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

Model Configuration
1 # Sets learning rate - this is "eta" ~ the "n"-like Greek letter
2 lr = 0.1
3
4 torch.manual_seed(42)
5 # Now we can create a model
6 model_relu = nn.Sequential()
7 model_relu.add_module('flatten', nn.Flatten())
8 model_relu.add_module('hidden0', nn.Linear(25, 5, bias=False))
9 model_relu.add_module('activation0', nn.ReLU())
10 model_relu.add_module('hidden1', nn.Linear(5, 3, bias=False))
11 model_relu.add_module('activation1', nn.ReLU())
12 model_relu.add_module('output', nn.Linear(3, 1, bias=False))
13 model_relu.add_module('sigmoid', nn.Sigmoid())
14
15 # Defines an SGD optimizer to update the parameters
16 optimizer_relu = optim.SGD(model_relu.parameters(), lr=lr)
17
18 # Defines a binary cross-entropy loss function
19 binary_loss_fn = nn.BCELoss()
Model Training
1 n_epochs = 50
2
3 sbs_relu = StepByStep(model_relu, binary_loss_fn, optimizer_relu)
4 sbs_relu.set_loaders(train_loader, val_loader)
5 sbs_relu.train(n_epochs)
Putting It All Together | 329