blacked

GANDLF/entrypoints/deploy.py

@@ -143,7 +143,7 @@ def new_way(
     output_dir: str,
     requires_gpu: bool,
     entrypoint: Optional[str],
-    log_file:str
+    log_file: str,
 ):
     """Generate frozen/deployable versions of trained GaNDLF models."""
     if log_file is not None:

GANDLF/entrypoints/preprocess.py

@@ -96,7 +96,7 @@ def new_way(
     label_pad: str,
     apply_augs: bool,
     crop_zero: bool,
-    log_file: bool
+    log_file: bool,
 ):
     """Generate training/inference data which are preprocessed to reduce resource footprint during computation."""
     if log_file is not None:

GANDLF/entrypoints/recover_config.py

@@ -55,7 +55,7 @@ def _recover_config(model_dir: Optional[str], mlcube: bool, output_file: str):
     help="Output file which will contain the logs.",
 )
 @append_copyright_to_help
-def new_way(model_dir, mlcube, output_file,log_file):
+def new_way(model_dir, mlcube, output_file, log_file):
     """Recovers a config file from a GaNDLF model. If used from within a deployed GaNDLF MLCube,
     attempts to extract the config from the embedded model."""
     if log_file is not None:

GANDLF/entrypoints/run.py

@@ -164,7 +164,7 @@ def new_way(
     resume: bool,
     output_path: str,
     raw_input: str,
-    log_file:str
+    log_file: str,
 ):
     """Semantic segmentation, regression, and classification for medical images using Deep Learning."""
     if log_file is not None:

GANDLF/entrypoints/split_csv.py

@@ -57,9 +57,8 @@ def _split_csv(input_csv: str, output_dir: str, config_path: Optional[str]):
     default=None,
     help="Output file which will contain the logs.",
 )
-
 @append_copyright_to_help
-def new_way(input_csv: str, output_dir: str, config: Optional[str],log_file):
+def new_way(input_csv: str, output_dir: str, config: Optional[str], log_file):
     """Split the data into training, validation, and testing sets and save them as csvs in the output directory."""
     if log_file is not None:
         logger_setup(log_file)