00135a70697dc9b4611971e5833e2d84501c3da7,keras/engine/training.py,Model,train_step,#Model#Any#,747

Before Change

          y, y_pred, sample_weight, regularization_losses=self.losses)
    self.optimizer.minimize(loss, self.trainable_variables, tape=tape)
    self.compiled_metrics.update_state(y, y_pred, sample_weight)
    return {m.name: m.result() for m in self.metrics}

  def make_train_function(self):
    Creates a function that executes one step of training.

After Change

    self.compiled_metrics.update_state(y, y_pred, sample_weight)
    // Collect metrics to return
    return_metrics = {}
    for metric in self.metrics:
      result = metric.result()
      if isinstance(result, dict):
        return_metrics.update(result)
      else:
        return_metrics[metric.name] = result
    return return_metrics

  def make_train_function(self):
    Creates a function that executes one step of training.

Instances