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• Description: Performs backpropagation of .

• Formula:

  $$gradInput = gradOutput \cdot \begin{cases} \frac{1}{1+e^{(-\beta * self)}}, ~~~~~~~\beta * self \le threshold \\ 1, ~~~~~~~~~~~~~~~~~~~~~\beta * self > threshold \end{cases}$$

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Each operator has calls. First, aclnnSoftplusBackwardGetWorkspaceSize is called to obtain the workspace size required for computation and the executor that contains the operator computation process. Then, aclnnSoftplusBackward is called to perform computation.

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• Parameters:

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  • [object Object]Atlas training products[object Object]: The data type can be FLOAT, FLOAT16, or DOUBLE.

• Returns:

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

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

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• Parameters:

  [object Object]

• Returns:

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

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• Deterministic compute:
  • aclnnSoftplusBackward defaults to a deterministic implementation.

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