code: def box_area(boxes: Tensor) -> Tensor:
      """
      Computes the area of a set of bounding boxes, which are specified by their
      (x1, y1, x2, y2) coordinates.
  
      Args:
          boxes (Tensor[N, 4]): boxes for which the area will be computed. They
              are expected to be in (x1, y1, x2, y2) format with
              ``0 <= x1 < x2`` and ``0 <= y1 < y2``.
  
      Returns:
          Tensor[N]: the area for each box
      """
      if not torch.jit.is_scripting() and not torch.jit.is_tracing():
          _log_api_usage_once(box_area)
      boxes = _upcast(boxes)
      return (boxes[:, 2] - boxes[:, 0]) * (boxes[:, 3] - boxes[:, 1])
  
imports: from typing import Tuple
  import torch
  import torchvision
  from torch import Tensor
  from torchvision.extension import _assert_has_ops
  from ..utils import _log_api_usage_once
  from ._box_convert import _box_cxcywh_to_xyxy, _box_xywh_to_xyxy, _box_xyxy_to_cxcywh, _box_xyxy_to_xywh
  from ._utils import _upcast
label_desc: Use image node_id 8 for calling a global function with example usage: box_area(boxes) and returns: unknown