From 15f7faef88357679064e0e9d3bd91dd18c7625d6 Mon Sep 17 00:00:00 2001
From: Sadik Armagan <sadik.armagan@arm.com>
Date: Wed, 18 Nov 2020 09:37:03 +0000
Subject: IVGCVSW-5377 'Add ArmNN TfLite delegate to ExecuteNetwork'

* Assign correct input values for the model
* Call the right Validate function for Mul and Sub operators
* Return the correct data type for kTfLiteInt8

Signed-off-by: Sadik Armagan <sadik.armagan@arm.com>
Change-Id: I6d23adf68d33d8be9a1fbf5d19dfe47939a6d3d6
---
 tests/ExecuteNetwork/ExecuteNetwork.cpp | 49 ++++++++++++++++++++++++---------
 1 file changed, 36 insertions(+), 13 deletions(-)

(limited to 'tests')

diff --git a/tests/ExecuteNetwork/ExecuteNetwork.cpp b/tests/ExecuteNetwork/ExecuteNetwork.cpp
index fa84a6ee4f..ba7ce29cd7 100644
--- a/tests/ExecuteNetwork/ExecuteNetwork.cpp
+++ b/tests/ExecuteNetwork/ExecuteNetwork.cpp
@@ -77,6 +77,14 @@ int TfLiteDelegateMainImpl(const ExecuteNetworkParams& params,
     for(unsigned int inputIndex = 0; inputIndex < numInputs; ++inputIndex)
     {
         int input = tfLiteInterpreter->inputs()[inputIndex];
+        TfLiteIntArray* inputDims = tfLiteInterpreter->tensor(input)->dims;
+
+        long inputSize = 1;
+        for (unsigned int dim = 0; dim < static_cast<unsigned int>(inputDims->size); ++dim)
+        {
+            inputSize *=  inputDims->data[dim];
+        }
+
         if (params.m_InputTypes[inputIndex].compare("float") == 0)
         {
             auto inputData = tfLiteInterpreter->typed_tensor<float>(input);
@@ -86,8 +94,15 @@ int TfLiteDelegateMainImpl(const ExecuteNetworkParams& params,
                                    params.m_InputTypes[inputIndex],
                                    armnn::EmptyOptional(),
                                    dataFile);
-            inputData = reinterpret_cast<float*>(&tensorData);
-            armnn::IgnoreUnused(inputData);
+
+            mapbox::util::apply_visitor([&](auto&& value)
+            {
+                for (unsigned int i = 0; i < inputSize; ++i)
+                {
+                    inputData[i] = value.data()[i];
+                }
+            },
+            tensorData);
         }
         else if (params.m_InputTypes[inputIndex].compare("int") == 0)
         {
@@ -98,8 +113,14 @@ int TfLiteDelegateMainImpl(const ExecuteNetworkParams& params,
                                    params.m_InputTypes[inputIndex],
                                    armnn::EmptyOptional(),
                                    dataFile);
-            inputData = reinterpret_cast<int32_t*>(&tensorData);
-            armnn::IgnoreUnused(inputData);
+            mapbox::util::apply_visitor([&](auto&& value)
+            {
+                for (unsigned int i = 0; i < inputSize; ++i)
+                {
+                    inputData[i] = value.data()[i];
+                }
+            },
+            tensorData);
         }
         else if (params.m_InputTypes[inputIndex].compare("qasymm8") == 0)
         {
@@ -110,8 +131,14 @@ int TfLiteDelegateMainImpl(const ExecuteNetworkParams& params,
                                    params.m_InputTypes[inputIndex],
                                    armnn::EmptyOptional(),
                                    dataFile);
-            inputData = reinterpret_cast<uint8_t*>(&tensorData);
-            armnn::IgnoreUnused(inputData);
+            mapbox::util::apply_visitor([&](auto&& value)
+            {
+                for (unsigned int i = 0; i < inputSize; ++i)
+                {
+                    inputData[i] = value.data()[i];
+                }
+            },
+            tensorData);
         }
         else
         {
@@ -128,21 +155,19 @@ int TfLiteDelegateMainImpl(const ExecuteNetworkParams& params,
         // Print out the output
         for (unsigned int outputIndex = 0; outputIndex < params.m_OutputNames.size(); ++outputIndex)
         {
-            std::cout << "Printing out the output" << std::endl;
             auto tfLiteDelegateOutputId = tfLiteInterpreter->outputs()[outputIndex];
-            TfLiteIntArray *outputDims = tfLiteInterpreter->tensor(tfLiteDelegateOutputId)->dims;
+            TfLiteIntArray* outputDims = tfLiteInterpreter->tensor(tfLiteDelegateOutputId)->dims;
 
-            int outputSize = 1;
+            long outputSize = 1;
             for (unsigned int dim = 0; dim < static_cast<unsigned int>(outputDims->size); ++dim)
             {
-                outputSize *= outputDims->data[dim];
+                outputSize *=  outputDims->data[dim];
             }
 
             std::cout << params.m_OutputNames[outputIndex] << ": ";
             if (params.m_OutputTypes[outputIndex].compare("float") == 0)
             {
                 auto tfLiteDelageOutputData = tfLiteInterpreter->typed_tensor<float>(tfLiteDelegateOutputId);
-
                 if(tfLiteDelageOutputData == NULL)
                 {
                     ARMNN_LOG(fatal) << "Output tensor is null, output type: "
@@ -162,7 +187,6 @@ int TfLiteDelegateMainImpl(const ExecuteNetworkParams& params,
             else if (params.m_OutputTypes[outputIndex].compare("int") == 0)
             {
                 auto tfLiteDelageOutputData = tfLiteInterpreter->typed_tensor<int32_t>(tfLiteDelegateOutputId);
-
                 if(tfLiteDelageOutputData == NULL)
                 {
                     ARMNN_LOG(fatal) << "Output tensor is null, output type: "
@@ -182,7 +206,6 @@ int TfLiteDelegateMainImpl(const ExecuteNetworkParams& params,
             else if (params.m_OutputTypes[outputIndex].compare("qasymm8") == 0)
             {
                 auto tfLiteDelageOutputData = tfLiteInterpreter->typed_tensor<uint8_t>(tfLiteDelegateOutputId);
-
                 if(tfLiteDelageOutputData == NULL)
                 {
                     ARMNN_LOG(fatal) << "Output tensor is null, output type: "
-- 
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