old_contents: # 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.
  # ==============================================================================
  """This test checks a situation where the same tensor is considered as an output
  multiple times because it has been duplicated by 2+ indentity ops. Previously,
  the tensor would be renamed multiple times, overwriting the output binding name
  which resulted in a runtime error when the binding would not be found.
  """
  
  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.ops import nn
  from tensorflow.python.platform import test
  
  
  class IdentityTest(trt_test.TfTrtIntegrationTestBase):
  
    def _ConstOp(self, shape):
      return constant_op.constant(np.random.randn(*shape), dtype=dtypes.float32)
  
    def GetParams(self):
      """Testing engine with the same tensor repeated as output via identity."""
      input_name = "input"
      input_dims = [100, 32]
      g = ops.Graph()
      with g.as_default():
        x = array_ops.placeholder(
            dtype=dtypes.float32, shape=input_dims, name=input_name)
  
        b = self._ConstOp((32, 4))
        x1 = math_ops.matmul(x, b)
        b = self._ConstOp((1, 4))
        x1 = x1 + b
  
        out1 = array_ops.identity(x1, name='output1')
        out2 = array_ops.identity(x1, name='output2')
        iden1 = array_ops.identity(x1)
        out3 = array_ops.identity(iden1, name='output3')
  
      return trt_test.TfTrtIntegrationTestParams(
          gdef=g.as_graph_def(),
          input_names=[input_name],
          input_dims=[input_dims],
          output_names=['output1', 'output2', 'output3'],
          expected_output_dims=[(100, 4), (100, 4), (100, 4)])
  
  
    def ExpectedEnginesToBuild(self, run_params):
      """Return the expected engines to build."""
      return ["TRTEngineOp_0"]
  
    def ShouldRunTest(self, run_params):
      """Whether to run the test."""
      # TODO(aaroey): Trt 4.0 forbids conversion for tensors with rank <3 in int8
      # mode, which is a bug. Re-enable this when trt library is fixed.
      return not trt_test.IsQuantizationMode(run_params.precision_mode)
  
  if __name__ == "__main__":
    test.main()
  
new_contents: # 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.
  # ==============================================================================
  """This test checks a situation where the same tensor is considered as an output
  multiple times because it has been duplicated by 2+ indentity ops. Previously,
  the tensor would be renamed multiple times, overwriting the output binding name
  which resulted in a runtime error when the binding would not be found.
  """
  
  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 math_ops
  from tensorflow.python.platform import test
  
  
  class IdentityTest(trt_test.TfTrtIntegrationTestBase):
  
    def _ConstOp(self, shape):
      return constant_op.constant(np.random.randn(*shape), dtype=dtypes.float32)
  
    def GetParams(self):
      """Testing engine with the same tensor repeated as output via identity."""
      input_name = "input"
      input_dims = [100, 32]
      g = ops.Graph()
      with g.as_default():
        x = array_ops.placeholder(
            dtype=dtypes.float32, shape=input_dims, name=input_name)
  
        b = self._ConstOp((32, 4))
        x1 = math_ops.matmul(x, b)
        b = self._ConstOp((1, 4))
        x1 = x1 + b
  
        out1 = array_ops.identity(x1, name='output1')
        out2 = array_ops.identity(x1, name='output2')
        iden1 = array_ops.identity(x1)
        out3 = array_ops.identity(iden1, name='output3')
  
      return trt_test.TfTrtIntegrationTestParams(
          gdef=g.as_graph_def(),
          input_names=[input_name],
          input_dims=[input_dims],
          output_names=['output1', 'output2', 'output3'],
          expected_output_dims=[(100, 4), (100, 4), (100, 4)])
  
  
    def ExpectedEnginesToBuild(self, run_params):
      """Return the expected engines to build."""
      return ["TRTEngineOp_0"]
  
    def ShouldRunTest(self, run_params):
      """Whether to run the test."""
      # TODO(aaroey): Trt 4.0 forbids conversion for tensors with rank <3 in int8
      # mode, which is a bug. Re-enable this when trt library is fixed.
      return not trt_test.IsQuantizationMode(run_params.precision_mode)
  
  if __name__ == "__main__":
    test.main()
  
subject: Remove unused imports