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/*
// Copyright (C) 2020-2022 Intel Corporation
//
// 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
//
// http://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.
*/
#include "pipelines/async_pipeline.h"
#include <chrono>
#include <cstdint>
#include <map>
#include <memory>
#include <stdexcept>
#include <string>
#include <utility>
#include <vector>
#include <openvino/openvino.hpp>
#include <models/model_base.h>
#include <models/results.h>
#include <utils/config_factory.h>
#include <utils/performance_metrics.hpp>
#include <utils/slog.hpp>
struct InputData;
struct MetaData;
AsyncPipeline::AsyncPipeline(std::unique_ptr<ModelBase>&& modelInstance, const ModelConfig& config, ov::Core& core)
: model(std::move(modelInstance)) {
compiledModel = model->compileModel(config, core);
// --------------------------- Create infer requests ------------------------------------------------
unsigned int nireq = config.maxAsyncRequests;
if (nireq == 0) {
try {
nireq = compiledModel.get_property(ov::optimal_number_of_infer_requests);
} catch (const ov::Exception& ex) {
throw std::runtime_error(
std::string("Every device used with the demo should support compiled model's property "
"'OPTIMAL_NUMBER_OF_INFER_REQUESTS'. Failed to query the property with error: ") +
ex.what());
}
}
slog::info << "\tNumber of inference requests: " << nireq << slog::endl;
requestsPool.reset(new RequestsPool(compiledModel, nireq));
// --------------------------- Call onLoadCompleted to complete initialization of model -------------
model->onLoadCompleted(requestsPool->getInferRequestsList());
}
AsyncPipeline::~AsyncPipeline() {
waitForTotalCompletion();
}
void AsyncPipeline::waitForData(bool shouldKeepOrder) {
std::unique_lock<std::mutex> lock(mtx);
condVar.wait(lock, [&]() {
return callbackException != nullptr || requestsPool->isIdleRequestAvailable() ||
(shouldKeepOrder ? completedInferenceResults.find(outputFrameId) != completedInferenceResults.end()
: !completedInferenceResults.empty());
});
if (callbackException) {
std::rethrow_exception(callbackException);
}
}
int64_t AsyncPipeline::submitData(const InputData& inputData, const std::shared_ptr<MetaData>& metaData) {
auto frameID = inputFrameId;
auto request = requestsPool->getIdleRequest();
if (!request) {
return -1;
}
auto startTime = std::chrono::steady_clock::now();
auto internalModelData = model->preprocess(inputData, request);
preprocessMetrics.update(startTime);
request.set_callback(
[this, request, frameID, internalModelData, metaData, startTime](std::exception_ptr ex) mutable {
{
const std::lock_guard<std::mutex> lock(mtx);
inferenceMetrics.update(startTime);
try {
if (ex) {
std::rethrow_exception(ex);
}
InferenceResult result;
result.frameId = frameID;
result.metaData = std::move(metaData);
result.internalModelData = std::move(internalModelData);
for (const auto& outName : model->getOutputsNames()) {
auto tensor = request.get_tensor(outName);
result.outputsData.emplace(outName, tensor);
}
completedInferenceResults.emplace(frameID, result);
requestsPool->setRequestIdle(request);
} catch (...) {
if (!callbackException) {
callbackException = std::current_exception();
}
}
}
condVar.notify_one();
});
inputFrameId++;
if (inputFrameId < 0)
inputFrameId = 0;
request.start_async();
return frameID;
}
std::unique_ptr<ResultBase> AsyncPipeline::getResult(bool shouldKeepOrder) {
auto infResult = AsyncPipeline::getInferenceResult(shouldKeepOrder);
if (infResult.IsEmpty()) {
return std::unique_ptr<ResultBase>();
}
auto startTime = std::chrono::steady_clock::now();
auto result = model->postprocess(infResult);
postprocessMetrics.update(startTime);
*result = static_cast<ResultBase&>(infResult);
return result;
}
InferenceResult AsyncPipeline::getInferenceResult(bool shouldKeepOrder) {
InferenceResult retVal;
{
const std::lock_guard<std::mutex> lock(mtx);
const auto& it =
shouldKeepOrder ? completedInferenceResults.find(outputFrameId) : completedInferenceResults.begin();
if (it != completedInferenceResults.end()) {
retVal = std::move(it->second);
completedInferenceResults.erase(it);
}
}
if (!retVal.IsEmpty()) {
outputFrameId = retVal.frameId;
outputFrameId++;
if (outputFrameId < 0) {
outputFrameId = 0;
}
}
return retVal;
}
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