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diff --git a/tensorflow/contrib/tensorrt/test/const_broadcast_test.py b/tensorflow/contrib/tensorrt/test/const_broadcast_test.py
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+++ b/tensorflow/contrib/tensorrt/test/const_broadcast_test.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.
+# ==============================================================================
+"""Script to test TF-TensorRT integration."""
+
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
+import numpy as np
+
+from tensorflow.contrib.tensorrt.test import tf_trt_integration_test_base as trt_test
+from tensorflow.python.framework import constant_op
+from tensorflow.python.framework import dtypes
+from tensorflow.python.framework import ops
+from tensorflow.python.ops import array_ops
+from tensorflow.python.ops import nn
+from tensorflow.python.platform import test
+
+
+class ConstBroadcastTest(trt_test.TfTrtIntegrationTestBase):
+
+  def GetParams(self):
+    """Test for Constant broadcasting in TF-TRT."""
+    dtype = dtypes.float32
+    input_name = 'input'
+    input_dims = [5, 12, 12, 2]
+    g = ops.Graph()
+    with g.as_default():
+      x = array_ops.placeholder(dtype=dtype, shape=input_dims, name=input_name)
+      filt1 = constant_op.constant(
+          0.3, shape=(3, 3, 2, 1), dtype=dtype, name='filt1')
+      y1 = nn.conv2d(x, filt1, strides=[1, 1, 1, 1], padding='SAME', name='y1')
+      z1 = nn.relu(y1, name='z1')
+      filt2 = constant_op.constant(
+          np.random.randn(9), shape=(3, 3, 1, 1), dtype=dtype, name='filt2')
+      y2 = nn.conv2d(z1, filt2, strides=[1, 1, 1, 1], padding='SAME', name='y2')
+      z2 = nn.relu(y2, name='z')
+      filt3 = constant_op.constant(
+          np.random.randn(3, 3, 1, 1),
+          shape=(3, 3, 1, 1),
+          dtype=dtype,
+          name='filt3')
+      y3 = nn.conv2d(z2, filt3, strides=[1, 1, 1, 1], padding='SAME', name='y3')
+      nn.relu(y3, name='output')
+    return trt_test.TfTrtIntegrationTestParams(
+        gdef=g.as_graph_def(),
+        input_names=[input_name],
+        input_dims=[input_dims],
+        num_expected_engines=1,
+        expected_output_dims=(5, 12, 12, 1),
+        allclose_atol=1.e-02,
+        allclose_rtol=1.e-02)
+
+
+if __name__ == '__main__':
+  test.main()