自定义后端

Backend是MNN对计算设备的抽象。MNN当前已经支持CPU、Vulkan、OpenCL、Metal等Backend,只在计算设备暂未支持时新增Backend,新增Op,请参阅新增Op文档

声明

所有新增Backend都需继承Backend类,并实现所有纯虚函数。

class XPUBackend final : public Backend {
  XPUBackend(MNNForwardType type, MemoryMode mode);
  virtual ~XPUBackend();
  virtual Execution* onCreate(const std::vector<Tensor*>& inputs, const std::vector<Tensor*>& outputs, const MNN::Op* op) override;
  virtual void onExecuteBegin() const override;
  virtual void onExecuteEnd() const override;
  virtual bool onAcquireBuffer(const Tensor* tensor, StorageType storageType) override;
  virtual bool onReleaseBuffer(const Tensor* tensor, StorageType storageType) override;
  virtual bool onClearBuffer() override;
  virtual void onCopyBuffer(const Tensor* srcTensor, const Tensor* dstTensor) const override;
}

构造与销毁

Backend构造时,可以额外指定内存环境,在内存受限环境中,应避免非必要的内存使用。可以在构造函数中,完成对计算设备访问的必要初始化,如GPU下预加载shader等。

/** backend memory mode */
enum MemoryMode {
    /** use memory without limit. */
    NORMAL = 0,
    /** use memory thriftily. */
    LIMIT = 1
};
/**
 * @brief initializer.
 * @param type  forward type.
 * @param mode  memory mode.
 */
Backend(MNNForwardType type, MemoryMode mode = NORMAL);

Execution创建

Backend需要通过onCreate为op创建出exection实例:

virtual Execution* onCreate(const std::vector<Tensor*>& inputs, const std::vector<Tensor*>& outputs, const MNN::Op* op) override;

可以在方法内根据op类型创建,但更建议提供注册接口:

class XPUBackend final : public Backend {
    // ...
    class Creator {
    public:
        /**
         * @brief create execution for given input, op on metal backend.
         * @param inputs    given input tensors.
         * @param op        given op.
         * @param backend   metal backend.
         * @return created execution if supported, NULL otherwise.
         */
        virtual Execution *onCreate(const std::vector<Tensor *> &inputs, const MNN::Op *op,
                                    Backend *backend) const = 0;
    };
    /**
     * @brief register creator for given op type.
     * @param type      given op type.
     * @param creator   registering creator.
     */
    static void addCreator(OpType type, Creator *creator);
    // ...
};
template <class T>
class XPUCreatorRegister {
public:
    /**
     * @brief initializer. register T creator for given op type.
     * @param type  given op type.
     */
    XPUCreatorRegister(OpType type) {
        T *test = new T;
        XPUBackend::addCreator(type, test);
    }
};

这样,Op Execution中,就可以通过注册追加Op类型:

class XPUPoolingCreator : public XPUBackend::Creator {
public:
    virtual Execution *onCreate(const std::vector<Tensor *> &inputs, const MNN::Op *op, Backend *backend) const {
        return new XPUPooling(backend, op->main_as_Pool());
    }
};
static XPUCreatorRegister<XPUPoolingCreator> __reg(OpType_Pooling);

内存管理

Backend通过onAcquireBuffer为tensor分配内存,通过onReleaseBuffer为tensor释放内存。内存有三种存储模式:STATIC内存不复用,一般用于op常量存储;DYNAMIC内存可复用,一般用于变量存储;DYNAMIC_SEPERATE内存在pipeline间可复用,一般用于pipeline常量存储。_onAcquireBuffer__onReleaseBuffer_中可以不实际分配/释放内存,只记录内存用量变更,在_onAllocateBuffer_调用时,再根据用量计算出优化方案,一次性完成分配/释放。

/** backend buffer storage type */
enum StorageType {
    /**
     use NOT reusable memory.
     - allocates memory when `onAcquireBuffer` is called.
     - releases memory when `onReleaseBuffer` is called or when the backend is deleted.
     - do NOTHING when `onClearBuffer` is called.
     */
    STATIC,
    /**
     use reusable memory.
     - allocates or reuses memory when `onAcquireBuffer` is called. prefers reusing.
     - collects memory for reuse when `onReleaseBuffer` is called
     - releases memory when `onClearBuffer` is called or when the backend is deleted.
     */
    DYNAMIC,
    /**
     use NOT reusable memory.
     - allocates memory when `onAcquireBuffer` is called.
     - do NOTHING when `onReleaseBuffer` is called.
     - releases memory when `onClearBuffer` is called or when the backend is deleted.
     */
    DYNAMIC_SEPERATE
};
/**
 * @brief allocate buffer of tensor for given storage type.
 * @param tensor        buffer provider.
 * @param storageType   buffer storage type.
 * @return success or not.
 */
virtual bool onAcquireBuffer(const Tensor* tensor, StorageType storageType) = 0;
/**
 * @brief release buffer of tensor for given storage type.
 * @param tensor        buffer provider.
 * @param storageType   buffer storage type.
 * @return success or not.
 */
virtual bool onReleaseBuffer(const Tensor* tensor, StorageType storageType) = 0;

在所有内存都分配完成后,backend会收到onAllocateBuffer回调:

/**
 * @brief callback after all buffers needed by backend ops were allocated.
 * @return success or not. (result not used currently)
 */
virtual bool onAllocateBuffer() {
    return true;
}

Backend在调用onClearBuffer时,需要释放所有DYNAMICDYNAMIC_SEPERATE存储模式的内存:

/**
 * @brief clear all dynamic buffers.
 * @return success or not.
 */
virtual bool onClearBuffer() = 0;

此外,backend还需要负责tensor数据的拷贝:

/**
 * @brief copy buffer from tensor to tensor.
 * @param srcTensor source buffer provider.
 * @param dstTensor dest buffer provider.
 */
virtual void onCopyBuffer(const Tensor* srcTensor, const Tensor* dstTensor) const = 0;

拷贝可能在backend内部,也可能在backend与CPU backend之间。 拷贝需要处理Tensor间的布局转换,相同布局时,可以直接拷贝数据;不同布局,如**NHWC****NC4HW4**,则一般需要做特殊转换。

Pipeline回调

Backend在pipeline执行的各个周期都会收到回调,onResizeBeginonResizeEnd在调整内存分配前后调用(op的onResize会在此间调用);onExecuteBeginonExecuteEnd在op执行前后调用(op的onExecute会在此间调用);onWaitFinish相对特殊,由用户主动调用,异步执行的pipeline需要同步等待完成。

/**
 * @brief callback before resize ops.
 */
virtual void onResizeBegin();
/**
 * @brief callback after resize ops.
 */
virtual void onResizeEnd();
/**
 * @brief callback before executing ops.
 */
virtual void onExecuteBegin() const = 0;
/**
 * @brief callback after executing ops.
 */
virtual void onExecuteEnd() const = 0;

注册Backend

最后,定义Backend Creator,注册方法中调用MNNInsertExtraBackendCreator就可以完成Backend的注册,这里的注册方法需要在BackendRegister.cpp中声明并调用:

class XPUBackendCreator : public BackendCreator {
    virtual Backend *onCreate(const Backend::Info &info) const {
        return new MetalBackend;
    }
};
void registerCPUBackendCreator() {
    MNNInsertExtraBackendCreator(MNN_FORWARD_CPU, new CPUBackendCreator);
};

使用cmake编译时,完成代码修改后,也需要相应修改CMakeLists.txt。