caffe-tensorflow
caffe-tensorflow copied to clipboard
What would it take to support multiple inputs from a set of inputs?
graph.py states
# A note on layers and outputs:
# In Caffe, each layer can produce multiple outputs ("tops") from a set of inputs
# ("bottoms"). The bottoms refer to other layers' tops. The top can rewrite a bottom
# (in case of in-place operations). Note that the layer's name is not used for establishing
# any connectivity. It's only used for data association. By convention, a layer with a
# single top will often use the same name (although this is not required).
#
# The current implementation only supports single-output nodes (note that a node can still
# have multiple children, since multiple child nodes can refer to the single top's name).
What would need to be done to add support for multiple-output nodes?