






from __future__ import annotations

from typing import Any


def     _a					(       *UpperCamelCase_   :			list[list[int]]				)	->				list[list[int]]:
						"""simple docstring"""







						if all(_check_not_integer(UpperCamelCase_				) for m in matrix_s				):
												for i in matrix_s[1:]:
																		_verify_matrix_sizes(matrix_s[0]      ,				UpperCamelCase_				)
												return [[sum(UpperCamelCase_				) for t in zip(*UpperCamelCase_				)] for m in zip(*UpperCamelCase_				)]
						raise TypeError("Expected a matrix, got int/list instead"				)


def     _a					(       UpperCamelCase_   :			list[list[int]]      ,				UpperCamelCase_   :			list[list[int]]				)	->				list[list[int]]:
						"""simple docstring"""







						if (
						    _check_not_integer(UpperCamelCase_				)
						    and _check_not_integer(UpperCamelCase_				)
						    and _verify_matrix_sizes(UpperCamelCase_      ,				UpperCamelCase_				)
						):
												return [[i - j for i, j in zip(*UpperCamelCase_				)] for m in zip(UpperCamelCase_      ,				UpperCamelCase_				)]
						raise TypeError("Expected a matrix, got int/list instead"				)


def     _a					(       UpperCamelCase_   :			list[list[int]]      ,				UpperCamelCase_   :			int | float				)	->				list[list[float]]:
						"""simple docstring"""







						return [[x * n for x in row] for row in matrix]


def     _a					(       UpperCamelCase_   :			list[list[int]]      ,				UpperCamelCase_   :			list[list[int]]				)	->				list[list[int]]:
						"""simple docstring"""







						if _check_not_integer(UpperCamelCase_				) and _check_not_integer(UpperCamelCase_				):
												lowerCAmelCase__ ,							lowerCAmelCase__	 =  _verify_matrix_sizes(UpperCamelCase_      ,				UpperCamelCase_				)

						if cols[0] != rows[1]:
												lowerCAmelCase__	 =  (
												    "Cannot multiply matrix of dimensions "
												    F"({rows[0]},{cols[0]}) and ({rows[1]},{cols[1]})"
												)
												raise ValueError(UpperCamelCase_				)
						return [
						    [sum(m * n for m, n in zip(UpperCamelCase_      ,				UpperCamelCase_				)				) for j in zip(*UpperCamelCase_				)] for i in matrix_a
						]


def     _a					(       UpperCamelCase_   :			int				)	->				list[list[int]]:
						"""simple docstring"""







						lowerCAmelCase__	 =  int(UpperCamelCase_				)
						return [[int(row == column				) for column in range(UpperCamelCase_				)] for row in range(UpperCamelCase_				)]


def     _a					(       UpperCamelCase_   :			list[list[int]]      ,				UpperCamelCase_   :			bool = True				)	->				list[list[int]] | map[list[int]]:
						"""simple docstring"""







						if _check_not_integer(UpperCamelCase_				):
												if return_map:
																		return map(UpperCamelCase_      ,				zip(*UpperCamelCase_				)				)
												else:
																		return list(map(UpperCamelCase_      ,				zip(*UpperCamelCase_				)				)				)
						raise TypeError("Expected a matrix, got int/list instead"				)


def     _a					(       UpperCamelCase_   :			list[list[int]]      ,				UpperCamelCase_   :			int      ,				UpperCamelCase_   :			int				)	->				list[list[int]]:
						"""simple docstring"""







						lowerCAmelCase__	 =  matrix[:row] + matrix[row + 1 :]
						return [row[:column] + row[column + 1 :] for row in minor]


def     _a					(       UpperCamelCase_   :			list[list[int]]				)	->				Any:
						"""simple docstring"""







						if len(UpperCamelCase_				) == 1:
												return matrix[0][0]

						return sum(
						    x * determinant(minor(UpperCamelCase_      ,				0      ,				UpperCamelCase_				)				) * (-1) ** i
						    for i, x in enumerate(matrix[0]				)				)


def     _a					(       UpperCamelCase_   :			list[list[int]]				)	->				list[list[float]] | None:
						"""simple docstring"""







						lowerCAmelCase__	 =  determinant(UpperCamelCase_				)
						if det == 0:
												return None

						lowerCAmelCase__	 =  [
						    [determinant(minor(UpperCamelCase_      ,				UpperCamelCase_      ,				UpperCamelCase_				)				) for j in range(len(UpperCamelCase_				)				)]
						    for i in range(len(UpperCamelCase_				)				)
						]

						lowerCAmelCase__	 =  [
						    [x * (-1) ** (row + col) for col, x in enumerate(matrix_minor[row]				)]
						    for row in range(len(UpperCamelCase_				)				)
						]
						lowerCAmelCase__	 =  list(transpose(UpperCamelCase_				)				)
						return scalar_multiply(UpperCamelCase_      ,				1 / det				)


def     _a					(       UpperCamelCase_   :			list[list[int]]				)	->				bool:
						"""simple docstring"""







						return not isinstance(UpperCamelCase_      ,				UpperCamelCase_				) and not isinstance(matrix[0]      ,				UpperCamelCase_				)


def     _a					(       UpperCamelCase_   :			list[list[int]]				)	->				tuple[int, int]:
						"""simple docstring"""







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


def     _a					(       UpperCamelCase_   :			list[list[int]]      ,				UpperCamelCase_   :			list[list[int]]				)	->				tuple[tuple[int, int], tuple[int, int]]:
						"""simple docstring"""







						lowerCAmelCase__	 =  _shape(UpperCamelCase_				) + _shape(UpperCamelCase_				)
						if shape[0] != shape[3] or shape[1] != shape[2]:
												lowerCAmelCase__	 =  (
												    "operands could not be broadcast together with shape "
												    F"({shape[0], shape[1]}), ({shape[2], shape[3]})"
												)
												raise ValueError(UpperCamelCase_				)
						return (shape[0], shape[2]), (shape[1], shape[3])


def     _a					(       )	->				None:
						"""simple docstring"""







						lowerCAmelCase__	 =  [[12, 10], [3, 9]]
						lowerCAmelCase__	 =  [[3, 4], [7, 4]]
						lowerCAmelCase__	 =  [[11, 12, 13, 14], [21, 22, 23, 24], [31, 32, 33, 34], [41, 42, 43, 44]]
						lowerCAmelCase__	 =  [[3, 0, 2], [2, 0, -2], [0, 1, 1]]
						print(F"Add Operation, {add(UpperCamelCase_      ,				UpperCamelCase_				) = } \n"				)
						print(
						    F"Multiply Operation, {multiply(UpperCamelCase_      ,				UpperCamelCase_				) = } \n"      ,				)
						print(F"Identity: {identity(5				)}\n"				)
						print(F"Minor of {matrix_c} = {minor(UpperCamelCase_      ,				1      ,				2				)} \n"				)
						print(F"Determinant of {matrix_b} = {determinant(UpperCamelCase_				)} \n"				)
						print(F"Inverse of {matrix_d} = {inverse(UpperCamelCase_				)}\n"				)


if __name__ == "__main__":
	import doctest

	doctest.testmod()
	main()














import unittest

import numpy as np
import PIL
import torch

from diffusers.image_processor import VaeImageProcessor


class        lowercase__       (     unittest.TestCase		):

	@property
	def 						UpperCAmelCase					(							self    )->   List[str]:







							'''simple docstring'''





							lowerCAmelCase__	 =  1
							lowerCAmelCase__	 =  3
							lowerCAmelCase__	 =  8
							lowerCAmelCase__	 =  8

							lowerCAmelCase__	 =  torch.rand((batch_size, num_channels, height, width)    )

							return sample

	def 						UpperCAmelCase					(							self						,      __UpperCAmelCase    )->   Dict:







							'''simple docstring'''





							if isinstance(image[0]						,      PIL.Image.Image    ):
													return np.stack([np.array(__UpperCAmelCase    ) for i in image]						,      axis=0    )
							elif isinstance(__UpperCAmelCase						,      torch.Tensor    ):
													return image.cpu().numpy().transpose(0						,      2						,      3						,      1    )
							return image

	def 						UpperCAmelCase					(							self    )->   Optional[int]:







							'''simple docstring'''





							lowerCAmelCase__	 =  VaeImageProcessor(do_resize=__UpperCAmelCase						,      do_normalize=__UpperCAmelCase    )

							lowerCAmelCase__	 =  self.dummy_sample
							lowerCAmelCase__	 =  self.to_np(__UpperCAmelCase    )

							for output_type in ["pt", "np", "pil"]:
													lowerCAmelCase__	 =  image_processor.postprocess(
													    image_processor.preprocess(__UpperCAmelCase    )						,      output_type=__UpperCAmelCase						,      )
													lowerCAmelCase__	 =  self.to_np(__UpperCAmelCase    )
													lowerCAmelCase__	 =  (input_np * 255).round() if output_type == "pil" else input_np
													assert (
													    np.abs(in_np - out_np    ).max() < 1E-6
													), F"decoded output does not match input for output_type {output_type}"

	def 						UpperCAmelCase					(							self    )->   int:







							'''simple docstring'''





							lowerCAmelCase__	 =  VaeImageProcessor(do_resize=__UpperCAmelCase						,      do_normalize=__UpperCAmelCase    )
							lowerCAmelCase__	 =  self.dummy_sample.cpu().numpy().transpose(0						,      2						,      3						,      1    )

							for output_type in ["pt", "np", "pil"]:
													lowerCAmelCase__	 =  image_processor.postprocess(image_processor.preprocess(__UpperCAmelCase    )						,      output_type=__UpperCAmelCase    )

													lowerCAmelCase__	 =  self.to_np(__UpperCAmelCase    )
													lowerCAmelCase__	 =  (input_np * 255).round() if output_type == "pil" else input_np
													assert (
													    np.abs(in_np - out_np    ).max() < 1E-6
													), F"decoded output does not match input for output_type {output_type}"

	def 						UpperCAmelCase					(							self    )->   Any:







							'''simple docstring'''





							lowerCAmelCase__	 =  VaeImageProcessor(do_resize=__UpperCAmelCase						,      do_normalize=__UpperCAmelCase    )

							lowerCAmelCase__	 =  self.dummy_sample.cpu().numpy().transpose(0						,      2						,      3						,      1    )
							lowerCAmelCase__	 =  image_processor.numpy_to_pil(__UpperCAmelCase    )

							for output_type in ["pt", "np", "pil"]:
													lowerCAmelCase__	 =  image_processor.postprocess(image_processor.preprocess(__UpperCAmelCase    )						,      output_type=__UpperCAmelCase    )
													for i, o in zip(__UpperCAmelCase						,      __UpperCAmelCase    ):
																			lowerCAmelCase__	 =  np.array(__UpperCAmelCase    )
																			lowerCAmelCase__	 =  self.to_np(__UpperCAmelCase    ) if output_type == "pil" else (self.to_np(__UpperCAmelCase    ) * 255).round()
																			assert (
																			    np.abs(in_np - out_np    ).max() < 1E-6
																			), F"decoded output does not match input for output_type {output_type}"

	def 						UpperCAmelCase					(							self    )->   Union[str, Any]:







							'''simple docstring'''





							lowerCAmelCase__	 =  VaeImageProcessor(do_resize=__UpperCAmelCase						,      do_normalize=__UpperCAmelCase    )

							lowerCAmelCase__	 =  self.dummy_sample
							lowerCAmelCase__	 =  input_pt_ad.squeeze(0    )

							lowerCAmelCase__	 =  image_processor.postprocess(
							    image_processor.preprocess(__UpperCAmelCase    )						,      output_type="np"						,      )
							lowerCAmelCase__	 =  image_processor.postprocess(
							    image_processor.preprocess(__UpperCAmelCase    )						,      output_type="np"						,      )

							lowerCAmelCase__	 =  self.to_np(self.dummy_sample    )
							lowerCAmelCase__	 =  input_np_ad.squeeze(0    )

							lowerCAmelCase__	 =  image_processor.postprocess(
							    image_processor.preprocess(__UpperCAmelCase    )						,      output_type="np"						,      )
							lowerCAmelCase__	 =  image_processor.postprocess(
							    image_processor.preprocess(__UpperCAmelCase    )						,      output_type="np"						,      )

							assert np.abs(out_pt_ad - out_pt_ad    ).max() < 1E-6
							assert np.abs(out_np_ad - out_np_ad    ).max() < 1E-6


	def 						UpperCAmelCase					(							self    )->   List[Any]:







							'''simple docstring'''





							lowerCAmelCase__	 =  VaeImageProcessor(do_resize=__UpperCAmelCase						,      do_normalize=__UpperCAmelCase    )

							lowerCAmelCase__	 =  self.dummy_sample
							lowerCAmelCase__	 =  list(__UpperCAmelCase    )

							lowerCAmelCase__	 =  image_processor.postprocess(
							    image_processor.preprocess(__UpperCAmelCase    )						,      output_type="np"						,      )

							lowerCAmelCase__	 =  image_processor.postprocess(
							    image_processor.preprocess(__UpperCAmelCase    )						,      output_type="np"						,      )

							lowerCAmelCase__	 =  self.to_np(self.dummy_sample    )
							list(__UpperCAmelCase    )

							lowerCAmelCase__	 =  image_processor.postprocess(
							    image_processor.preprocess(__UpperCAmelCase    )						,      output_type="np"						,      )

							lowerCAmelCase__	 =  image_processor.postprocess(
							    image_processor.preprocess(__UpperCAmelCase    )						,      output_type="np"						,      )

							assert np.abs(out_pt_ad - out_pt_list    ).max() < 1E-6
							assert np.abs(out_np_ad - out_np_list    ).max() < 1E-6






