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/*
* Copyright (C) 2017 The Android Open Source Project
*
* 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.
*/
#define LOG_TAG "CompilationBuilder"
#include "CompilationBuilder.h"
#include <algorithm>
#include <limits>
#include <memory>
#include <string>
#include <utility>
#include <vector>
#include "BurstBuilder.h"
#include "ExecutionBuilder.h"
#include "ExecutionBurstController.h"
#include "ExecutionPlan.h"
#include "Manager.h"
#include "ModelBuilder.h"
#include "Utils.h"
namespace android {
namespace nn {
using namespace hal;
CompilationBuilder::CompilationBuilder(const ModelBuilder* model,
const std::vector<std::shared_ptr<Device>>& devices,
bool explicitDeviceList)
: mModel(model),
mPartitioning(explicitDeviceList ? DeviceManager::kPartitioningWithoutFallback
: DeviceManager::get()->getPartitioning()),
mDevices(devices),
mExplicitDeviceList(explicitDeviceList) {
VLOG(COMPILATION) << "CompilationBuilder::CompilationBuilder";
}
int CompilationBuilder::finish() {
if (mFinished) {
LOG(ERROR) << "ANeuralNetworksCompilation_finish called more than once";
return ANEURALNETWORKS_BAD_STATE;
}
// TODO validate the rest
const auto deadline = makeDeadline(mTimeoutDuration);
mFinished = true;
if (mIsCacheInfoProvided) {
mPlan.setCaching(&mCacheDir, mToken);
}
if (mPartitioning) {
int n = mModel->partitionTheWork(mDevices, mPreference, mPriority, deadline, &mPlan);
switch (n) {
case ANEURALNETWORKS_NO_ERROR:
return n;
case ANEURALNETWORKS_UNEXPECTED_NULL:
case ANEURALNETWORKS_BAD_DATA:
// The two error codes above should only be used for errors in the user's
// request. In case of a user error, we won't try any fallback.
// TODO: Document this in NeuralNetworks.h and in the HAL. Make sure
// driver writers know which code they can return.
return n;
default:
// The error might be recoverable. Return the error only if falling back
// is not allowed.
if (!DeviceManager::partitioningAllowsFallback(mPartitioning)) {
return n;
}
if (mModel->hasOEMOperation()) {
LOG(ERROR) << "Cannot fall back to CPU because of an OEM operation";
return n;
}
if (mModel->hasExtensionOperation()) {
LOG(ERROR) << "Cannot fall back to CPU because of an extension operation";
return n;
}
break;
}
}
// Fallback to CPU
VLOG(COMPILATION) << "CompilationBuilder::finish with CPU fallback";
mPlan.reset();
mPlan.becomeSingleStep(DeviceManager::getCpuDevice(), mModel);
return mPlan.finish(mPreference, mPriority, deadline);
}
int CompilationBuilder::setPreference(int32_t preference) {
if (mFinished) {
LOG(ERROR) << "ANeuralNetworksCompilation_setPreference can't modify after compilation "
"finished";
return ANEURALNETWORKS_BAD_STATE;
}
if (preference >= kNumberOfPreferences) {
LOG(ERROR) << "ANeuralNetworksCompilation_setPreference invalid preference " << preference;
return ANEURALNETWORKS_BAD_DATA;
}
mPreference = preference;
return ANEURALNETWORKS_NO_ERROR;
}
int CompilationBuilder::setCaching(const std::string& cacheDir, const uint8_t* token) {
if (mFinished) {
LOG(ERROR)
<< "ANeuralNetworksCompilation_setCaching can't modify after compilation finished";
return ANEURALNETWORKS_BAD_STATE;
}
mCacheDir = cacheDir;
// Make sure the cache dir can concat with the filename.
if (!mCacheDir.empty() && mCacheDir.back() != '/') {
mCacheDir.push_back('/');
}
std::copy(token, token + ANEURALNETWORKS_BYTE_SIZE_OF_CACHE_TOKEN, mToken);
mIsCacheInfoProvided = true;
return ANEURALNETWORKS_NO_ERROR;
}
int CompilationBuilder::setPriority(int32_t priority) {
if (mFinished) {
LOG(ERROR) << "ANeuralNetworksCompilation_setPriority can't modify after compilation "
"finished";
return ANEURALNETWORKS_BAD_STATE;
}
if (priority != ANEURALNETWORKS_PRIORITY_LOW && priority != ANEURALNETWORKS_PRIORITY_MEDIUM &&
priority != ANEURALNETWORKS_PRIORITY_HIGH) {
LOG(ERROR) << "ANeuralNetworksCompilation_setPriority invalid priority " << priority;
return ANEURALNETWORKS_BAD_DATA;
}
mPriority = priority;
return ANEURALNETWORKS_NO_ERROR;
}
int CompilationBuilder::setTimeoutDuration(uint64_t duration) {
if (mFinished) {
LOG(ERROR) << "ANeuralNetworksCompilation_setTimeout can't modify after compilation "
"finished";
return ANEURALNETWORKS_BAD_STATE;
}
if (!mExplicitDeviceList || (mDevices.size() != 1)) {
LOG(ERROR) << "ANeuralNetworksCompilation_setTimeout called on an "
"ANeuralNetworksCompilation that was not created by "
"ANeuralNetworksCompilation_createForDevices with numDevices = 1";
return ANEURALNETWORKS_BAD_DATA;
}
if (duration > 0) {
mTimeoutDuration = duration;
} else {
mTimeoutDuration.reset();
}
return ANEURALNETWORKS_NO_ERROR;
}
int CompilationBuilder::setPartitioning(uint32_t partitioning) {
if (mFinished) {
LOG(ERROR) << "ANeuralNetworksCompilation_setPartitioning can't modify after compilation "
"finished";
return ANEURALNETWORKS_BAD_STATE;
}
mPartitioning = partitioning;
return ANEURALNETWORKS_NO_ERROR;
}
int CompilationBuilder::createExecution(ExecutionBuilder** execution) {
if (!mFinished) {
LOG(ERROR) << "ANeuralNetworksExecution_create passed an unfinished compilation";
*execution = nullptr;
return ANEURALNETWORKS_BAD_STATE;
}
if (!mPlan.isValid()) {
LOG(ERROR) << "ANeuralNetworksExecution_create passed an invalid compilation";
*execution = nullptr;
return ANEURALNETWORKS_BAD_STATE;
}
*execution = new (std::nothrow) ExecutionBuilder(this);
return (*execution ? ANEURALNETWORKS_NO_ERROR : ANEURALNETWORKS_OUT_OF_MEMORY);
}
int CompilationBuilder::createBurst(BurstBuilder** burst) {
if (!mFinished) {
LOG(ERROR) << "ANeuralNetworksBurst_create passed an unfinished compilation";
*burst = nullptr;
return ANEURALNETWORKS_BAD_STATE;
}
if (!mPlan.isValid()) {
LOG(ERROR) << "ANeuralNetworksBurst_create passed an invalid compilation";
*burst = nullptr;
return ANEURALNETWORKS_BAD_STATE;
}
std::vector<std::shared_ptr<ExecutionBurstController>> burstControllers =
mPlan.makeBursts(mPreference);
*burst = new (std::nothrow) BurstBuilder(this, std::move(burstControllers));
return (*burst ? ANEURALNETWORKS_NO_ERROR : ANEURALNETWORKS_OUT_OF_MEMORY);
}
int CompilationBuilder::forEachStepRoleOfInput(uint32_t index,
const StepRoleCallback& callback) const {
if (!mFinished) {
LOG(ERROR) << "ANeuralNetworksMemoryDesc_addInputRole passed an unfinished compilation";
return ANEURALNETWORKS_BAD_STATE;
}
if (!mPlan.isValid()) {
LOG(ERROR) << "ANeuralNetworksMemoryDesc_addInputRole passed an invalid compilation";
return ANEURALNETWORKS_BAD_STATE;
}
if (index >= mModel->inputCount()) {
LOG(ERROR) << "ANeuralNetworksMemoryDesc_addInputRole passed an invalid input index "
<< index;
return ANEURALNETWORKS_BAD_DATA;
}
mPlan.forEachStepRoleOfInput(index, callback);
return ANEURALNETWORKS_NO_ERROR;
}
int CompilationBuilder::forEachStepRoleOfOutput(uint32_t index,
const StepRoleCallback& callback) const {
if (!mFinished) {
LOG(ERROR) << "ANeuralNetworksMemoryDesc_addOutputRole passed an unfinished compilation";
return ANEURALNETWORKS_BAD_STATE;
}
if (!mPlan.isValid()) {
LOG(ERROR) << "ANeuralNetworksMemoryDesc_addOutputRole passed an invalid compilation";
return ANEURALNETWORKS_BAD_STATE;
}
if (index >= mModel->outputCount()) {
LOG(ERROR) << "ANeuralNetworksMemoryDesc_addOutputRole passed an invalid output index "
<< index;
return ANEURALNETWORKS_BAD_DATA;
}
mPlan.forEachStepRoleOfOutput(index, callback);
return ANEURALNETWORKS_NO_ERROR;
}
} // namespace nn
} // namespace android