docs/tutorial/layers/relu.md
Layer type: ReLU
CPU implementation: ./src/caffe/layers/relu_layer.cpp
CUDA GPU implementation: ./src/caffe/layers/relu_layer.cu
Sample (as seen in ./models/bvlc_reference_caffenet/train_val.prototxt)
layer {
name: "relu1"
type: "ReLU"
bottom: "conv1"
top: "conv1"
}
Given an input value x, The ReLU layer computes the output as x if x > 0 and negative_slope * x if x <= 0. When the negative slope parameter is not set, it is equivalent to the standard ReLU function of taking max(x, 0). It also supports in-place computation, meaning that the bottom and the top blob could be the same to preserve memory consumption.
ReLUParameter relu_param)
negative_slope [default 0]: specifies whether to leak the negative part by multiplying it with the slope value rather than setting it to 0../src/caffe/proto/caffe.proto:{% highlight Protobuf %} {% include proto/ReLUParameter.txt %} {% endhighlight %}