@ -395,11 +395,6 @@ def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, data_root, log
previous_mean_loss = 0
print("Mean loss of {} elements".format(size))
ititial_step = hypernetwork.step or 0
if ititial_step > steps:
return hypernetwork, filename
weights = hypernetwork.weights()
for weight in weights:
weight.requires_grad = True