def get_model(model_str, placeholders, numView, num_features, num_nodes,
num_clusters):
#model = None
if model_str == 'arga_ae':
model = ARGA(placeholders, numView, num_features, num_clusters)
elif model_str == 'arga_vae':
model = ARVGA(placeholders, num_features, num_nodes, features_nonzero)
return model
def get_model(model_str, placeholders, num_features, num_nodes,
features_nonzero):
discriminator = Discriminator()
d_real = discriminator.construct(placeholders['real_distribution'])
model = None
if model_str == 'arga_ae':
model = ARGA(placeholders, num_features, features_nonzero)
elif model_str == 'arga_vae':
model = ARVGA(placeholders, num_features, num_nodes, features_nonzero)
return d_real, discriminator, model