class_docstr: Base match cost class.
  
  Args:
      weight (Union[float, int]): Cost weight. Defaults to 1.
class_docstr_tok: ["Base","match","cost","class",".","Args",":","weight","(","Union","[","float",",","int","]",")",":","Cost","weight",".","Defaults","to","1","."]
docstr: Compute match cost.
  
  Args:
      pred_instances (:obj:`InstanceData`): Instances of model
          predictions. It includes ``priors``, and the priors can
          be anchors or points, or the bboxes predicted by the
          previous stage, has shape (n, 4). The bboxes predicted by
          the current model or stage will be named ``bboxes``,
          ``labels``, and ``scores``, the same as the ``InstanceData``
          in other places.
      gt_instances (:obj:`InstanceData`): Ground truth of instance
          annotations. It usually includes ``bboxes``, with shape (k, 4),
          and ``labels``, with shape (k, ).
      img_meta (dict, optional): Image information.
  
  Returns:
      Tensor: Match Cost matrix of shape (num_preds, num_gts).
code: def __call__(
      self,
      pred_instances: InstanceData,
      gt_instances: InstanceData,
      img_meta: Optional[dict] = None,
      **kwargs,
  ) -> Tensor:
      """Compute match cost.
  
      Args:
          pred_instances (:obj:`InstanceData`): Instances of model
              predictions. It includes ``priors``, and the priors can
              be anchors or points, or the bboxes predicted by the
              previous stage, has shape (n, 4). The bboxes predicted by
              the current model or stage will be named ``bboxes``,
              ``labels``, and ``scores``, the same as the ``InstanceData``
              in other places.
          gt_instances (:obj:`InstanceData`): Ground truth of instance
              annotations. It usually includes ``bboxes``, with shape (k, 4),
              and ``labels``, with shape (k, ).
          img_meta (dict, optional): Image information.
  
      Returns:
          Tensor: Match Cost matrix of shape (num_preds, num_gts).
      """
      pass
  
imports: from abc import abstractmethod
  from typing import Optional, Union
  import torch
  import torch.nn.functional
  from mmengine.structures import InstanceData
  from torch import Tensor
  from mmdet.registry import TASK_UTILS
  from mmdet.structures.bbox import bbox_overlaps, bbox_xyxy_to_cxcywh
label_desc: Use image node_id 2 for calling the BaseMatchCost obj's underlying member method code with example usage: obj.__call__(pred_instances, gt_instances, img_meta) without return types