

"""simple docstring"""

from __future__ import annotations

from typing import Any



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



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



def 			SCREAMING_SNAKE_CASE       (   lowercase__				,				lowercase__      ) ->	list[list[float]]:
	return [[x * n for x in row] for row in matrix]



def 			SCREAMING_SNAKE_CASE       (   lowercase__				,				lowercase__      ) ->	list[list[int]]:
	if _check_not_integer(lowercase__      ) and _check_not_integer(lowercase__      ):
		lowerCAmelCase__      :							Union[str, Any]    =							_verify_matrix_sizes(lowercase__				,				lowercase__      )

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



def 			SCREAMING_SNAKE_CASE       (   lowercase__      ) ->	list[list[int]]:
	lowerCAmelCase__      :							List[str]    =							int(lowercase__      )
	return [[int(row == column      ) for column in range(lowercase__      )] for row in range(lowercase__      )]



def 			SCREAMING_SNAKE_CASE       (   lowercase__				,				lowercase__ = True      ) ->	list[list[int]] | map[list[int]]:
	if _check_not_integer(lowercase__      ):
		if return_map:
			return map(lowercase__				,				zip(*lowercase__      )      )
		else:
			return list(map(lowercase__				,				zip(*lowercase__      )      )      )
	raise TypeError("Expected a matrix, got int/list instead"      )



def 			SCREAMING_SNAKE_CASE       (   lowercase__				,				lowercase__				,				lowercase__      ) ->	list[list[int]]:
	lowerCAmelCase__      :							Optional[Any]    =							matrix[:row] + matrix[row + 1 :]
	return [row[:column] + row[column + 1 :] for row in minor]



def 			SCREAMING_SNAKE_CASE       (   lowercase__      ) ->	Any:
	if len(lowercase__      ) == 1:
		return matrix[0][0]

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



def 			SCREAMING_SNAKE_CASE       (   lowercase__      ) ->	list[list[float]] | None:
	lowerCAmelCase__      :							Union[str, Any]    =							determinant(lowercase__      )
	if det == 0:
		return None

	lowerCAmelCase__      :							Dict    =							[
	    [determinant(minor(lowercase__				,				lowercase__				,				lowercase__      )      ) for j in range(len(lowercase__      )      )]
	    for i in range(len(lowercase__      )      )
	]

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



def 			SCREAMING_SNAKE_CASE       (   lowercase__      ) ->	bool:
	return not isinstance(lowercase__				,				lowercase__      ) and not isinstance(matrix[0]				,				lowercase__      )



def 			SCREAMING_SNAKE_CASE       (   lowercase__      ) ->	tuple[int, int]:
	return len(lowercase__      ), len(matrix[0]      )



def 			SCREAMING_SNAKE_CASE       (   lowercase__				,				lowercase__      ) ->	tuple[tuple[int, int], tuple[int, int]]:
	lowerCAmelCase__      :							int    =							_shape(lowercase__      ) + _shape(lowercase__      )
	if shape[0] != shape[3] or shape[1] != shape[2]:
		lowerCAmelCase__      :							Tuple    =							(
		    "operands could not be broadcast together with shape "
		    F"""({shape[0], shape[1]}), ({shape[2], shape[3]})"""
		)
		raise ValueError(lowercase__      )
	return (shape[0], shape[2]), (shape[1], shape[3])



def 			SCREAMING_SNAKE_CASE       (   ) ->	None:
	lowerCAmelCase__      :							int    =							[[1_2, 1_0], [3, 9]]
	lowerCAmelCase__      :							Any    =							[[3, 4], [7, 4]]
	lowerCAmelCase__      :							Optional[int]    =							[[1_1, 1_2, 1_3, 1_4], [2_1, 2_2, 2_3, 2_4], [3_1, 3_2, 3_3, 3_4], [4_1, 4_2, 4_3, 4_4]]
	lowerCAmelCase__      :							List[str]    =							[[3, 0, 2], [2, 0, -2], [0, 1, 1]]
	print(F"""Add Operation, {add(lowercase__				,				lowercase__      ) = } \n"""      )
	print(
	    F"""Multiply Operation, {multiply(lowercase__				,				lowercase__      ) = } \n"""				,				)
	print(F"""Identity: {identity(5      )}\n"""      )
	print(F"""Minor of {matrix_c} = {minor(lowercase__				,				1				,				2      )} \n"""      )
	print(F"""Determinant of {matrix_b} = {determinant(lowercase__      )} \n"""      )
	print(F"""Inverse of {matrix_d} = {inverse(lowercase__      )}\n"""      )


if __name__ == "__main__":
				import doctest

				doctest.testmod()
				main()









"""simple docstring"""

import torch
import torch.nn.functional as F

from diffusers import VQDiffusionScheduler

from .test_schedulers import SchedulerCommonTest






class  __a				(	__magic_name__					):





       """simple docstring"""


       __UpperCamelCase				:			Optional[int]          =	(VQDiffusionScheduler,)






       def  SCREAMING_SNAKE_CASE_  (      self ,				**snake_case      ):





        """simple docstring"""

        lowerCAmelCase__      :							str    =							{
            "num_vec_classes": 4_097,
            "num_train_timesteps": 100,
        }

        config.update(**snake_case      )
        return config






       def  SCREAMING_SNAKE_CASE_  (      self ,				snake_case      ):





        """simple docstring"""

        lowerCAmelCase__      :							Optional[int]    =							4
        lowerCAmelCase__      :							Optional[Any]    =							8
        lowerCAmelCase__      :							Union[str, Any]    =							8

        lowerCAmelCase__      :							Optional[Any]    =							torch.randint(0 ,				snake_case ,				(batch_size, height * width)      )

        return sample






       @property
       def  SCREAMING_SNAKE_CASE_  (      self      ):





        """simple docstring"""

        assert False






       def  SCREAMING_SNAKE_CASE_  (      self ,				snake_case      ):





        """simple docstring"""

        def model(snake_case ,				snake_case ,				*snake_case      ):
         lowerCAmelCase__ ,	lowerCAmelCase__      :							str    =							sample.shape
         lowerCAmelCase__      :							Dict    =							torch.rand((batch_size, num_vec_classes - 1, num_latent_pixels)      )
         lowerCAmelCase__      :							int    =							F.log_softmax(logits.double() ,				dim=1      ).float()
         return return_value

        return model






       def  SCREAMING_SNAKE_CASE_  (      self      ):





        """simple docstring"""

        for timesteps in [2, 5, 100, 1_000]:
         self.check_over_configs(num_train_timesteps=snake_case      )






       def  SCREAMING_SNAKE_CASE_  (      self      ):





        """simple docstring"""

        for num_vec_classes in [5, 100, 1_000, 4_000]:
         self.check_over_configs(num_vec_classes=snake_case      )






       def  SCREAMING_SNAKE_CASE_  (      self      ):





        """simple docstring"""

        for t in [0, 50, 99]:
         self.check_over_forward(time_step=snake_case      )






       def  SCREAMING_SNAKE_CASE_  (      self      ):





        """simple docstring"""

        pass






