

"""simple docstring"""




from __future__ import annotations

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






def        SCREAMING_SNAKE_CASE__	(  lowerCamelCase__     ,			lowerCamelCase__     ,			lowerCamelCase__     ,			lowerCamelCase__     ,			)  ->					list[float]:
	__lowerCamelCase    :    str 	=			coefficient_matrix.shape
	__lowerCamelCase    :    Optional[Any] 	=			constant_matrix.shape

	if rowsa != colsa:
		__lowerCamelCase    :    Optional[int] 	=			F"Coefficient matrix dimensions must be nxn but received {rowsa}x{colsa}"
		raise ValueError(lowerCamelCase__      )

	if colsa != 1:
		__lowerCamelCase    :    str 	=			F"Constant matrix must be nx1 but received {rowsa}x{colsa}"
		raise ValueError(lowerCamelCase__      )

	if rowsa != rowsa:
		__lowerCamelCase    :    int 	=			(
		    'Coefficient and constant matrices dimensions must be nxn and nx1 but '
		    F"received {rowsa}x{colsa} and {rowsa}x{colsa}"
		)
		raise ValueError(lowerCamelCase__      )

	if len(lowerCamelCase__      ) != rowsa:
		__lowerCamelCase    :    str 	=			(
		    'Number of initial values must be equal to number of rows in coefficient '
		    F"matrix but received {len(lowerCamelCase__      )} and {rowsa}"
		)
		raise ValueError(lowerCamelCase__      )

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

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

	__lowerCamelCase    :    Any 	=			table.shape

	strictly_diagonally_dominant(lowerCamelCase__      )

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

	return [float(lowerCamelCase__      ) for i in new_val]






def        SCREAMING_SNAKE_CASE__	(  lowerCamelCase__      )  ->					bool:
	__lowerCamelCase    :    Dict 	=			table.shape

	__lowerCamelCase    :    Any 	=			True

	for i in range(0     ,			lowerCamelCase__      ):
		__lowerCamelCase    :    List[Any] 	=			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()







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


a		=logging.get_logger(__name__)

a		={
    """sayakpaul/vit-msn-base""": """https://huggingface.co/sayakpaul/vit-msn-base/resolve/main/config.json""",
    # See all ViT MSN models at https://huggingface.co/models?filter=vit_msn
}






class 	A_		(	SCREAMING_SNAKE_CASE    ):
							_UpperCAmelCase   :  str										=				'''vit_msn'''
							def __init__(		self		:      Any       ,SCREAMING_SNAKE_CASE__		:      int=7_6_8       ,SCREAMING_SNAKE_CASE__		:      Optional[int]=1_2       ,SCREAMING_SNAKE_CASE__		:      Optional[Any]=1_2       ,SCREAMING_SNAKE_CASE__		:      Tuple=3_0_7_2       ,SCREAMING_SNAKE_CASE__		:      str="gelu"       ,SCREAMING_SNAKE_CASE__		:      Any=0.0       ,SCREAMING_SNAKE_CASE__		:      str=0.0       ,SCREAMING_SNAKE_CASE__		:      Any=0.02       ,SCREAMING_SNAKE_CASE__		:      int=1E-06       ,SCREAMING_SNAKE_CASE__		:      Optional[int]=2_2_4       ,SCREAMING_SNAKE_CASE__		:      Dict=1_6       ,SCREAMING_SNAKE_CASE__		:      int=3       ,SCREAMING_SNAKE_CASE__		:      List[str]=True       ,**SCREAMING_SNAKE_CASE__		:      str       ,):
								super().__init__(**SCREAMING_SNAKE_CASE__)

								__lowerCamelCase    :    List[Any] 	=			hidden_size
								__lowerCamelCase    :    Tuple 	=			num_hidden_layers
								__lowerCamelCase    :    Union[str, Any] 	=			num_attention_heads
								__lowerCamelCase    :    Dict 	=			intermediate_size
								__lowerCamelCase    :    List[Any] 	=			hidden_act
								__lowerCamelCase    :    Optional[Any] 	=			hidden_dropout_prob
								__lowerCamelCase    :    str 	=			attention_probs_dropout_prob
								__lowerCamelCase    :    List[str] 	=			initializer_range
								__lowerCamelCase    :    Optional[int] 	=			layer_norm_eps
								__lowerCamelCase    :    Tuple 	=			image_size
								__lowerCamelCase    :    Union[str, Any] 	=			patch_size
								__lowerCamelCase    :    Optional[Any] 	=			num_channels
								__lowerCamelCase    :    List[str] 	=			qkv_bias




