[object Object]

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

• Description: Performs root mean square layer normalization (RMSNorm), a normalization method widely used in large language models. Unlike LayerNorm, RMSNorm omits mean subtraction. The AddRmsNorm operator fuses the preceding Add operator with RMSNorm to reduce data movement operations.
• Formula:$$x_i=x1Ref_i+x2Ref_i$$ $$\operatorname{RmsNorm}(x_i)=\frac{1}{\operatorname{Rms}(\mathbf{x})} * x_i * gamma_i, \quad \text { where } \operatorname{Rms}(\mathbf{x})=\sqrt{\frac{1}{n} \sum_{i=1}^n x_i^2+epsilon}$$

[object Object]

Each operator has calls. First, [object Object] is called to obtain the input parameters and compute the required workspace size based on the process. Then, [object Object] is called to perform computation.

[object Object]

• Parameters

  [object Object]
  • [object Object]Atlas inference series products[object Object]:
    • The data types of [object Object], [object Object], and [object Object] cannot be BFLOAT16.
    • The [object Object] parameter has no effect in the current product scenario.

• 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]

• Boundary value specifications:
  • The output is Inf when the input is Inf.
  • The output is NaN when the input is NaN.
• Deterministic computation:
  • aclnnInplaceAddRmsNorm defaults to a deterministic implementation.

[object Object]

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