一、DataLoader参数解析

DataLoader官网使用手册

参数	描述
dataset	说明数据集所在的位置、数据总数等
batch_size	每次取多少张图片
shuffle	True乱序、False顺序(默认)
sampler
batch_sampler
num_workers	多进程，默认为0采用主进程加载数据
collate_fn
pin_memory
drop_last	True最后不满一个batch_size的去掉，False最后剩余多少也都要
timeout
worker_init_fn
generator
prefetch_factor
prefetch_factor
pin_memory_device

import torchvision
from torch.utils.data import DataLoader
from torch.utils.tensorboard import SummaryWritertest_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, targettest_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)#3writer = 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+1writer.close()

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