Fix CI

face_swapper/src/dataset.py

@@ -10,7 +10,7 @@ from torch.utils.data import Dataset
 from torchvision import io, transforms
 
 from .helper import warp_tensor
-from .types import Batch, WarpTemplate, BatchMode
+from .types import Batch, BatchMode, WarpTemplate
 
 
 class DynamicDataset(Dataset[Tensor]):

face_swapper/src/inferencing.py

@@ -24,7 +24,7 @@ def infer() -> None:
 	generator = Generator(CONFIG_PARSER)
 	generator.load_state_dict(state_dict)
 	generator.eval()
-	embedder = torch.jit.load(embedder_path, map_location = 'cpu') # type:ignore[no-untyped-call]
+	embedder = torch.jit.load(config.get('embedder_path'), map_location = 'cpu') # type:ignore[no-untyped-call]
 	embedder.eval()
 
 	source_tensor = io.read_image(config.get('source_path'))

face_swapper/src/models/discriminator.py

@@ -17,7 +17,6 @@ class Discriminator(nn.Module):
 		self.avg_pool = nn.AvgPool2d(kernel_size = 3, stride = 2, padding = (1, 1), count_include_pad = False)
 		self.discriminators = self.create_discriminators()
 
-
 	def create_discriminators(self) -> nn.ModuleList:
 		discriminators = nn.ModuleList()
 

face_swapper/src/training.py

@@ -1,7 +1,7 @@
 import os
-from configparser import ConfigParser
 import warnings
-from typing import Tuple, cast
+from configparser import ConfigParser
+from typing import Tuple
 
 import torch
 import torchvision
@@ -17,7 +17,7 @@ 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, OptimizerSet, WarpTemplate
+from .types import Batch, Embedding, OptimizerSet
 
 warnings.filterwarnings('ignore', category = UserWarning, module = 'torch')