def test_core_class():
input_shape = [1, 3, 4, 4]
param = ov.parameter(input_shape, np.float32, name="parameter")
relu = ov.relu(param, name="relu")
func = Function([relu], [param], "test")
func.get_ordered_ops()[2].friendly_name = "friendly"
cnn_network = IENetwork(func)
core = Core()
core.set_config({}, device_name="CPU")
executable_network = core.compile_model(cnn_network, "CPU", {})
td = TensorDesc("FP32", input_shape, "NCHW")
# from IPython import embed; embed()
request = executable_network.create_infer_request()
input_data = np.random.rand(*input_shape) - 0.5
expected_output = np.maximum(0.0, input_data)
input_blob = Blob(td, input_data)
request.set_input({"parameter": input_blob})
request.infer()
result = request.get_blob("relu").buffer
assert np.allclose(result, expected_output)
def test_ngraph_function_api():
shape = [2, 2]
parameter_a = ops.parameter(shape, dtype=np.float32, name="A")
parameter_b = ops.parameter(shape, dtype=np.float32, name="B")
parameter_c = ops.parameter(shape, dtype=np.float32, name="C")
model = (parameter_a + parameter_b) * parameter_c
function = Function(model, [parameter_a, parameter_b, parameter_c],
"TestFunction")
function.get_parameters()[1].set_partial_shape(PartialShape([3, 4, 5]))
ordered_ops = function.get_ordered_ops()
op_types = [op.get_type_name() for op in ordered_ops]
assert op_types == [
"Parameter", "Parameter", "Parameter", "Add", "Multiply", "Result"
]
assert len(function.get_ops()) == 6
assert function.get_output_size() == 1
assert function.get_output_op(0).get_type_name() == "Result"
assert function.get_output_element_type(
0) == parameter_a.get_element_type()
assert list(function.get_output_shape(0)) == [2, 2]
assert (function.get_parameters()[1].get_partial_shape()) == PartialShape(
[3, 4, 5])
assert len(function.get_parameters()) == 3
assert len(function.get_results()) == 1
assert function.get_friendly_name() == "TestFunction"
def test_repr_dynamic_shape():
shape = PartialShape([-1, 2])
parameter_a = ov.parameter(shape, dtype=np.float32, name="A")
parameter_b = ov.parameter(shape, dtype=np.float32, name="B")
model = parameter_a + parameter_b
function = Function(model, [parameter_a, parameter_b],
"simple_dyn_shapes_graph")
assert repr(function) == "<Function: 'simple_dyn_shapes_graph' ({?,2})>"
ops = function.get_ordered_ops()
for op in ops:
assert "{?,2}" in repr(op)
def test_sink_function_ctor():
input_data = ops.parameter([2, 2], name="input_data", dtype=np.float32)
rv = ops.read_value(input_data, "var_id_667")
add = ops.add(rv, input_data, name="MemoryAdd")
node = ops.assign(add, "var_id_667")
res = ops.result(add, "res")
function = Function(results=[res], sinks=[node], parameters=[input_data], name="TestFunction")
ordered_ops = function.get_ordered_ops()
op_types = [op.get_type_name() for op in ordered_ops]
assert op_types == ["Parameter", "ReadValue", "Add", "Assign", "Result"]
assert len(function.get_ops()) == 5
assert function.get_output_size() == 1
assert function.get_output_op(0).get_type_name() == "Result"
assert function.get_output_element_type(0) == input_data.get_element_type()
assert list(function.get_output_shape(0)) == [2, 2]
assert (function.get_parameters()[0].get_partial_shape()) == PartialShape([2, 2])
assert len(function.get_parameters()) == 1
assert len(function.get_results()) == 1
assert function.get_friendly_name() == "TestFunction"
def test_ngraph_function_api():
shape = [2, 2]
parameter_a = ops.parameter(shape, dtype=np.float32, name="A")
parameter_b = ops.parameter(shape, dtype=np.float32, name="B")
parameter_c = ops.parameter(shape, dtype=np.float32, name="C")
model = (parameter_a + parameter_b) * parameter_c
assert parameter_a.element_type == Type.f32
assert parameter_a.partial_shape == PartialShape([2, 2])
parameter_a.layout = ov.Layout("NCWH")
assert parameter_a.layout == ov.Layout("NCWH")
function = Function(model, [parameter_a, parameter_b, parameter_c], "TestFunction")
function.get_parameters()[1].set_partial_shape(PartialShape([3, 4, 5]))
ordered_ops = function.get_ordered_ops()
op_types = [op.get_type_name() for op in ordered_ops]
assert op_types == ["Parameter", "Parameter", "Parameter", "Add", "Multiply", "Result"]
assert len(function.get_ops()) == 6
assert function.get_output_size() == 1
assert ["A", "B", "C"] == [input.get_node().friendly_name for input in function.inputs]
assert ["Result"] == [output.get_node().get_type_name() for output in function.outputs]
assert function.input(0).get_node().friendly_name == "A"
assert function.output(0).get_node().get_type_name() == "Result"
assert function.input(tensor_name="A").get_node().friendly_name == "A"
assert function.output().get_node().get_type_name() == "Result"
assert function.get_output_op(0).get_type_name() == "Result"
assert function.get_output_element_type(0) == parameter_a.get_element_type()
assert list(function.get_output_shape(0)) == [2, 2]
assert (function.get_parameters()[1].get_partial_shape()) == PartialShape([3, 4, 5])
assert len(function.get_parameters()) == 3
results = function.get_results()
assert len(results) == 1
assert results[0].get_output_element_type(0) == Type.f32
assert results[0].get_output_partial_shape(0) == PartialShape([2, 2])
results[0].layout = ov.Layout("NC")
assert results[0].layout.to_string() == ov.Layout("NC")
assert function.get_friendly_name() == "TestFunction"
