"""simple docstring"""

def      lowercase		(						a__	:		Union[str, Any] ,  a__	:		Union[str, Any]     )						->   str:
					if a < 0 or b < 0:
										raise ValueError('''the value of both inputs must be positive'''     )
					_UpperCamelCase      						=	str(bin(lowercase__     )     )[2:]  # remove the leading "0b"
					_UpperCamelCase      						=	str(bin(lowercase__     )     )[2:]
					_UpperCamelCase      						=	max(len(lowercase__     ) ,  len(lowercase__     )     )
					return "0b" + "".join(
					    str(int('''1''' in (char_a, char_b)     )     )
					    for char_a, char_b in zip(a_binary.zfill(lowercase__     ) ,  b_binary.zfill(lowercase__     )     )     )


if __name__ == "__main__":
		import doctest

		doctest.testmod()



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


_UpperCamelCase 			=		logging.get_logger(__name__)

_UpperCamelCase 			=		{
    "CarlCochet/trajectory-transformer-halfcheetah-medium-v2": (
        "https://huggingface.co/CarlCochet/trajectory-transformer-halfcheetah-medium-v2/resolve/main/config.json"
    ),
    # See all TrajectoryTransformer models at https://huggingface.co/models?filter=trajectory_transformer
}







class   __lowercase      (_UpperCAmelCase ):
 _UpperCamelCase			  =  """trajectory_transformer"""
 _UpperCamelCase			  =  ["""past_key_values"""]
 _UpperCamelCase			  =  {
     """hidden_size""": """n_embd""",
     """num_attention_heads""": """n_head""",
     """num_hidden_layers""": """n_layer""",
 }
 def __init__(							self      ,							A_=100      ,							A_=5      ,							A_=1      ,							A_=1      ,							A_=249      ,							A_=6      ,							A_=17      ,							A_=25      ,							A_=4      ,							A_=4      ,							A_=128      ,							A_=0.1      ,							A_=0.1      ,							A_=0.1      ,							A_=0.0_006      ,							A_=512      ,							A_=0.02      ,							A_=1e-12      ,							A_=1      ,							A_=True      ,							A_=1      ,							A_=5_0256      ,							A_=5_0256      ,							**A_      ,							)					->int:



       '''simple docstring'''





       __lowerCAmelCase					:						Any					=					vocab_size
       __lowerCAmelCase					:						Tuple					=					action_weight
       __lowerCAmelCase					:						Tuple					=					reward_weight
       __lowerCAmelCase					:						Union[str, Any]					=					value_weight
       __lowerCAmelCase					:						List[str]					=					max_position_embeddings
       __lowerCAmelCase					:						str					=					block_size
       __lowerCAmelCase					:						Optional[Any]					=					action_dim
       __lowerCAmelCase					:						Union[str, Any]					=					observation_dim
       __lowerCAmelCase					:						Union[str, Any]					=					transition_dim
       __lowerCAmelCase					:						Dict					=					learning_rate
       __lowerCAmelCase					:						Any					=					n_layer
       __lowerCAmelCase					:						Any					=					n_head
       __lowerCAmelCase					:						Optional[int]					=					n_embd
       __lowerCAmelCase					:						str					=					embd_pdrop
       __lowerCAmelCase					:						Dict					=					attn_pdrop
       __lowerCAmelCase					:						Optional[int]					=					resid_pdrop
       __lowerCAmelCase					:						Union[str, Any]					=					initializer_range
       __lowerCAmelCase					:						Optional[int]					=					layer_norm_eps
       __lowerCAmelCase					:						Any					=					kaiming_initializer_range
       __lowerCAmelCase					:						List[str]					=					use_cache
       super().__init__(pad_token_id=A_      ,							bos_token_id=A_      ,							eos_token_id=A_      ,							**A_					)


