Re: Performance of XSLT in a neural network applicatio

I have to say that your conclusion doesn't follow logically from the evidence:
the fact that you failed to do something doesn't mean that it can't be done.
Furthermore, it's not safe to generalise properties of one implementation to
assume that they must be true of all possible implementations.

Nevertheless it's probably true to say that neither the XSLT language nor its
implementations are particularly designed for this kind of task. Remember the
notorious sentence at the start of the XSLT 1.0 specification: "XSLT is not
intended as a completely general-purpose XML transformation language". I've
always thought that was a rather odd thing to say, but if it said "XSLT is not
intended as a completely general-purpose programming language", then few would
quarrel.

Michael Kay
Saxonica



> On 22 Aug 2020, at 14:21, Roger L Costello costello@xxxxxxxxx
<xsl-list-service@xxxxxxxxxxxxxxxxxxxxxx> wrote:
>
> Hi Folks,
>
> I used XSLT to implement a neural network that recognizes handwritten
digits.
>
> I have a small training and test data set consisting of 100 and 10 records,
respectively.
>
> I also have a large training and test data set consisting of 60,000 and
10,000 records, respectively
>
> Neural networks involve a lot of matrix operations.
>
> In my first implementation I stored the data in XML and the matrix
operations operated on XML.
>
> In my second implementation I removed all XML and exclusively used XSLT maps
and XSLT sequences.
>
> In my third implementation I used Python instead of XSLT.
>
> Here are the performance results:
>
-----------------------------------------------------------------------------
----------
> For the small training and test data set:
>
> First implementation (XML): 6 and one-half minutes
>
> Second implementation (maps, sequences): 28.7 seconds
>
> Python implementation: less than 1 second
>
-----------------------------------------------------------------------------
----------
> For the large training and test data set:
>
> First implementation (XML): more than 24 hours (I stopped it after it had
run for 24 hours)
>
> Second implementation (maps, sequences): 5 hours
>
> Python implementation: 30 seconds
>
-----------------------------------------------------------------------------
----------
> Conclusion: XSLT is not a viable language for creating neural networks.
>
> /Roger