code: def _signal_distortion_ratio(
      preds: Tensor,
      target: Tensor,
      use_cg_iter: Optional[int] = None,
      filter_length: int = 512,
      zero_mean: bool = False,
      load_diag: Optional[float] = None,
  ) -> Tensor:
      """Wrapper for deprecated import.
  
      >>> import torch
      >>> g = torch.manual_seed(1)
      >>> preds = torch.randn(8000)
      >>> target = torch.randn(8000)
      >>> _signal_distortion_ratio(preds, target)
      tensor(-12.0589)
      >>> # use with permutation_invariant_training
      >>> preds = torch.randn(4, 2, 8000)  # [batch, spk, time]
      >>> target = torch.randn(4, 2, 8000)
      >>> best_metric, best_perm = _permutation_invariant_training(preds, target, _signal_distortion_ratio)
      >>> best_metric
      tensor([-11.6375, -11.4358, -11.7148, -11.6325])
      >>> best_perm
      tensor([[1, 0],
              [0, 1],
              [1, 0],
              [0, 1]])
  
      """
      _deprecated_root_import_func("signal_distortion_ratio", "audio")
      return signal_distortion_ratio(
          preds=preds,
          target=target,
          use_cg_iter=use_cg_iter,
          filter_length=filter_length,
          zero_mean=zero_mean,
          load_diag=load_diag,
      )
  
file_path: torchmetrics/src/torchmetrics/functional/audio/_deprecated.py
imports: from typing import Any, Callable, Optional, Tuple
  from torch import Tensor
  from typing_extensions import Literal
  from torchmetrics.functional.audio.pit import permutation_invariant_training, pit_permutate
  from torchmetrics.functional.audio.sdr import scale_invariant_signal_distortion_ratio, signal_distortion_ratio
  from torchmetrics.functional.audio.snr import scale_invariant_signal_noise_ratio, signal_noise_ratio
  from torchmetrics.utilities.prints import _deprecated_root_import_func
label_desc: Use image node_id 4 for calling a global function with example usage: _signal_distortion_ratio(preds, target, use_cg_iter, filter_length, zero_mean, load_diag) and returns: signal_distortion_ratio