code: def _compute_tensor(self, y_pred: torch.Tensor, y: torch.Tensor) -> torch.Tensor:  # type: ignore[override]
      if y_pred.ndimension() < 2:
          raise ValueError(
              "y_pred should have at least two dimensions."
          )
  
      return get_f_beta_score(
          y_pred=y_pred, y=y, include_background=self.include_background
      )
  
file_path: MONAI/monai/metrics/f_beta_score.py
imports: from __future__ import annotations
  from collections.abc import Sequence
  import torch
  from monai.metrics.utils import do_metric_reduction, ignore_background
  from monai.utils import MetricReduction
  from .metric import CumulativeIterationMetric
label_desc: Use image node_id 2 for calling the FBetaScore obj's underlying member method code with example usage: obj._compute_tensor(y_pred, y) and returns: get_f_beta_score