rm neps argument searcher_path

neps/api.py

@@ -26,6 +26,17 @@
 from neps.utils.common import get_searcher_data, get_value
 from neps.utils.data_loading import _get_loss
 
+VALID_SEARCHER = [
+    "default",
+    "bayesian_optimization",
+    "random_search",
+    "hyperband",
+    "priorband",
+    "mobster",
+    "asha",
+    "regularized_evolution",
+]
+
 
 def _post_evaluation_hook_function(
     _loss_value_on_error: None | float, _ignore_errors: bool
@@ -132,9 +143,8 @@ def run(
             "asha",
             "regularized_evolution",
         ]
-        | BaseOptimizer
+        | BaseOptimizer | Path
     ) = "default",
-    searcher_path: Path | str | None = None,
     **searcher_kwargs,
 ) -> None:
     """Run a neural pipeline search.
@@ -176,9 +186,8 @@ def run(
         cost_value_on_error: Setting this and loss_value_on_error to any float will
             supress any error and will use given cost value instead. default: None
         pre_load_hooks: List of functions that will be called before load_results().
-        searcher: Which optimizer to use. This is usually only needed by neps developers.
-        searcher_path: The path to the user created searcher. None when the user
-            is using NePS designed searchers.
+        searcher: Which optimizer to use. Can be a string identifier, an
+            instance of BaseOptimizer, or a Path to a custom optimizer.
         **searcher_kwargs: Will be passed to the searcher. This is usually only needed by
             neps develolpers.
 
@@ -250,7 +259,6 @@ def run(
                                                  cost_value_on_error)
         pre_load_hooks = optim_settings.get("pre_load_hooks", pre_load_hooks)
         searcher = optim_settings.get("searcher", searcher)
-        searcher_path = optim_settings.get("searcher_path", searcher_path)
         for key, value in optim_settings.get("searcher_kwargs", searcher_kwargs).items():
             searcher_kwargs[key] = value
 
@@ -310,7 +318,6 @@ def run(
             cost_value_on_error=cost_value_on_error,
             logger=logger,
             searcher=searcher,
-            searcher_path=searcher_path,
             **searcher_kwargs,
         )
 
@@ -380,7 +387,6 @@ def _run_args(
         ]
         | BaseOptimizer
     ) = "default",
-    searcher_path: Path | str | None = None,
     **searcher_kwargs,
 ) -> tuple[BaseOptimizer, dict]:
     try:
@@ -412,11 +418,11 @@ def _run_args(
         message = f"The pipeline_space has invalid type: {type(pipeline_space)}"
         raise TypeError(message) from e
 
-    if isinstance(searcher, str) and searcher_path is not None:
+    if isinstance(searcher, (str, Path)) and searcher not in VALID_SEARCHER:
         # The users has their own custom searcher.
         logging.info("Preparing to run user created searcher")
 
-        config = get_searcher_data(searcher, searcher_path)
+        config, searcher = get_searcher_data(searcher, loading_custom_searcher=True)
         searcher_info["searcher_selection"] = "user-yaml"
         searcher_info["neps_decision_tree"] = False
     else:
@@ -436,7 +442,7 @@ def _run_args(
             searcher_info["neps_decision_tree"] = False
             searcher_info["searcher_selection"] = "neps-default"
         # Fetching the searcher data, throws an error when the searcher is not found
-        config = get_searcher_data(searcher)
+        config, searcher = get_searcher_data(searcher)
 
     if "algorithm" in config:
         searcher_alg = config.pop("algorithm")

neps/utils/common.py

@@ -193,21 +193,19 @@ def get_initial_directory(pipeline_directory: Path | str | None = None) -> Path:
 
 
 def get_searcher_data(
-    searcher: str,
-    searcher_path: Path | str | None = None,
-) -> dict[str, Any]:
+    searcher: str | Path, loading_custom_searcher: bool = False
+) -> (dict[str, Any], str):
     """Returns the data from the YAML file associated with the specified searcher.
 
     Args:
         searcher: The name of the searcher.
-        searcher_path: The path to the directory where the searcher defined YAML file
-            is located.
+        loading_custom_searcher: Flag if searcher contains a custom yaml
 
     Returns:
-        The content of the YAML file.
+        The content of the YAML file and searcher name.
     """
-    if searcher_path is not None:
-        user_yaml_path = Path(searcher_path, searcher).with_suffix(".yaml")
+    if loading_custom_searcher:
+        user_yaml_path = Path(searcher).with_suffix(".yaml")
 
         if not user_yaml_path.exists():
             raise FileNotFoundError(
@@ -218,6 +216,9 @@ def get_searcher_data(
         with user_yaml_path.open("r") as file:
             data = yaml.safe_load(file)
 
+        file_name = user_yaml_path.stem
+        searcher = data.get("name", file_name)
+
     else:
         # TODO(eddiebergman): This is a bad idea as it relies on folder structure to be
         # correct, we should either have a dedicated resource folder or at least have
@@ -246,7 +247,7 @@ def get_searcher_data(
         with resource_path.open() as file:
             data = yaml.safe_load(file)
 
-    return data  # type: ignore
+    return data, searcher  # type: ignore
 
 
 # TODO(eddiebergman): This seems like a bad function name, I guess this is used for a

neps/utils/run_args_from_yaml.py

@@ -25,7 +25,6 @@
 COST_VALUE_ON_ERROR = "cost_value_on_error"
 IGNORE_ERROR = "ignore_errors"
 SEARCHER = "searcher"
-SEARCHER_PATH = "searcher_path"
 PRE_LOAD_HOOKS = "pre_load_hooks"
 SEARCHER_KWARGS = "searcher_kwargs"
 MAX_EVALUATIONS_PER_RUN = "max_evaluations_per_run"
@@ -73,7 +72,6 @@ def get_run_args_from_yaml(path: str) -> dict:
         LOSS_VALUE_ON_ERROR,
         COST_VALUE_ON_ERROR,
         IGNORE_ERROR,
-        SEARCHER_PATH,
     ]
 
     # Flatten the YAML file's structure to separate flat parameters (flat_config) and
@@ -412,7 +410,6 @@ def check_run_args(settings: Dict) -> None:
         LOSS_VALUE_ON_ERROR: float,
         COST_VALUE_ON_ERROR: float,
         IGNORE_ERROR: bool,
-        SEARCHER_PATH: str,
         SEARCHER_KWARGS: dict,
     }
     for param, value in settings.items():

tests/test_neps_api/testing_scripts/user_yaml_neps.py

@@ -19,13 +19,12 @@ def run_pipeline(val1, val2):
 # Testing using created yaml with api
 script_directory = os.path.dirname(os.path.abspath(__file__))
 parent_directory = os.path.join(script_directory, os.pardir)
-searcher_path = os.path.join(parent_directory, "testing_yaml")
+searcher_path = os.path.join(parent_directory, "testing_yaml/optimizer_test")
 neps.run(
     run_pipeline=run_pipeline,
     pipeline_space=pipeline_space,
     root_directory="user_yaml_bo",
     max_evaluations_total=1,
-    searcher="optimizer_test",
-    searcher_path=searcher_path,
+    searcher=searcher_path,
     initial_design_size=5,
 )

tests/test_yaml_run_args/run_args_empty.yaml

@@ -19,7 +19,6 @@ parallelization_setup:
 
 search:
   searcher:
-  searcher_path:
   searcher_kwargs:
     initial_design_size:
     surrogate_model:

tests/test_yaml_run_args/run_args_full.yaml

@@ -25,7 +25,6 @@ error_handling:
 
 search:
   searcher: "bayesian_optimization"
-  searcher_path: "/path/to/model"
   searcher_kwargs:
     initial_design_size: 5
     surrogate_model: gp

tests/test_yaml_run_args/run_args_full_same_level.yaml

@@ -15,7 +15,6 @@ loss_value_on_error: 2.4
 cost_value_on_error: 2.1
 ignore_errors: False
 searcher: "bayesian_optimization"
-searcher_path: "/path/to/searcher"
 searcher_kwargs:
   initial_design_size: 5
   surrogate_model: gp

tests/test_yaml_run_args/run_args_invalid_key.yaml

@@ -25,7 +25,6 @@ error_handling:
 
 search:
   searcher: "bayesian_optimization"
-  searcher_path: "/path/to/model"
   searcher_kwargs:
     initial_design_size: 5
     surrogate_model: gp

tests/test_yaml_run_args/run_args_invalid_type.yaml

@@ -22,7 +22,6 @@ error_handling:
 
 search:
   searcher: "bayesian_optimization"
-  searcher_path:
   searcher_kwargs:
     initial_design_size: 5
     surrogate_model: gp

tests/test_yaml_run_args/run_args_key_missing.yaml

@@ -15,7 +15,6 @@ loss_value_on_error: 2.4
 cost_value_on_error: 2.1
 ignore_errors: False
 searcher: "bayesian_optimization"
-searcher_path: "/path/to/searcher"
 searcher_kwargs:
   initial_design_size: 5
   surrogate_model: gp

tests/test_yaml_run_args/run_args_optional_loading_format.yaml

@@ -19,7 +19,6 @@ ignore_errors: False
 searcher: # Optional Loading
   path: "neps/optimizers/bayesian_optimization/optimizer.py"
   name: BayesianOptimization
-searcher_path: "/path/to/searcher"
 searcher_kwargs:
   initial_design_size: 5
   surrogate_model: gp

tests/test_yaml_run_args/run_args_partial.yaml

@@ -20,7 +20,6 @@ parallelization_setup:
 
 search:
   searcher: "bayesian_optimization"
-  searcher_path:
   searcher_kwargs:
     initial_design_size: 5
     surrogate_model: gp

tests/test_yaml_run_args/run_args_partial_same_level.yaml

@@ -11,5 +11,4 @@ continue_until_max_evaluation_completed: True
 loss_value_on_error: None
 ignore_errors: True
 searcher:
-searcher_path:
 pre_load_hooks: None

tests/test_yaml_run_args/run_args_wrong_name.yaml

@@ -25,7 +25,6 @@ error_handling:
 
 search:
   searcher: "bayesian_optimization"
-  searcher_path: "/path/to/model"
   searcher_kwargs:
     initial_design_size: 5
     surrogate_model: gp

tests/test_yaml_run_args/run_args_wrong_path.yaml

@@ -25,7 +25,6 @@ error_handling:
 
 search:
   searcher: "bayesian_optimization"
-  searcher_path: "/path/to/model"
   searcher_kwargs:
     initial_design_size: 5
     surrogate_model: gp

tests/test_yaml_run_args/test_yaml_run_args.py

@@ -112,7 +112,6 @@ def are_functions_equivalent(f1: Union[Callable, List[Callable]],
                 "cost_value_on_error": 3.7,
                 "ignore_errors": True,
                 "searcher": "bayesian_optimization",
-                "searcher_path": "/path/to/model",
                 "searcher_kwargs": {"initial_design_size": 5, "surrogate_model": "gp"},
                 "pre_load_hooks": [hook1, hook2],
             },
@@ -135,7 +134,6 @@ def are_functions_equivalent(f1: Union[Callable, List[Callable]],
                 "cost_value_on_error": 2.1,
                 "ignore_errors": False,
                 "searcher": "bayesian_optimization",
-                "searcher_path": "/path/to/searcher",
                 "searcher_kwargs": {"initial_design_size": 5, "surrogate_model": "gp"},
                 "pre_load_hooks": [hook1],
             },
@@ -181,7 +179,6 @@ def are_functions_equivalent(f1: Union[Callable, List[Callable]],
             "cost_value_on_error": 2.1,
             "ignore_errors": False,
             "searcher": BayesianOptimization,
-            "searcher_path": "/path/to/searcher",
             "searcher_kwargs": {
                 "initial_design_size": 5,
                 "surrogate_model": "gp"