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diff --git a/tensorflow/contrib/tensorrt/test/concatenation_test.py b/tensorflow/contrib/tensorrt/test/concatenation_test.py
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+++ b/tensorflow/contrib/tensorrt/test/concatenation_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.
+# ==============================================================================
+"""Model 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 gen_array_ops
+from tensorflow.python.ops import gen_math_ops
+from tensorflow.python.platform import test
+
+
+class ConcatenationTest(trt_test.TfTrtIntegrationTestBase):
+
+  def GetParams(self):
+    """Testing Concatenation in TF-TRT conversion."""
+    dtype = dtypes.float32
+    input_name = "input"
+    input_dims = [2, 3, 3, 1]
+    g = ops.Graph()
+    with g.as_default():
+      x = array_ops.placeholder(dtype=dtype, shape=input_dims, name=input_name)
+      # scale
+      a = constant_op.constant(np.random.randn(3, 1, 1), dtype=dtype)
+      r1 = x / a
+      a = constant_op.constant(np.random.randn(3, 1, 1), dtype=dtype)
+      r2 = a / x
+      a = constant_op.constant(np.random.randn(1, 3, 1), dtype=dtype)
+      r3 = a + x
+      a = constant_op.constant(np.random.randn(1, 3, 1), dtype=dtype)
+      r4 = x * a
+      a = constant_op.constant(np.random.randn(3, 1, 1), dtype=dtype)
+      r5 = x - a
+      a = constant_op.constant(np.random.randn(3, 1, 1), dtype=dtype)
+      r6 = a - x
+      a = constant_op.constant(np.random.randn(3, 1), dtype=dtype)
+      r7 = x - a
+      a = constant_op.constant(np.random.randn(3, 1), dtype=dtype)
+      r8 = a - x
+      a = constant_op.constant(np.random.randn(3, 1, 1), dtype=dtype)
+      r9 = gen_math_ops.maximum(x, a)
+      a = constant_op.constant(np.random.randn(3, 1), dtype=dtype)
+      r10 = gen_math_ops.minimum(a, x)
+      a = constant_op.constant(np.random.randn(3), dtype=dtype)
+      r11 = x * a
+      a = constant_op.constant(np.random.randn(1), dtype=dtype)
+      r12 = a * x
+      concat1 = array_ops.concat([r1, r2, r3, r4, r5, r6], axis=-1)
+      concat2 = array_ops.concat([r7, r8, r9, r10, r11, r12], axis=3)
+      x = array_ops.concat([concat1, concat2], axis=-1)
+      gen_array_ops.reshape(x, [2, -1], name=self.output_name)
+    return trt_test.TfTrtIntegrationTestParams(
+        gdef=g.as_graph_def(),
+        input_names=[input_name],
+        input_dims=[input_dims],
+        num_expected_engines=1,
+        expected_output_dims=(2, 126),
+        allclose_atol=1.e-03,
+        allclose_rtol=1.e-03)
+
+
+if __name__ == "__main__":
+  test.main()