From f05133b2ea37c6e2d3f151c42555f0d97b8f25e0 Mon Sep 17 00:00:00 2001 From: Diego Manzanas Date: Tue, 20 Feb 2024 12:07:14 -0600 Subject: [PATCH] Delete debugging files, adversarial attacks were incorrect --- .../debugInconsistenciesNodulemnist.m | 56 ----- .../NN/medmnist/process_debugNodule.m | 78 ------- ...ication_multipleAttacks_adrenalmnist3d.mat | Bin 29097 -> 0 bytes ...cation_multipleAttacks_fracturemnist3d.mat | Bin 29223 -> 0 bytes ...fication_multipleAttacks_nodulemnist3d.mat | Bin 29533 -> 0 bytes ...on_multipleAttacks_nodulemnist3d_debug.mat | Bin 50976 -> 0 bytes ...ification_multipleAttacks_organmnist3d.mat | Bin 29098 -> 0 bytes ...ication_multipleAttacks_synapsemnist3d.mat | Bin 28129 -> 0 bytes ...fication_multipleAttacks_vesselmnist3d.mat | Bin 28700 -> 0 bytes .../examples/NN/medmnist/verify_medmnist3d.m | 16 +- .../NN/medmnist/verify_medmnist3d_extraInfo.m | 192 ------------------ 11 files changed, 8 insertions(+), 334 deletions(-) delete mode 100644 code/nnv/examples/NN/medmnist/debugInconsistenciesNodulemnist.m delete mode 100644 code/nnv/examples/NN/medmnist/process_debugNodule.m delete mode 100644 code/nnv/examples/NN/medmnist/results/verification_multipleAttacks_adrenalmnist3d.mat delete mode 100644 code/nnv/examples/NN/medmnist/results/verification_multipleAttacks_fracturemnist3d.mat delete mode 100644 code/nnv/examples/NN/medmnist/results/verification_multipleAttacks_nodulemnist3d.mat delete mode 100644 code/nnv/examples/NN/medmnist/results/verification_multipleAttacks_nodulemnist3d_debug.mat delete mode 100644 code/nnv/examples/NN/medmnist/results/verification_multipleAttacks_organmnist3d.mat delete mode 100644 code/nnv/examples/NN/medmnist/results/verification_multipleAttacks_synapsemnist3d.mat delete mode 100644 code/nnv/examples/NN/medmnist/results/verification_multipleAttacks_vesselmnist3d.mat delete mode 100644 code/nnv/examples/NN/medmnist/verify_medmnist3d_extraInfo.m diff --git a/code/nnv/examples/NN/medmnist/debugInconsistenciesNodulemnist.m b/code/nnv/examples/NN/medmnist/debugInconsistenciesNodulemnist.m deleted file mode 100644 index 226053000d..0000000000 --- a/code/nnv/examples/NN/medmnist/debugInconsistenciesNodulemnist.m +++ /dev/null @@ -1,56 +0,0 @@ -%% Debug inconsistencies for nodulemnist verification results - -% get current dataset to verify -% dataset = medmnist_path + datasets(i).name; -dataset = "data/mat_files/nodulemnist3d.mat"; - - -disp("Begin verification of nodulemnist3d"); - -% Load data -load(dataset); - -% data to verify (test set) -test_images = permute(test_images, [2 3 4 5 1]); -test_labels = test_labels + 1; - -% load network -load("models/model_nodulemnist3d.mat"); -matlabNet = net; -net = matlab2nnv(net); - -% adversarial attacks -names = ["dark"]; -max_pixels = [50;100;200]; -noise_vals = [1]; - -% select volumes to verify -N = 200; -inputs = test_images(:,:,:,:,1:N); -targets = test_labels(1:N); - -% Initialize results -results = zeros(2, N, length(names), length(max_pixels), length(noise_vals)); -outputSets = cell(3,1); - -% verify volumes with all attack combos -for a=1:length(names) - for b=1:length(max_pixels) - for c=1:length(noise_vals) - % create attack from variables - adv_attack = struct; - adv_attack.Name = names(a); - adv_attack.max_pixels = max_pixels(b); - adv_attack.noise_de = noise_vals(c); - adv_attack.threshold = 150; - - % Compute verification - [outputSets{b}, results(:,:,a,b,c)] = verify_medmnist3d_extraInfo(net, inputs, targets, adv_attack); - end - end -end - -% save results -save("results/verification_multipleAttacks_nodulemnist3d_debug.mat", "results", "outputSets", "-v7.3"); - - diff --git a/code/nnv/examples/NN/medmnist/process_debugNodule.m b/code/nnv/examples/NN/medmnist/process_debugNodule.m deleted file mode 100644 index 9d982cd0c8..0000000000 --- a/code/nnv/examples/NN/medmnist/process_debugNodule.m +++ /dev/null @@ -1,78 +0,0 @@ -%% Let's take a look into this - -load('results/verification_multipleAttacks_nodulemnist3d_debug.mat'); - -% Only get verification results -results = results(1,:,:,:); -results = squeeze(results); -results = results'; -outputSets = outputSets'; - -% first discrepancy (5) -R1a = outputSets{1}; -R1 = R1a{5}{end}; -[lb1, ub1] = R1.getRanges; -R2a = outputSets{2}; -R2 = R2a{5}{end}; -[lb2, ub2] = R2.getRanges; -R3a = outputSets{3}; -R3 = R3a{5}{end}; -[lb3, ub3] = R3.getRanges; - -% The ranges are different, but the 3 bounds should be containing the other -% 2... We are probably doing somethig wrong, either when defining the input -% set, or something with the reachability (most likely the first...) - -% Let's visualize the output sets (exact) -figure; -Star.plot(R1,'r'); -figure; -Star.plot(R2,'r'); -figure; -Star.plot(R3,'r'); - - -% Let's see what the differences in the layer-by-layer sets are... - -% Layer 1 -r1 = R1a{5}{1}; -r2 = R2a{5}{1}; -r3 = R3a{5}{1}; - -rs1 = r1.toStar; -rs2 = r2.toStar; -rs3 = r3.toStar; - -% The next 3 statements should return true -% bool1 = rs1.isSubSet(rs2); -% bool2 = rs1.isSubSet(rs3); -% bool3 = rs2.isSubSet(rs3); -% this takes too long as stars are high dimensional (polyhedron not very -% efficient) - -% get ranges (overapprox) and see if the smaller bounds are within te -% larger ones (rs1 < rs2 < rs3) -[rs1L, rs1U] = rs1.estimateRanges; -[rs2L, rs2U] = rs2.estimateRanges; -[rs3L, rs3U] = rs3.estimateRanges; - -b1L = all(rs1L >= rs2L); -b1U = all(rs1U <= rs2U); -b2L = all(rs1L >= rs3L); -b2U = all(rs1U <= rs3U); -b3L = all(rs2L >= rs3L); -b3U = all(rs2U <= rs3U); - -% Lower bounds seem fine, but ot the upper bounds... - -% where do these assertions fail? -u1 = find(rs1U > rs2U); -u2 = find(rs1U > rs3U); -u3 = find(rs2U > rs3U); - -% these fail on all the perturbed pixels... -uu11 = rs1L(u1); -uu12 = rs2L(u1); - -% we are not defining the constraints on the input set correctly, some -% pixel values are outside the valid ranges... diff --git a/code/nnv/examples/NN/medmnist/results/verification_multipleAttacks_adrenalmnist3d.mat b/code/nnv/examples/NN/medmnist/results/verification_multipleAttacks_adrenalmnist3d.mat deleted file mode 100644 index 9df247df8bb1efd75faa379dd699450a6b50852c..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 29097 zcma%?X*3jW*#FBC5|drl$P$IJ?-N1@AxW08BuP?sh8atC*|)Nc$i9;;j6M6lZ!@y* zgTa{n`TfuTJnx_D)&251=Q{Vfzu(XGy$v;9KG)E^D<}EruA#r=#tg@`aUFk>C 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Ensure number of volumes are in dimension 5 of input array.") - end - - % Initialize variables - results = zeros(2,N); % 1-> verify result, 2-> verify time - - % Define reachability parameters - reachOptions = struct; - reachOptions.reachMethod = 'approx-star'; - % reachOptions.dis_opt = 'display'; - - outputSets = cell(N,1); - - % Evaluate all images - for i = 1:N - - % print progress - % if ~mod(i, 3) - disp("Verifying input volume " + string(i) + " of " + string(N) + "..."); - % end - - % Create set of volume images - vol = inputs(:,:,:,:,i); - % Choose attack - if strcmp(attack.Name,'linf') - I = L_inf_attack(vol, epsilon, max_pixels, max_value, min_value); - elseif strcmp(attack.Name, 'dark') - I = dark_attack(vol, max_pixels, threshold, noise_disturbance); - elseif strcmp(attack.Name, 'bright') - I = bright_attack(vol, max_pixels, threshold, noise_disturbance); - end - - t = tic; % start timer - - % Check for missclassification - vol = single(vol); - y = net.evaluate(vol); - [~, y] = max(y); - if y ~= targets(i) - results(1, i) = -1; % missclassified - results(2,i) = toc(t); - continue; - end - - % Check for falsification with upper and lower bounds - if strcmp(attack.Name,'linf') - yUpper = net.evaluate(I.vol_ub); - [~, yUpper] = max(yUpper); - yLower = net.evaluate(I.vol_lb); - [~, yLower] = max(yLower); - if yUpper ~= targets(i) || yLower ~= targets(i) - results(1,i) = 0; % not robust - results(2,i) = toc(t); - continue; - end - else - % disp("TODO: Add some sampling from the initial set to check for falsification.") - end - - % Compute reachability for verification - results(1,i) = net.verify_robustness(I, reachOptions, targets(i)); - results(2,i) = toc(t); - outputSets{i} = net.reachSet; - - end - -end - - -%% Helper Functions -% Return a VolumeStar of an Linf attack -function I = L_inf_attack(vol, epsilon, max_pixels, max_value, min_value) - volSize = size(vol); - n = numel(vol); - idxs = randperm(n, max_pixels); % select some random pixels from the input volume - disturbance = zeros(volSize, "like", vol); % initialize array (mostly zeros) - disturbance(idxs) = epsilon; % change to {epsilon} the randomly selected pixels - lb = max(vol - disturbance, min_value); - ub = min(vol + disturbance, max_value); - I = VolumeStar(single(lb), single(ub)); % default: single (assume onnx input models) -end - -% Return a VolumeStar of a drkening attack on a few pixels -function I = dark_attack(vol, max_pixels, threshold, noise_disturbance) - - % Initialize vars - ct = 0; % keep track of pixels modified - flag = 0; % determine when to stop modifying pixels - vol = single(vol); - at_vol = vol; - - % Create darkening attack - for i=1:size(vol,1) - for j=1:size(vol,2) - for k=1:size(vol,3) - if vol(i,j,k) > threshold - at_vol(i,j,k) = 0; - ct = ct + 1; - if ct >= max_pixels - flag = 1; - break; - end - end - end - if flag == 1 - break - end - end - if flag == 1 - break; - end - end - - % Define input set as VolumeStar - dif_vol = vol - at_vol; - noise = -dif_vol; - V(:,:,:,:,1) = vol; % center of set - V(:,:,:,:,2) = noise; % basis vectors - C = [1; -1]; % constraints - d = [255; noise_disturbance-255]; - I = VolumeStar(V, C, d, 255-noise_disturbance, 255); % input set - -end - -% Return a VolumeStar of a brightening attack on a few pixels -function I = bright_attack(vol, max_pixels, threshold, noise_disturbance) - - % Initialize vars - ct = 0; % keep track of pixels modified - flag = 0; % determine when to stop modifying pixels - vol = single(vol); - at_vol = vol; - - % Create brightening attack - for i=1:size(vol,1) - for j=1:size(vol,2) - for k=1:size(vol,3) - if vol(i,j,k) < threshold - at_vol(i,j,k) = 1; - ct = ct + 1; - if ct >= max_pixels - flag = 1; - break; - end - end - end - if flag == 1 - break - end - end - if flag == 1 - break; - end - end - - % Define input set as VolumeStar - dif_vol = vol - at_vol; - noise = -dif_vol; - V(:,:,:,:,1) = vol; % center of set - V(:,:,:,:,2) = noise; % basis vectors - C = [1; -1]; % constraints - d = [255; noise_disturbance-255]; % constraints - I = VolumeStar(V, C, d, 255-noise_disturbance, 255); % input set -end