checkpointing_steps_total_limit->checkpoints_total_limit (#2374)

examples/dreambooth/train_dreambooth.py

@@ -196,7 +196,7 @@ def parse_args(input_args=None):
         ),
     )
     parser.add_argument(
-        "--checkpointing_steps_total_limit",
+        "--checkpoints_total_limit",
         type=int,
         default=None,
         help=(
@@ -498,7 +498,7 @@ def get_full_repo_name(model_id: str, organization: Optional[str] = None, token:
 def main(args):
     logging_dir = Path(args.output_dir, args.logging_dir)
 
-    accelerator_project_config = ProjectConfiguration(total_limit=args.checkpointing_steps_total_limit)
+    accelerator_project_config = ProjectConfiguration(total_limit=args.checkpoints_total_limit)
 
     accelerator = Accelerator(
         gradient_accumulation_steps=args.gradient_accumulation_steps,

examples/dreambooth/train_dreambooth_lora.py

@@ -243,7 +243,7 @@ def parse_args(input_args=None):
         ),
     )
     parser.add_argument(
-        "--checkpointing_steps_total_limit",
+        "--checkpoints_total_limit",
         type=int,
         default=None,
         help=(
@@ -536,7 +536,7 @@ def get_full_repo_name(model_id: str, organization: Optional[str] = None, token:
 def main(args):
     logging_dir = Path(args.output_dir, args.logging_dir)
 
-    accelerator_project_config = ProjectConfiguration(total_limit=args.checkpointing_steps_total_limit)
+    accelerator_project_config = ProjectConfiguration(total_limit=args.checkpoints_total_limit)
 
     accelerator = Accelerator(
         gradient_accumulation_steps=args.gradient_accumulation_steps,

examples/research_projects/dreambooth_inpaint/train_dreambooth_inpaint.py

@@ -259,7 +259,7 @@ def parse_args():
         ),
     )
     parser.add_argument(
-        "--checkpointing_steps_total_limit",
+        "--checkpoints_total_limit",
         type=int,
         default=None,
         help=(
@@ -416,7 +416,7 @@ def main():
     args = parse_args()
     logging_dir = Path(args.output_dir, args.logging_dir)
 
-    accelerator_project_config = ProjectConfiguration(total_limit=args.checkpointing_steps_total_limit)
+    accelerator_project_config = ProjectConfiguration(total_limit=args.checkpoints_total_limit)
 
     accelerator = Accelerator(
         gradient_accumulation_steps=args.gradient_accumulation_steps,

examples/research_projects/dreambooth_inpaint/train_dreambooth_inpaint_lora.py

@@ -255,7 +255,7 @@ def parse_args():
         ),
     )
     parser.add_argument(
-        "--checkpointing_steps_total_limit",
+        "--checkpoints_total_limit",
         type=int,
         default=None,
         help=(
@@ -415,7 +415,7 @@ def main():
     args = parse_args()
     logging_dir = Path(args.output_dir, args.logging_dir)
 
-    accelerator_project_config = ProjectConfiguration(total_limit=args.checkpointing_steps_total_limit)
+    accelerator_project_config = ProjectConfiguration(total_limit=args.checkpoints_total_limit)
 
     accelerator = Accelerator(
         gradient_accumulation_steps=args.gradient_accumulation_steps,

examples/research_projects/multi_subject_dreambooth/train_multi_subject_dreambooth.py

@@ -171,7 +171,7 @@ def parse_args(input_args=None):
         ),
     )
     parser.add_argument(
-        "--checkpointing_steps_total_limit",
+        "--checkpoints_total_limit",
         type=int,
         default=None,
         help=(
@@ -476,7 +476,7 @@ def get_full_repo_name(model_id: str, organization: Optional[str] = None, token:
 def main(args):
     logging_dir = Path(args.output_dir, args.logging_dir)
 
-    accelerator_project_config = ProjectConfiguration(total_limit=args.checkpointing_steps_total_limit)
+    accelerator_project_config = ProjectConfiguration(total_limit=args.checkpoints_total_limit)
 
     accelerator = Accelerator(
         gradient_accumulation_steps=args.gradient_accumulation_steps,

examples/research_projects/onnxruntime/text_to_image/train_text_to_image.py

@@ -275,7 +275,7 @@ def parse_args():
         ),
     )
     parser.add_argument(
-        "--checkpointing_steps_total_limit",
+        "--checkpoints_total_limit",
         type=int,
         default=None,
         help=(
@@ -332,7 +332,7 @@ def main():
     args = parse_args()
     logging_dir = os.path.join(args.output_dir, args.logging_dir)
 
-    accelerator_project_config = ProjectConfiguration(total_limit=args.checkpointing_steps_total_limit)
+    accelerator_project_config = ProjectConfiguration(total_limit=args.checkpoints_total_limit)
 
     accelerator = Accelerator(
         gradient_accumulation_steps=args.gradient_accumulation_steps,

examples/research_projects/onnxruntime/textual_inversion/textual_inversion.py

@@ -291,7 +291,7 @@ def parse_args():
         ),
     )
     parser.add_argument(
-        "--checkpointing_steps_total_limit",
+        "--checkpoints_total_limit",
         type=int,
         default=None,
         help=(
@@ -477,7 +477,7 @@ def main():
     args = parse_args()
     logging_dir = os.path.join(args.output_dir, args.logging_dir)
 
-    accelerator_project_config = ProjectConfiguration(total_limit=args.checkpointing_steps_total_limit)
+    accelerator_project_config = ProjectConfiguration(total_limit=args.checkpoints_total_limit)
 
     accelerator = Accelerator(
         gradient_accumulation_steps=args.gradient_accumulation_steps,

examples/research_projects/onnxruntime/unconditional_image_generation/train_unconditional.py

@@ -233,7 +233,7 @@ def parse_args():
         ),
     )
     parser.add_argument(
-        "--checkpointing_steps_total_limit",
+        "--checkpoints_total_limit",
         type=int,
         default=None,
         help=(
@@ -276,7 +276,7 @@ def get_full_repo_name(model_id: str, organization: Optional[str] = None, token:
 def main(args):
     logging_dir = os.path.join(args.output_dir, args.logging_dir)
 
-    accelerator_project_config = ProjectConfiguration(total_limit=args.checkpointing_steps_total_limit)
+    accelerator_project_config = ProjectConfiguration(total_limit=args.checkpoints_total_limit)
 
     accelerator = Accelerator(
         gradient_accumulation_steps=args.gradient_accumulation_steps,

examples/text_to_image/train_text_to_image.py

@@ -276,7 +276,7 @@ def parse_args():
         ),
     )
     parser.add_argument(
-        "--checkpointing_steps_total_limit",
+        "--checkpoints_total_limit",
         type=int,
         default=None,
         help=(
@@ -343,7 +343,7 @@ def main():
         )
     logging_dir = os.path.join(args.output_dir, args.logging_dir)
 
-    accelerator_project_config = ProjectConfiguration(total_limit=args.checkpointing_steps_total_limit)
+    accelerator_project_config = ProjectConfiguration(total_limit=args.checkpoints_total_limit)
 
     accelerator = Accelerator(
         gradient_accumulation_steps=args.gradient_accumulation_steps,

examples/text_to_image/train_text_to_image_lora.py

@@ -311,7 +311,7 @@ def parse_args():
         ),
     )
     parser.add_argument(
-        "--checkpointing_steps_total_limit",
+        "--checkpoints_total_limit",
         type=int,
         default=None,
         help=(
@@ -364,7 +364,7 @@ def main():
     args = parse_args()
     logging_dir = os.path.join(args.output_dir, args.logging_dir)
 
-    accelerator_project_config = ProjectConfiguration(total_limit=args.checkpointing_steps_total_limit)
+    accelerator_project_config = ProjectConfiguration(total_limit=args.checkpoints_total_limit)
 
     accelerator = Accelerator(
         gradient_accumulation_steps=args.gradient_accumulation_steps,

examples/textual_inversion/textual_inversion.py

@@ -289,7 +289,7 @@ def parse_args():
         ),
     )
     parser.add_argument(
-        "--checkpointing_steps_total_limit",
+        "--checkpoints_total_limit",
         type=int,
         default=None,
         help=(
@@ -475,7 +475,7 @@ def main():
     args = parse_args()
     logging_dir = os.path.join(args.output_dir, args.logging_dir)
 
-    accelerator_project_config = ProjectConfiguration(total_limit=args.checkpointing_steps_total_limit)
+    accelerator_project_config = ProjectConfiguration(total_limit=args.checkpoints_total_limit)
 
     accelerator = Accelerator(
         gradient_accumulation_steps=args.gradient_accumulation_steps,

examples/unconditional_image_generation/train_unconditional.py

@@ -241,7 +241,7 @@ def parse_args():
         ),
     )
     parser.add_argument(
-        "--checkpointing_steps_total_limit",
+        "--checkpoints_total_limit",
         type=int,
         default=None,
         help=(
@@ -284,7 +284,7 @@ def get_full_repo_name(model_id: str, organization: Optional[str] = None, token:
 def main(args):
     logging_dir = os.path.join(args.output_dir, args.logging_dir)
 
-    accelerator_project_config = ProjectConfiguration(total_limit=args.checkpointing_steps_total_limit)
+    accelerator_project_config = ProjectConfiguration(total_limit=args.checkpoints_total_limit)
 
     accelerator = Accelerator(
         gradient_accumulation_steps=args.gradient_accumulation_steps,