caffe: model definition: write same layer with different phase using caffe.NetSpec()

Question

I want to set up a caffe CNN with python, using caffe.NetSpec() interface. Although I saw we can put test net in solver.prototxt, I would like to w

Answer 1

I found another way.
I could solve this problem returning the proto string.
Basically, you can add strings with the layers that are going to be replaced (in my case, the first layer).

def lenet(path_to_lmdb_train, path_to_lmdb_test,
          batch_size_train, batch_size_test ):
    n = caffe.NetSpec()
    n.data, n.label = L.Data(batch_size=batch_size_train, backend=P.Data.LMDB, source=path_to_lmdb_train,
                             include=dict(phase=caffe.TRAIN), transform_param=dict(scale=1./255), ntop=2)
    first_layer = str(n.to_proto())

    n.data, n.label = L.Data(batch_size=batch_size_test, backend=P.Data.LMDB, source=path_to_lmdb_test,
                             include=dict(phase=caffe.TEST), transform_param=dict(scale=1./255), ntop=2)
    n.conv1 = L.Convolution(n.data, kernel_size=5, num_output=20, weight_filler=dict(type='xavier'))
    n.pool1 = L.Pooling(n.conv1, kernel_size=2, stride=2, pool=P.Pooling.MAX)
    n.conv2 = L.Convolution(n.pool1, kernel_size=5, num_output=50, weight_filler=dict(type='xavier'))
    n.pool2 = L.Pooling(n.conv2, kernel_size=2, stride=2, pool=P.Pooling.MAX)
    n.ip1 = L.InnerProduct(n.pool2, num_output=500, weight_filler=dict(type='xavier'))
    n.relu1 = L.ReLU(n.ip1, in_place=True)
    n.ip2 = L.InnerProduct(n.relu1, num_output=10, weight_filler=dict(type='xavier'))
    n.loss = L.SoftmaxWithLoss( n.ip2, n.label )
    n.accuracy = L.Accuracy( n.ip2, n.label, include=dict(phase=caffe.TEST) )

    return first_layer + str(n.to_proto())