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pytest fixtures for the test suite.""" + +import tempfile +import shutil +from pathlib import Path +from unittest.mock import Mock, patch +import pytest +import torch + + +@pytest.fixture +def temp_dir(): + """Create a temporary directory for test files.""" + temp_dir = tempfile.mkdtemp() + yield Path(temp_dir) + shutil.rmtree(temp_dir) + + +@pytest.fixture +def temp_file(temp_dir): + """Create a temporary file for testing.""" + temp_file = temp_dir / "test_file.txt" + temp_file.write_text("test content") + return temp_file + + +@pytest.fixture +def sample_config(): + """Provide a sample configuration dictionary for testing.""" + return { + "model": { + "hidden_dim": 128, + "latent_dim": 64, + "num_layers": 3, + }, + "training": { + "learning_rate": 0.001, + "batch_size": 32, + "num_epochs": 100, + }, + "data": { + "dataset_name": "test_dataset", + "num_nodes": 1000, + } + } + + +@pytest.fixture +def mock_torch_device(): + """Mock torch device for consistent testing.""" + with patch('torch.cuda.is_available', return_value=False): + yield torch.device('cpu') + + +@pytest.fixture +def sample_tensor(): + """Create a sample tensor for testing.""" + return torch.randn(10, 5) + + +@pytest.fixture +def sample_graph_data(): + """Create sample graph data for testing.""" + # Simple graph with 5 nodes and some edges + edge_index = torch.tensor([[0, 1, 1, 2, 2, 3, 3, 4], + [1, 0, 2, 1, 3, 2, 4, 3]], dtype=torch.long) + x = torch.randn(5, 3) # 5 nodes with 3 features each + return { + 'x': x, + 'edge_index': edge_index, + 'num_nodes': 5, + 'num_edges': edge_index.size(1) + } + + +@pytest.fixture +def mock_model(): + """Create a mock model for testing.""" + mock = Mock() + mock.forward.return_value = (torch.randn(5, 2), torch.randn(5, 2)) # mean, log_var + mock.encode.return_value = torch.randn(5, 2) + mock.decode.return_value = torch.randn(5, 3) + mock.parameters.return_value = [torch.randn(10, 5, requires_grad=True)] + return mock + + +@pytest.fixture +def mock_optimizer(): + """Create a mock optimizer for testing.""" + mock = Mock() + mock.step.return_value = None + mock.zero_grad.return_value = None + return mock + + +@pytest.fixture +def mock_dataset(): + """Create a mock dataset for testing.""" + mock = Mock() + mock.__len__.return_value = 100 + mock.__getitem__.return_value = { + 'x': torch.randn(10, 3), + 'edge_index': torch.tensor([[0, 1], [1, 2]], dtype=torch.long).t() + } + return mock + + +@pytest.fixture(autouse=True) +def set_random_seeds(): + """Set random seeds for reproducible testing.""" + torch.manual_seed(42) + if torch.cuda.is_available(): + torch.cuda.manual_seed(42) + torch.cuda.manual_seed_all(42) + + +@pytest.fixture +def capture_logs(caplog): + """Fixture to capture and return logs for testing.""" + return caplog + + +@pytest.fixture +def mock_file_operations(): + """Mock file operations for testing without actual I/O.""" + with patch('builtins.open', mock_open(read_data="test data")): + with patch('os.path.exists', return_value=True): + with patch('os.makedirs'): + yield + + +def mock_open(read_data=""): + """Helper function to create a mock open function.""" + from unittest.mock import mock_open as _mock_open + return _mock_open(read_data=read_data) + + +@pytest.fixture +def isolated_environment(monkeypatch, temp_dir): + """Create an isolated environment for testing.""" + # Change to temporary directory + monkeypatch.chdir(temp_dir) + + # Set environment variables + monkeypatch.setenv("TEST_MODE", "true") + + yield temp_dir \ No newline at end of file diff --git a/tests/integration/__init__.py b/tests/integration/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/tests/test_infrastructure_validation.py b/tests/test_infrastructure_validation.py new file mode 100644 index 0000000..dc69ef7 --- /dev/null +++ b/tests/test_infrastructure_validation.py @@ -0,0 +1,106 @@ +"""Validation tests to ensure the testing infrastructure is working correctly.""" + +import pytest +import torch +from pathlib import Path + + +class TestInfrastructureValidation: + """Test class to validate the testing infrastructure setup.""" + + def test_pytest_is_working(self): + """Basic test to ensure pytest is functioning.""" + assert True + + def test_fixtures_are_available(self, temp_dir, sample_config): + """Test that shared fixtures are working.""" + assert isinstance(temp_dir, Path) + assert temp_dir.exists() + assert isinstance(sample_config, dict) + assert "model" in sample_config + + def test_torch_integration(self, sample_tensor, mock_torch_device): + """Test that PyTorch integration is working.""" + assert isinstance(sample_tensor, torch.Tensor) + assert sample_tensor.shape == (10, 5) + assert mock_torch_device == torch.device('cpu') + + def test_graph_data_fixture(self, sample_graph_data): + """Test that graph data fixtures work correctly.""" + assert 'x' in sample_graph_data + assert 'edge_index' in sample_graph_data + assert sample_graph_data['num_nodes'] == 5 + assert isinstance(sample_graph_data['x'], torch.Tensor) + assert isinstance(sample_graph_data['edge_index'], torch.Tensor) + + @pytest.mark.unit + def test_unit_marker(self): + """Test that unit test marker is working.""" + assert True + + @pytest.mark.integration + def test_integration_marker(self): + """Test that integration test marker is working.""" + assert True + + @pytest.mark.slow + def test_slow_marker(self): + """Test that slow test marker is working.""" + assert True + + def test_mock_model_fixture(self, mock_model): + """Test that mock model fixture is working.""" + assert hasattr(mock_model, 'forward') + assert hasattr(mock_model, 'encode') + assert hasattr(mock_model, 'decode') + + # Test mock model returns expected shapes + mean, log_var = mock_model.forward() + assert mean.shape == (5, 2) + assert log_var.shape == (5, 2) + + def test_temp_file_operations(self, temp_file): + """Test temporary file operations.""" + assert temp_file.exists() + assert temp_file.read_text() == "test content" + + def test_reproducible_random_seeds(self, sample_tensor): + """Test that random seeds are set for reproducible tests.""" + # Create another tensor with the same seed + torch.manual_seed(42) + other_tensor = torch.randn(10, 5) + + # They should be identical due to seed setting + torch.testing.assert_close(sample_tensor, other_tensor) + + def test_isolated_environment(self, isolated_environment): + """Test that isolated environment fixture works.""" + assert isinstance(isolated_environment, Path) + assert isolated_environment.exists() + + def test_coverage_excludes_test_files(self): + """Test that demonstrates coverage configuration.""" + # This test itself should be excluded from coverage + uncovered_code = "This line should be excluded from coverage" + assert uncovered_code is not None + + +def test_module_imports(): + """Test that we can import the main project modules.""" + try: + import config + assert True + except ImportError as e: + pytest.fail(f"Failed to import config module: {e}") + + # Skip other modules that have complex dependencies for now + # This allows the testing infrastructure to be validated independently + + +def test_torch_geometric_import(): + """Test that torch_geometric can be imported (when available).""" + try: + import torch_geometric + assert hasattr(torch_geometric, '__version__') + except ImportError: + pytest.skip("torch_geometric not available, skipping test") \ No newline at end of file diff --git a/tests/unit/__init__.py b/tests/unit/__init__.py new file mode 100644 index 0000000..e69de29