From 7bba2a95428b7dfd7eb619520d87c7d134360958 Mon Sep 17 00:00:00 2001
From: Ilya Churaev <ilya.churaev@intel.com>
Date: Tue, 15 Sep 2020 14:00:27 +0300
Subject: [PATCH] Fixed output names for case with redundant ops before result
 (#2209)

---
 .../cnn_network/cnn_ngraph_impl_tests.cpp     | 126 ++++++++++++++++++
 ngraph/core/src/graph_util.cpp                |   2 +
 2 files changed, 128 insertions(+)

diff --git a/inference-engine/tests/functional/inference_engine/cnn_network/cnn_ngraph_impl_tests.cpp b/inference-engine/tests/functional/inference_engine/cnn_network/cnn_ngraph_impl_tests.cpp
index 370c6a10c26..a1d2f6c440e 100644
--- a/inference-engine/tests/functional/inference_engine/cnn_network/cnn_ngraph_impl_tests.cpp
+++ b/inference-engine/tests/functional/inference_engine/cnn_network/cnn_ngraph_impl_tests.cpp
@@ -17,6 +17,10 @@
 #include <ie_parameter.hpp>
 #include <ie_core.hpp>
 #include <legacy/net_pass.h>
+#include <generic_ie.hpp>
+#include <legacy/convert_function_to_cnn_network.hpp>
+#include <transformations/convert_opset1_to_legacy/convert_opset1_to_legacy.hpp>
+#include <ngraph/pass/manager.hpp>
 
 #include <ngraph/opsets/opset3.hpp>
 #include <ngraph/function.hpp>
@@ -955,4 +959,126 @@ TEST(CNNNGraphImplTests, AddOutputToExperimentalOp) {
     auto outputs = network.getOutputsInfo();
     ASSERT_NE(outputs.find("exp.0"), outputs.end());
 }
+
+TEST(CNNNGraphImplTests, SaveOriginalResultNameForMultiOutputOp) {
+    std::string model = R"V0G0N(
+<net name="Activation" version="10">
+    <layers>
+        <layer name="in1" 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="exp" id="1" type="ExperimentalDetectronROIFeatureExtractor" version="experimental">
+            <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">
+                    <dim>1</dim>
+                    <dim>3</dim>
+                    <dim>22</dim>
+                    <dim>22</dim>
+                </port>
+            </output>
+        </layer>
+        <layer id="2" name="fake_const" type="Const" version="opset1">
+            <data offset="0" size="4" shape="1,1,1,1" element_type="f32"/>
+            <output>
+                <port id="1" precision="FP32">
+                    <dim>1</dim>
+                    <dim>1</dim>
+                    <dim>1</dim>
+                    <dim>1</dim>
+                </port>
+            </output>
+        </layer>
+        <layer id="3" name="text_features" type="Add" version="opset1">
+            <input>
+                <port id="0">
+                    <dim>1</dim>
+                    <dim>3</dim>
+                    <dim>22</dim>
+                    <dim>22</dim>
+                </port>
+                <port id="1">
+                    <dim>1</dim>
+                    <dim>1</dim>
+                    <dim>1</dim>
+                    <dim>1</dim>
+                </port>
+            </input>
+            <output>
+                <port id="2" precision="FP32">
+                    <dim>1</dim>
+                    <dim>3</dim>
+                    <dim>22</dim>
+                    <dim>22</dim>
+                </port>
+            </output>
+        </layer>
+        <layer name="output" type="Result" id="4" 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="3" to-port="0"/>
+        <edge from-layer="2" from-port="1" to-layer="3" to-port="1"/>
+        <edge from-layer="3" from-port="2" to-layer="4" to-port="0"/>
+    </edges>
+</net>
+)V0G0N";
+    InferenceEngine::Core core;
+    Blob::Ptr data = make_shared_blob<float>(TensorDesc(Precision::FP32, {4}, Layout::C));
+    data->allocate();
+    {
+        auto lockData = data->buffer();
+        float *dataPtr = lockData.as<float*>();
+
+        for (size_t i = 0; i < 4; ++i) {
+            dataPtr[i] = 0;
+        }
+    }
+    CNNNetwork network = core.ReadNetwork(model, data);
+    {
+        auto outputs = network.getOutputsInfo();
+        ASSERT_NE(outputs.find("text_features"), outputs.end());
+    }
+
+    auto nGraphFunc = network.getFunction();
+    // Disable shape inference (WA for generic operations)
+    ngraph::op::GenericIE::DisableReshape noReshape(nGraphFunc);
+
+    ngraph::pass::Manager manager;
+
+    manager.register_pass<ngraph::pass::ConvertOpSet1ToLegacy>();
+
+    manager.run_passes(nGraphFunc);
+
+    auto clonedNetwork = InferenceEngine::details::convertFunctionToICNNNetwork(nGraphFunc, network);
+    {
+        OutputsDataMap outputs;
+        clonedNetwork->getOutputsInfo(outputs);
+        ASSERT_NE(outputs.find("text_features"), outputs.end());
+    }
+}
 IE_SUPPRESS_DEPRECATED_END
diff --git a/ngraph/core/src/graph_util.cpp b/ngraph/core/src/graph_util.cpp
index d9c0f44d6b4..0bb6e8b89ce 100644
--- a/ngraph/core/src/graph_util.cpp
+++ b/ngraph/core/src/graph_util.cpp
@@ -902,6 +902,8 @@ bool ngraph::replace_output_update_name(Output<Node> output, const Output<Node>&
         if (has_result_output && !is_type<ngraph::op::Parameter>(replacement.get_node()))
         {
             replacement.get_node()->set_friendly_name(output.get_node()->get_friendly_name());
+            // Update output tensor name
+            replacement.get_tensor().set_name(output.get_node()->get_friendly_name());
         }
         output.replace(replacement);
         copy_runtime_info({replacement.get_node_shared_ptr(), output.get_node_shared_ptr()},