code: def _get_tensors(self, length):
      batch_size = 3
      vocab_size = 250
  
      input_ids = ids_tensor((batch_size, length), vocab_size)
      scores = (
          torch.ones(
              (batch_size, length),
              device=torch_device,
              dtype=torch.float,
          )
          / length
      )
      return input_ids, scores
  
file_path: H2O/h2o_flexgen/benchmark/third_party/transformers/tests/generation/test_generation_stopping_criteria.py
imports: import time
  import unittest
  from transformers import is_torch_available
  from transformers.testing_utils import require_torch, torch_device
  from ..test_modeling_common import ids_tensor
label_desc: Use image node_id 1 for calling the StoppingCriteriaTestCase obj's underlying member method code with example usage: obj._get_tensors(length) and returns: input_ids,  scores