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• Description: Performs element-wise multiplication of each tensor in the input tensor list by the corresponding scalar in the scalar list.

• Formula:

  $$x = [{x_0}, {x_1}, ... {x_{n-1}}]\\ scalars = [{scalars_0}, {scalars_1}, ... {scalars_{n-1}}]\\ y = [{y_0}, {y_1}, ... {y_{n-1}}]\\$$ $$y_i = x_i * scalars_i (i=0,1,...n-1)$$

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

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• Parameters

  [object Object]

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

    The data type of [object Object] must be FLOAT32 or INT64 and depends on that of [object Object]:

    • When [object Object] is of the FLOAT32, FLOAT16, or BFLOAT16 type, [object Object] must be FLOAT32.
    • When [object Object] is of the INT32 type, [object Object] must be INT64.

• Returns

  aclnnStatus: status code. For details, see .

  The first-phase API implements input parameter verification. The following errors may be thrown.

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• Parameters

  [object Object]

• Returns

  aclnnStatus: status code. For details, see .

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

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