jens
7b34529b24
git-svn-id: http://moon:8086/svn/matlab/trunk@91 801c6759-fa7c-4059-a304-17956f83a07c
38 lines
1.5 KiB
Matlab
38 lines
1.5 KiB
Matlab
function [params] = stack2params(stack)
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% Converts a "stack" structure into a flattened parameter vector and also
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% stores the network configuration. This is useful when working with
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% optimization toolboxes such as minFunc.
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%
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% [params, netconfig] = stack2params(stack)
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%
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% stack - the stack structure, where stack{1}.w = weights of first layer
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% stack{1}.b = weights of first layer
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% stack{2}.w = weights of second layer
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% stack{2}.b = weights of second layer
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% ... etc.
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% This is a non-standard version of the code to support conv nets
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% it allows higher layers to have window sizes >= 1 of the previous layer
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% If using a gpu pass inParams as your gpu datatype
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% Setup the compressed param vector
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params = [];
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for d = 1:numel(stack)
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% This can be optimized. But since our stacks are relatively short, it
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% is okay
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params = [params ; stack{d}.W(:) ; stack{d}.b(:) ];
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% Check that stack is of the correct form
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assert(size(stack{d}.W, 1) == size(stack{d}.b, 1), ...
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['The bias should be a *column* vector of ' ...
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int2str(size(stack{d}.W, 1)) 'x1']);
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% no layer size constrain with conv nets
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if d < numel(stack)
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assert(mod(size(stack{d+1}.W, 2), size(stack{d}.W, 1)) == 0, ...
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['The adjacent layers L' int2str(d) ' and L' int2str(d+1) ...
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' should have matching sizes.']);
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end
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end
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end |