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//
// Copyright © 2020 Arm Ltd. All rights reserved.
// SPDX-License-Identifier: MIT
//
#include <TestUtils.hpp>
#include <Optimizer.hpp>
#include <doctest/doctest.h>
TEST_SUITE("Optimizer")
{
using namespace armnn::optimizations;
TEST_CASE("MoveTransposeUpTest")
{
const armnn::TensorInfo info({ 1, 5, 2, 3 }, armnn::DataType::Float32);
const armnn::TensorInfo transposed({ 1, 3, 5, 2 }, armnn::DataType::Float32);
armnn::Graph graph;
armnn::LayerBindingId inputId = 0;
armnn::Layer* head = graph.AddLayer<armnn::OutputLayer>(0, "output");
std::string transposeLayerName = "original_transpose";
// Insert transpose
head = graph.InsertNewLayer<armnn::TransposeLayer>(head->GetInputSlot(0),
armnn::TransposeDescriptor({ 0, 3, 1, 2 }),
transposeLayerName.c_str());
head->GetOutputHandler().SetTensorInfo(transposed);
// Inserts layers that don't care about data format.
head = graph.InsertNewLayer<armnn::ActivationLayer>(head->GetInputSlot(0), armnn::ActivationDescriptor{}, "");
head->GetOutputHandler().SetTensorInfo(info);
head = graph.InsertNewLayer<armnn::AdditionLayer>(head->GetInputSlot(0), "");
head->GetOutputHandler().SetTensorInfo(info);
// Inserts input for 2nd input of Addition.
graph.InsertNewLayer<armnn::InputLayer>(head->GetInputSlot(1), inputId++, "")
->GetOutputHandler()
.SetTensorInfo(info);
head = graph.InsertNewLayer<armnn::FakeQuantizationLayer>(head->GetInputSlot(0),
armnn::FakeQuantizationDescriptor{}, "");
head->GetOutputHandler().SetTensorInfo(info);
head = graph.InsertNewLayer<armnn::FloorLayer>(head->GetInputSlot(0), "");
head->GetOutputHandler().SetTensorInfo(info);
head = graph.InsertNewLayer<armnn::MemCopyLayer>(head->GetInputSlot(0), "");
head->GetOutputHandler().SetTensorInfo(info);
head = graph.InsertNewLayer<armnn::MultiplicationLayer>(head->GetInputSlot(0), "");
head->GetOutputHandler().SetTensorInfo(info);
// Inserts input for 2nd input of Multiplication.
graph.InsertNewLayer<armnn::InputLayer>(head->GetInputSlot(1), inputId++, "")
->GetOutputHandler()
.SetTensorInfo(info);
// Inserts input.
graph.InsertNewLayer<armnn::InputLayer>(head->GetInputSlot(0), inputId++, "")
->GetOutputHandler()
.SetTensorInfo(info);
CHECK(CheckSequence(graph.cbegin(), graph.cend(), &IsLayerOfType<armnn::InputLayer>,
&IsLayerOfType<armnn::InputLayer>, &IsLayerOfType<armnn::InputLayer>,
&IsLayerOfType<armnn::MultiplicationLayer>, &IsLayerOfType<armnn::MemCopyLayer>,
&IsLayerOfType<armnn::FloorLayer>, &IsLayerOfType<armnn::FakeQuantizationLayer>,
&IsLayerOfType<armnn::AdditionLayer>, &IsLayerOfType<armnn::ActivationLayer>,
&IsLayerOfType<armnn::TransposeLayer>, &IsLayerOfType<armnn::OutputLayer>));
armnn::Optimizer::Pass(graph, armnn::MakeOptimizations(MoveTransposeUp()));
// The transpose is moved to the top. New transposes for layers with multiple inputs.
CHECK(CheckSequence(graph.cbegin(), graph.cend(), &IsLayerOfType<armnn::InputLayer>,
&IsLayerOfType<armnn::InputLayer>, &IsLayerOfType<armnn::InputLayer>,
&IsLayerOfType<armnn::TransposeLayer>, &IsLayerOfType<armnn::TransposeLayer>,
&IsLayerOfType<armnn::TransposeLayer>, &IsLayerOfType<armnn::MultiplicationLayer>,
&IsLayerOfType<armnn::MemCopyLayer>, &IsLayerOfType<armnn::FloorLayer>,
&IsLayerOfType<armnn::FakeQuantizationLayer>, &IsLayerOfType<armnn::AdditionLayer>,
&IsLayerOfType<armnn::ActivationLayer>, &IsLayerOfType<armnn::OutputLayer>));
std::list<std::string> testRelatedLayers = { transposeLayerName };
CHECK(CheckRelatedLayers<armnn::TransposeLayer>(graph, testRelatedLayers));
}
}
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