Merge branch 'main' into ema_model

Author: SahilCarterr

examples/advanced_diffusion_training/train_dreambooth_lora_flux_advanced.py

@@ -1650,6 +1650,8 @@ def save_model_hook(models, weights, output_dir):
                 elif isinstance(model, type(unwrap_model(text_encoder_one))):
                     if args.train_text_encoder:  # when --train_text_encoder_ti we don't save the layers
                         text_encoder_one_lora_layers_to_save = get_peft_model_state_dict(model)
+                elif isinstance(model, type(unwrap_model(text_encoder_two))):
+                    pass  # when --train_text_encoder_ti and --enable_t5_ti we don't save the layers
                 else:
                     raise ValueError(f"unexpected save model: {model.__class__}")
 

examples/dreambooth/train_dreambooth_flux.py

@@ -1288,7 +1288,6 @@ def load_model_hook(models, input_dir):
             # changes the learning rate of text_encoder_parameters_one and text_encoder_parameters_two to be
             # --learning_rate
             params_to_optimize[1]["lr"] = args.learning_rate
-            params_to_optimize[2]["lr"] = args.learning_rate
 
         optimizer = optimizer_class(
             params_to_optimize,

examples/dreambooth/train_dreambooth_lora_flux.py

@@ -1370,7 +1370,6 @@ def load_model_hook(models, input_dir):
             # changes the learning rate of text_encoder_parameters_one and text_encoder_parameters_two to be
             # --learning_rate
             params_to_optimize[1]["lr"] = args.learning_rate
-            params_to_optimize[2]["lr"] = args.learning_rate
 
         optimizer = optimizer_class(
             params_to_optimize,