Versioned name: PReLUBackprop-1
Short description: PReLUBackprop computes gradient for PReLU.
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)
Default value: NXC
input_forward- original input tensor of PReLU op. Required.
slope- slope tensor. Required.
output_delta- the gradient tensor with respect to the output. Required.
input_delta- the gradient tensor with respect to the input of PReLU.
slope_delta- the gradient tensor with respect to the slope.
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.
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_forwarddimensions starting from the second element:
slope_shape = input_forward_shape[1:]