aclnnThreshold&aclnnInplaceThreshold
Supported Products
| Product | Supported |
|---|---|
| √ | |
| √ | |
| × | |
| × | |
| √ |
Function
- Description: Sets the threshold for input x. If elements in x are greater than threshold, the elements are returned. Otherwise, value is returned.
- Formula:
Prototype
aclnnThreshold and aclnnInplaceThreshold implement the same function in different ways. Select a proper operator based on your requirements. The differences are as follows:
- aclnnThreshold: An output tensor object needs to be created to store the computation result.
- aclnnInplaceThreshold: No output tensor object needs to be created, and the computation result is stored in the memory of the input tensor.
Each operator has two-phase API calls. First, aclnnThresholdGetWorkspaceSize or aclnnInplaceThresholdGetWorkspaceSize is called to obtain the workspace size required for computation and the executor that contains the operator computation process. Then, aclnnThreshold or aclnnInplaceThreshold is called to perform computation.
aclnnStatus aclnnThresholdGetWorkspaceSize(
const aclTensor* self,
const aclScalar* threshold,
const aclScalar* value,
aclTensor* out,
uint64_t* workspaceSize,
aclOpExecutor** executor)aclnnStatus aclnnThreshold(
void* workspace,
uint64_t workspaceSize,
aclOpExecutor* executor,
aclrtStream stream)aclnnStatus aclnnInplaceThresholdGetWorkspaceSize(
aclTensor* selfRef,
const aclScalar* threshold,
const aclScalar* value,
uint64_t* workspaceSize,
aclOpExecutor** executor)aclnnStatus aclnnInplaceThreshold(
void* workspace,
uint64_t workspaceSize,
aclOpExecutor* executor,
aclrtStream stream)aclnnThresholdGetWorkspaceSize
Parameters
Atlas training series products : The data type can be FLOAT16, FLOAT32, INT32, INT8, UINT8, INT16, or INT64.
Returns:
aclnnStatus: status code. For details, see aclnn Return Codes.
The first-phase API implements input parameter verification. The following errors may be thrown:
Return Error Code Description ACLNN_ERR_PARAM_NULLPTR 161001 The passed self, threshold, value, or out is a null pointer. ACLNN_ERR_PARAM_INVALID 161002 The data type of self is not supported. self, threshold, and value do not meet the type deduction rules. The data type deduced from self, threshold, and value cannot be converted to the data type of out. The shape of self or out has more than eight dimensions, or the shapes of self and out are inconsistent.
aclnnThreshold
Parameters:
Name Input/Output Description workspace Input Address of the workspace to be allocated on the device. workspaceSize Input Size of the workspace to be allocated on the device, which is obtained by calling the first-phase API aclnnThresholdGetWorkspaceSize. executor Input Operator executor, containing the operator computation process. stream Input Stream for executing the task. Returns:
aclnnStatus: status code. For details, see aclnn Return Codes.
aclnnInplaceThresholdGetWorkspaceSize
Parameters:
Atlas training series products : The data type can be FLOAT16, FLOAT32, INT32, INT8, UINT8, INT16, or INT64.
Returns:
aclnnStatus: status code. For details, see aclnn Return Codes.
The first-phase API implements input parameter verification. The following errors may be thrown:
Return Error Code Description ACLNN_ERR_PARAM_NULLPTR 161001 The passed selfRef, threshold, or value is a null pointer. ACLNN_ERR_PARAM_INVALID 161002 The data type of selfRef is not supported. selfRef, threshold, and value do not meet the type deduction rules. The shape of selfRef has more than eight dimensions.
aclnnInplaceThreshold
Parameters
Name Input/Output Description workspace Input Address of the workspace to be allocated on the device. workspaceSize Input Size of the workspace to be allocated on the device, which is obtained by calling the first-phase API aclnnInplaceThresholdGetWorkspaceSize. executor Input Operator executor, containing the operator computation process. stream Input Stream for executing the task. Returns:
aclnnStatus: status code. For details, see aclnn Return Codes.
Constraints
- Deterministic compute:
- aclnnThreshold and aclnnInplaceThreshold default to a deterministic implementation.
Example
The following example is for reference only. For details, see Compilation and Running Sample.
#include <iostream>
#include <vector>
#include "acl/acl.h"
#include "aclnnop/aclnn_threshold.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) {
// (Fixed writing) 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 memory on the device.
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 the data on the host to the memory on the device.
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 the strides of the 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. (Fixed writing) Initialize the device and stream. For details, see the ACL API manual.
// Set the device ID in use.
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 the input and output based on the API.
std::vector<int64_t> selfShape = {8};
std::vector<int64_t> outShape = {8};
void* selfDeviceAddr = nullptr;
void* outDeviceAddr = nullptr;
aclTensor* self = nullptr;
aclScalar* threshold = nullptr;
aclScalar* value = nullptr;
aclTensor* out = nullptr;
std::vector<float> selfHostData = {0, 1, 2, 3, 4.1, 5, 6, 7};
std::vector<float> outHostData = {0, 0, 0, 0, 0, 0, 0, 0};
float thresholdVal = 4.1f;
float valueVal = 10.0f;
// Create a self aclTensor.
ret = CreateAclTensor(selfHostData, selfShape, &selfDeviceAddr, aclDataType::ACL_FLOAT, &self);
CHECK_RET(ret == ACL_SUCCESS, return ret);
// Create a threshold aclScalar.
threshold = aclCreateScalar(&thresholdVal, aclDataType::ACL_FLOAT);
CHECK_RET(threshold != nullptr, return ret);
// Create a value aclScalar.
value = aclCreateScalar(&valueVal, aclDataType::ACL_FLOAT);
CHECK_RET(value != nullptr, return ret);
// Create an out aclTensor.
ret = CreateAclTensor(outHostData, outShape, &outDeviceAddr, aclDataType::ACL_FLOAT, &out);
CHECK_RET(ret == ACL_SUCCESS, return ret);
// 3. Call the CANN operator library API, which needs to be replaced with the actual API.
uint64_t workspaceSize = 0;
aclOpExecutor* executor;
// Call the first-phase API of aclnnThreshold.
ret = aclnnThresholdGetWorkspaceSize(self, threshold, value, out, &workspaceSize, &executor);
CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("aclnnThresholdGetWorkspaceSize failed. ERROR: %d\n", ret); return ret);
// Allocate device memory based on the computed workspaceSize.
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 aclnnThreshold.
ret = aclnnThreshold(workspaceAddr, workspaceSize, executor, stream);
CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("aclnnThreshold failed. ERROR: %d\n", ret); return ret);
// aclnnInplaceThreshold API call example
uint64_t inplaceWorkspaceSize = 0;
aclOpExecutor* inplaceExecutor;
// Call the first-phase API of aclnnInplaceThreshold.
ret = aclnnInplaceThresholdGetWorkspaceSize(self, threshold, value, &inplaceWorkspaceSize, &inplaceExecutor);
CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("aclnnInplaceThresholdGetWorkspaceSize failed. ERROR: %d\n", ret); return ret);
// Allocate device memory based on the computed workspaceSize.
void* inplaceWorkspaceAddr = nullptr;
if (inplaceWorkspaceSize > 0) {
ret = aclrtMalloc(&inplaceWorkspaceAddr, inplaceWorkspaceSize, 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 aclnnInplaceThreshold.
ret = aclnnInplaceThreshold(inplaceWorkspaceAddr, inplaceWorkspaceSize, inplaceExecutor, stream);
CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("aclnnInplaceThreshold failed. ERROR: %d\n", ret); return ret);
// 4. (Fixed writing) Wait until the task execution is complete.
ret = aclrtSynchronizeStream(stream);
CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("aclrtSynchronizeStream failed. ERROR: %d\n", ret); return ret);
// 5. Obtain the output value and copy the result from the device memory to the host. Modify the configuration based on the API definition.
auto size = GetShapeSize(outShape);
std::vector<float> 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]);
}
auto inplaceSize = GetShapeSize(selfShape);
std::vector<float> inplaceResultData(inplaceSize, 0);
ret = aclrtMemcpy(inplaceResultData.data(), inplaceResultData.size() * sizeof(inplaceResultData[0]), outDeviceAddr, inplaceSize * sizeof(inplaceResultData[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 < inplaceSize; i++) {
LOG_PRINT("aclnnInplaceThreshold result[%ld] is: %f\n", i, inplaceResultData[i]);
}
// 6. Release aclTensor and aclScalar. Modify the configuration based on the API definition.
aclDestroyTensor(self);
aclDestroyScalar(threshold);
aclDestroyScalar(value);
aclDestroyTensor(out);
// 7. Release device resources. Modify the configuration based on the API definition.
aclrtFree(selfDeviceAddr);
aclrtFree(outDeviceAddr);
if (workspaceSize > 0) {
aclrtFree(workspaceAddr);
}
if (inplaceWorkspaceSize > 0) {
aclrtFree(inplaceWorkspaceAddr);
}
aclrtDestroyStream(stream);
aclrtResetDevice(deviceId);
aclFinalize();
return 0;
}