code: def brighten(
      tens: Tensor, coeff: float = -1, rgb: bool = True
  ) -> Tensor:
      r"""
          Brighten an image.
  
      Args:
          tens (Tensor) : Any regular ``caer.Tensor``.
          coeff (float): Coefficient value.
          rgb (bool): Operate on RGB images. Default: True.
  
      Returns:
          Tensor of shape ``(height, width, channels)``.
  
      Examples::
  
          >> tens = caer.data.sunrise(rgb=True)
          >> filtered = caer.transforms.brighten(tens, coeff=-1, rgb=True)
          >> filtered
          (427, 640, 3)
  
      """
      tens = to_tensor(tens, enforce_tensor=True)
      cspace = tens.cspace
  
      if coeff != -1:
          if coeff < 0.0 or coeff > 1.0:
              raise ValueError(
                  "Brightness coefficient can only be between 0.0 and 1.0"
              )
  
      if coeff == -1:
          coeff_t = 1 + random.uniform(
              0, 1
          )  # coeff between 1.0 and 1.5
      else:
          coeff_t = 1 + coeff  # coeff between 1.0 and 2.0
  
      tens = adjust_brightness(tens, coeff_t)
      return to_tensor(tens, cspace=cspace)
  
file_path: caer/caer/transforms/color.py
imports: import numpy
  import random
  import cv2
  import math
  from ..coreten import Tensor, to_tensor
  from ..annotations import Union, List, Tuple
  from .functional import is_list, _hls, _exposure_process
label_desc: Use image node_id 2 for calling a global function with example usage: brighten(tens, coeff, rgb) and returns: to_tensor