Any]     =			torch.cat((d[k], t[k])    ,    0)
													else:
															lowerCAmelCase_      :					Union[str, Any]     =			t

											lowerCAmelCase_      :					Union[str, Any]     =			torch.tensor(self.tokenizer.convert_tokens_to_ids('''[E]'''))
											lowerCAmelCase_      :					Tuple     =			torch.tensor(self.tokenizer.convert_tokens_to_ids('''[/E]'''))

									elif isinstance(_UpperCAmelCase    ,    _UpperCAmelCase) and all(isinstance(_x    ,    _UpperCAmelCase) for _x in x):
											lowerCAmelCase_      :					Dict     =			self.tokenizer(
											    _UpperCAmelCase    ,    padding='''max_length'''    ,    max_length=3_8_4    ,    truncation=_UpperCAmelCase    ,    return_tensors='''pt'''    ,    )

									else:
											raise Exception(
											    '''Type of parameter x was not recognized! Only `list of strings` for query or `list of lists of'''
											    ''' strings` for supports are supported.''')

									return d







							def        UpperCAmelCase__      (	self					:	List[str]    ,    A_					:	Tuple    ,    A_					:	Tuple    ,    A_					:	Union[str, Any]    ,    A_					:	Dict    ,    A_					:	List[str]=0.70):
									lowerCAmelCase_      :					int     =			[]
									for idx in range(len(W_query['''input_ids'''])):
											lowerCAmelCase_      :					List[Any]     =			range(p_start.shape[1])

											lowerCAmelCase_      :					Tuple     =			[]
											for start_id in start_indexes:
													for end_id in end_indexes:
															if start_id < end_id:
																	output.append(
																	    (
																	        start_id,
																	        end_id,
																	        p_start[idx][start_id].item(),
																	        p_end[idx][end_id].item(),
																	    ))

											output.sort(key=lambda A_: (tup[2] * tup[3])    ,    reverse=_UpperCAmelCase)
											lowerCAmelCase_      :					List[Any]     =			[]
											for k in range(len(_UpperCAmelCase)):
													if output[k][2] * output[k][3] >= thresh:
															lowerCAmelCase_ ,  lowerCAmelCase_      :					Union[str, Any]     =			output[k][0], output[k][1]
															lowerCAmelCase_      :					Dict     =			self.tokenizer.decode(W_query['''input_ids'''][idx][c_start_pos:c_end_pos])
															temp.append((decoded, output[k][2] * output[k][3]))

											final_outputs.append(_UpperCAmelCase)

									return final_outputs










A__  :  str       = 1000


def       UpperCamelCase(  __UpperCamelCase							:		float			):
		return x * x


def       UpperCamelCase(  __UpperCamelCase							:		Optional[int]					,__UpperCamelCase							:		float					,__UpperCamelCase							:		float					,__UpperCamelCase							:		int = 4			):
		assert callable(
		    __UpperCamelCase			), f"""the function(object) passed should be callable your input : {function}"""
		assert isinstance(__UpperCamelCase					,(float, int)			), f"""a should be float or integer your input : {a}"""
		assert isinstance(function(__UpperCamelCase			)					,(float, int)			), (
		    "the function should return integer or float return type of your function, "
		    f"""{type(__UpperCamelCase			)}"""
		)
		assert isinstance(__UpperCamelCase					,(float, int)			), f"""b should be float or integer your input : {b}"""
		assert (
		    isinstance(__UpperCamelCase					,__UpperCamelCase			) and precision > 0
		), f"""precision should be positive integer your input : {precision}"""

		# just applying the formula of simpson for approximate integration written in
		# mentioned article in first comment of this file and above this function

		lowerCAmelCase_      :					List[str]     =			(b - a) / N_STEPS
		lowerCAmelCase_      :					str     =			function(__UpperCamelCase			) + function(__UpperCamelCase			)

		for i in range(1					,__UpperCamelCase			):
				lowerCAmelCase_      :					Optional[Any]     =			a + h * i
				result += function(__UpperCamelCase			) * (4 if i % 2 else 2)

		result *= h / 3
		return round(__UpperCamelCase					,__UpperCamelCase			)


if __name__ == "__main__":
						import doctest

						doctest.testmod()





