class_docstr: Wrapper for deprecated import.
  
  >>> from torch import tensor
  >>> psnr = _PeakSignalNoiseRatio()
  >>> preds = tensor([[0.0, 1.0], [2.0, 3.0]])
  >>> target = tensor([[3.0, 2.0], [1.0, 0.0]])
  >>> psnr(preds, target)
  tensor(2.5527)
code: def __init__(
      self,
      data_range: Optional[Union[float, Tuple[float, float]]] = None,
      base: float = 10.0,
      reduction: Literal[
          "elementwise_mean", "sum", "none", None
      ] = "elementwise_mean",
      dim: Optional[Union[int, Tuple[int, ...]]] = None,
      **kwargs: Any,
  ) -> None:
      _deprecated_root_import_class("PeakSignalNoiseRatio", "image")
      super().__init__(
          data_range=data_range,
          base=base,
          reduction=reduction,
          dim=dim,
          **kwargs,
      )
  
imports: from typing import Any, Dict, Optional, Sequence, Tuple, Union
  from typing_extensions import Literal
  from torchmetrics.image.d_lambda import SpectralDistortionIndex
  from torchmetrics.image.ergas import ErrorRelativeGlobalDimensionlessSynthesis
  from torchmetrics.image.psnr import PeakSignalNoiseRatio
  from torchmetrics.image.rase import RelativeAverageSpectralError
  from torchmetrics.image.rmse_sw import RootMeanSquaredErrorUsingSlidingWindow
  from torchmetrics.image.sam import SpectralAngleMapper
  from torchmetrics.image.ssim import MultiScaleStructuralSimilarityIndexMeasure, StructuralSimilarityIndexMeasure
  from torchmetrics.image.tv import TotalVariation
  from torchmetrics.image.uqi import UniversalImageQualityIndex
  from torchmetrics.utilities.prints import _deprecated_root_import_class
label_desc: Use image node_id 1 to create a new _PeakSignalNoiseRatio object from inherited base classes: PeakSignalNoiseRatio with example: obj = _PeakSignalNoiseRatio(data_range, base, reduction, dim)