application_vnd.jupyter.stderr_output_1.png
from torchvision import datasets, transforms

import torch
from torch import nn, optim
from torch.utils.data import DataLoader
from torchvision import datasets, transforms
import time
transform_train = transforms.Compose([transforms.RandomHorizontalFlip(p=0.5), transforms.ToTensor(), transforms.Normalize((0.485, 0.456, 0.406), (0.229, 0.224, 0.225))])
transform = transforms.Compose([transforms.ToTensor(), transforms.Normalize(std=(0.485, 0.456, 0.406), mean=(0.226, 0.224, 0.225))])
train_dataset = datasets.CIFAR10(root='../input/cifar10/cifar-10-batches-py', train=True, transform=transform_train, download=True)
test_dataset = datasets.CIFAR10(root='../input/cifar10/cifar-10-batches-py', train=False, transform=transform, download=True)