fixed another numpy typo

src/MEDS_polars_functions/sharding.py

@@ -50,7 +50,10 @@ def shard_patients[
         >>> patients = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10], dtype=int)
         >>> shard_patients(patients, n_patients_per_shard=3)
         {'train/0': [9, 4, 8], 'train/1': [2, 1, 10], 'train/2': [6, 5], 'tuning/0': [3], 'held_out/0': [7]}
-        >>> external_splits = {'taskA/held_out': [8, 9, 10], 'taskB/held_out': [10, 8, 9]}
+        >>> external_splits = {
+        ...     'taskA/held_out': np.array([8, 9, 10], dtype=int),
+        ...     'taskB/held_out': np.array([10, 8, 9], dtype=int),
+        ... }
         >>> shard_patients(patients, 3, external_splits) # doctest: +NORMALIZE_WHITESPACE
         {'train/0': [5, 7, 4],
          'train/1': [1, 2],
@@ -73,6 +76,14 @@ def shard_patients[
 
     if external_splits is None:
         external_splits = {}
+    else:
+        for k in list(external_splits.keys()):
+            if not isinstance(external_splits[k], np.ndarray):
+                logger.warning(
+                    f"External split {k} is not a numpy array and thus type safety is not guaranteed. "
+                    f"Attempting to convert to numpy array of dtype {patients.dtype}."
+                )
+                external_splits[k] = np.array(external_splits[k], dtype=patients.dtype)
 
     patients = np.unique(patients)
 
@@ -118,7 +129,7 @@ def shard_patients[
             n_shards = int(np.ceil(n_pts / n_patients_per_shard))
             shards = np.array_split(pts, n_shards)
             for i, shard in enumerate(shards):
-                final_shards[f"{sp}/{i}"] = shard.to_list()
+                final_shards[f"{sp}/{i}"] = shard.tolist()
 
     seen = {}