code: def _preprocess_PROBABILITY(
      self,
      begin_index: int,
      input: torch.Tensor,
      norm_params: List[NormalizationParameters],
  ) -> torch.Tensor:
      clamped_input = torch.clamp(input, 1e-5, 1 - 1e-5)
      return self.negative_one_tensor * (
          ((self.one_tensor / clamped_input) - self.one_tensor).log()
      )
  
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 13 for calling the Preprocessor obj's underlying member method code with example usage: obj._preprocess_PROBABILITY(begin_index, input, norm_params) and returns: unknown