[PyTorch] testAccuacy in CPU

import torch
import torch.nn as nn
#from __future__ import print_function
import argparse
from PIL import Image
import torchvision.models as models
import skimage.io
from torch.autograd import Variable as V
from torch.nn import functional as f
from torchvision import transforms as trn

# define image transformation
centre_crop = trn.Compose([
        trn.ToPILImage(),
        trn.Scale(256),
        trn.CenterCrop(224),
        trn.ToTensor(),
        trn.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])
])

filename=r'/Users/dti/Desktop/PyTorch4testAccuracy/hymenoptera_data/test/bees/1.jpg'
img = skimage.io.imread(filename)

x = V(centre_crop(img).unsqueeze(0), volatile=True)

model = models.__dict__['resnet18']
model = torch.load('model5.pth')

logit = model(x)
print(logit)

h_x = f.softmax(logit).data.squeeze()
print(h_x)