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diff --git a/tensorflow/contrib/autograph/lang/directives.py b/tensorflow/contrib/autograph/lang/directives.py
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+++ b/tensorflow/contrib/autograph/lang/directives.py
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+# Copyright 2017 The TensorFlow Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ==============================================================================
+"""Directives are special no-op functions that serve as compilation markers.
+
+They provide static information like type hints, compilation and TensorFlow
+overrides.
+
+These serve as annotations in the compiled code, allowing the user some control
+over the compilation process. They have no functional role at runtime.
+"""
+
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
+
+UNSPECIFIED = object()
+
+
+def set_element_type(entity, dtype, shape=UNSPECIFIED):
+  """Indicates that the entity is expected hold items of specified type/shape.
+
+  The staged TensorFlow ops will reflect and assert this data type. Ignored
+  otherwise.
+
+  Args:
+    entity: The entity to annotate.
+    dtype: TensorFlow dtype value to assert for entity.
+    shape: Optional shape to assert for entity.
+  """
+  del entity
+  del dtype
+  del shape
+
+
+def set_loop_options(
+    parallel_iterations=UNSPECIFIED,
+    back_prop=UNSPECIFIED,
+    swap_memory=UNSPECIFIED,
+    maximum_iterations=UNSPECIFIED):
+  """Specifies additional arguments to be passed to the enclosing while_loop.
+
+  The parameters apply to and only to the immediately enclosing loop. It only
+  has effect if the loop is staged as a TF while_loop; otherwise the parameters
+  have no effect.
+
+  Args:
+    parallel_iterations: See tf.while_loop.
+    back_prop: See tf.while_loop.
+    swap_memory: See tf.while_loop.
+    maximum_iterations: See tf.while_loop.
+  """
+  del parallel_iterations
+  del back_prop
+  del swap_memory
+  del maximum_iterations