Fix merge conflicts

1 files changed, 6 insertions, 11 deletions

diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py
index 65a584bb..207808ee 100644
--- a/modules/hypernetworks/hypernetwork.py
+++ b/modules/hypernetworks/hypernetwork.py
@@ -373,6 +373,12 @@ def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, data_root, log
 

     scheduler = LearnRateScheduler(learn_rate, steps, ititial_step)

     

+    clip_grad_mode_value = clip_grad_mode == "value"

+    clip_grad_mode_norm = clip_grad_mode == "norm"

+    clip_grad_enabled = clip_grad_mode_value or clip_grad_mode_norm

+    if clip_grad_enabled:

+        clip_grad_sched = LearnRateScheduler(clip_grad_value, steps, ititial_step, verbose=False)

+    

     # dataset loading may take a while, so input validations and early returns should be done before this

     shared.state.textinfo = f"Preparing dataset from {html.escape(data_root)}..."

     with torch.autocast("cuda"):

@@ -389,21 +395,10 @@ def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, data_root, log
     previous_mean_loss = 0

     print("Mean loss of {} elements".format(size))

 

-    last_saved_file = "<none>"

-    last_saved_image = "<none>"

-    forced_filename = "<none>"

-

     ititial_step = hypernetwork.step or 0

     if ititial_step > steps:

         return hypernetwork, filename

     

-    clip_grad_mode_value = clip_grad_mode == "value"

-    clip_grad_mode_norm = clip_grad_mode == "norm"

-    clip_grad_enabled = clip_grad_mode_value or clip_grad_mode_norm

-    if clip_grad_enabled:

-        clip_grad_sched = LearnRateScheduler(clip_grad_value, steps, ititial_step, verbose=False)

-

-    scheduler = LearnRateScheduler(learn_rate, steps, ititial_step)

 

     weights = hypernetwork.weights()

     for weight in weights: