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//
// Copyright © 2022-2024 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
#include "AvgPool2DIgnoreValueChecker.hpp"
#include "QuantizeChecker.hpp"
#include "SplitChecker.hpp"
#include <backendsCommon/test/ActivationEndToEndTestImpl.hpp>
#include <armnn/IRuntime.hpp>
using namespace armnn;
using namespace tosa;
TEST_SUITE("TosaOperatorMappingOneToManyTests")
{
TEST_CASE("GetTosaMapping_AvgPool2DIgnoreValueLayer")
{
armnn::Pooling2dDescriptor descriptor;
descriptor.m_PoolType = armnn::PoolingAlgorithm::Average;
descriptor.m_PoolWidth = descriptor.m_PoolHeight = 2;
descriptor.m_StrideX = descriptor.m_StrideY = 2;
descriptor.m_PadLeft = 1;
descriptor.m_PadRight = 1;
descriptor.m_PadTop = 1;
descriptor.m_PadBottom = 1;
descriptor.m_PaddingMethod = armnn::PaddingMethod::IgnoreValue;
armnn::TensorInfo inputTensorInfo({ 1, 1, 4, 4 }, DataType::Float32);
armnn::TensorInfo outputTensorInfo({ 1, 1, 3, 3 }, DataType::Float32);
std::vector<std::vector<int32_t>> inputShape = {{ 1, 1, 4, 4 }};
std::vector<std::vector<int32_t>> intermediateShape = {{ 1, 1, 6, 6 }};
std::vector<std::vector<int32_t>> outputShape = {{ 1, 1, 3, 3 }};
TosaSerializationBasicBlock* basicBlock =
GetTosaMapping(nullptr, LayerType::Pooling2d, {&inputTensorInfo}, {&outputTensorInfo}, descriptor);
VerifyAvgPool2DIgnoreValue(basicBlock,
inputShape,
outputShape,
intermediateShape,
descriptor);
}
TEST_CASE("GetTosaMappingFromLayer_AvgPool2DIgnoreValueLayer")
{
IRuntime::CreationOptions options;
IRuntimePtr runtime(IRuntime::Create(options));
// Builds up the structure of the network.
INetworkPtr net(INetwork::Create());
armnn::Pooling2dDescriptor descriptor;
descriptor.m_PoolType = armnn::PoolingAlgorithm::Average;
descriptor.m_PoolWidth = descriptor.m_PoolHeight = 2;
descriptor.m_StrideX = descriptor.m_StrideY = 2;
descriptor.m_PadLeft = 1;
descriptor.m_PadRight = 1;
descriptor.m_PadTop = 1;
descriptor.m_PadBottom = 1;
descriptor.m_PaddingMethod = armnn::PaddingMethod::IgnoreValue;
IConnectableLayer* input0 = net->AddInputLayer(0, "input0");
IConnectableLayer* pool = net->AddPooling2dLayer(descriptor, "pool");
IConnectableLayer* output = net->AddOutputLayer(0, "output");
input0->GetOutputSlot(0).Connect(pool->GetInputSlot(0));
pool->GetOutputSlot(0).Connect(output->GetInputSlot(0));
armnn::TensorInfo inputTensorInfo({ 1, 1, 4, 4 }, DataType::Float32);
armnn::TensorInfo outputTensorInfo({ 1, 1, 3, 3 }, DataType::Float32);
std::vector<std::vector<int32_t>> inputShape = {{ 1, 1, 4, 4 }};
std::vector<std::vector<int32_t>> intermediateShape = {{ 1, 1, 6, 6 }};
std::vector<std::vector<int32_t>> outputShape = {{ 1, 1, 3, 3 }};
input0->GetOutputSlot(0).SetTensorInfo(inputTensorInfo);
pool->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
TosaSerializationBasicBlock* basicBlock = GetTosaMappingFromLayer(PolymorphicDowncast<Layer*>(pool));
VerifyAvgPool2DIgnoreValue(basicBlock,
inputShape,
outputShape,
intermediateShape,
descriptor);
}
TEST_CASE("GetTosaMapping_QuantizeLayer")
{
NullDescriptor descriptor;
DataType outputDataType = DataType::Signed32;
TensorInfo inputTensorInfo({ 1, 3, 3, 1 }, DataType::Float32);
TensorInfo outputTensorInfo({ 1, 3, 3, 1 }, outputDataType);
std::vector<int32_t> shape = { 1, 3, 3, 1 };
TosaSerializationBasicBlock* basicBlock =
GetTosaMapping(nullptr, LayerType::Quantize, {&inputTensorInfo}, {&outputTensorInfo}, descriptor);
VerifyQuantize(basicBlock, shape, ArmNNToDType(DataType::Float32), ArmNNToDType(outputDataType));
}
TEST_CASE("GetTosaMappingFromLayer_QuantizeLayer")
{
IRuntime::CreationOptions options;
IRuntimePtr runtime(IRuntime::Create(options));
// Builds up the structure of the network.
INetworkPtr net(INetwork::Create());
NullDescriptor descriptor;
DataType outputDataType = DataType::Signed32;
IConnectableLayer* input0 = net->AddInputLayer(0, "input0");
IConnectableLayer* quantize = net->AddQuantizeLayer("quantize");
IConnectableLayer* output = net->AddOutputLayer(0, "output");
input0->GetOutputSlot(0).Connect(quantize->GetInputSlot(0));
quantize->GetOutputSlot(0).Connect(output->GetInputSlot(0));
armnn::TensorInfo inputTensorInfo({ 1, 3, 3, 1 }, DataType::Float32);
armnn::TensorInfo outputTensorInfo({ 1, 3, 3, 1 }, outputDataType);
std::vector<int32_t> shape = { 1, 3, 3, 1 };
input0->GetOutputSlot(0).SetTensorInfo(inputTensorInfo);
quantize->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
TosaSerializationBasicBlock* basicBlock = GetTosaMappingFromLayer(PolymorphicDowncast<Layer*>(quantize));
VerifyQuantize(basicBlock, shape, ArmNNToDType(DataType::Float32), ArmNNToDType(outputDataType));
}
TEST_CASE("GetTosaMapping_SplitLayer")
{
const unsigned int numViews = 3;
const unsigned int numDimensions = 4;
armnn::ViewsDescriptor descriptor(numViews, numDimensions);
descriptor.SetAxis(static_cast<int32_t>(1));
std::vector<std::vector<int32_t>> inShape = {{ 1, 18, 4, 4 }};
std::vector<std::vector<int32_t>> outShape = {{ 1, 6, 4, 4 },{ 1, 6, 4, 4 },{ 1, 6, 4, 4 }};
armnn::TensorInfo inputTensorInfo({1, 18, 4, 4}, DataType::Float32);
armnn::TensorInfo outputTensorInfo({1, 6, 4, 4}, DataType::Float32);
TosaSerializationBasicBlock* basicBlock = GetTosaMapping(nullptr,
LayerType::Splitter,
{&inputTensorInfo},
{&outputTensorInfo, &outputTensorInfo, &outputTensorInfo},
descriptor);
VerifySplit(basicBlock,
inShape,
outShape,
descriptor);
}
TEST_CASE("GetTosaMappingFromLayer_SplitLayer")
{
IRuntime::CreationOptions options;
IRuntimePtr runtime(IRuntime::Create(options));
// Builds up the structure of the network.
INetworkPtr net(INetwork::Create());
const unsigned int numViews = 3;
const unsigned int numDimensions = 4;
armnn::ViewsDescriptor descriptor(numViews, numDimensions);
descriptor.SetAxis(static_cast<int32_t>(1));
std::vector<std::vector<int32_t>> inShape = {{ 1, 18, 4, 4 }};
std::vector<std::vector<int32_t>> outShape = {{ 1, 6, 4, 4 },{ 1, 6, 4, 4 },{ 1, 6, 4, 4 }};
IConnectableLayer* input0 = net->AddInputLayer(0, "input0");
IConnectableLayer* split = net->AddSplitterLayer(descriptor, "split");
IConnectableLayer* output0 = net->AddOutputLayer(0, "output0");
IConnectableLayer* output1 = net->AddOutputLayer(1, "output1");
IConnectableLayer* output2 = net->AddOutputLayer(2, "output2");
input0->GetOutputSlot(0).Connect(split->GetInputSlot(0));
split->GetOutputSlot(0).Connect(output0->GetInputSlot(0));
split->GetOutputSlot(1).Connect(output1->GetInputSlot(0));
split->GetOutputSlot(2).Connect(output2->GetInputSlot(0));
armnn::TensorInfo inputTensorInfo({1, 18, 4, 4}, DataType::Float32);
armnn::TensorInfo outputTensorInfo({1, 6, 4, 4}, DataType::Float32);
input0->GetOutputSlot(0).SetTensorInfo(inputTensorInfo);
split->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
split->GetOutputSlot(1).SetTensorInfo(outputTensorInfo);
split->GetOutputSlot(2).SetTensorInfo(outputTensorInfo);
TosaSerializationBasicBlock* basicBlock = GetTosaMappingFromLayer(PolymorphicDowncast<Layer*>(split));
VerifySplit(basicBlock,
inShape,
outShape,
descriptor);
}
// Activation
static std::vector<BackendId> tosaDefaultBackends = { "TosaRef" };
TEST_CASE("GetTosaMapping_ActivationFloat32")
{
ActivationEndToEndTest<DataType::Float32>(tosaDefaultBackends, ActivationFunction::LeakyReLu, 1.f, 0, 0.01f);
}
TEST_CASE("GetTosaMapping_ActivationFloat16")
{
ActivationEndToEndTest<DataType::Float16>(tosaDefaultBackends, ActivationFunction::LeakyReLu, 1.f, 0, 0.01f);
}
TEST_CASE("GetTosaMapping_ActivationInt32")
{
ActivationEndToEndTest<DataType::Signed32>(tosaDefaultBackends, ActivationFunction::LeakyReLu, 0.15f, 0, 0.01f);
}
TEST_CASE("GetTosaMapping_ActivationInt16")
{
ActivationEndToEndTest<DataType::QSymmS16>(tosaDefaultBackends, ActivationFunction::LeakyReLu, 0.35f, 0, 0.01f);
}
TEST_CASE("GetTosaMapping_ActivationInt8")
{
ActivationEndToEndTest<DataType::QSymmS8>(tosaDefaultBackends, ActivationFunction::LeakyReLu, 0.75f, 0, 0.01f);
}
TEST_CASE("UNSUPPORTED_GetTosaMapping_ActivationUInt8")
{
try
{
ActivationEndToEndTest<DataType::QAsymmU8>(tosaDefaultBackends, ActivationFunction::LeakyReLu, 1.f, 0, 0.01f);
FAIL("An exception should have been thrown");
}
catch (armnn::Exception& e)
{
CHECK_EQ(std::string(e.what()), "Failed to assign a backend to each layer");
}
}
}
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