Enable Model training/eval from generator in eager execution. Fixes t…

…ensorflow#18287

PiperOrigin-RevId: 196171525

tensorflow/python/keras/_impl/keras/engine/training_eager_test.py

@@ -402,6 +402,24 @@ def test_model_methods_with_eager_tensors_single_io(self):
     model.train_on_batch(inputs, targets)
     model.test_on_batch(inputs, targets)
 
+  def test_generator_methods(self):
+    model = keras.Sequential()
+    model.add(keras.layers.Dense(4, input_shape=(3,)))
+    optimizer = RMSPropOptimizer(learning_rate=0.001)
+    model.compile(optimizer, 'mse', metrics=['mae'])
+
+    x = np.random.random((10, 3))
+    y = np.random.random((10, 4))
+
+    def iterator():
+      while 1:
+        yield x, y
+
+    model.fit_generator(iterator(), steps_per_epoch=3, epochs=1)
+    model.evaluate_generator(iterator(), steps=3)
+    out = model.predict_generator(iterator(), steps=3)
+    self.assertEqual(out.shape, (30, 4))
+
 
 class LossWeightingTest(test.TestCase):
 

tensorflow/python/keras/_impl/keras/engine/training_generator.py

@@ -49,9 +49,6 @@ def fit_generator(model,
   epoch = initial_epoch
 
   do_validation = bool(validation_data)
-  model._make_train_function()
-  if do_validation:
-    model._make_test_function()
 
   is_sequence = isinstance(generator, Sequence)
   if not is_sequence and use_multiprocessing and workers > 1:
@@ -252,8 +249,6 @@ def evaluate_generator(model,
                        workers=1,
                        use_multiprocessing=False):
   """See docstring for `Model.evaluate_generator`."""
-  model._make_test_function()
-
   steps_done = 0
   wait_time = 0.01
   all_outs = []
@@ -346,8 +341,6 @@ def predict_generator(model,
                       use_multiprocessing=False,
                       verbose=0):
   """See docstring for `Model.predict_generator`."""
-  model._make_predict_function()
-
   steps_done = 0
   wait_time = 0.01
   all_outs = []