Automated rollback of commit 916df403fb

PiperOrigin-RevId: 230002892

tensorflow/python/keras/engine/base_layer.py

@@ -513,10 +513,11 @@ class Layer(checkpointable.Checkpointable):
       ValueError: if the layer's `call` method returns None (an invalid value).
     """
     input_list = nest.flatten(inputs)
-    # Accept NumPy inputs by converting to Tensors.
-    if all(isinstance(x, (np.ndarray, float, int)) for x in input_list):
-      inputs = nest.map_structure(ops.convert_to_tensor, inputs)
-      input_list = nest.flatten(inputs)
+    if context.executing_eagerly():
+      # Accept NumPy inputs by converting to Tensors when executing eagerly.
+      if all(isinstance(x, (np.ndarray, float, int)) for x in input_list):
+        inputs = nest.map_structure(ops.convert_to_tensor, inputs)
+        input_list = nest.flatten(inputs)
 
     # We will attempt to build a TF graph if & only if all inputs are symbolic.
     # This is always the case in graph mode. It can also be the case in eager

tensorflow/python/keras/engine/base_layer_test.py

@@ -26,8 +26,6 @@ from tensorflow.python.eager import context
 from tensorflow.python.framework import ops
 from tensorflow.python.framework import tensor_shape
 from tensorflow.python.framework import test_util
-from tensorflow.python.keras import keras_parameterized
-from tensorflow.python.keras import testing_utils
 from tensorflow.python.keras.engine import base_layer
 from tensorflow.python.keras.optimizer_v2 import rmsprop
 from tensorflow.python.ops import array_ops
@@ -73,7 +71,7 @@ class InvalidLayer(base_layer.Layer):
     raise ValueError('You did something wrong!')
 
 
-class BaseLayerTest(keras_parameterized.TestCase):
+class BaseLayerTest(test.TestCase, parameterized.TestCase):
 
   @parameterized.parameters(DynamicLayer1, DynamicLayer2)
   def test_dynamic_layer_in_functional_model_in_graph_mode(self, layer_class):
@@ -212,17 +210,6 @@ class BaseLayerTest(keras_parameterized.TestCase):
     with self.assertRaisesRegexp(ValueError, 'You did something wrong!'):
       _ = InvalidLayer()(inputs)
 
-  @keras_parameterized.run_with_all_model_types
-  @test_util.run_in_graph_and_eager_modes
-  def test_build_with_numpy_data(self):
-    model_layers = [
-        keras.layers.Dense(3, activation='relu', kernel_initializer='ones'),
-        keras.layers.Dense(1, activation='sigmoid', kernel_initializer='ones')
-    ]
-    model = testing_utils.get_model_from_layers(model_layers, input_shape=(4,))
-    model(np.zeros((2, 4), dtype='float32'))
-    self.assertTrue(model.built)
-
   def test_using_symbolic_tensors_with_tf_ops(self):
     # Single-input.
     x = keras.Input((3,))