MNN 执行推理（九）

系列文章目录

MNN createFromBuffer（一）
MNN createRuntime（二）
MNN createSession 之 Schedule（三）
MNN createSession 之创建流水线后端（四）
MNN Session 之维度计算（五）
MNN Session 之几何计算（六）
MNN Session 之 CPU 算子（七）
MNN Session 之 Vulkan 算子（八）
MNN 执行推理（九）

1、Interpreter::runSession

// source/core/Interpreter.cpp
ErrorCode Interpreter::runSession(Session* session) const {
    std::unique_lock<std::mutex> _l(mNet->lock);
#ifdef MNN_INTERNAL_ENABLED
    Timer timer;
#endif
    ErrorCode errorcode = session->run();

#ifdef MNN_INTERNAL_ENABLED
    if (shouldLog(FREQ_LOW)) {
        waitSessionFinish(session);
        float costTime = (float)timer.durationInUs() / (float)1000;
        logForRunSession(session, costTime, "Interpreter::runSession");
    }
#endif // MNN_INTERNAL_ENABLED

    return errorcode;
}

1.1 Session::run

Pipeline

// source/core/Session.cpp
ErrorCode Session::run() const {
    if (mNeedResize) {
        MNN_ERROR("Can't run session because not resized\n");
        return COMPUTE_SIZE_ERROR;
    }
    // mPipelines 类型为 std::vector<std::shared_ptr<Pipeline>>
    for (auto& iter : mPipelines) {
        auto error = iter->execute();
        if (NO_ERROR != error) {
            return error;
        }
    }
    return NO_ERROR;
}

1.1.1 Pipeline::execute

OpCacheInfo 、BackendCache、Command、CommandBuffer

// source/core/Pipeline.cpp
// typedef std::pair<BackendCache, std::vector<OpCacheInfo>> PipelineInfo
ErrorCode Pipeline::execute() {
    _copyInputs();
    auto& mBackend = mInfo.first.cache.first;
    auto& mBackupBackend = mInfo.first.cache.second;
    mBackend->onExecuteBegin();
    // mInfo 类型为 std::pair<BackendCache, std::vector<OpCacheInfo>>
    for (auto& info : mInfo.second) {
        auto& buffer = info.executeBuffer;
//#define LOG_VERPOSE
#ifdef LOG_VERPOSE
        FUNC_PRINT_ALL(info.op->name()->c_str(), s);
#endif
        for (auto& cmdP : buffer.command) {
            auto& cmd = *cmdP;
            auto code = cmd.execution->onExecute(cmd.workInputs, cmd.workOutputs);
// #define LOG_VERPOSE
#ifdef LOG_VERPOSE
            auto dumpT = [](Tensor* t) {
                auto size = TensorUtils::getRawSize(t);
                size = size > 10 ? 10 : size;
                if (t->getType() == halide_type_of<float>()) {
                    for (int i=0; i<size; ++i) {
                        MNN_PRINT("%f, ", t->host<float>()[i]);
                    }
                } else {
                    for (int i=0; i<size; ++i) {
                        MNN_PRINT("%d, ", t->host<int>()[i]);
                    }
                }
                MNN_PRINT("\n");
            };
            if (/* cmd.op->name() && cmd.op->name()->str() == "/embed/embed_/Gather_output_0"*/
                cmd.op->type() == OpType_Convolution) {
                MNN_PRINT("%s Input begin:\n", EnumNameOpType(cmd.op->type()));
                for (auto t : cmd.workInputs) {
                    dumpT(t);
                }
                MNN_PRINT("%s Output begin:\n", EnumNameOpType(cmd.op->type()));
                for (auto t : cmd.workOutputs) {
                    dumpT(t);
                }
            }
#endif
            if (NO_ERROR != code) {
                mBackend->onExecuteEnd();
                return code;
            }
        }
    }
    mBackend->onExecuteEnd();
    return NO_ERROR;
}

1.1.1.1 VulkanBackend::onExecuteBegin

    在函数 Pipeline::execute 中调用 Backend::onExecuteBegin 函数的代码如下：

	mBackend->onExecuteBegin();

    onExecuteBegin 函数是个虚函数， mBackend->onExecuteBegin 调用是个多态，其基类为 Backend，此处 mBackend 为 VulkanBackend，其具体实现代码如下：

// source/backend/vulkan/image/backend/VulkanBackend.cpp
void VulkanBackend::onExecuteBegin() const {
    if (!mDirect) {
        mCmdBuffers.push_back(mCmdBuffer->get());
    }
    // FUNC_PRINT_ALL(mDynamicMemoryPool->computeSize(), f);
}

VulkanBasicExecutionDirect::onExecute

1.1.1.2 Execution::onExecute

    在函数 Pipeline::execute 中调用 Execution::onExecute 函数的代码如下：

            auto code = cmd.execution->onExecute(cmd.workInputs, cmd.workOutputs);

    Execution::onExecute 函数是个虚函数，对于 Vulkan 来说，主要有 VulkanBasicExecutionDirect 和 VulkanBasicExecutionInDirect，我们以 VulkanBasicExecutionDirect 进行分析：

// source/backend/vulkan/image/execution/VulkanBasicExecution.cpp
ErrorCode VulkanBasicExecutionDirect::onExecute(const std::vector<Tensor *> &inputs, const std::vector<Tensor *> &outputs) {
    auto extra = static_cast<VulkanBackend *>(backend());
    extra->pushCommand(mCmdBuffer->get());
    return NO_ERROR;
}

1.1.1.3 Backend::onExecuteEnd

    在函数 Pipeline::execute 中调用 Backend::onExecuteEnd 函数的代码如下：

	mBackend->onExecuteEnd();

    Backend::onExecuteEnd 函数是个虚函数，对于 Vulkan 来说为 VulkanBackend ，以下为其代码：

// source/backend/vulkan/image/backend/VulkanBackend.cpp
void VulkanBackend::onExecuteEnd() const {
    _finish();
}

1.1.1.3.1 _finish

// source/backend/vulkan/image/backend/VulkanBackend.cpp
void VulkanBackend::_finish() const {
    if (mCmdBuffers.empty()) {
        return;
    }
    VkSubmitInfo submit_info = {/* .sType                = */ VK_STRUCTURE_TYPE_SUBMIT_INFO,
                                /* .pNext                = */ nullptr,
                                /* .waitSemaphoreCount   = */ 0,
                                /* .pWaitSemaphores      = */ nullptr,
                                /* .pWaitDstStageMask    = */ nullptr,
                                /* .commandBufferCount   = */ (uint32_t)mCmdBuffers.size(),
                                /* .pCommandBuffers      = */ mCmdBuffers.data(),
                                /* .signalSemaphoreCount = */ 0,
                                /* .pSignalSemaphores    = */ nullptr};
    auto fenceReal           = mFence->get();
    mFence->reset();
    CALL_VK(vkQueueSubmit(device().acquireDefaultDevQueue(), 1, &submit_info, fenceReal));

    auto res = mFence->wait();
    MNN_VK_CHECK(res);
    mCmdBuffers.clear();
}

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