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//
// Copyright © 2022 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
#include "LayersFwd.hpp"
#include <Network.hpp>
#include <TestUtils.hpp>
#include <doctest/doctest.h>
#include <armnn/backends/TensorHandle.hpp>
#include <Optimizer.hpp>
TEST_SUITE("Optimizer")
{
using namespace armnn;
using namespace armnn::optimizations;
TEST_CASE("ConvertConstFloat16DequantizeToConstFloat32")
{
Graph graph;
const unsigned int shape[] = {1, 2, 2, 3};
const TensorInfo constTensorInfo(4, shape, DataType::Float16, 1.0, 0, true);
const TensorInfo outputDequantizeInfo(4, shape, DataType::Float32, 1.0, 0, true);
ConstantLayer *constantLayer = graph.AddLayer<ConstantLayer>("constant");
std::vector<float> constantValues(constTensorInfo.GetNumElements(), 4.5f);
ConstTensor constTensor(constTensorInfo, constantValues.data());
constantLayer->m_LayerOutput = std::make_shared<ScopedTensorHandle>(constTensor);
constantLayer->GetOutputSlot().SetTensorInfo(constTensorInfo);
DequantizeLayer *dequantizeLayer = graph.AddLayer<DequantizeLayer>("dequantize");
dequantizeLayer->GetOutputSlot().SetTensorInfo(outputDequantizeInfo);
OutputLayer *output = graph.AddLayer<OutputLayer>(0, "output");
// Connect up constant -> dequantize -> output
constantLayer->GetOutputSlot().Connect(dequantizeLayer->GetInputSlot(0));
dequantizeLayer->GetOutputSlot().Connect(output->GetInputSlot(0));
auto checkConstantFloat16 = [](const armnn::Layer *const layer) -> bool {
return IsLayerOfType<ConstantLayer>(layer) &&
(layer->GetDataType() == DataType::Float16);
};
auto checkConstantFloat32 = [](const armnn::Layer *const layer) -> bool {
return IsLayerOfType<ConstantLayer>(layer) &&
(layer->GetDataType() == DataType::Float32);
};
CHECK(CheckSequence(graph.cbegin(), graph.cend(),
checkConstantFloat16,
&IsLayerOfType<DequantizeLayer>,
&IsLayerOfType<OutputLayer>));
armnn::Optimizer::Pass(graph, MakeOptimizations(ConvertConstDequantisationLayersToConstLayers()));
CHECK(CheckSequence(graph.cbegin(), graph.cend(),
checkConstantFloat32,
&IsLayerOfType<OutputLayer>));
}
TEST_CASE("ConvertConstInt8DequantizeToConstFloat32")
{
Graph graph;
const unsigned int shape[] = {1, 2, 2, 3};
const TensorInfo constTensorInfo(4, shape, DataType::QAsymmS8, 1.0, 0, true);
const TensorInfo outputDequantizeInfo(4, shape, DataType::Float32, 1.0, 0, true);
ConstantLayer *constantLayer = graph.AddLayer<ConstantLayer>("constant");
std::vector<int8_t> constantValues(constTensorInfo.GetNumElements(), 5);
ConstTensor constTensor(constTensorInfo, constantValues.data());
constantLayer->m_LayerOutput = std::make_shared<ScopedTensorHandle>(constTensor);
constantLayer->GetOutputSlot().SetTensorInfo(constTensorInfo);
DequantizeLayer *dequantizeLayer = graph.AddLayer<DequantizeLayer>("dequantize");
dequantizeLayer->GetOutputSlot().SetTensorInfo(outputDequantizeInfo);
OutputLayer *output = graph.AddLayer<OutputLayer>(0, "output");
// Connect up constant -> dequantize -> output
constantLayer->GetOutputSlot().Connect(dequantizeLayer->GetInputSlot(0));
dequantizeLayer->GetOutputSlot().Connect(output->GetInputSlot(0));
auto checkConstantQAsymmS8 = [](const armnn::Layer *const layer) -> bool {
return IsLayerOfType<ConstantLayer>(layer) &&
(layer->GetDataType() == DataType::QAsymmS8);
};
auto checkConstantFloat32 = [](const armnn::Layer *const layer) -> bool {
return IsLayerOfType<ConstantLayer>(layer) &&
(layer->GetDataType() == DataType::Float32);
};
CHECK(CheckSequence(graph.cbegin(), graph.cend(),
checkConstantQAsymmS8,
&IsLayerOfType<DequantizeLayer>,
&IsLayerOfType<OutputLayer>));
armnn::Optimizer::Pass(graph, MakeOptimizations(ConvertConstDequantisationLayersToConstLayers()));
CHECK(CheckSequence(graph.cbegin(), graph.cend(),
checkConstantFloat32,
&IsLayerOfType<OutputLayer>));
}
}
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