code: def process(self, training_example: dict) -> None:
      feature = training_example[self.field]
  
      feature = self.guard_fn(feature)
      feature = torch.log(feature)
  
      training_example[self.field] = feature
  
imports: import json
  from abc import ABC, abstractmethod
  from pathlib import Path
  from typing import Optional
  import torch
  from nemo.utils.decorators import experimental
label_desc: Use image node_id 4 for calling the LogCompression obj's underlying member method code with example usage: obj.process(training_example) without return types