code: def _create_dummy_results(self):
      bboxes = np.array(
          [
              [50, 60, 70, 80],
              [100, 120, 130, 150],
              [150, 160, 190, 200],
              [250, 260, 350, 360],
          ]
      )
      scores = np.array([1.0, 0.98, 0.96, 0.95])
      labels = np.array([0, 0, 1, 0])
      dummy_mask = np.zeros((4, 10, 10), dtype=np.uint8)
      dummy_mask[:, :5, :5] = 1
      return dict(
          bboxes=torch.from_numpy(bboxes),
          scores=torch.from_numpy(scores),
          labels=torch.from_numpy(labels),
          masks=torch.from_numpy(dummy_mask),
      )
  
imports: import os.path
  import tempfile
  import unittest
  import numpy
  import pycocotools.mask
  import torch
  from mmdet.evaluation.metrics import LVISMetric
  from mmengine.fileio import dump
label_desc: Use image node_id 2 for calling the TestLVISMetric obj's underlying member method code with example usage: obj._create_dummy_results() and returns: dict