[object Object]

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

• Function: performs linear interpolation between the start and end tensors based on the given weights and returns the interpolated tensor.

• Formulas:

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

• aclnnLerp and aclnnInplaceLerp implement the same function in different ways. Select a proper operator based on your requirements.
  • aclnnLerp: An output tensor object needs to be created to store the computation result.
  • aclnnInplaceLerp: 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, aclnnLerpGetWorkspaceSize or aclnnInplaceLerpGetWorkspaceSize is called to obtain the workspace size required for computation and the executor that contains the operator computation process. Then, aclnnLerp or aclnnInplaceLerp is called to perform computation.

[object Object]

• Parameter description:

  [object Object]
  • [object Object]Atlas inference products[object Object] and [object Object]Atlas training products[object Object]: BFLOAT16 is not supported.

• Returns

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

  The first-phase API performs input parameter validation. The following errors may be returned:

  [object Object]

[object Object]

• Parameter description:

  [object Object]

• Returns

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

[object Object]

• Parameter description:

  [object Object]
  • The [object Object]Atlas inference products[object Object] and [object Object]Atlas training products[object Object] do not support BFLOAT16.

• Returns

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

  The first-phase API performs input parameter validation. The following errors may be returned:

  [object Object]

[object Object]

• Parameter description:

  [object Object]

• Returns

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

[object Object]

• Deterministic computation:
  • The default deterministic implementation is used for aclnnLerp&aclnnInplaceLerp.

[object Object]

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

aclnnLerp

aclnnInplaceLerp