code: def test_xglm_sample(self):
      tokenizer = XGLMTokenizer.from_pretrained("facebook/xglm-564M")
      model = XGLMForCausalLM.from_pretrained("facebook/xglm-564M")
  
      torch.manual_seed(0)
      tokenized = tokenizer(
          "Today is a nice day and", return_tensors="pt"
      )
      input_ids = tokenized.input_ids
      output_ids = model.generate(
          input_ids, do_sample=True, num_beams=1
      )
      output_str = tokenizer.decode(
          output_ids[0], skip_special_tokens=True
      )
  
      EXPECTED_OUTPUT_STR = "Today is a nice day and the sun is shining. A nice day with warm rainy"
      self.assertEqual(output_str, EXPECTED_OUTPUT_STR)
  
imports: import datetime
  import math
  import unittest
  from transformers import XGLMConfig, is_torch_available
  from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
  from ...generation.test_generation_utils import GenerationTesterMixin
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
label_desc: Use image node_id 4 for calling the XGLMModelLanguageGenerationTest obj's underlying member method code with example usage: obj.test_xglm_sample() without return types