// Copyright (C) 2018-2022 Intel Corporation
// SPDX-License-Identifier: Apache-2.0
//

#include <string>
#include <ngraph/function.hpp>

#include "ngraph_reader_tests.hpp"

TEST_F(NGraphReaderTests, ReadNetworkWithTensorNames) {
    std::string model = R"V0G0N(
<net name="Network" version="10">
    <layers>
        <layer name="in1" type="Parameter" id="0" version="opset1">
            <data element_type="f32" shape="1,3,22,22"/>
            <output>
                <port id="0" precision="FP32" names="input">
                    <dim>1</dim>
                    <dim>3</dim>
                    <dim>22</dim>
                    <dim>22</dim>
                </port>
            </output>
        </layer>
        <layer name="activation" id="1" type="ReLU" version="opset1">
            <input>
                <port id="1" precision="FP32">
                    <dim>1</dim>
                    <dim>3</dim>
                    <dim>22</dim>
                    <dim>22</dim>
                </port>
            </input>
            <output>
                <port id="2" precision="FP32" names="relu\,t, identity_t">
                    <dim>1</dim>
                    <dim>3</dim>
                    <dim>22</dim>
                    <dim>22</dim>
                </port>
            </output>
        </layer>
        <layer name="output" type="Result" id="2" 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="1"/>
        <edge from-layer="1" from-port="2" to-layer="2" to-port="0"/>
    </edges>
</net>
)V0G0N";
    Core ie;
    Blob::Ptr weights;

    auto network = ie.ReadNetwork(model, weights);
    auto function = network.getFunction();
    auto inputs = network.getInputsInfo();
    auto outputs = network.getOutputsInfo();
    std::unordered_set<std::string> inNames;
    for (const auto& in : inputs)
        inNames.emplace(in.first);
    std::unordered_set<std::string> outNames;
    for (const auto& out : outputs)
        outNames.emplace(out.first);

    ASSERT_EQ(1, inputs.size());
    ASSERT_EQ(1, outputs.size());
    ASSERT_EQ(1, function->get_results().size());

    for (const auto& param : function->get_parameters()) {
        ASSERT_TRUE(!param->get_output_tensor(0).get_names().empty());
        for (const auto& name : param->get_output_tensor(0).get_names())
            ASSERT_TRUE(inNames.count(network.getOVNameForTensor(name)));
    }

    for (const auto& result : function->get_results()) {
        ASSERT_TRUE(!result->get_input_tensor(0).get_names().empty());
        for (const auto& name : result->get_input_tensor(0).get_names())
            ASSERT_TRUE(outNames.count(network.getOVNameForTensor(name)));
    }
    ASSERT_NO_THROW(network.getOVNameForTensor("relu,t"));
}
