[object Object]

Note: This API will be deprecated in later versions. Use aclnnMatmulAllReduce and aclnnAddRmsNorm instead.

[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 the MatMul, AllReduce, addition, and RMSNorm computation in sequence.
• Formula:$$mm\_out = all_reduce(x1 @ x2 + bias)$$ $$y = mm\_out + residual$$ $$normOut = \frac{y}{RMS(y)} * gamma, RMS(y) = \sqrt{\frac{1}{d} \sum_{i=1}^{d} y_{i}^{2} + epsilon}$$

[object Object]

• [object Object] and [object Object] implement the same function in different ways. Select a proper operator based on your requirements.

  • [object Object]: Two output tensor objects [object Object] and [object Object] need to be created to store the computation result.
  • [object Object]: One output tensor [object Object] needs to be created. The results that would have been stored in the output tensor [object Object] in the original non-inplace scenario are directly written to the memory of the input tensor [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 computation:

  • [object Object] defaults to non-deterministic implementation. You can set the HCCL_DETERMINISTIC environment variable to true to enable deterministic computation.

• The application scenario is the same as that of [object Object]. MC2 is disabled in incremental scenarios but enabled in full scenarios.

• The input [object Object] can be 2D or 3D with shape (m, k) or (b, s, k). [object Object] must be 2D with shape (k, n). The axes meet the input parameter requirements of the MatMul operator, and the k axes of [object Object] and [object Object] are equal. If [object Object] is not empty, it must be 1D with shape (n).

• The values of b*s, [object Object], [object Object], and [object Object] cannot exceed [object Object] (INT32_MAX).

• The input [object Object] must be 3D with shape (b, s, n). When [object Object] is 2D, (b*s) of [object Object] equals [object Object] of [object Object]. The input [object Object] must be 1D with shape (n).

• The shapes and data types of the outputs [object Object] and [object Object] are the same as those of [object Object], with the shape (b, s, n).

• The data types of the inputs [object Object], [object Object], [object Object], [object Object], [object Object], [object Object], and [object Object] must be the same.

• The [object Object] matrix cannot be transposed. The [object Object] matrix can be transposed or not transposed.

• 1, 2, 4, and 8 ranks are supported, and only the all-mesh networking of HCCS links is supported.

• Empty tensors with (b*s) and [object Object] being [object Object] are supported. Empty tensors with [object Object] being [object Object] are not supported.

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

[object Object]

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

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