Add basic test for aad and unet

.github/workflows/ci.yml

@@ -8,12 +8,27 @@ jobs:
   steps:
   - name: Checkout
     uses: actions/checkout@v4
-  - name: Set up Python 3.10
+  - name: Set up Python 3.12
     uses: actions/setup-python@v5
     with:
-     python-version: '3.10'
+     python-version: '3.12'
   - run: pip install flake8
   - run: pip install flake8-import-order
   - run: pip install mypy
   - run: flake8 embedding_converter face_swapper
   - run: mypy embedding_converter face_swapper
+ test:
+  strategy:
+   matrix:
+    os: [ macos-latest, ubuntu-latest, windows-latest ]
+  runs-on: ${{ matrix.os }}
+  steps:
+  - name: Checkout
+    uses: actions/checkout@v4
+  - name: Set up Python 3.12
+    uses: actions/setup-python@v5
+    with:
+     python-version: '3.12'
+  - run: pip install torch torchvision
+  - run: pip install pytest
+  - run: pytest

face_swapper/tests/test_networks.py

@@ -0,0 +1,19 @@
+import torch
+import pytest
+
+from face_swapper.src.networks.aad import AAD
+from face_swapper.src.networks.unet import UNet
+
+
+@pytest.mark.parametrize('output_size', [ 256 ])
+def test_aad_with_unet(output_size : int) -> None:
+	generator = AAD(512, 4096, output_size, 2).eval()
+	encoder = UNet(output_size).eval()
+
+	source_tensor = torch.randn(1, 512)
+	target_tensor = torch.randn(1, 3, output_size, output_size)
+
+	target_attributes = encoder(target_tensor)
+	output_tensor = generator(source_tensor, target_attributes)
+
+	assert output_tensor.shape == (1, 3, output_size, output_size)