Pytorch Cheatsheet for beginners

train_loader, test_loader in python code pattern

train_loader = torch.utils.data.DataLoader(train_data, batch_size=batch_size, num_workers=num_workers)
test_loader = torch.utils.data.DataLoader(test_data, batch_size=batch_size, num_workers=num_workers)

Pytorch dataloader helps load data in batches such as images.

Flavors of Pytorch Model Initialization

Functional

import torch.nn as nn

import torch.nn.functional as F

Object Oriented OOP

class Autoencoder(nn.Module):

    def __init__(self, encoding_dim):

        super(Autoencoder, self).__init__()

        ## encoder ##

        

        ## decoder ##

        

    def forward(self, x):

        # define feedforward behavior 

        # and scale the *output* layer with a sigmoid activation function

        

        return x

Best Practice:
Pytorch do sanity check load checkpoint and make sure everything worked. Imshow() the output image make sure it is the desired output. Do sanity check, visual check.