PReLUBackprop
PReLUBackprop#
Versioned name: PReLUBackprop-1
Category: Activation
Short description: PReLUBackprop computes gradient for PReLU.
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
Inputs:
1:
input_forward
- original input tensor of PReLU op. Required.Type: T
2:
slope
- slope tensor. Required.Type: T
3:
output_delta
- the gradient tensor with respect to the output. Required.Type: T
Outputs
1:
input_delta
- the gradient tensor with respect to the input of PReLU.2:
slope_delta
- the gradient tensor with respect to the slope.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_forward if one of the following rules is met:
1: PyTorch case: slope is 1D tensor and broadcast per channel, length of slope is equal to the length of input_forward in channel dimension.
2: PyTorch case: slope is 1D tensor and broadcast per tensor, length of slope is equal to 1.
3: Tensorflow case: slope is nD tensor and its dimensions must be equal to the
input_forward
dimensions starting from the second element:slope_shape = input_forward_shape[1:]