[paths]
mri_data = '/data/data_wnx1/_Data/AlzheimersDL/CNN+RNN-2class-1cnn+data/PET_volumes_customtemplate_float32/'
xls_data = '/export/home/nschense/alzheimers/alzheimers_nn/LP_ADNIMERGE.csv'

#CHANGE THESE BEFORE RUNNING
model_output = '/export/home/nschense/alzheimers/alzheimers_nn/saved_models/'

[training]
device = 'cuda:1'
runs = 10
max_epochs = 10

[dataset]
validation_split = 0.4 #Splits the dataset into the train and validation/test set, 50% each for validation and test
#|---TEST---|---VALIDATION---|---TRAIN---|
#|splt*0.5  | split*0.5      | 1-split   |

[model]
name = 'cnn-10x10'
image_channels = 1
clin_data_channels = 2

[hyperparameters]
batch_size = 32
learning_rate = 0.0001
droprate = 0.5

[operation]
silent = false

[ensemble]
name = 'cnn-10x10'
prune_threshold = 0.0 # Any models with accuracy below this threshold will be pruned, set to 0 to disable pruning