[object Object]

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

• Operator function: Performs multiplication computation between the tensor and scalar.
• Formula:$$out_i = self_i \times other$$

[object Object]

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

  • [object Object]: An output tensor object needs to be created to store the computation result.
  • [object Object]: No output tensor object needs to be created, and the computation result is stored in the memory of the input tensor.

• 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]
  • [object Object]
  • [object Object]
  • [object Object]

[object Object]

• Parameters:

  • [object Object] (const aclTensor *, computation input): input [object Object] in the formula, which is an aclTensor on the device. The shape dimensions cannot be greater than 8. are supported. The can be ND.

    • [object Object]Atlas inference products[object Object] and [object Object]Atlas training products[object Object]: The data type can be FLOAT, FLOAT16, DOUBLE, INT32, INT64, INT16, INT8, UINT8, BOOL, COMPLEX128, or COMPLEX64, and must meet the deduction relationship (see ) with [object Object].
    • [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]: The data type can be FLOAT, FLOAT16, DOUBLE, INT32, INT64, INT16, INT8, UINT8, BOOL, COMPLEX128, COMPLEX64, or BFLOAT16, and must meet the deduction relationship (see ) with [object Object].

  • other (aclScalar *, computation input): input [object Object] in the formula, which is an aclScalar on the host.

    • [object Object]Atlas inference products[object Object] and [object Object]Atlas training products[object Object]: The data type can be FLOAT, FLOAT16, DOUBLE, INT32, INT64, INT16, INT8, UINT8, BOOL, COMPLEX128, or COMPLEX64, and must meet the deduction relationship (see ) with [object Object].
    • [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]: The data type can be FLOAT, FLOAT16, DOUBLE, INT32, INT64, INT16, INT8, UINT8, BOOL, COMPLEX128, COMPLEX64, or BFLOAT16, and must meet the deduction relationship (see ) with [object Object].

  • [object Object] (aclTensor *, computation output): output [object Object] in the formula, which is an aclTensor on the device. The shape is the same as that of the input [object Object]. are supported. The can be ND. The data type must be convertible from that after [object Object] and [object Object] are deduced. For details, see .

    • [object Object]Atlas inference products[object Object] and [object Object]Atlas training products[object Object]: The data type can be FLOAT, FLOAT16, DOUBLE, INT32, INT64, INT16, INT8, UINT8, BOOL, COMPLEX128, or COMPLEX64.
    • [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]: The data type can be FLOAT, FLOAT16, DOUBLE, INT32, INT64, INT16, INT8, UINT8, BOOL, COMPLEX128, COMPLEX64, or BFLOAT16.

  • [object Object] (uint64_t *, output): size of the workspace to be allocated on the device.

  • [object Object] (aclOpExecutor **, output): operator executor, covering the operator computation process.

• Returns:

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

[object Object]

• Parameters:

  • [object Object] (void *, input): address of the workspace to be allocated on the device.
  • [object Object] (uint64_t, input): size of the workspace to be allocated on the device, which is obtained by calling the first-phase API [object Object].
  • [object Object] (aclOpExecutor *, input): operator executor, containing the operator computation process.
  • [object Object] (aclrtStream, input): stream for executing the task.

• Returns:

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

[object Object]

• Parameters:

  • [object Object] (aclTensor *, computation input | computation output): input and output tensor, that is, [object Object] and [object Object] in the formula. It is the aclTensor on the device. are supported. The can be ND.
    • [object Object]Atlas inference products[object Object] and [object Object]Atlas training products[object Object]: The data type can be FLOAT, FLOAT16, DOUBLE, INT32, INT64, INT16, INT8, UINT8, BOOL, COMPLEX128, or COMPLEX64, and must meet the deduction relationship (see ) with [object Object].
    • [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]: The data type can be FLOAT, FLOAT16, DOUBLE, INT32, INT64, INT16, INT8, UINT8, BOOL, COMPLEX128, COMPLEX64, or BFLOAT16, and must meet the deduction relationship (see ) with [object Object].
  • [object Object] (aclScalar *, computation input): input <idp:inline displayname="code" id="code17858186219">other[object Object] in the formula, which is an aclScalar on the host.
    • [object Object]Atlas inference products[object Object] and [object Object]Atlas training products[object Object]: The data type can be FLOAT, FLOAT16, DOUBLE, INT32, INT64, INT16, INT8, UINT8, BOOL, COMPLEX128, or COMPLEX64, and must meet the deduction relationship (see ) with [object Object].
    • [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]: The data type can be FLOAT, FLOAT16, DOUBLE, INT32, INT64, INT16, INT8, UINT8, BOOL, COMPLEX128, COMPLEX64, or BFLOAT16, and must meet the deduction relationship (see ) with [object Object].
  • [object Object] (uint64_t *, output): size of the workspace to be allocated on the device.
  • [object Object] (aclOpExecutor **, output): operator executor, covering the operator computation process.

• Returns:

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

[object Object]

• Parameters:

  • [object Object] (void *, input): address of the workspace to be allocated on the device.
  • [object Object] (uint64_t, input): size of the workspace to be allocated on the device, which is obtained by calling the first-phase API [object Object].
  • [object Object] (aclOpExecutor *, input): operator executor, containing the operator computation process.
  • [object Object] (aclrtStream, input): stream for executing the task.

• Returns:

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

[object Object]

• Deterministic computing:

  • [object Object] defaults to a deterministic implementation.

  When [object Object] is of the float type, there is no precision loss. When [object Object] is of the int32 or int64 type, precision loss may occur if the value of [object Object] is greater than 2^24. In this case, is recommended.

[object Object]

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

aclnnMuls sample code:

aclnnInplaceMuls sample code: