text: from model import mixer_b
  import os
  import cv2
  import numpy as np
  
  import paddle
  import paddle.nn as nn
  import paddle.vision.transforms as T
  from paddle.vision.datasets import Cifar10
  from PIL import Image
  
  val_transforms = T.Compose([
      T.Resize(224),
      T.ToTensor(),
      T.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])
  ])
  
  # 加载模型
  model = mixer_b(class_dim=10)
  params = paddle.load(os.path.join('save', "best_model.pdparams"))
  model.set_dict(params)
  model = paddle.Model(model)
  model.prepare(metrics=paddle.metric.Accuracy(topk=(1, 5)))
  
  # 配置数据集
  val_dataset = Cifar10(transform=val_transforms, backend='pil', mode='test')
  
  
  # 模型验证
  acc = model.evaluate(val_dataset, batch_size=16, num_workers=0)
  print(acc)
  