class_docstr: Mask sampling result.
docstr: torch.Tensor: concatenated positive and negative boxes
docstr_tok: ["torch.Tensor",":","concatenated","positive","and","negative","boxes"]
code: def masks(self):
      """torch.Tensor: concatenated positive and negative boxes"""
      return torch.cat([self.pos_masks, self.neg_masks])
  
file_path: dinov2/dinov2/eval/segmentation_m2f/core/box/samplers/mask_sampling_result.py
imports: import torch
  from .sampling_result import SamplingResult
label_desc: Use image node_id 2 for calling the MaskSamplingResult obj's underlying member method code with example usage: obj.masks() and returns: torch