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+classifiers = [ + "Development Status :: 4 - Beta", + "Intended Audience :: Science/Research", + "License :: OSI Approved :: MIT License", + "Programming Language :: Python :: 3", + "Programming Language :: Python :: 3.8", + "Programming Language :: Python :: 3.9", + "Programming Language :: Python :: 3.10", + "Programming Language :: Python :: 3.11", + "Topic :: Scientific/Engineering :: Artificial Intelligence", +] +packages = [ + { include = "videomamba" }, + { include = "mamba/mamba_ssm" }, + { include = "causal-conv1d/causal_conv1d" } +] + +[tool.poetry.dependencies] +python = "^3.9" +# apex = "0.1" # NVIDIA apex needs to be installed separately from source +av = "11.0.0" +# decord = "0.6.0" # Optional - video decoding library +deepspeed = "0.13.1" +einops = "0.7.0" +ftfy = "6.1.3" +fvcore = "^0.1.5" +imageio = "2.33.1" +lm-eval = "0.4.1" +numpy = "1.26.4" +omegaconf = "2.3.0" +opencv-python = "4.8.1.78" +packaging = "24.0" +pandas = "2.2.1" +pillow = "10.1.0" +pyyaml = "6.0.1" 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TYPE_CHECKING:", + "class .*\\bProtocol\\):", + "@(abc\\.)?abstractmethod", +] +precision = 2 +show_missing = true +skip_covered = false +sort = "Cover" + +[tool.coverage.html] +directory = "htmlcov" + +[tool.coverage.xml] +output = "coverage.xml" + +[tool.isort] +profile = "black" +line_length = 100 +multi_line_output = 3 +include_trailing_comma = true +force_grid_wrap = 0 +use_parentheses = true +ensure_newline_before_comments = true + +[tool.black] +line-length = 100 +target-version = ['py38', 'py39', 'py310', 'py311'] +include = '\.pyi?$' +extend-exclude = ''' +/( + # directories + \.eggs + | \.git + | \.hg + | \.mypy_cache + | \.tox + | \.venv + | build + | dist +)/ +''' + +[tool.mypy] +python_version = "3.8" +warn_return_any = true +warn_unused_configs = true +disallow_untyped_defs = false +disallow_incomplete_defs = false +check_untyped_defs = true +no_implicit_optional = true +warn_redundant_casts = true +warn_unused_ignores = true +warn_no_return = true +follow_imports = "normal" +ignore_missing_imports = true \ No newline at end of file diff --git a/tests/__init__.py b/tests/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/tests/conftest.py b/tests/conftest.py new file mode 100644 index 0000000..c1166b4 --- /dev/null +++ b/tests/conftest.py @@ -0,0 +1,193 @@ +""" +Shared pytest fixtures and configuration for VideoMamba tests. +""" +import os +import shutil +import tempfile +from pathlib import Path +from typing import Dict, Generator, Any + +import pytest +import torch +import numpy as np +from omegaconf import OmegaConf + + +@pytest.fixture +def temp_dir() -> Generator[Path, None, None]: + """Create a temporary directory that's cleaned up after the test.""" + temp_path = tempfile.mkdtemp() + yield Path(temp_path) + shutil.rmtree(temp_path) + + +@pytest.fixture +def sample_config() -> Dict[str, Any]: + """Provide a sample configuration dictionary for testing.""" + return { + "model": { + "name": "videomamba_tiny", + "num_classes": 400, + "drop_rate": 0.0, + "drop_path_rate": 0.1, + "head_drop_rate": 0.0, + }, + "data": { + "dataset": "kinetics400", + "num_frames": 16, + "sampling_rate": 4, + "num_workers": 8, + "batch_size": 32, + }, + "optimization": { + "lr": 1e-4, + "min_lr": 1e-6, + "warmup_epochs": 5, + "epochs": 30, + "weight_decay": 0.05, + }, + } + + +@pytest.fixture +def omega_config(sample_config: Dict[str, Any]) -> OmegaConf: + """Create an OmegaConf configuration object.""" + return OmegaConf.create(sample_config) + + +@pytest.fixture +def mock_video_tensor() -> torch.Tensor: + """Create a mock video tensor for testing (B, C, T, H, W).""" + batch_size = 2 + channels = 3 + num_frames = 16 + height = 224 + width = 224 + return torch.randn(batch_size, channels, num_frames, height, width) + + +@pytest.fixture +def mock_image_tensor() -> torch.Tensor: + """Create a mock image tensor for testing (B, C, H, W).""" + batch_size = 4 + channels = 3 + height = 224 + width = 224 + return torch.randn(batch_size, channels, height, width) + + +@pytest.fixture +def mock_labels() -> torch.Tensor: + """Create mock classification labels.""" + batch_size = 4 + num_classes = 400 + return torch.randint(0, num_classes, (batch_size,)) + + +@pytest.fixture +def device() -> torch.device: + """Get the appropriate device for testing (cuda if available, else cpu).""" + return torch.device("cuda" if torch.cuda.is_available() else "cpu") + + +@pytest.fixture(autouse=True) +def reset_random_seeds(): + """Reset random seeds before each test for reproducibility.""" + torch.manual_seed(42) + np.random.seed(42) + if torch.cuda.is_available(): + torch.cuda.manual_seed_all(42) + + +@pytest.fixture +def mock_checkpoint(temp_dir: Path) -> Path: + """Create a mock checkpoint file.""" + checkpoint_path = temp_dir / "mock_checkpoint.pth" + checkpoint_data = { + "model": {"dummy_weight": torch.randn(10, 10)}, + "optimizer": {"lr": 0.001}, + "epoch": 10, + "best_acc": 0.85, + } + torch.save(checkpoint_data, checkpoint_path) + return checkpoint_path + + +@pytest.fixture +def mock_video_file(temp_dir: Path) -> Path: + """Create a mock video file path (doesn't create actual video).""" + video_path = temp_dir / "test_video.mp4" + video_path.touch() # Create empty file + return video_path + + +@pytest.fixture +def mock_dataset_root(temp_dir: Path) -> Path: + """Create a mock dataset directory structure.""" + dataset_root = temp_dir / "mock_dataset" + dataset_root.mkdir() + + # Create some mock class directories + for i in range(5): + class_dir = dataset_root / f"class_{i:03d}" + class_dir.mkdir() + + # Create some mock video files + for j in range(3): + video_file = class_dir / f"video_{j:03d}.mp4" + video_file.touch() + + return dataset_root + + +@pytest.fixture +def mock_transforms(): + """Provide mock transform configuration.""" + from torchvision import transforms + + return transforms.Compose([ + transforms.Resize((224, 224)), + transforms.ToTensor(), + transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]), + ]) + + +@pytest.fixture(scope="session") +def test_data_dir() -> Path: + """Get the path to test data directory.""" + return Path(__file__).parent / "data" + + +@pytest.fixture +def cleanup_files(): + """Fixture to track and cleanup files created during tests.""" + files_to_cleanup = [] + + def add_file(filepath: Path): + files_to_cleanup.append(filepath) + + yield add_file + + # Cleanup + for filepath in files_to_cleanup: + if filepath.exists(): + if filepath.is_file(): + filepath.unlink() + elif filepath.is_dir(): + shutil.rmtree(filepath) + + +@pytest.fixture +def monkeypatch_env(monkeypatch): + """Fixture to safely set environment variables during tests.""" + def setenv(key: str, value: str): + monkeypatch.setenv(key, value) + + return setenv + + +@pytest.fixture +def capture_logs(caplog): + """Fixture to capture and assert on log messages.""" + with caplog.at_level("DEBUG"): + yield caplog \ 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_setup_validation.py b/tests/test_setup_validation.py new file mode 100644 index 0000000..b4ee688 --- /dev/null +++ b/tests/test_setup_validation.py @@ -0,0 +1,186 @@ +""" +Validation tests to ensure the testing infrastructure is properly set up. +""" +import sys +from pathlib import Path + +import pytest +import torch +import numpy as np + + +class TestInfrastructureSetup: + """Test class to validate the testing infrastructure setup.""" + + def test_python_version(self): + """Verify Python version is 3.8 or higher.""" + assert sys.version_info >= (3, 8), "Python 3.8+ is required" + + def test_pytest_installed(self): + """Verify pytest is properly installed.""" + import pytest + assert pytest.__version__ >= "8.0.0" + + def test_coverage_tools_installed(self): + """Verify coverage tools are installed.""" + import pytest_cov + import coverage + assert pytest_cov is not None + assert coverage is not None + + def test_mock_tools_installed(self): + """Verify mocking tools are installed.""" + import pytest_mock + from unittest.mock import Mock, MagicMock, patch + assert pytest_mock is not None + assert Mock is not None + + def test_torch_available(self): + """Verify PyTorch is available.""" + assert torch is not None + assert torch.__version__ is not None + + def test_numpy_available(self): + """Verify NumPy is available.""" + assert np is not None + assert np.__version__ is not None + + def test_directory_structure(self): + """Verify the test directory structure is correct.""" + test_root = Path(__file__).parent + assert test_root.exists() + assert (test_root / "__init__.py").exists() + assert (test_root / "conftest.py").exists() + assert (test_root / "unit").exists() + assert (test_root / "unit" / "__init__.py").exists() + assert (test_root / "integration").exists() + assert (test_root / "integration" / "__init__.py").exists() + + def test_project_structure(self): + """Verify the main project structure is accessible.""" + project_root = Path(__file__).parent.parent + assert (project_root / "videomamba").exists() + assert (project_root / "mamba").exists() + assert (project_root / "pyproject.toml").exists() + + @pytest.mark.unit + def test_unit_marker(self): + """Test that unit test marker works.""" + assert True + + @pytest.mark.integration + def test_integration_marker(self): + """Test that integration test marker works.""" + assert True + + @pytest.mark.slow + def test_slow_marker(self): + """Test that slow test marker works.""" + assert True + + def test_fixtures_available(self, temp_dir, sample_config, mock_video_tensor): + """Test that custom fixtures from conftest.py are available.""" + assert temp_dir.exists() + assert isinstance(sample_config, dict) + assert "model" in sample_config + assert mock_video_tensor.shape == (2, 3, 16, 224, 224) + + def test_temp_dir_cleanup(self, temp_dir): + """Test that temp_dir fixture properly creates and will clean up directories.""" + test_file = temp_dir / "test.txt" + test_file.write_text("test content") + assert test_file.exists() + # Cleanup will happen automatically after test + + def test_device_fixture(self, device): + """Test that device fixture returns appropriate device.""" + assert isinstance(device, torch.device) + assert device.type in ["cpu", "cuda"] + + def test_random_seed_reset(self): + """Test that random seeds are properly reset.""" + # First random number should be deterministic due to seed reset + first_torch = torch.rand(1).item() + first_numpy = np.random.rand() + + # These should be the same across test runs due to autouse fixture + assert 0 < first_torch < 1 + assert 0 < first_numpy < 1 + + def test_mock_checkpoint(self, mock_checkpoint): + """Test mock checkpoint fixture.""" + assert mock_checkpoint.exists() + data = torch.load(mock_checkpoint, weights_only=True) + assert "model" in data + assert "optimizer" in data + assert "epoch" in data + assert data["epoch"] == 10 + + def test_coverage_configured(self): + """Test that coverage is properly configured.""" + import coverage + cov = coverage.Coverage() + config = cov.config + # Just verify coverage can be instantiated + assert cov is not None + + +class TestPoetryCommands: + """Test Poetry script commands configuration.""" + + def test_pyproject_exists(self): + """Verify pyproject.toml exists.""" + pyproject_path = Path(__file__).parent.parent / "pyproject.toml" + assert pyproject_path.exists(), "pyproject.toml should exist" + + def test_poetry_scripts_configured(self): + """Verify Poetry scripts are configured.""" + try: + import tomllib # Python 3.11+ + except ImportError: + import tomli as tomllib # Python 3.9-3.10 + + pyproject_path = Path(__file__).parent.parent / "pyproject.toml" + + with open(pyproject_path, "rb") as f: + pyproject_data = tomllib.load(f) + + # Check Poetry scripts section + assert "tool" in pyproject_data + assert "poetry" in pyproject_data["tool"] + assert "scripts" in pyproject_data["tool"]["poetry"] + + scripts = pyproject_data["tool"]["poetry"]["scripts"] + assert "test" in scripts + assert "tests" in scripts + assert scripts["test"] == "pytest:main" + assert scripts["tests"] == "pytest:main" + + def test_pytest_configuration(self): + """Verify pytest is properly configured in pyproject.toml.""" + try: + import tomllib # Python 3.11+ + except ImportError: + import tomli as tomllib # Python 3.9-3.10 + + pyproject_path = Path(__file__).parent.parent / "pyproject.toml" + + with open(pyproject_path, "rb") as f: + pyproject_data = tomllib.load(f) + + # Check pytest configuration + assert "tool" in pyproject_data + assert "pytest" in pyproject_data["tool"] + assert "ini_options" in pyproject_data["tool"]["pytest"] + + pytest_config = pyproject_data["tool"]["pytest"]["ini_options"] + assert "testpaths" in pytest_config + assert "tests" in pytest_config["testpaths"] + assert "markers" in pytest_config + assert 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