Merge pull request #11 from lucasb-eyer/empty-stats

Don't compile/call function when there's no stats to be accumulated.

Author: ikostrikov2

beacon8/layers/BatchNormalization.py

@@ -42,7 +42,7 @@ def symb_forward(self, symb_input):
         else:
             return symb_input * self.inference_weight.dimshuffle(*d_shuffle) + self.inference_bias.dimshuffle(*d_shuffle)
 
-    def get_stat_updates(self,):
+    def get_stat_updates(self):
         assert (self.batch_mean is not None) and (self.batch_var is not None), "You need to do a forward pass first"
 
         stat_updates = list()
@@ -66,4 +66,4 @@ def training(self):
     def evaluate(self):
         Module.evaluate(self)
         self.inference_weight.set_value(self.weight.get_value() / _np.sqrt(self.buffer_variance.get_value() + self.eps))
-        self.inference_bias.set_value(self.bias.get_value() - self.inference_weight.get_value() * self.buffer_mean.get_value())
+        self.inference_bias.set_value(self.bias.get_value() - self.inference_weight.get_value() * self.buffer_mean.get_value())

beacon8/layers/Module.py

@@ -81,6 +81,10 @@ def accumulate_statistics(self, data_in):
             self.symb_forward(symb_in)
 
             stat_updates = self.get_stat_updates()
+            if not stat_updates:
+                # If there's no layer collecting statistics, we don't need to
+                # compile and call a function. This prevents theano errors.
+                return
 
             self.fn_accum_stats = _th.function(
                 inputs=[symb_in],