Create a classifier for mnist dataset

from __future__ import print_function
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.autograd import Variable

from torchvision import datasets, transforms
mnist = datasets.MNIST(root='.', train=True, download=True)

print("Number of training examples", mnist.train_data.shape)
print("Image information", mnist[0])

import matplotlib.pyplot as plt
%matplotlib inline
plt.imshow(mnist[0][0])

To Do: model

To Do: data loader

To Do: training setup

To Do: evaluate the performance of the classifier