numpy-discussion

[Numpy-discussion] Using dotblas

[Fernando P. <Fer...@co...>]

Hi all,

I've built NumPy 23.1 with dotblas enabled, and as per the readme I'm starting 
to pepper my code with things like:

# External packages
import Numeric as N

# Use BLAS-optimized versions when available
try:
     import dotblas
     N.dot = dotblas._dotblas.matrixproduct
     N.multiarray.innerproduct = dotblas._dotblas.innerproduct
except ImportError:
     print '*** dotblas not available, using regular Numeric functions'


I wonder if this is really necessary, and if so, why.

Is there any reason _not_ to use the dotblas versions when available?  If not, 
shouldn't Numeric itself pick them up internally so that it always exposes the 
fastest possible version?

I can always send in a patch to do this ( a trivial 5-liner like the above 
code), but I may just be missing something, as it seems too obvious not to be 
already the default.

Regards,

f.

Re: [Numpy-discussion] Using dotblas

[Fernando P. <Fer...@co...>]

Robert Kern wrote:

> Check the last few lines of Numeric.py .

Argh.  Could've saved myself the embarrasment :)

In my meager defense, the README.html file for doblas then needs to be 
updated, since that's what I followed:

# quote

Finally, if you don't know whether dotblas will be available on all the 
machines where you whish to run your code, you can simply use a try-except 
statement like this:

import Numeric
try:
     import dotblas
     Numeric.dot = dotblas.dot
  if we can't find the fast dotblas, just use the normal dot
except ImportError: pass

# /quote


Thanks, though.  I'll clean up my codes

f