BaseModel.py 文件源码

def _get_batch_normalization_weights(self,layer_name):
        beta = '%s/batch_normalization/beta:0'%(layer_name)
        gamma = '%s/batch_normalization/gamma:0'%(layer_name)
        mean = '%s/batch_normalization/moving_mean:0'%(layer_name)
        variance = '%s/batch_normalization/moving_variance:0'%(layer_name)
        if self.weights is None or beta not in self.weights:
            print('{:>23} {:>23}'.format(beta, 'using default initializer'))
            return None, None, None, None
        else:
            betax = self.weights[beta]
            gammax = self.weights[gamma]
            meanx = self.weights[mean]
            variancex = self.weights[variance]

            self.loaded_weights[beta]=1
            self.loaded_weights[gamma]=1
            self.loaded_weights[mean]=1
            self.loaded_weights[variance]=1
            #print('{:>23} {:>23}'.format(beta, 'load from %s'%self.flags.load_path))
            return betax,gammax,meanx,variancex