[object Object]

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

• Function: Calculates the logarithm with base 2.

• Formula:

  $$output_i=log_2(self_i)$$

[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, aclnnLog2GetWorkspaceSize or aclnnInplaceLog2GetWorkspaceSize is called to obtain the workspace size required for computation and the executor that contains the operator computation process. Then, aclnnLog2 or aclnnInplaceLog2 is called to perform computation.

[object Object]

• Parameters:

  [object Object]

• 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]

• Parameters:

  [object Object]

• Returns:

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

[object Object]

• Parameters:

  [object Object]

• 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]

• Parameters:

  [object Object]

• Returns:

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

[object Object]

• Deterministic computation:
  • [object Object] and [object Object] default to deterministic implementation.

[object Object]

The following examples are for reference only. For details, see .

Sample code of aclnnLog2:

Sample code of aclnnInplaceLog2: