class_docstr: Module that apply the sepia filter to tensors.
  
  Args:
      input: the input tensor with shape of :math:`(*, C, H, W)`.
      rescale: If True, the output tensor will be rescaled (max values be 1. or 255).
      eps: scalar to enforce numerical stability.
  
  Returns:
      Tensor: The sepia tensor of same size and numbers of channels
      as the input with shape :math:`(*, C, H, W)`.
  
  Example:
      >>>
      >>> input = torch.ones(3, 1, 1)
      >>> Sepia(rescale=False)(input)
      tensor([[[1.3510]],
      <BLANKLINE>
              [[1.2030]],
      <BLANKLINE>
              [[0.9370]]])
code: def __init__(self, rescale: bool = True, eps: float = 1e-6) -> None:
      self.rescale = rescale
      self.eps = eps
      super().__init__()
  
file_path: kornia/kornia/color/sepia.py
imports: import torch
  from kornia.core import Module, Tensor
label_desc: Use image node_id 1 to create a new Sepia object from inherited base classes: Module with example: obj = Sepia(rescale, eps)