code: def __call__(self, *inputs):
      # collect all of the lazily returned tform matrices
      tform_matrix = self.transforms[0](inputs[0])
      for tform in self.transforms[1:]:
          tform_matrix = tform_matrix.mm(tform(inputs[0]))
  
      if not isinstance(self.interp, (tuple, list)):
          interp = [self.interp] * len(inputs)
      else:
          interp = self.interp
  
      outputs = []
      idx = None
      for idx, _input in enumerate(inputs):
          input_tf = th_affine2d(_input, tform_matrix, mode=interp[idx])
          outputs.append(input_tf)
      return outputs if idx >= 1 else outputs[0]
  
imports: import math
  import random
  import torch
  from ..utils import th_affine2d, th_random_choice
label_desc: Use image node_id 2 for calling the AffineCompose obj's underlying member method code with example usage: obj.__call__() and returns: unknown