

from __future__ import annotations

from typing import Any






def        lowerCamelCase_  (				*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        lowerCamelCase_  (				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        lowerCamelCase_  (				UpperCAmelCase_				:  list[list[int]]				,							UpperCAmelCase_				:  int | float						)    ->					list[list[float]]:




	'''simple docstring'''




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






def        lowerCamelCase_  (				UpperCAmelCase_				:  list[list[int]]				,							UpperCAmelCase_				:  list[list[int]]						)    ->					list[list[int]]:




	'''simple docstring'''




	if _check_not_integer(UpperCAmelCase_						) and _check_not_integer(UpperCAmelCase_						):
		_UpperCamelCase						,		_UpperCamelCase :		List[Any]								=    _verify_matrix_sizes(UpperCAmelCase_				,							UpperCAmelCase_						)

	if cols[0] != rows[1]:
		_UpperCamelCase :		List[Any]								=    (
		    '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_  (				UpperCAmelCase_				:  int						)    ->					list[list[int]]:




	'''simple docstring'''




	_UpperCamelCase :		int								=    int(UpperCAmelCase_						)
	return [[int(row == column						) for column in range(UpperCAmelCase_						)] for row in range(UpperCAmelCase_						)]






def        lowerCamelCase_  (				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        lowerCamelCase_  (				UpperCAmelCase_				:  list[list[int]]				,							UpperCAmelCase_				:  int				,							UpperCAmelCase_				:  int						)    ->					list[list[int]]:




	'''simple docstring'''




	_UpperCamelCase :		Optional[Any]								=    matrix[:row] + matrix[row + 1 :]
	return [row[:column] + row[column + 1 :] for row in minor]






def        lowerCamelCase_  (				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        lowerCamelCase_  (				UpperCAmelCase_				:  list[list[int]]						)    ->					list[list[float]] | None:




	'''simple docstring'''




	_UpperCamelCase :		List[Any]								=    determinant(UpperCAmelCase_						)
	if det == 0:
		return None

	_UpperCamelCase :		Optional[int]								=    [
	    [determinant(minor(UpperCAmelCase_				,							UpperCAmelCase_				,							UpperCAmelCase_						)						) for j in range(len(UpperCAmelCase_						)						)]
	    for i in range(len(UpperCAmelCase_						)						)
	]

	_UpperCamelCase :		Union[str, Any]								=    [
	    [x * (-1) ** (row + col) for col, x in enumerate(matrix_minor[row]						)]
	    for row in range(len(UpperCAmelCase_						)						)
	]
	_UpperCamelCase :		Dict								=    list(transpose(UpperCAmelCase_						)						)
	return scalar_multiply(UpperCAmelCase_				,							1 / det						)






def        lowerCamelCase_  (				UpperCAmelCase_				:  list[list[int]]						)    ->					bool:




	'''simple docstring'''




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






def        lowerCamelCase_  (				UpperCAmelCase_				:  list[list[int]]						)    ->					tuple[int, int]:




	'''simple docstring'''




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






def        lowerCamelCase_  (				UpperCAmelCase_				:  list[list[int]]				,							UpperCAmelCase_				:  list[list[int]]						)    ->					tuple[tuple[int, int], tuple[int, int]]:




	'''simple docstring'''




	_UpperCamelCase :		Union[str, Any]								=    _shape(UpperCAmelCase_						) + _shape(UpperCAmelCase_						)
	if shape[0] != shape[3] or shape[1] != shape[2]:
		_UpperCamelCase :		Any								=    (
		    '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_  (				)    ->					None:




	'''simple docstring'''




	_UpperCamelCase :		Tuple								=    [[1_2, 1_0], [3, 9]]
	_UpperCamelCase :		List[str]								=    [[3, 4], [7, 4]]
	_UpperCamelCase :		Any								=    [[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]]
	_UpperCamelCase :		List[str]								=    [[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_tokenizers_available, is_torch_available


lowerCAmelCase__             =		{
    """configuration_markuplm""": ["""MARKUPLM_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MarkupLMConfig"""],
    """feature_extraction_markuplm""": ["""MarkupLMFeatureExtractor"""],
    """processing_markuplm""": ["""MarkupLMProcessor"""],
    """tokenization_markuplm""": ["""MarkupLMTokenizer"""],
}

try:
							if not is_tokenizers_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowerCAmelCase__             =		["""MarkupLMTokenizerFast"""]

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowerCAmelCase__             =		[
							    """MARKUPLM_PRETRAINED_MODEL_ARCHIVE_LIST""",
							    """MarkupLMForQuestionAnswering""",
							    """MarkupLMForSequenceClassification""",
							    """MarkupLMForTokenClassification""",
							    """MarkupLMModel""",
							    """MarkupLMPreTrainedModel""",
							]


if TYPE_CHECKING:
							from .configuration_markuplm import MARKUPLM_PRETRAINED_CONFIG_ARCHIVE_MAP, MarkupLMConfig
							from .feature_extraction_markuplm import MarkupLMFeatureExtractor
							from .processing_markuplm import MarkupLMProcessor
							from .tokenization_markuplm import MarkupLMTokenizer

							try:
														if not is_tokenizers_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .tokenization_markuplm_fast import MarkupLMTokenizerFast

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_markuplm import (
														    MARKUPLM_PRETRAINED_MODEL_ARCHIVE_LIST,
														    MarkupLMForQuestionAnswering,
														    MarkupLMForSequenceClassification,
														    MarkupLMForTokenClassification,
														    MarkupLMModel,
														    MarkupLMPreTrainedModel,
														)


else:
							import sys

							lowerCAmelCase__             =		_LazyModule(__name__, globals()["""__file__"""], _import_structure)




