


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


SCREAMING_SNAKE_CASE       :      List[Any]												= logging.get_logger(__name__)

SCREAMING_SNAKE_CASE       :      Optional[Any]												= {
    "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   ):
       lowercase_ :	int     =			"""decision_transformer"""
       lowercase_ :	str     =			["""past_key_values"""]
       lowercase_ :	str     =			{
           """max_position_embeddings""": """n_positions""",
           """num_attention_heads""": """n_head""",
           """num_hidden_layers""": """n_layer""",
       }
       def __init__(					self,      lowerCamelCase=17,      lowerCamelCase=4,      lowerCamelCase=1_28,      lowerCamelCase=40_96,      lowerCamelCase=True,      lowerCamelCase=1,      lowerCamelCase=10_24,      lowerCamelCase=3,      lowerCamelCase=1,      lowerCamelCase=None,      lowerCamelCase="relu",      lowerCamelCase=0.1,      lowerCamelCase=0.1,      lowerCamelCase=0.1,      lowerCamelCase=1E-5,      lowerCamelCase=0.0_2,      lowerCamelCase=True,      lowerCamelCase=True,      lowerCamelCase=5_02_56,      lowerCamelCase=5_02_56,      lowerCamelCase=False,      lowerCamelCase=False,      **lowerCamelCase,      )       ->   List[Any]:




           """simple docstring"""

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

           _lowercase       :							Optional[int]      		=		bos_token_id
           _lowercase       :							int      		=		eos_token_id

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






def 				UpperCamelCase_(      lowerCamelCase_							, lowerCamelCase_							, lowerCamelCase_ )    ->						float:
    _lowercase       :							Tuple      		=		(num_of_terms / 2) * (2 * first_term + (num_of_terms - 1) * common_diff)
    # formula for sum of series
    return total



def 				UpperCamelCase_(      )    ->						Optional[int]:
    print(sum_of_series(1							, 1							, 10 ) )


if __name__ == "__main__":
 import doctest

 doctest.testmod()


