export MXNET_LIBRARY_PATH=//anaconda3/lib/python3.8/site-packages/mxnet/
Test case for a rough inference run with MXNet model
./gradlew :integration:run
try (MxResource base = BaseMxResource.getSystemMxResource()) { Model model = Model.loadModel(Item.MLP); // Model model = Model.loadModel("test", Paths.get("/Users/cspchen/mxnet.java_package/cache/repo/test-models/mlp.tar.gz/mlp/")); Predictor<NDList, NDList> predictor = model.newPredictor(); NDArray input = NDArray.create(base, new Shape(1, 28, 28)).ones(); NDList inputs = new NDList(); inputs.add(input); NDList result = predictor.predict(inputs); NDArray expected = NDArray.create( base, new float[]{4.93476f, -0.76084447f, 0.37713608f, 0.6605506f, -1.3485785f, -0.8736369f , 0.018061712f, -1.3274033f, 1.0609543f, 0.24042489f}, new Shape(1, 10)); Assertions.assertAlmostEquals(result.get(0), expected); } catch (IOException e) { logger.error(e.getMessage(), e); }