rework the code to not use the walrus operator because colab's 3.7 does not support it

1 files changed, 5 insertions, 2 deletions

diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py
index 5ceed6ee..7f182712 100644
--- a/modules/hypernetworks/hypernetwork.py
+++ b/modules/hypernetworks/hypernetwork.py
@@ -429,13 +429,16 @@ def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, data_root, log
     weights = hypernetwork.weights()

     for weight in weights:

         weight.requires_grad = True

+

     # Here we use optimizer from saved HN, or we can specify as UI option.

-    if (optimizer_name := hypernetwork.optimizer_name) in optimizer_dict:

+    if hypernetwork.optimizer_name in optimizer_dict:

         optimizer = optimizer_dict[hypernetwork.optimizer_name](params=weights, lr=scheduler.learn_rate)

+        optimizer_name = hypernetwork.optimizer_name

     else:

-        print(f"Optimizer type {optimizer_name} is not defined!")

+        print(f"Optimizer type {hypernetwork.optimizer_name} is not defined!")

         optimizer = torch.optim.AdamW(params=weights, lr=scheduler.learn_rate)

         optimizer_name = 'AdamW'

+

     if hypernetwork.optimizer_state_dict:  # This line must be changed if Optimizer type can be different from saved optimizer.

         try:

             optimizer.load_state_dict(hypernetwork.optimizer_state_dict)