import tensorflow as tf


import layers
import networks


def _get_grad_norm(ys, xs):
  """Compute 2-norm of dys / dxs."""
  return tf.sqrt(
      tf.add_n([tf.reduce_sum(tf.square(g)) for g in tf.gradients(ys, xs)]))


def _num_filters_stub(block_id):
  return networks.num_filters(block_id, 8, 1, 8)


class NetworksTest(tf.test.TestCase):
