



from __future__ import annotations

import math



def __lowerCAmelCase	(       SCREAMING_SNAKE_CASE_  ,					SCREAMING_SNAKE_CASE_					) ->    list:
			if len(SCREAMING_SNAKE_CASE_					) != 2 or len(a[0]					) != 2 or len(SCREAMING_SNAKE_CASE_					) != 2 or len(b[0]					) != 2:
						raise Exception("Matrices are not 2x2"					)
			lowercase__   					=			[
			    [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	(       SCREAMING_SNAKE_CASE_  ,					SCREAMING_SNAKE_CASE_					) ->    Union[str, Any]:
			return [
			    [matrix_a[row][col] + matrix_b[row][col] for col in range(len(matrix_a[row]					)					)]
			    for row in range(len(SCREAMING_SNAKE_CASE_					)					)
			]



def __lowerCAmelCase	(       SCREAMING_SNAKE_CASE_  ,					SCREAMING_SNAKE_CASE_					) ->    Optional[int]:
			return [
			    [matrix_a[row][col] - matrix_b[row][col] for col in range(len(matrix_a[row]					)					)]
			    for row in range(len(SCREAMING_SNAKE_CASE_					)					)
			]



def __lowerCAmelCase	(       SCREAMING_SNAKE_CASE_					) ->    tuple[list, list, list, list]:
			if len(SCREAMING_SNAKE_CASE_					) % 2 != 0 or len(a[0]					) % 2 != 0:
						raise Exception("Odd matrices are not supported!"					)

			lowercase__   					=			len(SCREAMING_SNAKE_CASE_					)
			lowercase__   					=			matrix_length // 2

			lowercase__   					=			[[a[i][j] for j in range(SCREAMING_SNAKE_CASE_  ,					SCREAMING_SNAKE_CASE_					)] for i in range(SCREAMING_SNAKE_CASE_					)]
			lowercase__   					=			[
			    [a[i][j] for j in range(SCREAMING_SNAKE_CASE_  ,					SCREAMING_SNAKE_CASE_					)] for i in range(SCREAMING_SNAKE_CASE_  ,					SCREAMING_SNAKE_CASE_					)
			]

			lowercase__   					=			[[a[i][j] for j in range(SCREAMING_SNAKE_CASE_					)] for i in range(SCREAMING_SNAKE_CASE_					)]
			lowercase__   					=			[[a[i][j] for j in range(SCREAMING_SNAKE_CASE_					)] for i in range(SCREAMING_SNAKE_CASE_  ,					SCREAMING_SNAKE_CASE_					)]

			return top_left, top_right, bot_left, bot_right



def __lowerCAmelCase	(       SCREAMING_SNAKE_CASE_					) ->    tuple[int, int]:
			return len(SCREAMING_SNAKE_CASE_					), len(matrix[0]					)



def __lowerCAmelCase	(       SCREAMING_SNAKE_CASE_					) ->    None:
			print("\n".join(str(SCREAMING_SNAKE_CASE_					) for line in matrix					)					)



def __lowerCAmelCase	(       SCREAMING_SNAKE_CASE_  ,					SCREAMING_SNAKE_CASE_					) ->    list:
			if matrix_dimensions(SCREAMING_SNAKE_CASE_					) == (2, 2):
						return default_matrix_multiplication(SCREAMING_SNAKE_CASE_  ,					SCREAMING_SNAKE_CASE_					)

			lowercase__					,    lowercase__					,    lowercase__					,    lowercase__   					=			split_matrix(SCREAMING_SNAKE_CASE_					)
			lowercase__					,    lowercase__					,    lowercase__					,    lowercase__   					=			split_matrix(SCREAMING_SNAKE_CASE_					)

			lowercase__   					=			actual_strassen(SCREAMING_SNAKE_CASE_  ,					matrix_subtraction(SCREAMING_SNAKE_CASE_  ,					SCREAMING_SNAKE_CASE_					)					)
			lowercase__   					=			actual_strassen(matrix_addition(SCREAMING_SNAKE_CASE_  ,					SCREAMING_SNAKE_CASE_					)  ,					SCREAMING_SNAKE_CASE_					)
			lowercase__   					=			actual_strassen(matrix_addition(SCREAMING_SNAKE_CASE_  ,					SCREAMING_SNAKE_CASE_					)  ,					SCREAMING_SNAKE_CASE_					)
			lowercase__   					=			actual_strassen(SCREAMING_SNAKE_CASE_  ,					matrix_subtraction(SCREAMING_SNAKE_CASE_  ,					SCREAMING_SNAKE_CASE_					)					)
			lowercase__   					=			actual_strassen(matrix_addition(SCREAMING_SNAKE_CASE_  ,					SCREAMING_SNAKE_CASE_					)  ,					matrix_addition(SCREAMING_SNAKE_CASE_  ,					SCREAMING_SNAKE_CASE_					)					)
			lowercase__   					=			actual_strassen(matrix_subtraction(SCREAMING_SNAKE_CASE_  ,					SCREAMING_SNAKE_CASE_					)  ,					matrix_addition(SCREAMING_SNAKE_CASE_  ,					SCREAMING_SNAKE_CASE_					)					)
			lowercase__   					=			actual_strassen(matrix_subtraction(SCREAMING_SNAKE_CASE_  ,					SCREAMING_SNAKE_CASE_					)  ,					matrix_addition(SCREAMING_SNAKE_CASE_  ,					SCREAMING_SNAKE_CASE_					)					)

			lowercase__   					=			matrix_addition(matrix_subtraction(matrix_addition(SCREAMING_SNAKE_CASE_  ,					SCREAMING_SNAKE_CASE_					)  ,					SCREAMING_SNAKE_CASE_					)  ,					SCREAMING_SNAKE_CASE_					)
			lowercase__   					=			matrix_addition(SCREAMING_SNAKE_CASE_  ,					SCREAMING_SNAKE_CASE_					)
			lowercase__   					=			matrix_addition(SCREAMING_SNAKE_CASE_  ,					SCREAMING_SNAKE_CASE_					)
			lowercase__   					=			matrix_subtraction(matrix_subtraction(matrix_addition(SCREAMING_SNAKE_CASE_  ,					SCREAMING_SNAKE_CASE_					)  ,					SCREAMING_SNAKE_CASE_					)  ,					SCREAMING_SNAKE_CASE_					)

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



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

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

			lowercase__   					=			max(*SCREAMING_SNAKE_CASE_  ,					*SCREAMING_SNAKE_CASE_					)
			lowercase__   					=			int(math.pow(2  ,					math.ceil(math.loga(SCREAMING_SNAKE_CASE_					)					)					)					)
			lowercase__   					=			matrixa
			lowercase__   					=			matrixa

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

			lowercase__   					=			actual_strassen(SCREAMING_SNAKE_CASE_  ,					SCREAMING_SNAKE_CASE_					)

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


if __name__ == "__main__":
							lowercase_						=       [
							    [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],
							]
							lowercase_						=       [[0, 2, 1, 1], [16, 2, 3, 3], [2, 2, 7, 7], [13, 11, 22, 4]]
							print(strassen(matrixa, matrixa))









from ...utils import (
    OptionalDependencyNotAvailable,
    is_torch_available,
    is_transformers_available,
    is_transformers_version,
)


try:
							if not (is_transformers_available() and is_torch_available() and is_transformers_version(""">=""", """4.25.0""")):
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							from ...utils.dummy_torch_and_transformers_objects import (
							    VersatileDiffusionDualGuidedPipeline,
							    VersatileDiffusionImageVariationPipeline,
							    VersatileDiffusionPipeline,
							    VersatileDiffusionTextToImagePipeline,
							)
else:
							from .modeling_text_unet import UNetFlatConditionModel
							from .pipeline_versatile_diffusion import VersatileDiffusionPipeline
							from .pipeline_versatile_diffusion_dual_guided import VersatileDiffusionDualGuidedPipeline
							from .pipeline_versatile_diffusion_image_variation import VersatileDiffusionImageVariationPipeline
							from .pipeline_versatile_diffusion_text_to_image import VersatileDiffusionTextToImagePipeline




