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• Description: Performs backpropagation of .
• Formula:

  • Forward propagation of Softshrink:

    $$Softshrink(x)=\begin{cases} x-λ, if x > λ \\ x+λ, if x < -λ \\ 0, otherwise \\ \end{cases}$$

  • Backward propagation of Softshrink:

    $$gradInput= \begin{cases} gradOutput, \ if \ x > \lambda \\ gradOutput, \ if \ x <-\lambda \\ 0, \ otherwise \end{cases}$$

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

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• Parameters:

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

• 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:
  • aclnnSoftshrinkBackward defaults to a deterministic implementation.

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