



'''simple docstring'''



from collections import OrderedDict
from typing import Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices


lowerCAmelCase	:		Union[str, Any]				=   logging.get_logger(__name__)

lowerCAmelCase	:		int				=   {
    '''microsoft/swin-tiny-patch4-window7-224''': (
        '''https://huggingface.co/microsoft/swin-tiny-patch4-window7-224/resolve/main/config.json'''
    ),
    # See all Swin models at https://huggingface.co/models?filter=swin
}






class 					UpperCAmelCase__	(		__a							,       __a      ):
					a      :     List[str]        =							'''swin'''

					a      :     str        =							{
					    '''num_attention_heads''': '''num_heads''',
					    '''num_hidden_layers''': '''num_layers''',
					}



					def __init__(    self			,				UpperCamelCase=224			,				UpperCamelCase=4			,				UpperCamelCase=3			,				UpperCamelCase=96			,				UpperCamelCase=[2, 2, 6, 2]			,				UpperCamelCase=[3, 6, 12, 24]			,				UpperCamelCase=7			,				UpperCamelCase=4.0			,				UpperCamelCase=True			,				UpperCamelCase=0.0			,				UpperCamelCase=0.0			,				UpperCamelCase=0.1			,				UpperCamelCase="gelu"			,				UpperCamelCase=False			,				UpperCamelCase=0.02			,				UpperCamelCase=1E-5			,				UpperCamelCase=32			,				UpperCamelCase=None			,				UpperCamelCase=None			,				**UpperCamelCase			,				)     ->			Tuple:
						super().__init__(**snake_case__     )

						__lowerCAmelCase												=  image_size
						__lowerCAmelCase												=  patch_size
						__lowerCAmelCase												=  num_channels
						__lowerCAmelCase												=  embed_dim
						__lowerCAmelCase												=  depths
						__lowerCAmelCase												=  len(snake_case__     )
						__lowerCAmelCase												=  num_heads
						__lowerCAmelCase												=  window_size
						__lowerCAmelCase												=  mlp_ratio
						__lowerCAmelCase												=  qkv_bias
						__lowerCAmelCase												=  hidden_dropout_prob
						__lowerCAmelCase												=  attention_probs_dropout_prob
						__lowerCAmelCase												=  drop_path_rate
						__lowerCAmelCase												=  hidden_act
						__lowerCAmelCase												=  use_absolute_embeddings
						__lowerCAmelCase												=  layer_norm_eps
						__lowerCAmelCase												=  initializer_range
						__lowerCAmelCase												=  encoder_stride
						# we set the hidden_size attribute in order to make Swin work with VisionEncoderDecoderModel
						# this indicates the channel dimension after the last stage of the model
						__lowerCAmelCase												=  int(embed_dim * 2 ** (len(snake_case__     ) - 1)     )
						__lowerCAmelCase												=  ["stem"] + [F'''stage{idx}''' for idx in range(1			,				len(snake_case__     ) + 1     )]
						__lowerCAmelCase							,       __lowerCAmelCase												=  get_aligned_output_features_output_indices(
						    out_features=snake_case__			,				out_indices=snake_case__			,				stage_names=self.stage_names     )






class 					UpperCAmelCase__	(		__a      ):
					a      :     Dict        =							version.parse("""1.11"""      )



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



					@property
					def        UpperCAmelCase_ (    self     )     ->			Optional[int]:
						return 1E-4




'''simple docstring'''



from __future__ import annotations

import math



def   __lowerCAmelCase					(							lowerCamelCase   :						list				,		lowerCamelCase   :						list					):






	'''simple docstring'''




	if len(lowerCamelCase					) != 2 or len(a[0]					) != 2 or len(lowerCamelCase					) != 2 or len(b[0]					) != 2:
		raise Exception("Matrices are not 2x2"					)
	__lowerCAmelCase												=  [
	    [a[0][0] * b[0][0] + a[0][1] * b[1][0], a[0][0] * b[0][1] + a[0][1] * b[1][1]],
	    [a[1][0] * b[0][0] + a[1][1] * b[1][0], a[1][0] * b[0][1] + a[1][1] * b[1][1]],
	]
	return new_matrix



def   __lowerCAmelCase					(							lowerCamelCase   :						list				,		lowerCamelCase   :						list					):






	'''simple docstring'''




	return [
	    [matrix_a[row][col] + matrix_b[row][col] for col in range(len(matrix_a[row]					)					)]
	    for row in range(len(lowerCamelCase					)					)
	]



def   __lowerCAmelCase					(							lowerCamelCase   :						list				,		lowerCamelCase   :						list					):






	'''simple docstring'''




	return [
	    [matrix_a[row][col] - matrix_b[row][col] for col in range(len(matrix_a[row]					)					)]
	    for row in range(len(lowerCamelCase					)					)
	]



def   __lowerCAmelCase					(							lowerCamelCase   :						list					):






	'''simple docstring'''




	if len(lowerCamelCase					) % 2 != 0 or len(a[0]					) % 2 != 0:
		raise Exception("Odd matrices are not supported!"					)

	__lowerCAmelCase												=  len(lowerCamelCase					)
	__lowerCAmelCase												=  matrix_length // 2

	__lowerCAmelCase												=  [[a[i][j] for j in range(lowerCamelCase				,		lowerCamelCase					)] for i in range(lowerCamelCase					)]
	__lowerCAmelCase												=  [
	    [a[i][j] for j in range(lowerCamelCase				,		lowerCamelCase					)] for i in range(lowerCamelCase				,		lowerCamelCase					)
	]

	__lowerCAmelCase												=  [[a[i][j] for j in range(lowerCamelCase					)] for i in range(lowerCamelCase					)]
	__lowerCAmelCase												=  [[a[i][j] for j in range(lowerCamelCase					)] for i in range(lowerCamelCase				,		lowerCamelCase					)]

	return top_left, top_right, bot_left, bot_right



def   __lowerCAmelCase					(							lowerCamelCase   :						list					):






	'''simple docstring'''




	return len(lowerCamelCase					), len(matrix[0]					)



def   __lowerCAmelCase					(							lowerCamelCase   :						list					):






	'''simple docstring'''




	print("\n".join(str(lowerCamelCase					) for line in matrix					)					)



def   __lowerCAmelCase					(							lowerCamelCase   :						list				,		lowerCamelCase   :						list					):






	'''simple docstring'''




	if matrix_dimensions(lowerCamelCase					) == (2, 2):
		return default_matrix_multiplication(lowerCamelCase				,		lowerCamelCase					)

	__lowerCAmelCase							,       __lowerCAmelCase							,       __lowerCAmelCase							,       __lowerCAmelCase												=  split_matrix(lowerCamelCase					)
	__lowerCAmelCase							,       __lowerCAmelCase							,       __lowerCAmelCase							,       __lowerCAmelCase												=  split_matrix(lowerCamelCase					)

	__lowerCAmelCase												=  actual_strassen(lowerCamelCase				,		matrix_subtraction(lowerCamelCase				,		lowerCamelCase					)					)
	__lowerCAmelCase												=  actual_strassen(matrix_addition(lowerCamelCase				,		lowerCamelCase					)				,		lowerCamelCase					)
	__lowerCAmelCase												=  actual_strassen(matrix_addition(lowerCamelCase				,		lowerCamelCase					)				,		lowerCamelCase					)
	__lowerCAmelCase												=  actual_strassen(lowerCamelCase				,		matrix_subtraction(lowerCamelCase				,		lowerCamelCase					)					)
	__lowerCAmelCase												=  actual_strassen(matrix_addition(lowerCamelCase				,		lowerCamelCase					)				,		matrix_addition(lowerCamelCase				,		lowerCamelCase					)					)
	__lowerCAmelCase												=  actual_strassen(matrix_subtraction(lowerCamelCase				,		lowerCamelCase					)				,		matrix_addition(lowerCamelCase				,		lowerCamelCase					)					)
	__lowerCAmelCase												=  actual_strassen(matrix_subtraction(lowerCamelCase				,		lowerCamelCase					)				,		matrix_addition(lowerCamelCase				,		lowerCamelCase					)					)

	__lowerCAmelCase												=  matrix_addition(matrix_subtraction(matrix_addition(lowerCamelCase				,		lowerCamelCase					)				,		lowerCamelCase					)				,		lowerCamelCase					)
	__lowerCAmelCase												=  matrix_addition(lowerCamelCase				,		lowerCamelCase					)
	__lowerCAmelCase												=  matrix_addition(lowerCamelCase				,		lowerCamelCase					)
	__lowerCAmelCase												=  matrix_subtraction(matrix_subtraction(matrix_addition(lowerCamelCase				,		lowerCamelCase					)				,		lowerCamelCase					)				,		lowerCamelCase					)

	# construct the new matrix from our 4 quadrants
	__lowerCAmelCase												=  []
	for i in range(len(lowerCamelCase					)					):
		new_matrix.append(top_left[i] + top_right[i]					)
	for i in range(len(lowerCamelCase					)					):
		new_matrix.append(bot_left[i] + bot_right[i]					)
	return new_matrix



def   __lowerCAmelCase					(							lowerCamelCase   :						list				,		lowerCamelCase   :						list					):






	'''simple docstring'''




	if matrix_dimensions(lowerCamelCase					)[1] != matrix_dimensions(lowerCamelCase					)[0]:
		__lowerCAmelCase												=  (
		    "Unable to multiply these matrices, please check the dimensions.\n"
		    f'''Matrix A: {matrixa}\n'''
		    f'''Matrix B: {matrixa}'''
		)
		raise Exception(lowerCamelCase					)
	__lowerCAmelCase												=  matrix_dimensions(lowerCamelCase					)
	__lowerCAmelCase												=  matrix_dimensions(lowerCamelCase					)

	if dimensiona[0] == dimensiona[1] and dimensiona[0] == dimensiona[1]:
		return [matrixa, matrixa]

	__lowerCAmelCase												=  max(*lowerCamelCase				,		*lowerCamelCase					)
	__lowerCAmelCase												=  int(math.pow(2				,		math.ceil(math.loga(lowerCamelCase					)					)					)					)
	__lowerCAmelCase												=  matrixa
	__lowerCAmelCase												=  matrixa

	# Adding zeros to the matrices so that the arrays dimensions are the same and also
	# power of 2
	for i in range(0				,		lowerCamelCase					):
		if i < dimensiona[0]:
			for _ in range(dimensiona[1]				,		lowerCamelCase					):
				new_matrixa[i].append(0					)
		else:
			new_matrixa.append([0] * maxim					)
		if i < dimensiona[0]:
			for _ in range(dimensiona[1]				,		lowerCamelCase					):
				new_matrixa[i].append(0					)
		else:
			new_matrixa.append([0] * maxim					)

	__lowerCAmelCase												=  actual_strassen(lowerCamelCase				,		lowerCamelCase					)

	# Removing the additional zeros
	for i in range(0				,		lowerCamelCase					):
		if i < dimensiona[0]:
			for _ in range(dimensiona[1]				,		lowerCamelCase					):
				final_matrix[i].pop()
		else:
			final_matrix.pop()
	return final_matrix


if __name__ == "__main__":
	lowerCAmelCase	:		Tuple				=   [
	    [2, 3, 4, 5],
	    [6, 4, 3, 1],
	    [2, 3, 6, 7],
	    [3, 1, 2, 4],
	    [2, 3, 4, 5],
	    [6, 4, 3, 1],
	    [2, 3, 6, 7],
	    [3, 1, 2, 4],
	    [2, 3, 4, 5],
	    [6, 2, 3, 1],
	]
	lowerCAmelCase	:		Any				=   [[0, 2, 1, 1], [1_6, 2, 3, 3], [2, 2, 7, 7], [1_3, 1_1, 2_2, 4]]
	print(strassen(matrixa, matrixa))