[object Object]

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

• Description: Computes the group normalization result out, mean value meanOut, and reciprocal of the standard deviation rstdOut of the input self.

• Formula:

  Assume $x = self$, where $E[x] = \bar{x}$ represents the mean value of $x$, and $Var[x] = \frac{1}{n - 1} * \sum_{i=1}^n(x_i - E[x])^2$ represents the sample variance of $x$.

  $$out = \frac{x - E[x]}{\sqrt{Var[x] + eps}} * \gamma + \beta$$ $$meanOut = E[x]$$ $$rstdOut = \frac{1}{\sqrt{Var[x] + eps}}$$

[object Object]

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

[object Object]

• Parameters:

  [object Object]

  • [object Object]Atlas training series products[object Object] and [object Object]Atlas inference series products[object Object]:

    The data types of [object Object], [object Object], [object Object], [object Object], [object Object], and [object Object] cannot be BFLOAT16.

• Returns:

  aclnnStatus: 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:

  aclnnStatus: status code. For details, see .

[object Object]

• Deterministic computation:
  • aclnnGroupNorm defaults to a deterministic implementation.

[object Object]

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