Pytorch: steps to train a model

1.  set model status, for example, set the model to train or eval mode

model.train()
model.eval()

2. initialize running loss

running_loss = 0.0

3. load inputs and labels from dataloader

for inputs, labels in dataloaders[phase]:
    inputs, labels = Variable(inputs.cuda()), Variable(labels.cuda())

4. set the grad of optimizer to zero

 optimizer.zero_grad()

5. forward propaganda and culculate loss

outputs = model(inputs)
loss = criterion(outputs, labels)

6. backward propaganda

loss.backward()
optimizer.step()

7. update the loss

running_loss += loss.item() * inputs.size(0)