* Copyright (c) 2025 Huawei Technologies Co., Ltd.
* This program is free software, you can redistribute it and/or modify it under the terms and conditions of
* CANN Open Software License Agreement Version 2.0 (the "License").
* Please refer to the License for details. You may not use this file except in compliance with the License.
* THIS SOFTWARE IS PROVIDED ON AN "AS IS" BASIS, WITHOUT WARRANTIES OF ANY KIND, EITHER EXPRESS OR IMPLIED,
* INCLUDING BUT NOT LIMITED TO NON-INFRINGEMENT, MERCHANTABILITY, OR FITNESS FOR A PARTICULAR PURPOSE.
* See LICENSE in the root of the software repository for the full text of the License.
*/
#include <iostream>
#include <memory>
#include <type_traits>
#include <vector>
#include "acl/acl.h"
#include "aclnnop/aclnn_isin_tensor_scalar.h"
#define CHECK_RET(cond, return_expr) \
do { \
if (!(cond)) { \
return_expr; \
} \
} while (0)
#define LOG_PRINT(message, ...) \
do { \
printf(message, ##__VA_ARGS__); \
} while (0)
int64_t GetShapeSize(const std::vector<int64_t>& shape)
{
int64_t shape_size = 1;
for (auto i : shape) {
shape_size *= i;
}
return shape_size;
}
using StreamPtr = std::unique_ptr<std::remove_pointer<aclrtStream>::type, decltype(&aclrtDestroyStream)>;
using DeviceMemPtr = std::unique_ptr<void, decltype(&aclrtFree)>;
using TensorPtr = std::unique_ptr<aclTensor, decltype(&aclDestroyTensor)>;
using ScalarPtr = std::unique_ptr<aclScalar, decltype(&aclDestroyScalar)>;
int Init(int32_t deviceId, StreamPtr& stream, bool& initialized, bool& deviceSet)
{
auto ret = aclInit(nullptr);
CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("aclInit failed. ERROR: %d\n", ret); return ret);
initialized = true;
ret = aclrtSetDevice(deviceId);
CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("aclrtSetDevice failed. ERROR: %d\n", ret); return ret);
deviceSet = true;
aclrtStream rawStream = nullptr;
ret = aclrtCreateStream(&rawStream);
CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("aclrtCreateStream failed. ERROR: %d\n", ret); return ret);
stream.reset(rawStream);
return 0;
}
template <typename T>
int CreateAclTensor(const std::vector<T>& hostData, const std::vector<int64_t>& shape, aclDataType dataType,
DeviceMemPtr& deviceAddr, TensorPtr& tensor)
{
auto size = GetShapeSize(shape) * sizeof(T);
void* rawDeviceAddr = nullptr;
auto ret = aclrtMalloc(&rawDeviceAddr, size, ACL_MEM_MALLOC_HUGE_FIRST);
CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("aclrtMalloc failed. ERROR: %d\n", ret); return ret);
deviceAddr.reset(rawDeviceAddr);
ret = aclrtMemcpy(deviceAddr.get(), size, hostData.data(), size, ACL_MEMCPY_HOST_TO_DEVICE);
CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("aclrtMemcpy failed. ERROR: %d\n", ret); return ret);
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];
}
aclTensor* rawTensor = aclCreateTensor(shape.data(), shape.size(), dataType, strides.data(), 0,
aclFormat::ACL_FORMAT_ND, shape.data(), shape.size(), deviceAddr.get());
CHECK_RET(rawTensor != nullptr, LOG_PRINT("aclCreateTensor failed.\n"); return ACL_ERROR_FAILURE);
tensor.reset(rawTensor);
return 0;
}
aclError InitAcl(int32_t deviceId, StreamPtr& stream, bool& initialized, bool& deviceSet)
{
auto ret = Init(deviceId, stream, initialized, deviceSet);
CHECK_RET(ret == 0, LOG_PRINT("Init acl failed. ERROR: %d\n", ret); return ret);
return ACL_SUCCESS;
}
aclError CreateInputs(std::vector<int64_t>& elementShape, std::vector<int64_t>& outShape,
DeviceMemPtr& elementDeviceAddr, DeviceMemPtr& outDeviceAddr, TensorPtr& element, TensorPtr& out,
ScalarPtr& testElement, bool& assumeUnique, bool& invert)
{
std::vector<double> elementHostData = {0, 1, 2, 3, 2};
std::vector<char> outHostData = {0, 0, 0, 0, 0};
double testElementValue = 2;
aclScalar* rawScalar = aclCreateScalar(&testElementValue, aclDataType::ACL_DOUBLE);
CHECK_RET(rawScalar != nullptr, LOG_PRINT("aclCreateScalar failed.\n"); return ACL_ERROR_FAILURE);
testElement.reset(rawScalar);
auto ret = CreateAclTensor(elementHostData, elementShape, aclDataType::ACL_DOUBLE, elementDeviceAddr, element);
CHECK_RET(ret == ACL_SUCCESS, return ret);
ret = CreateAclTensor(outHostData, outShape, aclDataType::ACL_BOOL, outDeviceAddr, out);
CHECK_RET(ret == ACL_SUCCESS, return ret);
return ACL_SUCCESS;
}
aclError ExecOpApi(TensorPtr& element, ScalarPtr& testElement, bool assumeUnique, bool invert, TensorPtr& out,
DeviceMemPtr& workspaceAddr, uint64_t& workspaceSize, DeviceMemPtr& outDeviceAddr,
std::vector<int64_t>& outShape, StreamPtr& stream)
{
aclOpExecutor* executor;
auto ret = aclnnIsInTensorScalarGetWorkspaceSize(element.get(), testElement.get(), assumeUnique, invert, out.get(),
&workspaceSize, &executor);
CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("aclnnIsInTensorScalarGetWorkspaceSize failed. ERROR: %d\n", ret);
return ret);
if (workspaceSize > static_cast<uint64_t>(0)) {
void* rawWorkspaceAddr = nullptr;
ret = aclrtMalloc(&rawWorkspaceAddr, workspaceSize, ACL_MEM_MALLOC_HUGE_FIRST);
CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("allocate workspace failed. ERROR: %d\n", ret); return ret);
workspaceAddr.reset(rawWorkspaceAddr);
}
ret = aclnnIsInTensorScalar(workspaceAddr.get(), workspaceSize, executor, stream.get());
CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("aclnnIsInTensorScalar failed. ERROR: %d\n", ret); return ret);
ret = aclrtSynchronizeStream(stream.get());
CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("aclrtSynchronizeStream failed. ERROR: %d\n", ret); return ret);
auto size = GetShapeSize(outShape);
std::vector<char> resultData(size, 0);
ret = aclrtMemcpy(resultData.data(), resultData.size() * sizeof(resultData[0]), outDeviceAddr.get(),
size * sizeof(resultData[0]), ACL_MEMCPY_DEVICE_TO_HOST);
CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("copy result from device to host failed. ERROR: %d\n", ret); return ret);
for (int64_t i = 0; i < size; i++) {
LOG_PRINT("result[%ld] is: %d\n", i, resultData[i]);
}
return ACL_SUCCESS;
}
int main()
{
int32_t deviceId = 0;
bool initialized = false;
bool deviceSet = false;
std::shared_ptr<void> aclGuard(nullptr, [&](void*) {
if (deviceSet) {
aclrtResetDevice(deviceId);
}
if (initialized) {
aclFinalize();
}
});
StreamPtr stream(nullptr, &aclrtDestroyStream);
auto ret = InitAcl(deviceId, stream, initialized, deviceSet);
CHECK_RET(ret == ACL_SUCCESS, return ret);
std::vector<int64_t> elementShape = {5};
std::vector<int64_t> outShape = {5};
DeviceMemPtr elementDeviceAddr(nullptr, &aclrtFree);
DeviceMemPtr outDeviceAddr(nullptr, &aclrtFree);
TensorPtr element(nullptr, &aclDestroyTensor);
ScalarPtr testElement(nullptr, &aclDestroyScalar);
TensorPtr out(nullptr, &aclDestroyTensor);
bool assumeUnique = false;
bool invert = false;
ret = CreateInputs(elementShape, outShape, elementDeviceAddr, outDeviceAddr, element, out, testElement,
assumeUnique, invert);
CHECK_RET(ret == ACL_SUCCESS, return ret);
uint64_t workspaceSize = 0;
DeviceMemPtr workspaceAddr(nullptr, &aclrtFree);
ret = ExecOpApi(element, testElement, assumeUnique, invert, out, workspaceAddr, workspaceSize, outDeviceAddr,
outShape, stream);
CHECK_RET(ret == ACL_SUCCESS, return ret);
return 0;
}