import tensorflow as tf

            inputs=conv1_bn,
            pool_size=[2, 2],
            strides=2,
            name='pool1'
        )

        conv2 = tf.layers.conv2d(
            inputs=pool1,
            filters=64,
            kernel_size=[5,5],
            padding='same',
            use_bias=False,
            name='conv2'
        )
        conv2_bn = tf.nn.relu(tf.layers.batch_normalization(conv2, training=train))
        pool2 = tf.layers.max_pooling2d(
            inputs=conv2_bn,
            pool_size=[2, 2],
            strides=2,
            name='pool2'
        )

        v = tf.reshape(pool2, [-1, 4096])

        fc1 = tf.layers.dense(
            inputs=v,
            units=1024,
            activation=tf.nn.relu,
            use_bias=True,
            name='fc1'
