✨ [New] make it pip installable!

pyproject.toml

@@ -1,16 +1,25 @@
 [project]
 name = "yolo"
-version = "0.0.0"
+version = "0.1.0"
 dynamic = ["dependencies"]
 
 [tool.setuptools.dynamic]
 dependencies = {file = ["requirements.txt"]}
 
 [tool.setuptools.packages.find]
-where = ["yolo"]
+where = ["."]
+include = ["yolo*"]
+
+[tool.setuptools]
+package-data = {"yolo" = ["**/*.yaml"]}
+include-package-data = true
+
 
 [build-system]
 build-backend = "setuptools.build_meta"
 requires = [
     "setuptools",
 ]
+
+[project.scripts]
+yolo = "yolo.lazy:main"

yolo/lazy.py

@@ -0,0 +1,35 @@
+import sys
+from pathlib import Path
+
+import hydra
+import torch
+
+project_root = Path(__file__).resolve().parent.parent
+sys.path.append(str(project_root))
+
+from yolo.config.config import Config
+from yolo.model.yolo import get_model
+from yolo.tools.data_loader import create_dataloader
+from yolo.tools.solver import ModelTester, ModelTrainer
+from yolo.utils.logging_utils import custom_logger, validate_log_directory
+
+
+@hydra.main(config_path="config", config_name="config", version_base=None)
+def main(cfg: Config):
+    custom_logger()
+    save_path = validate_log_directory(cfg, cfg.name)
+    dataloader = create_dataloader(cfg)
+    device = torch.device(cfg.device)
+    model = get_model(cfg).to(device)
+
+    if cfg.task.task == "train":
+        trainer = ModelTrainer(cfg, model, save_path, device)
+        trainer.solve(dataloader)
+
+    if cfg.task.task == "inference":
+        tester = ModelTester(cfg, model, save_path, device)
+        tester.solve(dataloader)
+
+
+if __name__ == "__main__":
+    main()