code: def _set_transform_states(self, states):
      assert len(states) == len(self.transforms)
      for state, transform in zip(states, self.transforms):
          transform.set_state(state)
  
imports: import paddle
  import paddle.nn.functional
  import numpy
  from inference.transforms import AddHorizontalFlip, SigmoidForPred, LimitLongestSide
  from .ops import DistMaps, ScaleLayer, BatchImageNormalize
label_desc: Use image node_id 9 for calling the BasePredictor obj's underlying member method code with example usage: obj._set_transform_states(states) without return types