code: def test_bias_greenlist_logits():
      processor = WatermarkLogitsProcessor()
      scores = torch.tensor(
          [[0.5, 0.3, 0.2, 0.8], [0.1, 0.2, 0.7, 0.9]]
      )
      green_tokens_mask = torch.tensor(
          [[False, False, True, True], [False, False, False, True]]
      )
      greenlist_bias = 2.0
      result = processor._bias_greenlist_logits(
          scores, green_tokens_mask, greenlist_bias
      )
      assert np.allclose(
          result.tolist(), [[0.5, 0.3, 2.2, 2.8], [0.1, 0.2, 0.7, 2.9]]
      )
      assert result.shape == scores.shape
  
file_path: text-generation-inference/server/tests/utils/test_watermark.py
imports: import os
  import numpy
  import torch
  from text_generation_server.utils.watermark import WatermarkLogitsProcessor
label_desc: Use image node_id 4 for calling a global function with example usage: test_bias_greenlist_logits() without return types