diff --git a/.gitignore b/.gitignore
new file mode 100644
index 0000000..44a95a3
--- /dev/null
+++ b/.gitignore
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+*.py[cod]
+*$py.class
+
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+*.so
+
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+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+cover/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+.pybuilder/
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+.python-version
+
+# pipenv
+Pipfile.lock
+
+# poetry
+# Note: Do not ignore poetry.lock - it should be committed
+# poetry.lock is intentionally not ignored
+
+# pdm
+.pdm.toml
+.pdm-python
+.pdm-build/
+
+# PEP 582
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# pytype static type analyzer
+.pytype/
+
+# Cython debug symbols
+cython_debug/
+
+# PyCharm
+.idea/
+
+# Visual Studio Code
+.vscode/
+
+# Claude settings and history
+.claude/*
+
+# macOS
+.DS_Store
+
+# Windows
+Thumbs.db
+ehthumbs.db
+Desktop.ini
+
+# Linux
+*~
+
+# Temporary files
+*.tmp
+*.temp
+*.swp
+*.swo
+*.bak
+
+# Model weights and checkpoints (usually large files)
+*.pth
+*.pt
+*.h5
+*.ckpt
+*.safetensors
+checkpoints/
+weights/
+models/
+
+# Data files (often large)
+data/raw/
+data/processed/
+datasets/
+
+# Output and results
+outputs/
+results/
+runs/
+logs/
+tensorboard/
+
+# CUDA build artifacts
+*.cu.o
+*.cu.cpp
+model/cuda/build/
+model/cuda/*.so
+
+# Testing artifacts
+test_output/
+test_results/
+.benchmarks/
+
+# Documentation build
+docs/build/
+docs/_generated/
+
+# Secrets and credentials
+*.key
+*.pem
+*.crt
+secrets/
+credentials/
\ No newline at end of file
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index 0000000..e46db32
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+description = "Backport of pathlib-compatible object wrapper for zip files"
+optional = false
+python-versions = ">=3.9"
+groups = ["main"]
+markers = "python_version == \"3.9\""
+files = [
+    {file = "zipp-3.23.0-py3-none-any.whl", hash = "sha256:071652d6115ed432f5ce1d34c336c0adfd6a884660d1e9712a256d3d3bd4b14e"},
+    {file = "zipp-3.23.0.tar.gz", hash = "sha256:a07157588a12518c9d4034df3fbbee09c814741a33ff63c05fa29d26a2404166"},
+]
+
+[package.extras]
+check = ["pytest-checkdocs (>=2.4)", "pytest-ruff (>=0.2.1) ; sys_platform != \"cygwin\""]
+cover = ["pytest-cov"]
+doc = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
+enabler = ["pytest-enabler (>=2.2)"]
+test = ["big-O", "jaraco.functools", "jaraco.itertools", "jaraco.test", "more_itertools", "pytest (>=6,!=8.1.*)", "pytest-ignore-flaky"]
+type = ["pytest-mypy"]
+
+[metadata]
+lock-version = "2.1"
+python-versions = "^3.9"
+content-hash = "bda3d6eabdf894f44354d4a46c46a247b4b1c97c94e680c59fe599465bf3f13e"
diff --git a/pyproject.toml b/pyproject.toml
new file mode 100644
index 0000000..bcc8afc
--- /dev/null
+++ b/pyproject.toml
@@ -0,0 +1,169 @@
+[tool.poetry]
+name = "restore-rwkv"
+version = "0.1.0"
+description = "Medical Image Restoration with RWKV"
+authors = ["Your Name <you@example.com>"]
+readme = "README.md"
+license = "MIT"
+packages = [{include = "."}]
+
+[tool.poetry.dependencies]
+python = "^3.9"
+torch = "^2.0.0"
+torchvision = "^0.15.0"
+numpy = "^1.24.0"
+tqdm = "^4.66.0"
+pillow = "^10.0.0"
+scipy = "^1.10.0"
+scikit-image = "^0.21.0"
+matplotlib = "^3.7.0"
+einops = "^0.7.0"
+simpleitk = "^2.3.0"
+pandas = "^2.0.0"
+setuptools = "^69.0.0"
+
+[tool.poetry.group.dev.dependencies]
+pytest = "^8.0.0"
+pytest-cov = "^5.0.0"
+pytest-mock = "^3.12.0"
+pytest-xdist = "^3.5.0"
+black = "^24.0.0"
+isort = "^5.13.0"
+flake8 = "^7.0.0"
+mypy = "^1.8.0"
+pre-commit = "^3.6.0"
+
+
+[tool.pytest.ini_options]
+minversion = "8.0"
+addopts = [
+    "-ra",
+    "--strict-markers",
+    "--strict-config",
+    "--cov=.",
+    "--cov-branch",
+    "--cov-report=term-missing:skip-covered",
+    "--cov-report=html:htmlcov",
+    "--cov-report=xml:coverage.xml",
+    "--cov-fail-under=0",
+    "-vv",
+]
+testpaths = ["tests"]
+python_files = ["test_*.py", "*_test.py"]
+python_classes = ["Test*"]
+python_functions = ["test_*"]
+markers = [
+    "unit: Unit tests",
+    "integration: Integration tests",
+    "slow: Slow running tests",
+    "skip: Skip test",
+]
+filterwarnings = [
+    "error",
+    "ignore::UserWarning",
+    "ignore::DeprecationWarning",
+]
+norecursedirs = [
+    ".git",
+    ".tox",
+    "dist",
+    "build",
+    "*.egg",
+    "__pycache__",
+    ".pytest_cache",
+    "htmlcov",
+]
+
+[tool.coverage.run]
+source = ["."]
+branch = true
+parallel = true
+omit = [
+    "*/tests/*",
+    "*/test_*.py",
+    "*/__pycache__/*",
+    "*/site-packages/*",
+    "*/dist-packages/*",
+    "*/venv/*",
+    "*/.venv/*",
+    "*/setup.py",
+    "*/conftest.py",
+    "*/.pytest_cache/*",
+    "*/htmlcov/*",
+    "*/model/cuda/*",
+]
+
+[tool.coverage.report]
+exclude_lines = [
+    "pragma: no cover",
+    "def __repr__",
+    "def __str__",
+    "raise AssertionError",
+    "raise NotImplementedError",
+    "if __name__ == .__main__.:",
+    "if TYPE_CHECKING:",
+    "if typing.TYPE_CHECKING:",
+    "@abstractmethod",
+    "@abc.abstractmethod",
+    "except ImportError",
+    "pass",
+]
+precision = 2
+show_missing = true
+skip_covered = false
+skip_empty = true
+sort = "Cover"
+fail_under = 80
+
+[tool.coverage.html]
+directory = "htmlcov"
+title = "Restore RWKV Coverage Report"
+
+[tool.coverage.xml]
+output = "coverage.xml"
+
+[tool.isort]
+profile = "black"
+multi_line_output = 3
+include_trailing_comma = true
+force_grid_wrap = 0
+use_parentheses = true
+ensure_newline_before_comments = true
+line_length = 88
+skip_gitignore = true
+
+[tool.black]
+line-length = 88
+target-version = ['py38', 'py39', 'py310', 'py311']
+include = '\.pyi?$'
+extend-exclude = '''
+/(
+  # directories
+  \.eggs
+  | \.git
+  | \.hg
+  | \.mypy_cache
+  | \.tox
+  | \.venv
+  | _build
+  | buck-out
+  | build
+  | dist
+  | model/cuda
+)/
+'''
+
+[tool.mypy]
+python_version = "3.8"
+warn_return_any = true
+warn_unused_configs = true
+disallow_untyped_defs = false
+ignore_missing_imports = true
+exclude = [
+    "tests/",
+    "model/cuda/",
+]
+
+[build-system]
+requires = ["poetry-core>=1.0.0"]
+build-backend = "poetry.core.masonry.api"
\ No newline at end of file
diff --git a/run_tests.sh b/run_tests.sh
new file mode 100755
index 0000000..5720bbe
--- /dev/null
+++ b/run_tests.sh
@@ -0,0 +1,10 @@
+#!/bin/bash
+# Test runner script for the project
+
+# Run all tests
+if [ "$1" == "" ]; then
+    poetry run pytest
+# Run specific test file or directory
+else
+    poetry run pytest "$@"
+fi
\ 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..6bd7b29
--- /dev/null
+++ b/tests/conftest.py
@@ -0,0 +1,261 @@
+import os
+import sys
+import tempfile
+import shutil
+from pathlib import Path
+from typing import Generator, Dict, Any, List
+from unittest.mock import MagicMock
+
+import pytest
+import torch
+import numpy as np
+from PIL import Image
+
+
+sys.path.insert(0, str(Path(__file__).parent.parent))
+
+
+@pytest.fixture
+def temp_dir() -> Generator[Path, None, None]:
+    """Create a temporary directory for test files."""
+    temp_path = Path(tempfile.mkdtemp())
+    try:
+        yield temp_path
+    finally:
+        if temp_path.exists():
+            shutil.rmtree(temp_path)
+
+
+@pytest.fixture
+def mock_config() -> Dict[str, Any]:
+    """Provide a mock configuration dictionary."""
+    return {
+        "model": {
+            "name": "Restore_RWKV",
+            "channels": 3,
+            "layers": 4,
+            "hidden_dim": 128,
+        },
+        "training": {
+            "batch_size": 4,
+            "learning_rate": 1e-4,
+            "epochs": 10,
+            "device": "cpu",
+        },
+        "data": {
+            "root_dir": "/tmp/test_data",
+            "modalities": ["CT", "MRI", "PET"],
+            "image_size": 256,
+        },
+        "paths": {
+            "checkpoint_dir": "/tmp/checkpoints",
+            "log_dir": "/tmp/logs",
+            "output_dir": "/tmp/outputs",
+        }
+    }
+
+
+@pytest.fixture
+def sample_image_tensor() -> torch.Tensor:
+    """Create a sample image tensor for testing."""
+    return torch.randn(1, 3, 256, 256)
+
+
+@pytest.fixture
+def batch_image_tensor() -> torch.Tensor:
+    """Create a batch of image tensors for testing."""
+    return torch.randn(4, 3, 256, 256)
+
+
+@pytest.fixture
+def sample_numpy_image() -> np.ndarray:
+    """Create a sample numpy image array."""
+    return np.random.rand(256, 256, 3).astype(np.float32)
+
+
+@pytest.fixture
+def sample_pil_image() -> Image.Image:
+    """Create a sample PIL image."""
+    array = np.random.randint(0, 255, (256, 256, 3), dtype=np.uint8)
+    return Image.fromarray(array)
+
+
+@pytest.fixture
+def mock_model():
+    """Create a mock model for testing."""
+    model = MagicMock()
+    model.eval = MagicMock(return_value=model)
+    model.train = MagicMock(return_value=model)
+    model.parameters = MagicMock(return_value=[torch.randn(10, 10)])
+    model.state_dict = MagicMock(return_value={"layer1.weight": torch.randn(10, 10)})
+    model.load_state_dict = MagicMock()
+    model.cuda = MagicMock(return_value=model)
+    model.cpu = MagicMock(return_value=model)
+    model.to = MagicMock(return_value=model)
+    model.forward = MagicMock(return_value=torch.randn(4, 3, 256, 256))
+    return model
+
+
+@pytest.fixture
+def mock_dataloader():
+    """Create a mock dataloader for testing."""
+    dataloader = MagicMock()
+    dataloader.__iter__ = MagicMock(return_value=iter([
+        (torch.randn(4, 3, 256, 256), torch.randn(4, 3, 256, 256))
+        for _ in range(5)
+    ]))
+    dataloader.__len__ = MagicMock(return_value=5)
+    return dataloader
+
+
+@pytest.fixture
+def mock_optimizer():
+    """Create a mock optimizer for testing."""
+    optimizer = MagicMock()
+    optimizer.zero_grad = MagicMock()
+    optimizer.step = MagicMock()
+    optimizer.state_dict = MagicMock(return_value={"state": {}, "param_groups": []})
+    optimizer.load_state_dict = MagicMock()
+    return optimizer
+
+
+@pytest.fixture
+def mock_scheduler():
+    """Create a mock learning rate scheduler."""
+    scheduler = MagicMock()
+    scheduler.step = MagicMock()
+    scheduler.get_last_lr = MagicMock(return_value=[1e-4])
+    return scheduler
+
+
+@pytest.fixture
+def sample_medical_data(temp_dir: Path) -> Dict[str, Path]:
+    """Create sample medical imaging data files."""
+    data_paths = {}
+    modalities = ["CT", "MRI", "PET"]
+    
+    for modality in modalities:
+        modality_dir = temp_dir / modality
+        modality_dir.mkdir(exist_ok=True)
+        
+        for i in range(3):
+            img_path = modality_dir / f"sample_{i:03d}.png"
+            img = Image.fromarray(
+                np.random.randint(0, 255, (256, 256), dtype=np.uint8)
+            )
+            img.save(img_path)
+            
+        data_paths[modality] = modality_dir
+    
+    return data_paths
+
+
+@pytest.fixture
+def mock_loss_function():
+    """Create a mock loss function."""
+    loss_fn = MagicMock()
+    loss_fn.forward = MagicMock(return_value=torch.tensor(0.5))
+    loss_fn.__call__ = MagicMock(return_value=torch.tensor(0.5))
+    return loss_fn
+
+
+@pytest.fixture
+def device():
+    """Provide the appropriate device for testing."""
+    return torch.device("cuda" if torch.cuda.is_available() else "cpu")
+
+
+@pytest.fixture
+def random_seed():
+    """Set random seeds for reproducibility."""
+    seed = 42
+    torch.manual_seed(seed)
+    np.random.seed(seed)
+    if torch.cuda.is_available():
+        torch.cuda.manual_seed(seed)
+        torch.cuda.manual_seed_all(seed)
+    return seed
+
+
+@pytest.fixture(autouse=True)
+def cleanup_cuda():
+    """Clean up CUDA memory after each test."""
+    yield
+    if torch.cuda.is_available():
+        torch.cuda.empty_cache()
+
+
+@pytest.fixture
+def mock_transform():
+    """Create a mock transform function."""
+    def transform(x):
+        if isinstance(x, Image.Image):
+            return torch.randn(3, 256, 256)
+        return x
+    return transform
+
+
+@pytest.fixture
+def sample_checkpoint(temp_dir: Path) -> Path:
+    """Create a sample checkpoint file."""
+    checkpoint_path = temp_dir / "checkpoint.pth"
+    checkpoint = {
+        "epoch": 10,
+        "model_state_dict": {"layer1.weight": torch.randn(10, 10)},
+        "optimizer_state_dict": {"state": {}, "param_groups": []},
+        "loss": 0.123,
+        "metrics": {"psnr": 30.5, "ssim": 0.89}
+    }
+    torch.save(checkpoint, checkpoint_path)
+    return checkpoint_path
+
+
+@pytest.fixture
+def capture_stdout(monkeypatch):
+    """Capture stdout for testing print statements."""
+    import io
+    buffer = io.StringIO()
+    
+    def get_output():
+        return buffer.getvalue()
+    
+    monkeypatch.setattr(sys, "stdout", buffer)
+    return get_output
+
+
+@pytest.fixture
+def mock_tqdm(mocker):
+    """Mock tqdm progress bar."""
+    return mocker.patch("tqdm.tqdm", side_effect=lambda x, **kwargs: x)
+
+
+@pytest.fixture
+def isolated_filesystem(tmp_path):
+    """Create an isolated filesystem for testing."""
+    original_cwd = os.getcwd()
+    os.chdir(tmp_path)
+    try:
+        yield tmp_path
+    finally:
+        os.chdir(original_cwd)
+
+
+@pytest.fixture
+def sample_metrics() -> Dict[str, float]:
+    """Provide sample evaluation metrics."""
+    return {
+        "psnr": 28.5,
+        "ssim": 0.85,
+        "mae": 0.015,
+        "mse": 0.0025,
+        "ncc": 0.92,
+    }
+
+
+@pytest.fixture
+def mock_cuda_kernel(mocker):
+    """Mock CUDA kernel operations."""
+    mock = mocker.patch("torch.utils.cpp_extension.load")
+    mock.return_value.forward = MagicMock(return_value=torch.randn(4, 128, 256, 256))
+    mock.return_value.backward = MagicMock(return_value=(torch.randn(4, 128, 256, 256),))
+    return mock
\ 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..b1a1dcd
--- /dev/null
+++ b/tests/test_infrastructure_validation.py
@@ -0,0 +1,232 @@
+import sys
+from pathlib import Path
+
+import pytest
+import torch
+import numpy as np
+from PIL import Image
+
+
+class TestInfrastructureValidation:
+    """Validation tests to ensure the testing infrastructure is properly set up."""
+    
+    def test_python_version(self):
+        """Test that Python version meets requirements."""
+        assert sys.version_info >= (3, 8), "Python 3.8+ is required"
+    
+    def test_pytest_available(self):
+        """Test that pytest is properly installed."""
+        assert pytest.__version__, "pytest should be installed"
+    
+    def test_coverage_plugin(self):
+        """Test that pytest-cov plugin is available."""
+        import pytest_cov
+        assert pytest_cov, "pytest-cov should be installed"
+    
+    def test_mock_plugin(self):
+        """Test that pytest-mock plugin is available."""
+        import pytest_mock
+        assert pytest_mock, "pytest-mock should be installed"
+    
+    def test_torch_available(self):
+        """Test that PyTorch is properly installed."""
+        assert torch.__version__, "PyTorch should be installed"
+        tensor = torch.tensor([1.0, 2.0, 3.0])
+        assert tensor.shape == (3,)
+    
+    def test_numpy_available(self):
+        """Test that NumPy is properly installed."""
+        assert np.__version__, "NumPy should be installed"
+        array = np.array([1, 2, 3])
+        assert array.shape == (3,)
+    
+    def test_pillow_available(self):
+        """Test that Pillow is properly installed."""
+        assert Image, "Pillow should be installed"
+        img = Image.new('RGB', (10, 10))
+        assert img.size == (10, 10)
+    
+    @pytest.mark.unit
+    def test_unit_marker(self):
+        """Test that the unit test marker works."""
+        assert True, "Unit test marker should work"
+    
+    @pytest.mark.integration
+    def test_integration_marker(self):
+        """Test that the integration test marker works."""
+        assert True, "Integration test marker should work"
+    
+    @pytest.mark.slow
+    def test_slow_marker(self):
+        """Test that the slow test marker works."""
+        assert True, "Slow test marker should work"
+    
+    def test_project_imports(self):
+        """Test that project modules can be imported."""
+        try:
+            from tools import set_seeds, mkdir
+            assert set_seeds is not None
+            assert mkdir is not None
+        except ImportError as e:
+            pytest.fail(f"Failed to import project modules: {e}")
+    
+    def test_data_module_imports(self):
+        """Test that data modules can be imported."""
+        try:
+            from data.common import transformData, dataIO
+            assert transformData is not None
+            assert dataIO is not None
+        except ImportError as e:
+            pytest.fail(f"Failed to import data modules: {e}")
+    
+    @pytest.mark.skip(reason="Model requires CUDA kernel compilation")
+    def test_model_module_imports(self):
+        """Test that model modules can be imported."""
+        try:
+            from model import Restore_RWKV
+            assert Restore_RWKV is not None
+        except ImportError as e:
+            pytest.fail(f"Failed to import model modules: {e}")
+    
+    def test_evaluation_module_imports(self):
+        """Test that evaluation modules can be imported."""
+        try:
+            from evaluation.evaluation_metric import compute_measure
+            assert compute_measure is not None
+        except ImportError as e:
+            pytest.fail(f"Failed to import evaluation modules: {e}")
+    
+    def test_loss_module_imports(self):
+        """Test that loss modules can be imported."""
+        try:
+            from loss import losses
+            assert losses is not None
+        except ImportError as e:
+            pytest.fail(f"Failed to import loss modules: {e}")
+
+
+class TestFixturesValidation:
+    """Tests to validate that all fixtures work correctly."""
+    
+    def test_temp_dir_fixture(self, temp_dir):
+        """Test that temp_dir fixture creates and cleans up properly."""
+        assert temp_dir.exists()
+        assert temp_dir.is_dir()
+        test_file = temp_dir / "test.txt"
+        test_file.write_text("test")
+        assert test_file.exists()
+    
+    def test_mock_config_fixture(self, mock_config):
+        """Test that mock_config fixture provides valid configuration."""
+        assert "model" in mock_config
+        assert "training" in mock_config
+        assert "data" in mock_config
+        assert "paths" in mock_config
+        assert mock_config["model"]["name"] == "Restore_RWKV"
+    
+    def test_sample_image_tensor_fixture(self, sample_image_tensor):
+        """Test that sample_image_tensor fixture creates valid tensor."""
+        assert isinstance(sample_image_tensor, torch.Tensor)
+        assert sample_image_tensor.shape == (1, 3, 256, 256)
+    
+    def test_batch_image_tensor_fixture(self, batch_image_tensor):
+        """Test that batch_image_tensor fixture creates valid batch."""
+        assert isinstance(batch_image_tensor, torch.Tensor)
+        assert batch_image_tensor.shape == (4, 3, 256, 256)
+    
+    def test_sample_numpy_image_fixture(self, sample_numpy_image):
+        """Test that sample_numpy_image fixture creates valid array."""
+        assert isinstance(sample_numpy_image, np.ndarray)
+        assert sample_numpy_image.shape == (256, 256, 3)
+        assert sample_numpy_image.dtype == np.float32
+    
+    def test_sample_pil_image_fixture(self, sample_pil_image):
+        """Test that sample_pil_image fixture creates valid PIL image."""
+        assert isinstance(sample_pil_image, Image.Image)
+        assert sample_pil_image.size == (256, 256)
+    
+    def test_mock_model_fixture(self, mock_model):
+        """Test that mock_model fixture works correctly."""
+        assert hasattr(mock_model, 'eval')
+        assert hasattr(mock_model, 'train')
+        assert hasattr(mock_model, 'parameters')
+        result = mock_model.forward(torch.randn(4, 3, 256, 256))
+        assert result.shape == (4, 3, 256, 256)
+    
+    def test_mock_dataloader_fixture(self, mock_dataloader):
+        """Test that mock_dataloader fixture works correctly."""
+        assert len(mock_dataloader) == 5
+        for batch in mock_dataloader:
+            assert len(batch) == 2
+            break
+    
+    def test_mock_optimizer_fixture(self, mock_optimizer):
+        """Test that mock_optimizer fixture works correctly."""
+        assert hasattr(mock_optimizer, 'zero_grad')
+        assert hasattr(mock_optimizer, 'step')
+        mock_optimizer.zero_grad()
+        mock_optimizer.step()
+    
+    def test_sample_medical_data_fixture(self, sample_medical_data):
+        """Test that sample_medical_data fixture creates valid data."""
+        assert "CT" in sample_medical_data
+        assert "MRI" in sample_medical_data
+        assert "PET" in sample_medical_data
+        for modality, path in sample_medical_data.items():
+            assert path.exists()
+            assert path.is_dir()
+            images = list(path.glob("*.png"))
+            assert len(images) == 3
+    
+    def test_device_fixture(self, device):
+        """Test that device fixture returns valid device."""
+        assert isinstance(device, torch.device)
+        assert device.type in ['cpu', 'cuda']
+    
+    def test_random_seed_fixture(self, random_seed):
+        """Test that random_seed fixture sets seeds properly."""
+        assert random_seed == 42
+        tensor1 = torch.randn(10)
+        torch.manual_seed(42)
+        tensor2 = torch.randn(10)
+        assert torch.allclose(tensor1, tensor2)
+    
+    def test_sample_checkpoint_fixture(self, sample_checkpoint):
+        """Test that sample_checkpoint fixture creates valid checkpoint."""
+        assert sample_checkpoint.exists()
+        checkpoint = torch.load(sample_checkpoint, map_location='cpu')
+        assert "epoch" in checkpoint
+        assert "model_state_dict" in checkpoint
+        assert "optimizer_state_dict" in checkpoint
+        assert checkpoint["epoch"] == 10
+    
+    def test_sample_metrics_fixture(self, sample_metrics):
+        """Test that sample_metrics fixture provides valid metrics."""
+        assert "psnr" in sample_metrics
+        assert "ssim" in sample_metrics
+        assert sample_metrics["psnr"] == 28.5
+        assert sample_metrics["ssim"] == 0.85
+
+
+@pytest.mark.parametrize("test_input,expected", [
+    (1, 1),
+    (2, 4),
+    (3, 9),
+    (4, 16),
+])
+def test_parametrized_example(test_input, expected):
+    """Example of parametrized test to verify functionality."""
+    assert test_input ** 2 == expected
+
+
+def test_skip_example():
+    """Example of a test that can be skipped."""
+    if sys.platform == "win32":
+        pytest.skip("Skipping on Windows")
+    assert True
+
+
+def test_xfail_example():
+    """Example of a test expected to fail."""
+    pytest.xfail("This test is expected to fail")
+    assert False
\ 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