return to_proto(self)
+ def _to_proto(self, layers, names, autonames):
+ return self.fn._to_proto(layers, names, autonames)
+
class Function(object):
"""A Function specifies a layer, its parameters, and its inputs (which
return
bottom_names = []
for inp in self.inputs:
- inp.fn._to_proto(layers, names, autonames)
+ inp._to_proto(layers, names, autonames)
bottom_names.append(layers[inp.fn].top[inp.n])
layer = caffe_pb2.LayerParameter()
layer.type = self.type_name
autonames = Counter()
layers = OrderedDict()
for name, top in six.iteritems(self.tops):
- top.fn._to_proto(layers, names, autonames)
+ top._to_proto(layers, names, autonames)
net = caffe_pb2.NetParameter()
net.layer.extend(layers.values())
return net