code: def _multiclass_confusion_matrix_update(
      preds: Tensor, target: Tensor, num_classes: int
  ) -> Tensor:
      """Compute the bins to update the confusion matrix with."""
      unique_mapping = target.to(torch.long) * num_classes + preds.to(
          torch.long
      )
      bins = _bincount(unique_mapping, minlength=num_classes**2)
      return bins.reshape(num_classes, num_classes)
  
imports: from typing import Optional, Tuple
  import torch
  from torch import Tensor
  from typing_extensions import Literal
  from torchmetrics.utilities.checks import _check_same_shape
  from torchmetrics.utilities.data import _bincount
  from torchmetrics.utilities.enums import ClassificationTask
  from torchmetrics.utilities.prints import rank_zero_warn
label_desc: Use image node_id 11 for calling a global function with example usage: _multiclass_confusion_matrix_update(preds, target, num_classes) and returns: bins