aosp12/external/android-nn-driver/test/Concurrent.cpp

127 lines
4.0 KiB
C++

//
// Copyright © 2017 Arm Ltd. All rights reserved.
// SPDX-License-Identifier: MIT
//
#include "DriverTestHelpers.hpp"
#include "../1.0/HalPolicy.hpp"
#include <boost/test/unit_test.hpp>
#include <log/log.h>
BOOST_AUTO_TEST_SUITE(ConcurrentDriverTests)
using ArmnnDriver = armnn_driver::ArmnnDriver;
using DriverOptions = armnn_driver::DriverOptions;
using HalPolicy = armnn_driver::hal_1_0::HalPolicy;
using namespace android::nn;
using namespace android::hardware;
using namespace driverTestHelpers;
using namespace armnn_driver;
// Add our own test for concurrent execution
// The main point of this test is to check that multiple requests can be
// executed without waiting for the callback from previous execution.
// The operations performed are not significant.
BOOST_AUTO_TEST_CASE(ConcurrentExecute)
{
ALOGI("ConcurrentExecute: entry");
auto driver = std::make_unique<ArmnnDriver>(DriverOptions(armnn::Compute::CpuRef));
HalPolicy::Model model = {};
// add operands
int32_t actValue = 0;
float weightValue[] = {2, 4, 1};
float biasValue[] = {4};
AddInputOperand<HalPolicy>(model, hidl_vec<uint32_t>{1, 3});
AddTensorOperand<HalPolicy>(model, hidl_vec<uint32_t>{1, 3}, weightValue);
AddTensorOperand<HalPolicy>(model, hidl_vec<uint32_t>{1}, biasValue);
AddIntOperand<HalPolicy>(model, actValue);
AddOutputOperand<HalPolicy>(model, hidl_vec<uint32_t>{1, 1});
// make the fully connected operation
model.operations.resize(1);
model.operations[0].type = HalPolicy::OperationType::FULLY_CONNECTED;
model.operations[0].inputs = hidl_vec<uint32_t>{0, 1, 2, 3};
model.operations[0].outputs = hidl_vec<uint32_t>{4};
// make the prepared models
const size_t maxRequests = 5;
size_t preparedModelsSize = 0;
android::sp<V1_0::IPreparedModel> preparedModels[maxRequests];
for (size_t i = 0; i < maxRequests; ++i)
{
auto preparedModel = PrepareModel(model, *driver);
if (preparedModel.get() != nullptr)
{
preparedModels[i] = PrepareModel(model, *driver);
preparedModelsSize++;
}
}
BOOST_TEST(maxRequests == preparedModelsSize);
// construct the request data
DataLocation inloc = {};
inloc.poolIndex = 0;
inloc.offset = 0;
inloc.length = 3 * sizeof(float);
RequestArgument input = {};
input.location = inloc;
input.dimensions = hidl_vec<uint32_t>{};
DataLocation outloc = {};
outloc.poolIndex = 1;
outloc.offset = 0;
outloc.length = 1 * sizeof(float);
RequestArgument output = {};
output.location = outloc;
output.dimensions = hidl_vec<uint32_t>{};
// build the requests
V1_0::Request requests[maxRequests];
android::sp<IMemory> outMemory[maxRequests];
float* outdata[maxRequests];
for (size_t i = 0; i < maxRequests; ++i)
{
requests[i].inputs = hidl_vec<RequestArgument>{input};
requests[i].outputs = hidl_vec<RequestArgument>{output};
// set the input data (matching source test)
float indata[] = {2, 32, 16};
AddPoolAndSetData<float>(3, requests[i], indata);
// add memory for the output
outMemory[i] = AddPoolAndGetData<float>(1, requests[i]);
outdata[i] = static_cast<float*>(static_cast<void*>(outMemory[i]->getPointer()));
}
// invoke the execution of the requests
ALOGI("ConcurrentExecute: executing requests");
android::sp<ExecutionCallback> cb[maxRequests];
for (size_t i = 0; i < maxRequests; ++i)
{
cb[i] = ExecuteNoWait(preparedModels[i], requests[i]);
}
// wait for the requests to complete
ALOGI("ConcurrentExecute: waiting for callbacks");
for (size_t i = 0; i < maxRequests; ++i)
{
ARMNN_ASSERT(cb[i]);
cb[i]->wait();
}
// check the results
ALOGI("ConcurrentExecute: validating results");
for (size_t i = 0; i < maxRequests; ++i)
{
BOOST_TEST(outdata[i][0] == 152);
}
ALOGI("ConcurrentExecute: exit");
}
BOOST_AUTO_TEST_SUITE_END()