code: def __call__(self, x, ts, **kwargs):
      map_tensor = paddle.to_tensor(
          self.timestep_map, place=ts.place, dtype=ts.dtype
      )
      new_ts = map_tensor[ts]
      if self.rescale_timesteps:
          new_ts = paddle.cast(new_ts, "float32") * (
              1000.0 / self.original_num_steps
          )
      return self.model(x, new_ts, **kwargs)
  
file_path: PaddleHub/modules/image/text_to_image/disco_diffusion_clip_rn50/reverse_diffusion/model/respace.py
imports: import numpy
  import paddle
  from .gaussian_diffusion import GaussianDiffusion
label_desc: Use image node_id 2 for calling the _WrappedModel obj's underlying member method code with example usage: obj.__call__(x, ts) and returns: self