simplyfy code by updating accelerate to 0.30.0

fine_tune.py

@@ -271,8 +271,8 @@ def fn_recursive_set_mem_eff(module: torch.nn.Module):
 
     # make lambda function for calling optimizer.train() and optimizer.eval() if schedule-free optimizer is used
     if use_schedule_free_optimizer:
-        optimizer_train_if_needed = lambda: (optimizer.optimizer if hasattr(optimizer, "optimizer") else optimizer).train()
-        optimizer_eval_if_needed = lambda: (optimizer.optimizer if hasattr(optimizer, "optimizer") else optimizer).eval()
+        optimizer_train_if_needed = lambda: optimizer.train()
+        optimizer_eval_if_needed = lambda: optimizer.eval()
     else:
         optimizer_train_if_needed = lambda: None
         optimizer_eval_if_needed = lambda: None

requirements.txt

@@ -1,4 +1,4 @@
-accelerate==0.29.2
+accelerate==0.30.0
 transformers==4.36.2
 diffusers[torch]==0.25.0
 ftfy==6.1.1
@@ -9,6 +9,7 @@ pytorch-lightning==1.9.0
 bitsandbytes==0.43.0
 prodigyopt==1.0
 lion-pytorch==0.0.6
+schedulefree==1.2.5
 tensorboard
 safetensors==0.4.2
 # gradio==3.16.2

sdxl_train.py

@@ -435,8 +435,8 @@ def fn_recursive_set_mem_eff(module: torch.nn.Module):
 
     # make lambda function for calling optimizer.train() and optimizer.eval() if schedule-free optimizer is used
     if use_schedule_free_optimizer:
-        optimizer_train_if_needed = lambda: (optimizer.optimizer if hasattr(optimizer, "optimizer") else optimizer).train()
-        optimizer_eval_if_needed = lambda: (optimizer.optimizer if hasattr(optimizer, "optimizer") else optimizer).eval()
+        optimizer_train_if_needed = lambda: optimizer.train()
+        optimizer_eval_if_needed = lambda: optimizer.eval()
     else:
         optimizer_train_if_needed = lambda: None
         optimizer_eval_if_needed = lambda: None

sdxl_train_control_net_lllite.py

@@ -294,8 +294,8 @@ def train(args):
 
     # make lambda function for calling optimizer.train() and optimizer.eval() if schedule-free optimizer is used
     if use_schedule_free_optimizer:
-        optimizer_train_if_needed = lambda: (optimizer.optimizer if hasattr(optimizer, "optimizer") else optimizer).train()
-        optimizer_eval_if_needed = lambda: (optimizer.optimizer if hasattr(optimizer, "optimizer") else optimizer).eval()
+        optimizer_train_if_needed = lambda: optimizer.train()
+        optimizer_eval_if_needed = lambda: optimizer.eval()
     else:
         optimizer_train_if_needed = lambda: None
         optimizer_eval_if_needed = lambda: None

sdxl_train_control_net_lllite_old.py

@@ -262,8 +262,8 @@ def train(args):
 
     # make lambda function for calling optimizer.train() and optimizer.eval() if schedule-free optimizer is used
     if use_schedule_free_optimizer:
-        optimizer_train_if_needed = lambda: (optimizer.optimizer if hasattr(optimizer, "optimizer") else optimizer).train()
-        optimizer_eval_if_needed = lambda: (optimizer.optimizer if hasattr(optimizer, "optimizer") else optimizer).eval()
+        optimizer_train_if_needed = lambda: optimizer.train()
+        optimizer_eval_if_needed = lambda: optimizer.eval()
     else:
         optimizer_train_if_needed = lambda: None
         optimizer_eval_if_needed = lambda: None

train_controlnet.py

@@ -284,8 +284,8 @@ def train(args):
 
     # make lambda function for calling optimizer.train() and optimizer.eval() if schedule-free optimizer is used
     if use_schedule_free_optimizer:
-        optimizer_train_if_needed = lambda: (optimizer.optimizer if hasattr(optimizer, "optimizer") else optimizer).train()
-        optimizer_eval_if_needed = lambda: (optimizer.optimizer if hasattr(optimizer, "optimizer") else optimizer).eval()
+        optimizer_train_if_needed = lambda: optimizer.train()
+        optimizer_eval_if_needed = lambda: optimizer.eval()
     else:
         optimizer_train_if_needed = lambda: None
         optimizer_eval_if_needed = lambda: None

train_db.py

@@ -247,8 +247,8 @@ def train(args):
 
     # make lambda function for calling optimizer.train() and optimizer.eval() if schedule-free optimizer is used
     if use_schedule_free_optimizer:
-        optimizer_train_if_needed = lambda: (optimizer.optimizer if hasattr(optimizer, "optimizer") else optimizer).train()
-        optimizer_eval_if_needed = lambda: (optimizer.optimizer if hasattr(optimizer, "optimizer") else optimizer).eval()
+        optimizer_train_if_needed = lambda: optimizer.train()
+        optimizer_eval_if_needed = lambda: optimizer.eval()
     else:
         optimizer_train_if_needed = lambda: None
         optimizer_eval_if_needed = lambda: None

train_textual_inversion_XTI.py

@@ -342,8 +342,8 @@ def train(args):
 
     # make lambda function for calling optimizer.train() and optimizer.eval() if schedule-free optimizer is used
     if use_schedule_free_optimizer:
-        optimizer_train_if_needed = lambda: (optimizer.optimizer if hasattr(optimizer, "optimizer") else optimizer).train()
-        optimizer_eval_if_needed = lambda: (optimizer.optimizer if hasattr(optimizer, "optimizer") else optimizer).eval()
+        optimizer_train_if_needed = lambda: optimizer.train()
+        optimizer_eval_if_needed = lambda: optimizer.eval()
     else:
         optimizer_train_if_needed = lambda: None
         optimizer_eval_if_needed = lambda: None