diff --git a/tensorflow/python/keras/engine/base_layer.py b/tensorflow/python/keras/engine/base_layer.py
index 7a8c865ca64..ad954c1f972 100644
--- a/tensorflow/python/keras/engine/base_layer.py
+++ b/tensorflow/python/keras/engine/base_layer.py
@@ -2488,8 +2488,11 @@ class TensorFlowOpLayer(Layer):
                constants=None,
                trainable=True,
                dtype=None):
+    # Pass autocast=False, as if inputs are cast, input types might not match
+    # Operation type.
     super(TensorFlowOpLayer, self).__init__(
-        name=_TF_OP_LAYER_NAME_PREFIX + name, trainable=trainable, dtype=dtype)
+        name=_TF_OP_LAYER_NAME_PREFIX + name, trainable=trainable, dtype=dtype,
+        autocast=False)
     if not isinstance(node_def, bytes):
       node_def = node_def.encode('utf-8')
     self.node_def = node_def_pb2.NodeDef.FromString(node_def)
diff --git a/tensorflow/python/keras/layers/tensorflow_op_layer_test.py b/tensorflow/python/keras/layers/tensorflow_op_layer_test.py
index 54455cad73a..a853ce5eed0 100644
--- a/tensorflow/python/keras/layers/tensorflow_op_layer_test.py
+++ b/tensorflow/python/keras/layers/tensorflow_op_layer_test.py
@@ -126,6 +126,15 @@ def _reuse_op():
   return keras.Model(inputs, outputs)
 
 
+def _float64_op():
+  inputs = keras.Input(shape=(10,))
+  x = keras.layers.Dense(10, dtype='float64')(inputs)
+  x = gen_nn_ops.relu(x)
+  assert x.dtype == 'float64', 'x has dtype: %s' % x.dtype
+  outputs = keras.layers.Dense(10)(x)
+  return keras.Model(inputs, outputs)
+
+
 class LayerWithLayer(keras.layers.Layer):
 
   def build(self, input_shape):
@@ -179,6 +188,7 @@ class AutoLambdaTest(keras_parameterized.TestCase):
       ('op_with_tensor_list', _op_with_tensor_list),
       ('add_n', _add_n),
       ('_reuse_op', _reuse_op),
+      ('_float64_op', _float64_op),
       ('_inner_layer', _inner_layer),
       ('_reuse_ancillary_layer', _reuse_ancillary_layer),
   )