code: def compute_area(inputs: List[Any], iou_type: str = "bbox") -> Tensor:
      """Compute area of input depending on the specified iou_type.
  
      Default output for empty input is :class:`~torch.Tensor`
  
      """
      import pycocotools.mask as mask_utils
      from torchvision.ops import box_area
  
      if len(inputs) == 0:
          return Tensor([])
  
      if iou_type == "bbox":
          return box_area(torch.stack(inputs))
      if iou_type == "segm":
          inputs = [{"size": i[0], "counts": i[1]} for i in inputs]
          return torch.tensor(mask_utils.area(inputs).astype("float"))
  
      raise Exception(f"IOU type {iou_type} is not supported")
  
imports: import logging
  from typing import Any, Callable, Dict, List, Optional, Sequence, Tuple, Union
  import numpy
  import torch
  import torch.distributed
  from torch import IntTensor, Tensor
  from torchmetrics.detection.helpers import _fix_empty_tensors, _input_validator
  from torchmetrics.metric import Metric
  from torchmetrics.utilities.data import _cumsum
  from torchmetrics.utilities.imports import _MATPLOTLIB_AVAILABLE, _PYCOCOTOOLS_AVAILABLE, _TORCHVISION_GREATER_EQUAL_0_8
  from torchmetrics.utilities.plot import _AX_TYPE, _PLOT_OUT_TYPE
label_desc: Use image node_id 1 for calling a global function with example usage: compute_area(inputs, iou_type) and returns: Tensor, box_area, torch