ed7782f0f59f1eef6453f47633fe9e15bda00f84,deepchem/models/tensorflow_models/__init__.py,TensorflowGraphModel,fit,#TensorflowGraphModel#Any#Any#Any#Any#Any#,298

Before Change

            output = fetched_values[:len(self.train_graph.output)]
            loss = fetched_values[-1]
            avg_loss += loss
            y_pred = np.squeeze(np.array(output))
            y_b = y_b.flatten()
            n_batches += 1
          if epoch % checkpoint_interval == checkpoint_interval - 1:
            saver.save(sess, self._save_path, global_step=epoch)

After Change

            epoch_end_indices.append(index)
          sess.run(self.train_graph.graph.queue.close())

        epoch_end_indices = []
        enqueue_thread = threading.Thread(target=enqueue, args=[sess, dataset, nb_epoch, epoch_end_indices])
        enqueue_thread.daemon = True
        enqueue_thread.start()

        // Main training loop.
        try:
          epoch = 0
          index = 0
          index_in_epoch = 0
          avg_loss = 0.0
          while True:
            if index_in_epoch % log_every_N_batches == 0:
              log("On batch %d" % index_in_epoch, self.verbose)
            // Run training op.
            fetches = self.train_graph.output + [
                train_op, self.train_graph.loss
            ]
            fetched_values = sess.run(fetches)
            loss = fetched_values[-1]
            avg_loss += loss
            index += 1
            index_in_epoch += 1
            if len(epoch_end_indices) > 0 and index >= epoch_end_indices[0]:
              // We have reached the end of an epoch.
              if epoch % checkpoint_interval == checkpoint_interval - 1:
                saver.save(sess, self._save_path, global_step=epoch)
              avg_loss = float(avg_loss) / index_in_epoch
              log("Ending epoch %d: Average loss %g" % (epoch, avg_loss),
                  self.verbose)
              index_in_epoch = 0
              avg_loss = 0.0
              del epoch_end_indices[0]
        except tf.errors.OutOfRangeError:
          // We have reached the end of the data.
          pass
        // Always save a final checkpoint when complete.

Instances