update notebook

VowpalWabbit · Nov 28, 2023 · af207ff · af207ff
1 parent 20f8a21
commit af207ff
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Showing 3 changed files with 106 additions and 39 deletions.
diff --git a/notebooks/news_recommendation_byom.ipynb b/notebooks/news_recommendation_byom.ipynb
diff --git a/src/learn_to_pick/pytorch/feature_embedder.py b/src/learn_to_pick/pytorch/feature_embedder.py
@@ -39,13 +39,13 @@ def format(
 
         if len(context_featurized.dense) > 0:
             raise NotImplementedError(
-                "pytorch policy doesn't support context with dense feature"
+                "pytorch policy doesn't support context with dense features"
             )
 
         for action_featurized in actions_featurized:
             if len(action_featurized.dense) > 0:
                 raise NotImplementedError(
-                    "pytorch policy doesn't support action with dense feature"
+                    "pytorch policy doesn't support action with dense features"
                 )
 
         context_sparse = self.encode(

diff --git a/src/learn_to_pick/pytorch/policy.py b/src/learn_to_pick/pytorch/policy.py
@@ -4,7 +4,7 @@
 from learn_to_pick.pytorch.feature_embedder import PyTorchFeatureEmbedder
 import torch
 import os
-from typing import Any, Optional, PathLike, TypeVar, Union
+from typing import Any, Optional, TypeVar, Union
 
 TEvent = TypeVar("TEvent", bound=base.Event)
 
@@ -55,7 +55,7 @@ def learn(self, event: TEvent) -> None:
     def log(self, event):
         pass
 
-    def save(self, path: Optional[Union[str, PathLike]]) -> None:
+    def save(self, path: Optional[Union[str, os.PathLike]]) -> None:
         state = {
             "workspace_state_dict": self.workspace.state_dict(),
             "optimizer_state_dict": self.workspace.optim.state_dict(),
@@ -69,7 +69,7 @@ def save(self, path: Optional[Union[str, PathLike]]) -> None:
             os.makedirs(dir, exist_ok=True)
         torch.save(state, path)
 
-    def load(self, path: Optional[Union[str, PathLike]]) -> None:
+    def load(self, path: Optional[Union[str, os.PathLike]]) -> None:
         import parameterfree
 
         if os.path.exists(path):