class_docstr: Base class for dense detector. We define a dense detector as a fully-convolutional model that
  makes per-pixel (i.e. dense) predictions.
code: def _move_to_current_device(self, x):
      return move_device_like(x, self.pixel_mean)
  
imports: import numpy
  from typing import Dict, List, Optional, Tuple
  import torch
  from torch import Tensor, nn
  from detectron2.data.detection_utils import convert_image_to_rgb
  from detectron2.layers import move_device_like
  from detectron2.modeling import Backbone
  from detectron2.structures import Boxes, ImageList, Instances
  from detectron2.utils.events import get_event_storage
  from ..postprocessing import detector_postprocess
label_desc: Use image node_id 3 for calling the DenseDetector obj's underlying member method code with example usage: obj._move_to_current_device(x) and returns: move_device_like