
from __future__ import annotations

from typing import Any






def        lowerCamelCase__    (    *__lowerCAmelCase  :  Dict    ):




			"""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        lowerCamelCase__    (    __lowerCAmelCase  :  Any   ,							__lowerCAmelCase  :  Union[str, Any]    ):




			"""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        lowerCamelCase__    (    __lowerCAmelCase  :  List[Any]   ,							__lowerCAmelCase  :  Dict    ):




			"""simple docstring"""


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






def        lowerCamelCase__    (    __lowerCAmelCase  :  Optional[int]   ,							__lowerCAmelCase  :  Dict    ):




			"""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        lowerCamelCase__    (    __lowerCAmelCase  :  Optional[int]    ):




			"""simple docstring"""


			lowerCAmelCase_      =     int(__UpperCamelCase    )
			return [[int(row == column    ) for column in range(__UpperCamelCase    )] for row in range(__UpperCamelCase    )]






def        lowerCamelCase__    (    __lowerCAmelCase  :  Optional[Any]   ,							__lowerCAmelCase  :  str = True    ):




			"""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        lowerCamelCase__    (    __lowerCAmelCase  :  Dict   ,							__lowerCAmelCase  :  Union[str, Any]   ,							__lowerCAmelCase  :  str    ):




			"""simple docstring"""


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






def        lowerCamelCase__    (    __lowerCAmelCase  :  int    ):




			"""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        lowerCamelCase__    (    __lowerCAmelCase  :  str    ):




			"""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        lowerCamelCase__    (    __lowerCAmelCase  :  int    ):




			"""simple docstring"""


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






def        lowerCamelCase__    (    __lowerCAmelCase  :  str    ):




			"""simple docstring"""


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






def        lowerCamelCase__    (    __lowerCAmelCase  :  int   ,							__lowerCAmelCase  :  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        lowerCamelCase__    (    ):




			"""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 torch
import torch.nn.functional as F

from diffusers import VQDiffusionScheduler

from .test_schedulers import SchedulerCommonTest





class      _lowerCAmelCase (     __a	):
				_lowercase      		=(VQDiffusionScheduler,)




				def 					__a						( self    ,    **_UpperCamelCase					)    ->				List[str]:
							lowerCAmelCase_      =     {
							    "num_vec_classes": 4_097,
							    "num_train_timesteps": 100,
							}

							config.update(**_UpperCamelCase					)
							return config




				def 					__a						( self    ,    _UpperCamelCase					)    ->				str:
							lowerCAmelCase_      =     4
							lowerCAmelCase_      =     8
							lowerCAmelCase_      =     8

							lowerCAmelCase_      =     torch.randint(0    ,    _UpperCamelCase    ,    (batch_size, height * width)					)

							return sample




				@property
				def 					__a						( self					)    ->				List[str]:
							assert False




				def 					__a						( self    ,    _UpperCamelCase					)    ->				Tuple:
							def model(_UpperCamelCase    ,    _UpperCamelCase    ,    *_UpperCamelCase					):
										lowerCAmelCase_     ,  lowerCAmelCase_      =     sample.shape
										lowerCAmelCase_      =     torch.rand((batch_size, num_vec_classes - 1, num_latent_pixels)					)
										lowerCAmelCase_      =     F.log_softmax(logits.double()    ,    dim=1					).float()
										return return_value

							return model




				def 					__a						( self					)    ->				str:
							for timesteps in [2, 5, 100, 1_000]:
										self.check_over_configs(num_train_timesteps=_UpperCamelCase					)




				def 					__a						( self					)    ->				Dict:
							for num_vec_classes in [5, 100, 1_000, 4_000]:
										self.check_over_configs(num_vec_classes=_UpperCamelCase					)




				def 					__a						( self					)    ->				Tuple:
							for t in [0, 50, 99]:
										self.check_over_forward(time_step=_UpperCamelCase					)




				def 					__a						( self					)    ->				List[str]:
							pass



