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//
// Copyright © 2022 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
#pragma once
#include <armnn/INetwork.hpp>
#include <CommonTestUtils.hpp>
#include <ResolveType.hpp>
#include <doctest/doctest.h>
namespace
{
template<typename armnn::DataType DataType>
armnn::INetworkPtr CreateSliceNetwork(const armnn::TensorShape& inputShape,
const armnn::TensorShape& outputShape,
const armnn::SliceDescriptor& descriptor,
const float qScale = 1.0f,
const int32_t qOffset = 0)
{
using namespace armnn;
INetworkPtr network(INetwork::Create());
TensorInfo inputTensorInfo(inputShape, DataType, qScale, qOffset, true);
TensorInfo outputTensorInfo(outputShape, DataType, qScale, qOffset);
IConnectableLayer* slice = network->AddSliceLayer(descriptor, "slice");
IConnectableLayer* input = network->AddInputLayer(0, "input");
IConnectableLayer* output = network->AddOutputLayer(0, "output");
Connect(input, slice, inputTensorInfo, 0, 0);
Connect(slice, output, outputTensorInfo, 0, 0);
return network;
}
template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
void SliceEndToEnd(const std::vector<armnn::BackendId>& backends)
{
using namespace armnn;
const TensorShape& inputShape = { 3, 2, 3 };
const TensorShape& outputShape = { 2, 1, 3 };
SliceDescriptor descriptor;
descriptor.m_Begin = { 1, 0, 0 };
descriptor.m_Size = { 2, 1, 3 };
INetworkPtr network = CreateSliceNetwork<ArmnnType>(inputShape, outputShape, descriptor);
CHECK(network);
std::vector<T> inputData{ 1, 1, 1, 2, 2, 2,
3, 3, 3, 4, 4, 4,
5, 5, 5, 6, 6, 6 };
std::vector<T> expectedOutput{ 3, 3, 3,
5, 5, 5 };
std::map<int, std::vector<T>> inputTensorData = { { 0, inputData } };
std::map<int, std::vector<T>> expectedOutputData = { { 0, expectedOutput } };
EndToEndLayerTestImpl<ArmnnType, ArmnnType>(std::move(network), inputTensorData, expectedOutputData, backends);
}
template<armnn::DataType ArmnnType>
void SliceEndToEndFloat16(const std::vector<armnn::BackendId>& backends)
{
using namespace armnn;
using namespace half_float::literal;
using Half = half_float::half;
const TensorShape& inputShape = { 3, 2, 3 };
const TensorShape& outputShape = { 2, 1, 3 };
SliceDescriptor descriptor;
descriptor.m_Begin = { 1, 0, 0 };
descriptor.m_Size = { 2, 1, 3 };
INetworkPtr network = CreateSliceNetwork<ArmnnType>(inputShape, outputShape, descriptor);
CHECK(network);
std::vector<Half> inputData{ 1._h, 1._h, 1._h, 2._h, 2._h, 2._h,
3._h, 3._h, 3._h, 4._h, 4._h, 4._h,
5._h, 5._h, 5._h, 6._h, 6._h, 6._h };
std::vector<Half> expectedOutput{ 3._h, 3._h, 3._h,
5._h, 5._h, 5._h };
std::map<int, std::vector<Half>> inputTensorData = { { 0, inputData } };
std::map<int, std::vector<Half>> expectedOutputData = { { 0, expectedOutput } };
EndToEndLayerTestImpl<ArmnnType, ArmnnType>(std::move(network), inputTensorData, expectedOutputData, backends);
}
} // anonymous namespace
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