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pre_processing_deserialization.cpp
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// Copyright (C) 2018-2025 Intel Corporation
// SPDX-License-Identifier: Apache-2.0
//
#include <gmock/gmock.h>
#include "frontend_test.hpp"
#include "openvino/core/preprocess/pre_post_process.hpp"
class IRFrontendTestsPreProcessing : public ::testing::Test, public IRFrontendTestsImpl {
protected:
void SetUp() override {}
void TearDown() override {
RemoveTemporalFiles();
}
};
TEST_F(IRFrontendTestsPreProcessing, pre_processing) {
std::string xmlModel = R"V0G0N(
<?xml version="1.0" ?>
<net name="Network" version="10">
<pre-process mean-precision="FP32" reference-layer-name="input">
<channel id="0">
<mean offset="0" size="1936"/>
</channel>
<channel id="1">
<mean offset="1936" size="1936"/>
</channel>
<channel id="2">
<mean offset="3872" size="1936"/>
</channel>
</pre-process>
<layers>
<layer name="input" type="Parameter" id="0" version="opset1">
<data shape="1,3,22,22" element_type="f32"/>
<output>
<port id="0" precision="FP32">
<dim>1</dim>
<dim>3</dim>
<dim>22</dim>
<dim>22</dim>
</port>
</output>
</layer>
<layer name="output" type="Result" id="1" version="opset1">
<input>
<port id="0" precision="FP32">
<dim>1</dim>
<dim>3</dim>
<dim>22</dim>
<dim>22</dim>
</port>
</input>
</layer>
</layers>
<edges>
<edge from-layer="0" from-port="0" to-layer="1" to-port="0"/>
</edges>
</net>
)V0G0N";
int dataSizeinFloat = 22 * 22 * 3;
std::vector<unsigned char> buffer(dataSizeinFloat * sizeof(float), 0);
float* floatBuffer = reinterpret_cast<float*>(buffer.data());
for (int i = 0; i < dataSizeinFloat; i++) {
floatBuffer[i] = 1;
}
createTemporalModelFile(xmlModel, buffer);
std::shared_ptr<ov::Model> model;
OV_ASSERT_NO_THROW(model = core.read_model(xmlFileName, binFileName));
ASSERT_TRUE(!!model);
}
namespace ov {
namespace test {
using testing::ElementsAre;
using testing::Property;
using testing::UnorderedElementsAre;
TEST_F(IRFrontendTestsPreProcessing, check_tensor_names_after_read_and_pre_post_processing) {
std::string xml_model = R"V0G0N(
<?xml version="1.0" ?>
<net name="Model" version="11">
<layers>
<layer id="0" name="A" type="Parameter" version="opset1">
<data shape="" element_type="f32" />
<output>
<port id="0" precision="f32" names="input_a" />
</output>
</layer>
<layer id="1" name="B" type="Parameter" version="opset1">
<data shape="" element_type="f32" />
<output>
<port id="0" precision="f32" names="input_b" />
</output>
</layer>
<layer id="2" name="my_const" type="Const" version="opset1">
<data element_type="f32" shape="" offset="0" size="4" />
<output>
<port id="0" precision="f32" />
</output>
</layer>
<layer id="3" name="Add" type="Add" version="opset1">
<data auto_broadcast="numpy" />
<input>
<port id="0" precision="f32" />
<port id="1" precision="f32" />
</input>
<output>
<port id="0" precision="f32" names="add_result" />
</output>
</layer>
<layer id="4" name="output_a" type="Result" version="opset1">
<input>
<port id="0" precision="f32" />
</input>
</layer>
<layer id="5" name="output_b" type="Result" version="opset1">
<input>
<port id="0" precision="f32" />
</input>
</layer>
</layers>
<edges>
<edge from-layer="0" from-port="0" to-layer="3" to-port="0" />
<edge from-layer="1" from-port="0" to-layer="5" to-port="0" />
<edge from-layer="2" from-port="0" to-layer="3" to-port="1" />
<edge from-layer="3" from-port="0" to-layer="4" to-port="0" />
</edges>
<rt_info />
</net>
// )V0G0N";
constexpr auto DATA_COUNT = 1;
std::vector<unsigned char> buffer(DATA_COUNT * sizeof(float), 0);
std::fill_n(reinterpret_cast<float*>(buffer.data()), DATA_COUNT, 1.f);
createTemporalModelFile(xml_model, buffer);
std::shared_ptr<Model> model;
OV_ASSERT_NO_THROW(model = core.read_model(xmlFileName, binFileName));
ASSERT_NE(model, nullptr);
EXPECT_THAT(model->inputs(),
ElementsAre(Property("Input 0", &Output<Node>::get_names, UnorderedElementsAre("input_a")),
Property("Input 1", &Output<Node>::get_names, UnorderedElementsAre("input_b"))));
EXPECT_THAT(model->outputs(),
ElementsAre(Property("Output 0", &Output<Node>::get_names, UnorderedElementsAre("add_result")),
// Directly connected to model input shows input's names.
Property("Output 1", &Output<Node>::get_names, UnorderedElementsAre("input_b"))));
auto p = preprocess::PrePostProcessor(model);
p.output(0).tensor().set_element_type(element::f16);
p.output(1).tensor().set_element_type(element::i32);
model = p.build();
EXPECT_THAT(model->inputs(),
ElementsAre(Property("Input 0", &Output<Node>::get_names, UnorderedElementsAre("input_a")),
Property("Input 1", &Output<Node>::get_names, UnorderedElementsAre("input_b"))));
EXPECT_THAT(model->outputs(),
ElementsAre(Property("Output 0", &Output<Node>::get_names, UnorderedElementsAre("add_result")),
// After PPP (inserts convert node) the tensor names stay on model's input.
Property("Output 1", &Output<Node>::get_names, testing::IsEmpty())));
}
} // namespace test
} // namespace ov