from __future__ import annotations

from decimal import Decimal

from numpy import array

def   SCREAMING_SNAKE_CASE_	(		snake_case__				)	->      int:
							lowerCAmelCase      						=						Decimal

							# Check if the provided matrix has 2 rows and 2 columns
							# since this implementation only works for 2x2 matrices
							if len(snake_case__				) == 2 and len(matrix[0]				) == 2 and len(matrix[1]				) == 2:
														# Calculate the determinant of the matrix
														lowerCAmelCase      						=						float(
														    d(matrix[0][0]				) * d(matrix[1][1]				) - d(matrix[1][0]				) * d(matrix[0][1]				)				)
														if determinant == 0:
																					raise ValueError('''This matrix has no inverse.'''				)

														# Creates a copy of the matrix with swapped positions of the elements
														lowerCAmelCase      						=						[[0.0, 0.0], [0.0, 0.0]]
														lowerCAmelCase      						=						matrix[1][1], matrix[0][0]
														lowerCAmelCase      						=						-matrix[1][0], -matrix[0][1]

														# Calculate the inverse of the matrix
														return [
														    [(float(d(snake_case__				)				) / determinant) or 0.0 for n in row] for row in swapped_matrix
														]
							elif (
							    len(snake_case__				) == 3
							    and len(matrix[0]				) == 3
							    and len(matrix[1]				) == 3
							    and len(matrix[2]				) == 3
							):
														# Calculate the determinant of the matrix using Sarrus rule
														lowerCAmelCase      						=						float(
														    (
														        (d(matrix[0][0]				) * d(matrix[1][1]				) * d(matrix[2][2]				))
														        + (d(matrix[0][1]				) * d(matrix[1][2]				) * d(matrix[2][0]				))
														        + (d(matrix[0][2]				) * d(matrix[1][0]				) * d(matrix[2][1]				))
														    )
														    - (
														        (d(matrix[0][2]				) * d(matrix[1][1]				) * d(matrix[2][0]				))
														        + (d(matrix[0][1]				) * d(matrix[1][0]				) * d(matrix[2][2]				))
														        + (d(matrix[0][0]				) * d(matrix[1][2]				) * d(matrix[2][1]				))
														    )				)
														if determinant == 0:
																					raise ValueError('''This matrix has no inverse.'''				)

														# Creating cofactor matrix
														lowerCAmelCase      						=						[
														    [d(0.0				), d(0.0				), d(0.0				)],
														    [d(0.0				), d(0.0				), d(0.0				)],
														    [d(0.0				), d(0.0				), d(0.0				)],
														]
														lowerCAmelCase      						=						(d(matrix[1][1]				) * d(matrix[2][2]				)) - (
														    d(matrix[1][2]				) * d(matrix[2][1]				)
														)
														lowerCAmelCase      						=						-(
														    (d(matrix[1][0]				) * d(matrix[2][2]				)) - (d(matrix[1][2]				) * d(matrix[2][0]				))
														)
														lowerCAmelCase      						=						(d(matrix[1][0]				) * d(matrix[2][1]				)) - (
														    d(matrix[1][1]				) * d(matrix[2][0]				)
														)
														lowerCAmelCase      						=						-(
														    (d(matrix[0][1]				) * d(matrix[2][2]				)) - (d(matrix[0][2]				) * d(matrix[2][1]				))
														)
														lowerCAmelCase      						=						(d(matrix[0][0]				) * d(matrix[2][2]				)) - (
														    d(matrix[0][2]				) * d(matrix[2][0]				)
														)
														lowerCAmelCase      						=						-(
														    (d(matrix[0][0]				) * d(matrix[2][1]				)) - (d(matrix[0][1]				) * d(matrix[2][0]				))
														)
														lowerCAmelCase      						=						(d(matrix[0][1]				) * d(matrix[1][2]				)) - (
														    d(matrix[0][2]				) * d(matrix[1][1]				)
														)
														lowerCAmelCase      						=						-(
														    (d(matrix[0][0]				) * d(matrix[1][2]				)) - (d(matrix[0][2]				) * d(matrix[1][0]				))
														)
														lowerCAmelCase      						=						(d(matrix[0][0]				) * d(matrix[1][1]				)) - (
														    d(matrix[0][1]				) * d(matrix[1][0]				)
														)

														# Transpose the cofactor matrix (Adjoint matrix)
														lowerCAmelCase      						=						array(snake_case__				)
														for i in range(3				):
																					for j in range(3				):
																												lowerCAmelCase      						=						cofactor_matrix[j][i]

        # Inverse of the matrix using the formula (1/determinant) * adjoint matrix
														lowerCAmelCase      						=						array(snake_case__				)
														for i in range(3				):
																					for j in range(3				):
																												inverse_matrix[i][j] /= d(snake_case__				)

        # Calculate the inverse of the matrix
														return [[float(d(snake_case__				)				) or 0.0 for n in row] for row in inverse_matrix]
							raise ValueError('''Please provide a matrix of size 2x2 or 3x3.'''				)




from collections import OrderedDict
from typing import List, Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


a  :      Optional[int]            =    logging.get_logger(__name__)

a  :      Optional[Any]            =    {
    """google/efficientnet-b7""": """https://huggingface.co/google/efficientnet-b7/resolve/main/config.json""",
}

class 					_lowercase    (     UpperCAmelCase__			):






    '''simple docstring'''
    SCREAMING_SNAKE_CASE:				Dict          =    'efficientnet'




    def __init__(    self       ,						lowerCamelCase__ = 3       ,						lowerCamelCase__ = 600       ,						lowerCamelCase__ = 2.0       ,						lowerCamelCase__ = 3.1       ,						lowerCamelCase__ = 8       ,						lowerCamelCase__ = [3, 3, 5, 3, 5, 5, 3]       ,						lowerCamelCase__ = [32, 16, 24, 40, 80, 112, 192]       ,						lowerCamelCase__ = [16, 24, 40, 80, 112, 192, 320]       ,						lowerCamelCase__ = []       ,						lowerCamelCase__ = [1, 2, 2, 2, 1, 2, 1]       ,						lowerCamelCase__ = [1, 2, 2, 3, 3, 4, 1]       ,						lowerCamelCase__ = [1, 6, 6, 6, 6, 6, 6]       ,						lowerCamelCase__ = 0.2_5       ,						lowerCamelCase__ = "swish"       ,						lowerCamelCase__ = 2_560       ,						lowerCamelCase__ = "mean"       ,						lowerCamelCase__ = 0.0_2       ,						lowerCamelCase__ = 0.0_0_1       ,						lowerCamelCase__ = 0.9_9       ,						lowerCamelCase__ = 0.5       ,						lowerCamelCase__ = 0.2       ,						**lowerCamelCase__       ,						):
       super().__init__(**lowerCamelCase__ )

       lowerCAmelCase_:							str       =	num_channels
       lowerCAmelCase_:							str       =	image_size
       lowerCAmelCase_:							int       =	width_coefficient
       lowerCAmelCase_:							Union[str, Any]       =	depth_coefficient
       lowerCAmelCase_:							int       =	depth_divisor
       lowerCAmelCase_:							List[str]       =	kernel_sizes
       lowerCAmelCase_:							Tuple       =	in_channels
       lowerCAmelCase_:							List[str]       =	out_channels
       lowerCAmelCase_:							List[str]       =	depthwise_padding
       lowerCAmelCase_:							Optional[int]       =	strides
       lowerCAmelCase_:							List[str]       =	num_block_repeats
       lowerCAmelCase_:							Any       =	expand_ratios
       lowerCAmelCase_:							List[Any]       =	squeeze_expansion_ratio
       lowerCAmelCase_:							Optional[int]       =	hidden_act
       lowerCAmelCase_:							Optional[int]       =	hidden_dim
       lowerCAmelCase_:							Dict       =	pooling_type
       lowerCAmelCase_:							Optional[Any]       =	initializer_range
       lowerCAmelCase_:							int       =	batch_norm_eps
       lowerCAmelCase_:							List[str]       =	batch_norm_momentum
       lowerCAmelCase_:							List[Any]       =	dropout_rate
       lowerCAmelCase_:							Union[str, Any]       =	drop_connect_rate
       lowerCAmelCase_:							Tuple       =	sum(lowerCamelCase__ ) * 4





class 					_lowercase    (     UpperCAmelCase__			):






    '''simple docstring'''
    SCREAMING_SNAKE_CASE:				Optional[Any]          =    version.parse('1.11'			)




    @property
    def      _a    (    self ):
       return OrderedDict(
           [
               ("pixel_values", {0: "batch", 1: "num_channels", 2: "height", 3: "width"}),
           ] )




    @property
    def      _a    (    self ):
       return 1E-5