class_docstr: The parameter offload solver.
  
  Args:
      region_list (List[Region]): represents the linearized DNN computing graph.
      memory_budget (float): the given memory budget.
      error_factor (float): the error factor.
          It is used to reduce the memory budget. Due to some errors in the estimation of peak memory and execution time.
docstr: return the FP16 computing performance of the current NVIDIA GPU.
  
  Raises:
      TypeError: Unknown NVIDIA GPU device.
docstr_tok: ["return","the","FP16","computing","performance","of","the","current","NVIDIA","GPU",".","Raises",":","TypeError",":","Unknown","NVIDIA","GPU","device","."]
code: def _extract_computing_power(self):
      """
      return the FP16 computing performance of the current NVIDIA GPU.
  
      Raises:
          TypeError: Unknown NVIDIA GPU device.
      """
  
      nvmlInit()
      handle = nvmlDeviceGetHandleByIndex(0)
      device_name = nvmlDeviceGetName(handle)
      units = 1e12
  
      if device_name.__contains__("RTX 3080"):
          return NvDevicePower.RTX3080_FP16 * units
      elif device_name.__contains__("RTX 3090"):
          return NvDevicePower.RTX3090_FP16 * units
      elif device_name.__contains__("V100"):
          return NvDevicePower.V100_FP16 * units
      elif device_name.__contains__("A100"):
          return NvDevicePower.A100_FP16 * units
      else:
          raise TypeError(
              f"Unknown NVIDIA GPU device name {device_name}"
          )
  
imports: import time
  from abc import ABC, abstractmethod
  from typing import Dict, List, Type
  import torch
  from torch.fx.node import Node
  from colossalai.utils.device import get_current_device
  from .region import Region
  from .training_simulator import AsynTrainingSimulator, SynTrainingSimulator, TrainingSimulator
  from .util import NodeInfo, NvDevicePower
label_desc: Use image node_id 9 for calling the Solver obj's underlying member method code with example usage: obj._extract_computing_power() and returns: unknown, unknown, unknown, unknown