code: def create_predictor(
      self,
      transformation: Transformation,
      trained_network: nn.Module,
      device: torch.device,
  ) -> PTSPredictor:
      prediction_network = ARPredictionNetwork(
          prediction_length=self.prediction_length,
          context_length=self.context_length,
          num_parallel_samples=self.num_parallel_samples,
      ).to(device)
  
      copy_parameters(trained_network, prediction_network)
  
      return PTSPredictor(
          input_transform=transformation,
          prediction_net=prediction_network,
          batch_size=self.trainer.batch_size,
          freq=self.freq,
          prediction_length=self.prediction_length,
          device=device,
      )
  
file_path: gluonts/src/gluonts/nursery/SCott/model/ar/ar_estimator.py
imports: from typing import List, Optional
  import torch
  import torch.nn
  from pts import Trainer
  from pts.dataset import FieldName
  from pts.model import PTSEstimator, PTSPredictor, copy_parameters
  from pts.modules import DistributionOutput, StudentTOutput
  from pts.transform import Transformation, Chain, InstanceSplitter, ExpectedNumInstanceSampler
  from pts.transform.sampler import CustomUniformSampler
  from .ar_network import ARTrainingNetwork, ARPredictionNetwork
label_desc: Use image node_id 4 for calling the AREstimator obj's underlying member method code with example usage: obj.create_predictor(transformation, trained_network, device) and returns: PTSPredictor