def test_iO17_default_fp32_io(
        self,
        int32_float32_two_input_model,
        int32_float32_two_output_model,
    ):
        """
        With minimum_deployment_target set >= iOS16, and if the compute precision is
        set to fp32. By default, a fp32 i/o model is produced.
        """
        # Example 1
        mlmodel = ct.convert(
            int32_float32_two_input_model,
            compute_precision=ct.precision.FLOAT32,
            minimum_deployment_target=ct.target.iOS16,
        )
        assert_input_dtype(mlmodel, expected_type_str="int32", index=0)
        assert_input_dtype(mlmodel, expected_type_str="fp32", index=1)
        assert_output_dtype(mlmodel, expected_type_str="fp32", index=0)

        # Example 2
        mlmodel = ct.convert(
            int32_float32_two_output_model,
            compute_precision=ct.precision.FLOAT32,
            minimum_deployment_target=ct.target.iOS16,
        )
        assert_input_dtype(mlmodel, expected_type_str="fp32", index=0)
        assert_input_dtype(mlmodel, expected_type_str="fp32", index=1)
        assert_output_dtype(mlmodel, expected_type_str="fp32", index=0)
        assert_output_dtype(mlmodel, expected_type_str="int32", index=1)

        With minimum_deployment_target set >= iOS16, and if the compute precision is
        set to fp32. By default, a fp32 i/o model is produced.
        
coremltools/converters/mil/frontend/tensorflow/test/test_tf_conversion_api.py