From 0ea0a08aad80d3c4aaf41bcb8916e14e8f88edeb Mon Sep 17 00:00:00 2001
From: Teresa Charlin <teresa.charlinreyes@arm.com>
Date: Tue, 2 Aug 2022 14:17:39 +0100
Subject: Bug Fixes for refactor of the ExecuteNetwork.

* dot file to be generated when -v is given. It was only being generated when using the delegate as executor
* output name read from m_Params.m_OutputNames instead of m_TfLiteInterpreter
* typo: "delage" instead of "delegate"
* QAsymmS8 templated as int8, instead of uint8


Change-Id: Ie13ae0f7e6395c0ebcb5ecda32e72082dee8aa6c

Signed-off-by: Teresa Charlin <teresa.charlinreyes@arm.com>
Change-Id: Iac97a23927ba42290ebeb3446bbd36da15045e07
---
 tests/ExecuteNetwork/ArmNNExecutor.cpp        | 11 ++++++++++-
 tests/ExecuteNetwork/ExecuteNetworkParams.cpp |  8 --------
 tests/ExecuteNetwork/TfliteExecutor.cpp       | 18 +++++++++---------
 3 files changed, 19 insertions(+), 18 deletions(-)

diff --git a/tests/ExecuteNetwork/ArmNNExecutor.cpp b/tests/ExecuteNetwork/ArmNNExecutor.cpp
index 5be3383061..d1892f9d42 100644
--- a/tests/ExecuteNetwork/ArmNNExecutor.cpp
+++ b/tests/ExecuteNetwork/ArmNNExecutor.cpp
@@ -533,6 +533,15 @@ armnn::IOptimizedNetworkPtr ArmNNExecutor::OptimizeNetwork(armnn::INetwork* netw
         LogAndThrow("Optimize returned nullptr");
     }
 
+    // If v,visualize-optimized-model is enabled then construct a file name for the dot file.
+    if (m_Params.m_EnableLayerDetails)
+    {
+        fs::path filename = m_Params.m_ModelPath;
+        filename.replace_extension("dot");
+        std::fstream file(filename.c_str(), std::ios_base::out);
+        optNet->SerializeToDot(file);
+    }
+
     return optNet;
 }
 
@@ -683,12 +692,12 @@ void ArmNNExecutor::CompareAndPrintResult(std::vector<const void*> otherOutput)
                     break;
                 }
                 case armnn::DataType::QSymmS8:
+                case armnn::DataType::QAsymmS8:
                 {
                     result = ComputeRMSE<int8_t>(outputTensor.second.GetMemoryArea(), otherOutput[index++], size);
                     break;
                 }
                 case armnn::DataType::QAsymmU8:
-                case armnn::DataType::QAsymmS8:
                 {
                     result = ComputeRMSE<uint8_t>(outputTensor.second.GetMemoryArea(), otherOutput[index++], size);
                     break;
diff --git a/tests/ExecuteNetwork/ExecuteNetworkParams.cpp b/tests/ExecuteNetwork/ExecuteNetworkParams.cpp
index f341c30738..17c08717e4 100644
--- a/tests/ExecuteNetwork/ExecuteNetworkParams.cpp
+++ b/tests/ExecuteNetwork/ExecuteNetworkParams.cpp
@@ -171,14 +171,6 @@ armnnDelegate::DelegateOptions ExecuteNetworkParams::ToDelegateOptions() const
     }
     delegateOptions.SetOptimizerOptions(options);
 
-    // If v,visualize-optimized-model is enabled then construct a file name for the dot file.
-    if (m_EnableLayerDetails)
-    {
-        fs::path filename = m_ModelPath;
-        filename.replace_extension("dot");
-        delegateOptions.SetSerializeToDot(filename);
-    }
-
     return delegateOptions;
 }
 
diff --git a/tests/ExecuteNetwork/TfliteExecutor.cpp b/tests/ExecuteNetwork/TfliteExecutor.cpp
index dc495be5c3..98b6c9dad1 100644
--- a/tests/ExecuteNetwork/TfliteExecutor.cpp
+++ b/tests/ExecuteNetwork/TfliteExecutor.cpp
@@ -144,7 +144,7 @@ std::vector<const void *> TfLiteExecutor::Execute()
                 outputSize *=  outputDims->data[dim];
             }
 
-            std::cout << m_TfLiteInterpreter->tensor(tfLiteDelegateOutputId)->name << ": ";
+            std::cout << m_Params.m_OutputNames[outputIndex] << ": ";
             results.push_back(m_TfLiteInterpreter->tensor(tfLiteDelegateOutputId)->allocation);
 
             switch (m_TfLiteInterpreter->tensor(tfLiteDelegateOutputId)->type)
@@ -152,38 +152,38 @@ std::vector<const void *> TfLiteExecutor::Execute()
 
                 case kTfLiteFloat32:
                 {
-                    auto tfLiteDelageOutputData = m_TfLiteInterpreter->typed_tensor<float>(tfLiteDelegateOutputId);
+                    auto tfLiteDelegateOutputData = m_TfLiteInterpreter->typed_tensor<float>(tfLiteDelegateOutputId);
 
                     for (int i = 0; i < outputSize; ++i)
                     {
-                        fprintf(outputTensorFile, "%f ", tfLiteDelageOutputData[i]);
+                        fprintf(outputTensorFile, "%f ", tfLiteDelegateOutputData[i]);
                     }
                     break;
                 }
                 case kTfLiteInt32:
                 {
-                    auto tfLiteDelageOutputData = m_TfLiteInterpreter->typed_tensor<int32_t>(tfLiteDelegateOutputId);
+                    auto tfLiteDelegateOutputData = m_TfLiteInterpreter->typed_tensor<int32_t>(tfLiteDelegateOutputId);
                     for (int i = 0; i < outputSize; ++i)
                     {
-                        fprintf(outputTensorFile, "%d ", tfLiteDelageOutputData[i]);
+                        fprintf(outputTensorFile, "%d ", tfLiteDelegateOutputData[i]);
                     }
                     break;
                 }
                 case kTfLiteUInt8:
                 {
-                    auto tfLiteDelageOutputData = m_TfLiteInterpreter->typed_tensor<uint8_t>(tfLiteDelegateOutputId);
+                    auto tfLiteDelegateOutputData = m_TfLiteInterpreter->typed_tensor<uint8_t>(tfLiteDelegateOutputId);
                     for (int i = 0; i < outputSize; ++i)
                     {
-                        fprintf(outputTensorFile, "%u ", tfLiteDelageOutputData[i]);
+                        fprintf(outputTensorFile, "%u ", tfLiteDelegateOutputData[i]);
                     }
                     break;
                 }
                 case kTfLiteInt8:
                 {
-                    auto tfLiteDelageOutputData = m_TfLiteInterpreter->typed_tensor<int8_t>(tfLiteDelegateOutputId);
+                    auto tfLiteDelegateOutputData = m_TfLiteInterpreter->typed_tensor<int8_t>(tfLiteDelegateOutputId);
                     for (int i = 0; i < outputSize; ++i)
                     {
-                        fprintf(outputTensorFile, "%d ", tfLiteDelageOutputData[i]);
+                        fprintf(outputTensorFile, "%d ", tfLiteDelegateOutputData[i]);
                     }
                     break;
                 }
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