parameters: (self, sess)
docstring: Function to run the Sparse Retraining routine on Bonsai Obj
docstring_summary: Function to run the Sparse Retraining routine on Bonsai Obj
docstring_tokens: Function to run the Sparse Retraining routine on Bonsai Obj
function: def runSparseTraining(self, sess):
          '''
          Function to run the Sparse Retraining routine on Bonsai Obj
          '''
          currW = self.bonsaiObj.W.eval()
          currV = self.bonsaiObj.V.eval()
          currZ = self.bonsaiObj.Z.eval()
          currT = self.bonsaiObj.T.eval()
  
          newW = utils.copySupport(self.__thrsdW, currW)
          newV = utils.copySupport(self.__thrsdV, currV)
          newZ = utils.copySupport(self.__thrsdZ, currZ)
          newT = utils.copySupport(self.__thrsdT, currT)
  
          fd_st = {self.__Wth: newW, self.__Vth: newV,
                   self.__Zth: newZ, self.__Tth: newT}
          sess.run(self.sparseRetrainGroup, feed_dict=fd_st)
function_tokens: def runSparseTraining ( self , sess ) : currW = self . bonsaiObj . W . eval ( ) currV = self . bonsaiObj . V . eval ( ) currZ = self . bonsaiObj . Z . eval ( ) currT = self . bonsaiObj . T . eval ( ) newW = utils . copySupport ( self . __thrsdW , currW ) newV = utils . copySupport ( self . __thrsdV , currV ) newZ = utils . copySupport ( self . __thrsdZ , currZ ) newT = utils . copySupport ( self . __thrsdT , currT ) fd_st = { self . __Wth : newW , self . __Vth : newV , self . __Zth : newZ , self . __Tth : newT } sess . run ( self . sparseRetrainGroup , feed_dict = fd_st )