code: def pixel_image(shape, sd=None, init_val=None):
      
      if sd is not None and init_val is not None:
          warnings.warn(
              "`pixel_image` received both an initial value and a sd argument. Ignoring sd in favor of the supplied initial value."
          )
  
      sd = sd or 0.01
      init_val = init_val or np.random.normal(size=shape, scale=sd).astype(np.float32)
      return tf.Variable(init_val)
docs: A naive, pixel-based image parameterization.
      Defaults to a random initialization, but can take a supplied init_val argument
      instead.
  
      Args:
        shape: shape of resulting image, [batch, width, height, channels].
        sd: standard deviation of param initialization noise.
        init_val: an initial value to use instead of a random initialization. Needs
          to have the same shape as the supplied shape argument.
  
      Returns:
        tensor with shape from first argument.