code: def test_lm_generate_gpt2_beam_search_xla(self):
      model = TFGPT2LMHeadModel.from_pretrained("gpt2")
      tokenizer = GPT2Tokenizer.from_pretrained("gpt2")
  
      tokenizer.pad_token = tokenizer.eos_token
      tokenizer.padding_side = "left"
  
      sentences = ["The dog", "The flying machine"]
      expected_output_strings = [
          "The dog was found in the backyard of a home in the 6500 block of South Main Street",
          "The flying machine is a very powerful machine, but it's not a very powerful machine. It's",
      ]
      input_ids = tokenizer(
          sentences, return_tensors="tf", padding=True
      )
  
      output_ids = model.generate(
          **input_ids, do_sample=False, num_beams=2
      )
      output_strings = tokenizer.batch_decode(
          output_ids, skip_special_tokens=True
      )
      self.assertListEqual(output_strings, expected_output_strings)
  
      xla_generate = tf.function(model.generate, jit_compile=True)
      output_ids = xla_generate(
          **input_ids, do_sample=False, num_beams=2
      )
      output_strings = tokenizer.batch_decode(
          output_ids, skip_special_tokens=True
      )
      self.assertListEqual(output_strings, expected_output_strings)
  
imports: from __future__ import annotations
  import unittest
  from transformers import GPT2Config, is_tf_available
  from transformers.testing_utils import require_tf, require_tf2onnx, slow
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_tf_common import TFModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
  from ...test_pipeline_mixin import PipelineTesterMixin
  from ...utils.test_modeling_tf_core import TFCoreModelTesterMixin
label_desc: Use image node_id 7 for calling the TFGPT2ModelLanguageGenerationTest obj's underlying member method code with example usage: obj.test_lm_generate_gpt2_beam_search_xla() without return types