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//
// Copyright © 2023 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
#pragma once
namespace
{
armnn::INetworkPtr CreateReverseV2Network(const armnn::TensorInfo& inputInfo,
const armnn::TensorInfo& axisInfo,
const armnn::TensorInfo& outputInfo,
const std::vector<int32_t>& axisData)
{
using namespace armnn;
INetworkPtr network(INetwork::Create());
IConnectableLayer* inputLayer = network->AddInputLayer(0, "input");
IConnectableLayer* axisLayer = network->AddConstantLayer(ConstTensor(axisInfo, axisData));
IConnectableLayer* reverseLayer = network->AddReverseV2Layer("reverseV2");
IConnectableLayer* outputLayer = network->AddOutputLayer(0, "output");
Connect(inputLayer, reverseLayer, inputInfo, 0, 0);
Connect(axisLayer, reverseLayer, axisInfo, 0, 1);
Connect(reverseLayer, outputLayer, outputInfo, 0, 0);
return network;
}
template <armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
void ReverseV2EndToEnd(const std::vector<BackendId>& backends)
{
float qScale = 1.0f;
int32_t qOffset = 0;
bool qConst = true;
TensorInfo inputInfo ( { 2, 3, 4 }, ArmnnType, qScale, qOffset, qConst);
TensorInfo axisInfo ( { 1 } , DataType::Signed32, qScale, qOffset, qConst);
TensorInfo outputInfo ( { 2, 3, 4 }, ArmnnType, qScale, qOffset);
std::vector<T> inputData = armnnUtils::QuantizedVector<T>({
1, 2, 3, 4,
5, 6 , 7, 8,
9, 10, 11, 12,
13, 14, 15, 16,
17, 18, 19, 20,
21, 22, 23, 24
}, qScale, qOffset);
std::vector<int32_t> axisData = { 1 };
std::vector<T> expectedOutputData = armnnUtils::QuantizedVector<T>({
9, 10, 11, 12,
5, 6, 7 , 8,
1, 2, 3, 4,
21, 22, 23, 24,
17, 18, 19, 20,
13, 14, 15, 16
}, qScale, qOffset);
INetworkPtr network = CreateReverseV2Network(inputInfo, axisInfo, outputInfo, axisData);
std::map<int, std::vector<T>> inputTensor = { { 0, inputData } };
std::map<int, std::vector<T>> expectedOutputTensor = { { 0, expectedOutputData } };
EndToEndLayerTestImpl<ArmnnType, ArmnnType>(std::move(network), inputTensor, expectedOutputTensor, backends);
}
} // anonymous namespace
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