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


A__       :   Any   						=					logging.get_logger(__name__)

A__       :   Any   						=					{
    """openbmb/cpm-ant-10b""": """https://huggingface.co/openbmb/cpm-ant-10b/blob/main/config.json"""
    # See all CPMAnt models at https://huggingface.co/models?filter=cpmant
}





class 						lowercase       (  __UpperCamelCase					):
					__a					=    """cpmant"""
					def __init__(		self ,	SCREAMING_SNAKE_CASE__ = 30720 ,	SCREAMING_SNAKE_CASE__ = 4096 ,	SCREAMING_SNAKE_CASE__ = 32 ,	SCREAMING_SNAKE_CASE__ = 128 ,	SCREAMING_SNAKE_CASE__ = 10240 ,	SCREAMING_SNAKE_CASE__ = 48 ,	SCREAMING_SNAKE_CASE__ = 0.0 ,	SCREAMING_SNAKE_CASE__ = 512 ,	SCREAMING_SNAKE_CASE__ = 2048 ,	SCREAMING_SNAKE_CASE__ = 1E-6 ,	SCREAMING_SNAKE_CASE__ = 1.0 ,	SCREAMING_SNAKE_CASE__ = 32 ,	SCREAMING_SNAKE_CASE__ = 32 ,	SCREAMING_SNAKE_CASE__ = 32 ,	SCREAMING_SNAKE_CASE__ = True ,	**SCREAMING_SNAKE_CASE__ ,	):
								"""simple docstring"""







								super().__init__(**SCREAMING_SNAKE_CASE__    )
								lowerCAmelCase__ :    int				      =			prompt_types
								lowerCAmelCase__ :    List[Any]				      =			prompt_length
								lowerCAmelCase__ :    Union[str, Any]				      =			segment_types
								lowerCAmelCase__ :    List[Any]				      =			hidden_size
								lowerCAmelCase__ :    Any				      =			num_attention_heads
								lowerCAmelCase__ :    Any				      =			dim_head
								lowerCAmelCase__ :    int				      =			dim_ff
								lowerCAmelCase__ :    Union[str, Any]				      =			num_hidden_layers
								lowerCAmelCase__ :    Any				      =			position_bias_num_buckets
								lowerCAmelCase__ :    Any				      =			position_bias_max_distance
								lowerCAmelCase__ :    Union[str, Any]				      =			dropout_p
								lowerCAmelCase__ :    str				      =			eps
								lowerCAmelCase__ :    Optional[Any]				      =			use_cache
								lowerCAmelCase__ :    Any				      =			vocab_size
								lowerCAmelCase__ :    int				      =			init_std





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



def      _a     (   __UpperCamelCase       :  NDArray[floataa]	,__UpperCamelCase       :  NDArray[floataa]    ):
			lowerCAmelCase__      ,				lowerCAmelCase__ :    Any				      =			np.shape(__UpperCamelCase    )

			lowerCAmelCase__ :    NDArray[floataa]				      =			np.zeros((rows, 1)	,dtype=__UpperCamelCase    )
			for row in reversed(range(__UpperCamelCase    )    ):
						lowerCAmelCase__ :    List[str]				      =			0
						for col in range(row + 1	,__UpperCamelCase    ):
									total += coefficients[row, col] * x[col]

						lowerCAmelCase__ :    int				      =			(vector[row] - total) / coefficients[row, row]

			return x



def      _a     (   __UpperCamelCase       :  NDArray[floataa]	,__UpperCamelCase       :  NDArray[floataa]    ):
			lowerCAmelCase__      ,				lowerCAmelCase__ :    str				      =			np.shape(__UpperCamelCase    )
			if rows != columns:
						return np.array(()	,dtype=__UpperCamelCase    )

			# augmented matrix
			lowerCAmelCase__ :    NDArray[floataa]				      =			np.concatenate((coefficients, vector)	,axis=1    )
			lowerCAmelCase__ :    List[str]				      =			augmented_mat.astype('''float64'''    )

			# scale the matrix leaving it triangular
			for row in range(rows - 1    ):
						lowerCAmelCase__ :    str				      =			augmented_mat[row, row]
						for col in range(row + 1	,__UpperCamelCase    ):
									lowerCAmelCase__ :    Optional[int]				      =			augmented_mat[col, row] / pivot
									augmented_mat[col, :] -= factor * augmented_mat[row, :]

			lowerCAmelCase__ :    int				      =			retroactive_resolution(
			    augmented_mat[:, 0:columns]	,augmented_mat[:, columns : columns + 1]    )

			return x


if __name__ == "__main__":
							import doctest

							doctest.testmod()



