[object Object]

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

• Function: Checks whether each element in the input tensor is greater than or equal to the value of the other scalar. A tensor of the Bool type is returned, indicating whether the condition is met for each element in the input tensor.

• Formula: For the input parameter [object Object] and the comparison scalar [object Object], [object Object] can be expressed by the following formula:

  $$out_{i}= (self_i >= other) ? True : False$$

[object Object]

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

• 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 performs 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 computing:
  • [object Object] and [object Object] default to deterministic implementation.

[object Object]

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

• The following is the sample code of aclnnGeScalar for Ascend 950PR/Ascend 950DT, [object Object]Atlas A3 training products/Atlas A3 inference products[object Object], [object Object]Atlas A2 training products/Atlas A2 inference products[object Object], [object Object]Atlas inference products[object Object], and [object Object]Atlas training products[object Object]:

• Sample code of aclnnInplaceGeScalar for the Ascend 950PR/Ascend 950DT, [object Object]Atlas A3 training products/Atlas A3 inference products[object Object], [object Object]Atlas A2 training products/Atlas A2 inference products[object Object], [object Object]Atlas inference products[object Object], and [object Object]Atlas training products[object Object]: