BUG: no activation pre-softmax

network.py

@@ -52,7 +52,9 @@ def init_inference(self, config):
  # Reduce the time-dimension to make a single prediction
  acts = tf.reduce_mean(acts, axis=1)
 
- self.logits = tf.contrib.layers.fully_connected(acts, self.output_dim)
+ self.logits = tf.contrib.layers.fully_connected(acts,
+ self.output_dim,
+ activation_fn=None)
  self.probs = tf.nn.softmax(self.logits)
 
  def init_loss(self):
@@ -110,9 +112,9 @@ def set_momentum(self, session):
  #TODO: write a builder nicely later
  def get_optimizer(self, config):
  logger.debug("Config " + str(config))
- 
+
  optimizer_name = config.get('name')
- 
+
  if optimizer_name.lower() == 'momentum':
  return tf.train.MomentumOptimizer(config.get('learning_rate'), self.mom_var)
  elif optimizer_name.lower() == 'adam':
@@ -125,10 +127,10 @@ def get_optimizer(self, config):
  beta_2 = config.get('beta_2')
  if config.get('epsilon') != None:
  t_epsilon = config.get('epsilon')
- 
+
  return tf.train.AdamOptimizer(config.get('learning_rate'), beta1=beta_1, beta2=beta_2, epsilon=t_epsilon)
  return tf.train.GradientDescentOptimizer(config.get('learning_rate'))
- 
+
 
  def feed_dict(self, inputs, labels=None):
  """