aclnnHardtanh&aclnnInplaceHardtanh
Applicable Products
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Function
Description: Clamps all elements of the input to the range [clipValueMin, clipValueMax]. If an element is greater than clipValueMax, it is clamped to clipValueMax. If an element is less than clipValueMin, it is clamped to clipValueMin. Otherwise, the element remains unchanged.
Formula:
Function Prototype
aclnnHardtanh and aclnnInplaceHardtanh implement the same functionality. The differences are as follows. Select the appropriate operator based on your actual scenario.
aclnnHardtanh: Requires creating a new output tensor object to store the computation result.
aclnnInplaceHardtanh: Does not require creating 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 "aclnnHardtanhGetWorkspaceSize" or "aclnnInplaceHardtanhGetWorkspaceSize" API to obtain the workspace size required for computation and the executor that contains the operator computation process, and then call the "aclnnHardtanh" or "aclnnInplaceHardtanh" API to execute the computation.
aclnnStatus aclnnHardtanhGetWorkspaceSize(
const aclTensor *self,
const aclScalar *clipValueMin,
const aclScalar *clipValueMax,
aclTensor *out,
uint64_t *workspaceSize,
aclOpExecutor **executor)aclnnStatus aclnnHardtanh(
void *workspace,
uint64_t workspaceSize,
aclOpExecutor *executor,
aclrtStream stream)aclnnStatus aclnnInplaceHardtanhGetWorkspaceSize(
aclTensor *selfRef,
const aclScalar *clipValueMin,
const aclScalar *clipValueMax,
uint64_t *workspaceSize,
aclOpExecutor **executor)aclnnStatus aclnnInplaceHardtanh(
void *workspace,
uint64_t workspaceSize,
aclOpExecutor *executor,
aclrtStream stream)aclnnHardtanhGetWorkspaceSize
Parameters:
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 One of the input parameters self, out, clipValueMax, or clipValueMin is a null pointer. ACLNN_ERR_PARAM_INVALID 161002 The data types of self and out are not within the supported range. The data type of self is inconsistent with that of out. The shape of self is inconsistent with that of out. The value of clipValueMin is greater than that of clipValueMax.
aclnnHardtanh
Parameters:
Parameter Input/Output Description workspace Input Address of the workspace applied on the device side. workspaceSize Input Size of the workspace applied on the device side, obtained by the first-phase API aclnnHardtanhGetWorkspaceSize. executor Input Op executor that contains the operator computation flow. stream Input Specifies the stream on which the task is executed. Return value:
aclnnStatus: return code. For details, see aclnn Return Codes.
aclnnInplaceHardtanhGetWorkspaceSize
Parameters:
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 A null pointer is passed for selfRef, clipValueMax, or clipValueMin. ACLNN_ERR_PARAM_INVALID 161002 The data type of selfRef is not within the supported range. The value of clipValueMin is greater than clipValueMax.
aclnnInplaceHardtanh
Parameters:
Parameter Input/Output Description workspace Input Workspace memory address applied for on the Device side. workspaceSize Input Workspace size applied for on the Device side, obtained from the first-phase API aclnnInplaceHardtanhGetWorkspaceSize. executor Input Operator executor that 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
None.
Example
The following provides example code for reference only. For details about compilation and running, see Compile and Run Samples.
#include <iostream>
#include <vector>
#include "acl/acl.h"
#include "aclnnop/aclnn_hardtanh.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;
}
int Init(int32_t deviceId, aclrtStream* stream) {
// Boilerplate for resource initialization.
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 side.
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 data from the host side to the 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);
// Calculate the strides of 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 the device/stream. See the acl API manual.
// Fill in the deviceId based on the actual device.
int32_t deviceId = 0;
aclrtStream stream;
auto ret = Init(deviceId, &stream);
// Handle the check as needed.
CHECK_RET(ret == 0, LOG_PRINT("Init acl failed. ERROR: %d\n", ret); return ret);
// 2. Construct the input and output. Customize the construction based on the API.
std::vector<int64_t> selfShape = {4, 2};
std::vector<int64_t> outShape = {4, 2};
void* selfDeviceAddr = nullptr;
void* outDeviceAddr = nullptr;
aclTensor* self = nullptr;
aclTensor* out = nullptr;
aclScalar* clipValueMin = nullptr;
aclScalar* clipValueMax = nullptr;
std::vector<float> selfHostData = {0, 1, 2, 3};
std::vector<float> outHostData = {0, 0, 0, 0};
float clipValueMinValue = 1.2f;
float clipValueMaxValue = 2.4f;
// Create self aclTensor.
ret = CreateAclTensor(selfHostData, selfShape, &selfDeviceAddr, aclDataType::ACL_FLOAT, &self);
CHECK_RET(ret == ACL_SUCCESS, return ret);
// Create clipValueMin aclScalar.
clipValueMin = aclCreateScalar(&clipValueMinValue, aclDataType::ACL_FLOAT);
CHECK_RET(clipValueMin != nullptr, return ret);
// Create clipValueMax aclScalar.
clipValueMax = aclCreateScalar(&clipValueMaxValue, aclDataType::ACL_FLOAT);
CHECK_RET(clipValueMax != nullptr, return ret);
// Create out aclTensor.
ret = CreateAclTensor(outHostData, outShape, &outDeviceAddr, aclDataType::ACL_FLOAT, &out);
CHECK_RET(ret == ACL_SUCCESS, return ret);
// Example of aclnnHardtanh API call.
// 3. Call the CANN operator library API.
// Call the first-phase API of aclnnHardtanh.
uint64_t workspaceSize = 0;
aclOpExecutor* executor;
ret = aclnnHardtanhGetWorkspaceSize(self, clipValueMin, clipValueMax, out, &workspaceSize, &executor);
CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("aclnnHardtanhGetWorkspaceSize failed. ERROR: %d\n", ret); return ret);
// Apply for device memory based on the workspaceSize calculated 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 aclnnHardtanh.
ret = aclnnHardtanh(workspaceAddr, workspaceSize, executor, stream);
CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("aclnnHardtanh failed. ERROR: %d\n", ret); return ret);
// 4. (Boilerplate) Synchronize and wait for task execution to 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 memory. Modify this based on the specific API definition.
auto size = GetShapeSize(outShape);
std::vector<float> resultData(size, 0);
ret = aclrtMemcpy(resultData.data(), resultData.size() * sizeof(resultData[0]), outDeviceAddr, size * sizeof(float),
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 the aclnnInplaceHardtanh API
// 3. Call the CANN operator library API.
LOG_PRINT("\ntest aclnnInplaceHardtanh\n");
// Call the first-phase API of aclnnInplaceHardtanh.
uint64_t inplaceWorkspaceSize = 0;
aclOpExecutor* inplaceExecutor;
ret = aclnnInplaceHardtanhGetWorkspaceSize(self, clipValueMin, clipValueMax, &inplaceWorkspaceSize, &inplaceExecutor);
CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("aclnnInplaceHardtanhGetWorkspaceSize failed. ERROR: %d\n", ret); return ret);
// Allocate device memory based on the workspaceSize calculated by the first-phase API.
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 aclnnInplaceHardtanh.
ret = aclnnInplaceHardtanh(inplaceWorkspaceAddr, inplaceWorkspaceSize, inplaceExecutor, stream);
CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("aclnnInplaceHardtanh failed. ERROR: %d\n", ret); return ret);
// 4. (Boilerplate) Synchronously wait for task execution to 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 memory. Modify based on the specific API definition.
size = GetShapeSize(outShape);
ret = aclrtMemcpy(resultData.data(), resultData.size() * sizeof(resultData[0]), selfDeviceAddr, size * sizeof(float),
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 and aclScalar. Modify based on the specific API definition.
aclDestroyTensor(self);
aclDestroyScalar(clipValueMin);
aclDestroyScalar(clipValueMax);
aclDestroyTensor(out);
// 7. Release device resources. Modify based on the specific API definition.
aclrtFree(selfDeviceAddr);
aclrtFree(outDeviceAddr);
if (workspaceSize > 0) {
aclrtFree(workspaceAddr);
}
aclrtDestroyStream(stream);
aclrtResetDevice(deviceId);
aclFinalize();
return 0;
}