Added whoami function and a test case for searcher as BaseOptimizer

.github/workflows/tests.yaml

@@ -41,4 +41,4 @@ jobs:
 
       - name: Run pytest
         timeout-minutes: 15
-        run: poetry run pytest -m "all_examples or metahyper"
+        run: poetry run pytest -m "all_examples or metahyper or yaml_api"

src/neps/api.py

@@ -206,10 +206,12 @@ def run(
 
     if isinstance(searcher, BaseOptimizer):
         searcher_instance = searcher
-        searcher_alg = "custom"
+        searcher_name = "custom"
+        searcher_alg = searcher.whoami()
         user_defined_searcher = True
     else:
-        (
+        (   
+            searcher_name,
             searcher_instance, 
             searcher_alg, 
             searcher_config, 
@@ -238,7 +240,7 @@ def run(
     # Used to create the yaml holding information about the searcher.
     # Also important for testing and debugging the api.
     searcher_info = {
-        "searcher_name": str(searcher),
+        "searcher_name": searcher_name,
         "searcher_alg": searcher_alg,
         "user_defined_searcher": user_defined_searcher,
         "searcher_args_user_modified": False,
@@ -430,4 +432,4 @@ def _run_args(
         **searcher_config,
     )
 
-    return searcher_instance, searcher_alg, searcher_config, searcher_info, user_defined_searcher
+    return searcher, searcher_instance, searcher_alg, searcher_config, searcher_info, user_defined_searcher

src/neps/optimizers/base_optimizer.py

@@ -92,3 +92,6 @@ def get_learning_curve(self, result: str | dict | float) -> float | Any:
             learning_curve_on_error=self.learning_curve_on_error,
             ignore_errors=self.ignore_errors,
         )
+
+    def whoami(self):
+        return type(self).__name__

tests/test_neps_api/examples_test_api.py

@@ -1,6 +1,8 @@
 import logging
 
 import neps
+from neps.optimizers.bayesian_optimization.optimizer import BayesianOptimization
+from neps.search_spaces.search_space import SearchSpace
 
 pipeline_space_fidelity_priors = dict(
     val1=neps.FloatParameter(lower=-10, upper=10, default=1),
@@ -80,3 +82,16 @@ def run_pipeline(val1, val2):
     max_evaluations_total=1,
     eta=2,
 )
+
+# Testing neps when the user creates their own custom searcher
+search_space = SearchSpace(**pipeline_space_fidelity)
+my_custom_searcher = BayesianOptimization(
+    pipeline_space=search_space, initial_design_size=5
+)
+neps.run(
+    run_pipeline=run_pipeline,
+    pipeline_space=pipeline_space_not_fidelity,
+    root_directory="bo_custom_created",
+    max_evaluations_total=1,
+    searcher=my_custom_searcher,
+)

tests/test_neps_api/test_yaml_api.py

@@ -59,6 +59,12 @@ def no_logs_gte_error(caplog):
         "user_defined_searcher": False,
         "searcher_args_user_modified": False,
     },
+    "bo_custom_created": {
+        "searcher_name": "custom",
+        "searcher_alg": "BayesianOptimization",
+        "user_defined_searcher": True,
+        "searcher_args_user_modified": False,
+    },
 }