    def training_step(self, train_batch, batch_idx):
        """
        Training the data as batches and returns training loss on each batch

        :param train_batch: Batch data
        :param batch_idx: Batch indices

        :return: output - Training loss
        """
        x, y = train_batch
        logits = self.forward(x)
        loss = self.cross_entropy_loss(logits, y)
        return {"loss": loss}
Training the data as batches and returns training loss on each batch

:param train_batch: Batch data
:param batch_idx: Batch indices

:return: output - Training loss
tests/integration/frameworks/mlflow/MNIST/mnist_autolog_example.py