code: def test_lm_generate_xglm(self, verify_outputs=True):
      model = TFXGLMForCausalLM.from_pretrained("facebook/xglm-564M")
      input_ids = tf.convert_to_tensor(
          [[2, 268, 9865]], dtype=tf.int32
      )  # The dog
      # </s> The dog is a very friendly dog. He is very affectionate and loves to play with other
      expected_output_ids = [2, 268, 9865, 67, 11, 1988, 57252, 9865, 5, 984, 67, 1988, 213838, 1658, 53, 70446, 33, 6657, 278, 1581]  # fmt: skip
      output_ids = model.generate(
          input_ids, do_sample=False, num_beams=1
      )
      if verify_outputs:
          self.assertListEqual(
              output_ids[0].numpy().tolist(), expected_output_ids
          )
  
imports: from __future__ import annotations
  import unittest
  from transformers import XGLMConfig, XGLMTokenizer, is_tf_available
  from transformers.testing_utils import require_tf, 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
label_desc: Use image node_id 1 for calling the TFXGLMModelLanguageGenerationTest obj's underlying member method code with example usage: obj.test_lm_generate_xglm(verify_outputs) without return types