/
config_augment.txt
39 lines (34 loc) · 1.65 KB
/
config_augment.txt
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[model]
base: 'Classifier_ConvBBB' # network: [ Classifier_BBB, Classifier_ConvBBB]
early_stopping: True # early stopping [True/False]
conditioner: "nonlinear"
[priors]
prior: 'Gaussian' # Gaussian, GaussianMixture, Cauchy, Laplacian, LaplaceMixture
prior_init: '0, 1e-1' #initialisation of prior '5e-1, 1e-1, 1e-3', '0, 1e-2' '0.75, 1, 0.0009' '0.75, 1, 1e-3''0, 1'
[data]
dataset: 'MBFRConf' # dataset class [MNIST, MBFRConfident, MBFRConf+Uncert]
datadir: './dataMiraBest' # name of directory to download data into - no . in './' if using pathlib
datamean: 0.0031 # mean for normalisation MNIST[0.1307, 0.3081], MiraBest[0.0031, 0.0350]
datastd: 0.0350 # stdev for normalisation
augment: True #True/False. No augmentation at test time.
[training]
seed: 122
seed_data: 14
batch_size: 50 # [128, 50]
frac_val:0.2 # for train:val split
epochs: 1500 # total number of epochs
imsize: 150 # pixels on side of image [28, 150]
hidden_size: 800 # number of hidden units per layer - mlp
num_classes: 2 # number of target classes [10, 2]
lr0: 5e-5 # initial learning rate with lr scheduler
#optimizer: 'SGD'
momentum: 0.9
decay: 1e-5
reduction: "sum"
burnin: None
temp: 1e-2 #[00: 1, 0:5e-1, 1:1e-1, 2:5e-2, 3:1e-2, 4:5e-3, 5:1e-3, 6:5e-4, 7:1e-4, 8: 5e-5, 9:1e-5, 10:2e-1, 11:2e-2,12:2e-3, 13:2e-4 14:2e-5]
kernel_size: 5
pac: False
[output]
test_data: 'MBFRConfident' #{'MBFRConfident', 'MBFRUncertain', 'MBHybrid'} for uncert calc
path_out: '/share/nas2/dmohan/bbb/RadioGalaxies-BBB/exps_final/nonlinear_shuffle/gaussian/augment/vi_'