original_docstring: Returns the index number for the next action.
  
          The epsilon greedy strategy for taking the action depends on if the
          model is in training mode or in testing/running mode.
          
docstring: Returns the index number for the next action.
  The epsilon greedy strategy for taking the action depends on if the
  model is in training mode or in testing/running mode.
docstring_tokens: Returns the index number for the next action . The epsilon greedy strategy for taking the action depends on if the model is in training mode or in testing / running mode .
code: def select_action(
          self,
          state_idx:tuple,
          train_mode:bool,
      ):
          """Returns the index number for the next action.
  
          The epsilon greedy strategy for taking the action depends on if the
          model is in training mode or in testing/running mode.
          """
          epsilon = self.train_epsilon if train_mode else self.run_epsilon
          return self.epsilon_greedy_strategy(state_idx, self.q_func, epsilon)
code_tokens: def select_action ( self , state_idx : tuple , train_mode : bool , ) : epsilon = self . train_epsilon if train_mode else self . run_epsilon return self . epsilon_greedy_strategy ( state_idx , self . q_func , epsilon )
short_docstring: Returns the index number for the next action.
short_docstring_tokens: Returns the index number for the next action .
comment: """Returns the index number for the next action.
  
          The epsilon greedy strategy for taking the action depends on if the
          model is in training mode or in testing/running mode.
          """