class_docstr: Create and update states for computing group stats tp, fp, tn and fn.
code: def _update_states(
      self,
      group_stats: List[
          Tuple[torch.Tensor, torch.Tensor, torch.Tensor, torch.Tensor]
      ],
  ) -> None:
      for group, stats in enumerate(group_stats):
          tp, fp, tn, fn = stats
          self.tp[group] += tp
          self.fp[group] += fp
          self.tn[group] += tn
          self.fn[group] += fn
  
imports: from typing import Any, Dict, List, Optional, Sequence, Tuple, Union
  import torch
  from torch import Tensor
  from typing_extensions import Literal
  from torchmetrics.functional.classification.group_fairness import _binary_groups_stat_scores, _compute_binary_demographic_parity, _compute_binary_equal_opportunity
  from torchmetrics.functional.classification.stat_scores import _binary_stat_scores_arg_validation
  from torchmetrics.metric import Metric
  from torchmetrics.utilities import rank_zero_warn
  from torchmetrics.utilities.imports import _MATPLOTLIB_AVAILABLE
  from torchmetrics.utilities.plot import _AX_TYPE, _PLOT_OUT_TYPE
label_desc: Use image node_id 2 for calling the _AbstractGroupStatScores obj's underlying member method code with example usage: obj._update_states(group_stats) without return types