code: def __init__(
      self,
      frequent,
      rank,
      batch_size,
      test_program,
      feed_list,
      fetch_list,
      val_targets,
      rec_prefix,
      image_size=(112, 112),
  ):
      self.frequent: int = frequent
      self.rank: int = rank
      self.batch_size: int = batch_size
  
      self.test_program: paddle.static.Program = test_program
      self.feed_list: List[paddle.fluid.framework.Variable] = feed_list
      self.fetch_list: List[
          paddle.fluid.framework.Variable
      ] = fetch_list
  
      self.highest_acc_list: List[float] = [0.0] * len(val_targets)
      self.ver_list: List[object] = []
      self.ver_name_list: List[str] = []
      self.init_dataset(
          val_targets=val_targets,
          data_dir=rec_prefix,
          image_size=image_size,
      )
  
      gpu_id = int(os.getenv("FLAGS_selected_gpus", 0))
      place = paddle.CUDAPlace(gpu_id)
      self.executor = paddle.static.Executor(place)
      self.data_feeder = paddle.fluid.DataFeeder(
          place=place,
          feed_list=self.feed_list,
          program=self.test_program,
      )
  
file_path: insightface/recognition/arcface_paddle/static/utils/verification.py
imports: import time
  import os
  import numpy
  import sklearn
  import paddle
  import logging
  from utils.verification import evaluate
  from datasets import load_bin
label_desc: Use image node_id 1 to create a new CallBackVerification object from inherited base classes: object with example: obj = CallBackVerification(frequent, rank, batch_size, test_program, feed_list, fetch_list, val_targets, rec_prefix, image_size)