docstr: Performs Gamma Correction on the input image. Also known as 
  Power Law Transform. This function transforms the input image 
  pixelwise according 
  to the equation Out = In**gamma after scaling each 
  pixel to the range 0 to 1.
  
  Arguments
  ---------
  value : float
      <1 : image will tend to be lighter
      =1 : image will stay the same
      >1 : image will tend to be darker
code: def __init__(self, value):
      """
      Performs Gamma Correction on the input image. Also known as
      Power Law Transform. This function transforms the input image
      pixelwise according
      to the equation Out = In**gamma after scaling each
      pixel to the range 0 to 1.
  
      Arguments
      ---------
      value : float
          <1 : image will tend to be lighter
          =1 : image will stay the same
          >1 : image will tend to be darker
      """
      self.value = value
  
imports: import random
  import torch
  from torchvision.transforms.functional import to_tensor
  import numpy
  from ..utils import th_random_choice
label_desc: Use image node_id 1 to create a new Gamma object  with example: obj = Gamma(value)