docstr: Builds a tf.Graph for the test.
docstr_tok: ["Builds","a","tf.Graph","for","the","test","."]
code: def GraphFn(self, inp):
      """Builds a tf.Graph for the test."""
      tensor = inp * 2.0
      tensor = array_ops.reshape(
          tensor, [-1] + self.tensor_shapes[1][1:]
      )
      with ops.get_default_graph()._attr_scope(
          {
              "_tftrt_op_max_batch_size": attr_value_pb2.AttrValue(
                  i=self.max_batch_sizes[1]
              )
          }
      ):
          tensor = tensor + 3.0
      tensor = array_ops.reshape(
          tensor, [-1] + self.tensor_shapes[2][1:]
      )
      with ops.get_default_graph()._attr_scope(
          {
              "_tftrt_op_max_batch_size": attr_value_pb2.AttrValue(
                  i=self.max_batch_sizes[2]
              )
          }
      ):
          tensor = tensor * 4.0
      tensor = array_ops.reshape(
          tensor, [-1] + self.tensor_shapes[3][1:]
      )
      with ops.get_default_graph()._attr_scope(
          {
              "_tftrt_op_max_batch_size": attr_value_pb2.AttrValue(
                  i=self.max_batch_sizes[3]
              )
          }
      ):
          tensor += tensor + 5.0
      return array_ops.identity(tensor, name="output_0")
  
imports: import unittest
  from tensorflow.core.framework import attr_value_pb2
  from tensorflow.python.compiler.tensorrt.test import tf_trt_integration_test_base
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.ops import array_ops
  from tensorflow.python.platform import test
label_desc: Use image node_id 1 for calling the AnnotateMaxBatchSizesTest obj's underlying member method code with example usage: obj.GraphFn(inp) and returns: array_ops