[object Object]

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

• API description: Applies the nearest neighbor interpolation algorithm to upsample the input signal composed of several input channels. If the input shape is (N, C, L), the output shape is (N, C, outputSize).
• Formula:$$out(N, C, l) = self(N, C, min(floor((l + 0.5) * scales), L-1))$$

[object Object]

Each operator has calls. First, aclnnUpsampleNearestExact1dGetWorkspaceSize is called to obtain the workspace size required for computation and the executor that contains the operator computation process. Then, [object Object] is called to perform computation.

[object Object]

• Parameters:

  [object Object]

  • [object Object]Atlas inference products[object Object]:

    The data types of the input parameter [object Object] and output parameter [object Object] do not support BFLOAT16.

• Returns:

  aclnnStatus: status code. For details, see .

  The first-phase API implements input parameter verification. The following errors may be thrown.

  [object Object]

[object Object]

• Parameters:

  [object Object]

• Returns:

  aclnnStatus: status code. For details, see .

[object Object]

• Either outputSize or scales must be used.
  • If the value of scales is less than or equal to 0, the value of outputSize is used.
  • If the value of scales is greater than 0, the value of scales is used, and $outputSize = [floor(self\_L * scales)]$.
• Deterministic computing:
  • aclnnUpsampleNearestExact1d defaults to a deterministic implementation.

[object Object]

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