compute_bn_statistics_depth.py 文件源码

def make_testable(train_model_path):
    # load the train net prototxt as a protobuf message
    with open(train_model_path) as f:
        train_str = f.read()
    train_net = caffe_pb2.NetParameter()
    text_format.Merge(train_str, train_net)

    # add the mean, var top blobs to all BN layers
    for layer in train_net.layer:
        #print layer.type 
        #print type(layer.top)
        if layer.type == "BN" and len(layer.top) == 1:
            layer.top.append(layer.top[0] + "-mean")
            layer.top.append(layer.top[0] + "-var")

    # remove the test data layer if present
    if train_net.layer[1].name == "data" and train_net.layer[1].include:
        train_net.layer.remove(train_net.layer[1])
        if train_net.layer[0].include:
            # remove the 'include {phase: TRAIN}' layer param
            train_net.layer[0].include.remove(train_net.layer[0].include[0])
    return train_net