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Improve evaluate_from_recipe usability #558

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merged 2 commits into from
Dec 11, 2022
Merged

Improve evaluate_from_recipe usability #558

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31d26b6
fix
Louis-Dupont Dec 8, 2022
8695e50
Merge branch 'master' into hotfix/SG-000-remove_friction_for_evaluate…
Louis-Dupont Dec 11, 2022
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13 changes: 9 additions & 4 deletions src/super_gradients/training/sg_trainer/sg_trainer.py
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Original file line number Diff line number Diff line change
Expand Up @@ -270,17 +270,22 @@ def evaluate_from_recipe(cls, cfg: DictConfig) -> None:
name=cfg.val_dataloader, dataset_params=cfg.dataset_params.val_dataset_params, dataloader_params=cfg.dataset_params.val_dataloader_params
)

checkpoints_dir = Path(get_checkpoints_dir_path(experiment_name=cfg.experiment_name, ckpt_root_dir=cfg.ckpt_root_dir))
checkpoint_path = str(checkpoints_dir / cfg.training_hyperparams.ckpt_name)
logger.info(f"Evaluating checkpoint: {checkpoint_path}")
if cfg.checkpoint_params.checkpoint_path is None:
logger.info(
"checkpoint_params.checkpoint_path was not provided, " "so the recipe will be evaluated using checkpoints_dir/training_hyperparams.ckpt_name"
)
checkpoints_dir = Path(get_checkpoints_dir_path(experiment_name=cfg.experiment_name, ckpt_root_dir=cfg.ckpt_root_dir))
cfg.checkpoint_params.checkpoint_path = str(checkpoints_dir / cfg.training_hyperparams.ckpt_name)

logger.info(f"Evaluating checkpoint: {cfg.checkpoint_params.checkpoint_path}")

# BUILD NETWORK
model = models.get(
model_name=cfg.architecture,
num_classes=cfg.arch_params.num_classes,
arch_params=cfg.arch_params,
pretrained_weights=cfg.checkpoint_params.pretrained_weights,
checkpoint_path=checkpoint_path,
checkpoint_path=cfg.checkpoint_params.checkpoint_path,
load_backbone=cfg.checkpoint_params.load_backbone,
)

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2 changes: 1 addition & 1 deletion src/super_gradients/training/utils/checkpoint_utils.py
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Expand Up @@ -138,7 +138,7 @@ def copy_ckpt_to_local_folder(

def read_ckpt_state_dict(ckpt_path: str, device="cpu"):
if not os.path.exists(ckpt_path):
raise ValueError("Incorrect Checkpoint path")
raise FileNotFoundError(f"Incorrect Checkpoint path: {ckpt_path} (This should be an absolute path)")

if device == "cuda":
state_dict = torch.load(ckpt_path)
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