gen_merged_model.py 文件源码

def load_and_fill_biases(src_model, src_weights, dst_model, dst_weights):
    with open(src_model) as f:
        model = caffe.proto.caffe_pb2.NetParameter()
        pb.text_format.Merge(f.read(), model)

    for i, layer in enumerate(model.layer):
        if layer.type == 'Convolution': # or layer.type == 'Scale':
            # Add bias layer if needed
            if layer.convolution_param.bias_term == False:
                layer.convolution_param.bias_term = True
                layer.convolution_param.bias_filler.type = 'constant'
                layer.convolution_param.bias_filler.value = 0.0

    with open(dst_model, 'w') as f:
        f.write(pb.text_format.MessageToString(model))

    caffe.set_mode_cpu()
    net_src = caffe.Net(src_model, src_weights, caffe.TEST)
    net_dst = caffe.Net(dst_model, caffe.TEST)
    for key in net_src.params.keys():
        for i in range(len(net_src.params[key])):
            net_dst.params[key][i].data[:] = net_src.params[key][i].data[:]

    if dst_weights is not None:
        # Store params
        pass

    return net_dst