code: def _send_feedback(
      self,
      optimization_result: OptimizeInferenceResult,
      store_latencies: bool = False,
  ):
      model_orig = optimization_result.original_model.model
      model_name = get_model_name(model_orig)
      model_info = {
          "model_name": model_name,
          "model_size": f"{get_model_size_mb(model_orig)} MB",
          "framework": optimization_result.original_model.framework.value,
      }
      self.feedback_collector.store_info(
          key="model_id", value=generate_model_id(model_orig)
      )
      self.feedback_collector.store_info(
          key="model_metadata", value=model_info
      )
      self.feedback_collector.store_info(
          key="hardware_setup", value=get_hw_setup(self.device).__dict__
      )
      optimizations = self.feedback_collector.get("optimizations")
      original_model_dict = {
          "compiler": optimization_result.original_model.framework.value,
          "technique": "original",
          "latency": optimization_result.original_model.latency_seconds,
      }
      optimizations.insert(0, original_model_dict)
      self.feedback_collector.send_feedback()
  
      if store_latencies:
          model_id = self.feedback_collector.get("model_id", "")
          with open(
              f"{model_name}_latencies_{model_id[:10]}.json", "w"
          ) as f:
              json.dump(
                  {
                      "optimizations": optimizations,
                  },
                  f,
              )
      self.feedback_collector.reset("optimizations")
      self.feedback_collector.reset("model_id")
      self.feedback_collector.reset("model_metadata")
  
imports: import json
  import pickle
  import sys
  from typing import Any, Union, Iterable, Sequence, Dict, Callable, List
  from loguru import logger
  from nebullvm import setup_logger
  from nebullvm.config import MIN_NUMBER
  from nebullvm.core.models import OptimizeInferenceResult, DeviceType
  from nebullvm.operations.base import Operation
  from nebullvm.operations.optimizations.optimize_inference import OptimizeInferenceOp
  from nebullvm.tools.data import DataManager
  from nebullvm.tools.feedback_collector import FeedbackCollector
  from tabulate import tabulate
  from nebullvm.tools.hardware_utils import get_hw_setup
  from nebullvm.tools.utils import get_model_size_mb, get_model_name, generate_model_id
label_desc: Use image node_id 2 for calling the SpeedsterRootOp obj's underlying member method code with example usage: obj._send_feedback(optimization_result, store_latencies) without return types