Ad

Saturday, March 2, 2019

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.

2 comments:

Debug Google Cloud Error - Failed to enable API please make sure you have the IAM permission to enable API

 If you are not expecting this message,  and think you have the permission to enable API read on. Before using Google Cloud services, genera...