[mlpack] disadvantages of using tuple as framework for neural network

[Shangtong Zhang]

Hi,


I implement cnn based on current framework of NN.
I meet some problem when I try to test my cnn on mnist dataset.
To do classification on mnist dataset, I try to realize LeNet5,
but LeNet5 has so many connections.
In one layer, there are 6 feature maps, and in next layer there are 16 feature maps.
And an implementation in theano connects these two layers use full connection.
This means there are 6 * 16 = 96 connections,
then I need to instantiates 96 class of ConnectionType and store them in a tuple.
so I need to get a tuple like c1, c2, c3, ………, c96, it’s too large that I can’t write it manually.
But it seems I can't generate it automatically
or I need some very complicate c++ technique to do this.
http://stackoverflow.com/questions/28410697/c-convert-vector-to-tuple

So I think tuple isn't appropriate for this work.
I suggest that we use vector to replace tuple and have a base class for all ConnectionType class.
In this way, ConnectionTraits may also be not used.




Shangtong Zhang,
Third Year Undergraduate,
School of Computer Science,
Fudan University, China.
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