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Differences on cpu vs gpu computation
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Submodule cora
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| end | ||
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| toc(t); | ||
| net_app = net; | ||
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| %% Let's visualize the ranges for every possible output | ||
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| %% There are some discrepancies that we can observe here | ||
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| % Load network | ||
| mnist_model = load('../Tutorial/NN/MNIST/mnist_model_fc.mat'); | ||
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| % Create NNV model | ||
| net1 = matlab2nnv(mnist_model.net); | ||
| net2 = matlab2nnv(mnist_model.net); | ||
| net3 = matlab2nnv(mnist_model.net); | ||
| net4 = matlab2nnv(mnist_model.net); | ||
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| % Load data (no download necessary) | ||
| digitDatasetPath = fullfile(matlabroot,'toolbox','nnet','nndemos', ... | ||
| 'nndatasets','DigitDataset'); | ||
| % Images | ||
| imds = imageDatastore(digitDatasetPath, ... | ||
| 'IncludeSubfolders',true,'LabelSource','foldernames'); | ||
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| % Load first image in dataset | ||
| [img, fileInfo] = readimage(imds,600); | ||
| img = single(img); % change precision | ||
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| % Create input set | ||
| ones_ = ones(size(img), 'single'); | ||
| disturbance = 2 .* ones_; % one pixel value (images are not normalized, they get normalized in the ImageInputLayer) | ||
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| % However, we need to ensure the values are within the valid range for pixels ([0 255]) | ||
| lb_min = zeros(size(img)); % minimum allowed values for lower bound is 0 | ||
| ub_max = 255*ones(size(img)); % maximum allowed values for upper bound is 255 | ||
| lb_clip = max((img-disturbance),lb_min); | ||
| ub_clip = min((img+disturbance), ub_max); | ||
| IS = ImageStar(lb_clip, ub_clip); % this is the input set we will use | ||
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| % First, we need to define the reachability options | ||
| reachOptions = struct; % initialize | ||
| reachOptions.reachMethod = 'approx-star'; % using approxiate method | ||
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| %% Let's compute reach sets to evaluate the differences | ||
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| R1 = net1.reach(IS, reachOptions); | ||
| y1 = net1.evaluate(img); | ||
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| reachOptions.device = 'gpu'; | ||
| IS = ImageStar(lb_clip, ub_clip); % this is the input set we will use | ||
| R2 = net2.reach(IS, reachOptions); | ||
| y2 = net2.evaluate(gpuArray(img)); | ||
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| %% Now on double precision | ||
| reachOptions = struct; % initialize | ||
| reachOptions.reachMethod = 'approx-star'; % using approximate method | ||
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| IS = ImageStar(lb_clip, ub_clip); % this is the input set we will use | ||
| IS = IS.changeVarsPrecision('double'); | ||
| net3 = net3.changeParamsPrecision('double'); | ||
| R3 = net3.reach(IS, reachOptions); | ||
| y3 = net3.evaluate(double(img)); | ||
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| reachOptions.device = 'gpu'; | ||
| ImageStar(lb_clip, ub_clip); % this is the input set we will use | ||
| IS = IS.changeVarsPrecision('double'); | ||
| net4.changeParamsPrecision('double'); | ||
| R4 = net4.reach(IS, reachOptions); | ||
| y4 = net4.evaluate(gpuArray(double(img))); | ||
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| %% What do the output ranges look like for all of them? | ||
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| [lb1, ub1] = R1.estimateRanges; | ||
| [lb2, ub2] = R2.estimateRanges; | ||
| [lb3, ub3] = R3.estimateRanges; | ||
| [lb4, ub4] = R4.estimateRanges; | ||
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| outputRanges = [lb1; lb2; lb3; lb4; ub1; ub2; ub3; ub4]; | ||
| outputRanges = squeeze(outputRanges)' | ||
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| %% where did it go wrong? | ||
| %% Layer 1 | ||
| r1 = net1.reachSet{1}; | ||
| r2 = net2.reachSet{1}; | ||
| r3 = net3.reachSet{1}; | ||
| r4 = net4.reachSet{1}; | ||
| % | ||
| % [lb1, ub1] = r1.estimateRanges; | ||
| % [lb2, ub2] = r2.estimateRanges; | ||
| % [lb3, ub3] = r3.estimateRanges; | ||
| % [lb4, ub4] = r4.estimateRanges; | ||
| % | ||
| % layer1 = {lb1; lb2; lb3; lb4; ub1; ub2; ub3; ub4}; | ||
| % % layer1 = squeeze(layer1)'; | ||
| % | ||
| %% Layer 2 | ||
| r1 = net1.reachSet{2}; | ||
| r2 = net2.reachSet{2}; | ||
| r3 = net3.reachSet{2}; | ||
| r4 = net4.reachSet{2}; | ||
| % | ||
| % [lb1, ub1] = r1.estimateRanges; | ||
| % [lb2, ub2] = r2.estimateRanges; | ||
| % [lb3, ub3] = r3.estimateRanges; | ||
| % [lb4, ub4] = r4.estimateRanges; | ||
| % | ||
| % layer2 = {lb1; lb2; lb3; lb4; ub1; ub2; ub3; ub4}; | ||
| % | ||
| %% Layer 3 | ||
| r1 = net1.reachSet{3}; | ||
| r2 = net2.reachSet{3}; | ||
| r3 = net3.reachSet{3}; | ||
| r4 = net4.reachSet{3}; | ||
| % | ||
| % [lb1, ub1] = r1.estimateRanges; | ||
| % [lb2, ub2] = r2.estimateRanges; | ||
| % [lb3, ub3] = r3.estimateRanges; | ||
| % [lb4, ub4] = r4.estimateRanges; | ||
| % | ||
| % layer3 = {lb1; lb2; lb3; lb4; ub1; ub2; ub3; ub4}; | ||
| % | ||
| %% Layer 4 | ||
| r1 = net1.reachSet{4}; | ||
| r2 = net2.reachSet{4}; | ||
| r3 = net3.reachSet{4}; | ||
| r4 = net4.reachSet{4}; | ||
| % | ||
| % [lb1, ub1] = r1.estimateRanges; | ||
| % [lb2, ub2] = r2.estimateRanges; | ||
| % [lb3, ub3] = r3.estimateRanges; | ||
| % [lb4, ub4] = r4.estimateRanges; | ||
| % | ||
| % layer4 = {lb1; lb2; lb3; lb4; ub1; ub2; ub3; ub4}; | ||
| % | ||
| %% Layer 5 | ||
| r1 = net1.reachSet{5}; | ||
| r2 = net2.reachSet{5}; | ||
| r3 = net3.reachSet{5}; | ||
| r4 = net4.reachSet{5}; | ||
| % | ||
| % [lb1, ub1] = r1.estimateRanges; | ||
| % [lb2, ub2] = r2.estimateRanges; | ||
| % [lb3, ub3] = r3.estimateRanges; | ||
| % [lb4, ub4] = r4.estimateRanges; | ||
| % | ||
| % layer5 = {lb1; lb2; lb3; lb4; ub1; ub2; ub3; ub4}; | ||
| % | ||
| % | ||
| %% Layer 6 | ||
| r1 = net1.reachSet{6}; | ||
| r2 = net2.reachSet{6}; | ||
| r3 = net3.reachSet{6}; | ||
| r4 = net4.reachSet{6}; | ||
| % | ||
| % [lb1, ub1] = r1.estimateRanges; | ||
| % [lb2, ub2] = r2.estimateRanges; | ||
| % [lb3, ub3] = r3.estimateRanges; | ||
| % [lb4, ub4] = r4.estimateRanges; | ||
| % | ||
| % layer6 = {lb1; lb2; lb3; lb4; ub1; ub2; ub3; ub4}; | ||
| % | ||
| % | ||
| %% Layer 7 | ||
| r1 = net1.reachSet{7}; | ||
| r2 = net2.reachSet{7}; | ||
| r3 = net3.reachSet{7}; | ||
| r4 = net4.reachSet{7}; | ||
| % | ||
| % [lb1, ub1] = r1.estimateRanges; | ||
| % [lb2, ub2] = r2.estimateRanges; | ||
| % [lb3, ub3] = r3.estimateRanges; | ||
| % [lb4, ub4] = r4.estimateRanges; | ||
| % | ||
| % layer7 = {lb1; lb2; lb3; lb4; ub1; ub2; ub3; ub4}; | ||
| % | ||
| % | ||
| %% Layer 8 | ||
| r1 = net1.reachSet{8}; | ||
| r2 = net2.reachSet{8}; | ||
| r3 = net3.reachSet{8}; | ||
| r4 = net4.reachSet{8}; | ||
| % | ||
| % [lb1, ub1] = r1.estimateRanges; | ||
| % [lb2, ub2] = r2.estimateRanges; | ||
| % [lb3, ub3] = r3.estimateRanges; | ||
| % [lb4, ub4] = r4.estimateRanges; | ||
| % | ||
| % layer8 = {lb1; lb2; lb3; lb4; ub1; ub2; ub3; ub4}; | ||
| % | ||
| % | ||
| %% Layer 9 | ||
| r1 = net1.reachSet{9}; | ||
| r2 = net2.reachSet{9}; | ||
| r3 = net3.reachSet{9}; | ||
| r4 = net4.reachSet{9}; | ||
| % | ||
| % [lb1, ub1] = r1.estimateRanges; | ||
| % [lb2, ub2] = r2.estimateRanges; | ||
| % [lb3, ub3] = r3.estimateRanges; | ||
| % [lb4, ub4] = r4.estimateRanges; | ||
| % | ||
| % layer9 = {lb1; lb2; lb3; lb4; ub1; ub2; ub3; ub4}; | ||
| % | ||
| %% Layer 10 | ||
| r1 = net1.reachSet{10}; | ||
| r2 = net2.reachSet{10}; | ||
| r3 = net3.reachSet{10}; | ||
| r4 = net4.reachSet{10}; | ||
| % | ||
| % [lb1, ub1] = r1.estimateRanges; | ||
| % [lb2, ub2] = r2.estimateRanges; | ||
| % [lb3, ub3] = r3.estimateRanges; | ||
| % [lb4, ub4] = r4.estimateRanges; | ||
| % | ||
| % layer10 = {lb1; lb2; lb3; lb4; ub1; ub2; ub3; ub4}; | ||
| % | ||
| %% Layer 11 | ||
| r1 = net1.reachSet{11}; | ||
| r2 = net2.reachSet{11}; | ||
| r3 = net3.reachSet{11}; | ||
| r4 = net4.reachSet{11}; | ||
| % | ||
| % [lb1, ub1] = r1.estimateRanges; | ||
| % [lb2, ub2] = r2.estimateRanges; | ||
| % [lb3, ub3] = r3.estimateRanges; | ||
| % [lb4, ub4] = r4.estimateRanges; | ||
| % | ||
| % layer11 = {lb1; lb2; lb3; lb4; ub1; ub2; ub3; ub4}; |