aclnnMhcPost

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产品支持情况

产品 是否支持
Ascend 950PR/Ascend 950DT
Atlas A3 训练系列产品/Atlas A3 推理系列产品
Atlas A2 训练系列产品/Atlas A2 推理系列产品
Atlas 200I/500 A2 推理产品 ×
Atlas 推理系列产品 ×
Atlas 训练系列产品 ×

功能说明

  • 接口功能:MhcPost基于一系列计算对mHC架构中上一层输出htouth_{t}^{out}进行Post Mapping,对上一层的输入xlx_l进行Res Mapping,然后对二者进行残差连接,得到下一层的输入xl+1x_{l+1}

  • 计算公式:

    xl+1=(Hlres)T×xl+hlout⊗Htpostx_{l+1} = (H_{l}^{res})^{T} \times x_l + h_{l}^{out} \otimes H_{t}^{post}

函数原型

算子执行接口为两段式接口,必须先调用"aclnnMhcPostGetWorkspaceSize"接口获取计算所需workspace大小以及包含了算子计算流程的执行器,再调用"aclnnMhcPost"接口执行计算。

aclnnStatus aclnnMhcPostGetWorkspaceSize(
    const aclTensor  *x,
    const aclTensor  *hRes,
    const aclTensor  *hOut,
    const aclTensor  *hPost,
    aclTensor        *out,
    uint64_t         *workspaceSize,
    aclOpExecutor    **executor)
aclnnStatus aclnnMhcPost(
    void           *workspace,
    uint64_t        workspaceSize,
    aclOpExecutor  *executor,
    aclrtStream     stream)

aclnnMhcPostGetWorkspaceSize

  • 参数说明:

    参数名 输入/输出 描述 使用说明 数据类型 数据格式 维度(shape) 非连续Tensor
    x 输入 待计算的张量,表示网络中mHC层的输入数据。 - FLOAT16、BFLOAT16 ND [B,S,N,D]、[T,N,D]
    hRes 输入 mHC的hRes变换矩阵,是做完sinkhorn变换后的双随机矩阵。 - FLOAT32 ND [B,S,N,N]、[T,N,N]
    hOut 输入 Atten/MLP层的输出。 数据类型与x相同。 FLOAT16、BFLOAT16 ND [B,S,D]、[T,D]
    hPost 输入 mHC的hPost变换矩阵。 - FLOAT32 ND [B,S,N]、[T,N]
    out 输出 网络中mHC层的输出数据,作为下一层的输入。 数据类型与x相同。 FLOAT16、BFLOAT16 ND [B,S,N,D]、[T,N,D] -
    workspaceSize 输出 返回需要在Device侧申请的workspace大小。 - - - - -
    executor 输出 返回op执行器,包含了算子计算流程。 - - - - -
  • 返回值:

    返回aclnnStatus状态码,具体参见aclnn返回码

    第一段接口完成入参校验,出现以下场景时报错:

    返回值 错误码 描述
    ACLNN_ERR_PARAM_NULLPTR 161001 x、hRes、hOut、hPost、out存在空指针。
    ACLNN_ERR_PARAM_INVALID 161002 x、hRes、hOut、hPost、out的数据类型不在支持的范围内。
    x、hRes、hOut、hPost、out的shape维度不在支持的范围内。
    x、hRes、hOut、hPost、out的数据类型或shape不匹配。

aclnnMhcPost

  • 参数说明:

    参数名 输入/输出 描述
    workspace 输入 在Device侧申请的workspace内存地址。
    workspaceSize 输入 在Device侧申请的workspace大小,由第一段接口aclnnMhcPostGetWorkspaceSize获取。
    executor 输入 op执行器,包含了算子计算流程。
    stream 输入 指定执行任务的stream流。
  • 返回值:

    返回aclnnStatus状态码,具体参见aclnn返回码

约束说明

  • aclnnMhcPost默认确定性实现。

调用示例

示例代码如下,仅供参考,具体编译和执行过程请参考编译与运行样例

#include <iostream>
#include <vector>
#include <cmath>
#include <cstring>
#include "acl/acl.h"
#include "aclnnop/aclnn_mhc_post.h"
#include "securec.h"

using namespace std;

namespace {

#define CHECK_RET(cond) ((cond) ? true :(false))

#define LOG_PRINT(message, ...)                                                                                        \
    do {                                                                                                               \
        printf(message, ##__VA_ARGS__);                                                                                \
    } while (0)

int64_t GetShapeSize(const std::vector<int64_t> &shape) {
    int64_t shapeSize = 1;
    for (auto i : shape) {
        shapeSize *= i;
    }
    return shapeSize;
}

int Init(int32_t deviceId, aclrtStream *stream) {
    // Fixed writing method, resource initialization.
    auto ret = aclInit(nullptr);
    if (!CHECK_RET(ret == ACL_SUCCESS)) {
        LOG_PRINT("aclInit failed. ERROR: %d\n", ret);
        return ret;
    }
    ret = aclrtSetDevice(deviceId);
    if (!CHECK_RET(ret == ACL_SUCCESS)) {
        LOG_PRINT("aclrtSetDevice failed. ERROR: %d\n", ret);
        return ret;
    }
    ret = aclrtCreateStream(stream);
    if (!CHECK_RET(ret == ACL_SUCCESS)) {
        LOG_PRINT("aclrtCreateStream failed. ERROR: %d\n", ret);
        return ret;
    }
    return 0;
}

template <typename T>
int CreateAclTensor(const std::vector<T> &hostData, const std::vector<int64_t> &shape, void **deviceAddr,
                    aclDataType dataType, aclTensor **tensor) {
    auto size = GetShapeSize(shape) * sizeof(T);
    // Call aclrtMalloc to request device side memory.
    auto ret = aclrtMalloc(deviceAddr, size, ACL_MEM_MALLOC_HUGE_FIRST);
    if (!CHECK_RET(ret == ACL_SUCCESS)) {
        LOG_PRINT("aclrtMalloc failed. ERROR: %d\n", ret);
        return ret;
    }
    // Call aclrtMemcpy to copy host side data to device side memory.
    ret = aclrtMemcpy(*deviceAddr, size, hostData.data(), size, ACL_MEMCPY_HOST_TO_DEVICE);
    if (!CHECK_RET(ret == ACL_SUCCESS)) {
        LOG_PRINT("aclrtMemcpy failed. ERROR: %d\n", ret);
        return ret;
    }

    // Calculate the strides of continuous tensors.
    std::vector<int64_t> strides(shape.size(), 1);
    for (int64_t i = shape.size() - 2; i >= 0; i--) {
        strides[i] = shape[i + 1] * strides[i + 1];
    }

    // Call the aclCreateTensor interface to create aclTensor.
    *tensor = aclCreateTensor(shape.data(), shape.size(), dataType, strides.data(), 0, aclFormat::ACL_FORMAT_ND,
                              shape.data(), shape.size(), *deviceAddr);
    return 0;
}

} // namespace

int main() {
    // 1. (Fixed writing method)  device/stream initialization. Refer to the API's external interface list.
    // Fill in the deviceId based on your actual device.
    int32_t deviceId = 0;
    aclrtStream stream;
    auto ret = Init(deviceId, &stream);
    if (!CHECK_RET(ret == ACL_SUCCESS)) {
        LOG_PRINT("Init acl failed. ERROR: %d\n", ret);
        return ret;
    }

    // 2. To construct input and output, it is necessary to customize the construction according to the API interface.
    // Example: BSND format (B, S, n, D)
    std::vector<int64_t> xShape = {1, 1024, 4, 5120};   // BSND
    std::vector<int64_t> hResShape = {1, 1024, 4, 4};   // BSND
    std::vector<int64_t> hOutShape = {1, 1024, 5120};   // BSD
    std::vector<int64_t> hPostShape = {1, 1024, 4};     // BSn
    std::vector<int64_t> outShape = {1, 1024, 4, 5120};  // BSND

    void *xDeviceAddr = nullptr;
    void *hResDeviceAddr = nullptr;
    void *hOutDeviceAddr = nullptr;
    void *hPostDeviceAddr = nullptr;
    void *outDeviceAddr = nullptr;

    aclTensor *xTensor = nullptr;
    aclTensor *hResTensor = nullptr;
    aclTensor *hOutTensor = nullptr;
    aclTensor *hPostTensor = nullptr;
    aclTensor *outTensor = nullptr;

    int64_t xShapeSize = GetShapeSize(xShape);
    int64_t hResShapeSize = GetShapeSize(hResShape);
    int64_t hOutShapeSize = GetShapeSize(hOutShape);
    int64_t hPostShapeSize = GetShapeSize(hPostShape);
    int64_t outShapeSize = GetShapeSize(outShape);

    std::vector<aclFloat16> xHostData(xShapeSize, aclFloatToFloat16(1.0f));
    std::vector<float> hResHostData(hResShapeSize, 1.0f);
    std::vector<aclFloat16> hOutHostData(hOutShapeSize, aclFloatToFloat16(1.0f));
    std::vector<float> hPostHostData(hPostShapeSize, 1.0f);
    std::vector<aclFloat16> outHostData(outShapeSize, aclFloatToFloat16(0.0f));

    // Create x aclTensor.
    ret = CreateAclTensor(xHostData, xShape, &xDeviceAddr, aclDataType::ACL_FLOAT16, &xTensor);
    if (!CHECK_RET(ret == ACL_SUCCESS)) {
        return ret;
    }
    // Create hRes aclTensor.
    ret = CreateAclTensor(hResHostData, hResShape, &hResDeviceAddr, aclDataType::ACL_FLOAT, &hResTensor);
    if (!CHECK_RET(ret == ACL_SUCCESS)) {
        return ret;
    }
    // Create hOut aclTensor.
    ret = CreateAclTensor(hOutHostData, hOutShape, &hOutDeviceAddr, aclDataType::ACL_FLOAT16, &hOutTensor);
    if (!CHECK_RET(ret == ACL_SUCCESS)) {
        return ret;
    }
    // Create hPost aclTensor.
    ret = CreateAclTensor(hPostHostData, hPostShape, &hPostDeviceAddr, aclDataType::ACL_FLOAT, &hPostTensor);
    if (!CHECK_RET(ret == ACL_SUCCESS)) {
        return ret;
    }
    // Create out aclTensor.
    ret = CreateAclTensor(outHostData, outShape, &outDeviceAddr, aclDataType::ACL_FLOAT16, &outTensor);
    if (!CHECK_RET(ret == ACL_SUCCESS)) {
        return ret;
    }

    // 3. Call CANN operator library API.
    uint64_t workspaceSize = 0;
    aclOpExecutor *executor;
    // Call the first interface.
    ret = aclnnMhcPostGetWorkspaceSize(
        xTensor, hResTensor, hOutTensor, hPostTensor, outTensor,
        &workspaceSize, &executor);
    if (!CHECK_RET(ret == ACL_SUCCESS)) {
        LOG_PRINT("aclnnMhcPostGetWorkspaceSize failed. ERROR: %d\n", ret);
        return ret;
    }
    // Apply for device memory based on the workspaceSize calculated from the first interface paragraph.
    void *workspaceAddr = nullptr;
    if (workspaceSize > 0U) {
        ret = aclrtMalloc(&workspaceAddr, workspaceSize, ACL_MEM_MALLOC_HUGE_FIRST);
        if (!CHECK_RET(ret == ACL_SUCCESS)) {
            LOG_PRINT("allocate workspace failed. ERROR: %d\n", ret);
            return ret;
        }
    }
    // Call the second interface.
    ret = aclnnMhcPost(workspaceAddr, workspaceSize, executor, stream);
    if (!CHECK_RET(ret == ACL_SUCCESS)) {
        LOG_PRINT("aclnnMhcPost failed. ERROR: %d\n", ret);
        return ret;
    }

    // 4. (Fixed writing method) Synchronize and wait for task execution to end.
    ret = aclrtSynchronizeStream(stream);
    if (!CHECK_RET(ret == ACL_SUCCESS)) {
        LOG_PRINT("aclrtSynchronizeStream failed. ERROR: %d\n", ret);
        return ret;
    }

    // 5. Retrieve the output value, copy the result from the device side memory to the host side.
    auto size = GetShapeSize(outShape);
    std::vector<aclFloat16> resultData(size, aclFloatToFloat16(0.0f));
    ret = aclrtMemcpy(resultData.data(), resultData.size() * sizeof(resultData[0]), outDeviceAddr,
                      size * sizeof(resultData[0]), ACL_MEMCPY_DEVICE_TO_HOST);
    if (!CHECK_RET(ret == ACL_SUCCESS)) {
        LOG_PRINT("copy result from device to host failed. ERROR: %d\n", ret);
        return ret;
    }
    // 6. Release resources.
    aclDestroyTensor(xTensor);
    aclDestroyTensor(hResTensor);
    aclDestroyTensor(hOutTensor);
    aclDestroyTensor(hPostTensor);
    aclDestroyTensor(outTensor);
    aclrtFree(xDeviceAddr);
    aclrtFree(hResDeviceAddr);
    aclrtFree(hOutDeviceAddr);
    aclrtFree(hPostDeviceAddr);
    aclrtFree(outDeviceAddr);
    if (workspaceSize > 0U) {
        aclrtFree(workspaceAddr);
    }
    aclrtDestroyStream(stream);
    aclrtResetDevice(deviceId);
    aclFinalize();
    return 0;
}