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!pip install jovian --upgrade --quiet
project_name='my-course-prj'
jovian.commit(project=project_name)
[jovian] Detected Colab notebook... [jovian] Please enter your API key ( from https://jovian.ai/ ): API KEY: ·········· [jovian] Uploading colab notebook to Jovian... [jovian] Capturing environment.. [jovian] Committed successfully! https://jovian.ai/abdevilliers/my-course-prj 
'https://jovian.ai/abdevilliers/my-course-prj'
import os
import torch
import torchvision
import tarfile
import torch.nn as nn
import numpy as np
import torch.nn.functional as F
from torchvision.datasets.utils import download_url
from torchvision.datasets import ImageFolder
from torch.utils.data import DataLoader
import torchvision.transforms as tt
from torch.utils.data import random_split
from torchvision.utils import make_grid
import matplotlib
import matplotlib.pyplot as plt
%matplotlib inline

matplotlib.rcParams['figure.facecolor'] = '#ffffff'
from torchvision.datasets.utils import download_url


# Dowload the dataset
dataset_url = "https://s3.amazonaws.com/fast-ai-imageclas/food-101.tgz"
download_url(dataset_url, '.')

# Extract from archive
with tarfile.open('./food-101.tgz', 'r:gz') as tar:
    tar.extractall(path='./data')
Downloading https://s3.amazonaws.com/fast-ai-imageclas/food-101.tgz to ./food-101.tgz 
HBox(children=(FloatProgress(value=1.0, bar_style='info', max=1.0), HTML(value='')))