





from __future__ import annotations

from typing import Any






def  SCREAMING_SNAKE_CASE__							(				*UpperCamelCase__:							list[list[int]]			):
		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  SCREAMING_SNAKE_CASE__							(				UpperCamelCase__:							list[list[int]]    ,      UpperCamelCase__:							list[list[int]]			):
		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  SCREAMING_SNAKE_CASE__							(				UpperCamelCase__:							list[list[int]]    ,      UpperCamelCase__:							int | float			):
		return [[x * n for x in row] for row in matrix]






def  SCREAMING_SNAKE_CASE__							(				UpperCamelCase__:							list[list[int]]    ,      UpperCamelCase__:							list[list[int]]			):
		if _check_not_integer(UpperCamelCase__			) and _check_not_integer(UpperCamelCase__			):
				SCREAMING_SNAKE_CASE__		,  SCREAMING_SNAKE_CASE__								=					_verify_matrix_sizes(UpperCamelCase__    ,      UpperCamelCase__			)

		if cols[0] != rows[1]:
				SCREAMING_SNAKE_CASE__								=					(
				    """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  SCREAMING_SNAKE_CASE__							(				UpperCamelCase__:							int			):
		SCREAMING_SNAKE_CASE__								=					int(UpperCamelCase__			)
		return [[int(row == column			) for column in range(UpperCamelCase__			)] for row in range(UpperCamelCase__			)]






def  SCREAMING_SNAKE_CASE__							(				UpperCamelCase__:							list[list[int]]    ,      UpperCamelCase__:							bool = True			):
		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  SCREAMING_SNAKE_CASE__							(				UpperCamelCase__:							list[list[int]]    ,      UpperCamelCase__:							int    ,      UpperCamelCase__:							int			):
		SCREAMING_SNAKE_CASE__								=					matrix[:row] + matrix[row + 1 :]
		return [row[:column] + row[column + 1 :] for row in minor]






def  SCREAMING_SNAKE_CASE__							(				UpperCamelCase__:							list[list[int]]			):
		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  SCREAMING_SNAKE_CASE__							(				UpperCamelCase__:							list[list[int]]			):
		SCREAMING_SNAKE_CASE__								=					determinant(UpperCamelCase__			)
		if det == 0:
				return None

		SCREAMING_SNAKE_CASE__								=					[
		    [determinant(minor(UpperCamelCase__    ,      UpperCamelCase__    ,      UpperCamelCase__			)			) for j in range(len(UpperCamelCase__			)			)]
		    for i in range(len(UpperCamelCase__			)			)
		]

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






def  SCREAMING_SNAKE_CASE__							(				UpperCamelCase__:							list[list[int]]			):
		return not isinstance(UpperCamelCase__    ,      UpperCamelCase__			) and not isinstance(matrix[0]    ,      UpperCamelCase__			)






def  SCREAMING_SNAKE_CASE__							(				UpperCamelCase__:							list[list[int]]			):
		return len(UpperCamelCase__			), len(matrix[0]			)






def  SCREAMING_SNAKE_CASE__							(				UpperCamelCase__:							list[list[int]]    ,      UpperCamelCase__:							list[list[int]]			):
		SCREAMING_SNAKE_CASE__								=					_shape(UpperCamelCase__			) + _shape(UpperCamelCase__			)
		if shape[0] != shape[3] or shape[1] != shape[2]:
				SCREAMING_SNAKE_CASE__								=					(
				    """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  SCREAMING_SNAKE_CASE__							(				):
		SCREAMING_SNAKE_CASE__								=					[[12, 10], [3, 9]]
		SCREAMING_SNAKE_CASE__								=					[[3, 4], [7, 4]]
		SCREAMING_SNAKE_CASE__								=					[[11, 12, 13, 14], [21, 22, 23, 24], [31, 32, 33, 34], [41, 42, 43, 44]]
		SCREAMING_SNAKE_CASE__								=					[[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()






from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_torch_available,
)


_lowerCamelCase       =	{
    'configuration_gptsan_japanese': ['GPTSAN_JAPANESE_PRETRAINED_CONFIG_ARCHIVE_MAP', 'GPTSanJapaneseConfig'],
    'tokenization_gptsan_japanese': ['GPTSanJapaneseTokenizer'],
}

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_lowerCamelCase       =	[
	    'GPTSAN_JAPANESE_PRETRAINED_MODEL_ARCHIVE_LIST',
	    'GPTSanJapaneseForConditionalGeneration',
	    'GPTSanJapaneseModel',
	    'GPTSanJapanesePreTrainedModel',
	]
	_lowerCamelCase       =	[
	    'GPTSanJapaneseTokenizer',
	]


if TYPE_CHECKING:
	from .configuration_gptsan_japanese import GPTSAN_JAPANESE_PRETRAINED_CONFIG_ARCHIVE_MAP, GPTSanJapaneseConfig
	from .tokenization_gptsan_japanese import GPTSanJapaneseTokenizer

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_gptsan_japanese import (
		    GPTSAN_JAPANESE_PRETRAINED_MODEL_ARCHIVE_LIST,
		    GPTSanJapaneseForConditionalGeneration,
		    GPTSanJapaneseModel,
		    GPTSanJapanesePreTrainedModel,
		)
		from .tokenization_gptsan_japanese import GPTSanJapaneseTokenizer


else:
	import sys

	_lowerCamelCase       =	_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)