[object Object]

[object Object][object Object]undefined[object Object]

• Description: Performs linear interpolation between the start and end tensors based on the given weight and returns the interpolated tensor.

• Formula:

$$\text { out }_i=\text { start }_i+\text { weight }_i \times\left(\text { end }_i-\text { start }_i\right)$$ [object Object]

• [object Object] and [object Object] implement the same function in different ways. Select a proper operator based on your requirements.

  • [object Object]: An output tensor object needs to be created to store the computation result.
  • [object Object]: No output tensor object needs to be created, and the computation result is stored in the memory of the input tensor.

• Each operator has calls. First, [object Object] or [object Object] is called to obtain the workspace size required for computation and the executor that contains the operator computation process. Then, [object Object] or [object Object] is called to perform computation.

  • [object Object]
  • [object Object]
  • [object Object]
  • [object Object]

[object Object]

• Parameters:

  • [object Object] (aclTensor*, compute input): input [object Object] in the formula. It is an aclTensor on the device. The data type of self is the same as that of end, weight, and out. The shapes of self, end, and weight must meet the . are supported. The can be ND.
    • [object Object]Atlas inference products[object Object] and [object Object]Atlas training products[object Object]: The data type can be FLOAT16 or FLOAT.
    • [object Object]Atlas A2 training products/Atlas A2 inference products[object Object] and [object Object]Atlas A3 training products/Atlas A3 inference products[object Object]: The data type can be BFLOAT16, FLOAT16, or FLOAT.
  • [object Object] (aclTensor*, compute input): input [object Object] in the formula. It is an aclTensor on the device. The data type of self is the same as that of end, weight, and out. The shapes of self, end, and weight must meet the . are supported. The can be ND.
    • [object Object]Atlas inference products[object Object] and [object Object]Atlas training products[object Object]: The data type can be FLOAT16 or FLOAT.
    • [object Object]Atlas A2 training products/Atlas A2 inference products[object Object] and [object Object]Atlas A3 training products/Atlas A3 inference products[object Object]: The data type can be BFLOAT16, FLOAT16, or FLOAT.
  • [object Object] (aclTensor*, compute input): input [object Object] in the formula. It is an aclTensor on the device. The data type of self and end, weight, and out is the same. The shapes of self and end, weight, and out must meet the broadcast relationship (../common/broadcast_relationship.md). are supported. The can be ND.
    • [object Object]Atlas inference products[object Object] and [object Object]Atlas training products[object Object]: The data type can be FLOAT16 or FLOAT.
    • [object Object]Atlas A2 training products/Atlas A2 inference products[object Object] and [object Object]Atlas A3 training products/Atlas A3 inference products[object Object]: The data type can be BFLOAT16, FLOAT16, or FLOAT.
  • [object Object] (aclTensor*, compute output): [object Object] in the formula. It is an aclTensor on the device. The data type of self is the same as that of end, weight, and out. The shape of out is the same as that of the tensor after self, end, and weight are broadcast. are supported. The can be ND.
    • [object Object]Atlas inference products[object Object] and [object Object]Atlas training products[object Object]: The data type can be FLOAT16 or FLOAT.
    • [object Object]Atlas A2 training products/Atlas A2 inference products[object Object] and [object Object]Atlas A3 training products/Atlas A3 inference products[object Object]: The data type can be BFLOAT16, FLOAT16, or FLOAT.
  • [object Object] (uint64_t*, output): size of the workspace to be allocated on the device.
  • [object Object] (aclOpExecutor**, output): operator executor, containing the operator computation process.

• Returns:

  [object Object]: status code. For details, see .

[object Object]

• Parameters:

  • [object Object] (void*, input): address of the workspace to be allocated on the device.
  • [object Object] (uint64_t, input): size of the workspace to be allocated on the device, which is obtained by calling aclnnLerpGetWorkspaceSize.
  • [object Object] (aclOpExecutor*, input): operator executor, containing the operator computation process.
  • [object Object] (aclrtStream, input): stream for executing the task.

• Returns:

  [object Object]: status code. For details, see .

[object Object]

• Parameters:

  • [object Object] (aclTensor*, compute input/output): [object Object] and [object Object] in the formula, aclTensor on the device. The data types of selfRef, end, and weight are the same. The shapes of selfRef, end, and weight meet the , and the shape after broadcasting is the same as that of [object Object]. are supported. The can be ND.
    • [object Object]Atlas inference products[object Object] and [object Object]Atlas training products[object Object]: The data type can be FLOAT16 or FLOAT.
    • [object Object]Atlas A2 training products/Atlas A2 inference products[object Object] and [object Object]Atlas A3 training products/Atlas A3 inference products[object Object]: The data type can be BFLOAT16, FLOAT16, or FLOAT.
  • [object Object] (aclTensor*, compute input): [object Object] in the formula, aclTensor on the device. The data types of selfRef, end, and weight are the same. The shapes of selfRef, end, and weight meet the . The shape after broadcasting is the same as that of [object Object]. are supported. The can be ND.
    • [object Object]Atlas inference products[object Object] and [object Object]Atlas training products[object Object]: The data type can be FLOAT16 or FLOAT.
    • [object Object]Atlas A2 training products/Atlas A2 inference products[object Object] and [object Object]Atlas A3 training products/Atlas A3 inference products[object Object]: The data type can be BFLOAT16, FLOAT16, or FLOAT.
  • [object Object] (aclTensor*, compute input): [object Object] in the formula, aclTensor on the device. The data types of selfRef, end, weight, and out are the same. The shapes of selfRef, end, and weight meet the . are supported. The can be ND.
    • [object Object]Atlas inference products[object Object] and [object Object]Atlas training products[object Object]: The data type can be FLOAT16 or FLOAT.
    • [object Object]Atlas A2 training products/Atlas A2 inference products[object Object] and [object Object]Atlas A3 training products/Atlas A3 inference products[object Object]: The data type can be BFLOAT16, FLOAT16, or FLOAT.
  • [object Object] (uint64_t*, output): size of the workspace to be allocated on the device.
  • [object Object] (aclOpExecutor**, output): operator executor, containing the operator computation process.

• Returns:

  [object Object]: status code. For details, see .

[object Object]

• Parameters:

  • [object Object] (void*, input): address of the workspace to be allocated on the device.
  • [object Object] (uint64_t, input): size of the workspace to be allocated on the device, which is obtained by calling aclnnInplaceLerpGetWorkspaceSize.
  • [object Object] (aclOpExecutor*, input): operator executor, containing the operator computation process.
  • [object Object] (aclrtStream, input): stream for executing the task.

• Returns:

  [object Object]: status code. For details, see .

[object Object]

• Deterministic computation:
  • aclnnLerp&aclnnInplaceLerp defaults to deterministic implementation.

[object Object]

The following example is for reference only. For details, see .

aclnnLerp

aclnnInplaceLerp