code: def _preprocess_CONTINUOUS(
      self,
      begin_index: int,
      input: torch.Tensor,
      norm_params: List[NormalizationParameters],
  ) -> torch.Tensor:
      means = self._fetch_parameter(begin_index, "means")
      stddevs = self._fetch_parameter(begin_index, "stddevs")
      continuous_output = (input - means) / stddevs
      return continuous_output
  
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 19 for calling the Preprocessor obj's underlying member method code with example usage: obj._preprocess_CONTINUOUS(begin_index, input, norm_params) and returns: continuous_output