docstr: Returns the max_batch_size that the converter should use for tests.
docstr_tok: ["Returns","the","max_batch_size","that","the","converter","should","use","for","tests","."]
code: def GetMaxBatchSize(self, run_params):
      """Returns the max_batch_size that the converter should use for tests."""
      if run_params.dynamic_engine:
          return None
  
      # Build the engine with the allowed max_batch_size less than the actual
      # max_batch_size, to fore the runtime to execute the native segment. This
      # is to test that combined_non_max_suppression, which doesn't have a TF GPU
      # implementation, can be executed natively even though the it is in the
      # the graph for the TRTEngineOp with a GPU as a default device.
      return super().GetMaxBatchSize(run_params) - 1
  
imports: import os
  from tensorflow.python.compiler.tensorrt import utils
  from tensorflow.python.compiler.tensorrt.test import tf_trt_integration_test_base
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import image_ops_impl
  from tensorflow.python.platform import test
label_desc: Use image node_id 3 for calling the CombinedNmsExecuteNativeSegmentTest obj's underlying member method code with example usage: obj.GetMaxBatchSize(run_params) and returns: unknown, None