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3 years ago
!pip install jovian --upgrade --quiet
project_name='my-course-project'
jovian.commit(project=project_name)
[jovian] Detected Colab notebook... [jovian] Uploading colab notebook to Jovian... [jovian] Capturing environment.. [jovian] Attaching records (metrics, hyperparameters, dataset etc.) [jovian] Committed successfully! https://jovian.ai/am67663/my-course-project 
'https://jovian.ai/am67663/my-course-project'
import os
import torch
import torchvision
import tarfile
from torchvision.datasets.utils import download_url
from torch.utils.data import random_split

CIFAR - 100: This dataset is just like the CIFAR-10, except it has 100 classes containing 600 images each. There are 500 training images and 100 testing images per class. The 100 classes in the CIFAR-100 are grouped into 20 superclasses. Each image comes with a "fine" label (the class to which it belongs) and a "coarse" label (the superclass to which it belongs).