aclnnNeScalar&aclnnInplaceNeScalar

Applicable Products

Product	Supported
Ascend 950PR/Ascend 950DT	√
Atlas A3 training products/Atlas A3 inference products	√
Atlas A2 training products/Atlas A2 inference products	√
Atlas 200I/500 A2 inference products	×
Atlas inference products	×
Atlas training products	√

Function

Description: Computes whether the value of each element in selfRef is not equal to the value of other.
Formula:

out_i​=(self_i \ne other)?[1]:[0]

selfRef_i​=(selfRef_i \ne other)?[1]:[0]

Function Prototype

aclnnNeScalar and aclnnInplaceNeScalar implement the same function. The differences in usage are as follows. Select the appropriate operator based on your actual scenario.
- aclnnNeScalar: Create a new output tensor object to store the computation result.
- aclnnInplaceNeScalar: No need to create a new output tensor object. The computation result is stored directly in the memory of the input tensor.
Each operator is divided into a two-phase API. You must first call the "aclnnNeScalarGetWorkspaceSize" or "aclnnInplaceNeScalarGetWorkspaceSize" API to obtain the input parameters and calculate the required workspace size based on the computation process, and then call the "aclnnNeScalar" or "aclnnInplaceNeScalar" API to perform the computation.

aclnnStatus aclnnNeScalarGetWorkspaceSize(
    const aclTensor *self,
    const aclScalar *other,
    aclTensor       *out,
    uint64_t        *workspaceSize,
    aclOpExecutor  **executor)

aclnnStatus aclnnNeScalar(
    void             *workspace,
    uint64_t          workspaceSize,
    aclOpExecutor    *executor,
    const aclrtStream stream)

aclnnStatus aclnnInplaceNeScalarGetWorkspaceSize(
    aclTensor       *selfRef,
    const aclScalar *other,
    uint64_t        *workspaceSize,
    aclOpExecutor  **executor)

aclnnStatus aclnnInplaceNeScalar(
    void             *workspace,
    uint64_t          workspaceSize,
    aclOpExecutor    *executor,
    aclrtStream       stream)

aclnnNeScalarGetWorkspaceSize

Parameters:

Parameter	Input/Output	Description	Instruction	Data Type	Data Format	Shape	Non-contiguous Tensor
self (aclTensor*)	Input	self in the formula.	Supports non-contiguous tensors.	DOUBLE, FLOAT16, FLOAT, BFLOAT16, INT64, INT32, INT8, UINT8, BOOL, INT16, COMPLEX64, COMPLEX128, UINT64	ND	0-8	√
other (aclScalar*)	Input	other in the formula.	-	DOUBLE, FLOAT16, FLOAT, BFLOAT16, INT64, INT32, INT8, UINT8, BOOL, INT16, COMPLEX64, COMPLEX128, UINT64	-	-	-
out (aclTensor*)	Output	out in the formula.	The data type of out must be convertible to BOOL.	DOUBLE, FLOAT16, FLOAT, BFLOAT16, INT64, INT32, INT8, UINT8, BOOL, INT16, COMPLEX64, COMPLEX128, UINT64, UINT32, UINT16	ND	0-8	√
workspaceSize (uint64_t*)	Output	Returns the workspace size to be requested on the Device side.	-	-	-	-	-
executor (aclOpExecutor**)	Output	Returns the op executor, which contains the operator computation flow.	-	-	-	-	-

Atlas A2 training products/Atlas A2 inference products, Atlas A3 training products/Atlas A3 inference products:
- self and other do not support UINT64.
- out does not support UINT64, UINT32, or UINT16.
Atlas training products:
- self and other do not support BFLOAT16 or UINT64.
- out does not support BFLOAT16, UINT64, UINT32, or UINT16.

Return value:

aclnnStatus: return code. For details, see aclnn Return Codes.

The first-phase API performs input parameter validation and returns an error in the following scenarios:

Return Value	Error Code	Description
ACLNN_ERR_PARAM_NULLPTR	161001	self, other, or out is a null pointer.
ACLNN_ERR_PARAM_INVALID	161002	The data type of self, other, or out is not within the supported range.
		The data types of self and other do not satisfy the data type deduction rules.
		The shapes of self and out are different.
		The number of dimensions of self and out exceeds 8.

aclnnInplaceNeScalar

Parameters:

Parameter	Input/Output	Description
workspace	Input	Address of the workspace memory applied for on the Device side.
workspaceSize	Input	Size of the workspace applied for on the Device side, obtained from the first-phase API aclnnNeScalarGetWorkspaceSize.
executor	Input	Op executor, which contains the operator computation process.
stream	Input	Specifies the stream for task execution.

Return value:

aclnnStatus: return code. For details, see aclnn Return Codes.

aclnnInplaceNeScalarGetWorkspaceSize

Parameters:

Parameter	Input/Output	Description	Instruction	Data Type	Data Format	Shape	Non-contiguous Tensor
selfRef (aclTensor*)	Input/Output	selfRef in the formula.	Supports non-contiguous tensors.	DOUBLE, FLOAT16, BFLOAT16, FLOAT, INT32, INT64, UINT64, INT8, UINT8, INT16, BOOL, COMPLEX64, COMPLEX128	ND	0-8	√
other (aclScalar*)	Input	The "other" in the formula.	-	DOUBLE, FLOAT16, BFLOAT16, FLOAT, INT32, INT64, UINT64, INT8, UINT8, INT16, BOOL, COMPLEX64, COMPLEX128	-	-	-
workspaceSize (uint64_t*)	Output	Returns the workspace size to be allocated on the Device side.	-	-	-	-	-
Executor (aclOpExecutor**)	Output	Returns the op executor, which contains the operator computation process.	-	-	-	-	-

Atlas A2 training products/Atlas A2 inference products, Atlas A3 training products/Atlas A3 inference products: UINT64 is not supported.
Atlas training products: BFLOAT16 and UINT64 are not supported.

Return value:

aclnnStatus: return code. For details, see aclnn Return Codes.

The first-phase API performs input parameter validation and returns an error in the following scenarios:

Return Value	Error Code	Description
ACLNN_ERR_PARAM_NULLPTR	161001	Indicates that selfRef or other is a null pointer.
ACLNN_ERR_PARAM_INVALID	161002	The data types of selfRef and other are not within the supported range.
		The data types of selfRef and other do not satisfy the data type deduction rules.
		The dimension of selfRef is greater than 8.

aclnnInplaceNeScalar

Parameters

Parameter	Input/Output	Description
workspace	Input	Address of the workspace memory applied for on the Device side.
workspaceSize	Input	Size of the workspace applied for on the Device side, obtained from the first-phase API aclnnInplaceNeScalarGetWorkspaceSize.
Executor	Input	Operator executor, which contains the operator computation flow.
stream	Input	Specifies the stream for executing the task.

Return value:

aclnnStatus: return code. For details, see aclnn Return Codes.

Constraints

Deterministic computation:
- aclnnNeScalar&aclnnInplaceNeScalar default to a deterministic implementation.

Example

The following provides example code for reference only. For details about compilation and running, see Compile and Run Samples.

Example code for calling the aclnnNeScalar&aclnnInplaceNeScalar API:

#include <iostream>
#include <vector>
#include "acl/acl.h"
#include "aclnnop/aclnn_ne_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 shapeSize = 1;
    for (auto i : shape) {
        shapeSize *= i;
    }
    return shapeSize;
}

int Init(int32_t deviceId, aclrtStream *stream)
{
    // Boilerplate: initialize resources.
    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);
    // Call aclrtMalloc to allocate device memory.
    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);
    // Call aclrtMemcpy to copy host data to device memory.
    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);

    // Compute strides for a contiguous tensor.
    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 aclCreateTensor to create an aclTensor.
    *tensor = aclCreateTensor(shape.data(),
        shape.size(),
        dataType,
        strides.data(),
        0,
        aclFormat::ACL_FORMAT_ND,
        shape.data(),
        shape.size(),
        *deviceAddr);
    return 0;
}

int main()
{
    // 1. (Boilerplate) Initialize device/stream. See the acl API manual.
    // Fill in the deviceId based on your actual device.
    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);
    // 2. Construct inputs and outputs. Customize based on the API definition.
    std::vector<int64_t> selfShape = {4, 2};
    std::vector<int64_t> otherShape = {4, 2};
    std::vector<int64_t> outShape = {4, 2};
    void *selfDeviceAddr = nullptr;
    void *otherDeviceAddr = nullptr;
    void* outDeviceAddr = nullptr;
    aclTensor *self = nullptr;
    aclScalar *other = nullptr;
    aclTensor *out = nullptr;
    std::vector<double> selfHostData = {0, 1, 2, 3, 4, 5, 6, 7};
    std::vector<double> outHostData = {0, 0, 0, 0, 0, 0, 0, 0};
    double otherValue = 1.0f;

    // Create self aclTensor.
    ret = CreateAclTensor(selfHostData, selfShape, &selfDeviceAddr, aclDataType::ACL_DOUBLE, &self);
    CHECK_RET(ret == ACL_SUCCESS, return ret);
    // Create other aclScalar.
    other = aclCreateScalar(&otherValue, aclDataType::ACL_DOUBLE);
    CHECK_RET(ret == ACL_SUCCESS, return ret);
    // Create out aclTensor.
    ret = CreateAclTensor(outHostData, outShape, &outDeviceAddr, aclDataType::ACL_DOUBLE, &out);
    CHECK_RET(ret == ACL_SUCCESS, return ret);

    // Example of calling aclnnNeScalar.
    // 3. Call the CANN operator library API. Replace with the specific API name.
    uint64_t workspaceSize = 0;
    aclOpExecutor *executor;
    // Call the first-phase API of aclnnNeScalar.
    ret = aclnnNeScalarGetWorkspaceSize(self, other, out, &workspaceSize, &executor);
    CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("aclnnNeScalarGetWorkspaceSize failed. ERROR: %d\n", ret); return ret);
    // Allocate device memory based on the workspaceSize computed by the first-phase API.
    void *workspaceAddr = nullptr;
    if (workspaceSize > 0) {
        ret = aclrtMalloc(&workspaceAddr, workspaceSize, ACL_MEM_MALLOC_HUGE_FIRST);
        CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("allocate workspace failed. ERROR: %d\n", ret); return ret);
    }
    // Call the second-phase API of aclnnNeScalar.
    ret = aclnnNeScalar(workspaceAddr, workspaceSize, executor, stream);
    CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("aclnnNeScalar failed. ERROR: %d\n", ret); return ret);
    // 4. (Boilerplate) Synchronize and wait for task completion.
    ret = aclrtSynchronizeStream(stream);
    CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("aclrtSynchronizeStream failed. ERROR: %d\n", ret); return ret);
    // 5. Retrieve the output value. Copy the result from device memory to host. Modify based on the specific API definition.
    auto size = GetShapeSize(selfShape);
    std::vector<double> resultData(size, 0);
    ret = aclrtMemcpy(resultData.data(),
        resultData.size() * sizeof(resultData[0]),
        outDeviceAddr,
        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: %f\n", i, resultData[i]);
    }

    // Example of calling aclnnInplaceNeScalar.
    // 3. Call the CANN operator library API. Replace with the specific API name.
    LOG_PRINT("\ntest aclnnInplaceNeScalar\n");
    // Call the first-phase API of aclnnInplaceNeScalar.
    ret = aclnnInplaceNeScalarGetWorkspaceSize(self, other, &workspaceSize, &executor);
    CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("aclnnInplaceNeScalarGetWorkspaceSize failed. ERROR: %d\n", ret); return ret);
    // Allocate device memory based on the workspaceSize computed by the first-phase API.
    if (workspaceSize > 0) {
        ret = aclrtMalloc(&workspaceAddr, workspaceSize, ACL_MEM_MALLOC_HUGE_FIRST);
        CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("allocate workspace failed. ERROR: %d\n", ret); return ret);
    }
    // Call the second-phase API of aclnnNeScalar.
    ret = aclnnInplaceNeScalar(workspaceAddr, workspaceSize, executor, stream);
    CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("aclnnInplaceNeScalar failed. ERROR: %d\n", ret); return ret);
    // 4. (Boilerplate) Synchronize and wait for task completion.
    ret = aclrtSynchronizeStream(stream);
    CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("aclrtSynchronizeStream failed. ERROR: %d\n", ret); return ret);
    // 5. Retrieve the output value. Copy the result from device memory to host. Modify based on the specific API definition.
    ret = aclrtMemcpy(resultData.data(),
        resultData.size() * sizeof(resultData[0]),
        selfDeviceAddr,
        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: %f\n", i, resultData[i]);
    }

    // 6. Release aclTensor. Modify based on the specific API definition.
    aclDestroyTensor(self);
    aclDestroyScalar(other);
    aclDestroyTensor(out);

    // 7. Release device resources. Modify based on the specific API definition.
    aclrtFree(selfDeviceAddr);
    aclrtFree(otherDeviceAddr);
    aclrtFree(outDeviceAddr);
    if (workspaceSize > 0) {
       aclrtFree(workspaceAddr);
    }
    aclrtDestroyStream(stream);
    aclrtResetDevice(deviceId);
    aclFinalize();
    return 0;
}```