[object Object]

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

• Function: Calculates the KL divergence.
• Formulas:

  • Defines loss_pointwise and saves the intermediate result.

    $$loss\_pointwise_i=\begin{cases} NaN & \text{ if }&logTarget=false \text{ and } target_i <= 0, \\ target_i * \left ( \log{(target_i)}- self_i \right ) & \text{ if }& logTarget=false, \\ \exp^ {target_i} * \left ( target_i- self_i \right ) & \text{ else. } \end{cases}$$

  • Formula for computing [object Object]:

    $$out=\begin{cases} \bar{loss\_pointwise} & \text{ if }& reduction= 1, \\ \sum loss\_pointwise & \text{ elif }& reduction= 2,\\ \frac{\sum loss\_pointwise}{self.size(0)} & \text{ elif }& reduction= 3,\\ loss\_pointwise & \text{ else. } \end{cases}$$

[object Object]

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

[object Object]

• Parameter description:

  [object Object]
  • [object Object]Atlas inference products[object Object] and [object Object]Atlas training products[object Object]: BFLOAT16 is not supported.

• Returns

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

  The first-phase API performs input parameter validation. The following errors may be returned:

  [object Object]

[object Object]

• Parameter description:

  [object Object]

• Returns

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

[object Object]

• Deterministic computation:
  • Default deterministic implementation of aclnnKlDiv.

[object Object]

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