Anastasiia Pnevskaia
59872ee072
* Fixed output_model logic. * Removed InputCutInfo, disabled input cut in ovc. * Disabled output cut, added tests for setting shapes or types for not all inputs. * Returned support of numpy type. * Separated MO and OVC python API tests. * Small corrections. * Added output dir test, exceptions test. * Tests fixed. * Corrected extension param description. * Corrected input description, minor code corrections.
122 lines
4.1 KiB
Python
122 lines
4.1 KiB
Python
# Copyright (C) 2018-2023 Intel Corporation
|
|
# SPDX-License-Identifier: Apache-2.0
|
|
|
|
import pytest
|
|
import numpy as np
|
|
|
|
from common.mo_convert_test_class import CommonMOConvertTest
|
|
from common.onnx_layer_test_class import save_to_onnx
|
|
|
|
import openvino.runtime as ov
|
|
from openvino.runtime import PartialShape, Model
|
|
|
|
|
|
class TestExtensions(CommonMOConvertTest):
|
|
def create_onnx_model(self, tmp_dir):
|
|
#
|
|
# Create ONNX model
|
|
#
|
|
|
|
import onnx
|
|
from onnx import helper
|
|
from onnx import TensorProto
|
|
|
|
shape = [2, 3, 4]
|
|
|
|
input = helper.make_tensor_value_info('input', TensorProto.FLOAT, shape)
|
|
output = helper.make_tensor_value_info('output', TensorProto.FLOAT, shape)
|
|
|
|
node_def = onnx.helper.make_node(
|
|
'LeakyRelu',
|
|
inputs=['input'],
|
|
outputs=['LeakyRelu_data'],
|
|
alpha=0.1
|
|
)
|
|
node_def2 = onnx.helper.make_node(
|
|
'Elu',
|
|
inputs=['LeakyRelu_data'],
|
|
outputs=['output'],
|
|
alpha=0.1
|
|
)
|
|
|
|
# Create the graph (GraphProto)
|
|
graph_def = helper.make_graph(
|
|
[node_def, node_def2],
|
|
'test_model',
|
|
[input],
|
|
[output],
|
|
)
|
|
|
|
# Create the model (ModelProto)
|
|
onnx_net = helper.make_model(graph_def, producer_name='test_model')
|
|
|
|
# save model to .onnx and return path to the model
|
|
return save_to_onnx(onnx_net, tmp_dir)
|
|
|
|
def create_custom_extension_leaky_relu_to_relu():
|
|
# replaces LeakyRelu with Relu
|
|
from openvino.frontend import ConversionExtension
|
|
from openvino.frontend import NodeContext
|
|
import openvino.runtime.opset8 as ops
|
|
|
|
def custom_converter(node: NodeContext):
|
|
input = node.get_input(0)
|
|
relu = ops.relu(input)
|
|
return [relu.output(0)]
|
|
|
|
return ConversionExtension("LeakyRelu", custom_converter)
|
|
|
|
def create_custom_extension_elu_to_sigmoid():
|
|
# replaces Elu with Sigmoid
|
|
from openvino.frontend import ConversionExtension
|
|
from openvino.frontend import NodeContext
|
|
import openvino.runtime.opset8 as ops
|
|
|
|
def custom_converter(node: NodeContext):
|
|
input = node.get_input(0)
|
|
sigm = ops.sigmoid(input)
|
|
return [sigm.output(0)]
|
|
|
|
return ConversionExtension("Elu", custom_converter)
|
|
|
|
def create_ref_graph1():
|
|
shape = PartialShape([2, 3, 4])
|
|
param = ov.opset8.parameter(shape, dtype=np.float32)
|
|
param.get_output_tensor(0).set_names({"input"})
|
|
relu = ov.opset8.relu(param)
|
|
relu.get_output_tensor(0).set_names({"LeakyRelu_data"})
|
|
elu = ov.opset8.elu(relu, alpha=0.1)
|
|
elu.get_output_tensor(0).set_names({"output"})
|
|
|
|
return Model([elu], [param], "test")
|
|
|
|
def create_ref_graph2():
|
|
shape = PartialShape([2, 3, 4])
|
|
param = ov.opset8.parameter(shape, dtype=np.float32)
|
|
param.get_output_tensor(0).set_names({"input"})
|
|
relu = ov.opset8.relu(param)
|
|
relu.get_output_tensor(0).set_names({"LeakyRelu_data"})
|
|
sigmoid = ov.opset8.sigmoid(relu)
|
|
sigmoid.get_output_tensor(0).set_names({"output"})
|
|
|
|
return Model([sigmoid], [param], "test")
|
|
|
|
test_data = [
|
|
{'params_test': {'extension': create_custom_extension_leaky_relu_to_relu()},
|
|
'ref_graph': create_ref_graph1()},
|
|
{'params_test': {'extension': [create_custom_extension_leaky_relu_to_relu(),
|
|
create_custom_extension_elu_to_sigmoid()]},
|
|
'ref_graph': create_ref_graph2()}
|
|
]
|
|
|
|
@pytest.mark.parametrize("params", test_data)
|
|
@pytest.mark.nightly
|
|
@pytest.mark.precommit
|
|
def test_mo_convert_extensions(self, params, ie_device, precision, ir_version,
|
|
temp_dir, use_new_frontend, use_old_api):
|
|
onnx_net_path = self.create_onnx_model(temp_dir)
|
|
|
|
test_params = params['params_test']
|
|
test_params.update({'input_model': onnx_net_path})
|
|
self._test_by_ref_graph(temp_dir, test_params, params['ref_graph'])
|