DAY38 Dataset和DataLoader

@浙大疏锦行

importtorchimporttorch.nnasnnimporttorch.optimasoptimfromtorch.utils.dataimportDataLoader,Datasetfromtorchvisionimportdatasets,transformsimportmatplotlib.pyplotasplt torch.manual_seed(42)

transform=transforms.Compose([transforms.ToTensor(),transforms.Normalize((0.1307,),(0.3081,))])

train_dataset=datasets.MNIST(root='./data',train=True,download=True,transform=transform)test_dataset=datasets.MNIST(root='./data',train=False,transform=transform)

importmatplotlib.pyplotasplt sample_idx=torch.randint(0,len(train_dataset),size=(1,)).item()image,label=train_dataset[sample_idx]

fromtorchvisionimportdatasets,transformsclassMNIST(Dataset):def__init____init__(self,root,train=True,transform=None):self.data,self.targets=fetch_mnist_data(root,train)self.transform=transformdef__len__(self):returnlen(self.data)def__getitem__(self,idx):img,target=self.data[idx],self.targets[idx]ifself.transformisnotNone:img=self.transform(img)returnimg,target

defimshow(img):img=img*0.3081+0.1307nping=img.numpy()plt.imshow(nping[0],cmap='gray')plt.show()print(f"Label:{label}")imshow(image)

train_loader=DataLoader(train_dataset,batch_size=64,shuffle=True)test_loader=DataLoader(test_dataset,batch_size=1000)

下载cifar数据集并获取其中一张图片

importtorchvisionimportnumpyasnp transform=transforms.Compose([transforms.ToTensor(),transforms.Normalize((0.5,0.5,0.5),(0.5,0.5,0.5))])train_dataset=torchvision.datasets.CIFAR10(root='./data',train=True,download=True,transform=transform)sample_idx=0image,label=train_dataset[sample_idx]# 类别名称classes=('plane','car','bird','cat','deer','dog','frog','horse','ship','truck')print(f"图片形状:{image.shape}")print(f"标签:{label}-{classes[label]}")defimshow(img):img=img*0.5+0.5npimg=img.numpy()plt.imshow(np.transpose(npimg,(1,2,0)))plt.axis('off')imshow(image)plt.title(f'Label:{classes[label]}({label})')plt.show()