Simplify state_dict and fix Windows CI

- Remove template_path from state_dict (determined at load time)
- Remove hasattr check in load_state_dict
- Remove redundant test_path test

Signed-off-by: Soumya Snigdha Kundu <soumya_snigdha.kundu@kcl.ac.uk>

Author: aymuos15

monai/apps/auto3dseg/bundle_gen.py

@@ -373,9 +373,12 @@ def state_dict(self) -> dict:
 
         Returns:
             A dictionary containing the BundleAlgo state to serialize.
+
+        Note:
+            template_path is excluded as it is determined dynamically at load time
+            based on which path successfully imports the Algo class.
         """
         return {
-            "template_path": self.template_path,
             "data_stats_files": self.data_stats_files,
             "data_list_file": self.data_list_file,
             "mlflow_tracking_uri": self.mlflow_tracking_uri,
@@ -395,8 +398,7 @@ def load_state_dict(self, state: dict) -> None:
             state: A dictionary containing the state to restore.
         """
         for key, value in state.items():
-            if hasattr(self, key):
-                setattr(self, key, value)
+            setattr(self, key, value)
 
 
 # path to download the algo_templates

monai/auto3dseg/utils.py

@@ -490,9 +490,8 @@ def algo_from_json(filename: str, template_path: PathLike | None = None, **kwarg
     if algo is None:
         raise ValueError(f"Failed to instantiate Algo from target '{target}' with paths {template_paths}")
 
-    # Restore the state (skip template_path as it's set to the working import path below)
-    state_to_load = {k: v for k, v in state.items() if k != "template_path"}
-    algo.load_state_dict(state_to_load)
+    # Restore the state
+    algo.load_state_dict(state)
 
     # Use the path that successfully imported the class, not the original saved path
     # (the original path may no longer exist if the workdir was moved)

tests/auto3dseg/test_json_serialization.py

@@ -14,7 +14,6 @@
 import os
 import tempfile
 import unittest
-from pathlib import Path
 
 import numpy as np
 import torch
@@ -46,11 +45,6 @@ def test_torch_tensor(self) -> None:
         result = _make_json_serializable(t)
         assert result == [1.0, 2.0]
 
-    def test_path(self) -> None:
-        p = Path("/some/path")
-        # Use str(p) since path separators differ on Windows vs Unix
-        assert _make_json_serializable(p) == str(p)
-
     def test_fallback(self) -> None:
         class Custom:
             def __str__(self) -> str: