Update dependency lightning to >=2.6,<2.7 (#76)

Set `weights_only=False` when loading ckpts, since Lightning now defers to torch's default (`True`)
* See PR on this change: Lightning-AI/pytorch-lightning#21072

---------

Co-authored-by: Nathan Painchaud <[email protected]>

Author: renovate[bot]

pyproject.toml

@@ -9,7 +9,7 @@ dependencies = [
     "hydra-colorlog>=1.2.0,<2",
     "hydra-core>=1.3.2,<2",
     "hydra-optuna-sweeper>=1.2.0,<2",
-    "lightning>=2.5.0.post0,<2.6",
+    "lightning>=2.6,<2.7",
     "rich>=14,<15",
     "rootutils>=1.0.7,<2",
     "torchmetrics>=1.8,<1.9",

src/lightning_hydra_template/eval.py

@@ -57,7 +57,7 @@ def evaluate(cfg: DictConfig) -> tuple[dict[str, Any], dict[str, Any]]:
         log_hyperparameters(object_dict)
 
     log.info("Starting testing!")
-    trainer.test(model=model, datamodule=datamodule, ckpt_path=cfg.ckpt_path)
+    trainer.test(model=model, datamodule=datamodule, ckpt_path=cfg.ckpt_path, weights_only=False)
 
     # for predictions use trainer.predict(...)
     # predictions = trainer.predict(model=model, dataloaders=dataloaders, ckpt_path=cfg.ckpt_path)

src/lightning_hydra_template/train.py

@@ -74,7 +74,7 @@ def train(cfg: DictConfig) -> tuple[dict[str, Any], dict[str, Any]]:
 
     if cfg.get("train"):
         log.info("Starting training!")
-        trainer.fit(model=model, datamodule=datamodule, ckpt_path=cfg.get("ckpt_path"))
+        trainer.fit(model=model, datamodule=datamodule, ckpt_path=cfg.get("ckpt_path"), weights_only=False)
 
     train_metrics = trainer.callback_metrics
 
@@ -84,7 +84,7 @@ def train(cfg: DictConfig) -> tuple[dict[str, Any], dict[str, Any]]:
         if ckpt_path == "":
             log.warning("Best ckpt not found! Using current weights for testing...")
             ckpt_path = None
-        trainer.test(model=model, datamodule=datamodule, ckpt_path=ckpt_path)
+        trainer.test(model=model, datamodule=datamodule, ckpt_path=ckpt_path, weights_only=False)
         log.info(f"Best ckpt path: {ckpt_path}")
 
     test_metrics = trainer.callback_metrics