class_docstr: Mean-squared error loss function.
  
  This function assumes the input images are in the [0.0, 1.0] range. To
  match existing neural compression implementations, the MSE result is
  multiplied by ``scale_param``, which is 255.0**2 by default.
  
  Args:
      scale_param: The scaling parameter for the loss term.
code: def __init__(self, scale_param: float = 255.0**2):
      super().__init__()
      self.scale_param = scale_param
  
imports: import torch.nn.functional
  from torch import Tensor
  from ._distortion_loss import DistortionLoss
label_desc: Use image node_id 1 to create a new MSELoss object from inherited base classes: DistortionLoss with example: obj = MSELoss(scale_param)