code: def test_generate_fp16(self):
      config, input_dict = self.model_tester.prepare_config_and_inputs()
      input_ids = input_dict["input_ids"]
      attention_mask = input_ids.ne(1).to(torch_device)
      model = (
          LEDForConditionalGeneration(config).eval().to(torch_device)
      )
      if torch_device == "cuda":
          model.half()
      model.generate(input_ids, attention_mask=attention_mask)
      model.generate(
          num_beams=4,
          do_sample=True,
          early_stopping=False,
          num_return_sequences=3,
      )
  
imports: import copy
  import tempfile
  import unittest
  from transformers import LEDConfig, is_torch_available
  from transformers.models.auto import get_values
  from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
  from transformers.utils import cached_property
  from ...generation.test_generation_utils import GenerationTesterMixin
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_common import ModelTesterMixin, ids_tensor
label_desc: Use image node_id 8 for calling the LEDModelTest obj's underlying member method code with example usage: obj.test_generate_fp16() without return types