Update

3 files changed, 11 insertions, 5 deletions

diff --git a/training/strategy/dreambooth.py b/training/strategy/dreambooth.py
index 0286673..695174a 100644
--- a/training/strategy/dreambooth.py
+++ b/training/strategy/dreambooth.py
@@ -106,7 +106,7 @@ def dreambooth_strategy_callbacks(
         with ema_context():
             yield
 
-    def on_before_optimize(lr: float, epoch: int):
+    def on_before_optimize(epoch: int):
         params_to_clip = [unet.parameters()]
         if epoch < train_text_encoder_epochs:
             params_to_clip.append(text_encoder.parameters())
diff --git a/training/strategy/lora.py b/training/strategy/lora.py
index 912ff26..89269c0 100644
--- a/training/strategy/lora.py
+++ b/training/strategy/lora.py
@@ -79,10 +79,14 @@ def lora_strategy_callbacks(
         tokenizer.eval()
         yield
 
-    def on_before_optimize(lr: float, epoch: int):
+    def on_before_optimize(epoch: int):
         if not pti_mode:
             accelerator.clip_grad_norm_(
-                itertools.chain(unet.parameters(), text_encoder.parameters()),
+                itertools.chain(
+                    unet.parameters(),
+                    text_encoder.text_model.encoder.parameters(),
+                    text_encoder.text_model.final_layer_norm.parameters(),
+                ),
                 max_grad_norm
             )
 
@@ -95,7 +99,9 @@ def lora_strategy_callbacks(
             return torch.stack(params) if len(params) != 0 else None
 
     @torch.no_grad()
-    def on_after_optimize(w, lr: float):
+    def on_after_optimize(w, lrs: dict[str, float]):
+        lr = lrs["emb"] or lrs["0"]
+
         if use_emb_decay and w is not None:
             lambda_ = emb_decay * lr
 
diff --git a/training/strategy/ti.py b/training/strategy/ti.py
index 6a637c3..d735dac 100644
--- a/training/strategy/ti.py
+++ b/training/strategy/ti.py
@@ -104,7 +104,7 @@ def textual_inversion_strategy_callbacks(
             yield
 
     @torch.no_grad()
-    def on_before_optimize(lr: float, epoch: int):
+    def on_before_optimize(epoch: int):
         if use_emb_decay:
             params = [
                 p