code: def create_transformation(
      self, is_full_batch=False
  ) -> Transformation:
      return Chain(
          [
              InstanceSplitter(
                  target_field=FieldName.TARGET,
                  is_pad_field=FieldName.IS_PAD,
                  start_field=FieldName.START,
                  forecast_start_field=FieldName.FORECAST_START,
                  # train_sampler=ExpectedNumInstanceSampler(num_instances=1),
                  train_sampler=CustomUniformSampler(),
                  past_length=self.context_length,
                  future_length=self.prediction_length,
                  is_full_batch=is_full_batch,
                  time_series_fields=[],  # [FieldName.FEAT_DYNAMIC_REAL]
              )
          ]
      )
  
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 2 for calling the AREstimator obj's underlying member method code with example usage: obj.create_transformation(is_full_batch) and returns: Chain