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config.py
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config.py
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import os
''' Hyperparameter '''
latent_variable_dim = 40 # The output dimension of encoder, and the dimention of predefined class centriods
BatchSize = 4096
base_lr = 0.1
epoches = 120 # max epochs
lr_step = 30
''' model '''
model_path = r'./model/MNIST' # path to save model
mean_var_path = r'./mean_var_pkl' # path to save mean and covariance of eacg class
reconstruction_path = r"./reconstruction/MNIST" # path to save reconstruction results
recon_flag = True # whether test reconstruction or not
generate_samples_path = r"./generate_samples/MNIST" # path to save generate samples
generate_flag = True # whether generate samples or not
''' PEDCC setting '''
class_num=10 # The number of class centroids
PEDCC_root=r"./ui_pkl/"
PEDCC_ui=os.path.join(PEDCC_root,str(class_num)+"_"+str(latent_variable_dim)+".pkl")