Add tests using mocker to main.py

src/test_main.py

@@ -0,0 +1,34 @@
+import pytest
+from unittest.mock import Mock
+from main import Net
+import torch
+
+@pytest.fixture
+def net():
+    return Net()
+
+def test_net_init(net):
+    pytest.assume(isinstance(net.fc1, torch.nn.Linear))
+    pytest.assume(isinstance(net.fc2, torch.nn.Linear))
+    pytest.assume(isinstance(net.fc3, torch.nn.Linear))
+
+def test_net_forward(mocker, net):
+    mock_tensor = mocker.Mock(spec=torch.Tensor)
+    mock_tensor.view.return_value = mock_tensor
+    output = net(mock_tensor)
+    pytest.assume(isinstance(output, torch.Tensor))
+
+def test_training_loop(mocker):
+    mock_images = mocker.Mock(spec=torch.Tensor)
+    mock_labels = mocker.Mock(spec=torch.Tensor)
+    mock_trainloader = [(mock_images, mock_labels) for _ in range(10)]
+    model = Net()
+    optimizer = torch.optim.SGD(model.parameters(), lr=0.01)
+    criterion = torch.nn.NLLLoss()
+    for images, labels in mock_trainloader:
+        optimizer.zero_grad()
+        output = model(images)
+        loss = criterion(output, labels)
+        loss.backward()
+        optimizer.step()
+    pytest.assume(model.state_dict() is not None)