Address code review feedback: add deterministic seeds and improve mocks

tests/inference/test_data.py

@@ -63,16 +63,19 @@ class TestTileFeatureTensorDataset:
     @pytest.fixture
     def sample_features(self):
         """Create sample features for testing."""
+        np.random.seed(42)
         return np.random.rand(100, 768).astype(np.float32)
 
     @pytest.fixture
     def large_features(self):
         """Create large sample features for testing padding/truncation."""
+        np.random.seed(42)
         return np.random.rand(25000, 768).astype(np.float32)
 
     @pytest.fixture
     def small_features(self):
         """Create small sample features for testing padding."""
+        np.random.seed(42)
         return np.random.rand(50, 768).astype(np.float32)
 
     def test_dataset_initialization(self, sample_features):
@@ -157,6 +160,7 @@ class TestTileFeatureTensorDataset:
 
     def test_features_exact_size(self):
         """Test that features of exactly n_max_tiles are not modified."""
+        np.random.seed(42)
         n_max_tiles = 100
         features = np.random.rand(n_max_tiles, 768).astype(np.float32)
         dataset = TileFeatureTensorDataset(
@@ -178,6 +182,7 @@ class TestTileFeatureTensorDataset:
 
     def test_different_feature_dimensions(self):
         """Test dataset with different feature dimensions."""
+        np.random.seed(42)
         for dim in [256, 512, 768, 1024]:
             features = np.random.rand(100, dim).astype(np.float32)
             dataset = TileFeatureTensorDataset(

tests/inference/test_paladin.py

@@ -157,6 +157,7 @@ class TestLogitsToPointEstimates:
     def test_logits_to_point_estimates_shape(self):
         """Test that output shape is correct."""
         # logits shape: (batch_size, 2 * n_tasks)
+        torch.manual_seed(42)
         batch_size = 4
         n_tasks = 5
         logits = torch.rand(batch_size, 2 * n_tasks)
@@ -185,6 +186,7 @@ class TestLogitsToPointEstimates:
 
     def test_logits_to_point_estimates_multiple_batches(self):
         """Test with multiple batches."""
+        torch.manual_seed(42)
         logits = torch.rand(10, 8)  # 10 batches, 4 tasks
         result = logits_to_point_estimates(logits)
         assert result.shape == (10, 4)

tests/test_gradio_app.py

@@ -177,10 +177,10 @@ class TestGetOncotreeCodeName:
         """Test that invalid code returns 'Unknown'."""
         from mosaic.gradio_app import get_oncotree_code_name, oncotree_code_map
 
-        # Mock the requests.get call to return 404
+        # Mock the requests.get call to return empty response (no matching codes)
         mock_response = mocker.Mock()
-        mock_response.status_code = 404
-        mock_response.json.return_value = []
+        mock_response.status_code = 200
+        mock_response.json.return_value = []  # Empty list means no matching codes found
         mocker.patch("requests.get", return_value=mock_response)
 
         # Clear cache and use an invalid code