diff --git a/tensorflow/python/keras/layers/local.py b/tensorflow/python/keras/layers/local.py
index c33c88f3a3d..e3ae0c39cc3 100644
--- a/tensorflow/python/keras/layers/local.py
+++ b/tensorflow/python/keras/layers/local.py
@@ -29,6 +29,7 @@ from tensorflow.python.keras.engine.base_layer import Layer
 from tensorflow.python.keras.engine.input_spec import InputSpec
 from tensorflow.python.keras.utils import conv_utils
 from tensorflow.python.keras.utils import tf_utils
+from tensorflow.python.ops import sparse_ops
 from tensorflow.python.util.tf_export import keras_export
 
 
@@ -807,7 +808,7 @@ def local_conv_sparse_matmul(inputs, kernel, kernel_idxs, kernel_shape,
       Output (N+2)-D dense tensor with shape `output_shape`.
   """
   inputs_flat = K.reshape(inputs, (K.shape(inputs)[0], -1))
-  output_flat = K.sparse_ops.sparse_tensor_dense_mat_mul(
+  output_flat = sparse_ops.sparse_tensor_dense_mat_mul(
       kernel_idxs, kernel, kernel_shape, inputs_flat, adjoint_b=True)
   output_flat_transpose = K.transpose(output_flat)
 
diff --git a/tensorflow/python/keras/layers/noise_test.py b/tensorflow/python/keras/layers/noise_test.py
index 96c6d595bdf..47133891aa8 100644
--- a/tensorflow/python/keras/layers/noise_test.py
+++ b/tensorflow/python/keras/layers/noise_test.py
@@ -21,7 +21,7 @@ from __future__ import print_function
 import numpy as np
 
 from tensorflow.python import keras
-from tensorflow.python.keras.backend import dtypes_module
+from tensorflow.python.framework import dtypes
 from tensorflow.python.keras import keras_parameterized
 from tensorflow.python.keras import testing_utils
 from tensorflow.python.platform import test
@@ -48,7 +48,7 @@ class NoiseLayersTest(keras_parameterized.TestCase):
 
   @staticmethod
   def _make_model(dtype, class_type):
-    assert dtype in (dtypes_module.float32, dtypes_module.float64)
+    assert dtype in (dtypes.float32, dtypes.float64)
     assert class_type in ('gaussian_noise', 'gaussian_dropout', 'alpha_noise')
     model = keras.Sequential()
     model.add(keras.layers.Dense(8, input_shape=(32,), dtype=dtype))
@@ -70,22 +70,22 @@ class NoiseLayersTest(keras_parameterized.TestCase):
     model.train_on_batch(np.zeros((8, 32)), np.zeros((8, 8)))
 
   def test_noise_float32(self):
-    self._train_model(dtypes_module.float32, 'gaussian_noise')
+    self._train_model(dtypes.float32, 'gaussian_noise')
 
   def test_noise_float64(self):
-    self._train_model(dtypes_module.float64, 'gaussian_noise')
+    self._train_model(dtypes.float64, 'gaussian_noise')
 
   def test_dropout_float32(self):
-    self._train_model(dtypes_module.float32, 'gaussian_dropout')
+    self._train_model(dtypes.float32, 'gaussian_dropout')
 
   def test_dropout_float64(self):
-    self._train_model(dtypes_module.float64, 'gaussian_dropout')
+    self._train_model(dtypes.float64, 'gaussian_dropout')
 
   def test_alpha_dropout_float32(self):
-    self._train_model(dtypes_module.float32, 'alpha_noise')
+    self._train_model(dtypes.float32, 'alpha_noise')
 
   def test_alpha_dropout_float64(self):
-    self._train_model(dtypes_module.float64, 'alpha_noise')
+    self._train_model(dtypes.float64, 'alpha_noise')
 
 
 if __name__ == '__main__':