Image Classification with Logistic Regression (Minimal)

# Uncomment and run the commands below if imports fail
# !conda install numpy pytorch torchvision cpuonly -c pytorch -y
# !pip install matplotlib --upgrade --quiet
!pip install jovian --upgrade --quiet

WARNING: You are using pip version 20.1; however, version 20.1.1 is available.
You should consider upgrading via the '/opt/conda/bin/python3.7 -m pip install --upgrade pip' command.

import torch
import jovian
import torchvision
import torch.nn as nn
import matplotlib.pyplot as plt
import torch.nn.functional as F
import torchvision.transforms as transforms
from torchvision.datasets import MNIST
from torch.utils.data import random_split
from torch.utils.data import DataLoader

Dataset & Data loaders

# Download dataset
dataset = MNIST(root='data/', train=True, transform=transforms.ToTensor(), download=True)

# Training validation & test dataset
train_ds, val_ds = random_split(dataset, [50000, 10000])
test_ds = MNIST(root='data/', train=False, transform=transforms.ToTensor())

# Dataloaders
batch_size = 128
train_loader = DataLoader(train_ds, batch_size, shuffle=True)
val_loader = DataLoader(val_ds, batch_size*2)
test_loader = DataLoader(test_ds, batch_size*2)