CaffeUNet_2D.py 文件源码

def add_batchnormscale(self, input, name):

        if True : # necessary?
            batch_norm_param={'moving_average_fraction': 0.95, 'use_global_stats': True }
            param = [dict(lr_mult=0),dict(lr_mult=0),dict(lr_mult=0)]
            l = L.BatchNorm(input, name=name+'_bn', batch_norm_param=batch_norm_param, param=param, include={'phase': caffe.TEST}, ntop=1)
            setattr(self.net_spec, name+'_bn', l)

            batch_norm_param={'moving_average_fraction': 0.95, 'use_global_stats': False }
            l = L.BatchNorm(input, name=name+'_bn', top=name+'_bn', batch_norm_param=batch_norm_param, param=param, include={'phase': caffe.TRAIN}, ntop=0)
            setattr(self.net_spec, name+'_bn' + '_train', l)

            l = L.Scale(getattr(self.net_spec, name+'_bn'), scale_param = { 'bias_term': True } )
            setattr(self.net_spec, name, l)
        else : # here without split in use_global_stats True/False
            l = L.Scale(L.BatchNorm(input), scale_param={'bias_term': True})
            setattr(self.net_spec, name, l)

        return l