def import_onnx_model(model: onnx.ModelProto) -> Function:
onnx.checker.check_model(model)
model_byte_string = model.SerializeToString()
ie = IECore()
ie_network = ie.read_network(model=model_byte_string,
weights=b"",
init_from_buffer=True)
capsule = ie_network._get_function_capsule()
ng_function = Function.from_capsule(capsule)
return ng_function
def test_GetIENetworkFromNGraph():
element_type = Type.f32
param = Parameter(element_type, Shape([1, 3, 22, 22]))
relu = Relu(param)
func = Function([relu], [param], 'test')
caps = Function.to_capsule(func)
cnnNetwork = IENetwork(caps)
assert cnnNetwork != None
assert cnnNetwork.get_function() != None
caps2 = cnnNetwork.get_function()
func2 = Function.from_capsule(caps2)
assert func2 != None
def test_import_onnx_function():
model_path = os.path.join(os.path.dirname(__file__), "models/add_abc.onnx")
ie = IECore()
ie_network = ie.read_network(model=model_path)
capsule = ie_network._get_function_capsule()
ng_function = Function.from_capsule(capsule)
dtype = np.float32
value_a = np.array([1.0], dtype=dtype)
value_b = np.array([2.0], dtype=dtype)
value_c = np.array([3.0], dtype=dtype)
runtime = get_runtime()
computation = runtime.computation(ng_function)
result = computation(value_a, value_b, value_c)
assert np.allclose(result, np.array([6], dtype=dtype))
def function_from_cnn(cnn_network: IENetwork) -> Function:
"""Get nGraph function from Inference Engine CNN network."""
capsule = cnn_network._get_function_capsule()
ng_function = Function.from_capsule(capsule)
return ng_function
