code: def ycbcr_to_rgb(image: Tensor) -> Tensor:
      r"""Convert an YCbCr image to RGB.
  
      The image data is assumed to be in the range of (0, 1).
  
      Args:
          image: YCbCr Image to be converted to RGB with shape :math:`(*, 3, H, W)`.
  
      Returns:
          RGB version of the image with shape :math:`(*, 3, H, W)`.
  
      Examples:
          >>> input = torch.rand(2, 3, 4, 5)
          >>> output = ycbcr_to_rgb(input)  # 2x3x4x5
      """
      if not isinstance(image, Tensor):
          raise TypeError(
              f"Input type is not a Tensor. Got {type(image)}"
          )
  
      if len(image.shape) < 3 or image.shape[-3] != 3:
          raise ValueError(
              f"Input size must have a shape of (*, 3, H, W). Got {image.shape}"
          )
  
      y: Tensor = image[..., 0, :, :]
      cb: Tensor = image[..., 1, :, :]
      cr: Tensor = image[..., 2, :, :]
  
      delta: float = 0.5
      cb_shifted: Tensor = cb - delta
      cr_shifted: Tensor = cr - delta
  
      r: Tensor = y + 1.403 * cr_shifted
      g: Tensor = y - 0.714 * cr_shifted - 0.344 * cb_shifted
      b: Tensor = y + 1.773 * cb_shifted
      return torch.stack([r, g, b], -3).clamp(0, 1)
  
file_path: kornia/kornia/color/ycbcr.py
imports: import torch
  from torch import Tensor, nn
label_desc: Use image node_id 4 for calling a global function with example usage: ycbcr_to_rgb(image) and returns: torch