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diff --git a/tensorflow/contrib/tensorrt/test/batch_matmul_test.py b/tensorflow/contrib/tensorrt/test/batch_matmul_test.py
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+++ b/tensorflow/contrib/tensorrt/test/batch_matmul_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 math_ops
+from tensorflow.python.platform import test
+
+
+class BatchMatMulTest(trt_test.TfTrtIntegrationTestBase):
+
+  def GetParams(self):
+    """Testing conversion of BatchMatMul in TF-TRT conversion."""
+    dtype = dtypes.float32
+    input_name = "input"
+    input_dims = [12, 5, 8, 12]
+    w1_name = "matmul_w1"
+    w1_dims = [12, 5, 12, 7]
+    w2_name = "matmul_w2"
+    w2_dims = [12, 12, 7]
+    g = ops.Graph()
+    with g.as_default():
+      inp = array_ops.placeholder(
+          dtype=dtype, shape=[None] + input_dims[1:], name=input_name)
+      w1 = array_ops.placeholder(dtype=dtype, shape=w1_dims, name=w1_name)
+      w2 = array_ops.placeholder(dtype=dtype, shape=w2_dims, name=w2_name)
+      with g.device("/GPU:0"):
+        b = constant_op.constant(np.random.randn(12, 5, 12, 7), dtype=dtype)
+        c = constant_op.constant(np.random.randn(5, 1, 1), dtype=dtype)
+        d = constant_op.constant(np.random.randn(5, 1, 1), dtype=dtype)
+        x1 = math_ops.matmul(inp, b)
+        x1 = x1 + c
+        x2 = math_ops.matmul(inp, w1)
+        x2 = x2 * d
+        e = gen_array_ops.reshape(inp, [12, 40, 12])
+        x3 = math_ops.matmul(e, w2)
+        f = constant_op.constant(np.random.randn(40, 1), dtype=dtype)
+        x3 = x3 + f
+        x3 = gen_array_ops.reshape(x3, [12, 5, 8, 7])
+        out = x1 + x2 + x3
+      array_ops.squeeze(out, name=self.output_name)
+    return trt_test.TfTrtIntegrationTestParams(
+        gdef=g.as_graph_def(),
+        input_names=[input_name, w1_name, w2_name],
+        input_dims=[input_dims, w1_dims, w2_dims],
+        num_expected_engines=1,
+        expected_output_dims=(12, 5, 8, 7),
+        allclose_atol=1.e-03,
+        allclose_rtol=1.e-03)
+
+
+if __name__ == "__main__":
+  test.main()