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• API function: Implements the FusedEmaAdam fusion optimizer.
• Formula:$$(correction_{\beta_1},correction_{\beta_2})=\begin{cases} (1,1),&biasCorrection=False\\ (1-\beta_1^{step},1-\beta_2^{step}),&biasCorrection=True \end{cases}$$ $$grad=\begin{cases} grad+weightDecay*var,&mode=0\\ grad,&mode=1 \end{cases}$$ $$m_{out}=\beta_1*m+(1-\beta_1)*grad$$ $$v_{out}=\beta_2*v+(1-\beta_2)*grad^2$$ $$m_{next}=m_{out}/correction_{\beta_1}$$ $$v_{next}=v_{out}/correction_{\beta_2}$$ $$denom=\sqrt{v_{next}}+eps$$ $$update=\begin{cases} m_{next}/denom,&mode=0\\ m_{next}/denom+weightDecay*var,&mode=1 \end{cases}$$ $$var_{out}=var-lr*update$$ $$s_{out}=emaDecay*s+(1-emaDecay)*var_{out}$$

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

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• Parameters:

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• 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:

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• Returns:

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

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The data types and shapes of the input grad, var, m, v, and s must be the same.

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

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