>I'm still not sure what was stopping the inner
>loop from working earlier - but removing the redundancy in "j=0" and so
>on seems to have solved it.
Call me crazy, but be careful when programming python in different text
editors and in general, ie cutting and pasting, tabing and spacing.
Loops ca
>I'm afraid you're using terminology (and abbreviations!) that I can't follow.
>Let me try to restate what's going on and you can correct me as I screw up. You
>have a neural net that has 80 output units. You have 25000 observations that
>you
>are using to train the neural net. Each observation ve
> If I run it from the shell (unix) I get: Segmentation fault and see a
> core dump in my processes. If I run it in the python shell I get as
> above:
> File "D:\Python24\Lib\site-packages\numpy\core\defmatrix.py", line
> 149, in
That's a Window's path... Does Windows even make full use o
Im using rprop (not dependent on error function in this case ie.
standard rprop vs. irprop or arprop) for an MLP tanh, sigmod nnet as
part of a hybrid model. I guess I was using a little Matlab thought
when I wrote the SSE funtion. My batches are about 25,000 x 80 so my
absolute error (diff betwee
Using large arrays of data I found it is MUCH faster to cast arrays to
matricies and then multiply the two matricies togther
(scipy.matrix(ARRAY1)*scipy.matrix(ARRAY2)) in order to do a matrix
multipy of two arrays vs. scipy.matrixmultipy(ARRAY1, ARRAY2).
Are there any logical/efficiency errors w
Good point. Finding the SSE using an absolute error matrix of (25000 x
1) is insane. I pulled out the error function (for now) and I'm back
in business. Thanks for all the great advise.
--
http://mail.python.org/mailman/listinfo/python-list
If I run it from the shell (unix) I get: Segmentation fault and see a
core dump in my processes. If I run it in the python shell I get as
above:
File "D:\Python24\Lib\site-packages\numpy\core\defmatrix.py", line
149, in
__mul__
return N.dot(self, other)
MemoryError
I your experience as one of
I'm running operations large arrays of floats, approx 25,000 x 80.
Python (scipy) does not seem to come close to using 4GB of wired mem,
but segments at around a gig. Everything works fine on smaller batches
of data around 10,000 x 80 and uses a max of ~600mb of mem. Any Ideas?
Is this just too m
Ok, so I found out that even though mylist[] and all objects in it were
fine ie id(mylist[i]) != id(mylist[all others]) what was happening is
that during a reproduction function a shallow copies were being made
making all offspring (genetic algorithm) have different
id(mylist[0..n]), however the ac
Ok, so I found out that even though mylist[] and all objects in it were
fine ie id(mylist[i]) != id(mylist[all others]) what was happening is
that during a reproduction function a shallow copies were being made
making all offspring (genetic algorithm) have different
id(mylist[0..n]), however the ac
Ok, so I found out that even though mylist[] and all objects in it were
fine ie id(mylist[i]) != id(mylist[all others]) what was happening is
that during a reproduction function a shallow copies were being made
making all offspring (genetic algorithm) have different
id(mylist[0..n]), however the ac
Ok, so I found out that even though mylist[] and all objects in it were
fine ie id(mylist[i]) != id(mylist[all others]) what was happening is
that during a reproduction function a shallow copies were being made
making all offspring (genetic algorithm) have different
id(mylist[0..n]), however the ac
Ok, so I found out that even though mylist[] and all objects in it were
fine ie id(mylist[i]) != id(mylist[all others]) what was happening is
that during a reproduction function a shallow copies were being made
making all offspring (genetic algorithm) have different
id(mylist[0..n]), however the ac
The Problem (very basic, but strange):
I have a list holding a population of objects, each object has 5 vars
and appropriate funtions to get or modify the vars. When objects in
the list have identical vars (like all = 5 for var "a" and all = 10 for
var "b" across all vars and objects) and i chang
14 matches
Mail list logo
