






from __future__ import annotations

import math

import numpy as np
from numpy.linalg import norm





def 	lowerCAmelCase_		(lowercase__						:       np.ndarray     ,					lowercase__						:       np.ndarray       )		->    float:


				'''simple docstring'''




				return math.sqrt(sum(pow(a - b     ,					2       ) for a, b in zip(lowercase__     ,					lowercase__       )       )       )





def 	lowerCAmelCase_		(lowercase__						:       np.ndarray     ,					lowercase__						:       np.ndarray       )		->    list[list[list[float] | float]]:


				'''simple docstring'''




				if dataset.ndim != value_array.ndim:
								lowerCAmelCase__      			=						(
								    '''Wrong input data\'s dimensions... '''
								    f'dataset : {dataset.ndim}, value_array : {value_array.ndim}'
								)
								raise ValueError(lowercase__       )

				try:
								if dataset.shape[1] != value_array.shape[1]:
												lowerCAmelCase__      			=						(
												    '''Wrong input data\'s shape... '''
												    f'dataset : {dataset.shape[1]}, value_array : {value_array.shape[1]}'
												)
												raise ValueError(lowercase__       )
				except IndexError:
								if dataset.ndim != value_array.ndim:
												raise TypeError('''Wrong shape'''       )

				if dataset.dtype != value_array.dtype:
								lowerCAmelCase__      			=						(
								    '''Input data have different datatype... '''
								    f'dataset : {dataset.dtype}, value_array : {value_array.dtype}'
								)
								raise TypeError(lowercase__       )

				lowerCAmelCase__      			=						[]

				for value in value_array:
								lowerCAmelCase__      			=						euclidean(lowercase__     ,					dataset[0]       )
								lowerCAmelCase__      			=						dataset[0].tolist()

								for dataset_value in dataset[1:]:
												lowerCAmelCase__      			=						euclidean(lowercase__     ,					lowercase__       )

												if dist > temp_dist:
																lowerCAmelCase__      			=						temp_dist
																lowerCAmelCase__      			=						dataset_value.tolist()

								answer.append([vector, dist]       )

				return answer





def 	lowerCAmelCase_		(lowercase__						:       np.ndarray     ,					lowercase__						:       np.ndarray       )		->    float:


				'''simple docstring'''




				return np.dot(lowercase__     ,					lowercase__       ) / (norm(lowercase__       ) * norm(lowercase__       ))


if __name__ == "__main__":
			import doctest

			doctest.testmod()













from ...configuration_utils import PretrainedConfig
class  lowerCAmelCase_       (				snake_case__					):
							UpperCamelCase_		:List[str]		      =    'bert-generation'




							def __init__(   self     :   Tuple ,							SCREAMING_SNAKE_CASE_     :   List[str]=50_358 ,							SCREAMING_SNAKE_CASE_     :   List[Any]=1_024 ,							SCREAMING_SNAKE_CASE_     :   Optional[Any]=24 ,							SCREAMING_SNAKE_CASE_     :   Any=16 ,							SCREAMING_SNAKE_CASE_     :   Tuple=4_096 ,							SCREAMING_SNAKE_CASE_     :   str="gelu" ,							SCREAMING_SNAKE_CASE_     :   List[str]=0.1 ,							SCREAMING_SNAKE_CASE_     :   Tuple=0.1 ,							SCREAMING_SNAKE_CASE_     :   List[Any]=512 ,							SCREAMING_SNAKE_CASE_     :   List[Any]=0.02 ,							SCREAMING_SNAKE_CASE_     :   Union[str, Any]=1e-12 ,							SCREAMING_SNAKE_CASE_     :   List[Any]=0 ,							SCREAMING_SNAKE_CASE_     :   Union[str, Any]=2 ,							SCREAMING_SNAKE_CASE_     :   int=1 ,							SCREAMING_SNAKE_CASE_     :   str="absolute" ,							SCREAMING_SNAKE_CASE_     :   Tuple=True ,							**SCREAMING_SNAKE_CASE_     :   str ,							):
											super().__init__(pad_token_id=SCREAMING_SNAKE_CASE_ ,							bos_token_id=SCREAMING_SNAKE_CASE_ ,							eos_token_id=SCREAMING_SNAKE_CASE_ ,							**SCREAMING_SNAKE_CASE_	)

											lowerCAmelCase__      			=						vocab_size
											lowerCAmelCase__      			=						hidden_size
											lowerCAmelCase__      			=						num_hidden_layers
											lowerCAmelCase__      			=						num_attention_heads
											lowerCAmelCase__      			=						hidden_act
											lowerCAmelCase__      			=						intermediate_size
											lowerCAmelCase__      			=						hidden_dropout_prob
											lowerCAmelCase__      			=						attention_probs_dropout_prob
											lowerCAmelCase__      			=						max_position_embeddings
											lowerCAmelCase__      			=						initializer_range
											lowerCAmelCase__      			=						layer_norm_eps
											lowerCAmelCase__      			=						position_embedding_type
											lowerCAmelCase__      			=						use_cache





