update rm searcher_kwargs key from yaml for user

automl · Jun 14, 2024 · 5f3e541 · 5f3e541
1 parent 12bc542
commit 5f3e541
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Showing 3 changed files with 24 additions and 30 deletions.
diff --git a/neps/api.py b/neps/api.py
@@ -283,7 +283,7 @@ def run(
     if inspect.isclass(searcher):
         if issubclass(searcher, BaseOptimizer):
             search_space = SearchSpace(**pipeline_space)
-            searcher = searcher(search_space)
+            searcher = searcher(search_space, **searcher_kwargs)
         else:
             # Raise an error if searcher is not a subclass of BaseOptimizer
             raise TypeError(
@@ -410,7 +410,7 @@ def _run_args(
         raise TypeError(message) from e
 
     if isinstance(searcher, (str, Path)) and searcher not in \
-        SearcherConfigs.get_searchers() and searcher is not "default":
+        SearcherConfigs.get_searchers() and searcher != "default":
         # The users has their own custom searcher.
         logging.info("Preparing to run user created searcher")
 
@@ -450,15 +450,6 @@ def _run_args(
         # Map the old 'algorithm' argument to 'strategy'
         config['strategy'] = config.pop("algorithm")
 
-    # Check for deprecated 'algorithm' argument
-    if "algorithm" in config:
-        warnings.warn(
-            "The 'algorithm' argument is deprecated and will be removed in future versions. Please use 'strategy' instead.",
-            DeprecationWarning
-        )
-        # Map the old 'algorithm' argument to 'strategy'
-        config['strategy'] = config.pop("algorithm")
-
     if "strategy" in config:
         searcher_alg = config.pop("strategy")
     else:

diff --git a/neps/utils/run_args.py b/neps/utils/run_args.py
@@ -61,7 +61,7 @@ def get_run_args_from_yaml(path: str) -> dict:
     settings = {}
 
     # List allowed NEPS run arguments with simple types (e.g., string, int). Parameters
-    # like 'searcher_kwargs', 'run_pipeline', 'preload_hooks', 'pipeline_space',
+    # like 'run_pipeline', 'preload_hooks', 'pipeline_space',
     # and 'searcher' are excluded due to needing specialized processing.
     expected_parameters = [
         ROOT_DIRECTORY,
@@ -147,7 +147,7 @@ def config_loader(path: str) -> dict:
 
 def extract_leaf_keys(d: dict, special_keys: dict | None = None) -> tuple[dict, dict]:
     """Recursive function to extract leaf keys and their values from a nested dictionary.
-    Special keys (e.g. 'searcher_kwargs', 'run_pipeline') are also extracted if present
+    Special keys (e.g.'run_pipeline') are also extracted if present
     and their corresponding values (dict) at any level in the nested structure.
 
     :param d: The dictionary to extract values from.
@@ -157,7 +157,6 @@ def extract_leaf_keys(d: dict, special_keys: dict | None = None) -> tuple[dict,
     """
     if special_keys is None:
         special_keys = {
-            SEARCHER_KWARGS: None,
             RUN_PIPELINE: None,
             PRE_LOAD_HOOKS: None,
             SEARCHER: None,
@@ -183,8 +182,8 @@ def handle_special_argument_cases(settings: dict, special_configs: dict) -> None
     This function updates 'settings' with values from 'special_configs'. It handles
     specific keys that require more complex processing, such as 'pipeline_space' and
     'searcher', which may need to load a function/dict from paths. It also manages nested
-    configurations like 'searcher_kwargs' and 'pre_load_hooks' which need individual
-    processing or function loading.
+    configurations like 'pre_load_hooks' which need individual processing or function
+    loading.
 
     Parameters:
     - settings (dict): The dictionary to be updated with processed configurations.
@@ -269,8 +268,12 @@ def process_searcher(key: str, special_configs: dict, settings: dict):
             # determine if dict contains path_loading or the actual searcher config
             expected_keys = {"path", "name"}
             actual_keys = set(searcher.keys())
-            if expected_keys == actual_keys:
-                searcher = load_and_return_object(searcher["path"], searcher["name"], key)
+            if expected_keys.issubset(actual_keys):
+                path = searcher.pop("path")
+                name = searcher.pop("name")
+                settings[SEARCHER_KWARGS] = searcher
+                searcher = load_and_return_object(path, name, key)
+
         elif isinstance(searcher, (str, Path)):
             pass
         else:
@@ -426,7 +429,7 @@ def check_run_args(settings: dict) -> None:
             if not all(callable(item) for item in value):
                 raise TypeError("All items in 'pre_load_hooks' must be callable.")
         elif param == SEARCHER:
-            if not (isinstance(param, str) or issubclass(param, BaseOptimizer)):
+            if not (isinstance(param, (str, dict)) or issubclass(param, BaseOptimizer)):
                 raise TypeError(
                     "Parameter 'searcher' must be a string or a class that is a subclass "
                     "of BaseOptimizer."
@@ -510,6 +513,9 @@ def check_double_reference(
             if name == RUN_ARGS:
                 # Ignoring run_args argument
                 continue
+            if name == SEARCHER_KWARGS and func_arguments[name] == {}:
+                continue
+
             if name in yaml_arguments:
                 raise ValueError(
                     f"Conflict for argument '{name}': Argument is defined both via "

diff --git a/tests/test_yaml_run_args/test_yaml_run_args.py b/tests/test_yaml_run_args/test_yaml_run_args.py
@@ -111,8 +111,8 @@ def are_functions_equivalent(f1: Union[Callable, List[Callable]],
                 "loss_value_on_error": 4.2,
                 "cost_value_on_error": 3.7,
                 "ignore_errors": True,
-                "searcher": "bayesian_optimization",
-                "searcher_kwargs": {"initial_design_size": 5, "surrogate_model": "gp"},
+                "searcher": {"strategy": "bayesian_optimization",
+                             "initial_design_size": 5, "surrogate_model": "gp"},
                 "pre_load_hooks": [hook1, hook2],
             },
         ),
@@ -133,8 +133,8 @@ def are_functions_equivalent(f1: Union[Callable, List[Callable]],
                 "loss_value_on_error": 2.4,
                 "cost_value_on_error": 2.1,
                 "ignore_errors": False,
-                "searcher": "bayesian_optimization",
-                "searcher_kwargs": {"initial_design_size": 5, "surrogate_model": "gp"},
+                "searcher": {"strategy": "bayesian_optimization",
+                             "initial_design_size": 5, "surrogate_model": "gp"},
                 "pre_load_hooks": [hook1],
             },
         ),
@@ -147,8 +147,8 @@ def are_functions_equivalent(f1: Union[Callable, List[Callable]],
                 "overwrite_working_directory": True,
                 "post_run_summary": False,
                 "continue_until_max_evaluation_completed": False,
-                "searcher": "bayesian_optimization",
-                "searcher_kwargs": {"initial_design_size": 5, "surrogate_model": "gp"},
+                "searcher": {"strategy": "bayesian_optimization",
+                             "initial_design_size": 5, "surrogate_model": "gp"},
             },
         ),
         (
@@ -178,11 +178,8 @@ def are_functions_equivalent(f1: Union[Callable, List[Callable]],
             "loss_value_on_error": 2.4,
             "cost_value_on_error": 2.1,
             "ignore_errors": False,
-            "searcher": BayesianOptimization,
-            "searcher_kwargs": {
-                "initial_design_size": 5,
-                "surrogate_model": "gp"
-            },
+            "searcher": {"strategy": "bayesian_optimization", "initial_design_size": 5,
+                         "surrogate_model": "gp"},
             "pre_load_hooks": [hook1]
 
         })