text: # 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
  
  from tensorflow.python.compiler.tensorrt.test import tf_trt_integration_test_base as trt_test
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import constant_op
  from tensorflow.python.ops import nn_ops
  from tensorflow.python.ops import array_ops
  from tensorflow.python.platform import test
  
  
  class TopKTest(trt_test.TfTrtIntegrationTestBase):
    """Testing Top-K in TF-TRT conversion."""
  
    def GraphFn(self, x):
      k = 5
      k_tensor = constant_op.constant(k, dtype=dtypes.int32, name="Const")
      values, indices = nn_ops.top_k(x, k_tensor, name="TopK")
      values = array_ops.identity(values, name="output_0")
      indices = array_ops.identity(indices, name="output_1")
      return values, indices
  
    def GetParams(self):
      k = 5
      return self.BuildParams(self.GraphFn, dtypes.float32, [[100, 100]],
                              [[100, k], [100, k]])
  
    def ExpectedEnginesToBuild(self, run_params):
      """Return the expected engines to build."""
      return {"TRTEngineOp_0": ["Const", "TopK"]}
  
  
  class TopKOutputTypeTest(trt_test.TfTrtIntegrationTestBase):
    """Testing that output type of engine using Top-K is set correctly."""
  
    def GraphFn(self, x):
      k = 5
      k_tensor = constant_op.constant(k, dtype=dtypes.int32, name="Const")
      values, indices = nn_ops.top_k(x, k_tensor, name="TopK")
      # Reshape will act as a layer between the TopK output and the engine
      # output, requiring the output tensor of reshape to be set explicitly to
      # int32.
      indices = array_ops.reshape(indices, [100, 1, 5], name="Reshape")
      values = array_ops.identity(values, name="output_0")
      indices = array_ops.identity(indices, name="output_1")
      return values, indices
  
    def GetParams(self):
      k = 5
      return self.BuildParams(self.GraphFn, dtypes.float32, [[100, 100]],
                              [[100, k], [100, 1, k]])
  
    def ExpectedEnginesToBuild(self, run_params):
      """Return the expected engines to build."""
      return {"TRTEngineOp_0": ["Const", "TopK", "Reshape", "Reshape/shape"]}
  
  
  if __name__ == "__main__":
    test.main()
  