






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

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


a_					= {
    'configuration_vision_encoder_decoder': ['VisionEncoderDecoderConfig', 'VisionEncoderDecoderOnnxConfig']
}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  a_					= ['VisionEncoderDecoderModel']

try:
  if not is_tf_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  a_					= ['TFVisionEncoderDecoderModel']

try:
  if not is_flax_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  a_					= ['FlaxVisionEncoderDecoderModel']

if TYPE_CHECKING:
  from .configuration_vision_encoder_decoder import VisionEncoderDecoderConfig, VisionEncoderDecoderOnnxConfig

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_vision_encoder_decoder import VisionEncoderDecoderModel

  try:
    if not is_tf_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_tf_vision_encoder_decoder import TFVisionEncoderDecoderModel

  try:
    if not is_flax_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_flax_vision_encoder_decoder import FlaxVisionEncoderDecoderModel

else:
  import sys

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







'''simple docstring'''
from __future__ import annotations

import numpy as np
from numpy import floataa
from numpy.typing import NDArray





def  _a(  UpperCamelCase__				:						NDArray[floataa],	UpperCamelCase__				:						NDArray[floataa],	UpperCamelCase__				:						list[int],	UpperCamelCase__				:						int,	):




      '''simple docstring'''






      SCREAMING_SNAKE_CASE__		,	SCREAMING_SNAKE_CASE__     :				Tuple									=coefficient_matrix.shape
      SCREAMING_SNAKE_CASE__		,	SCREAMING_SNAKE_CASE__     :				Tuple									=constant_matrix.shape

      if rowsa != colsa:
            SCREAMING_SNAKE_CASE__     :				Any									=f"Coefficient matrix dimensions must be nxn but received {rowsa}x{colsa}"
            raise ValueError(UpperCamelCase__							)

      if colsa != 1:
            SCREAMING_SNAKE_CASE__     :				str									=f"Constant matrix must be nx1 but received {rowsa}x{colsa}"
            raise ValueError(UpperCamelCase__							)

      if rowsa != rowsa:
            SCREAMING_SNAKE_CASE__     :				str									=(
                '''Coefficient and constant matrices dimensions must be nxn and nx1 but '''
                f"received {rowsa}x{colsa} and {rowsa}x{colsa}"
            )
            raise ValueError(UpperCamelCase__							)

      if len(UpperCamelCase__							) != rowsa:
            SCREAMING_SNAKE_CASE__     :				Union[str, Any]									=(
                '''Number of initial values must be equal to number of rows in coefficient '''
                f"matrix but received {len(UpperCamelCase__							)} and {rowsa}"
            )
            raise ValueError(UpperCamelCase__							)

      if iterations <= 0:
            raise ValueError('''Iterations must be at least 1'''							)

      SCREAMING_SNAKE_CASE__     :				NDArray[floataa]									=np.concatenate(
          (coefficient_matrix, constant_matrix),	axis=1							)

      SCREAMING_SNAKE_CASE__		,	SCREAMING_SNAKE_CASE__     :				Any									=table.shape

      strictly_diagonally_dominant(UpperCamelCase__							)

      # Iterates the whole matrix for given number of times
      for _ in range(UpperCamelCase__							):
            SCREAMING_SNAKE_CASE__     :				List[str]									=[]
            for row in range(UpperCamelCase__							):
                  SCREAMING_SNAKE_CASE__     :				Optional[Any]									=0
                  for col in range(UpperCamelCase__							):
                        if col == row:
                              SCREAMING_SNAKE_CASE__     :				int									=table[row][col]
                        elif col == cols - 1:
                              SCREAMING_SNAKE_CASE__     :				Any									=table[row][col]
                        else:
                              temp += (-1) * table[row][col] * init_val[col]
                  SCREAMING_SNAKE_CASE__     :				int									=(temp + val) / denom
                  new_val.append(UpperCamelCase__							)
            SCREAMING_SNAKE_CASE__     :				Optional[Any]									=new_val

      return [float(UpperCamelCase__							) for i in new_val]





def  _a(  UpperCamelCase__				:						NDArray[floataa]							):




      '''simple docstring'''






      SCREAMING_SNAKE_CASE__		,	SCREAMING_SNAKE_CASE__     :				Optional[int]									=table.shape

      SCREAMING_SNAKE_CASE__     :				Any									=True

      for i in range(0,	UpperCamelCase__							):
            SCREAMING_SNAKE_CASE__     :				int									=0
            for j in range(0,	cols - 1							):
                  if i == j:
                        continue
                  else:
                        total += table[i][j]

            if table[i][i] <= total:
                  raise ValueError('''Coefficient matrix is not strictly diagonally dominant'''							)

      return is_diagonally_dominant


# Test Cases
if __name__ == "__main__":
  import doctest

  doctest.testmod()