Daniel Voigt Godoy - Deep Learning with PyTorch Step-by-Step A Beginner’s Guide-leanpub

Define - Model Configuration V4
1 %%writefile model_configuration/v4.py
2
3 # Sets learning rate - this is "eta" ~ the "n"-like Greek letter
4 lr = 0.1
5
6 torch.manual_seed(42)
7 # Now we can create a model
8 model = nn.Sequential(nn.Linear(1, 1))
9
10 # Defines an SGD optimizer to update the parameters
11 # (now retrieved directly from the model)
12 optimizer = optim.SGD(model.parameters(), lr=lr)
13
14 # Defines an MSE loss function
15 loss_fn = nn.MSELoss(reduction='mean')
Run - Model Configuration V4
%run -i model_configuration/v4.py
Let’s inspect the randomly initialized parameters of our model:
print(model.state_dict())
Output
OrderedDict([('0.weight', tensor([[0.7645]])),
('0.bias', tensor([0.8300]))])
These are CPU tensors, since our model wasn’t sent anywhere (yet).
And now the fun begins: Let’s put our StepByStep class to good use and train our
model.
196 | Chapter 2.1: Going Classy