





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


_lowerCamelCase   				=			logging.get_logger(__name__)

_lowerCamelCase   				=			{
    '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   UpperCamelCase_       (     UpperCamelCase__    ):
							lowerCamelCase_           =					"decision_transformer"
							lowerCamelCase_           =					["past_key_values"]
							lowerCamelCase_           =					{
							    "max_position_embeddings": "n_positions",
							    "num_attention_heads": "n_head",
							    "num_hidden_layers": "n_layer",
							}


							def __init__(							self    :str							,				__A    :List[Any]=17							,				__A    :Optional[int]=4							,				__A    :str=128							,				__A    :int=4096							,				__A    :Any=True							,				__A    :int=1							,				__A    :int=1024							,				__A    :int=3							,				__A    :Union[str, Any]=1							,				__A    :int=None							,				__A    :str="relu"							,				__A    :Union[str, Any]=0.1							,				__A    :Tuple=0.1							,				__A    :Optional[int]=0.1							,				__A    :Optional[int]=1E-5							,				__A    :int=0.0_2							,				__A    :Any=True							,				__A    :Dict=True							,				__A    :Optional[int]=5_0256							,				__A    :Dict=5_0256							,				__A    :str=False							,				__A    :Optional[Any]=False							,				**__A    :Any							,				)   ->   List[str]:



									"""simple docstring"""



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

									SCREAMING_SNAKE_CASE__			=      bos_token_id
									SCREAMING_SNAKE_CASE__			=      eos_token_id

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






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


_lowerCamelCase   				=			logging.get_logger(__name__)




class   UpperCamelCase_       (     UpperCamelCase__    ):
							lowerCamelCase_           =					"timm_backbone"


							def __init__(							self    :Union[str, Any]							,				__A    :str=None							,				__A    :Union[str, Any]=3							,				__A    :str=True							,				__A    :Any=True							,				__A    :Optional[Any]=None							,				**__A    :List[str]							,				)   ->   Tuple:



									"""simple docstring"""



									super().__init__(**__A		)
									SCREAMING_SNAKE_CASE__			=      backbone
									SCREAMING_SNAKE_CASE__			=      num_channels
									SCREAMING_SNAKE_CASE__			=      features_only
									SCREAMING_SNAKE_CASE__			=      use_pretrained_backbone
									SCREAMING_SNAKE_CASE__			=      True
									SCREAMING_SNAKE_CASE__			=      out_indices if out_indices is not None else (-1,)