IVGCVSW-4485 Remove Boost assert

 * Change boost assert to armnn assert
 * Change include file to armnn assert
 * Fix ARMNN_ASSERT_MSG issue with multiple conditions
 * Change BOOST_ASSERT to BOOST_TEST where appropriate
 * Remove unused include statements

Signed-off-by: Narumol Prangnawarat <narumol.prangnawarat@arm.com>
Change-Id: I5d0fa3a37b7c1c921216de68f0073aa34702c9ff

6 files changed, 28 insertions, 29 deletions

diff --git a/src/backends/backendsCommon/test/layerTests/ActivationTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/ActivationTestImpl.cpp
index 319434e093..a82048cd81 100644
--- a/src/backends/backendsCommon/test/layerTests/ActivationTestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/ActivationTestImpl.cpp
@@ -1212,9 +1212,9 @@ LayerTestResult<T,4> CompareActivationTestImpl(
     SetWorkloadOutput(refData, refInfo, 0, outputTensorInfo, outputHandleRef.get());
 
     std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateActivation(data, info);
-    BOOST_ASSERT(workload != nullptr);
+    ARMNN_ASSERT(workload != nullptr);
     std::unique_ptr<armnn::IWorkload> workloadRef = refWorkloadFactory.CreateActivation(refData, refInfo);
-    BOOST_ASSERT(workloadRef != nullptr);
+    ARMNN_ASSERT(workloadRef != nullptr);
 
     inputHandle->Allocate();
     outputHandle->Allocate();
diff --git a/src/backends/backendsCommon/test/layerTests/ComparisonTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/ComparisonTestImpl.cpp
index 2156b0ee9e..a6b703b08b 100644
--- a/src/backends/backendsCommon/test/layerTests/ComparisonTestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/ComparisonTestImpl.cpp
@@ -5,7 +5,7 @@
 
 #include "ComparisonTestImpl.hpp"
 
-
+#include <armnn/utility/Assert.hpp>
 #include <Half.hpp>
 #include <QuantizeHelper.hpp>
 #include <ResolveType.hpp>
@@ -18,8 +18,6 @@
 
 #include <test/TensorHelpers.hpp>
 
-#include <boost/assert.hpp>
-
 namespace
 {
 
@@ -44,13 +42,13 @@ LayerTestResult<uint8_t, NumDims> ComparisonTestImpl(
     int outQuantOffset)
 {
     IgnoreUnused(memoryManager);
-    BOOST_ASSERT(shape0.GetNumDimensions() == NumDims);
+    ARMNN_ASSERT(shape0.GetNumDimensions() == NumDims);
     armnn::TensorInfo inputTensorInfo0(shape0, ArmnnInType, quantScale0, quantOffset0);
 
-    BOOST_ASSERT(shape1.GetNumDimensions() == NumDims);
+    ARMNN_ASSERT(shape1.GetNumDimensions() == NumDims);
     armnn::TensorInfo inputTensorInfo1(shape1, ArmnnInType, quantScale1, quantOffset1);
 
-    BOOST_ASSERT(outShape.GetNumDimensions() == NumDims);
+    ARMNN_ASSERT(outShape.GetNumDimensions() == NumDims);
     armnn::TensorInfo outputTensorInfo(outShape, armnn::DataType::Boolean, outQuantScale, outQuantOffset);
 
     auto input0 = MakeTensor<InType, NumDims>(inputTensorInfo0, values0);
diff --git a/src/backends/backendsCommon/test/layerTests/ConcatTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/ConcatTestImpl.cpp
index 1e40b42dcf..9e08e30dec 100644
--- a/src/backends/backendsCommon/test/layerTests/ConcatTestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/ConcatTestImpl.cpp
@@ -61,7 +61,7 @@ bool NeedPermuteForConcat(
         }
         else
         {
-            BOOST_ASSERT_MSG(nDimensions == tensorInfo.GetShape().GetNumDimensions(),
+            ARMNN_ASSERT_MSG(nDimensions == tensorInfo.GetShape().GetNumDimensions(),
                 "Input shapes must have the same number of dimensions");
         }
     }
@@ -92,7 +92,7 @@ void Generate3dPermuteVectorForConcat(
     unsigned int & concatDim,
     std::pair<PermutationVector, PermutationVector> & permutations)
 {
-    BOOST_ASSERT_MSG(numDimensions <= 3,
+    ARMNN_ASSERT_MSG(numDimensions <= 3,
        "Only dimensions 1,2 and 3 are supported by this helper");
     unsigned int expandedBy = 3 - numDimensions;
     unsigned int expandedConcatAxis = concatDim + expandedBy;
@@ -113,7 +113,7 @@ void Generate3dPermuteVectorForConcat(
     }
     else
     {
-        BOOST_ASSERT(expandedConcatAxis == 0);
+        ARMNN_ASSERT(expandedConcatAxis == 0);
         concatDim = 0;
     }
 }
@@ -127,7 +127,7 @@ template<typename T> void PermuteTensorData(
     std::vector<T>& outputData)
 {
     IgnoreUnused(memoryManager);
-    BOOST_ASSERT_MSG(inputData != nullptr, "inputData must not be null");
+    ARMNN_ASSERT_MSG(inputData != nullptr, "inputData must not be null");
     if (inputData == nullptr)
     {
         // Nullptr is an error in the test. By returning without doing the concatenation
@@ -179,7 +179,7 @@ template<typename T> void PermuteInputsForConcat(
     TensorInfo & outputTensorInfo)
 {
     IgnoreUnused(memoryManager);
-    BOOST_ASSERT_MSG(inputTensorInfos.size() > 1,
+    ARMNN_ASSERT_MSG(inputTensorInfos.size() > 1,
         "Expecting more than one tensor to be concatenated here");
 
     unsigned int numDims = 0;
@@ -200,12 +200,12 @@ template<typename T> void PermuteInputsForConcat(
 
             // Store the reverese permutation.
             permuteVector = permutations.second;
-            BOOST_ASSERT_MSG(!permuteVector.IsEqual(identity),
+            ARMNN_ASSERT_MSG(!permuteVector.IsEqual(identity),
                 "Test logic error, we don't need permutation, so we shouldn't arrive here");
         }
         else
         {
-            BOOST_ASSERT_MSG(numDims == tensorInfo.GetShape().GetNumDimensions(),
+            ARMNN_ASSERT_MSG(numDims == tensorInfo.GetShape().GetNumDimensions(),
                 "All inputs must have the same number of dimensions");
         }
 
@@ -244,7 +244,7 @@ template <typename T> void PermuteOutputForConcat(
     std::unique_ptr<ITensorHandle> && inputDataHandle,
     T * data)
 {
-    BOOST_ASSERT_MSG(data != nullptr, "data must not be null");
+    ARMNN_ASSERT_MSG(data != nullptr, "data must not be null");
     if (data == nullptr)
     {
         // Nullptr is an error in the test. By returning without doing the permutation
@@ -279,7 +279,7 @@ template<typename T> void Concatenate(
     unsigned int concatDim,
     bool useSubtensor)
 {
-    BOOST_ASSERT_MSG(output != nullptr, "output must not be null");
+    ARMNN_ASSERT_MSG(output != nullptr, "output must not be null");
     if (output == nullptr)
     {
         // Nullptr is an error in the test. By returning without doing the permutation
diff --git a/src/backends/backendsCommon/test/layerTests/Conv2dTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/Conv2dTestImpl.cpp
index 50ad667dde..c66027efdf 100644
--- a/src/backends/backendsCommon/test/layerTests/Conv2dTestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/Conv2dTestImpl.cpp
@@ -169,9 +169,9 @@ template<typename T, typename B>
 void ApplyBias(std::vector<T>& v, float vScale, int32_t vOffset,
     const std::vector<B>& bias, float bScale, int32_t bOffset, uint32_t w, uint32_t h)
 {
-    BOOST_ASSERT_MSG((armnn::IsQuantizedType<T>() && vScale != 0.0f) || (!armnn::IsQuantizedType<T>()),
+    ARMNN_ASSERT_MSG((armnn::IsQuantizedType<T>() && vScale != 0.0f) || (!armnn::IsQuantizedType<T>()),
                      "Invalid type and parameter combination.");
-    BOOST_ASSERT_MSG((armnn::IsQuantizedType<B>() && bScale != 0.0f) || (!armnn::IsQuantizedType<B>()),
+    ARMNN_ASSERT_MSG((armnn::IsQuantizedType<B>() && bScale != 0.0f) || (!armnn::IsQuantizedType<B>()),
                      "Invalid type and parameter combination.");
 
     // Note we need to dequantize and re-quantize the image value and the bias.
@@ -183,7 +183,7 @@ void ApplyBias(std::vector<T>& v, float vScale, int32_t vOffset,
             for (uint32_t x = 0; x < w; ++x)
             {
                 uint32_t offset = (i * h + y) * w + x;
-                BOOST_ASSERT(offset < v.size());
+                ARMNN_ASSERT(offset < v.size());
                 T& outRef = v[offset];
                 float dOutput = SelectiveDequantize(outRef, vScale, vOffset);
                 outRef = SelectiveQuantize<T>(dOutput + dBias, vScale, vOffset);
@@ -236,11 +236,11 @@ LayerTestResult<T, 4> SimpleConvolution2dTestImpl(
     bool biasEnabled = bias.size() > 0;
 
     // This function currently assumes 1 batch of input/output (and duplicates this into 2 batches).
-    BOOST_ASSERT(inputNum == 1);
-    BOOST_ASSERT(outputNum == 1);
+    ARMNN_ASSERT(inputNum == 1);
+    ARMNN_ASSERT(outputNum == 1);
 
     // If a bias is used, its size must equal the number of output channels.
-    BOOST_ASSERT(!biasEnabled || bias.size() == outputChannels);
+    ARMNN_ASSERT(!biasEnabled || bias.size() == outputChannels);
 
 
     // Note these tensors will use two (identical) batches.
@@ -1627,7 +1627,7 @@ LayerTestResult<T, 4> DepthwiseConvolution2dAsymmetricTestImpl(
 
     // If a bias is used, its size must equal the number of output channels.
     bool biasEnabled = bias.size() > 0;
-    BOOST_ASSERT(!biasEnabled || bias.size() == outputChannels);
+    ARMNN_ASSERT(!biasEnabled || bias.size() == outputChannels);
 
     // Creates the tensors.
     armnn::TensorInfo inputTensorInfo =
@@ -2135,11 +2135,11 @@ LayerTestResult<T, 4> DepthwiseConvolution2dTestImpl(
     bool biasEnabled = bias.size() > 0;
 
     // This function currently assumes 1 batch of input/output (and duplicates this into 2 batches).
-    BOOST_ASSERT(inputNum == 1);
-    BOOST_ASSERT(outputNum == 1);
+    ARMNN_ASSERT(inputNum == 1);
+    ARMNN_ASSERT(outputNum == 1);
 
     // If a bias is used, its size must equal the number of output channels.
-    BOOST_ASSERT(!biasEnabled || bias.size() == outputChannels);
+    ARMNN_ASSERT(!biasEnabled || bias.size() == outputChannels);
 
 
     // Note these tensors will use two (identical) batches.
diff --git a/src/backends/backendsCommon/test/layerTests/LayerTestResult.hpp b/src/backends/backendsCommon/test/layerTests/LayerTestResult.hpp
index c277d2d5e1..c64fc88024 100644
--- a/src/backends/backendsCommon/test/layerTests/LayerTestResult.hpp
+++ b/src/backends/backendsCommon/test/layerTests/LayerTestResult.hpp
@@ -6,6 +6,7 @@
 #pragma once
 
 #include <armnn/Tensor.hpp>
+#include <armnn/utility/Assert.hpp>
 
 #include <boost/multi_array.hpp>
 
@@ -14,7 +15,7 @@
 template <std::size_t n>
 boost::array<unsigned int, n> GetTensorShapeAsArray(const armnn::TensorInfo& tensorInfo)
 {
-    BOOST_ASSERT_MSG(n == tensorInfo.GetNumDimensions(),
+    ARMNN_ASSERT_MSG(n == tensorInfo.GetNumDimensions(),
         "Attempting to construct a shape array of mismatching size");
 
     boost::array<unsigned int, n> shape;
diff --git a/src/backends/backendsCommon/test/layerTests/SoftmaxTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/SoftmaxTestImpl.cpp
index 772ae2ccc7..953b543acb 100644
--- a/src/backends/backendsCommon/test/layerTests/SoftmaxTestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/SoftmaxTestImpl.cpp
@@ -104,7 +104,7 @@ LayerTestResult<T, n> SimpleSoftmaxBaseTestImpl(
     outputHandle->Allocate();
     CopyDataToITensorHandle(inputHandle.get(), input.origin());
 
-    BOOST_ASSERT(workload);
+    ARMNN_ASSERT(workload);
 
     ExecuteWorkload(*workload, memoryManager);