def test_get_result_index():
input_shape = PartialShape([1])
param = ops.parameter(input_shape, dtype=np.float32, name="data")
relu = ops.relu(param, name="relu")
function = Function(relu, [param], "TestFunction")
assert len(function.outputs) == 1
assert function.get_result_index(function.outputs[0]) == 0
def test_parameter_index_invalid():
shape1 = PartialShape([1])
param1 = ops.parameter(shape1, dtype=np.float32, name="data1")
relu = ops.relu(param1, name="relu")
function = Function(relu, [param1], "TestFunction")
shape2 = PartialShape([2])
param2 = ops.parameter(shape2, dtype=np.float32, name="data2")
assert function.get_parameter_index(param2) == -1
def test_compress_model_transformation():
node_constant = ov.opset8.constant(np.array([[0.0, 0.1, -0.1], [-2.5, 2.5, 3.0]], dtype=np.float32))
node_ceil = ov.opset8.ceiling(node_constant)
func = Function(node_ceil, [], "TestFunction")
assert func.get_ordered_ops()[0].get_element_type().get_type_name() == "f32"
compress_model_transformation(func)
assert func is not None
assert func.get_ordered_ops()[0].get_element_type().get_type_name() == "f16"
def test_function_add_output_incorrect_tensor_name():
input_shape = PartialShape([1])
param = ops.parameter(input_shape, dtype=np.float32, name="data")
relu1 = ops.relu(param, name="relu1")
relu1.get_output_tensor(0).set_names({"relu_t1"})
relu2 = ops.relu(relu1, name="relu2")
function = Function(relu2, [param], "TestFunction")
assert len(function.get_results()) == 1
with pytest.raises(RuntimeError) as e:
function.add_outputs("relu_t")
assert "Tensor name relu_t was not found." in str(e.value)
def test_add_outputs_incorrect_outputs_list():
input_shape = PartialShape([1])
param = ops.parameter(input_shape, dtype=np.float32, name="data")
relu1 = ops.relu(param, name="relu1")
relu1.get_output_tensor(0).set_names({"relu_t1"})
function = Function(relu1, [param], "TestFunction")
assert len(function.get_results()) == 1
with pytest.raises(TypeError) as e:
function.add_outputs([0, 0])
assert "Incorrect type of a value to add as output at index 0" in str(
e.value)
def test_function_add_output_incorrect_idx():
input_shape = PartialShape([1])
param = ops.parameter(input_shape, dtype=np.float32, name="data")
relu1 = ops.relu(param, name="relu1")
relu1.get_output_tensor(0).set_names({"relu_t1"})
relu2 = ops.relu(relu1, name="relu2")
function = Function(relu2, [param], "TestFunction")
assert len(function.get_results()) == 1
with pytest.raises(RuntimeError) as e:
function.add_outputs(("relu1", 10))
assert "Cannot add output to port 10 operation relu1 has only 1 outputs." in str(
e.value)
def test_get_result_index_invalid():
shape1 = PartialShape([1])
param1 = ops.parameter(shape1, dtype=np.float32, name="data1")
relu1 = ops.relu(param1, name="relu1")
function = Function(relu1, [param1], "TestFunction")
shape2 = PartialShape([2])
param2 = ops.parameter(shape2, dtype=np.float32, name="data2")
relu2 = ops.relu(param2, name="relu2")
invalid_output = relu2.outputs()[0]
assert len(function.outputs) == 1
assert function.get_result_index(invalid_output) == -1
def test_evaluate():
param1 = ops.parameter(Shape([2, 1]), dtype=np.float32, name="data1")
param2 = ops.parameter(Shape([2, 1]), dtype=np.float32, name="data2")
add = ops.add(param1, param2)
func = Function(add, [param1, param2], "TestFunction")
input1 = np.array([2, 1], dtype=np.float32).reshape(2, 1)
input2 = np.array([3, 7], dtype=np.float32).reshape(2, 1)
out_tensor = Tensor("float32", Shape([2, 1]))
assert func.evaluate([out_tensor], [Tensor(input1), Tensor(input2)])
assert np.allclose(out_tensor.data, np.array([5, 8]).reshape(2, 1))
def test_function_add_output_port():
input_shape = PartialShape([1])
param = ops.parameter(input_shape, dtype=np.float32, name="data")
relu1 = ops.relu(param, name="relu1")
relu1.get_output_tensor(0).set_names({"relu_t1"})
relu2 = ops.relu(relu1, name="relu2")
function = Function(relu2, [param], "TestFunction")
assert len(function.get_results()) == 1
new_outs = function.add_outputs(relu1.output(0))
assert len(function.get_results()) == 2
assert len(new_outs) == 1
assert new_outs[0].get_node() == function.outputs[1].get_node()
assert new_outs[0].get_index() == function.outputs[1].get_index()
def test_evaluate_invalid_input_shape():
param1 = ops.parameter(Shape([2, 1]), dtype=np.float32, name="data1")
param2 = ops.parameter(Shape([2, 1]), dtype=np.float32, name="data2")
add = ops.add(param1, param2)
func = Function(add, [param1, param2], "TestFunction")
with pytest.raises(RuntimeError) as e:
assert func.evaluate(
[Tensor("float32", Shape([2, 1]))],
[
Tensor("float32", Shape([3, 1])),
Tensor("float32", Shape([3, 1]))
],
)
assert "must be compatible with the partial shape: {2,1}" in str(e.value)
def test_function_add_outputs_tensor_name():
input_shape = PartialShape([1])
param = ops.parameter(input_shape, dtype=np.float32, name="data")
relu1 = ops.relu(param, name="relu1")
relu1.get_output_tensor(0).set_names({"relu_t1"})
assert "relu_t1" in relu1.get_output_tensor(0).names
relu2 = ops.relu(relu1, name="relu2")
function = Function(relu2, [param], "TestFunction")
assert len(function.get_results()) == 1
new_outs = function.add_outputs("relu_t1")
assert len(function.get_results()) == 2
assert isinstance(function.outputs[1].get_tensor(), DescriptorTensor)
assert "relu_t1" in function.outputs[1].get_tensor().names
assert len(new_outs) == 1
assert new_outs[0].get_node() == function.outputs[1].get_node()
assert new_outs[0].get_index() == function.outputs[1].get_index()
def create_function_with_memory(input_shape, data_type):
input_data = ops.parameter(input_shape, name="input_data", dtype=data_type)
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")
func = Function(results=[res], sinks=[node], parameters=[input_data], name="name")
return func
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"
core = Core()
model = core.compile_model(func, "CPU", {})
request = model.create_infer_request()
input_data = np.random.rand(*input_shape).astype(np.float32) - 0.5
expected_output = np.maximum(0.0, input_data)
input_tensor = Tensor(input_data)
results = request.infer({"parameter": input_tensor})
assert np.allclose(results, expected_output)
def test_serialize_pass_v2():
core = Core()
xml_path = "./serialized_function.xml"
bin_path = "./serialized_function.bin"
shape = [100, 100, 2]
parameter_a = ov.opset8.parameter(shape, dtype=np.float32, name="A")
parameter_b = ov.opset8.parameter(shape, dtype=np.float32, name="B")
model = ov.opset8.floor(ov.opset8.minimum(ov.opset8.abs(parameter_a), parameter_b))
func = Function(model, [parameter_a, parameter_b], "Function")
serialize(func, xml_path, bin_path)
assert func is not None
res_func = core.read_model(model=xml_path, weights=bin_path)
assert func.get_parameters() == res_func.get_parameters()
assert func.get_ordered_ops() == res_func.get_ordered_ops()
os.remove(xml_path)
os.remove(bin_path)
def test_function_add_outputs_op_name():
input_shape = PartialShape([1])
param = ops.parameter(input_shape, dtype=np.float32, name="data")
relu1 = ops.relu(param, name="relu1")
relu1.get_output_tensor(0).set_names({"relu_t1"})
relu2 = ops.relu(relu1, name="relu2")
function = Function(relu2, [param], "TestFunction")
assert len(function.get_results()) == 1
function.add_outputs(("relu1", 0))
assert len(function.get_results()) == 2
def test_replace_parameter():
shape1 = PartialShape([1])
param1 = ops.parameter(shape1, dtype=np.float32, name="data")
shape2 = PartialShape([2])
param2 = ops.parameter(shape2, dtype=np.float32, name="data")
relu = ops.relu(param1, name="relu")
function = Function(relu, [param1], "TestFunction")
param_index = function.get_parameter_index(param1)
function.replace_parameter(param_index, param2)
assert function.get_parameter_index(param2) == param_index
assert function.get_parameter_index(param1) == -1
def test_validate_nodes_and_infer_types():
param1 = ops.parameter(Shape([2, 1]), dtype=np.float32, name="data1")
param2 = ops.parameter(Shape([2, 1]), dtype=np.float32, name="data2")
add = ops.add(param1, param2)
func = Function(add, [param1, param2], "TestFunction")
invalid_shape = Shape([3, 7])
param3 = ops.parameter(invalid_shape, dtype=np.float32, name="data3")
func.replace_parameter(0, param3)
with pytest.raises(RuntimeError) as e:
func.validate_nodes_and_infer_types()
assert "Argument shapes are inconsistent" in str(e.value)
def get_test_function():
param = ov.opset8.parameter(PartialShape([1, 3, 22, 22]), name="parameter")
relu = ov.opset8.relu(param)
res = ov.opset8.result(relu, name="result")
return Function([res], [param], "test")
def test_parameter_index():
input_shape = PartialShape([1])
param = ops.parameter(input_shape, dtype=np.float32, name="data")
relu = ops.relu(param, name="relu")
function = Function(relu, [param], "TestFunction")
assert function.get_parameter_index(param) == 0