Save fitcsvms running in parfor loop

Question

Aleksander Tyczynski 2019-8-5

0
链接

此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/474933-save-fitcsvms-running-in-parfor-loop

评论： Edric Ellis 2019-8-6

Hello,

I have a code which I am trying to get running faster, it has 3 fitcsvm function. To do so (I cannot use the GPU) I decided to perform a parfor loop.

However, I cannot use the save function and if the save is outside the loop a 'variable not found' error occurs

parfor i = 1:3
    if i == 1
    SVM_tt = fitcsvm(features_dt(:,1:10),features_dt(:,11),...
    'Standardize',true,'KernelFunction','RBF','BoxConstraint', tt_C, 'KernelScale',tt_sigma);
    end
    if i == 2
    SVM_bb = fitcsvm(features_bp(:,1:10),features_bp(:,11),...
    'Standardize',true,'KernelFunction','RBF','BoxConstraint', bb_C, 'KernelScale',bb_sigma);
    end
    if i == 3
    SVM_ss = fitcsvm(features_swa(:,1:10),features_swa(:,11),...
    'Standardize',true,'KernelFunction','RBF','BoxConstraint', ss_C, 'KernelScale',ss_sigma);
    end
end
save('SVM_dt.mat','SVM_tt');
save('SVM_bp.mat','SVM_bb');
save('SVM_swa.mat','SVM_ss');

Without the parfor loop the code wors perfectly fine.

Thank you,

0 个评论
显示 -2更早的评论隐藏 -2更早的评论

请先登录，再进行评论。

请先登录，再回答此问题。

Answer 1

Edric Ellis 2019-8-6

1
链接

此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/474933-save-fitcsvms-running-in-parfor-loop#answer_386425

Your outputs are not available after the parfor loop because the parfor variable classification considers them to be loop temporary variables. More details in the doc.

The simplest thing to do here is to make cell array inputs and outputs for your parfor loop.

% Step 1 - set up input cell arrays
features = {features_dt, features_bp, features_swa};
constraints = {tt_C, bb_C, ss_C};
scales = {tt_sigma, bb_sigma, ss_sigma};
parfor i = 1:3
    % Step 2 - access cell array contents in parfor loop
    f = features{i};
    SVM{i} = fitcsvm(f(:, 1:10), f(:, 11), ...
                     'Standardize',true,...
                     'KernelFunction','RBF',...
                     'BoxConstraint', constraints{i}, ...
                     'KernelScale',scales{i});
end
% Step 3 - split output cell array
[SVM_tt, SVM_bb, SVM_ss] = deal(SVM{:});

This works because parfor sees the "sliced" assignment into SVM, and knows that you are performing independent computations, and that it can therefore make the value available after the loop completes.