Make the default for `run_eagerly` the value of

`tf.config.experimental_run_functions_eagerly`

PiperOrigin-RevId: 251570860

tensorflow/python/keras/engine/training.py

@@ -27,6 +27,7 @@ from tensorflow.python.data.ops import dataset_ops
 from tensorflow.python.data.ops import iterator_ops
 from tensorflow.python.distribute import distribution_strategy_context
 from tensorflow.python.eager import context
+from tensorflow.python.eager import def_function
 from tensorflow.python.eager import monitoring
 from tensorflow.python.framework import composite_tensor_utils
 from tensorflow.python.framework import constant_op
@@ -403,7 +404,9 @@ class Model(network.Network):
                        'is enabled.')
     if not self.dynamic:
       if self._run_eagerly is None:
-        return False
+        # Respect `tf.config.experimental_run_functions_eagerly` unless
+        # `run_eagerly` was explicitly passed to `compile`.
+        return def_function.RUN_FUNCTIONS_EAGERLY
       else:
         return self._run_eagerly
     else:

tensorflow/python/keras/engine/training_test.py

@@ -30,6 +30,7 @@ from tensorflow.python import keras
 from tensorflow.python import tf2
 from tensorflow.python.data.ops import dataset_ops
 from tensorflow.python.eager import context
+from tensorflow.python.eager import def_function
 from tensorflow.python.eager import function
 from tensorflow.python.framework import ops
 from tensorflow.python.framework import tensor_shape
@@ -81,6 +82,16 @@ class CompileTest(keras_parameterized.TestCase):
         self.assertEqual(model.loss_functions[i].fn, loss_list[i])
     self.assertAllEqual(model._loss_weights_list, [1.] * len(loss_list))
 
+  def test_respect_run_functions_eagerly(self):
+    with context.eager_mode():
+      model = testing_utils.get_small_sequential_mlp(
+          num_hidden=10, num_classes=2, input_dim=3)
+      model.compile('sgd', 'mse')
+      def_function.run_functions_eagerly(True)
+      self.assertTrue(model.run_eagerly)
+      def_function.run_functions_eagerly(False)
+      self.assertFalse(model.run_eagerly)
+
   @keras_parameterized.run_all_keras_modes
   @parameterized.named_parameters(('loss_string', 'mse'),
                                   ('loss_function', losses.mean_squared_error),