K折交叉验证代码实现——详细注释版

czijin

于 2024-10-23 22:22:48 发布

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分类专栏：机器学习文章标签：机器学习 K折交叉验证

本文链接：https://blog.youkuaiyun.com/m0_52049033/article/details/143195202

版权

在这里插入图片描述

正常方法

#---------------------------------Torch Modules --------------------------------------------------------
from __future__ import print_function
import numpy as np
import pandas as pd
import torch.nn as nn
import math
import torch.nn.functional as F
import torch
import torchvision
from torch.nn import init
import torch.optim as optim
from torchvision import datasets, transforms
from torchvision import models
import torch.nn.functional as F
from torch.utils import data
import matplotlib.pyplot as plt
import os
os.environ["KMP_DUPLICATE_LIB_OK"]="TRUE"

###-----------------------------------variables-----------------------------------------------
# for Normalization
mean = [0.5]
std = [0.5]
# batch size
batch_size =128
epoch = 1        # epoch
lr = 0.01

##-----------------------------------Commands to download and perpare the MNIST dataset ------------------------------------
train_transform = transforms.Compose([
        transforms.ToTensor(),
        transforms.Normalize(mean, std)
        ])
 
test_transform = transforms.Compose([
        transforms.ToTensor(),
        transforms.Normalize(mean, std)
        ])
 
    
train_loader = torch.utils.data.DataLoader(
        datasets.MNIST('./mnist', train=True, download=True,
                       transform=train_transform),
        batch_size=batch_size, shuffle=True) # train dataset
 
test_loader = torch.utils.data.DataLoader(
        datasets.MNIST('./mnist', train=False, 
                         transform=test_transform),
        batch_size=batch_size, shuffle=False) # test dataset loader的形状为128,1,28,28

#visualization
def show_images(imgs, num_rows, num_cols, titles=None, scale=1.5): 
    """Plot a list of images."""
    figsize = (num_cols * scale, num_rows * scale)
    _, axes = plt.subplots(num_rows, num_cols, figsize=figsize)
    axes = axes.flatten()
    for i, (ax, img) in enumerate(