Solve comflict

deepmd/main.py

@@ -770,7 +770,14 @@ def main_parser() -> argparse.ArgumentParser:
         """
         ),
     )
+<<<<<<< HEAD
     parser_list_model_branch.add_argument("INPUT", help="The input multi-task pre-trained model file")
+=======
+    parser_list_model_branch.add_argument(
+        "INPUT", help="The input multi-task pre-trained model file"
+    )
+
+>>>>>>> 50b00090e1ac2777faf84446f5d4e04bcef55188
     return parser
 
 
@@ -828,7 +835,7 @@ def main():
         "compress",
         "convert-from",
         "train-nvnmd",
-        "list-model-branch"
+        "list-model-branch",
     ):
         deepmd_main = BACKENDS[args.backend]().entry_point_hook
     elif args.command is None:

deepmd/pt/entrypoints/main.py

@@ -71,7 +71,6 @@
 from deepmd.utils.summary import SummaryPrinter as BaseSummaryPrinter
 
 log = logging.getLogger(__name__)
-from IPython import embed
 
 
 def get_trainer(
@@ -329,7 +328,7 @@ def main(args: Optional[Union[List[str], argparse.Namespace]] = None):
         #  Pretrained model must be multitask mode
         assert finetune_from_multi_task, "When using --list-model-branch, the pretrained model must be multitask model"
         model_branch = list(model_params["model_dict"].keys())
-        log.info(f"Available model branches are {model_branch}")        
+        log.info(f"Available model branches are {model_branch}")
     else:
         raise RuntimeError(f"Invalid command {FLAGS.command}!")
 

deepmd/pt/utils/finetune.py

@@ -5,7 +5,6 @@
 )
 
 import torch
-from IPython import embed
 
 from deepmd.pt.utils import (
     env,