


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   __a			(    __UpperCamelCase      ):
 __lowercase :							Optional[Any]        = 'decision_transformer'
 __lowercase :							List[Any]        = ['past_key_values']
 __lowercase :							Dict        = {
     'max_position_embeddings': 'n_positions',
     'num_attention_heads': 'n_head',
     'num_hidden_layers': 'n_layer',
 }
 def __init__(   self				, lowerCAmelCase__=17				, lowerCAmelCase__=4				, lowerCAmelCase__=128				, lowerCAmelCase__=4_096				, lowerCAmelCase__=True				, lowerCAmelCase__=1				, lowerCAmelCase__=1_024				, 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__=50_256				, lowerCAmelCase__=50_256				, lowerCAmelCase__=False				, lowerCAmelCase__=False				, **lowerCAmelCase__				, )					->				str:




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

        lowercase__:   List[Any]  			=   bos_token_id
        lowercase__:   Union[str, Any]  			=   eos_token_id

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






from __future__ import annotations




def    snake_case_     (  snake_case			,							snake_case     )  ->				bool:
       if len(snake_case     ) == 0:
              return False
       lowercase__:   Any  			=   len(snake_case     ) // 2
       if a_list[midpoint] == item:
              return True
       if item < a_list[midpoint]:
              return binary_search(a_list[:midpoint]			,							snake_case     )
       else:
              return binary_search(a_list[midpoint + 1 :]			,							snake_case     )


if __name__ == "__main__":
 __lowerCAmelCase		       =							input('''Enter numbers separated by comma:\n''').strip()
 __lowerCAmelCase		       =							[int(item.strip()) for item in user_input.split(''',''')]
 __lowerCAmelCase		       =							int(input('''Enter the number to be found in the list:\n''').strip())
 __lowerCAmelCase		       =							'''''' if binary_search(sequence, target) else '''not '''
 print(F'''{target} was {not_str}found in {sequence}''')


