lr, num_epochs = 0.01, 10 d2l.train_ch6(net, train_iter, test_iter, num_epochs, lr)
training on cpu
no other results?
Please use a GPU for deep nets. A CPU could be 100 times slower than a GPU.
For the AlexNet on Fashion-MNIST, a GPU takes ~ 20 seconds per epoch, which means a CPU would take 2000 seconds ~ 30 minutes.
@ChenYangyao thank for your reply. I don’t have gpus. I’m using colab for learning.
And now I can’t find any exercitations because of my finance undergraduate diploma.
@StevenJokes I think colab lets you use a GPU for free? Tools -> Change runtime type -> choose ‘GPU’ under Hardware Accelerator
I have known it. But 12 hours will disconnect.
And you can find why colab is not so friendly in my discussion:
And there is an issue of python 3.6:
aha, I see. maybe you can try the kaggle.com free kernel? It allows 30 hours a week of GPU use for its contests I think.
I’ll try. @Nish
If I change Dataset then how do I change the below statement like dataset of Animals?
train_iter, test_iter = d2l.load_data_fashion_mnist(batch_size, resize=224)