



from __future__ import annotations

from decimal import Decimal

from numpy import array





def 							A     (					_UpperCAmelCase    :       list[list[float]]   )    ->			list[list[float]]:







			'''simple docstring'''
			_UpperCAmelCase			=       Decimal

			# Check if the provided matrix has 2 rows and 2 columns
			# since this implementation only works for 2x2 matrices
			if len(lowerCAmelCase__   ) == 2 and len(matrix[0]   ) == 2 and len(matrix[1]   ) == 2:
						# Calculate the determinant of the matrix
						_UpperCAmelCase			=       float(
						    d(matrix[0][0]   ) * d(matrix[1][1]   ) - d(matrix[1][0]   ) * d(matrix[0][1]   )   )
						if determinant == 0:
									raise ValueError('This matrix has no inverse.'   )

						# Creates a copy of the matrix with swapped positions of the elements
						_UpperCAmelCase			=       [[0.0, 0.0], [0.0, 0.0]]
						_UpperCAmelCase	,					_UpperCAmelCase			=       matrix[1][1], matrix[0][0]
						_UpperCAmelCase	,					_UpperCAmelCase			=       -matrix[1][0], -matrix[0][1]

						# Calculate the inverse of the matrix
						return [
						    [(float(d(lowerCAmelCase__   )   ) / determinant) or 0.0 for n in row] for row in swapped_matrix
						]
			elif (
			    len(lowerCAmelCase__   ) == 3
			    and len(matrix[0]   ) == 3
			    and len(matrix[1]   ) == 3
			    and len(matrix[2]   ) == 3
			):
						# Calculate the determinant of the matrix using Sarrus rule
						_UpperCAmelCase			=       float(
						    (
						        (d(matrix[0][0]   ) * d(matrix[1][1]   ) * d(matrix[2][2]   ))
						        + (d(matrix[0][1]   ) * d(matrix[1][2]   ) * d(matrix[2][0]   ))
						        + (d(matrix[0][2]   ) * d(matrix[1][0]   ) * d(matrix[2][1]   ))
						    )
						    - (
						        (d(matrix[0][2]   ) * d(matrix[1][1]   ) * d(matrix[2][0]   ))
						        + (d(matrix[0][1]   ) * d(matrix[1][0]   ) * d(matrix[2][2]   ))
						        + (d(matrix[0][0]   ) * d(matrix[1][2]   ) * d(matrix[2][1]   ))
						    )   )
						if determinant == 0:
									raise ValueError('This matrix has no inverse.'   )

						# Creating cofactor matrix
						_UpperCAmelCase			=       [
						    [d(0.0   ), d(0.0   ), d(0.0   )],
						    [d(0.0   ), d(0.0   ), d(0.0   )],
						    [d(0.0   ), d(0.0   ), d(0.0   )],
						]
						_UpperCAmelCase			=       (d(matrix[1][1]   ) * d(matrix[2][2]   )) - (
						    d(matrix[1][2]   ) * d(matrix[2][1]   )
						)
						_UpperCAmelCase			=       -(
						    (d(matrix[1][0]   ) * d(matrix[2][2]   )) - (d(matrix[1][2]   ) * d(matrix[2][0]   ))
						)
						_UpperCAmelCase			=       (d(matrix[1][0]   ) * d(matrix[2][1]   )) - (
						    d(matrix[1][1]   ) * d(matrix[2][0]   )
						)
						_UpperCAmelCase			=       -(
						    (d(matrix[0][1]   ) * d(matrix[2][2]   )) - (d(matrix[0][2]   ) * d(matrix[2][1]   ))
						)
						_UpperCAmelCase			=       (d(matrix[0][0]   ) * d(matrix[2][2]   )) - (
						    d(matrix[0][2]   ) * d(matrix[2][0]   )
						)
						_UpperCAmelCase			=       -(
						    (d(matrix[0][0]   ) * d(matrix[2][1]   )) - (d(matrix[0][1]   ) * d(matrix[2][0]   ))
						)
						_UpperCAmelCase			=       (d(matrix[0][1]   ) * d(matrix[1][2]   )) - (
						    d(matrix[0][2]   ) * d(matrix[1][1]   )
						)
						_UpperCAmelCase			=       -(
						    (d(matrix[0][0]   ) * d(matrix[1][2]   )) - (d(matrix[0][2]   ) * d(matrix[1][0]   ))
						)
						_UpperCAmelCase			=       (d(matrix[0][0]   ) * d(matrix[1][1]   )) - (
						    d(matrix[0][1]   ) * d(matrix[1][0]   )
						)

						# Transpose the cofactor matrix (Adjoint matrix)
						_UpperCAmelCase			=       array(lowerCAmelCase__   )
						for i in range(3   ):
									for j in range(3   ):
												_UpperCAmelCase			=       cofactor_matrix[j][i]

        # Inverse of the matrix using the formula (1/determinant) * adjoint matrix
						_UpperCAmelCase			=       array(lowerCAmelCase__   )
						for i in range(3   ):
									for j in range(3   ):
												inverse_matrix[i][j] /= d(lowerCAmelCase__   )

        # Calculate the inverse of the matrix
						return [[float(d(lowerCAmelCase__   )   ) or 0.0 for n in row] for row in inverse_matrix]
			raise ValueError('Please provide a matrix of size 2x2 or 3x3.'   )





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


UpperCAmelCase__       =	logging.get_logger(__name__)

UpperCAmelCase__       =	{
    "edbeeching/decision-transformer-gym-hopper-medium": (
        "https://huggingface.co/edbeeching/decision-transformer-gym-hopper-medium/resolve/main/config.json"
    ),
    # See all DecisionTransformer models at https://huggingface.co/models?filter=decision_transformer
}







class       __lowerCAmelCase   (      A						):
			UpperCamelCase        =					'''decision_transformer'''
			UpperCamelCase        =					['''past_key_values''']
			UpperCamelCase        =					{
			    '''max_position_embeddings''': '''n_positions''',
			    '''num_attention_heads''': '''n_head''',
			    '''num_hidden_layers''': '''n_layer''',
			}



			def __init__(						self       :  Any			,		A       :  Optional[int]=17			,		A       :  List[str]=4			,		A       :  int=1_28			,		A       :  Union[str, Any]=40_96			,		A       :  Any=True			,		A       :  Any=1			,		A       :  List[Any]=10_24			,		A       :  List[Any]=3			,		A       :  Tuple=1			,		A       :  Any=None			,		A       :  Optional[int]="relu"			,		A       :  Union[str, Any]=0.1			,		A       :  Optional[int]=0.1			,		A       :  Optional[int]=0.1			,		A       :  Optional[int]=1E-5			,		A       :  List[Any]=0.0_2			,		A       :  Tuple=True			,		A       :  Union[str, Any]=True			,		A       :  str=5_02_56			,		A       :  Union[str, Any]=5_02_56			,		A       :  List[Any]=False			,		A       :  Optional[int]=False			,		**A       :  int			,		)       ->   Union[str, Any]:



						"""simple docstring"""






						_UpperCAmelCase			=       state_dim
						_UpperCAmelCase			=       act_dim
						_UpperCAmelCase			=       hidden_size
						_UpperCAmelCase			=       max_ep_len
						_UpperCAmelCase			=       action_tanh
						_UpperCAmelCase			=       vocab_size
						_UpperCAmelCase			=       n_positions
						_UpperCAmelCase			=       n_layer
						_UpperCAmelCase			=       n_head
						_UpperCAmelCase			=       n_inner
						_UpperCAmelCase			=       activation_function
						_UpperCAmelCase			=       resid_pdrop
						_UpperCAmelCase			=       embd_pdrop
						_UpperCAmelCase			=       attn_pdrop
						_UpperCAmelCase			=       layer_norm_epsilon
						_UpperCAmelCase			=       initializer_range
						_UpperCAmelCase			=       scale_attn_weights
						_UpperCAmelCase			=       use_cache
						_UpperCAmelCase			=       scale_attn_by_inverse_layer_idx
						_UpperCAmelCase			=       reorder_and_upcast_attn

						_UpperCAmelCase			=       bos_token_id
						_UpperCAmelCase			=       eos_token_id

						super().__init__(bos_token_id=A			,		eos_token_id=A			,		**A)
