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

Note: When using this API, ensure that the driver firmware package and CANN package are in the 8.0.RC2 version or later. Otherwise, an error, such as BUS ERROR, will be reported.

[object Object]

• Description: Performs mm + reduce_scatter_base computation.

• Formula:

$$output=reduce_scatter(x1@x2+bias)$$ [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 process. Then, [object Object] is called to perform computation.

[object Object]

• Parameters

  [object Object]

• Returns

  [object Object]: 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

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

[object Object]

• Deterministic compute:

  • [object Object] defaults to a non-deterministic implementation. You can call [object Object] to enable deterministic compute.

• Input [object Object] must be 2D with shape [object Object]. m must be an integer multiple of [object Object].

• Input [object Object] must be 2D with shape [object Object]. The axes must meet the input parameter requirements of the [object Object] operator. The k axes must be equal and fall within the range of [256, 65535).

• [object Object] and [object Object] support empty tensors. m and n can be empty, but k cannot be empty. The following conditions must be met:

  • m is empty, k is not empty, and n is not empty.
  • If m is not empty, k is not empty, and n is empty.
  • If m is empty, k is not empty, and n is empty.

• Matrix [object Object] can be transposed or not transposed, and matrix [object Object] can only be not transposed.

• The data type of [object Object] and [object Object] must be the same as that of output.

• [object Object] does not support non-zero input.

• The output is 2D with shape (m/rank_size, n), where [object Object] indicates the number of devices.

• [object Object]Atlas A2 training products/Atlas A2 inference products[object Object]: supports two, four, or eight devices and only the all mesh networking of HCCS links.

• [object Object]Atlas A3 training products/Atlas A3 inference products[object Object]: supports two, four, eight, sixteen, or thirty-two devices and only the double ring networking of HCCS links.

• [object Object]Atlas A2 training products/Atlas A2 inference products[object Object]: supports only one communication domain for MC2 operators within a model.

[object Object]

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

• [object Object]Atlas A2 training products/Atlas A2 inference products[object Object] and [object Object]Atlas A3 training products/Atlas A3 inference products[object Object]:

  [object Object]