六、DataLoader

一、DataLoader参数解析

DataLoader官网使用手册

import torchvision
from torch.utils.data import DataLoader
from torch.utils.tensorboard import SummaryWriter

test_data = torchvision.datasets.CIFAR10("CIFAR_10",train=False,transform=torchvision.transforms.ToTensor())
#Ctrl按住，点击CIFAR10，找到__getitem__类，查看返回值return img, target

test_loader = DataLoader(dataset=test_data,batch_size=64,shuffle=True,num_workers=0,drop_last=False)
#drop_last=False，最后剩余多少也都要 
#shuffle=True，乱序

#测试一下
img,target = test_data[0]
print(img.shape)#torch.Size([3, 32, 32])
print(target)#3


writer = SummaryWriter("y_log")
i = 0
for data in test_loader:
    imgs,targets = data
    #print(type(imgs))
    writer.add_images("test_data",imgs,i)
    i = i+1

writer.close()
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在Terminal下运行tensorboard --logdir=y_log --port=2312，logdir为打开事件文件的路径，port为指定端口打开；
通过指定端口2312进行打开tensorboard，若不设置port参数，默认通过6006端口进行打开。

点击该链接或者复制链接到浏览器打开即可

import torchvision
from torch.utils.data import DataLoader
from torch.utils.tensorboard import SummaryWriter

test_data = torchvision.datasets.CIFAR10("CIFAR_10",train=False,transform=torchvision.transforms.ToTensor())
#Ctrl按住，点击CIFAR10，找到__getitem__类，查看返回值return img, target

test_loader = DataLoader(dataset=test_data,batch_size=64,shuffle=False,num_workers=0,drop_last=True)
#drop_last=True，不满一组的舍去 
#shuffle=False，顺序

img,target = test_data[0]
print(img.shape)#torch.Size([3, 32, 32])
print(target)#3


writer = SummaryWriter("y_log")

for epoch in range(3):
    i = 0
    for data in test_loader:
        imgs,targets = data
        #print(type(imgs))
        writer.add_images("Epoch:{}".format(epoch),imgs,i)
        i = i+1

writer.close()

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