original_docstring: 
          Train the (local) network and update the target network 
          
docstring: Train the (local) network and update the target network
docstring_tokens: Train the ( local ) network and update the target network
code: def _learn(self):    
          """
          Train the (local) network and update the target network 
          """
          if len(self.memory) <= self.batchSize*self.batchEpochs:
              return
          
          for _ in range(self.batchEpochs):
              # repeat gradient descent for self.batchEpochs             
              self._batchStep(self.batchSize)
              
          # update the target network
          if self.targetDqnUpdatePace < 1:
              self.softTargetUpdate()
          elif self.numberExperiences %  (self.targetDqnUpdatePace) == 0: 
              self.hardTargetUpdate()
code_tokens: def _learn ( self ) : if len ( self . memory ) <= self . batchSize * self . batchEpochs : return for _ in range ( self . batchEpochs ) : self . _batchStep ( self . batchSize ) if self . targetDqnUpdatePace < 1 : self . softTargetUpdate ( ) elif self . numberExperiences % ( self . targetDqnUpdatePace ) == 0 : self . hardTargetUpdate ( )
short_docstring: Train the (local) network and update the target network
short_docstring_tokens: Train the ( local ) network and update the target network
comment: """
          Train the (local) network and update the target network 
          """$SEP$# repeat gradient descent for self.batchEpochs             $SEP$# update the target network