



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__							:   List[str]  	=    "decision_transformer"
       UpperCAmelCase__							:   Union[str, Any]  	=    ["past_key_values"]
       UpperCAmelCase__							:   Optional[int]  	=    {
           "max_position_embeddings": "n_positions",
           "num_attention_heads": "n_head",
           "num_hidden_layers": "n_layer",
       }
       def __init__(     self,     SCREAMING_SNAKE_CASE_=17,     SCREAMING_SNAKE_CASE_=4,     SCREAMING_SNAKE_CASE_=128,     SCREAMING_SNAKE_CASE_=4096,     SCREAMING_SNAKE_CASE_=True,     SCREAMING_SNAKE_CASE_=1,     SCREAMING_SNAKE_CASE_=1024,     SCREAMING_SNAKE_CASE_=3,     SCREAMING_SNAKE_CASE_=1,     SCREAMING_SNAKE_CASE_=None,     SCREAMING_SNAKE_CASE_="relu",     SCREAMING_SNAKE_CASE_=0.1,     SCREAMING_SNAKE_CASE_=0.1,     SCREAMING_SNAKE_CASE_=0.1,     SCREAMING_SNAKE_CASE_=1e-5,     SCREAMING_SNAKE_CASE_=0.02,     SCREAMING_SNAKE_CASE_=True,     SCREAMING_SNAKE_CASE_=True,     SCREAMING_SNAKE_CASE_=5_0256,     SCREAMING_SNAKE_CASE_=5_0256,     SCREAMING_SNAKE_CASE_=False,     SCREAMING_SNAKE_CASE_=False,     **SCREAMING_SNAKE_CASE_,     )	->						str:
          UpperCamelCase       :    Optional[int]		      =      state_dim
          UpperCamelCase       :    Optional[int]		      =      act_dim
          UpperCamelCase       :    Tuple		      =      hidden_size
          UpperCamelCase       :    int		      =      max_ep_len
          UpperCamelCase       :    List[str]		      =      action_tanh
          UpperCamelCase       :    Dict		      =      vocab_size
          UpperCamelCase       :    Optional[int]		      =      n_positions
          UpperCamelCase       :    List[str]		      =      n_layer
          UpperCamelCase       :    Optional[int]		      =      n_head
          UpperCamelCase       :    Optional[Any]		      =      n_inner
          UpperCamelCase       :    Any		      =      activation_function
          UpperCamelCase       :    Any		      =      resid_pdrop
          UpperCamelCase       :    List[str]		      =      embd_pdrop
          UpperCamelCase       :    str		      =      attn_pdrop
          UpperCamelCase       :    List[str]		      =      layer_norm_epsilon
          UpperCamelCase       :    Tuple		      =      initializer_range
          UpperCamelCase       :    int		      =      scale_attn_weights
          UpperCamelCase       :    Optional[int]		      =      use_cache
          UpperCamelCase       :    Dict		      =      scale_attn_by_inverse_layer_idx
          UpperCamelCase       :    Tuple		      =      reorder_and_upcast_attn

          UpperCamelCase       :    Union[str, Any]		      =      bos_token_id
          UpperCamelCase       :    Optional[int]		      =      eos_token_id

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









def      lowerCamelCase_						(			UpperCamelCase__							: str )	->			bool:





				"""simple docstring"""


				__lowerCamelCase									=       0
				for ch in input_str:
								__lowerCamelCase									=       ord(UpperCamelCase__ )
								__lowerCamelCase									=       pow(2					,	UpperCamelCase__ )

								# If we already turned on bit for current character's unicode
								if bitmap >> ch_unicode & 1 == 1:
												return False
								bitmap |= ch_bit_index_on
				return True


if __name__ == "__main__":
					import doctest

					doctest.testmod()


