code: def apply_box_deltas_3D(boxes, deltas):
      """Applies the given deltas to the given boxes.
      boxes: [N, 6] where each row is y1, x1, y2, x2, z1, z2
      deltas: [N, 6] where each row is [dy, dx, dz, log(dh), log(dw), log(dd)]
      """
      # Convert to y, x, h, w
      height = boxes[:, 2] - boxes[:, 0]
      width = boxes[:, 3] - boxes[:, 1]
      depth = boxes[:, 5] - boxes[:, 4]
      center_y = boxes[:, 0] + 0.5 * height
      center_x = boxes[:, 1] + 0.5 * width
      center_z = boxes[:, 4] + 0.5 * depth
      # Apply deltas
      center_y += deltas[:, 0] * height
      center_x += deltas[:, 1] * width
      center_z += deltas[:, 2] * depth
      height *= torch.exp(deltas[:, 3])
      width *= torch.exp(deltas[:, 4])
      depth *= torch.exp(deltas[:, 5])
      # Convert back to y1, x1, y2, x2
      y1 = center_y - 0.5 * height
      x1 = center_x - 0.5 * width
      z1 = center_z - 0.5 * depth
      y2 = y1 + height
      x2 = x1 + width
      z2 = z1 + depth
      result = torch.stack([y1, x1, y2, x2, z1, z2], dim=1)
      return result
  
imports: import numpy
  import scipy.misc
  import scipy.ndimage
  import torch
  from torch.autograd import Variable
  import torch.nn
label_desc: Use image node_id 11 for calling a global function with example usage: apply_box_deltas_3D(boxes, deltas) and returns: result