Add docstrings to kimm.list_models, `kimm.utils.get_reparameterized…

…_model` (#49)

kimm/_src/utils/model_registry.py

@@ -78,8 +78,23 @@ def list_models(
     name: typing.Optional[str] = None,
     feature_extractor: typing.Optional[bool] = None,
     weights: typing.Optional[typing.Union[bool, str]] = None,
-) -> typing.List[str]:
-    result_names: typing.Set = set()
+):
+    """List the models with the given arguments.
+
+    Args:
+        name: An optional `str` specifying the substring of the name of the
+            model to seatch for. If not specified, all models will be included.
+        feature_extractor: Whether to include models that support
+            feature extraction. Defaults to `None`, which means this
+            argument is not considered.
+        weights: An optional boolean or `str` specifying the name of the
+            pretrained weights. The available values are (`"imagenet"`).
+            Defaults to `None`, which means this argument is not considered.
+
+    Returns:
+        A list of model names.
+    """
+    result_names: typing.Set[str] = set()
     for info in MODEL_REGISTRY:
         # Add by default
         result_names.add(info["name"])

kimm/_src/utils/model_utils.py

@@ -4,6 +4,17 @@
 
 @kimm_export(parent_path=["kimm.utils"])
 def get_reparameterized_model(model: BaseModel):
+    """Get the reparameterized model.
+
+    Internally, this function calls `get_reparameterized_model` from the
+    provided `model`.
+
+    Args:
+        model: A `BaseModel` to convert to its reparameterized form.
+
+    Returns:
+        An instance of the same class as `model` in its reparameterized form.
+    """
     if not hasattr(model, "get_reparameterized_model"):
         raise ValueError(
             "There is no 'get_reparameterized_model' method in the model. "