





'''simple docstring'''






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  _A (					__lowercase		):
		lowercase__:   Any				     =   '''decision_transformer'''
		lowercase__:   Union[str, Any]				     =   ['''past_key_values''']
		lowercase__:   List[str]				     =   {
		    '''max_position_embeddings''': '''n_positions''',
		    '''num_attention_heads''': '''n_head''',
		    '''num_hidden_layers''': '''n_layer''',
		}

		def __init__(   self					:   Tuple  ,      __magic_name__					:   Optional[Any]=17  ,      __magic_name__					:   Any=4  ,      __magic_name__					:   Union[str, Any]=1_28  ,      __magic_name__					:   Optional[Any]=40_96  ,      __magic_name__					:   List[Any]=True  ,      __magic_name__					:   List[Any]=1  ,      __magic_name__					:   Optional[Any]=10_24  ,      __magic_name__					:   Union[str, Any]=3  ,      __magic_name__					:   Tuple=1  ,      __magic_name__					:   Dict=None  ,      __magic_name__					:   Tuple="relu"  ,      __magic_name__					:   List[str]=0.1  ,      __magic_name__					:   Optional[int]=0.1  ,      __magic_name__					:   Any=0.1  ,      __magic_name__					:   str=1E-5  ,      __magic_name__					:   Dict=0.02  ,      __magic_name__					:   List[str]=True  ,      __magic_name__					:   List[str]=True  ,      __magic_name__					:   Optional[int]=5_02_56  ,      __magic_name__					:   Optional[Any]=5_02_56  ,      __magic_name__					:   int=False  ,      __magic_name__					:   Union[str, Any]=False  ,      **__magic_name__					:   int  ,      )					->    int:


					"""simple docstring"""

					__snake_case					:      str							      =     state_dim
					__snake_case					:      Optional[Any]							      =     act_dim
					__snake_case					:      Dict							      =     hidden_size
					__snake_case					:      int							      =     max_ep_len
					__snake_case					:      Any							      =     action_tanh
					__snake_case					:      Union[str, Any]							      =     vocab_size
					__snake_case					:      Optional[Any]							      =     n_positions
					__snake_case					:      Optional[int]							      =     n_layer
					__snake_case					:      List[Any]							      =     n_head
					__snake_case					:      Tuple							      =     n_inner
					__snake_case					:      int							      =     activation_function
					__snake_case					:      List[Any]							      =     resid_pdrop
					__snake_case					:      Union[str, Any]							      =     embd_pdrop
					__snake_case					:      int							      =     attn_pdrop
					__snake_case					:      Optional[Any]							      =     layer_norm_epsilon
					__snake_case					:      Optional[Any]							      =     initializer_range
					__snake_case					:      str							      =     scale_attn_weights
					__snake_case					:      str							      =     use_cache
					__snake_case					:      List[Any]							      =     scale_attn_by_inverse_layer_idx
					__snake_case					:      Dict							      =     reorder_and_upcast_attn

					__snake_case					:      Any							      =     bos_token_id
					__snake_case					:      Dict							      =     eos_token_id

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









'''simple docstring'''






def 					_a						(       _lowerCamelCase ) ->				int:



			"""simple docstring"""


			if not isinstance(_lowerCamelCase    ,	_lowerCamelCase ):
						raise TypeError("""only integers accepted as input""" )
			else:
						__snake_case					:      List[Any]							      =     str(abs(_lowerCamelCase ) )
						__snake_case					:      Union[str, Any]							      =     [list(_lowerCamelCase ) for char in range(len(_lowerCamelCase ) )]
						for index in range(len(_lowerCamelCase ) ):
									num_transpositions[index].pop(_lowerCamelCase )
						return max(
						    int("""""".join(list(_lowerCamelCase ) ) ) for transposition in num_transpositions )


if __name__ == "__main__":
	__import__("doctest").testmod()


