






"""simple docstring"""





from __future__ import annotations

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



def     __lowercase					(    a :				NDArray[floataa]       ,		a :				NDArray[floataa]       ,		a :				list[int]       ,		a :				int       ,		)					->					list[float]:
      __snake_case      :    str  			=coefficient_matrix.shape
      __snake_case      :    List[Any]  			=constant_matrix.shape

      if rowsa != colsa:
            __snake_case      :    Union[str, Any]  			=f'''Coefficient matrix dimensions must be nxn but received {rowsa}x{colsa}'''
            raise ValueError(SCREAMING_SNAKE_CASE_ )

      if colsa != 1:
            __snake_case      :    List[Any]  			=f'''Constant matrix must be nx1 but received {rowsa}x{colsa}'''
            raise ValueError(SCREAMING_SNAKE_CASE_ )

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

      if len(SCREAMING_SNAKE_CASE_ ) != rowsa:
            __snake_case      :    int  			=(
                "Number of initial values must be equal to number of rows in coefficient "
                f'''matrix but received {len(SCREAMING_SNAKE_CASE_ )} and {rowsa}'''
            )
            raise ValueError(SCREAMING_SNAKE_CASE_ )

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

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

      __snake_case      :    Any  			=table.shape

      strictly_diagonally_dominant(SCREAMING_SNAKE_CASE_ )

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

      return [float(SCREAMING_SNAKE_CASE_ ) for i in new_val]



def     __lowercase					(    a :				NDArray[floataa] )					->					bool:
      __snake_case      :    Dict  			=table.shape

      __snake_case      :    Tuple  			=True

      for i in range(0       ,		SCREAMING_SNAKE_CASE_ ):
            __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()










"""simple docstring"""





from ...configuration_utils import PretrainedConfig
from ...utils import logging


UpperCamelCase_	:				Optional[int]										= logging.get_logger(__name__)

UpperCamelCase_	:				Union[str, Any]										= {"""ctrl""": """https://huggingface.co/ctrl/resolve/main/config.json"""}


class      _lowercase (     lowerCAmelCase						):
      _a   :     str								=   '''ctrl'''
      _a   :     Optional[int]								=   ['''past_key_values''']
      _a   :     List[Any]								=   {
          '''max_position_embeddings''': '''n_positions''',
          '''hidden_size''': '''n_embd''',
          '''num_attention_heads''': '''n_head''',
          '''num_hidden_layers''': '''n_layer''',
      }


      def __init__(    self				:	str							,   a				:	Optional[int]=2_4_6_5_3_4							,   a				:	Optional[int]=2_5_6							,   a				:	Optional[int]=1_2_8_0							,   a				:	Any=8_1_9_2							,   a				:	int=4_8							,   a				:	Optional[Any]=1_6							,   a				:	str=0.1							,   a				:	str=0.1							,   a				:	Any=1e-6							,   a				:	Optional[int]=0.0_2							,   a				:	int=True							,   **a				:	str							,   ):





            """simple docstring"""







            __snake_case      :    Tuple  			=vocab_size
            __snake_case      :    Optional[Any]  			=n_positions
            __snake_case      :    List[Any]  			=n_embd
            __snake_case      :    Any  			=n_layer
            __snake_case      :    Any  			=n_head
            __snake_case      :    str  			=dff
            __snake_case      :    List[str]  			=resid_pdrop
            __snake_case      :    str  			=embd_pdrop
            __snake_case      :    Union[str, Any]  			=layer_norm_epsilon
            __snake_case      :    List[Any]  			=initializer_range

            __snake_case      :    Any  			=use_cache

            super().__init__(**a						)


