• Layer type: ReLU

• Doxygen Documentation

• Header: ./include/caffe/layers/relu_layer.hpp

• 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.

• Parameters (ReLUParameter relu_param)
  • Optional
    • negative_slope [default 0]: specifies whether to leak the negative part by multiplying it with the slope value rather than setting it to 0.
• From ./src/caffe/proto/caffe.proto:

{% highlight Protobuf %} {% include proto/ReLUParameter.txt %} {% endhighlight %}