code: def test_calc_greenlist_mask():
      processor = WatermarkLogitsProcessor()
      scores = torch.tensor(
          [[0.5, 0.3, 0.2, 0.8], [0.1, 0.2, 0.7, 0.9]]
      )
      greenlist_token_ids = torch.tensor([2, 3])
      result = processor._calc_greenlist_mask(
          scores, greenlist_token_ids
      )
      assert result.tolist() == [
          [False, False, False, False],
          [False, False, True, True],
      ]
      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 3 for calling a global function with example usage: test_calc_greenlist_mask() without return types