code: def input_prototype(self) -> Tuple[torch.Tensor, torch.Tensor]:
      return (
          torch.randn(
              1, len(self.normalization_parameters), device=self.device
          ),
          torch.ones(
              1,
              len(self.normalization_parameters),
              dtype=torch.uint8,
              device=self.device,
          ),
      )
  
imports: import logging
  from typing import cast, Dict, List, Optional, Tuple
  import torch
  from reagent.core.parameters import NormalizationParameters
  from reagent.preprocessing.identify_types import DO_NOT_PREPROCESS, ENUM, FEATURE_TYPES
  from reagent.preprocessing.normalization import EPS, MAX_FEATURE_VALUE, MIN_FEATURE_VALUE
  from torch.nn import Module, Parameter
label_desc: Use image node_id 2 for calling the Preprocessor obj's underlying member method code with example usage: obj.input_prototype() and returns: torch,  torch