/*
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* Copyright (C) 2017 The Android Open Source Project
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#define LOG_TAG "CompilationBuilder"
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#include "CompilationBuilder.h"
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#include "BurstBuilder.h"
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#include "ExecutionBuilder.h"
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#include "ExecutionBurstController.h"
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#include "ExecutionPlan.h"
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#include "Manager.h"
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#include "ModelBuilder.h"
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#include "Utils.h"
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namespace android {
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namespace nn {
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CompilationBuilder::CompilationBuilder(const ModelBuilder* model,
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const std::vector<std::shared_ptr<Device>>& devices,
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bool explicitDeviceList)
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: mModel(model),
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mPartitioning(explicitDeviceList ? DeviceManager::kPartitioningWithoutFallback
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: DeviceManager::get()->getPartitioning()),
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mDevices(devices),
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mExplicitDeviceList(explicitDeviceList) {
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VLOG(COMPILATION) << "CompilationBuilder::CompilationBuilder";
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}
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int CompilationBuilder::finish() {
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if (mFinished) {
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LOG(ERROR) << "ANeuralNetworksCompilation_finish called more than once";
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return ANEURALNETWORKS_BAD_STATE;
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}
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// TODO validate the rest
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mFinished = true;
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if (mIsCacheInfoProvided) {
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mPlan.setCaching(&mCacheDir, mToken);
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}
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if (mPartitioning) {
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int n = mModel->partitionTheWork(mDevices, mPreference, &mPlan);
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switch (n) {
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case ANEURALNETWORKS_NO_ERROR:
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return n;
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case ANEURALNETWORKS_UNEXPECTED_NULL:
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case ANEURALNETWORKS_BAD_DATA:
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// The two error codes above should only be used for errors in the user's
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// request. In case of a user error, we won't try any fallback.
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// TODO: Document this in NeuralNetworks.h and in the HAL. Make sure
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// driver writers know which code they can return.
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return n;
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default:
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// The error might be recoverable. Return the error only if falling back
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// is not allowed.
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if (!DeviceManager::partitioningAllowsFallback(mPartitioning)) {
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return n;
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}
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if (mModel->hasOEMOperation()) {
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LOG(ERROR) << "Cannot fall back to CPU because of an OEM operation";
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return n;
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}
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if (mModel->hasExtensionOperation()) {
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LOG(ERROR) << "Cannot fall back to CPU because of an extension operation";
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return n;
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}
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break;
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}
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}
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// Fallback to CPU
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VLOG(COMPILATION) << "CompilationBuilder::finish with CPU fallback";
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mPlan.reset();
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mPlan.becomeSingleStep(DeviceManager::getCpuDevice(), mModel);
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return mPlan.finish(mModel, mPreference);
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}
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int CompilationBuilder::setPreference(int32_t preference) {
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if (mFinished) {
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LOG(ERROR) <<
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"ANeuralNetworksCompilation_setPreference can't modify after compilation finished";
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return ANEURALNETWORKS_BAD_STATE;
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}
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if (preference >= kNumberOfPreferences) {
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LOG(ERROR) << "ANeuralNetworksCompilation_setPreference invalid preference " << preference;
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return ANEURALNETWORKS_BAD_DATA;
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}
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mPreference = preference;
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return ANEURALNETWORKS_NO_ERROR;
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}
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int CompilationBuilder::setCaching(const std::string& cacheDir, const uint8_t* token) {
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if (mFinished) {
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LOG(ERROR)
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<< "ANeuralNetworksCompilation_setCaching can't modify after compilation finished";
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return ANEURALNETWORKS_BAD_STATE;
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}
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mCacheDir = cacheDir;
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// Make sure the cache dir can concat with the filename.
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if (!mCacheDir.empty() && mCacheDir.back() != '/') {
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mCacheDir.push_back('/');
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}
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std::copy(token, token + ANEURALNETWORKS_BYTE_SIZE_OF_CACHE_TOKEN, mToken);
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mIsCacheInfoProvided = true;
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return ANEURALNETWORKS_NO_ERROR;
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}
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int CompilationBuilder::setPartitioning(uint32_t partitioning) {
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if (mFinished) {
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LOG(ERROR) <<
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"ANeuralNetworksCompilation_setPartitioning can't modify after compilation finished";
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return ANEURALNETWORKS_BAD_STATE;
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}
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mPartitioning = partitioning;
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return ANEURALNETWORKS_NO_ERROR;
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}
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int CompilationBuilder::createExecution(ExecutionBuilder **execution) {
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if (!mFinished) {
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LOG(ERROR) << "ANeuralNetworksExecution_create passed an unfinished compilation";
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*execution = nullptr;
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return ANEURALNETWORKS_BAD_STATE;
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}
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if (!mPlan.isValid()) {
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LOG(ERROR) << "ANeuralNetworksExecution_create passed an invalid compilation";
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*execution = nullptr;
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return ANEURALNETWORKS_BAD_STATE;
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}
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*execution = new (std::nothrow) ExecutionBuilder(this);
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return (*execution ? ANEURALNETWORKS_NO_ERROR : ANEURALNETWORKS_OUT_OF_MEMORY);
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}
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int CompilationBuilder::createBurst(BurstBuilder** burst) {
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if (!mFinished) {
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LOG(ERROR) << "ANeuralNetworksBurst_create passed an unfinished compilation";
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*burst = nullptr;
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return ANEURALNETWORKS_BAD_STATE;
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}
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if (!mPlan.isValid()) {
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LOG(ERROR) << "ANeuralNetworksBurst_create passed an invalid compilation";
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*burst = nullptr;
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return ANEURALNETWORKS_BAD_STATE;
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}
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std::vector<std::shared_ptr<ExecutionBurstController>> burstControllers = mPlan.makeBursts();
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*burst = new (std::nothrow) BurstBuilder(this, std::move(burstControllers));
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return (*burst ? ANEURALNETWORKS_NO_ERROR : ANEURALNETWORKS_OUT_OF_MEMORY);
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}
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} // namespace nn
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} // namespace android
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