def test_real_div_int_builder_to_backend(self, compute_unit, backend):
        """
        For the neuralnetwork backend, the real_div is producing float output even for int inputs,
        while the mlprogram backend produces int type output.
        """
        x = np.array([[10, 20, 30], [40, 50, 60]], dtype=np.float32)
        y = np.array([[11, 12, 13], [14, 15, 16]], dtype=np.float32)

        if backend.backend == "neuralnetwork":
            dtype = np.float32
        else:
            dtype = np.int32
        expected_outputs = np.array(x / y, dtype=dtype)

        build = lambda x, y: mb.real_div(x=x, y=y)

        expected_output_types = (2, 3, types.int32)
        input_placeholders = {
            "x": mb.placeholder(shape=x.shape, dtype=types.int32),
            "y": mb.placeholder(shape=y.shape, dtype=types.int32),
        }
        input_values = {"x": x, "y": y}
        run_compare_builder(
            build,
            input_placeholders,
            input_values,
            expected_output_types,
            expected_outputs,
            compute_unit=compute_unit,
            backend=backend,
        )

        For the neuralnetwork backend, the real_div is producing float output even for int inputs,
        while the mlprogram backend produces int type output.
        
coremltools/converters/mil/mil/ops/tests/iOS14/test_elementwise_binary.py