from __future__ import absolute_import
from __future__ import division
from __future__ import print_function

import tensorflow as tf
import tensorflow.contrib.slim as slim

def vision_net(inputs, num_classes=10):
  conv1 = slim.conv2d(inputs, 16, [8, 8], 4, scope="conv1")
  conv2 = slim.conv2d(conv1, 32, [4, 4], 2, scope="conv2")
  fc1 = slim.conv2d(conv2, 512, [10, 10], padding="VALID", scope="fc1")
  fc2 = slim.conv2d(fc1, num_classes, [1, 1], activation_fn=None, normalizer_fn=None, scope="fc2")
  return tf.squeeze(fc2, [1, 2])