message: Moar comments.
diff: @@ -32,8 +32,9 @@ def get_default_hyperparams() -> Dict:
  In other words, returns a dict whose paramaters come from the AGZ paper:
  {
  - k: number of filters (AlphaGoZero used 256)
  - fc_width: ???
  + k: number of filters (AlphaGoZero used 256). We use 128 by default for
  + a 19x19 go board.
  + fc_width: Dimensionality of the fully connected linear layer
  num_shared_layers: number of shared residual blocks. AGZ used both 19
  and 39. Here we use 19 because it's faster to train.
  l2_strength: The L2 regularization parameter. Note AGZ paper has this
  @@ -60,8 +61,7 @@ class DualNetwork(object):
  self.session = tf.Session()
  self.name = None
  if use_cpu:
  - # TODO(jhoak): Why is this here? tf.device should only be for
  - # graphing.
  + # Set up the computation-graph context to use CPU context
  with tf.device("/cpu:0"):
  self.set_up_network()
  else:
  