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diff --git a/tensorflow/python/autograph/operators/exceptions.py b/tensorflow/python/autograph/operators/exceptions.py
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+# Copyright 2018 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.
+# ==============================================================================
+"""Exception handling statements: assert, etc."""
+
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
+from tensorflow.python.framework import tensor_util
+from tensorflow.python.ops import control_flow_ops
+from tensorflow.python.util import tf_inspect
+
+
+def assert_stmt(expression1, expression2):
+  """Functional form of an assert statement.
+
+  This follows the semantics of the Python assert statement, however the
+  concrete implementations may deviate from it. See the respective
+  implementation for details.
+
+  In general, the assert statement should not be used for control flow.
+  Furthermore, it is encouraged that the assertion expressions should not have
+  side effects.
+
+  Args:
+    expression1: Any
+    expression2: Callable[[], Any], returns the expression to include in the
+        error message when expression1 evaluates to False. When expression1 is
+        True, the result of expression2 will not be evaluated, however,
+        expression2 itself may be evaluated in some implementations.
+
+  Returns:
+    Any, implementation-dependent.
+
+  Raises:
+    ValueError: if any arguments are illegal.
+  """
+  if not callable(expression2):
+    raise ValueError('{} must be a callable'.format(expression2))
+  args, _, keywords, _ = tf_inspect.getargspec(expression2)
+  if args or keywords:
+    raise ValueError('{} may not have any arguments'.format(expression2))
+
+  if tensor_util.is_tensor(expression1):
+    return _tf_assert_stmt(expression1, expression2)
+  else:
+    return _py_assert_stmt(expression1, expression2)
+
+
+def _tf_assert_stmt(expression1, expression2):
+  """Overload of assert_stmt that stages a TF Assert.
+
+  This implementation deviates from Python semantics as follows:
+    (1) the assertion is verified regardless of the state of __debug__
+    (2) on assertion failure, the graph execution will fail with
+        tensorflow.errors.ValueError, rather than AssertionError.
+
+  Args:
+    expression1: tensorflow.Tensor, must evaluate to a tf.bool scalar
+    expression2: Callable[[], Union[tensorflow.Tensor, List[tensorflow.Tensor]]]
+
+  Returns:
+    tensorflow.Operation
+  """
+  expression2_tensors = expression2()
+  if not isinstance(expression2_tensors, list):
+    expression2_tensors = [expression2_tensors]
+  return control_flow_ops.Assert(expression1, expression2_tensors)
+
+
+def _py_assert_stmt(expression1, expression2):
+  """Overload of assert_stmt that executes a Python assert statement."""
+  assert expression1, expression2()
+  return None