Object instantiation for training an autoencoder written in PyTorch.

instantiate_objects.py

#  use gpu if available
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")

# create a model from `AE` autoencoder class
# load it to the specified device, either gpu or cpu
model = AE(input_shape=784).to(device)

# create an optimizer object
# Adam optimizer with learning rate 1e-3
optimizer = optim.Adam(model.parameters(), lr=1e-3)

# mean-squared error loss
criterion = nn.MSELoss()