"""simple docstring"""



from __future__ import annotations

import math
import random
from collections.abc import Collection
from typing import overload



class   _A						:




    """simple docstring"""




    def __init__(		self				:  List[Any]						,   A_				:  Collection[float] | None = None     )     ->							int:






         if components is None:
              __snake_case				=				[]
         __snake_case				=				list(A_     )
    def __len__(		self				:  Any     )     ->							str:
         return len(self.__components     )
    def __str__(		self				:  str     )     ->							List[str]:
         return "(" + ",".join(map(A_						,   self.__components     )     ) + ")"
    def __add__(		self				:  int						,   A_				:  Vector     )     ->							Dict:
         __snake_case				=				len(self     )
         if size == len(A_     ):
              __snake_case				=				[self.__components[i] + other.component(A_     ) for i in range(A_     )]
              return Vector(A_     )
         else:
              raise Exception('''must have the same size'''     )
    def __sub__(		self				:  Dict						,   A_				:  Vector     )     ->							Dict:
         __snake_case				=				len(self     )
         if size == len(A_     ):
              __snake_case				=				[self.__components[i] - other.component(A_     ) for i in range(A_     )]
              return Vector(A_     )
         else:  # error case
              raise Exception('''must have the same size'''     )
    @overload
    def __mul__(		self				:  Optional[Any]						,   A_				:  float     )     ->							Dict:
         ...
    @overload
    def __mul__(		self				:  Union[str, Any]						,   A_				:  Vector     )     ->							Any:
         ...
    def __mul__(		self				:  int						,   A_				:  float | Vector     )     ->							Dict:






         if isinstance(A_						,   (float, int)     ):
              __snake_case				=				[c * other for c in self.__components]
              return Vector(A_     )
         elif isinstance(A_						,   A_     ) and len(self     ) == len(A_     ):
              __snake_case				=				len(self     )
              __snake_case				=				[self.__components[i] * other.component(A_     ) for i in range(A_     )]
              return sum(A_     )
         else:  # error case
              raise Exception('''invalid operand!'''     )
    def 			lowercase       (		self				:  Union[str, Any]     )     ->							Optional[int]:
         return Vector(self.__components     )
    def 			lowercase       (		self				:  Optional[int]						,   A_				:  int     )     ->							List[Any]:






         if isinstance(A_						,   A_     ) and -len(self.__components     ) <= i < len(self.__components     ):
              return self.__components[i]
         else:
              raise Exception('''index out of range'''     )
    def 			lowercase       (		self				:  Optional[int]						,   A_				:  int						,   A_				:  float     )     ->							Tuple:
         assert -len(self.__components     ) <= pos < len(self.__components     )
         __snake_case				=				value
    def 			lowercase       (		self				:  Dict     )     ->							Dict:






         if len(self.__components     ) == 0:
              raise Exception('''Vector is empty'''     )
         __snake_case				=				[c**2 for c in self.__components]
         return math.sqrt(sum(A_     )     )







    def 			lowercase       (		self				:  Union[str, Any]						,   A_				:  Vector						,   A_				:  bool = False     )     ->							List[Any]:
         __snake_case				=				self * other
         __snake_case				=				self.euclidean_length() * other.euclidean_length()
         if deg:
              return math.degrees(math.acos(num / den     )     )
         else:
              return math.acos(num / den     )






def  SCREAMING_SNAKE_CASE							(  snake_case):
     assert isinstance(_UpperCamelCase,   _UpperCamelCase)
     return Vector([0] * dimension)





def  SCREAMING_SNAKE_CASE							(  snake_case,   snake_case):
     assert isinstance(_UpperCamelCase,   _UpperCamelCase) and (isinstance(_UpperCamelCase,   _UpperCamelCase))
     __snake_case				=				[0] * dimension
     __snake_case				=				1
     return Vector(_UpperCamelCase)





def  SCREAMING_SNAKE_CASE							(  snake_case,   snake_case,   snake_case):
     assert (
         isinstance(_UpperCamelCase,   _UpperCamelCase)
         and isinstance(_UpperCamelCase,   _UpperCamelCase)
         and (isinstance(_UpperCamelCase,   (int, float)))
     )
     return x * scalar + y





def  SCREAMING_SNAKE_CASE							(  snake_case,   snake_case,   snake_case):
     random.seed(_UpperCamelCase)
     __snake_case				=				[random.randint(_UpperCamelCase,   _UpperCamelCase) for _ in range(_UpperCamelCase)]
     return Vector(_UpperCamelCase)



class   _A						:




    """simple docstring"""




    def __init__(		self				:  List[str]						,   A_				:  list[list[float]]						,   A_				:  int						,   A_				:  int     )     ->							int:
         __snake_case				=				matrix
         __snake_case				=				w
         __snake_case				=				h
    def __str__(		self				:  Dict     )     ->							Any:
         __snake_case				=				""
         for i in range(self.__height     ):
              ans += "|"
              for j in range(self.__width     ):
                   if j < self.__width - 1:
                        ans += str(self.__matrix[i][j]     ) + ","
                   else:
                        ans += str(self.__matrix[i][j]     ) + "|\n"
         return ans
    def __add__(		self				:  Optional[Any]						,   A_				:  Matrix     )     ->							int:






         if self.__width == other.width() and self.__height == other.height():
              __snake_case				=				[]
              for i in range(self.__height     ):
                   __snake_case				=				[
                       self.__matrix[i][j] + other.component(A_						,   A_     )
                       for j in range(self.__width     )
                   ]
                   matrix.append(A_     )
              return Matrix(A_						,   self.__width						,   self.__height     )
         else:
              raise Exception('''matrix must have the same dimension!'''     )
    def __sub__(		self				:  int						,   A_				:  Matrix     )     ->							Tuple:






         if self.__width == other.width() and self.__height == other.height():
              __snake_case				=				[]
              for i in range(self.__height     ):
                   __snake_case				=				[
                       self.__matrix[i][j] - other.component(A_						,   A_     )
                       for j in range(self.__width     )
                   ]
                   matrix.append(A_     )
              return Matrix(A_						,   self.__width						,   self.__height     )
         else:
              raise Exception('''matrices must have the same dimension!'''     )
    @overload
    def __mul__(		self				:  Optional[int]						,   A_				:  float     )     ->							int:
         ...
    @overload
    def __mul__(		self				:  List[Any]						,   A_				:  Vector     )     ->							Optional[int]:
         ...
    def __mul__(		self				:  Union[str, Any]						,   A_				:  float | Vector     )     ->							int:






         if isinstance(A_						,   A_     ):  # matrix-vector
              if len(A_     ) == self.__width:
                   __snake_case				=				zero_vector(self.__height     )
                   for i in range(self.__height     ):
                        __snake_case				=				[
                            self.__matrix[i][j] * other.component(A_     )
                            for j in range(self.__width     )
                        ]
                        ans.change_component(A_						,   sum(A_     )     )
                   return ans
              else:
                   raise Exception(
                       '''vector must have the same size as the '''
                       '''number of columns of the matrix!'''     )
         elif isinstance(A_						,   (int, float)     ):  # matrix-scalar
              __snake_case				=				[
                  [self.__matrix[i][j] * other for j in range(self.__width     )]
                  for i in range(self.__height     )
              ]
              return Matrix(A_						,   self.__width						,   self.__height     )
         return None
    def 			lowercase       (		self				:  Tuple     )     ->							Optional[Any]:
         return self.__height
    def 			lowercase       (		self				:  Union[str, Any]     )     ->							Union[str, Any]:
         return self.__width
    def 			lowercase       (		self				:  Tuple						,   A_				:  int						,   A_				:  int     )     ->							str:






         if 0 <= x < self.__height and 0 <= y < self.__width:
              return self.__matrix[x][y]
         else:
              raise Exception('''change_component: indices out of bounds'''     )
    def 			lowercase       (		self				:  List[str]						,   A_				:  int						,   A_				:  int						,   A_				:  float     )     ->							List[Any]:






         if 0 <= x < self.__height and 0 <= y < self.__width:
              __snake_case				=				value
         else:
              raise Exception('''change_component: indices out of bounds'''     )
    def 			lowercase       (		self				:  List[str]						,   A_				:  int						,   A_				:  int     )     ->							int:






         if self.__height != self.__width:
              raise Exception('''Matrix is not square'''     )
         __snake_case				=				self.__matrix[:x] + self.__matrix[x + 1 :]
         for i in range(len(A_     )     ):
              __snake_case				=				minor[i][:y] + minor[i][y + 1 :]
         return Matrix(A_						,   self.__width - 1						,   self.__height - 1     ).determinant()
    def 			lowercase       (		self				:  int						,   A_				:  int						,   A_				:  int     )     ->							Optional[Any]:






         if self.__height != self.__width:
              raise Exception('''Matrix is not square'''     )
         if 0 <= x < self.__height and 0 <= y < self.__width:
              return (-1) ** (x + y) * self.minor(A_						,   A_     )
         else:
              raise Exception('''Indices out of bounds'''     )







    def 			lowercase       (		self				:  Tuple     )     ->							Optional[Any]:






         if self.__height != self.__width:
              raise Exception('''Matrix is not square'''     )
         if self.__height < 1:
              raise Exception('''Matrix has no element'''     )
         elif self.__height == 1:
              return self.__matrix[0][0]
         elif self.__height == 2:
              return (
                  self.__matrix[0][0] * self.__matrix[1][1]
                  - self.__matrix[0][1] * self.__matrix[1][0]
              )
         else:
              __snake_case				=				[
                  self.__matrix[0][y] * self.cofactor(0						,   A_     ) for y in range(self.__width     )
              ]
              return sum(A_     )






def  SCREAMING_SNAKE_CASE							(  snake_case):
     __snake_case				=				[[0] * n for _ in range(_UpperCamelCase)]
     return Matrix(_UpperCamelCase,   _UpperCamelCase,   _UpperCamelCase)





def  SCREAMING_SNAKE_CASE							(  snake_case,   snake_case,   snake_case,   snake_case):
     random.seed(_UpperCamelCase)
     __snake_case				=				[
         [random.randint(_UpperCamelCase,   _UpperCamelCase) for _ in range(_UpperCamelCase)] for _ in range(_UpperCamelCase)
     ]
     return Matrix(_UpperCamelCase,   _UpperCamelCase,   _UpperCamelCase)







'''simple docstring'''
from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
    is_vision_available,
)


UpperCamelCase__			=      {
    'configuration_layoutlmv3': [
        'LAYOUTLMV3_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'LayoutLMv3Config',
        'LayoutLMv3OnnxConfig',
    ],
    'processing_layoutlmv3': ['LayoutLMv3Processor'],
    'tokenization_layoutlmv3': ['LayoutLMv3Tokenizer'],
}

try:
 if not is_tokenizers_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 UpperCamelCase__			=      ['LayoutLMv3TokenizerFast']

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 UpperCamelCase__			=      [
     'LAYOUTLMV3_PRETRAINED_MODEL_ARCHIVE_LIST',
     'LayoutLMv3ForQuestionAnswering',
     'LayoutLMv3ForSequenceClassification',
     'LayoutLMv3ForTokenClassification',
     'LayoutLMv3Model',
     'LayoutLMv3PreTrainedModel',
 ]

try:
 if not is_tf_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 UpperCamelCase__			=      [
     'TF_LAYOUTLMV3_PRETRAINED_MODEL_ARCHIVE_LIST',
     'TFLayoutLMv3ForQuestionAnswering',
     'TFLayoutLMv3ForSequenceClassification',
     'TFLayoutLMv3ForTokenClassification',
     'TFLayoutLMv3Model',
     'TFLayoutLMv3PreTrainedModel',
 ]

try:
 if not is_vision_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 UpperCamelCase__			=      ['LayoutLMv3FeatureExtractor']
 UpperCamelCase__			=      ['LayoutLMv3ImageProcessor']


if TYPE_CHECKING:
 from .configuration_layoutlmva import (
     LAYOUTLMV3_PRETRAINED_CONFIG_ARCHIVE_MAP,
     LayoutLMvaConfig,
     LayoutLMvaOnnxConfig,
 )
 from .processing_layoutlmva import LayoutLMvaProcessor
 from .tokenization_layoutlmva import LayoutLMvaTokenizer

 try:
  if not is_tokenizers_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .tokenization_layoutlmva_fast import LayoutLMvaTokenizerFast

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_layoutlmva import (
      LAYOUTLMV3_PRETRAINED_MODEL_ARCHIVE_LIST,
      LayoutLMvaForQuestionAnswering,
      LayoutLMvaForSequenceClassification,
      LayoutLMvaForTokenClassification,
      LayoutLMvaModel,
      LayoutLMvaPreTrainedModel,
  )

 try:
  if not is_tf_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_tf_layoutlmva import (
      TF_LAYOUTLMV3_PRETRAINED_MODEL_ARCHIVE_LIST,
      TFLayoutLMvaForQuestionAnswering,
      TFLayoutLMvaForSequenceClassification,
      TFLayoutLMvaForTokenClassification,
      TFLayoutLMvaModel,
      TFLayoutLMvaPreTrainedModel,
  )

 try:
  if not is_vision_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .feature_extraction_layoutlmva import LayoutLMvaFeatureExtractor
  from .image_processing_layoutlmva import LayoutLMvaImageProcessor

else:
 import sys

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




