IVGCVSW-6359 Create a single definition of TContainer

 * Added a single definition of TContainer to include/armnn/Utils.hpp
 * Change all files which contained their own identical definitions of TContainer to use the new one


Signed-off-by: David Monahan <David.Monahan@arm.com>
Change-Id: I63e633693a430bbbd6a29001cafa19742ef8309a

1 files changed, 10 insertions, 11 deletions

diff --git a/src/armnn/test/ModelAccuracyCheckerTest.cpp b/src/armnn/test/ModelAccuracyCheckerTest.cpp
index 47f112ee72..47ae3f4b0a 100644
--- a/src/armnn/test/ModelAccuracyCheckerTest.cpp
+++ b/src/armnn/test/ModelAccuracyCheckerTest.cpp
@@ -3,6 +3,7 @@
 // SPDX-License-Identifier: MIT
 //
 #include "ModelAccuracyChecker.hpp"
+#include <armnn/Utils.hpp>
 
 #include <doctest/doctest.h>
 
@@ -52,8 +53,6 @@ struct TestHelper
 
 TEST_SUITE("ModelAccuracyCheckerTest")
 {
-using TContainer =
-        mapbox::util::variant<std::vector<float>, std::vector<int>, std::vector<unsigned char>, std::vector<int8_t>>;
 
 TEST_CASE_FIXTURE(TestHelper, "TestFloat32OutputTensorAccuracy")
 {
@@ -61,12 +60,12 @@ TEST_CASE_FIXTURE(TestHelper, "TestFloat32OutputTensorAccuracy")
 
     // Add image 1 and check accuracy
     std::vector<float> inferenceOutputVector1 = {0.05f, 0.10f, 0.70f, 0.15f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f};
-    TContainer inference1Container(inferenceOutputVector1);
-    std::vector<TContainer> outputTensor1;
+    armnn::TContainer inference1Container(inferenceOutputVector1);
+    std::vector<armnn::TContainer> outputTensor1;
     outputTensor1.push_back(inference1Container);
 
     std::string imageName = "val_01.JPEG";
-    checker.AddImageResult<TContainer>(imageName, outputTensor1);
+    checker.AddImageResult<armnn::TContainer>(imageName, outputTensor1);
 
     // Top 1 Accuracy
     float totalAccuracy = checker.GetAccuracy(1);
@@ -74,12 +73,12 @@ TEST_CASE_FIXTURE(TestHelper, "TestFloat32OutputTensorAccuracy")
 
     // Add image 2 and check accuracy
     std::vector<float> inferenceOutputVector2 = {0.10f, 0.0f, 0.0f, 0.0f, 0.05f, 0.70f, 0.0f, 0.0f, 0.0f, 0.15f};
-    TContainer inference2Container(inferenceOutputVector2);
-    std::vector<TContainer> outputTensor2;
+    armnn::TContainer inference2Container(inferenceOutputVector2);
+    std::vector<armnn::TContainer> outputTensor2;
     outputTensor2.push_back(inference2Container);
 
     imageName = "val_02.JPEG";
-    checker.AddImageResult<TContainer>(imageName, outputTensor2);
+    checker.AddImageResult<armnn::TContainer>(imageName, outputTensor2);
 
     // Top 1 Accuracy
     totalAccuracy = checker.GetAccuracy(1);
@@ -91,12 +90,12 @@ TEST_CASE_FIXTURE(TestHelper, "TestFloat32OutputTensorAccuracy")
 
     // Add image 3 and check accuracy
     std::vector<float> inferenceOutputVector3 = {0.0f, 0.10f, 0.0f, 0.0f, 0.05f, 0.70f, 0.0f, 0.0f, 0.0f, 0.15f};
-    TContainer inference3Container(inferenceOutputVector3);
-    std::vector<TContainer> outputTensor3;
+    armnn::TContainer inference3Container(inferenceOutputVector3);
+    std::vector<armnn::TContainer> outputTensor3;
     outputTensor3.push_back(inference3Container);
 
     imageName = "val_03.JPEG";
-    checker.AddImageResult<TContainer>(imageName, outputTensor3);
+    checker.AddImageResult<armnn::TContainer>(imageName, outputTensor3);
 
     // Top 1 Accuracy
     totalAccuracy = checker.GetAccuracy(1);