code: def test_xglm_sample(self):
      tokenizer = XGLMTokenizer.from_pretrained("facebook/xglm-564M")
      model = TFXGLMForCausalLM.from_pretrained("facebook/xglm-564M")
  
      tf.random.set_seed(0)
      tokenized = tokenizer(
          "Today is a nice day and", return_tensors="tf"
      )
      input_ids = tokenized.input_ids
      # forces the generation to happen on CPU, to avoid GPU-related quirks (and assure same output regardless of the available devices)
      with tf.device(":/CPU:0"):
          output_ids = model.generate(
              input_ids, do_sample=True, seed=[7, 0]
          )
      output_str = tokenizer.decode(
          output_ids[0], skip_special_tokens=True
      )
  
      EXPECTED_OUTPUT_STR = "Today is a nice day and warm evening here over Southern Alberta!! Today when they closed schools due"
      self.assertEqual(output_str, EXPECTED_OUTPUT_STR)
  
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 2 for calling the TFXGLMModelLanguageGenerationTest obj's underlying member method code with example usage: obj.test_xglm_sample() without return types