diff --git a/tensorflow/python/keras/layers/__init__.py b/tensorflow/python/keras/layers/__init__.py
index 87dfa34f932..07cb1bdf1b3 100644
--- a/tensorflow/python/keras/layers/__init__.py
+++ b/tensorflow/python/keras/layers/__init__.py
@@ -18,8 +18,11 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
+from tensorflow.python import tf2
+
 # Generic layers.
 # pylint: disable=g-bad-import-order
+# pylint: disable=g-import-not-at-top
 from tensorflow.python.keras.engine.input_layer import Input
 from tensorflow.python.keras.engine.input_layer import InputLayer
 from tensorflow.python.keras.engine.input_spec import InputSpec
@@ -27,10 +30,20 @@ from tensorflow.python.keras.engine.base_layer import Layer
 from tensorflow.python.keras.engine.base_preprocessing_layer import PreprocessingLayer
 
 # Preprocessing layers.
-from tensorflow.python.keras.layers.preprocessing.normalization import Normalization
-from tensorflow.python.keras.layers.preprocessing.normalization_v1 import Normalization as NormalizationV1
-from tensorflow.python.keras.layers.preprocessing.text_vectorization import TextVectorization
-from tensorflow.python.keras.layers.preprocessing.text_vectorization_v1 import TextVectorization as TextVectorizationV1
+if tf2.enabled():
+  from tensorflow.python.keras.layers.preprocessing.normalization import Normalization
+  from tensorflow.python.keras.layers.preprocessing.normalization_v1 import Normalization as NormalizationV1
+  NormalizationV2 = Normalization
+  from tensorflow.python.keras.layers.preprocessing.text_vectorization import TextVectorization
+  from tensorflow.python.keras.layers.preprocessing.text_vectorization_v1 import TextVectorization as TextVectorizationV1
+  TextVectorizationV2 = TextVectorization
+else:
+  from tensorflow.python.keras.layers.preprocessing.normalization_v1 import Normalization
+  from tensorflow.python.keras.layers.preprocessing.normalization import Normalization as NormalizationV2
+  NormalizationV1 = Normalization
+  from tensorflow.python.keras.layers.preprocessing.text_vectorization_v1 import TextVectorization
+  from tensorflow.python.keras.layers.preprocessing.text_vectorization import TextVectorization as TextVectorizationV2
+  TextVectorizationV1 = TextVectorization
 
 # Advanced activations.
 from tensorflow.python.keras.layers.advanced_activations import LeakyReLU
@@ -121,8 +134,14 @@ from tensorflow.python.keras.layers.noise import GaussianDropout
 
 # Normalization layers.
 from tensorflow.python.keras.layers.normalization import LayerNormalization
-from tensorflow.python.keras.layers.normalization import BatchNormalization
-from tensorflow.python.keras.layers.normalization_v2 import BatchNormalization as BatchNormalizationV2
+if tf2.enabled():
+  from tensorflow.python.keras.layers.normalization_v2 import BatchNormalization
+  from tensorflow.python.keras.layers.normalization import BatchNormalization as BatchNormalizationV1
+  BatchNormalizationV2 = BatchNormalization
+else:
+  from tensorflow.python.keras.layers.normalization import BatchNormalization
+  from tensorflow.python.keras.layers.normalization_v2 import BatchNormalization as BatchNormalizationV2
+  BatchNormalizationV1 = BatchNormalization
 
 # Kernelized layers.
 from tensorflow.python.keras.layers.kernelized import RandomFourierFeatures
@@ -163,14 +182,32 @@ from tensorflow.python.keras.layers.recurrent import SimpleRNNCell
 from tensorflow.python.keras.layers.recurrent import PeepholeLSTMCell
 from tensorflow.python.keras.layers.recurrent import SimpleRNN
 
-from tensorflow.python.keras.layers.recurrent import GRU
-from tensorflow.python.keras.layers.recurrent import GRUCell
-from tensorflow.python.keras.layers.recurrent import LSTM
-from tensorflow.python.keras.layers.recurrent import LSTMCell
-from tensorflow.python.keras.layers.recurrent_v2 import GRU as GRU_v2
-from tensorflow.python.keras.layers.recurrent_v2 import GRUCell as GRUCell_v2
-from tensorflow.python.keras.layers.recurrent_v2 import LSTM as LSTM_v2
-from tensorflow.python.keras.layers.recurrent_v2 import LSTMCell as LSTMCell_v2
+if tf2.enabled():
+  from tensorflow.python.keras.layers.recurrent_v2 import GRU
+  from tensorflow.python.keras.layers.recurrent_v2 import GRUCell
+  from tensorflow.python.keras.layers.recurrent_v2 import LSTM
+  from tensorflow.python.keras.layers.recurrent_v2 import LSTMCell
+  from tensorflow.python.keras.layers.recurrent import GRU as GRUV1
+  from tensorflow.python.keras.layers.recurrent import GRUCell as GRUCellV1
+  from tensorflow.python.keras.layers.recurrent import LSTM as LSTMV1
+  from tensorflow.python.keras.layers.recurrent import LSTMCell as LSTMCellV1
+  GRUV2 = GRU
+  GRUCellV2 = GRUCell
+  LSTMV2 = LSTM
+  LSTMCellV2 = LSTMCell
+else:
+  from tensorflow.python.keras.layers.recurrent import GRU
+  from tensorflow.python.keras.layers.recurrent import GRUCell
+  from tensorflow.python.keras.layers.recurrent import LSTM
+  from tensorflow.python.keras.layers.recurrent import LSTMCell
+  from tensorflow.python.keras.layers.recurrent_v2 import GRU as GRUV2
+  from tensorflow.python.keras.layers.recurrent_v2 import GRUCell as GRUCellV2
+  from tensorflow.python.keras.layers.recurrent_v2 import LSTM as LSTMV2
+  from tensorflow.python.keras.layers.recurrent_v2 import LSTMCell as LSTMCellV2
+  GRUV1 = GRU
+  GRUCellV1 = GRUCell
+  LSTMV1 = LSTM
+  LSTMCellV1 = LSTMCell
 
 # Convolutional-recurrent layers.
 from tensorflow.python.keras.layers.convolutional_recurrent import ConvLSTM2D
diff --git a/tensorflow/python/keras/layers/cudnn_recurrent_test.py b/tensorflow/python/keras/layers/cudnn_recurrent_test.py
index e3e193c3b63..1c20918ffc8 100644
--- a/tensorflow/python/keras/layers/cudnn_recurrent_test.py
+++ b/tensorflow/python/keras/layers/cudnn_recurrent_test.py
@@ -460,7 +460,7 @@ class CuDNNV1OnlyTest(keras_parameterized.TestCase):
     input_shape = (3, 5)
 
     def gru(cudnn=False, **kwargs):
-      layer_class = keras.layers.CuDNNGRU if cudnn else keras.layers.GRU
+      layer_class = keras.layers.CuDNNGRU if cudnn else keras.layers.GRUV1
       return layer_class(2, input_shape=input_shape, **kwargs)
 
     def get_layer_weights(layer):
diff --git a/tensorflow/python/keras/layers/rnn_cell_wrapper_v2_test.py b/tensorflow/python/keras/layers/rnn_cell_wrapper_v2_test.py
index 15cbf68c87a..a01e56be097 100644
--- a/tensorflow/python/keras/layers/rnn_cell_wrapper_v2_test.py
+++ b/tensorflow/python/keras/layers/rnn_cell_wrapper_v2_test.py
@@ -256,7 +256,7 @@ class RNNCellWrapperTest(test.TestCase, parameterized.TestCase):
     with self.assertRaisesRegexp(ValueError, "does not work with "):
       wrapper_cls(cell)
 
-    cell = layers.LSTMCell_v2(10)
+    cell = layers.LSTMCellV2(10)
     with self.assertRaisesRegexp(ValueError, "does not work with "):
       wrapper_cls(cell)
 
diff --git a/tensorflow/python/keras/saving/hdf5_format_test.py b/tensorflow/python/keras/saving/hdf5_format_test.py
index 96557410030..19340c1d86d 100644
--- a/tensorflow/python/keras/saving/hdf5_format_test.py
+++ b/tensorflow/python/keras/saving/hdf5_format_test.py
@@ -145,7 +145,7 @@ class TestWeightSavingAndLoading(test.TestCase, parameterized.TestCase):
             (None, input_dim, 4, 4, 4),
         ],
         [
-            (keras.layers.GRU(output_dim)),
+            (keras.layers.GRUV1(output_dim)),
             [np.random.random((input_dim, output_dim)),
              np.random.random((output_dim, output_dim)),
              np.random.random((output_dim,)),
@@ -158,7 +158,7 @@ class TestWeightSavingAndLoading(test.TestCase, parameterized.TestCase):
             (None, 4, input_dim),
         ],
         [
-            (keras.layers.LSTM(output_dim)),
+            (keras.layers.LSTMV1(output_dim)),
             [np.random.random((input_dim, output_dim)),
              np.random.random((output_dim, output_dim)),
              np.random.random((output_dim,)),
diff --git a/tensorflow/python/layers/normalization.py b/tensorflow/python/layers/normalization.py
index c6f06069d7c..2554721eca2 100644
--- a/tensorflow/python/layers/normalization.py
+++ b/tensorflow/python/layers/normalization.py
@@ -20,7 +20,7 @@ from __future__ import division
 from __future__ import print_function
 
 
-from tensorflow.python.keras import layers as keras_layers
+from tensorflow.python.keras.layers import normalization as keras_normalization
 from tensorflow.python.layers import base
 from tensorflow.python.ops import init_ops
 from tensorflow.python.util import deprecation
@@ -28,7 +28,7 @@ from tensorflow.python.util.tf_export import tf_export
 
 
 @tf_export(v1=['layers.BatchNormalization'])
-class BatchNormalization(keras_layers.BatchNormalization, base.Layer):
+class BatchNormalization(keras_normalization.BatchNormalization, base.Layer):
   """Batch Normalization layer from http://arxiv.org/abs/1502.03167.
 
   "Batch Normalization: Accelerating Deep Network Training by Reducing
@@ -170,7 +170,7 @@ class BatchNormalization(keras_layers.BatchNormalization, base.Layer):
 @deprecation.deprecated(
     date=None, instructions='Use keras.layers.BatchNormalization instead.  In '
     'particular, `tf.control_dependencies(tf.GraphKeys.UPDATE_OPS)` should not '
-    'be used (consult the `tf.keras.layers.batch_normalization` '
+    'be used (consult the `tf.keras.layers.BatchNormalization` '
     'documentation).')
 @tf_export(v1=['layers.batch_normalization'])
 def batch_normalization(inputs,