add dadapt_adan and fix bug in decay steps for te

optimizer/optimizers.py

@@ -204,8 +204,8 @@ class EveryDreamOptimizer():
             lr_scheduler = get_scheduler(
                 te_config.get("lr_scheduler", args.lr_scheduler),
                 optimizer=self.optimizer_te,
-                num_warmup_steps=te_config.get("lr_warmup_steps", None),
-                num_training_steps=unet_config.get("lr_decay_steps", None) or unet_config["lr_decay_steps"]
+                num_warmup_steps=int(te_config.get("lr_warmup_steps", None)) or unet_config["lr_warmup_steps"],
+                num_training_steps=int(te_config.get("lr_decay_steps", None)) or unet_config["lr_decay_steps"]
             )
             ret_val.append(lr_scheduler)    
 
@@ -272,19 +272,23 @@ class EveryDreamOptimizer():
 
         default_lr = 1e-6
         curr_lr = args.lr
-        d0 = 1e-6 # dadapt 
+        d0 = 1e-6 # dadapt
         decouple = True # seems bad to turn off, dadapt_adam only
-        momentum = 0.0 # dadapt_sgd only
+        momentum = 0.0 # dadapt_sgd
+        no_prox = False # ????, dadapt_adan
+        growth_rate=float("inf") # dadapt
 
         if local_optimizer_config is not None:
-            betas = local_optimizer_config["betas"] or betas
-            epsilon = local_optimizer_config["epsilon"] or epsilon
-            weight_decay = local_optimizer_config["weight_decay"] or weight_decay
-            optimizer_name = local_optimizer_config["optimizer"] or "adamw8bit"
+            betas = local_optimizer_config.get("betas", betas)
+            epsilon = local_optimizer_config.get("epsilon", epsilon)
+            weight_decay = local_optimizer_config.get("weight_decay", weight_decay)
+            no_prox =  local_optimizer_config.get("no_prox", False)
+            optimizer_name = local_optimizer_config.get("optimizer", "adamw8bit")
             curr_lr = local_optimizer_config.get("lr", curr_lr)
             d0 = local_optimizer_config.get("d0", d0)
             decouple = local_optimizer_config.get("decouple", decouple)
             momentum = local_optimizer_config.get("momentum", momentum)
+            growth_rate = local_optimizer_config.get("growth_rate", growth_rate)
             if args.lr is not None:
                 curr_lr = args.lr
                 logging.info(f"Overriding LR from optimizer config with main config/cli LR setting: {curr_lr}")
@@ -335,6 +339,19 @@ class EveryDreamOptimizer():
                         growth_rate=1e5,
                         decouple=decouple,
                     )
+                elif optimizer_name == "dadapt_adan":
+                    opt_class = dadaptation.DAdaptAdan
+                    optimizer = opt_class(
+                        itertools.chain(parameters),
+                        lr=curr_lr,
+                        betas=(betas[0], betas[1]),
+                        no_prox=no_prox,
+                        weight_decay=weight_decay,
+                        eps=epsilon,
+                        d0=d0,
+                        log_every=args.log_step,
+                        growth_rate=growth_rate,
+                    )
                 elif optimizer_name == "dadapt_lion":
                     opt_class = dadaptation.DAdaptLion
                     optimizer = opt_class(

requirements.txt

@@ -1,7 +1,7 @@
 torch==2.0.1 
 torchvision==0.15.2
 transformers==4.29.2
-diffusers[torch]==0.14.0
+diffusers[torch]==0.17.1
 pynvml==11.4.1
 bitsandbytes==0.38.1
 ftfy==6.1.1