code: def __call__(self, ir_model):
      latency = self.predictors.predict(ir_model, "nni-ir")
      return latency < self.threshold
  
imports: import time
  import json
  import random
  import logging
  import argparse
  import numpy
  import torch
  import torchvision.transforms
  import torchvision.datasets
  import nni
  from nn_meter import load_latency_predictor
  import nni.retiarii.nn.pytorch
  import nni.retiarii.strategy
  from nni.retiarii.evaluator.functional import FunctionalEvaluator
  from nni.retiarii.utils import original_state_dict_hooks
  from nni.retiarii.oneshot.pytorch.utils import AverageMeterGroup
  from nni.retiarii.experiment.pytorch import RetiariiExeConfig, RetiariiExperiment
  from network import ShuffleNetV2OneShot, load_and_parse_state_dict
  from utils import CrossEntropyLabelSmooth, accuracy, ToBGRTensor, get_archchoice_by_model
label_desc: Use image node_id 2 for calling the LatencyFilter obj's underlying member method code with example usage: obj.__call__(ir_model) and returns: unknown