def METHOD_NAME():
    return inference_pb2.ModelSession(
        inputAxes=["xyc"],
        outputAxes=["xyc"],
        hasTraining=False,
        inputShapes=[
            inference_pb2.InputShape(
                shapeType=0,
                shape=inference_pb2.NamedInts(
                    namedInts=[
                        inference_pb2.NamedInt(name="x", size=1024),
                        inference_pb2.NamedInt(name="y", size=512),
                        inference_pb2.NamedInt(name="c", size=1),
                    ]
                ),
            ),
        ],
        outputShapes=[
            inference_pb2.OutputShape(
                shapeType=1,
                referenceTensor="input",
                offset=inference_pb2.NamedFloats(
                    namedFloats=[
                        inference_pb2.NamedFloat(name="x", size=16),
                        inference_pb2.NamedFloat(name="y", size=32),
                        inference_pb2.NamedFloat(name="c", size=3),
                    ]
                ),
                scale=inference_pb2.NamedFloats(
                    namedFloats=[
                        inference_pb2.NamedFloat(name="x", size=1),
                        inference_pb2.NamedFloat(name="y", size=0.5),
                        inference_pb2.NamedFloat(name="c", size=2),
                    ]
                ),
                halo=inference_pb2.NamedInts(
                    namedInts=[
                        inference_pb2.NamedInt(name="x", size=256),
                        inference_pb2.NamedInt(name="y", size=128),
                        inference_pb2.NamedInt(name="c", size=1),
                    ]
                ),
            )
        ],
        inputNames=["input"],
        outputNames=["output"],
    )