code: def __call__(self, *inputs):
      outputs = []
      idx = None
      for idx, _input in enumerate(inputs):
          _in_gs = Grayscale(keep_channels=True)(_input)
          alpha = 1.0 + self.value
          _in = th.clamp(_blend(_input, _in_gs, alpha), 0, 1)
          outputs.append(_in)
      return outputs if idx >= 1 else outputs[0]
  
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 2 for calling the Saturation obj's underlying member method code with example usage: obj.__call__() and returns: unknown