�feat: expose both imputation and classification GRUD;

pypots/cli/tuning.py

@@ -14,6 +14,7 @@
 from .base import BaseCommand
 from .utils import load_package_from_path
 from ..classification import BRITS as BRITS_classification
+from ..classification import GRUD as GRUD_classification
 from ..classification import Raindrop
 from ..clustering import CRLI, VaDER
 from ..data.saving.h5 import load_dict_from_h5
@@ -80,8 +81,9 @@
  "pypots.imputation.GPVAE": GPVAE,
  "pypots.imputation.BRITS": BRITS,
  "pypots.imputation.MRNN": MRNN,
+ "pypots.imputation.GRUD": GRUD,
  # classification models
- "pypots.classification.GRUD": GRUD,
+ "pypots.classification.GRUD": GRUD_classification,
  "pypots.classification.BRITS": BRITS_classification,
  "pypots.classification.Raindrop": Raindrop,
  # clustering models
@@ -248,7 +250,7 @@ def run(self):
  )
  raise RuntimeError(
  f"Hyperparameters do not match. Mismatched hyperparameters "
- f"(in the tuning configuration but not in the given model's arguments): {list(mismatched)}"
+ f"(in the tuning configuration but not in {model_class.__name__}'s arguments): {list(mismatched)}"
  )
 
  # initializing optimizer and model