code: def iou(
      predict: torch.Tensor,
      target: torch.Tensor,
      mask: Optional[torch.Tensor] = None,
  ) -> torch.Tensor:
      """
      This is a great loss because it emphasizes on the active
      regions of the predict and targets
      """
      dims = tuple(range(predict.dim())[1:])
      if mask is not None:
          predict = predict * mask
          target = target * mask
      intersect = (predict * target).sum(dims)
      union = (predict + target - predict * target).sum(dims) + 1e-4
      return (intersect / union).sum() / intersect.numel()
  
file_path: pytorch3d/pytorch3d/implicitron/tools/metric_utils.py
imports: import math
  from typing import Optional, Tuple
  import torch
  from torch.nn import functional
label_desc: Use image node_id 12 for calling a global function with example usage: iou(predict, target, mask) and returns: unknown