comment out schedulefree wrapper

library/train_util.py

@@ -3303,19 +3303,19 @@ def int_or_float(value):
         help='additional arguments for optimizer (like "weight_decay=0.01 betas=0.9,0.999 ...") / オプティマイザの追加引数（例： "weight_decay=0.01 betas=0.9,0.999 ..."）',
     )
 
-    parser.add_argument(
-        "--optimizer_schedulefree_wrapper",
-        action="store_true",
-        help="use schedulefree_wrapper any optimizer / 任意のオプティマイザにschedulefree_wrapperを使用",
-    )
+    # parser.add_argument(
+    #     "--optimizer_schedulefree_wrapper",
+    #     action="store_true",
+    #     help="use schedulefree_wrapper any optimizer / 任意のオプティマイザにschedulefree_wrapperを使用",
+    # )
 
-    parser.add_argument(
-        "--schedulefree_wrapper_args",
-        type=str,
-        default=None,
-        nargs="*",
-        help='additional arguments for schedulefree_wrapper (like "momentum=0.9 weight_decay_at_y=0.1 ...") / オプティマイザの追加引数（例： "momentum=0.9 weight_decay_at_y=0.1 ..."）',
-    )
+    # parser.add_argument(
+    #     "--schedulefree_wrapper_args",
+    #     type=str,
+    #     default=None,
+    #     nargs="*",
+    #     help='additional arguments for schedulefree_wrapper (like "momentum=0.9 weight_decay_at_y=0.1 ...") / オプティマイザの追加引数（例： "momentum=0.9 weight_decay_at_y=0.1 ..."）',
+    # )
 
     parser.add_argument("--lr_scheduler_type", type=str, default="", help="custom scheduler module / 使用するスケジューラ")
     parser.add_argument(
@@ -4375,8 +4375,6 @@ def get_optimizer(args, trainable_params):
             optimizer_kwargs[key] = value
     # logger.info(f"optkwargs {optimizer}_{kwargs}")
 
-    schedulefree_wrapper_kwargs = {}
-
     lr = args.learning_rate
     optimizer = None
 
@@ -4622,23 +4620,23 @@ def get_optimizer(args, trainable_params):
 
         if "." not in case_sensitive_optimizer_type:  # from torch.optim
             optimizer_module = torch.optim
-            optimizer_class = getattr(optimizer_module, case_sensitive_optimizer_type)
-            optimizer = optimizer_class(trainable_params, lr=lr, **optimizer_kwargs)
         else:  # from other library
             values = case_sensitive_optimizer_type.split(".")
             optimizer_module = importlib.import_module(".".join(values[:-1]))
             case_sensitive_optimizer_type = values[-1]
 
-            optimizer_class = getattr(optimizer_module, case_sensitive_optimizer_type)
-            optimizer = optimizer_class(trainable_params, lr=lr, **optimizer_kwargs)
+        optimizer_class = getattr(optimizer_module, case_sensitive_optimizer_type)
+        optimizer = optimizer_class(trainable_params, lr=lr, **optimizer_kwargs)
 
+    """
     # wrap any of above optimizer with schedulefree, if optimizer is not schedulefree
     if args.optimizer_schedulefree_wrapper and not optimizer_type.endswith("schedulefree".lower()):
         try:
             import schedulefree as sf
         except ImportError:
             raise ImportError("No schedulefree / schedulefreeがインストールされていないようです")
 
+        schedulefree_wrapper_kwargs = {}
         if args.schedulefree_wrapper_args is not None and len(args.schedulefree_wrapper_args) > 0:
             for arg in args.schedulefree_wrapper_args:
                 key, value = arg.split("=")
@@ -4709,6 +4707,7 @@ def __instancecheck__(self, instance):
         optimizer = OptimizerProxy(sf_wrapper)
 
         logger.info(f"wrap optimizer with ScheduleFreeWrapper | {schedulefree_wrapper_kwargs}")
+    """
 
     optimizer_name = optimizer_class.__module__ + "." + optimizer_class.__name__
     optimizer_args = ",".join([f"{k}={v}" for k, v in optimizer_kwargs.items()])
@@ -4717,7 +4716,7 @@ def __instancecheck__(self, instance):
 
 
 def is_schedulefree_optimizer(optimizer: Optimizer, args: argparse.Namespace) -> bool:
-    return args.optimizer_type.lower().endswith("schedulefree".lower()) or args.optimizer_schedulefree_wrapper
+    return args.optimizer_type.lower().endswith("schedulefree".lower()) # or args.optimizer_schedulefree_wrapper
 
 
 def get_dummy_scheduler(optimizer: Optimizer) -> Any: