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Diffstat (limited to 'src/armnn/test/OptimizerTests.cpp')
-rw-r--r--src/armnn/test/OptimizerTests.cpp108
1 files changed, 55 insertions, 53 deletions
diff --git a/src/armnn/test/OptimizerTests.cpp b/src/armnn/test/OptimizerTests.cpp
index 7fe69a9380..e68546c9dd 100644
--- a/src/armnn/test/OptimizerTests.cpp
+++ b/src/armnn/test/OptimizerTests.cpp
@@ -15,6 +15,7 @@
#include <armnn/INetwork.hpp>
#include <armnn/LayerVisitorBase.hpp>
+#include <armnn/utility/Assert.hpp>
#include <armnn/utility/PolymorphicDowncast.hpp>
#include <armnnUtils/FloatingPointConverter.hpp>
@@ -22,7 +23,7 @@
#include <backendsCommon/LayerSupportBase.hpp>
#include <backendsCommon/TensorHandle.hpp>
-#include <boost/test/unit_test.hpp>
+#include <doctest/doctest.h>
using namespace armnn;
@@ -140,10 +141,11 @@ void CreateLSTMLayerHelper(Graph &graph, bool CifgEnabled)
} // namespace
-BOOST_AUTO_TEST_SUITE(Optimizer)
+TEST_SUITE("Optimizer")
+{
using namespace armnn::optimizations;
-BOOST_AUTO_TEST_CASE(LSTMValidateTensorShapesFromInputsCIFGDisabledTest)
+TEST_CASE("LSTMValidateTensorShapesFromInputsCIFGDisabledTest")
{
Graph graph;
@@ -151,10 +153,10 @@ BOOST_AUTO_TEST_CASE(LSTMValidateTensorShapesFromInputsCIFGDisabledTest)
CreateLSTMLayerHelper(graph, false);
//This function used to call ValidateShapesFromInputs();
- BOOST_CHECK_NO_THROW(graph.InferTensorInfos());
+ CHECK_NOTHROW(graph.InferTensorInfos());
}
-BOOST_AUTO_TEST_CASE(LSTMValidateTensorShapesFromInputsCIFGEnabledTest)
+TEST_CASE("LSTMValidateTensorShapesFromInputsCIFGEnabledTest")
{
Graph graph;
@@ -162,10 +164,10 @@ BOOST_AUTO_TEST_CASE(LSTMValidateTensorShapesFromInputsCIFGEnabledTest)
CreateLSTMLayerHelper(graph, true);
//This function used to call ValidateShapesFromInputs();
- BOOST_CHECK_NO_THROW(graph.InferTensorInfos());
+ CHECK_NOTHROW(graph.InferTensorInfos());
}
-BOOST_AUTO_TEST_CASE(InsertConvertersTest)
+TEST_CASE("InsertConvertersTest")
{
const armnn::TensorInfo info({ 1, 5, 2, 3 }, armnn::DataType::Float16);
@@ -191,7 +193,7 @@ BOOST_AUTO_TEST_CASE(InsertConvertersTest)
->GetOutputHandler().SetTensorInfo(info);
// Check graph layer sequence before inserting convert layers
- BOOST_TEST(CheckSequence(graph.cbegin(),
+ CHECK(CheckSequence(graph.cbegin(),
graph.cend(),
&IsLayerOfType<armnn::InputLayer>,
&IsLayerOfType<armnn::InputLayer>,
@@ -241,7 +243,7 @@ BOOST_AUTO_TEST_CASE(InsertConvertersTest)
}
// Check sequence of layers after inserting convert layers
- BOOST_TEST(CheckSequence(graph.cbegin(),
+ CHECK(CheckSequence(graph.cbegin(),
graph.cend(),
&IsLayerOfType<armnn::InputLayer>,
&IsLayerOfType<armnn::InputLayer>,
@@ -284,7 +286,7 @@ void CreateConvolution2dGraph(Graph &graph, const unsigned int* inputShape,
layer->GetOutputSlot().Connect(output->GetInputSlot(0));
}
-BOOST_AUTO_TEST_CASE(Conv2dValidateTensorShapesFromInputs)
+TEST_CASE("Conv2dValidateTensorShapesFromInputs")
{
Graph graph;
const unsigned int inputShape[] = { 1, 3, 8, 16 };
@@ -292,10 +294,10 @@ BOOST_AUTO_TEST_CASE(Conv2dValidateTensorShapesFromInputs)
const unsigned int outputShape[] = { 1, 2, 4, 14 };
CreateConvolution2dGraph(graph, inputShape, weightsShape, outputShape);
- BOOST_CHECK_NO_THROW(graph.InferTensorInfos());
+ CHECK_NOTHROW(graph.InferTensorInfos());
}
-BOOST_AUTO_TEST_CASE(Conv2dValidateTensorShapesFromInputsNhwc)
+TEST_CASE("Conv2dValidateTensorShapesFromInputsNhwc")
{
Graph graph;
const unsigned int inputShape[] = { 1, 8, 16, 3 };
@@ -303,7 +305,7 @@ BOOST_AUTO_TEST_CASE(Conv2dValidateTensorShapesFromInputsNhwc)
const unsigned int outputShape[] = { 1, 4, 14, 2 };
CreateConvolution2dGraph(graph, inputShape, weightsShape, outputShape, DataLayout::NHWC);
- BOOST_CHECK_NO_THROW(graph.InferTensorInfos());
+ CHECK_NOTHROW(graph.InferTensorInfos());
}
void CreateDepthwiseConvolution2dGraph(Graph &graph, const unsigned int* inputShape,
@@ -334,7 +336,7 @@ void CreateDepthwiseConvolution2dGraph(Graph &graph, const unsigned int* inputSh
layer->GetOutputSlot().Connect(output->GetInputSlot(0));
}
-BOOST_AUTO_TEST_CASE(DepthwiseConv2dValidateTensorShapesFromInputs)
+TEST_CASE("DepthwiseConv2dValidateTensorShapesFromInputs")
{
Graph graph;
const unsigned int inputShape[] = { 1, 2, 3, 3 };
@@ -342,10 +344,10 @@ BOOST_AUTO_TEST_CASE(DepthwiseConv2dValidateTensorShapesFromInputs)
const unsigned int outputShape[] = { 1, 2, 1, 1 };
CreateDepthwiseConvolution2dGraph(graph, inputShape, weightsShape, outputShape);
- BOOST_CHECK_NO_THROW(graph.InferTensorInfos());
+ CHECK_NOTHROW(graph.InferTensorInfos());
}
-BOOST_AUTO_TEST_CASE(DepthwiseConv2dValidateTensorShapesFromInputsNhwc)
+TEST_CASE("DepthwiseConv2dValidateTensorShapesFromInputsNhwc")
{
Graph graph;
const unsigned int inputShape[] = { 1, 3, 3, 2 };
@@ -353,7 +355,7 @@ BOOST_AUTO_TEST_CASE(DepthwiseConv2dValidateTensorShapesFromInputsNhwc)
const unsigned int outputShape[] = { 1, 1, 1, 2 };
CreateDepthwiseConvolution2dGraph(graph, inputShape, weightsShape, outputShape, DataLayout::NHWC);
- BOOST_CHECK_NO_THROW(graph.InferTensorInfos());
+ CHECK_NOTHROW(graph.InferTensorInfos());
}
void CreatePooling2dGraph(Graph& graph, const unsigned int* inputShape, const unsigned int* outputShape,
@@ -384,24 +386,24 @@ void CreatePooling2dGraph(Graph& graph, const unsigned int* inputShape, const u
layer->GetOutputSlot().Connect(output->GetInputSlot(0));
}
-BOOST_AUTO_TEST_CASE(Pooling2dValidateTensorShapesFromInputs)
+TEST_CASE("Pooling2dValidateTensorShapesFromInputs")
{
Graph graph;
const unsigned int inputShape[] = { 5, 3, 52, 60 };
const unsigned int outputShape[] = { 5, 3, 11, 13 };
CreatePooling2dGraph(graph, inputShape, outputShape, DataLayout::NCHW);
- BOOST_CHECK_NO_THROW(graph.InferTensorInfos());
+ CHECK_NOTHROW(graph.InferTensorInfos());
}
-BOOST_AUTO_TEST_CASE(Pooling2dValidateTensorShapesFromInputsNhwc)
+TEST_CASE("Pooling2dValidateTensorShapesFromInputsNhwc")
{
Graph graph;
const unsigned int inputShape[] = { 5, 52, 60, 3 };
const unsigned int outputShape[] = { 5, 11, 13, 3 };
CreatePooling2dGraph(graph, inputShape, outputShape, DataLayout::NHWC);
- BOOST_CHECK_NO_THROW(graph.InferTensorInfos());
+ CHECK_NOTHROW(graph.InferTensorInfos());
}
void CreateResizeBilinearGraph(Graph& graph,
@@ -429,24 +431,24 @@ void CreateResizeBilinearGraph(Graph& graph,
layer->GetOutputSlot().Connect(output->GetInputSlot(0));
}
-BOOST_AUTO_TEST_CASE(ResizeBilinearValidateTensorShapesFromInputs)
+TEST_CASE("ResizeBilinearValidateTensorShapesFromInputs")
{
Graph graph;
const unsigned int inputShape[] = { 1, 2, 4, 5 };
const unsigned int outputShape[] = { 1, 2, 3, 4 };
CreateResizeBilinearGraph(graph, inputShape, outputShape);
- BOOST_CHECK_NO_THROW(graph.InferTensorInfos());
+ CHECK_NOTHROW(graph.InferTensorInfos());
}
-BOOST_AUTO_TEST_CASE(ResizeBilinearValidateTensorShapesFromInputsNhwc)
+TEST_CASE("ResizeBilinearValidateTensorShapesFromInputsNhwc")
{
Graph graph;
const unsigned int inputShape[] = { 1, 4, 5, 2 };
const unsigned int outputShape[] = { 1, 3, 4, 2 };
CreateResizeBilinearGraph(graph, inputShape, outputShape, DataLayout::NHWC);
- BOOST_CHECK_NO_THROW(graph.InferTensorInfos());
+ CHECK_NOTHROW(graph.InferTensorInfos());
}
void CreateGatherGraph(Graph& graph,
@@ -470,7 +472,7 @@ void CreateGatherGraph(Graph& graph,
layer->GetOutputSlot().Connect(output->GetInputSlot(0));
}
-BOOST_AUTO_TEST_CASE(GatherValidateTensorShapesFromInputs)
+TEST_CASE("GatherValidateTensorShapesFromInputs")
{
Graph graph;
armnn::TensorInfo paramsInfo({10, 5}, DataType::Float32);
@@ -479,10 +481,10 @@ BOOST_AUTO_TEST_CASE(GatherValidateTensorShapesFromInputs)
CreateGatherGraph(graph, paramsInfo, indicesInfo, outputInfo);
- BOOST_CHECK_NO_THROW(graph.InferTensorInfos());
+ CHECK_NOTHROW(graph.InferTensorInfos());
}
-BOOST_AUTO_TEST_CASE(GatherValidateTensorShapesFromInputs1DParams)
+TEST_CASE("GatherValidateTensorShapesFromInputs1DParams")
{
Graph graph;
armnn::TensorInfo paramsInfo({8}, DataType::Float32);
@@ -491,10 +493,10 @@ BOOST_AUTO_TEST_CASE(GatherValidateTensorShapesFromInputs1DParams)
CreateGatherGraph(graph, paramsInfo, indicesInfo, outputInfo);
- BOOST_CHECK_NO_THROW(graph.InferTensorInfos());
+ CHECK_NOTHROW(graph.InferTensorInfos());
}
-BOOST_AUTO_TEST_CASE(GatherValidateTensorShapesFromInputsMultiDimIndices)
+TEST_CASE("GatherValidateTensorShapesFromInputsMultiDimIndices")
{
Graph graph;
armnn::TensorInfo paramsInfo({3, 2, 5}, DataType::Float32);
@@ -503,10 +505,10 @@ BOOST_AUTO_TEST_CASE(GatherValidateTensorShapesFromInputsMultiDimIndices)
CreateGatherGraph(graph, paramsInfo, indicesInfo, outputInfo);
- BOOST_CHECK_NO_THROW(graph.InferTensorInfos());
+ CHECK_NOTHROW(graph.InferTensorInfos());
}
-BOOST_AUTO_TEST_CASE(DetectionPostProcessValidateTensorShapes)
+TEST_CASE("DetectionPostProcessValidateTensorShapes")
{
Graph graph;
armnn::TensorInfo boxEncodingsInfo({1, 10, 4}, DataType::QAsymmU8);
@@ -538,7 +540,7 @@ BOOST_AUTO_TEST_CASE(DetectionPostProcessValidateTensorShapes)
input0->GetOutputSlot().Connect(layer->GetInputSlot(0));
input1->GetOutputSlot().Connect(layer->GetInputSlot(1));
- BOOST_CHECK_NO_THROW(graph.InferTensorInfos());
+ CHECK_NOTHROW(graph.InferTensorInfos());
}
class MockLayerSupport : public LayerSupportBase
@@ -612,21 +614,21 @@ public:
};
};
-BOOST_AUTO_TEST_CASE(BackendCapabilityTest)
+TEST_CASE("BackendCapabilityTest")
{
BackendId backendId = "MockBackend";
armnn::BackendOptions::BackendOption nonConstWeights{"NonConstWeights", true};
// MockBackend does not support the NonConstWeights capability
- BOOST_CHECK(!armnn::HasCapability(nonConstWeights, backendId));
- BOOST_CHECK(!armnn::HasCapability("NonConstWeights", backendId));
+ CHECK(!armnn::HasCapability(nonConstWeights, backendId));
+ CHECK(!armnn::HasCapability("NonConstWeights", backendId));
// MockBackend does not support the AsyncExecution capability
- BOOST_CHECK(!armnn::GetCapability("AsyncExecution", backendId).has_value());
+ CHECK(!armnn::GetCapability("AsyncExecution", backendId).has_value());
}
-BOOST_AUTO_TEST_CASE(BackendHintTest)
+TEST_CASE("BackendHintTest")
{
class TestBackendAssignment : public LayerVisitorBase<VisitorNoThrowPolicy>
{
@@ -635,14 +637,14 @@ BOOST_AUTO_TEST_CASE(BackendHintTest)
{
IgnoreUnused(id, name);
auto inputLayer = PolymorphicDowncast<const InputLayer*>(layer);
- BOOST_TEST((inputLayer->GetBackendId() == "MockBackend"));
+ CHECK((inputLayer->GetBackendId() == "MockBackend"));
}
void VisitOutputLayer(const IConnectableLayer* layer, LayerBindingId id, const char* name = nullptr) override
{
IgnoreUnused(id, name);
auto outputLayer = PolymorphicDowncast<const OutputLayer*>(layer);
- BOOST_TEST((outputLayer->GetBackendId() == "MockBackend"));
+ CHECK((outputLayer->GetBackendId() == "MockBackend"));
}
void VisitActivationLayer(const IConnectableLayer* layer,
@@ -651,7 +653,7 @@ BOOST_AUTO_TEST_CASE(BackendHintTest)
{
IgnoreUnused(activationDescriptor, name);
auto activation = PolymorphicDowncast<const ActivationLayer*>(layer);
- BOOST_TEST((activation->GetBackendId() == "CustomBackend"));
+ CHECK((activation->GetBackendId() == "CustomBackend"));
}
};
@@ -718,7 +720,7 @@ BOOST_AUTO_TEST_CASE(BackendHintTest)
lastLayer,
EmptyOptional());
- BOOST_TEST(res.IsOk());
+ CHECK(res.IsOk());
TestBackendAssignment visitor;
for (auto it = firstLayer; it != lastLayer; ++it)
@@ -728,7 +730,7 @@ BOOST_AUTO_TEST_CASE(BackendHintTest)
}
// Tests that OptimizeForExclusiveConnections works, fusing when needed, using BatchNorm fusing as example
-BOOST_AUTO_TEST_CASE(OptimizeForExclusiveConnectionsFuseTest)
+TEST_CASE("OptimizeForExclusiveConnectionsFuseTest")
{
using namespace armnn;
// Define layers information
@@ -786,8 +788,8 @@ BOOST_AUTO_TEST_CASE(OptimizeForExclusiveConnectionsFuseTest)
conv->GetOutputSlot(0).Connect(batchNorm->GetInputSlot(0));
batchNorm->GetOutputSlot(0).Connect(output->GetInputSlot(0));
- BOOST_CHECK(4 == graph.GetNumLayers());
- BOOST_TEST(CheckSequence(graph.cbegin(), graph.cend(),
+ CHECK(4 == graph.GetNumLayers());
+ CHECK(CheckSequence(graph.cbegin(), graph.cend(),
&IsLayerOfType<InputLayer>,
&IsLayerOfType<Convolution2dLayer>,
&IsLayerOfType<BatchNormalizationLayer>,
@@ -801,15 +803,15 @@ BOOST_AUTO_TEST_CASE(OptimizeForExclusiveConnectionsFuseTest)
(layer->GetNameStr() == "fused-batchNorm-into-convolution");
};
- BOOST_CHECK(3 == graph.GetNumLayers());
- BOOST_TEST(CheckSequence(graph.cbegin(), graph.cend(),
+ CHECK(3 == graph.GetNumLayers());
+ CHECK(CheckSequence(graph.cbegin(), graph.cend(),
&IsLayerOfType<InputLayer>,
checkFusedConv2d,
&IsLayerOfType<OutputLayer>));
}
// Tests that OptimizeForExclusiveConnections works, not fusing when not needed, using BatchNorm fusing as example
-BOOST_AUTO_TEST_CASE(OptimizeForExclusiveConnectionsWithoutFuseTest)
+TEST_CASE("OptimizeForExclusiveConnectionsWithoutFuseTest")
{
// Define the network
Graph graph;
@@ -828,8 +830,8 @@ BOOST_AUTO_TEST_CASE(OptimizeForExclusiveConnectionsWithoutFuseTest)
batchNorm->GetOutputSlot(0).Connect(output->GetInputSlot(0));
conv->GetOutputSlot(0).Connect(output2->GetInputSlot(0));
- BOOST_CHECK(5 == graph.GetNumLayers());
- BOOST_TEST(CheckSequence(graph.cbegin(), graph.cend(),
+ CHECK(5 == graph.GetNumLayers());
+ CHECK(CheckSequence(graph.cbegin(), graph.cend(),
&IsLayerOfType<armnn::InputLayer>,
&IsLayerOfType<armnn::Convolution2dLayer>,
&IsLayerOfType<armnn::BatchNormalizationLayer>,
@@ -838,12 +840,12 @@ BOOST_AUTO_TEST_CASE(OptimizeForExclusiveConnectionsWithoutFuseTest)
// Optimize graph
armnn::Optimizer::Pass(graph, armnn::MakeOptimizations(FuseBatchNormIntoConvolution2DFloat32()));
- BOOST_CHECK(5 == graph.GetNumLayers());
- BOOST_TEST(CheckSequence(graph.cbegin(), graph.cend(),
+ CHECK(5 == graph.GetNumLayers());
+ CHECK(CheckSequence(graph.cbegin(), graph.cend(),
&IsLayerOfType<armnn::InputLayer>,
&IsLayerOfType<armnn::Convolution2dLayer>,
&IsLayerOfType<armnn::BatchNormalizationLayer>,
&IsLayerOfType<armnn::OutputLayer>,
&IsLayerOfType<armnn::OutputLayer>));
}
-BOOST_AUTO_TEST_SUITE_END()
+}
generated by cgit v1.2.1 (git 2.23.0) at 2024-06-14 00:42:09 +0000