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/*
* Copyright (c) 2019-2020 Arm Limited. All rights reserved.
*
* SPDX-License-Identifier: Apache-2.0
*
* Licensed under the Apache License, Version 2.0 (the License); you may
* not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an AS IS BASIS, WITHOUT
* WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#pragma once
#include <array>
#include <queue>
#include <stdlib.h>
#include <string>
#include <vector>
namespace InferenceProcess {
struct DataPtr {
void *data;
size_t size;
DataPtr(void *data = nullptr, size_t size = 0);
void invalidate();
void clean();
};
struct InferenceJob {
std::string name;
DataPtr networkModel;
std::vector<DataPtr> input;
std::vector<DataPtr> output;
std::vector<DataPtr> expectedOutput;
size_t numBytesToPrint;
std::vector<uint8_t> pmuEventConfig;
uint32_t pmuCycleCounterEnable;
std::vector<uint32_t> pmuEventCount;
uint64_t pmuCycleCounterCount;
InferenceJob();
InferenceJob(const std::string &name,
const DataPtr &networkModel,
const std::vector<DataPtr> &input,
const std::vector<DataPtr> &output,
const std::vector<DataPtr> &expectedOutput,
size_t numBytesToPrint,
const std::vector<uint8_t> &pmuEventConfig,
const uint32_t pmuCycleCounterEnable);
void invalidate();
void clean();
};
class InferenceProcess {
public:
InferenceProcess(uint8_t *_tensorArena, size_t _tensorArenaSize) :
lock(0), tensorArena(_tensorArena), tensorArenaSize(_tensorArenaSize) {}
bool push(const InferenceJob &job);
bool runJob(InferenceJob &job);
bool run(bool exitOnEmpty = true);
private:
volatile uint32_t lock;
uint8_t *tensorArena;
const size_t tensorArenaSize;
std::queue<InferenceJob> inferenceJobQueue;
void getLock();
void freeLock();
};
} // namespace InferenceProcess
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