





'''simple docstring'''




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


a__					:			Optional[Any]          =     logging.get_logger(__name__)

a__					:			List[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 				__snake_case     (					_snake_case							):
	__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      ,       UpperCamelCase_=17      ,       UpperCamelCase_=4      ,       UpperCamelCase_=128      ,       UpperCamelCase_=4096      ,       UpperCamelCase_=True      ,       UpperCamelCase_=1      ,       UpperCamelCase_=1024      ,       UpperCamelCase_=3      ,       UpperCamelCase_=1      ,       UpperCamelCase_=None      ,       UpperCamelCase_="relu"      ,       UpperCamelCase_=0.1      ,       UpperCamelCase_=0.1      ,       UpperCamelCase_=0.1      ,       UpperCamelCase_=1E-5      ,       UpperCamelCase_=0.0_2      ,       UpperCamelCase_=True      ,       UpperCamelCase_=True      ,       UpperCamelCase_=5_0256      ,       UpperCamelCase_=5_0256      ,       UpperCamelCase_=False      ,       UpperCamelCase_=False      ,       **UpperCamelCase_      ,       )      ->		Optional[Any]:
		snake_case__	       =   state_dim
		snake_case__	       =   act_dim
		snake_case__	       =   hidden_size
		snake_case__	       =   max_ep_len
		snake_case__	       =   action_tanh
		snake_case__	       =   vocab_size
		snake_case__	       =   n_positions
		snake_case__	       =   n_layer
		snake_case__	       =   n_head
		snake_case__	       =   n_inner
		snake_case__	       =   activation_function
		snake_case__	       =   resid_pdrop
		snake_case__	       =   embd_pdrop
		snake_case__	       =   attn_pdrop
		snake_case__	       =   layer_norm_epsilon
		snake_case__	       =   initializer_range
		snake_case__	       =   scale_attn_weights
		snake_case__	       =   use_cache
		snake_case__	       =   scale_attn_by_inverse_layer_idx
		snake_case__	       =   reorder_and_upcast_attn

		snake_case__	       =   bos_token_id
		snake_case__	       =   eos_token_id

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










'''simple docstring'''

import os
from math import logaa

def     __magic_name__							(				__UpperCAmelCase = "base_exp.txt"   )    ->       int:

   '''simple docstring'''







   __SCREAMING_SNAKE_CASE   				=							0
   __SCREAMING_SNAKE_CASE   				=							0
   for i, line in enumerate(open(os.path.join(os.path.dirname(__UpperCAmelCase   )				,						__UpperCAmelCase   )   )   ):
      __SCREAMING_SNAKE_CASE				,  __SCREAMING_SNAKE_CASE   				=							list(map(__UpperCAmelCase				,						line.split(""","""   )   )   )
      if x * logaa(__UpperCAmelCase   ) > largest:
         __SCREAMING_SNAKE_CASE   				=							x * logaa(__UpperCAmelCase   )
         __SCREAMING_SNAKE_CASE   				=							i + 1
   return result


if __name__ == "__main__":
    print(solution())





