def test__training_step__tr_batch_end__flow_dict(tmp_path):
    """Tests that only training_step can be used."""

    class TestModel(DeterministicModel):
        def training_step(self, batch, batch_idx):
            acc = self.step(batch, batch_idx)
            acc = acc + batch_idx
            self.training_step_called = True
            self.out = {"loss": acc, "random_things": [1, "a", torch.tensor(2)]}
            return self.out

        def on_train_batch_end(self, tr_step_output, *_):
            assert self.count_num_graphs(tr_step_output) == 0

        def backward(self, loss):
            return LightningModule.backward(self, loss)

    model = TestModel()
    model.val_dataloader = None

    trainer = Trainer(
        default_root_dir=tmp_path,
        limit_train_batches=2,
        limit_val_batches=2,
        max_epochs=2,
        log_every_n_steps=1,
        enable_model_summary=False,
    )
    trainer.fit(model)

    # make sure correct steps were called
    assert model.training_step_called
Tests that only training_step can be used.
tests/tests_pytorch/loops/test_training_loop_flow_dict.py