Fix CI

embedding_converter/src/exporting.py

@@ -19,7 +19,7 @@ def export() -> None:
 		'opset_version': CONFIG.getint('exporting', 'opset_version')
 	}
 
-	makedirs(config.get('directory_path'), exist_ok = True)
+	makedirs(config.get('directory_path'), exist_ok = True) # type:ignore[arg-type]
 	model = EmbeddingConverterTrainer.load_from_checkpoint(config.get('source_path'), map_location = 'cpu')
 	model.eval()
 	model.ir_version = torch.tensor(config.get('ir_version'))

face_swapper/src/training.py

@@ -18,7 +18,7 @@ from .helper import calc_embedding
 from .models.discriminator import Discriminator
 from .models.generator import Generator
 from .models.loss import AdversarialLoss, AttributeLoss, DiscriminatorLoss, GazeLoss, IdentityLoss, MotionLoss, ReconstructionLoss
-from .types import Batch, BatchMode, Embedding, OptimizerConfig, WarpTemplate
+from .types import Batch, BatchMode, Embedding, OptimizerSet, WarpTemplate
 
 warnings.filterwarnings('ignore', category = UserWarning, module = 'torch')
 
@@ -52,7 +52,7 @@ class FaceSwapperTrainer(lightning.LightningModule):
 		output_tensor = self.generator(source_embedding, target_tensor)
 		return output_tensor
 
-	def configure_optimizers(self) -> Tuple[OptimizerConfig, OptimizerConfig]:
+	def configure_optimizers(self) -> Tuple[OptimizerSet, OptimizerSet]:
 		learning_rate = CONFIG.getfloat('training.trainer', 'learning_rate')
 		generator_optimizer = torch.optim.AdamW(self.generator.parameters(), lr = learning_rate, betas = (0.0, 0.999), weight_decay = 1e-4)
 		discriminator_optimizer = torch.optim.AdamW(self.discriminator.parameters(), lr = learning_rate, betas = (0.0, 0.999), weight_decay = 1e-4)

face_swapper/src/types.py

@@ -17,7 +17,8 @@ EmbedderModule : TypeAlias = Module
 GazerModule : TypeAlias = Module
 MotionExtractorModule : TypeAlias = Module
 
-OptimizerConfig : TypeAlias = Any
+Config : TypeAlias = Dict[str, Any]
+OptimizerSet : TypeAlias = Any
 
 WarpTemplate = Literal['vgg_face_hq_to_arcface_128_v2', 'arcface_128_v2_to_arcface_112_v2']
 WarpTemplateSet : TypeAlias = Dict[WarpTemplate, Tensor]