class_docstr: The result of the OptimizeInferenceOp
class_docstr_tok: ["The","result","of","the","OptimizeInferenceOp"]
code: def throughput_improvement_rate(self) -> Optional[float]:
      if self.optimized_model is None:
          return None
      if self.original_model.throughput == 0:
          return -1
      return (
          self.optimized_model.throughput
          / self.original_model.throughput
      )
  
imports: import subprocess
  from dataclasses import dataclass
  from enum import Enum
  from functools import cached_property
  from typing import Optional, Any, Union, Tuple, List, Dict
  import numpy
  from nebullvm.optional_modules.tensorflow import tensorflow
  from nebullvm.optional_modules.torch import torch
label_desc: Use image node_id 3 for calling the OptimizeInferenceResult obj's underlying member method code with example usage: obj.throughput_improvement_rate() and returns: unknown, None, unknown