def conv(ch, x, s):
    conv_layer = ConvolutionalLayer(n_output_chns=ch, kernel_size=3, feature_normalization='batch', w_initializer=self.initializers['w'])
    acti_layer = ActiLayer(func='selu')
    res_flow = (conv_layer(x, is_training=is_training) + s)
    return acti_layer(res_flow)
def conv(ch, x, s):
    conv_layer = ConvolutionalLayer(n_output_chns=ch, kernel_size=3, feature_normalization='batch', w_initializer=self.initializers['w'])
    acti_layer = ActiLayer(func='selu')
    res_flow = (conv_layer(x, is_training=is_training) + s)
    return acti_layer(res_flow)