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• Description: Computes the backward pass of , calculating the gradients of tensors x, gx, and gamma, as well as the sum of tensor dy.

• Formula:

  $$dgx_i = tmpone_i * rstd + dvar * tmptwo_i + dmean$$ $$dx_i = alpha * {dgx}_i$$ $$dbeta = \sum_{i=1}^{N} dy_i$$ $$dgamma = \sum_{i=1}^{N} dy_i * rstd * {tmptwo}_i$$

  Where:

  $$oneDiv=-1/SizeOf(gamma)$$ $$tmpone_i = dy_i * gamma$$ $$tmptwo_i = alpha * x_i + {gx}_i - mean$$ $$dvar = (oneDiv) * \sum_{i=1}^{N} {tmpone}_i * {tmptwo}_i * {rstd}^3$$ $$dmean = (oneDiv) * \sum_{i=1}^{N} {tmpone}_i * rstd$$

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Each operator has calls. First, aclnnDeepNormGradGetWorkspaceSize is called to obtain the workspace size required for computation and the executor that contains the operator computation flow. Then, aclnnDeepNormGrad is called to perform computation.

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• Parameters

  [object Object]
  • For [object Object]Atlas inference products[object Object], the data types of [object Object], [object Object], [object Object], [object Object], [object Object], and [object Object] cannot be BFLOAT16.

• Return Value

  [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]

• Return Value

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

[object Object]

• Unsupported types:

  DOUBLE: not supported by the instruction set.

• Boundary value specifications:

  • The output is Inf when the input is Inf.
  • The output is NaN when the input is NaN.

• Deterministic computation:

  • aclnnDeepNormGrad defaults to a non-deterministic implementation. Enabling deterministic computation via aclrtCtxSetSysParamOpt is not supported.

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