Istft

该样例旨在提供快速上手、开发和调试算子的最小化实现，其核心目标是使用最精简的代码展示算子的核心功能，而非提供生产级的安全保障。

不推荐用户直接将样例作为业务代码，若用户将示例代码应用在自身的真实业务场景中且发生了安全问题，则需用户自行承担。

#include <iostream>
#include <vector>
#include "asdsip.h"
#include "acl/acl.h"
#include "aclnn/acl_meta.h"
using namespace AsdSip;

#define CHECK_RET(cond, return_expr) \
    do {                             \
        if (!(cond)) {               \
            return_expr;             \
        }                            \
    } while (0)

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

#define ASD_STATUS_CHECK(err)                                                \
    do {                                                                     \
        AsdSip::AspbStatus err_ = (err);                                     \
        if (err_ != AsdSip::ErrorType::ACL_SUCCESS) {                                      \
            std::cout << "Execute failed." << std::endl; \
            exit(-1);                                                        \
        }                                                                    \
    } 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)
{
    // 固定写法，AscendCL初始化
    auto ret = aclInit(nullptr);
    CHECK_RET(ret == ::ACL_SUCCESS, LOG_PRINT("aclInit failed. ERROR: %d\n", ret); return ret);
    ret = aclrtSetDevice(deviceId);
    CHECK_RET(ret == ::ACL_SUCCESS, LOG_PRINT("aclrtSetDevice failed. ERROR: %d\n", ret); return ret);
    ret = aclrtCreateStream(stream);
    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);
    // 调用aclrtMalloc申请device侧内存
    auto ret = aclrtMalloc(deviceAddr, size, ACL_MEM_MALLOC_HUGE_FIRST);
    CHECK_RET(ret == ::ACL_SUCCESS, LOG_PRINT("aclrtMalloc failed. ERROR: %d\n", ret); return ret);
    // 调用aclrtMemcpy将host侧数据复制到device侧内存上
    ret = aclrtMemcpy(*deviceAddr, size, hostData.data(), size, ACL_MEMCPY_HOST_TO_DEVICE);
    CHECK_RET(ret == ::ACL_SUCCESS, LOG_PRINT("aclrtMemcpy failed. ERROR: %d\n", ret); return ret);

    // 计算连续tensor的strides
    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];
    }

    // 调用aclCreateTensor接口创建aclTensor
    *tensor = aclCreateTensor(shape.data(),
        shape.size(),
        dataType,
        strides.data(),
        0,
        aclFormat::ACL_FORMAT_ND,
        shape.data(),
        shape.size(),
        *deviceAddr);
    return 0;
}

int main()
{
    int32_t deviceId = 0;
    aclrtStream stream;
    auto ret = Init(deviceId, &stream);
    CHECK_RET(ret == ::ACL_SUCCESS, LOG_PRINT("Init acl failed. ERROR: %d\n", ret); return ret);

    // 创造tensor的Host侧数据
    int64_t channel = 10, nFrames = 20, nFft = 16, hopLen = 4, winLen = 16;
    int64_t outLen = nFft + hopLen * (nFrames - 1) - nFft / 2 - nFft / 2;
    bool returnComplex = true;
    bool center = true, normalized = false, onesidedOpt = false;
    const int64_t tensorInSize = channel * nFrames * nFft;
    const int64_t tensorWinSize = winLen;
    const int64_t tensorOutSize = channel * outLen;
    std::vector<int64_t> selfShape = {channel, nFft, nFrames};
    std::vector<int64_t> winShape = {winLen};
    std::vector<int64_t> outShape = {channel, outLen};

    std::vector<std::complex<float>> inputHostData(tensorInSize, std::complex<float>(0, 0));
    for (int i = 0; i < tensorInSize; i++) {
        inputHostData[i] = std::complex<float>(i *  200.0f / tensorInSize - 100, i *  100.0f / tensorInSize - 50);
    }
    std::vector<float> winHostData(tensorWinSize, 0.0f);
    for (int i = 0; i < tensorWinSize; i++) {
        winHostData[i] = 1.0f / winLen * i ;
    }
    std::vector<std::complex<float>> outHostData(tensorOutSize, std::complex<float>(0, 0));

    void *inputDeviceAddr = nullptr;
    void *winDeviceAddr = nullptr;
    void *outDeviceAddr = nullptr;
    aclTensor *input = nullptr;
    aclTensor *win = nullptr;
    aclTensor *out = nullptr;
    ret = CreateAclTensor(inputHostData, selfShape, &inputDeviceAddr, aclDataType::ACL_COMPLEX64, &input);
    CHECK_RET(ret == ::ACL_SUCCESS, return ret);
    ret = CreateAclTensor(winHostData, winShape, &winDeviceAddr, aclDataType::ACL_FLOAT, &win);
    CHECK_RET(ret == ::ACL_SUCCESS, return ret);
    ret = CreateAclTensor(outHostData, outShape, &outDeviceAddr, aclDataType::ACL_COMPLEX64, &out);
    CHECK_RET(ret == ::ACL_SUCCESS, return ret);

    asdFftHandle handle;
    asdFftCreate(handle);
    asdFftIstftMakePlan(handle, input, nFft, hopLen, winLen, center, normalized, onesidedOpt, 0, returnComplex);

    size_t work_size;
    asdFftGetWorkspaceSize(handle, work_size);
    void *workspaceAddr = nullptr;
    if (work_size > 0) {
        ret = aclrtMalloc(&workspaceAddr, static_cast<int64_t>(work_size), ACL_MEM_MALLOC_HUGE_FIRST);
        CHECK_RET(ret == ::ACL_SUCCESS, LOG_PRINT("allocate workspace failed. ERROR: %d\n", ret); return ret);
    }
    asdFftSetWorkspace(handle, (uint8_t *)workspaceAddr);

    asdFftSetStream(handle, stream);
    ASD_STATUS_CHECK(asdFftExecIstft(handle, input, win, out));

    ret = aclrtSynchronizeStream(stream);
    CHECK_RET(ret == ::ACL_SUCCESS, LOG_PRINT("aclrtSynchronizeStream failed. ERROR: %d\n", ret); return ret);

    asdFftDestroy(handle);

    auto size = GetShapeSize(outShape);
    std::vector<std::complex<float>> outData(size, 0);
    ret = aclrtMemcpy(outData.data(),
        outData.size() * sizeof(outData[0]),
        outDeviceAddr,
        size * sizeof(outData[0]),
        ACL_MEMCPY_DEVICE_TO_HOST);

    // 打印输出tensor值中前16个
    for (int64_t i = 0; i < 16; i++) {
        std::cout << static_cast<std::complex<float>>(outData[i]) << "\t";
    }
    std::cout << "\nend result" << std::endl;
    std::cout << "Execute successfully." << std::endl;

    aclDestroyTensor(input);
    aclDestroyTensor(win);
    aclDestroyTensor(out);
    aclrtFree(inputDeviceAddr);
    aclrtFree(winDeviceAddr);
    aclrtFree(outDeviceAddr);
    if (work_size > 0) {
        aclrtFree(workspaceAddr);
    }
    aclrtDestroyStream(stream);
    aclrtResetDevice(deviceId);
    aclFinalize();
    return 0;
}