def METHOD_NAME(inception_model_pytorch):
    """Test the InceptionBlocks model that WebGME folks provided us."""
    galaxy_images_output = torch.zeros((1, 5, 64, 64))
    ebv_output = torch.zeros((1,))
    # Run the model once to get some ground truth outpot (from PyTorch)
    output = inception_model_pytorch(galaxy_images_output, ebv_output).detach().numpy()
    # Convert to MDF
    mdf_model, params_dict = pytorch_to_mdf(
        model=inception_model_pytorch,
        args=(galaxy_images_output, ebv_output),
        trace=True,
    )
    # Get the graph
    mdf_graph = mdf_model.graphs[0]
    # Add inputs to the parameters dict so we can feed this to the EvaluableGraph for initialization of all
    # graph inputs.
    params_dict["input1"] = galaxy_images_output.numpy()
    params_dict["input2"] = ebv_output.numpy()
    eg = EvaluableGraph(graph=mdf_graph, verbose=False)
    eg.evaluate(initializer=params_dict)
    output_mdf = eg.output_enodes[0].get_output()
    assert np.allclose(
        output,
        output_mdf,
    )
    mdf_model2 = Model.from_json(mdf_model.to_json())