Rename to resume_path only

embedding_converter/README.md

@@ -53,7 +53,7 @@ max_epochs = 4096
 [training.output]
 directory_path = .outputs
 file_pattern = arcface_converter_simswap_{epoch}_{step}
-resume_file_path = .outputs/last.ckpt
+resume_path = .outputs/last.ckpt
 ```
 
 ```

embedding_converter/config.ini

@@ -17,7 +17,7 @@ max_epochs =
 [training.output]
 directory_path =
 file_pattern =
-resume_file_path =
+resume_path =
 
 [exporting]
 directory_path =

embedding_converter/src/dataset.py

@@ -3,7 +3,6 @@ import random
 
 import cv2
 from torch import Tensor
-
 from torch.utils.data import Dataset
 from torchvision import transforms
 

embedding_converter/src/training.py

@@ -119,7 +119,7 @@ def create_trainer() -> Trainer:
 
 def train() -> None:
 	dataset_file_pattern = CONFIG.get('training.dataset', 'file_pattern')
-	resume_file_path = CONFIG.get('training.output', 'resume_file_path')
+	output_resume_path = CONFIG.get('training.output', 'resume_path')
 
 	dataset = DynamicDataset(dataset_file_pattern)
 	training_loader, validation_loader = create_loaders(dataset)
@@ -128,7 +128,7 @@ def train() -> None:
 	tuner = Tuner(trainer)
 	tuner.lr_find(embedding_converter_trainer, training_loader, validation_loader)
 
-	if os.path.exists(resume_file_path):
-		trainer.fit(embedding_converter_trainer, training_loader, validation_loader, ckpt_path = resume_file_path)
+	if os.path.exists(output_resume_path):
+		trainer.fit(embedding_converter_trainer, training_loader, validation_loader, ckpt_path = output_resume_path)
 	else:
 		trainer.fit(embedding_converter_trainer, training_loader, validation_loader)

embedding_converter/src/types.py

@@ -1,4 +1,4 @@
-from typing import Any, Dict, TypeAlias
+from typing import Any, TypeAlias
 
 from numpy.typing import NDArray
 from torch import Tensor

face_swapper/README.md

@@ -84,7 +84,7 @@ preview_frequency = 250
 [training.output]
 directory_path = .outputs
 file_pattern = face-swapper_{epoch}_{step}
-resume_file_path = .outputs/last.ckpt
+resume_path = .outputs/last.ckpt
 ```
 
 ```

face_swapper/config.ini

@@ -42,7 +42,7 @@ preview_frequency =
 [training.output]
 directory_path =
 file_pattern =
-resume_file_path =
+resume_path =
 
 [exporting]
 directory_path =

face_swapper/src/training.py

@@ -129,7 +129,7 @@ def train() -> None:
 	same_person_probability = CONFIG.getfloat('preparing.dataset', 'same_person_probability')
 	batch_size = CONFIG.getint('training.loader', 'batch_size')
 	num_workers = CONFIG.getint('training.loader', 'num_workers')
-	resume_file_path = CONFIG.get('training.output', 'resume_file_path')
+	output_resume_path = CONFIG.get('training.output', 'resume_path')
 
 	dataset = DataLoader(dataset_path, dataset_image_pattern, dataset_directory_pattern, same_person_probability)
 	training_loader = TorchDataLoader(dataset, batch_size = batch_size, shuffle = True, num_workers = num_workers, drop_last = True, pin_memory = True, persistent_workers = True)
@@ -137,7 +137,7 @@ def train() -> None:
 	face_swapper_trainer = FaceSwapperTrainer()
 	trainer = create_trainer()
 
-	if os.path.isfile(resume_file_path):
-		trainer.fit(face_swapper_trainer, training_loader, validation_loader, ckpt_path = resume_file_path)
+	if os.path.isfile(output_resume_path):
+		trainer.fit(face_swapper_trainer, training_loader, validation_loader, ckpt_path = output_resume_path)
 	else:
 		trainer.fit(face_swapper_trainer, training_loader, validation_loader)