import tensorflow as tf

def guard_nan(x):
  return x if not math.isnan(x) else -1.


def _blur_expand(input):
  k_size = 9
  kernels = [2, 4, 6]
  channels = [input] + [nut.blur_gaussian(input, k, k_size)[0] for k in kernels]
  res = tf.concat(channels, axis=3)
  return res


class Autoencoder:
  train_set, test_set = None, None
  permutation = None
  batch_shape = None
