From bb46dde88befe14583eaac83f65775a7543d4586 Mon Sep 17 00:00:00 2001
From: Rob Hughes <robert.hughes@arm.com>
Date: Wed, 20 May 2020 15:27:37 +0100
Subject: Fix a few build warnings:

* Remove redundant asserts for unsigned ints being positive
* Remove unneeded include of lightweight_test.hpp header
* Remove unused exception variable names
* Replace hardcoded 0.0f with T() for some template functions
* Add a few static_casts

Change-Id: I290b0433cf995f6d0199422eaa10f816e5fd8eb9
Signed-off-by: Robert Hughes <robert.hughes@arm.com>
---
 .../test/layerTests/Conv2dTestImpl.cpp             |  6 +-
 .../test/layerTests/LstmTestImpl.cpp               | 76 +++++++++++-----------
 .../layerTests/TransposeConvolution2dTestImpl.cpp  |  2 +-
 3 files changed, 42 insertions(+), 42 deletions(-)

(limited to 'src/backends/backendsCommon/test/layerTests')

diff --git a/src/backends/backendsCommon/test/layerTests/Conv2dTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/Conv2dTestImpl.cpp
index 154ece2657..acc888ebc0 100644
--- a/src/backends/backendsCommon/test/layerTests/Conv2dTestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/Conv2dTestImpl.cpp
@@ -76,7 +76,7 @@ boost::multi_array<T, 1> GetBias2(bool biasEnabled, float qScale)
     if(biasEnabled)
     {
         armnn::TensorInfo biasDesc({static_cast<unsigned int>(Bias2.size())}, ArmnnType);
-        boost::multi_array<T, 1> bias = MakeTensor<T, 1>(biasDesc, QuantizedVector<T>(Bias2, qScale, 0.0f));
+        boost::multi_array<T, 1> bias = MakeTensor<T, 1>(biasDesc, QuantizedVector<T>(Bias2, qScale, 0));
         return bias;
     }
     else
@@ -92,7 +92,7 @@ boost::multi_array<T, 1> GetBias4(bool biasEnabled, float qScale)
     if(biasEnabled)
     {
         armnn::TensorInfo biasDesc({static_cast<unsigned int>(Bias4.size())}, ArmnnType);
-        boost::multi_array<T, 1> bias = MakeTensor<T, 1>(biasDesc, QuantizedVector<T>(Bias4, qScale, 0.0f));
+        boost::multi_array<T, 1> bias = MakeTensor<T, 1>(biasDesc, QuantizedVector<T>(Bias4, qScale, 0));
         return bias;
     }
     else
@@ -108,7 +108,7 @@ boost::multi_array<T, 1> GetBias8(bool biasEnabled, float qScale)
     if(biasEnabled)
     {
         armnn::TensorInfo biasDesc({static_cast<unsigned int>(Bias4.size())}, ArmnnType);
-        boost::multi_array<T, 1> bias = MakeTensor<T, 1>(biasDesc, QuantizedVector<T>(Bias8, qScale, 0.0f));
+        boost::multi_array<T, 1> bias = MakeTensor<T, 1>(biasDesc, QuantizedVector<T>(Bias8, qScale, 0));
         return bias;
     }
     else
diff --git a/src/backends/backendsCommon/test/layerTests/LstmTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/LstmTestImpl.cpp
index 0ae55e4c60..c7f902ab04 100644
--- a/src/backends/backendsCommon/test/layerTests/LstmTestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/LstmTestImpl.cpp
@@ -160,28 +160,28 @@ LstmNoCifgNoPeepholeNoProjectionTestImpl(
 
     LayerTestResult<T, 2> ret(outputTensorInfo);
 
-    std::vector<float> inputVector;
+    std::vector<T> inputVector;
     inputVector.assign(input.data(), input.data() + (batchSize * inputSize));
-    auto inputTensor = MakeTensor<float,2>(inputTensorInfo, inputVector);
+    auto inputTensor = MakeTensor<T,2>(inputTensorInfo, inputVector);
 
-    std::vector<float> cellStateInVector(batchSize * numUnits, 0.f);
-    auto cellStateInTensor = MakeTensor<float,2>(cellStateInTensorInfo, cellStateInVector);
+    std::vector<T> cellStateInVector(batchSize * numUnits, T());
+    auto cellStateInTensor = MakeTensor<T,2>(cellStateInTensorInfo, cellStateInVector);
 
-    std::vector<float> outputStateInVector(batchSize * outputSize, 0.f);
-    auto outputStateInTensor = MakeTensor<float,2>(outputStateInTensorInfo, outputStateInVector);
+    std::vector<T> outputStateInVector(batchSize * outputSize, T());
+    auto outputStateInTensor = MakeTensor<T,2>(outputStateInTensorInfo, outputStateInVector);
 
-    std::vector<float> scratchBufferVector(batchSize * numUnits * 4, 0.f);
-    auto scratchBufferTensor = MakeTensor<float,2>(scratchBufferTensorInfo, scratchBufferVector);
+    std::vector<T> scratchBufferVector(batchSize * numUnits * 4, T());
+    auto scratchBufferTensor = MakeTensor<T,2>(scratchBufferTensorInfo, scratchBufferVector);
 
-    std::vector<float> outputStateOutVector(batchSize * outputSize, 0.f);
-    auto outputStateOutTensor = MakeTensor<float,2>(outputStateOutTensorInfo, outputStateOutVector);
+    std::vector<T> outputStateOutVector(batchSize * outputSize, T());
+    auto outputStateOutTensor = MakeTensor<T,2>(outputStateOutTensorInfo, outputStateOutVector);
 
-    std::vector<float> cellStateOutVector(batchSize * numUnits, 0.f);
-    auto cellStateOutTensor = MakeTensor<float,2>(cellStateOutTensorInfo, cellStateOutVector);
+    std::vector<T> cellStateOutVector(batchSize * numUnits, T());
+    auto cellStateOutTensor = MakeTensor<T,2>(cellStateOutTensorInfo, cellStateOutVector);
 
-    std::vector<float> outputVector;
+    std::vector<T> outputVector;
     outputVector.assign(outputExpected.data(), outputExpected.data() + (batchSize * outputSize));
-    ret.outputExpected = MakeTensor<float, 2>(outputTensorInfo, outputVector);
+    ret.outputExpected = MakeTensor<T, 2>(outputTensorInfo, outputVector);
 
     std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo);
     std::unique_ptr<armnn::ITensorHandle> cellStateInHandle =
@@ -363,28 +363,28 @@ LstmLayerNoCifgWithPeepholeWithProjectionTestImpl(armnn::IWorkloadFactory& workl
 
     LayerTestResult<T, 2> ret(outputTensorInfo);
 
-    std::vector<float> inputVector;
+    std::vector<T> inputVector;
     inputVector.assign(input.data(), input.data() + (batchSize * inputSize));
-    auto inputTensor = MakeTensor<float,2>(inputTensorInfo, inputVector);
+    auto inputTensor = MakeTensor<T,2>(inputTensorInfo, inputVector);
 
-    std::vector<float> cellStateInVector(batchSize * numUnits, 0.f);
-    auto cellStateInTensor = MakeTensor<float,2>(cellStateInTensorInfo, cellStateInVector);
+    std::vector<T> cellStateInVector(batchSize * numUnits, T());
+    auto cellStateInTensor = MakeTensor<T,2>(cellStateInTensorInfo, cellStateInVector);
 
-    std::vector<float> outputStateInVector(batchSize * outputSize, 0.f);
-    auto outputStateInTensor = MakeTensor<float,2>(outputStateInTensorInfo, outputStateInVector);
+    std::vector<T> outputStateInVector(batchSize * outputSize, T());
+    auto outputStateInTensor = MakeTensor<T,2>(outputStateInTensorInfo, outputStateInVector);
 
-    std::vector<float> scratchBufferVector(batchSize * numUnits * 4, 0.f);
-    auto scratchBufferTensor = MakeTensor<float,2>(scratchBufferTensorInfo, scratchBufferVector);
+    std::vector<T> scratchBufferVector(batchSize * numUnits * 4, T());
+    auto scratchBufferTensor = MakeTensor<T,2>(scratchBufferTensorInfo, scratchBufferVector);
 
-    std::vector<float> outputStateOutVector(batchSize * outputSize, 0.f);
-    auto outputStateOutTensor = MakeTensor<float,2>(outputStateOutTensorInfo, outputStateOutVector);
+    std::vector<T> outputStateOutVector(batchSize * outputSize, T());
+    auto outputStateOutTensor = MakeTensor<T,2>(outputStateOutTensorInfo, outputStateOutVector);
 
-    std::vector<float> cellStateOutVector(batchSize * numUnits, 0.f);
-    auto cellStateOutTensor = MakeTensor<float,2>(cellStateOutTensorInfo, cellStateOutVector);
+    std::vector<T> cellStateOutVector(batchSize * numUnits, T());
+    auto cellStateOutTensor = MakeTensor<T,2>(cellStateOutTensorInfo, cellStateOutVector);
 
-    std::vector<float> outputVector;
+    std::vector<T> outputVector;
     outputVector.assign(outputExpected.data(), outputExpected.data() + (batchSize * outputSize));
-    ret.outputExpected = MakeTensor<float, 2>(outputTensorInfo, outputVector);
+    ret.outputExpected = MakeTensor<T, 2>(outputTensorInfo, outputVector);
 
     std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo);
     std::unique_ptr<armnn::ITensorHandle> cellStateInHandle =
@@ -1195,27 +1195,27 @@ LayerTestResult<T, 2> LstmLayerWithCifgWithPeepholeNoProjectionTestImpl(
 
 
     // List of outputs
-    std::vector<float> scratchBufferVector(batchSize * scratchBufferSize, 0.f);
-    auto scratchBufferTensor = MakeTensor<float,2>(scratchBufferTensorInfo, scratchBufferVector);
+    std::vector<T> scratchBufferVector(batchSize * scratchBufferSize, T());
+    auto scratchBufferTensor = MakeTensor<T,2>(scratchBufferTensorInfo, scratchBufferVector);
     LayerTestResult<T, 2> ret0(scratchBufferTensorInfo);
 
     // Output state for a certain time step
-    std::vector<float> outputStateOutVector(batchSize * outputSize, 0.f);
-    auto outputStateOutTensor = MakeTensor<float,2>(outputStateOutTensorInfo, outputStateOutVector);
+    std::vector<T> outputStateOutVector(batchSize * outputSize, T());
+    auto outputStateOutTensor = MakeTensor<T,2>(outputStateOutTensorInfo, outputStateOutVector);
     LayerTestResult<T, 2> ret1(outputStateOutTensorInfo);
 
     // Cell state for a certain time step
-    std::vector<float> cellStateOutVector(batchSize * cellSize, 0.f);
-    auto cellStateOutTensor = MakeTensor<float,2>(cellStateOutTensorInfo, cellStateOutVector);
+    std::vector<T> cellStateOutVector(batchSize * cellSize, T());
+    auto cellStateOutTensor = MakeTensor<T,2>(cellStateOutTensorInfo, cellStateOutVector);
     LayerTestResult<T, 2> ret2(cellStateOutTensorInfo);
 
     // Output for a certain time step
-    std::vector<float> outputVector(batchSize * outputSize, 0.f);
-    auto outputTensor = MakeTensor<float, 2>(outputTensorInfo, outputVector);
-    std::vector<float> outputData;
+    std::vector<T> outputVector(batchSize * outputSize, T());
+    auto outputTensor = MakeTensor<T, 2>(outputTensorInfo, outputVector);
+    std::vector<T> outputData;
     outputData.assign(outputExpected.data(), outputExpected.data() + batchSize*outputSize);
     LayerTestResult<T, 2> ret3(outputTensorInfo);
-    ret3.outputExpected = MakeTensor<float, 2>(outputTensorInfo, outputData);
+    ret3.outputExpected = MakeTensor<T, 2>(outputTensorInfo, outputData);
 
     // Prepare the inputs and outputs for the workload
     std::unique_ptr<armnn::ITensorHandle> inputHandle =
diff --git a/src/backends/backendsCommon/test/layerTests/TransposeConvolution2dTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/TransposeConvolution2dTestImpl.cpp
index 813c623cff..a599bae4b5 100644
--- a/src/backends/backendsCommon/test/layerTests/TransposeConvolution2dTestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/TransposeConvolution2dTestImpl.cpp
@@ -105,7 +105,7 @@ void TransposeConvolution2dTestImpl(armnn::IWorkloadFactory& workloadFactory,
     ExecuteWorkload(*workload, memoryManager);
 
     // copy output
-    output.second = std::vector<T>(output.first.GetNumElements(), 0.0f);
+    output.second = std::vector<T>(output.first.GetNumElements(), T());
     CopyDataFromITensorHandle(output.second.data(), outputHandle.get());
 }
 
-- 
cgit v1.2.1