code: def test_small_model_pt(self):
      generator = pipeline(
          "text2text-generation",
          model="patrickvonplaten/t5-tiny-random",
          framework="pt",
      )
      # do_sample=False necessary for reproducibility
      outputs = generator("Something there", do_sample=False)
      self.assertEqual(outputs, [{"generated_text": ""}])
  
      num_return_sequences = 3
      outputs = generator(
          "Something there",
          num_return_sequences=num_return_sequences,
          num_beams=num_return_sequences,
      )
      target_outputs = [
          {
              "generated_text": "Beide Beide Beide Beide Beide Beide Beide Beide Beide"
          },
          {
              "generated_text": "Beide Beide Beide Beide Beide Beide Beide Beide"
          },
          {"generated_text": ""},
      ]
      self.assertEqual(outputs, target_outputs)
  
      outputs = generator(
          "This is a test",
          do_sample=True,
          num_return_sequences=2,
          return_tensors=True,
      )
      self.assertEqual(
          outputs,
          [
              {"generated_token_ids": ANY(torch.Tensor)},
              {"generated_token_ids": ANY(torch.Tensor)},
          ],
      )
      generator.tokenizer.pad_token_id = (
          generator.model.config.eos_token_id
      )
      generator.tokenizer.pad_token = "<pad>"
      outputs = generator(
          ["This is a test", "This is a second test"],
          do_sample=True,
          num_return_sequences=2,
          batch_size=2,
          return_tensors=True,
      )
      self.assertEqual(
          outputs,
          [
              [
                  {"generated_token_ids": ANY(torch.Tensor)},
                  {"generated_token_ids": ANY(torch.Tensor)},
              ],
              [
                  {"generated_token_ids": ANY(torch.Tensor)},
                  {"generated_token_ids": ANY(torch.Tensor)},
              ],
          ],
      )
  
file_path: H2O/h2o_flexgen/benchmark/third_party/transformers/tests/pipelines/test_pipelines_text2text_generation.py
imports: import unittest
  from transformers import MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING, TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING, Text2TextGenerationPipeline, pipeline
  from transformers.testing_utils import require_tf, require_torch
  from transformers.utils import is_torch_available
  from .test_pipelines_common import ANY, PipelineTestCaseMeta
label_desc: Use image node_id 3 for calling the Text2TextGenerationPipelineTests obj's underlying member method code with example usage: obj.test_small_model_pt() without return types