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Diffstat (limited to 'src/backends/tosaCommon/test/OneToOneMappingTests.cpp')
-rw-r--r--src/backends/tosaCommon/test/OneToOneMappingTests.cpp136
1 files changed, 129 insertions, 7 deletions
diff --git a/src/backends/tosaCommon/test/OneToOneMappingTests.cpp b/src/backends/tosaCommon/test/OneToOneMappingTests.cpp
index 04d1eb46aa..af9f9e26df 100644
--- a/src/backends/tosaCommon/test/OneToOneMappingTests.cpp
+++ b/src/backends/tosaCommon/test/OneToOneMappingTests.cpp
@@ -4,6 +4,7 @@
//
#include "TosaTestUtils.hpp"
+#include "CommonTestUtils.hpp"
using namespace armnn;
using namespace tosa;
@@ -18,7 +19,7 @@ TEST_CASE("GetTosaMapping_AdditionLayer")
std::vector<std::vector<int32_t>> outputShape = {{ 1, 2, 4, 2 }};
TosaSerializationBasicBlock* basicBlock =
- GetTosaMapping(LayerType::Addition, {&info, &info}, {&info}, BaseDescriptor(), false);
+ GetTosaMapping(nullptr, LayerType::Addition, {&info, &info}, {&info}, BaseDescriptor());
AssertTosaOneToOneMappingBasicBlock(
basicBlock, inputShape, outputShape, Op_ADD, Attribute_NONE, BaseDescriptor(), LayerType::Addition);
}
@@ -50,11 +51,132 @@ TEST_CASE("GetTosaMappingFromLayer_AdditionLayer")
std::vector<std::vector<int32_t>> outputShape = {{ 1, 2, 4, 2 }};
TosaSerializationBasicBlock* basicBlock =
- GetTosaMappingFromLayer(PolymorphicDowncast<Layer*>(add), false);
+ GetTosaMappingFromLayer(PolymorphicDowncast<Layer*>(add));
AssertTosaOneToOneMappingBasicBlock(
basicBlock, inputShape, outputShape, Op_ADD, Attribute_NONE, BaseDescriptor(), LayerType::Addition);
}
+TEST_CASE("GetTosaMapping_ConstantLayer")
+{
+ TensorInfo outputInfo = TensorInfo({ 1, 2, 4, 2 }, DataType::Float32, 0.0f, 0, true);
+ std::vector<std::vector<int32_t>> outputShape = {{ 1, 2, 4, 2 }};
+
+ TosaSerializationBasicBlock* basicBlock =
+ GetTosaMapping(nullptr, LayerType::Constant, {}, {&outputInfo}, BaseDescriptor());
+ AssertTosaOneToOneMappingBasicBlock(
+ basicBlock, {}, outputShape, Op_CONST, Attribute_NONE, BaseDescriptor(), LayerType::Constant);
+}
+
+TEST_CASE("GetTosaMappingFromLayer_ConstantLayer")
+{
+ IRuntime::CreationOptions options;
+ IRuntimePtr runtime(IRuntime::Create(options));
+
+ // Builds up the structure of the network.
+ INetworkPtr net(INetwork::Create());
+
+ TensorInfo info = TensorInfo({ 1, 2, 4, 2 }, DataType::Float32, 0.0f, 0, true);
+ std::vector<std::vector<int32_t>> outputShape = {{ 1, 2, 4, 2 }};
+
+ std::vector<float> data = GenerateRandomData<float>(info.GetNumElements());
+ armnn::ConstTensor constTensor(info, data);
+
+ IConnectableLayer* constant = net->AddConstantLayer(constTensor, "constant");
+ IConnectableLayer* output = net->AddOutputLayer(0, "output");
+
+ constant->GetOutputSlot(0).Connect(output->GetInputSlot(0));
+ constant->GetOutputSlot(0).SetTensorInfo(info);
+
+ TosaSerializationBasicBlock* basicBlock =
+ GetTosaMappingFromLayer(PolymorphicDowncast<Layer*>(constant));
+ AssertTosaOneToOneMappingBasicBlock(
+ basicBlock, {}, outputShape, Op_CONST, Attribute_NONE, BaseDescriptor(), LayerType::Constant);
+}
+
+TEST_CASE("GetTosaMapping_Conv2dLayer")
+{
+ armnn::Convolution2dDescriptor descriptor;
+ descriptor.m_PadLeft = 1;
+ descriptor.m_PadRight = 1;
+ descriptor.m_PadTop = 1;
+ descriptor.m_PadBottom = 1;
+ descriptor.m_StrideX = 2;
+ descriptor.m_StrideY = 2;
+ descriptor.m_DilationX = 2;
+ descriptor.m_DilationY = 2;
+ descriptor.m_BiasEnabled = true;
+
+ const armnn::TensorInfo inputInfo ({ 1, 5, 5, 1 }, armnn::DataType::Float32);
+ const armnn::TensorInfo outputInfo({ 1, 3, 3, 1 }, armnn::DataType::Float32);
+ const armnn::TensorInfo weightsInfo({ 1, 3, 3, 1 }, armnn::DataType::Float32, 0.0f, 0, true);
+ const armnn::TensorInfo biasesInfo ({ 1 }, armnn::DataType::Float32, 0.0f, 0, true);
+
+ std::vector<std::vector<int32_t>> inputShape = {{ 1, 5, 5, 1 }, { 1, 3, 3, 1 }, { 1 }};
+ std::vector<std::vector<int32_t>> outputShape = {{ 1, 3, 3, 1 }};
+
+ TosaSerializationBasicBlock* basicBlock = GetTosaMapping(nullptr,
+ LayerType::Convolution2d,
+ {&inputInfo, &weightsInfo, &biasesInfo},
+ {&outputInfo},
+ descriptor);
+ AssertTosaOneToOneMappingBasicBlock(
+ basicBlock, inputShape, outputShape, Op_CONV2D, Attribute_ConvAttribute, descriptor, LayerType::Convolution2d);
+}
+
+TEST_CASE("GetTosaMappingFromLayer_Conv2dLayer")
+{
+ IRuntime::CreationOptions options;
+ IRuntimePtr runtime(IRuntime::Create(options));
+
+ // Builds up the structure of the network.
+ INetworkPtr net(INetwork::Create());
+
+ armnn::Convolution2dDescriptor descriptor;
+ descriptor.m_PadLeft = 1;
+ descriptor.m_PadRight = 1;
+ descriptor.m_PadTop = 1;
+ descriptor.m_PadBottom = 1;
+ descriptor.m_StrideX = 2;
+ descriptor.m_StrideY = 2;
+ descriptor.m_DilationX = 2;
+ descriptor.m_DilationY = 2;
+ descriptor.m_BiasEnabled = true;
+
+ const armnn::TensorInfo inputInfo ({ 1, 5, 5, 1 }, armnn::DataType::Float32);
+ const armnn::TensorInfo outputInfo({ 1, 3, 3, 1 }, armnn::DataType::Float32);
+ const armnn::TensorInfo weightsInfo({ 1, 3, 3, 1 }, armnn::DataType::Float32, 0.0f, 0, true);
+ const armnn::TensorInfo biasesInfo ({ 1 }, armnn::DataType::Float32, 0.0f, 0, true);
+
+ std::vector<std::vector<int32_t>> inputShape = {{ 1, 5, 5, 1 }};
+ std::vector<std::vector<int32_t>> outputShape = {{ 1, 3, 3, 1 }};
+
+ std::vector<float> weightsData = GenerateRandomData<float>(weightsInfo.GetNumElements());
+ armnn::ConstTensor weights(weightsInfo, weightsData);
+
+ std::vector<float> biasesData = GenerateRandomData<float>(biasesInfo.GetNumElements());
+ armnn::ConstTensor biases(biasesInfo, biasesData);
+
+ armnn::IConnectableLayer* const inputLayer = net->AddInputLayer(0, "input0");
+ armnn::IConnectableLayer* const weightsLayer = net->AddConstantLayer(weights, "weights");
+ armnn::IConnectableLayer* const biasesLayer = net->AddConstantLayer(biases, "biases");
+ armnn::IConnectableLayer* const convLayer = net->AddConvolution2dLayer(descriptor, "conv2d");
+ armnn::IConnectableLayer* const outputLayer = net->AddOutputLayer(0);
+
+ inputLayer->GetOutputSlot(0).Connect(convLayer->GetInputSlot(0));
+ weightsLayer->GetOutputSlot(0).Connect(convLayer->GetInputSlot(1));
+ biasesLayer->GetOutputSlot(0).Connect(convLayer->GetInputSlot(2));
+ convLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
+
+ inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo);
+ weightsLayer->GetOutputSlot(0).SetTensorInfo(weightsInfo);
+ biasesLayer->GetOutputSlot(0).SetTensorInfo(biasesInfo);
+ convLayer->GetOutputSlot(0).SetTensorInfo(outputInfo);
+
+ TosaSerializationBasicBlock* basicBlock = GetTosaMappingFromLayer(PolymorphicDowncast<Layer*>(convLayer));
+ AssertTosaOneToOneMappingBasicBlock(
+ basicBlock, inputShape, outputShape, Op_CONV2D, Attribute_ConvAttribute, descriptor, LayerType::Convolution2d);
+}
+
TEST_CASE("GetTosaMapping_MaxPool2DLayer")
{
armnn::Pooling2dDescriptor descriptor;
@@ -74,7 +196,7 @@ TEST_CASE("GetTosaMapping_MaxPool2DLayer")
std::vector<std::vector<int32_t>> outputShape = {{ 1, 1, 3, 3 }};
TosaSerializationBasicBlock* basicBlock =
- GetTosaMapping(LayerType::Pooling2d, {&inputTensorInfo}, {&outputTensorInfo}, descriptor, false);
+ GetTosaMapping(nullptr, LayerType::Pooling2d, {&inputTensorInfo}, {&outputTensorInfo}, descriptor);
AssertTosaOneToOneMappingBasicBlock(
basicBlock, inputShape, outputShape, Op_MAX_POOL2D, Attribute_PoolAttribute, descriptor, LayerType::Pooling2d);
}
@@ -114,7 +236,7 @@ TEST_CASE("GetTosaMappingFromLayer_MaxPool2DLayer")
pool->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
TosaSerializationBasicBlock* basicBlock =
- GetTosaMappingFromLayer(PolymorphicDowncast<Layer*>(pool), false);
+ GetTosaMappingFromLayer(PolymorphicDowncast<Layer*>(pool));
AssertTosaOneToOneMappingBasicBlock(
basicBlock, inputShape, outputShape, Op_MAX_POOL2D, Attribute_PoolAttribute, descriptor, LayerType::Pooling2d);
}
@@ -138,7 +260,7 @@ TEST_CASE("GetTosaMapping_AvgPool2DLayer")
std::vector<std::vector<int32_t>> outputShape = {{ 1, 1, 3, 3 }};
TosaSerializationBasicBlock* basicBlock =
- GetTosaMapping(LayerType::Pooling2d, {&inputTensorInfo}, {&outputTensorInfo}, descriptor, false);
+ GetTosaMapping(nullptr, LayerType::Pooling2d, {&inputTensorInfo}, {&outputTensorInfo}, descriptor);
AssertTosaOneToOneMappingBasicBlock(basicBlock,
inputShape,
outputShape,
@@ -183,7 +305,7 @@ TEST_CASE("GetTosaMappingFromLayer_AvgPool2DLayer")
pool->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
TosaSerializationBasicBlock* basicBlock =
- GetTosaMappingFromLayer(PolymorphicDowncast<Layer*>(pool), false);
+ GetTosaMappingFromLayer(PolymorphicDowncast<Layer*>(pool));
AssertTosaOneToOneMappingBasicBlock(basicBlock,
inputShape,
outputShape,
@@ -196,7 +318,7 @@ TEST_CASE("GetTosaMappingFromLayer_AvgPool2DLayer")
TEST_CASE("GetTosaMapping_Unimplemented")
{
TosaSerializationBasicBlock* basicBlock =
- GetTosaMapping(LayerType::UnidirectionalSequenceLstm, {}, {}, BaseDescriptor(), false);
+ GetTosaMapping(nullptr, LayerType::UnidirectionalSequenceLstm, {}, {}, BaseDescriptor());
CHECK(basicBlock->GetName() == "");
CHECK(basicBlock->GetTensors().size() == 0);
generated by cgit v1.2.1 (git 2.23.0) at 2024-06-07 09:17:36 +0000