Deep Convolutional Neural Networks (AlexNet)

http://d2l.ai/chapter_convolutional-modern/alexnet.html

lr, num_epochs = 0.01, 10
d2l.train_ch6(net, train_iter, test_iter, num_epochs, lr)

training on cpu


no other results?
no pic?


so slow?

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

@Nish
I have known it. But 12 hours will disconnect. :mask:
And you can find why colab is not so friendly in my discussion:
http://d2l.ai/chapter_appendix-tools-for-deep-learning/colab.html

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
Thanks.

Hi!!
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)
Any Suggestion??