Documentation
Download

aclnnIndexFillTensor&aclnnInplaceIndexFillTensor

📄 View source code

Supported Products

ProductSupported
Atlas A3 training series products/Atlas A3 inference series products√
Atlas A2 training products/Atlas A2 inference products√
Atlas 200I/500 A2 inference products×
Atlas inference series products×
Atlas training series products√

Function

  • Description: Replaces the value at the position specified by index with value along the specified axis dim of the input self.

  • Example: Input self:

      [[1, 2, 3],

       [4, 5, 6],

       [7, 8, 9]]

    If dim = 0, index = [0, 2], and value = 0, the computation result of the operator is as follows:

      [[0, 0, 0],

       [4, 5, 6],

       [0, 0, 0]]

    If dim = 1, index = [0, 2], and value = 0, the computation result of the operator is as follows:

      [[0, 2, 0],

       [0, 5, 0],

       [0, 8, 0]]

Prototype

  • aclnnIndexFillTensor and aclnnInplaceIndexFillTensor implement the same function in different ways. Select a proper operator based on your requirements.

    • aclnnIndexFillTensor: An output tensor object needs to be created to store the computation result.
    • aclnnInplaceIndexFillTensor: 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, aclnnIndexFillTensorGetWorkspaceSize or aclnnInplaceIndexFillTensorGetWorkspaceSize is called to obtain the workspace size required for computation and the executor that contains the operator computation process. Then, aclnnIndexFillTensor or aclnnInplaceIndexFillTensor is called to perform computation.

aclnnStatus aclnnIndexFillTensorGetWorkspaceSize(
 const aclTensor*   self,
 int64_t            dim,
 const aclIntArray* index,
 const aclScalar*   value,
 aclTensor*         out,
 uint64_t*          workspaceSize,
 aclOpExecutor**    executor)
aclnnStatus aclnnIndexFillTensor(
 void*              workspace,
 uint64_t           workspaceSize,
 aclOpExecutor*     executor,
 aclrtStream        stream)
aclnnStatus aclnnInplaceIndexFillTensorGetWorkspaceSize(
 aclTensor*         selfRef,
 int64_t            dim,
 const aclIntArray* index,
 const aclScalar*   value,
 uint64_t*          workspaceSize,
 aclOpExecutor**    executor)
aclnnStatus aclnnInplaceIndexFillTensor(
 void*              workspace,
 uint64_t           workspaceSize,
 aclOpExecutor*     executor,
 aclrtStream        stream)

aclnnIndexFillTensorGetWorkspaceSize

  • Parameters

    Name Input/Output Description Precaution Data Type Data Format Dimension (Shape) Non-contiguous Tensor
    self Input self in the function example, corresponding to the tensor whose value at the specified position is to be replaced by value. - FLOAT16, FLOAT, INT32, INT64, BOOL, BFLOAT16 ND 0–8 √
    dim Input Dimension to be filled by self. When self is 1D to 8D, the value range of dim is [–self.dim(), self.dim()). When self is 0D, the value range of dim is [–1, 1). int64 - - -
    index Input Index to be filled by self in the dim dimension. The element value is less than the size of dim corresponding to self. - - - -
    value Input Data value to be filled. The data type can be converted to that of self. Same as that of self. - - -
    out Output Output tensor. - Same as that of self. ND Same as that of self. √
    workspaceSize Output Size of the workspace required to be allocated on the device. - - - - -
    executor Output Operator executor, containing the operator computation process. - - - - -
    • Atlas training series products: The data type cannot be BFLOAT16.

  • 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, index, value, or out is a null pointer.
    ACLNN_ERR_PARAM_INVALID 161002 The data type of self, index, or value is not supported.
    The absolute value of dim exceeds the maximum dim value of self or the number of dimensions exceeds 8.
    The index value exceeds the maximum dim value of self.
    The shape of self is different from that of out.
    The data type of self is different from that of out.

aclnnIndexFillTensor

  • 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 aclnnIndexFillTensorTensor.
    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.

aclnnInplaceIndexFillTensorGetWorkspaceSize

  • Parameters

    Name Input/Output Description Precaution Data Type Data Format Dimension (Shape) Non-contiguous Tensor
    selfRef Input Tensor whose value at the specified position is to be replaced by value. - FLOAT16, FLOAT, INT32, INT64, BOOL, BFLOAT16 ND 0–8 √
    dim Input Dimension to be filled by selfRef. When self is 1D to 8D, the value range of dim is [–self.dim(), self.dim()). When self is 0D, the value range of dim is [–1, 1). int64 - - -
    index Input Index to be filled by self in the dim dimension. The element value is less than the size of dim corresponding to selfRef. - - - -
    value Input Data value to be filled. - Same as that of selfRef. - - -
    workspaceSize Output Size of the workspace required to be allocated on the device. - - - - -
    executor Output Operator executor, containing the operator computation process. - - - - -
    • Atlas training series products: The data type cannot be BFLOAT16.

  • 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, index, or value is a null pointer.
    ACLNN_ERR_PARAM_INVALID 161002 The data type of selfRef, index, or value is not supported.
    The absolute value of dim exceeds the maximum dim value of selfRef or the number of dimensions exceeds 8.
    The index value exceeds the maximum dim value of selfRef.

aclnnInplaceIndexFillTensor

  • 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 aclnnInplaceIndexFillTensorGetWorkspaceSize.
    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 computation:
    • aclnnIndexFillTensor and aclnnInplaceIndexFillTensor default to a deterministic implementation.

Example

The following example is for reference only. For details, see Compilation and Running Sample.

aclnnIndexFillTensor call example:

#include <iostream>
#include <vector>
#include "acl/acl.h"
#include "aclnnop/aclnn_index_fill_tensor.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 list of external ACL APIs.
  // 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 inputs and outputs based on the API definition.
  std::vector<int64_t> selfShape = {3, 3};
  std::vector<int64_t> outShape = selfShape;
  void* selfDeviceAddr = nullptr;
  void* outDeviceAddr = nullptr; 
  aclTensor* self = nullptr;
  aclScalar* value = nullptr;
  aclIntArray* index = nullptr;
  aclTensor* out = nullptr;
  std::vector<float> selfHostData = {0, 1, 2, 3, 4, 5, 6, 7, 8};
  std::vector<float> outHostData = {0, 0, 0, 0, 0, 0, 0, 0, 0};
  int64_t dim = 1;
  float fillVal = 10;
  int64_t indexVal = 0;
  // Create a self aclTensor.
  ret = CreateAclTensor(selfHostData, selfShape, &selfDeviceAddr, aclDataType::ACL_FLOAT, &self);
  CHECK_RET(ret == ACL_SUCCESS, return ret);
  // Create an out aclTensor.
  ret = CreateAclTensor(outHostData, outShape, &outDeviceAddr, aclDataType::ACL_FLOAT, &out);
  CHECK_RET(ret == ACL_SUCCESS, return ret);
  // Create a value aclScalar.
  value = aclCreateScalar(&fillVal, aclDataType::ACL_FLOAT);
  CHECK_RET(value != nullptr, return ret);
  // Create an index aclIntArray.
  index = aclCreateIntArray(&indexVal, 1);
  CHECK_RET(index != nullptr, 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 aclnnIndexFillTensor.
  ret = aclnnIndexFillTensorGetWorkspaceSize(self, dim, index, value, out, &workspaceSize, &executor);
  CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("aclnnIndexFillTensorGetWorkspaceSize failed. ERROR: %d\n", ret); return ret);
  // Allocate device memory based on 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 aclnnIndexFillTensor.
  ret = aclnnIndexFillTensor(workspaceAddr, workspaceSize, executor, stream);
  CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("aclnnIndexFillTensor 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 code 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]);
  }

  // 6. Release allocated variables. Modify the code based on the API definition.
  aclDestroyTensor(self);
  aclDestroyTensor(out);
  aclDestroyScalar(value);
  aclDestroyIntArray(index);

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

aclnnInplaceIndexFillTensor call example:

#include <iostream>
#include <vector>
#include "acl/acl.h"
#include "aclnnop/aclnn_index_fill_tensor.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 inputs and outputs based on the API definition.
  std::vector<int64_t> selfShape = {3, 3};
  void* selfDeviceAddr = nullptr;
  aclTensor* self = nullptr;
  aclScalar* value = nullptr;
  aclIntArray* index = nullptr;
  std::vector<float> selfHostData = {0, 1, 2, 3, 4, 5, 6, 7, 8};

  int64_t dim = 1;
  float fillVal = 10;
  int64_t indexVal = 0;
  // Create a self aclTensor.
  ret = CreateAclTensor(selfHostData, selfShape, &selfDeviceAddr, aclDataType::ACL_FLOAT, &self);
  CHECK_RET(ret == ACL_SUCCESS, return ret);
  // Create a value aclScalar.
  value = aclCreateScalar(&fillVal, aclDataType::ACL_FLOAT);
  CHECK_RET(value != nullptr, return ret);
  // Create an index aclIntArray.
  index = aclCreateIntArray(&indexVal, 1);
  CHECK_RET(index != nullptr, 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 aclnnInplaceIndexFillTensor.
  ret = aclnnInplaceIndexFillTensorGetWorkspaceSize(self, dim, index, value, &workspaceSize, &executor);
  CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("aclnnInplaceIndexFillTensorGetWorkspaceSize failed. ERROR: %d\n", ret); return ret);
  // Allocate device memory based on 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 aclnnInplaceIndexFillTensor.
  ret = aclnnInplaceIndexFillTensor(workspaceAddr, workspaceSize, executor, stream);
  CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("aclnnInplaceIndexFillTensor 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 code based on the API definition.
  auto size = GetShapeSize(selfShape);
  std::vector<float> resultData(size, 0);
  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 allocated variables. Modify the code based on the API definition.
  aclDestroyTensor(self);
  aclDestroyScalar(value);
  aclDestroyIntArray(index);

  // 7. Release device resources. Modify the code based on the API definition.
  aclrtFree(selfDeviceAddr);
  if (workspaceSize > 0) {
    aclrtFree(workspaceAddr);
  }
  aclrtDestroyStream(stream);
  aclrtResetDevice(deviceId);
  aclFinalize();
  return 0;
}
This site uses cookies to improve your browsing experience. By continuing to browse this site, you agree to our use of cookies.View Details