Jovian
Sign In
Learn practical skills, build real-world projects, and advance your career
5 years ago
import numpy as np
import torch
from torchvision.datasets import CIFAR10

import matplotlib.pyplot as plt
%matplotlib inline

from torch.utils.data.sampler import SubsetRandomSampler
from torch.utils.data.dataloader import DataLoader

import torch.nn as nn

import torch.nn.functional as F


dataset = CIFAR10(root = '/data', download = True)
Files already downloaded and verified 
len(dataset)
50000
test_data = CIFAR10(root = '/data', train = False)
len(test_data)
10000
print(dataset.class_to_idx)
{'airplane': 0, 'automobile': 1, 'bird': 2, 'cat': 3, 'deer': 4, 'dog': 5, 'frog': 6, 'horse': 7, 'ship': 8, 'truck': 9}