Pytorch, Deep Learning, Optimization, Tensorboard, Deep Dives.
momentum=0.9) model.train() # train step def train(data): inputs, labels = data[0].to(device=device), data[1].to(device=device) outputs = model(inputs) loss = criterion(outputs, labels) optimizer.zero_grad() loss.backward() optimizer.step() # training loop wrapped with profiler object with