aclnnMultinomialTensor

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Function

Draws numsamples samples from the input tensor based on the probability distribution of each object, and stores the indices of these samples in the output tensor.

Function Prototype

Each operator is divided into a two-phase API. You must first call the "aclnnMultinomialTensorGetWorkspaceSize" API to obtain the workspace size required for computation and the executor that contains the operator computation process, and then call the "aclnnMultinomialTensor" API to execute the computation.

aclnnStatus aclnnMultinomialTensorGetWorkspaceSize(
  const aclTensor*      self,
  int64_t               numsamples,
  bool                  replacement,
  const aclTensor*      seedTensor,
  const aclTensor*      offsetTensor,
  int64_t               offset,
  aclTensor*            out,
  uint64_t*             workspaceSize,
  aclOpExecutor**       executor)

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

aclnnMultinomialTensorGetWorkspaceSize

• Parameters:

  Parameter	Input/Output	Description	Instruction	Data Type	Data Format	Dimension (Shape)	Non-Contiguous Tensor
  self (aclTensor*)	Input	Input tensor, representing the probability of each object distribution.	The value range of self must be greater than or equal to 0.	BFLOAT16, FLOAT16, FLOAT, DOUBLE	ND	Must be (N, C) or (C), and have the same dimensions as self and out.	√
  numsamples (int64_t)	Input	Number of samples to draw from each multinomial distribution.	numsamples is a positive number. When replacement is false, numsamples must not exceed C.	INT64	-	-	-
  replacement (bool)	Input	Determines whether elements are sampled with replacement.	-	BOOL	-	-	-
  seedTensor (aclTensor*)	Input	Sets the seed value for the random number generator, which affects the generated random number sequence.	-	INT64	ND	Must be [1].	√
  offsetTensor (aclTensor*)	Input	Specifies the offset for the random number operator as the sum with the scalar offset. The offset of a random number affects the position of the generated random number sequence. After setting the offset, the generated random number sequence starts from the specified position.	-	INT64	ND	Must be [1].	√
  offset (int64_t)	Input	Serves as the accumulation amount for offsetTensor.	-	INT64	-	-	-
  out (aclTensor*)	Output	Output tensor.	-	INT64	ND	Has the shape (N, numsamples) or (numsamples), with the same dimensions as self and out.	√
  workspaceSize (uint64_t*)	Output	Returns the workspace size to be applied for on the Device side.	-	-	-	-	-
  executor (aclOpExecutor**)	Output	Returns the operator executor, which includes the operator computation process.	-	-	-	-	-

• 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 Code	Error Code	Description
  ACLNN_ERR_PARAM_NULLPTR	161001	The passed self or out is a null pointer.
  ACLNN_ERR_PARAM_INVALID	161002	The data type of self is not within the supported range.
  		The data type of out is not INT64.
  		The dimension of self is not 1D or 2D.
  		The dimensions of self and out are inconsistent.
  		The value of numsamples is less than or equal to 0.
  		replacement is false and numsamples is greater than the size of the last dimension of self.
  		The size of the last dimension of self must not exceed 2^24.
  		The last dimension of out must be consistent with the size of numsamples.
  		When self is a 2D tensor, the first dimension of out must be equal to the size of the first dimension of self.

aclnnMultinomialTensor

• Parameters:

  Parameter	Input/Output	Description
  workspace	Input	The workspace memory address applied on the device side.
  workspaceSize	Input	Size of the workspace applied on the Device side, obtained through the first-phase API aclnnMultinomialTensorGetWorkspaceSize.
  executor	Input	Operator executor, which contains the operator computation flow.
  stream	Input	Specifies the stream for task execution.

• Return value

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

Constraints

• Deterministic computation:

  • aclnnMultinomialTensor defaults to a deterministic implementation.

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_multinomial.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 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 apply for device-side 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);
  // Copy data from the host side to the device side memory by calling aclrtMemcpy.
  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];
  }

  // Create an aclTensor by calling the aclCreateTensor API.
  *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.
  // Set deviceId based on the 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 the input and output. Customize the construction based on the API interface.
  std::vector<int64_t> selfShape = {8};
  std::vector<int64_t> outShape = {4};
  std::vector<int64_t> seedShape = {1};
  std::vector<int64_t> offsetShape = {1};
  void* selfDeviceAddr = nullptr;
  void* outDeviceAddr = nullptr;
  aclTensor* self = nullptr;
  aclTensor* out = nullptr;
  void* seedDeviceAddr = nullptr;
  aclTensor* seed = nullptr;
  void* offsetDeviceAddr = nullptr;
  aclTensor* offset = nullptr;
  int64_t offset2 = 102;
  std::vector<float> selfHostData = {0, 10, 3, 0, 1, 2, 1, 1};
  std::vector<int64_t> outHostData = {2, 0, 1, 2};
  std::vector<int64_t> seedHostData = {0};
  std::vector<int64_t> offsetHostData = {392};
  int64_t numsamples = 4;
  bool replacement = false;

  // Create the self aclTensor.
  ret = CreateAclTensor(selfHostData, selfShape, &selfDeviceAddr, aclDataType::ACL_FLOAT, &self);
  CHECK_RET(ret == ACL_SUCCESS, return ret);
  // Create the seed aclTensor.
  ret = CreateAclTensor(seedHostData, seedShape, &seedDeviceAddr, aclDataType::ACL_INT64, &seed);
  CHECK_RET(ret == ACL_SUCCESS, return ret);
  // Create the offset aclTensor.
  ret = CreateAclTensor(offsetHostData, offsetShape, &offsetDeviceAddr, aclDataType::ACL_INT64, &offset);
  CHECK_RET(ret == ACL_SUCCESS, return ret);

  ret = CreateAclTensor(outHostData, outShape, &outDeviceAddr, aclDataType::ACL_INT64, &out);
  CHECK_RET(ret == ACL_SUCCESS, return ret);

  // 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 aclnnMultinomialTensor.
  ret = aclnnMultinomialTensorGetWorkspaceSize(self, numsamples, replacement, seed, offset, offset2, out, &workspaceSize, &executor);
  CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("aclnnMultinomialTensorGetWorkspaceSize 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 aclnnMultinomialTensor.
  ret = aclnnMultinomialTensor(workspaceAddr, workspaceSize, executor, stream);
  CHECK_RET(ret == ACL_SUCCESS, LOG_PRINT("aclnnMultinomialTensor 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 this step based on the specific API definition.
  auto size = GetShapeSize(outShape);
  std::vector<int64_t> 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: %ld\n", i, resultData[i]);
  }

  // 6. Release aclTensor and aclScalar. Modify based on the specific API definition.
  aclDestroyTensor(self);
  aclDestroyTensor(out);
  aclDestroyTensor(seed);
  aclDestroyTensor(offset);

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

  return 0;
}