[object Object]

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

• Operator function: Activation function. Returns a tensor with the same shape as the input tensor by performing elementwise computation on the input tensor.

• Formula:

$$tanh(self)=\frac{e^{self}-e^{-self}}{e^{self} + e^{-self}}$$ [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, aclnnTanhGetWorkspaceSize or aclnnInplaceTanhGetWorkspaceSize is called to obtain the workspace size required for computation and the executor that contains the operator computation process. Then, aclnnTanh or aclnnInplaceTanh is called to perform computation.

[object Object]

• Parameters

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

• Returns

  [object Object]: 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

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

[object Object]

• Parameters

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

• Returns

  [object Object]: 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

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

[object Object]

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

[object Object]

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