Pytorch, Pytorch Rnn, Pytorch Mnist Dataset, Build Model With Pytorch.
labels) # Backward and optimize optimizer.zero_grad() loss.backward() optimizer.step() if (i+1) % 100 == 0: print ('Epoch [{}/{}], Step [{}/{}], Loss: {:.4f}' .format(epoch + 1, num_epochs, i + 1, total_step, loss.item())) pass pass pass train(num_epochs, model, loaders) Output: Evaluate the model