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//
// Copyright © 2017 Arm Ltd. All rights reserved.
// SPDX-License-Identifier: MIT
//
#include "OperationsUtils.h"
#include "../DriverTestHelpers.hpp"
#include "../TestTensor.hpp"
#include "../1.1/HalPolicy.hpp"
#include <boost/test/unit_test.hpp>
#include <boost/test/data/test_case.hpp>
#include <log/log.h>
#include <array>
#include <cmath>
BOOST_AUTO_TEST_SUITE(TransposeTests)
using namespace android::hardware;
using namespace driverTestHelpers;
using namespace armnn_driver;
using HalPolicy = hal_1_1::HalPolicy;
namespace
{
#ifndef ARMCOMPUTECL_ENABLED
static const std::array<armnn::Compute, 1> COMPUTE_DEVICES = {{ armnn::Compute::CpuRef }};
#else
static const std::array<armnn::Compute, 2> COMPUTE_DEVICES = {{ armnn::Compute::CpuRef, armnn::Compute::GpuAcc }};
#endif
void TransposeTestImpl(const TestTensor & inputs, int32_t perm[],
const TestTensor & expectedOutputTensor, armnn::Compute computeDevice)
{
auto driver = std::make_unique<ArmnnDriver>(DriverOptions(computeDevice));
HalPolicy::Model model = {};
AddInputOperand<HalPolicy>(model,inputs.GetDimensions());
AddTensorOperand<HalPolicy>(model,
hidl_vec<uint32_t>{4},
perm,
HalPolicy::OperandType::TENSOR_INT32);
AddOutputOperand<HalPolicy>(model, expectedOutputTensor.GetDimensions());
model.operations.resize(1);
model.operations[0].type = HalPolicy::OperationType::TRANSPOSE;
model.operations[0].inputs = hidl_vec<uint32_t>{0, 1};
model.operations[0].outputs = hidl_vec<uint32_t>{2};
android::sp<V1_0::IPreparedModel> preparedModel = PrepareModel(model, *driver);
// the request's memory pools will follow the same order as
// the inputs
DataLocation inloc = {};
inloc.poolIndex = 0;
inloc.offset = 0;
inloc.length = inputs.GetNumElements() * sizeof(float);
RequestArgument input = {};
input.location = inloc;
input.dimensions = inputs.GetDimensions();
// and an additional memory pool is needed for the output
DataLocation outloc = {};
outloc.poolIndex = 1;
outloc.offset = 0;
outloc.length = expectedOutputTensor.GetNumElements() * sizeof(float);
RequestArgument output = {};
output.location = outloc;
output.dimensions = expectedOutputTensor.GetDimensions();
// make the request based on the arguments
V1_0::Request request = {};
request.inputs = hidl_vec<RequestArgument>{input};
request.outputs = hidl_vec<RequestArgument>{output};
// set the input data
AddPoolAndSetData(inputs.GetNumElements(),
request,
inputs.GetData());
// add memory for the output
android::sp<IMemory> outMemory = AddPoolAndGetData<float>(expectedOutputTensor.GetNumElements(), request);
float* outdata = static_cast<float*>(static_cast<void*>(outMemory->getPointer()));
if (preparedModel.get() != nullptr)
{
auto execStatus = Execute(preparedModel, request);
}
const float * expectedOutput = expectedOutputTensor.GetData();
for (unsigned int i = 0; i < expectedOutputTensor.GetNumElements(); ++i)
{
BOOST_TEST(outdata[i] == expectedOutput[i]);
}
}
} // namespace
BOOST_DATA_TEST_CASE(Transpose , COMPUTE_DEVICES)
{
int32_t perm[] = {2, 3, 1, 0};
TestTensor input{armnn::TensorShape{1, 2, 2, 2},{1, 2, 3, 4, 5, 6, 7, 8}};
TestTensor expected{armnn::TensorShape{2, 2, 2, 1},{1, 5, 2, 6, 3, 7, 4, 8}};
TransposeTestImpl(input, perm, expected, sample);
}
BOOST_DATA_TEST_CASE(TransposeNHWCToArmNN , COMPUTE_DEVICES)
{
int32_t perm[] = {0, 3, 1, 2};
TestTensor input{armnn::TensorShape{1, 2, 2, 3},{1, 2, 3, 11, 12, 13, 21, 22, 23, 31, 32, 33}};
TestTensor expected{armnn::TensorShape{1, 3, 2, 2},{1, 11, 21, 31, 2, 12, 22, 32, 3, 13, 23, 33}};
TransposeTestImpl(input, perm, expected, sample);
}
BOOST_DATA_TEST_CASE(TransposeArmNNToNHWC , COMPUTE_DEVICES)
{
int32_t perm[] = {0, 2, 3, 1};
TestTensor input{armnn::TensorShape{1, 2, 2, 2},{1, 2, 3, 4, 5, 6, 7, 8}};
TestTensor expected{armnn::TensorShape{1, 2, 2, 2},{1, 5, 2, 6, 3, 7, 4, 8}};
TransposeTestImpl(input, perm, expected, sample);
}
BOOST_AUTO_TEST_SUITE_END()
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