






from __future__ import annotations

from typing import Any


class       __SCREAMING_SNAKE_CASE   :






						def __init__(		self       ,  _UpperCamelCase       ,  _UpperCamelCase       ,  _UpperCamelCase = 0				):






												"""simple docstring"""
												lowerCAmelCase__  ,    lowerCAmelCase__        =  row, column
												lowerCAmelCase__        =  [[default_value for c in range(_UpperCamelCase				)] for r in range(_UpperCamelCase				)]






						def __str__(		self				):






												"""simple docstring"""
												lowerCAmelCase__        =  F"Matrix consist of {self.row} rows and {self.column} columns\n"

												# Make string identifier
												lowerCAmelCase__        =  0
												for row_vector in self.array:
																		for obj in row_vector:
																								lowerCAmelCase__        =  max(_UpperCamelCase       ,  len(str(_UpperCamelCase				)				)				)
												lowerCAmelCase__        =  F"%{max_element_length}s"

												# Make string and return
												def single_line(_UpperCamelCase				) -> str:
																		nonlocal string_format_identifier
																		lowerCAmelCase__        =  '['
																		line += ", ".join(string_format_identifier % (obj,) for obj in row_vector				)
																		line += "]"
																		return line

												s += "\n".join(single_line(_UpperCamelCase				) for row_vector in self.array				)
												return s






						def __repr__(		self				):






												"""simple docstring"""
												return str(self				)






						def  UpperCamelCase__ (		self       ,  _UpperCamelCase				):






												"""simple docstring"""
												if not (isinstance(_UpperCamelCase       ,  (list, tuple)				) and len(_UpperCamelCase				) == 2):
																		return False
												elif not (0 <= loc[0] < self.row and 0 <= loc[1] < self.column):
																		return False
												else:
																		return True






						def __getitem__(		self       ,  _UpperCamelCase				):






												"""simple docstring"""
												assert self.validate_indicies(_UpperCamelCase				)
												return self.array[loc[0]][loc[1]]






						def __setitem__(		self       ,  _UpperCamelCase       ,  _UpperCamelCase				):






												"""simple docstring"""
												assert self.validate_indicies(_UpperCamelCase				)
												lowerCAmelCase__        =  value






						def __add__(		self       ,  _UpperCamelCase				):






												"""simple docstring"""
												assert isinstance(_UpperCamelCase       ,  _UpperCamelCase				)
												assert self.row == another.row and self.column == another.column

												# Add
												lowerCAmelCase__        =  Matrix(self.row       ,  self.column				)
												for r in range(self.row				):
																		for c in range(self.column				):
																								lowerCAmelCase__        =  self[r, c] + another[r, c]
												return result






						def __neg__(		self				):






												"""simple docstring"""
												lowerCAmelCase__        =  Matrix(self.row       ,  self.column				)
												for r in range(self.row				):
																		for c in range(self.column				):
																								lowerCAmelCase__        =  -self[r, c]
												return result






						def __sub__(		self       ,  _UpperCamelCase				):






												"""simple docstring"""
												return self + (-another)






						def __mul__(		self       ,  _UpperCamelCase				):






												"""simple docstring"""

												if isinstance(_UpperCamelCase       ,  (int, float)				):  # Scalar multiplication
																		lowerCAmelCase__        =  Matrix(self.row       ,  self.column				)
																		for r in range(self.row				):
																								for c in range(self.column				):
																														lowerCAmelCase__        =  self[r, c] * another
																		return result
												elif isinstance(_UpperCamelCase       ,  _UpperCamelCase				):  # Matrix multiplication
																		assert self.column == another.row
																		lowerCAmelCase__        =  Matrix(self.row       ,  another.column				)
																		for r in range(self.row				):
																								for c in range(another.column				):
																														for i in range(self.column				):
																																				result[r, c] += self[r, i] * another[i, c]
																		return result
												else:
																		lowerCAmelCase__        =  F"Unsupported type given for another ({type(_UpperCamelCase				)})"
																		raise TypeError(_UpperCamelCase				)






						def  UpperCamelCase__ (		self				):






												"""simple docstring"""
												lowerCAmelCase__        =  Matrix(self.column       ,  self.row				)
												for r in range(self.row				):
																		for c in range(self.column				):
																								lowerCAmelCase__        =  self[r, c]
												return result







						def  UpperCamelCase__ (		self       ,  _UpperCamelCase       ,  _UpperCamelCase				):






												"""simple docstring"""
												assert isinstance(_UpperCamelCase       ,  _UpperCamelCase				) and isinstance(_UpperCamelCase       ,  _UpperCamelCase				)
												assert self.row == self.column == u.row == v.row  # u, v should be column vector
												assert u.column == v.column == 1  # u, v should be column vector

												# Calculate
												lowerCAmelCase__        =  v.transpose()
												lowerCAmelCase__        =  (v_t * self * u)[0, 0] + 1
												if numerator_factor == 0:
																		return None  # It's not invertable
												return self - ((self * u) * (v_t * self) * (1.0 / numerator_factor))


# Testing
if __name__ == "__main__":







					def 		_UpperCamelCase				(      )					->				None:

											"""simple docstring"""



											lowerCAmelCase__        =  Matrix(3      ,    3      ,    0						)
											for i in range(3						):
																	lowerCAmelCase__        =  1
											print(F"a^(-1) is {ainv}"						)
											# u, v
											lowerCAmelCase__        =  Matrix(3      ,    1      ,    0						)
											lowerCAmelCase__  ,    lowerCAmelCase__  ,    lowerCAmelCase__        =  1, 2, -3
											lowerCAmelCase__        =  Matrix(3      ,    1      ,    0						)
											lowerCAmelCase__  ,    lowerCAmelCase__  ,    lowerCAmelCase__        =  4, -2, 5
											print(F"u is {u}"						)
											print(F"v is {v}"						)
											print(F"uv^T is {u * v.transpose()}"						)
											# Sherman Morrison
											print(F"(a + uv^T)^(-1) is {ainv.sherman_morrison(UpperCamelCase_      ,    UpperCamelCase_						)}"						)







					def 		_UpperCamelCase				(      )					->				None:

											"""simple docstring"""



											import doctest

											doctest.testmod()


					testa()













from typing import TYPE_CHECKING

# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__snake_case      :      Dict             =       {"""configuration_focalnet""": ["""FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP""", """FocalNetConfig"""]}


try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					__snake_case      :      str             =       [
					    """FOCALNET_PRETRAINED_MODEL_ARCHIVE_LIST""",
					    """FocalNetForImageClassification""",
					    """FocalNetForMaskedImageModeling""",
					    """FocalNetBackbone""",
					    """FocalNetModel""",
					    """FocalNetPreTrainedModel""",
					]

if TYPE_CHECKING:
					from .configuration_focalnet import FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP, FocalNetConfig

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_focalnet import (
										    FOCALNET_PRETRAINED_MODEL_ARCHIVE_LIST,
										    FocalNetBackbone,
										    FocalNetForImageClassification,
										    FocalNetForMaskedImageModeling,
										    FocalNetModel,
										    FocalNetPreTrainedModel,
										)

else:
					import sys

					__snake_case      :      List[Any]             =       _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)





