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Description: Performs backpropagation of . Formula:

$$output = \begin{cases} gradOutput, &if\ self \gt 0 \\ gradOutput*negativeSlope, &if\ self \le 0 \end{cases}$$ [object Object]

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

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• Parameters:

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  • [object Object]Atlas inference series products[object Object] and [object Object]Atlas training series products[object Object]: The data type of gradOutput, self, and out can be FLOAT, FLOAT16, or DOUBLE. The data type of negativeSlope can be FLOAT, FLOAT16, DOUBLE, INT32, INT64, INT8, BOOL, INT16, or UINT8.

• Returns:

  aclnnStatus: 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:

  aclnnStatus: status code. For details, see .

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

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