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• Description: Implements the AdamW optimizer function.

• Formula:

  $$m_{t}=\beta_{1} m_{t-1}+\left(1-\beta_{1}\right) g_{t} \\$$ $$v_{t}=\beta_{2} v_{t-1}+\left(1-\beta_{2}\right) g_{t}^{2}$$ $$\hat{m}_{t}=\frac{m_{t}}{1-\beta_{1}^{t}} \\$$ $$\hat{v}_{t}=\frac{v_{t}}{1-\beta_{2}^{t}} \\$$ $$\theta_{t+1}=\theta_{t}-\frac{\eta}{\sqrt{\hat{v}_{t}}+\epsilon} \hat{m}_{t}-\eta \cdot \lambda \cdot \theta_{t-1}$$

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Each operator has calls. First, aclnnApplyAdamWV2GetWorkspaceSize is called to obtain the workspace size required for computation and the executor that contains the operator computation process. Then, aclnnApplyAdamWV2 is called to perform computation.

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• Parameters:

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• 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:

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• Returns:

  aclnnStatus: status code. For details, see .

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If the data types of varRef, mRef, and vRef in the input tensor are the same, the data type can be FLOAT16, BFLOAT16, or FLOAT32.

• Deterministic compute:
  • aclnnApplyAdamWV2 defaults to a deterministic implementation.

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