[object Object]

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

• Function: Returns the correction result of the input tensor under the specified indices based on the given maxNorm and normType.

• Formula for vector norm, where p indicates the norm type specified by normType:

  $$||X||_{p}=\sqrt[p]{\sum_{i=1}^nx_{i}^p}$$ $$Where X = (x_{1}, x_{2}, ..., x_{n}), x_{n})$$

  If the computed norm is greater than maxNorm, normalization is applied by multiplying the elements along the zeroth dimension specified by indices by the following coefficient:

  $$scalar = \frac{maxNorm}{currentNorm+1e^{-7}}$$

[object Object]

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

[object Object]

• Parameters

  [object Object]
  • [object Object]Atlas inference products[object Object] and [object Object]Atlas training products[object Object]: The data type cannot be BFLOAT16.

• Returns

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

  The first-phase API implements input parameter validation. The following error codes may be returned.

  [object Object]

[object Object]

• Parameters

  [object Object]

• Returns

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

[object Object]

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

[object Object]

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