Merge branch 'keras-2' of github.com:fchollet/keras into keras-2

Author: fchollet

keras/engine/training.py

@@ -1518,7 +1518,7 @@ def evaluate(self, x, y, batch_size=32, verbose=1, sample_weight=None):
             check_batch_axis=False,
             batch_size=batch_size)
         # prepare inputs, delegate logic to _test_loop
-        if self.uses_learning_phase and not isinstance(K.learning_phase, int):
+        if self.uses_learning_phase and not isinstance(K.learning_phase(), int):
             ins = x + y + sample_weights + [0.]
         else:
             ins = x + y + sample_weights
@@ -1562,7 +1562,7 @@ def predict(self, x, batch_size=32, verbose=0):
                                  'Batch size: ' + str(batch_size) + '.')
 
         # prepare inputs, delegate logic to _predict_loop
-        if self.uses_learning_phase and not isinstance(K.learning_phase, int):
+        if self.uses_learning_phase and not isinstance(K.learning_phase(), int):
             ins = x + [0.]
         else:
             ins = x
@@ -1612,7 +1612,7 @@ def train_on_batch(self, x, y,
             sample_weight=sample_weight,
             class_weight=class_weight,
             check_batch_axis=True)
-        if self.uses_learning_phase and not isinstance(K.learning_phase, int):
+        if self.uses_learning_phase and not isinstance(K.learning_phase(), int):
             ins = x + y + sample_weights + [1.]
         else:
             ins = x + y + sample_weights
@@ -1654,7 +1654,7 @@ def test_on_batch(self, x, y, sample_weight=None):
             x, y,
             sample_weight=sample_weight,
             check_batch_axis=True)
-        if self.uses_learning_phase and not isinstance(K.learning_phase, int):
+        if self.uses_learning_phase and not isinstance(K.learning_phase(), int):
             ins = x + y + sample_weights + [0.]
         else:
             ins = x + y + sample_weights
@@ -1675,7 +1675,7 @@ def predict_on_batch(self, x):
         """
         x = _standardize_input_data(x, self._feed_input_names,
                                     self._feed_input_shapes)
-        if self.uses_learning_phase and not isinstance(K.learning_phase, int):
+        if self.uses_learning_phase and not isinstance(K.learning_phase(), int):
             ins = x + [0.]
         else:
             ins = x