class_docstr: Wrapper for deprecated import.
  
  >>> import torch
  >>> _ = torch.manual_seed(42)
  >>> tv = _TotalVariation()
  >>> img = torch.rand(5, 3, 28, 28)
  >>> tv(img)
  tensor(7546.8018)
code: def __init__(
      self,
      reduction: Literal["mean", "sum", "none", None] = "sum",
      **kwargs: Any,
  ) -> None:
      _deprecated_root_import_class("TotalVariation", "image")
      super().__init__(reduction=reduction, **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 _TotalVariation object from inherited base classes: TotalVariation with example: obj = _TotalVariation(reduction)