aboutsummaryrefslogtreecommitdiff
path: root/modules/hypernetworks
diff options
context:
space:
mode:
Diffstat (limited to 'modules/hypernetworks')
-rw-r--r--modules/hypernetworks/hypernetwork.py6
1 files changed, 3 insertions, 3 deletions
diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py
index 0128419b..4541af18 100644
--- a/modules/hypernetworks/hypernetwork.py
+++ b/modules/hypernetworks/hypernetwork.py
@@ -435,8 +435,8 @@ def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, gradient_step,
optimizer_name = hypernetwork.optimizer_name
else:
print(f"Optimizer type {hypernetwork.optimizer_name} is not defined!")
- optimizer = torch.optim.AdamW(params=weights, lr=scheduler.learn_rate)
- optimizer_name = 'AdamW'
+ 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:
@@ -582,7 +582,7 @@ def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, gradient_step,
shared.state.textinfo = f"""
<p>
Loss: {loss_step:.7f}<br/>
-Step: {hypernetwork.step}<br/>
+Step: {steps_done}<br/>
Last prompt: {html.escape(batch.cond_text[0])}<br/>
Last saved hypernetwork: {html.escape(last_saved_file)}<br/>
Last saved image: {html.escape(last_saved_image)}<br/>