PReLU
PReLU#
Versioned name: PReLU-1
Category: Activation
Short description: Parametric rectified linear unit element-wise activation function.
Detailed description: PReLU operation is introduced in this article. PReLU performs element-wise parametric ReLU operation on a given input tensor, based on the following mathematical formula:
Attributes:
data_format
Description: data_format denotes the data format of the input and output data.
Range of values: NXC or NCX (X means HW for 2D, DHW for 3D)
Type: string
Default value: NXC
Required: no
per_channel_broadcast
Description: per_channel_broadcast denotes whether to apply per_channel broadcast when slope is 1D tensor.
Range of values: False or True
Type: bool
Default value: True
Required: no
Inputs:
1:
input
- input tensor. Required.Type: T
2:
slope
- slope tensor. Required.Type: T
Outputs
1:
output
- output tensor.Type: T
Types:
T: f32, f16, bf16
Note: Inputs and outputs have the same data type denoted by T. For example, if input is f32 tensor, then all other tensors have f32 data type.
Broadcasting rules:
Only slope tensor supports broadcasting semantics. Slope tensor is uni-directionally broadcasted to input if one of the following rules is met:
1: slope is 1D tensor and per_channel_broadcast is set to True, the length of slope tensor is equal to the length of input of channel dimension.
2: slope is 1D tensor and per_channel_broadcast is set to False, the length of slope tensor is equal to the length of input of the rightmost dimension.
3: slope is nD tensor, starting from the rightmost dimension, ::math::input.shape[i] == slope.shape[i] or ::math::slope.shape[i] == 1 or slope dimension i is empty.