[object Object]

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

Description: Zeros input elements randomly with a probability of [object Object] and scales the output by [object Object] during training.

$$out_i=\begin{cases}0,&\text { with probability }p \\\frac{1}{1-p}input_i,&\text { with probability }1-p\end{cases}$$ [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]
• [object Object]

[object Object]

• Parameters

  • [object Object] (aclTensor*, computation input): tensor to be processed, [object Object] in the formula, [object Object] on the device. Empty tensors are not supported. are supported. The can be ND.

    • [object Object]Atlas training products[object Object]: The data type can be FLOAT16 or FLOAT32.
    • [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 BFLOAT16, FLOAT16, or FLOAT32.

  • [object Object] (double, computation input): DOUBLE type on the host, probability of setting elements to zero, [object Object] in the formula. The data type can be DOUBLE. The value range is [0, 1].

  • [object Object] (bool, computation input): BOOL type on the host, indicating whether the scenario is a training scenario. The data type can be BOOL.

  • [object Object] (int64_t, computation input): INT64 type on the host, random number seed, which affects the generated random number sequence. The data type can be INT64.

  • [object Object] (int64_t, computation input): INT64 type on the host, random number offset, which affects the position of the generated random number sequence. The data type can be INT64.

  • [object Object] (aclTensor*, computation output): output tensor, [object Object] in the formula, [object Object] on the device. The data type must be convertible from the input. The shape must be the same as that of [object Object]. are supported. The can be ND.

    • [object Object]Atlas training products[object Object]: The data type can be FLOAT16 or FLOAT32.
    • [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 BFLOAT16, FLOAT16, or FLOAT32.

  • [object Object] (aclTensor*, computation output): bitmask data stored as UINT8. [object Object] on the device. The data type can be UINT8. The shape must be ([object Object](number of elements in [object Object], 128)/8), indicating that the number of bits must be aligned with 128. [object Object] indicates that the number of elements in the input is rounded up to a multiple of 128. For example, the result of align (1111, 128) is 1152. are supported. The can be ND. If [object Object] is set to [object Object] or [object Object], or [object Object] is set to [object Object], the passed [object Object] is not processed. In other scenarios, the [object Object] is generated using the given [object Object] as the zero probability.

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

  • [object Object] (aclOpExecutor**, output): operator executor, containing 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 computation:
  • [object Object] defaults to a deterministic implementation.

[object Object]

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