New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Working with float32 data #5776

Open
elanmart opened this Issue Nov 10, 2015 · 1 comment

Comments

Projects
None yet
2 participants
@elanmart

elanmart commented Nov 10, 2015

Hi,

I was wondreing why sklearn does not allow me to specify the dtype I'd like to use.

I'm working with rather large dataset, which fits into my RAM as float32, but when I'm trying to train a simple SGD on it, the model tries to copy my data into float64, causing MemoryError.

I can change this in my local sklearn build, but I guess there is a good reason why this is not a free parameter?

@amueller

This comment has been minimized.

Show comment
Hide comment
@amueller

amueller Nov 12, 2015

Member

PR welcome ;)
It would be great to have both 32 and 64 bit everywhere, I think.
This means using fused types everywhere in Cython.

One of the reasons not to do that was the explosion in the generated C code, but I think with #5492 we need to be somewhat less careful about that.

Member

amueller commented Nov 12, 2015

PR welcome ;)
It would be great to have both 32 and 64 bit everywhere, I think.
This means using fused types everywhere in Cython.

One of the reasons not to do that was the explosion in the generated C code, but I think with #5492 we need to be somewhat less careful about that.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment