import tensorflow as tf

        else:
            block_conv_input = bottom
        input_filter = bottom.get_shape().as_list()[-1]
        block_conv_1 = self.conv_layer(bottom, 1, input_filter, channel_list[0], 1, name + "_branch2a")
        block_norm_1 = tf.layers.batch_normalization(inputs=block_conv_1, axis = 3, momentum=configs['_BATCH_NORM_DECAY'], epsilon=configs['_BATCH_NORM_EPSILON'], center=True, scale=True, training=self.is_training, fused=True)
        block_relu_1 = tf.nn.relu(block_norm_1)

        block_conv_2 = self.conv_layer(block_relu_1, 3, channel_list[0], channel_list[1], 1, name + "_branch2b")
        block_norm_2 = tf.layers.batch_normalization(inputs=block_conv_2, axis = 3, momentum=configs['_BATCH_NORM_DECAY'], epsilon=configs['_BATCH_NORM_EPSILON'], center=True, scale=True, training=self.is_training, fused=True)
        block_relu_2 = tf.nn.relu(block_norm_2)
