IVGCVSW-5963 'Move unit tests to new framework'
* Used doctest in ArmNN unit tests
Signed-off-by: Sadik Armagan <sadik.armagan@arm.com>
Change-Id: Ia9cf5fc72775878885c5f864abf2c56b3a935f1a
diff --git a/src/backends/backendsCommon/test/WorkloadDataValidation.cpp b/src/backends/backendsCommon/test/WorkloadDataValidation.cpp
index 182c913..2034a65 100644
--- a/src/backends/backendsCommon/test/WorkloadDataValidation.cpp
+++ b/src/backends/backendsCommon/test/WorkloadDataValidation.cpp
@@ -13,13 +13,13 @@
#include <reference/workloads/RefWorkloads.hpp>
#include <reference/RefWorkloadFactory.hpp>
-#include <boost/test/unit_test.hpp>
+#include <doctest/doctest.h>
using namespace armnn;
-BOOST_AUTO_TEST_SUITE(WorkloadInfoValidation)
-
-BOOST_AUTO_TEST_CASE(BatchNormalizationQueueDescriptor_Validate_DifferentQuantizationData)
+TEST_SUITE("WorkloadInfoValidation")
+{
+TEST_CASE("BatchNormalizationQueueDescriptor_Validate_DifferentQuantizationData")
{
TensorShape inputShape { 1, 3, 2, 2 };
TensorShape outputShape { 1, 3, 2, 2 };
@@ -42,18 +42,18 @@
invalidData.m_Beta= &sameTensor;
invalidData.m_Gamma = &sameTensor;
- BOOST_CHECK_NO_THROW(RefBatchNormalizationWorkload(invalidData, invalidInfo));
+ CHECK_NOTHROW(RefBatchNormalizationWorkload(invalidData, invalidInfo));
}
-BOOST_AUTO_TEST_CASE(QueueDescriptor_Validate_WrongNumOfInputsOutputs)
+TEST_CASE("QueueDescriptor_Validate_WrongNumOfInputsOutputs")
{
InputQueueDescriptor invalidData;
WorkloadInfo invalidInfo;
//Invalid argument exception is expected, because no inputs and no outputs were defined.
- BOOST_CHECK_THROW(RefWorkloadFactory().CreateInput(invalidData, invalidInfo), armnn::InvalidArgumentException);
+ CHECK_THROWS_AS(RefWorkloadFactory().CreateInput(invalidData, invalidInfo), armnn::InvalidArgumentException);
}
-BOOST_AUTO_TEST_CASE(RefPooling2dFloat32Workload_Validate_WrongDimTensor)
+TEST_CASE("RefPooling2dFloat32Workload_Validate_WrongDimTensor")
{
armnn::TensorInfo inputTensorInfo;
armnn::TensorInfo outputTensorInfo;
@@ -71,10 +71,10 @@
AddInputToWorkload(invalidData, invalidInfo, inputTensorInfo, nullptr);
// Invalid argument exception is expected, input tensor has to be 4D.
- BOOST_CHECK_THROW(RefPooling2dWorkload(invalidData, invalidInfo), armnn::InvalidArgumentException);
+ CHECK_THROWS_AS(RefPooling2dWorkload(invalidData, invalidInfo), armnn::InvalidArgumentException);
}
-BOOST_AUTO_TEST_CASE(SoftmaxQueueDescriptor_Validate_WrongInputHeight)
+TEST_CASE("SoftmaxQueueDescriptor_Validate_WrongInputHeight")
{
unsigned int inputHeight = 1;
unsigned int inputWidth = 1;
@@ -102,10 +102,10 @@
AddOutputToWorkload(invalidData, invalidInfo, outputTensorInfo, nullptr);
//Invalid argument exception is expected, because height != 1.
- BOOST_CHECK_THROW(RefSoftmaxWorkload(invalidData, invalidInfo), armnn::InvalidArgumentException);
+ CHECK_THROWS_AS(RefSoftmaxWorkload(invalidData, invalidInfo), armnn::InvalidArgumentException);
}
-BOOST_AUTO_TEST_CASE(FullyConnectedQueueDescriptor_Validate_RequiredDataMissing)
+TEST_CASE("FullyConnectedQueueDescriptor_Validate_RequiredDataMissing")
{
unsigned int inputWidth = 1;
unsigned int inputHeight = 1;
@@ -149,11 +149,11 @@
//Invalid argument exception is expected, because not all required fields have been provided.
//In particular inputsData[0], outputsData[0] and weightsData can not be null.
- BOOST_CHECK_THROW(RefFullyConnectedWorkload(invalidData, invalidInfo), armnn::InvalidArgumentException);
+ CHECK_THROWS_AS(RefFullyConnectedWorkload(invalidData, invalidInfo), armnn::InvalidArgumentException);
}
-BOOST_AUTO_TEST_CASE(NormalizationQueueDescriptor_Validate_WrongInputHeight)
+TEST_CASE("NormalizationQueueDescriptor_Validate_WrongInputHeight")
{
constexpr unsigned int inputNum = 5;
constexpr unsigned int inputHeight = 32;
@@ -197,10 +197,10 @@
invalidData.m_Parameters.m_K = kappa;
//Invalid argument exception is expected, because input height != output height.
- BOOST_CHECK_THROW(RefNormalizationWorkload(invalidData, invalidInfo), armnn::InvalidArgumentException);
+ CHECK_THROWS_AS(RefNormalizationWorkload(invalidData, invalidInfo), armnn::InvalidArgumentException);
}
-BOOST_AUTO_TEST_CASE(SplitterQueueDescriptor_Validate_WrongWindow)
+TEST_CASE("SplitterQueueDescriptor_Validate_WrongWindow")
{
constexpr unsigned int inputNum = 1;
constexpr unsigned int inputHeight = 32;
@@ -233,16 +233,15 @@
armnn::SplitterQueueDescriptor::ViewOrigin window(wOrigin);
invalidData.m_ViewOrigins.push_back(window);
- BOOST_TEST_INFO("Invalid argument exception is expected, because split window dimensionality does not "
- "match input.");
- BOOST_CHECK_THROW(RefSplitterWorkload(invalidData, invalidInfo), armnn::InvalidArgumentException);
+ INFO("Invalid argument exception is expected, because split window dimensionality does not match input.");
+ CHECK_THROWS_AS(RefSplitterWorkload(invalidData, invalidInfo), armnn::InvalidArgumentException);
// Invalid, since window extends past the boundary of input tensor.
std::vector<unsigned int> wOrigin3 = {0, 0, 15, 0};
armnn::SplitterQueueDescriptor::ViewOrigin window3(wOrigin3);
invalidData.m_ViewOrigins[0] = window3;
- BOOST_TEST_INFO("Invalid argument exception is expected (wOrigin3[2]+ outputHeight > inputHeight");
- BOOST_CHECK_THROW(RefSplitterWorkload(invalidData, invalidInfo), armnn::InvalidArgumentException);
+ INFO("Invalid argument exception is expected (wOrigin3[2]+ outputHeight > inputHeight");
+ CHECK_THROWS_AS(RefSplitterWorkload(invalidData, invalidInfo), armnn::InvalidArgumentException);
std::vector<unsigned int> wOrigin4 = {0, 0, 0, 0};
@@ -253,12 +252,12 @@
armnn::SplitterQueueDescriptor::ViewOrigin window5(wOrigin4);
invalidData.m_ViewOrigins.push_back(window5);
- BOOST_TEST_INFO("Invalid exception due to number of split windows not matching number of outputs.");
- BOOST_CHECK_THROW(RefSplitterWorkload(invalidData, invalidInfo), armnn::InvalidArgumentException);
+ INFO("Invalid exception due to number of split windows not matching number of outputs.");
+ CHECK_THROWS_AS(RefSplitterWorkload(invalidData, invalidInfo), armnn::InvalidArgumentException);
}
-BOOST_AUTO_TEST_CASE(ConcatQueueDescriptor_Validate_WrongWindow)
+TEST_CASE("ConcatQueueDescriptor_Validate_WrongWindow")
{
constexpr unsigned int inputNum = 1;
constexpr unsigned int inputChannels = 3;
@@ -291,16 +290,15 @@
armnn::ConcatQueueDescriptor::ViewOrigin window(wOrigin);
invalidData.m_ViewOrigins.push_back(window);
- BOOST_TEST_INFO("Invalid argument exception is expected, because merge window dimensionality does not "
- "match input.");
- BOOST_CHECK_THROW(RefConcatWorkload(invalidData, invalidInfo), armnn::InvalidArgumentException);
+ INFO("Invalid argument exception is expected, because merge window dimensionality does not match input.");
+ CHECK_THROWS_AS(RefConcatWorkload(invalidData, invalidInfo), armnn::InvalidArgumentException);
// Invalid, since window extends past the boundary of output tensor.
std::vector<unsigned int> wOrigin3 = {0, 0, 15, 0};
armnn::ConcatQueueDescriptor::ViewOrigin window3(wOrigin3);
invalidData.m_ViewOrigins[0] = window3;
- BOOST_TEST_INFO("Invalid argument exception is expected (wOrigin3[2]+ inputHeight > outputHeight");
- BOOST_CHECK_THROW(RefConcatWorkload(invalidData, invalidInfo), armnn::InvalidArgumentException);
+ INFO("Invalid argument exception is expected (wOrigin3[2]+ inputHeight > outputHeight");
+ CHECK_THROWS_AS(RefConcatWorkload(invalidData, invalidInfo), armnn::InvalidArgumentException);
std::vector<unsigned int> wOrigin4 = {0, 0, 0, 0};
@@ -311,11 +309,11 @@
armnn::ConcatQueueDescriptor::ViewOrigin window5(wOrigin4);
invalidData.m_ViewOrigins.push_back(window5);
- BOOST_TEST_INFO("Invalid exception due to number of merge windows not matching number of inputs.");
- BOOST_CHECK_THROW(RefConcatWorkload(invalidData, invalidInfo), armnn::InvalidArgumentException);
+ INFO("Invalid exception due to number of merge windows not matching number of inputs.");
+ CHECK_THROWS_AS(RefConcatWorkload(invalidData, invalidInfo), armnn::InvalidArgumentException);
}
-BOOST_AUTO_TEST_CASE(AdditionQueueDescriptor_Validate_InputNumbers)
+TEST_CASE("AdditionQueueDescriptor_Validate_InputNumbers")
{
armnn::TensorInfo input1TensorInfo;
armnn::TensorInfo input2TensorInfo;
@@ -336,20 +334,20 @@
AddOutputToWorkload(invalidData, invalidInfo, outputTensorInfo, nullptr);
// Too few inputs.
- BOOST_CHECK_THROW(RefAdditionWorkload<>(invalidData, invalidInfo), armnn::InvalidArgumentException);
+ CHECK_THROWS_AS(RefAdditionWorkload<>(invalidData, invalidInfo), armnn::InvalidArgumentException);
AddInputToWorkload(invalidData, invalidInfo, input2TensorInfo, nullptr);
// Correct.
- BOOST_CHECK_NO_THROW(RefAdditionWorkload<>(invalidData, invalidInfo));
+ CHECK_NOTHROW(RefAdditionWorkload<>(invalidData, invalidInfo));
AddInputToWorkload(invalidData, invalidInfo, input3TensorInfo, nullptr);
// Too many inputs.
- BOOST_CHECK_THROW(RefAdditionWorkload<>(invalidData, invalidInfo), armnn::InvalidArgumentException);
+ CHECK_THROWS_AS(RefAdditionWorkload<>(invalidData, invalidInfo), armnn::InvalidArgumentException);
}
-BOOST_AUTO_TEST_CASE(AdditionQueueDescriptor_Validate_InputShapes)
+TEST_CASE("AdditionQueueDescriptor_Validate_InputShapes")
{
armnn::TensorInfo input1TensorInfo;
armnn::TensorInfo input2TensorInfo;
@@ -371,7 +369,7 @@
AddInputToWorkload(invalidData, invalidInfo, input2TensorInfo, nullptr);
AddOutputToWorkload(invalidData, invalidInfo, outputTensorInfo, nullptr);
- BOOST_CHECK_THROW(RefAdditionWorkload<>(invalidData, invalidInfo), armnn::InvalidArgumentException);
+ CHECK_THROWS_AS(RefAdditionWorkload<>(invalidData, invalidInfo), armnn::InvalidArgumentException);
}
// Output size not compatible with input sizes.
@@ -388,11 +386,11 @@
AddOutputToWorkload(invalidData, invalidInfo, outputTensorInfo, nullptr);
// Output differs.
- BOOST_CHECK_THROW(RefAdditionWorkload<>(invalidData, invalidInfo), armnn::InvalidArgumentException);
+ CHECK_THROWS_AS(RefAdditionWorkload<>(invalidData, invalidInfo), armnn::InvalidArgumentException);
}
}
-BOOST_AUTO_TEST_CASE(MultiplicationQueueDescriptor_Validate_InputTensorDimensionMismatch)
+TEST_CASE("MultiplicationQueueDescriptor_Validate_InputTensorDimensionMismatch")
{
armnn::TensorInfo input0TensorInfo;
armnn::TensorInfo input1TensorInfo;
@@ -423,7 +421,7 @@
AddInputToWorkload(invalidData, invalidInfo, input0TensorInfo, nullptr);
AddInputToWorkload(invalidData, invalidInfo, input1TensorInfo, nullptr);
- BOOST_CHECK_THROW(RefMultiplicationWorkload<>(invalidData, invalidInfo), armnn::InvalidArgumentException);
+ CHECK_THROWS_AS(RefMultiplicationWorkload<>(invalidData, invalidInfo), armnn::InvalidArgumentException);
}
// Checks dimension consistency for input and output tensors.
@@ -448,11 +446,11 @@
AddInputToWorkload(invalidData, invalidInfo, input0TensorInfo, nullptr);
AddInputToWorkload(invalidData, invalidInfo, input1TensorInfo, nullptr);
- BOOST_CHECK_THROW(RefMultiplicationWorkload<>(invalidData, invalidInfo), armnn::InvalidArgumentException);
+ CHECK_THROWS_AS(RefMultiplicationWorkload<>(invalidData, invalidInfo), armnn::InvalidArgumentException);
}
}
-BOOST_AUTO_TEST_CASE(ReshapeQueueDescriptor_Validate_MismatchingNumElements)
+TEST_CASE("ReshapeQueueDescriptor_Validate_MismatchingNumElements")
{
armnn::TensorInfo inputTensorInfo;
armnn::TensorInfo outputTensorInfo;
@@ -471,11 +469,11 @@
AddOutputToWorkload(invalidData, invalidInfo, outputTensorInfo, nullptr);
// InvalidArgumentException is expected, because the number of elements don't match.
- BOOST_CHECK_THROW(RefReshapeWorkload(invalidData, invalidInfo), armnn::InvalidArgumentException);
+ CHECK_THROWS_AS(RefReshapeWorkload(invalidData, invalidInfo), armnn::InvalidArgumentException);
}
-BOOST_AUTO_TEST_CASE(LstmQueueDescriptor_Validate)
+TEST_CASE("LstmQueueDescriptor_Validate")
{
armnn::DataType dataType = armnn::DataType::Float32;
@@ -568,61 +566,61 @@
data.m_Parameters.m_LayerNormEnabled = true;
// check wrong number of outputs
- BOOST_CHECK_THROW(data.Validate(info), armnn::InvalidArgumentException);
+ CHECK_THROWS_AS(data.Validate(info), armnn::InvalidArgumentException);
AddOutputToWorkload(data, info, outputTensorInfo, nullptr);
// check wrong cifg parameter configuration
data.m_Parameters.m_CifgEnabled = true;
armnn::TensorInfo scratchBufferTensorInfo2({batchSize, numUnits * 3}, dataType, qScale, qOffset);
SetWorkloadOutput(data, info, 0, scratchBufferTensorInfo2, nullptr);
- BOOST_CHECK_THROW(data.Validate(info), armnn::InvalidArgumentException);
+ CHECK_THROWS_AS(data.Validate(info), armnn::InvalidArgumentException);
data.m_Parameters.m_CifgEnabled = false;
SetWorkloadOutput(data, info, 0, scratchBufferTensorInfo, nullptr);
// check wrong inputGateBias configuration
data.m_InputGateBias = nullptr;
- BOOST_CHECK_THROW(data.Validate(info), armnn::InvalidArgumentException);
+ CHECK_THROWS_AS(data.Validate(info), armnn::InvalidArgumentException);
data.m_InputGateBias = &inputGateBiasTensor;
// check inconsistant projection parameters
data.m_Parameters.m_ProjectionEnabled = false;
- BOOST_CHECK_THROW(data.Validate(info), armnn::InvalidArgumentException);
+ CHECK_THROWS_AS(data.Validate(info), armnn::InvalidArgumentException);
data.m_Parameters.m_ProjectionEnabled = true;
data.m_ProjectionWeights = nullptr;
- BOOST_CHECK_THROW(data.Validate(info), armnn::InvalidArgumentException);
+ CHECK_THROWS_AS(data.Validate(info), armnn::InvalidArgumentException);
data.m_ProjectionWeights = &projectionWeightsTensor;
// check missing input layer normalisation weights
data.m_InputLayerNormWeights = nullptr;
- BOOST_CHECK_THROW(data.Validate(info), armnn::InvalidArgumentException);
+ CHECK_THROWS_AS(data.Validate(info), armnn::InvalidArgumentException);
data.m_InputLayerNormWeights = &inputLayerNormWeightsTensor;
// layer norm disabled but normalisation weights are present
data.m_Parameters.m_LayerNormEnabled = false;
- BOOST_CHECK_THROW(data.Validate(info), armnn::InvalidArgumentException);
+ CHECK_THROWS_AS(data.Validate(info), armnn::InvalidArgumentException);
data.m_Parameters.m_LayerNormEnabled = true;
// check invalid outputTensor shape
armnn::TensorInfo incorrectOutputTensorInfo({batchSize, outputSize + 1}, dataType, qScale, qOffset);
SetWorkloadOutput(data, info, 3, incorrectOutputTensorInfo, nullptr);
- BOOST_CHECK_THROW(data.Validate(info), armnn::InvalidArgumentException);
+ CHECK_THROWS_AS(data.Validate(info), armnn::InvalidArgumentException);
SetWorkloadOutput(data, info, 3, outputTensorInfo, nullptr);
// check invalid cell clipping parameters
data.m_Parameters.m_ClippingThresCell = -1.0f;
- BOOST_CHECK_THROW(data.Validate(info), armnn::InvalidArgumentException);
+ CHECK_THROWS_AS(data.Validate(info), armnn::InvalidArgumentException);
data.m_Parameters.m_ClippingThresCell = 0.0f;
// check invalid projection clipping parameters
data.m_Parameters.m_ClippingThresProj = -1.0f;
- BOOST_CHECK_THROW(data.Validate(info), armnn::InvalidArgumentException);
+ CHECK_THROWS_AS(data.Validate(info), armnn::InvalidArgumentException);
data.m_Parameters.m_ClippingThresProj = 0.0f;
// check correct configuration
- BOOST_CHECK_NO_THROW(data.Validate(info));
+ CHECK_NOTHROW(data.Validate(info));
}
-BOOST_AUTO_TEST_CASE(BiasPerAxisQuantization_Validate)
+TEST_CASE("BiasPerAxisQuantization_Validate")
{
constexpr unsigned int nInput = 1u;
constexpr unsigned int cInput = 3u;
@@ -667,7 +665,7 @@
ScopedTensorHandle biasHandle1(biasInfo1);
queueDescriptor.m_Bias = &biasHandle1;
- BOOST_CHECK_NO_THROW(queueDescriptor.Validate(workloadInfo));
+ CHECK_NOTHROW(queueDescriptor.Validate(workloadInfo));
// Test 2: wrong per-axis quantization values
const std::vector<float> biasPerAxisScales2 = { 4.00f, 5.00f };
@@ -676,7 +674,7 @@
ScopedTensorHandle biasHandle2(biasInfo2);
queueDescriptor.m_Bias = &biasHandle2;
- BOOST_CHECK_NO_THROW(queueDescriptor.Validate(workloadInfo));
+ CHECK_NOTHROW(queueDescriptor.Validate(workloadInfo));
// Test 3: mismatched number of quantization scales
const std::vector<float> biasPerAxisScales3 = { 3.75f, 5.25f, 5.25f };
@@ -685,7 +683,7 @@
ScopedTensorHandle biasHandle3(biasInfo3);
queueDescriptor.m_Bias = &biasHandle3;
- BOOST_CHECK_THROW(queueDescriptor.Validate(workloadInfo), InvalidArgumentException);
+ CHECK_THROWS_AS(queueDescriptor.Validate(workloadInfo), InvalidArgumentException);
}
-BOOST_AUTO_TEST_SUITE_END()
+}