Run non-optimization updates on predict for stateful RNN's

.gitignore

@@ -9,6 +9,7 @@ keras/datasets/temp/*
 docs/site/*
 docs/theme/*
 tags
+Keras.egg-info
 
 # test-related
 .coverage

keras/layers/containers.py

@@ -113,6 +113,11 @@ def set_weights(self, weights):
             self.layers[i].set_weights(weights[:nb_param])
             weights = weights[nb_param:]
 
+    def reset_states(self):
+        for layer in self.layers:
+            if hasattr(layer, 'reset_states') and getattr(layer, 'stateful', False):
+                layer.reset_states()
+
     def get_config(self):
         return {"name": self.__class__.__name__,
                 "layers": [layer.get_config() for layer in self.layers]}

keras/models.py

@@ -419,7 +419,7 @@ def compile(self, optimizer, loss,
 
         self._train = K.function(train_ins, [train_loss], updates=updates)
         self._train_with_acc = K.function(train_ins, [train_loss, train_accuracy], updates=updates)
-        self._predict = K.function(predict_ins, [self.y_test])
+        self._predict = K.function(predict_ins, [self.y_test], updates=self.updates)
         self._test = K.function(test_ins, [test_loss])
         self._test_with_acc = K.function(test_ins, [test_loss, test_accuracy])