docstr: Arguments
  ---------
  value : float
      Fractional zoom.
      =1 : no zoom
      >1 : zoom-in (value-1)%
      <1 : zoom-out (1-value)%
  
  interp : string in {'bilinear', 'nearest'} or list of strings
      type of interpolation to use. You can provide a different
      type of interpolation for each input, e.g. if you have two
      inputs then you can say `interp=['bilinear','nearest']
  
  lazy: boolean
      If true, just return transformed
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code: def __init__(self, value, interp="bilinear", lazy=False):
      """
      Arguments
      ---------
      value : float
          Fractional zoom.
          =1 : no zoom
          >1 : zoom-in (value-1)%
          <1 : zoom-out (1-value)%
  
      interp : string in {'bilinear', 'nearest'} or list of strings
          type of interpolation to use. You can provide a different
          type of interpolation for each input, e.g. if you have two
          inputs then you can say `interp=['bilinear','nearest']
  
      lazy: boolean
          If true, just return transformed
      """
  
      if not isinstance(value, (tuple, list)):
          value = (value, value)
      self.value = value
      self.interp = interp
      self.lazy = lazy
  
imports: import math
  import random
  import torch
  from ..utils import th_affine2d, th_random_choice
label_desc: Use image node_id 1 to create a new Zoom object  with example: obj = Zoom(value, interp, lazy)