'''simple docstring'''




from __future__ import annotations

import math

import numpy as np
from numpy.linalg import norm

def _lowercase	(      lowerCamelCase__							,    lowerCamelCase__						)					->       float:





       """simple docstring"""


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

def _lowercase	(      lowerCamelCase__							,    lowerCamelCase__						)					->       list[list[list[float] | float]]:





       """simple docstring"""


       if dataset.ndim != value_array.ndim:
              __UpperCAmelCase  :				int       				=		(
                  "Wrong input data's dimensions... "
                  f"""dataset : {dataset.ndim}, value_array : {value_array.ndim}"""
              )
              raise ValueError(lowerCamelCase__						)

       try:
              if dataset.shape[1] != value_array.shape[1]:
                     __UpperCAmelCase  :				Optional[int]       				=		(
                         "Wrong input data's shape... "
                         f"""dataset : {dataset.shape[1]}, value_array : {value_array.shape[1]}"""
                     )
                     raise ValueError(lowerCamelCase__						)
       except IndexError:
              if dataset.ndim != value_array.ndim:
                     raise TypeError("Wrong shape"						)

       if dataset.dtype != value_array.dtype:
              __UpperCAmelCase  :				List[Any]       				=		(
                  "Input data have different datatype... "
                  f"""dataset : {dataset.dtype}, value_array : {value_array.dtype}"""
              )
              raise TypeError(lowerCamelCase__						)

       __UpperCAmelCase  :				str       				=		[]

       for value in value_array:
              __UpperCAmelCase  :				int       				=		euclidean(lowerCamelCase__							,    dataset[0]						)
              __UpperCAmelCase  :				str       				=		dataset[0].tolist()

              for dataset_value in dataset[1:]:
                     __UpperCAmelCase  :				Optional[int]       				=		euclidean(lowerCamelCase__							,    lowerCamelCase__						)

                     if dist > temp_dist:
                            __UpperCAmelCase  :				List[str]       				=		temp_dist
                            __UpperCAmelCase  :				List[str]       				=		dataset_value.tolist()

              answer.append([vector, dist]						)

       return answer

def _lowercase	(      lowerCamelCase__							,    lowerCamelCase__						)					->       float:





       """simple docstring"""


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


if __name__ == "__main__":
   import doctest

   doctest.testmod()







'''simple docstring'''




from ...configuration_utils import PretrainedConfig
from ...utils import logging


_a   :	Any 							=   logging.get_logger(__name__)

_a   :	List[Any] 							=   {
    "microsoft/cvt-13": "https://huggingface.co/microsoft/cvt-13/resolve/main/config.json",
    # See all Cvt models at https://huggingface.co/models?filter=cvt
}






class 		__A       (__magic_name__   ):
       snake_case       :Any				    =					"cvt"






       def __init__(      self				,     UpperCamelCase_=3				,     UpperCamelCase_=[7, 3, 3]				,     UpperCamelCase_=[4, 2, 2]				,     UpperCamelCase_=[2, 1, 1]				,     UpperCamelCase_=[64, 1_92, 3_84]				,     UpperCamelCase_=[1, 3, 6]				,     UpperCamelCase_=[1, 2, 10]				,     UpperCamelCase_=[4.0, 4.0, 4.0]				,     UpperCamelCase_=[0.0, 0.0, 0.0]				,     UpperCamelCase_=[0.0, 0.0, 0.0]				,     UpperCamelCase_=[0.0, 0.0, 0.1]				,     UpperCamelCase_=[True, True, True]				,     UpperCamelCase_=[False, False, True]				,     UpperCamelCase_=["dw_bn", "dw_bn", "dw_bn"]				,     UpperCamelCase_=[3, 3, 3]				,     UpperCamelCase_=[1, 1, 1]				,     UpperCamelCase_=[2, 2, 2]				,     UpperCamelCase_=[1, 1, 1]				,     UpperCamelCase_=[1, 1, 1]				,     UpperCamelCase_=0.0_2				,     UpperCamelCase_=1E-12				,     **UpperCamelCase_				,     ):
              super().__init__(**UpperCamelCase_      )
              __UpperCAmelCase  :				Optional[int]       				=		num_channels
              __UpperCAmelCase  :				Optional[Any]       				=		patch_sizes
              __UpperCAmelCase  :				List[str]       				=		patch_stride
              __UpperCAmelCase  :				Tuple       				=		patch_padding
              __UpperCAmelCase  :				int       				=		embed_dim
              __UpperCAmelCase  :				str       				=		num_heads
              __UpperCAmelCase  :				Any       				=		depth
              __UpperCAmelCase  :				List[str]       				=		mlp_ratio
              __UpperCAmelCase  :				List[str]       				=		attention_drop_rate
              __UpperCAmelCase  :				Dict       				=		drop_rate
              __UpperCAmelCase  :				Dict       				=		drop_path_rate
              __UpperCAmelCase  :				str       				=		qkv_bias
              __UpperCAmelCase  :				Optional[int]       				=		cls_token
              __UpperCAmelCase  :				Optional[Any]       				=		qkv_projection_method
              __UpperCAmelCase  :				Tuple       				=		kernel_qkv
              __UpperCAmelCase  :				Optional[Any]       				=		padding_kv
              __UpperCAmelCase  :				Optional[int]       				=		stride_kv
              __UpperCAmelCase  :				Any       				=		padding_q
              __UpperCAmelCase  :				List[Any]       				=		stride_q
              __UpperCAmelCase  :				Union[str, Any]       				=		initializer_range
              __UpperCAmelCase  :				Any       				=		layer_norm_eps






