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config_hmc.txt
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config_hmc.txt
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[model]
base: 'MLP' # network: [ Classifier_BBB, Classifier_ConvBBB]
early_stopping: True # early stopping [True/False]
[priors]
prior: 'Laplacian' # Gaussian, GaussianMixture, Cauchy, Laplacian, LaplaceMixture
prior_init: '0, 1' #initialisation of prior '5e-1, 1e-1, 1e-3', '0, 1e-2' '0.75, 1, 0.0009' '0.75, 1, 1e-3'
[data]
dataset: 'MNIST' # dataset class [MNIST, MBFRConfident, MBFRConf+Uncert]
datadir: './dataMNIST' # /dataMiraBest or /dataMNIST name of directory to download data into - no . in './' if using pathlib
datamean: 0.1307 # mean for normalisation MNIST[0.1307, 0.3081], MiraBest[0.0031, 0.0350]
datastd: 0.3081 # stdev for normalisation
augment: False #True/False. No augmentation at test time
[training]
batch_size: 128 # [128, 50]
frac_val: 0.2 # for train:val split
imsize: 28 # pixels on side of image [28, 150]
hidden_size: 64 # number of hidden units per layer - mlp
num_classes: 10 # number of target classes [10, 2]
[output]
filename_uncert: './mirabest_uncert.csv'
test_data: 'MBFRConfident' #{'MBFRConfident', 'MBFRUncertain', 'MBHybrid'} for uncert calc
pruning: 'Fisher' #{'Unpruned', 'SNR', 'Fisher'}