6e5cf676b113af8d70e34224f23bc8eace618856,mloop/nnlearner.py,SingleNeuralNet,fit,#SingleNeuralNet#Any#Any#,120

Before Change

                + str(self.tf_session.run(
                        self.loss_func,
                        feed_dict={self.input_placeholder: params,
                                   self.output_placeholder: [[c] for c in costs],
                                   self.regularisation_coefficient_placeholder: 0,
                                   })))

After Change

                                                   self.regularisation_coefficient_placeholder: self.regularisation_coefficient,
                                                   self.keep_prob_placeholder: self.keep_prob,
                                                   })
            (l, ul) = self._loss(params, costs)
            self.log.debug("Fit neural network with total training cost " + str(l)
                    + ", with unregularized cost " + str(ul))
            if l > threshold:
                break

Instances