






"""simple docstring"""


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


_UpperCamelCase    :   Optional[int]   			=						logging.get_logger(__name__)

_UpperCamelCase    :   Optional[int]   			=						{
    '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 						snake_case  (  UpperCAmelCase	):
    __magic_name__   					=					'''decision_transformer'''
    __magic_name__   					=					['''past_key_values''']
    __magic_name__   					=					{
        '''max_position_embeddings''': '''n_positions''',
        '''num_attention_heads''': '''n_head''',
        '''num_hidden_layers''': '''n_layer''',
    }





    def __init__(							self     : Tuple    ,		A     : int=1_7    ,		A     : Any=4    ,		A     : int=1_2_8    ,		A     : Union[str, Any]=4_0_9_6    ,		A     : Optional[Any]=True    ,		A     : Optional[Any]=1    ,		A     : Union[str, Any]=1_0_2_4    ,		A     : Dict=3    ,		A     : Any=1    ,		A     : Any=None    ,		A     : Tuple="relu"    ,		A     : Optional[Any]=0.1    ,		A     : str=0.1    ,		A     : int=0.1    ,		A     : Dict=1E-5    ,		A     : Dict=0.02    ,		A     : Any=True    ,		A     : Dict=True    ,		A     : Dict=5_0_2_5_6    ,		A     : int=5_0_2_5_6    ,		A     : Tuple=False    ,		A     : List[Any]=False    ,		**A     : Tuple    ,		):


      '''simple docstring'''




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

      a					:      Tuple    =       bos_token_id
      a					:      Any    =       eos_token_id

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












"""simple docstring"""


def       snake_case  (A_				:int				):







  '''simple docstring'''

  if isinstance(A_     ,      A_				):
    raise TypeError('\'float\' object cannot be interpreted as an integer'				)
  if isinstance(A_     ,      A_				):
    raise TypeError('\'str\' object cannot be interpreted as an integer'				)

  if num == 0:
    return "0b0"

  a					:      List[Any]    =       False

  if num < 0:
    a					:      Optional[int]    =       True
    a					:      Dict    =       -num

  a					:      list[int]    =       []
  while num > 0:
    binary.insert(0     ,      num % 2				)
    num >>= 1

  if negative:
    return "-0b" + "".join(str(A_				) for e in binary				)

  return "0b" + "".join(str(A_				) for e in binary				)


if __name__ == "__main__":
   import doctest

   doctest.testmod()




