change type hint for 'sampling'

Author: SimonBlanke

src/gradient_free_optimizers/optimizer_search/bayesian_optimization.py

@@ -58,7 +58,7 @@ def __init__(
         nth_process: int = None,
         warm_start_smbo=None,
         max_sample_size: int = 10000000,
-        sampling: dict = {"random": 1000000},
+        sampling: Dict[Literal["random"], int] = {"random": 1000000},
         replacement: bool = True,
         gpr=gaussian_process["gp_nonlinear"],
         xi: float = 0.03,

src/gradient_free_optimizers/optimizer_search/direct_algorithm.py

@@ -53,7 +53,7 @@ def __init__(
         nth_process: int = None,
         warm_start_smbo=None,
         max_sample_size: int = 10000000,
-        sampling: dict = {"random": 1000000},
+        sampling: Dict[Literal["random"], int] = {"random": 1000000},
         replacement: bool = True,
     ):
         super().__init__(

src/gradient_free_optimizers/optimizer_search/ensemble_optimizer.py

@@ -21,7 +21,7 @@ def __init__(
         nth_process: int = None,
         warm_start_smbo=None,
         max_sample_size: int = 10000000,
-        sampling: dict = {"random": 1000000},
+        sampling: Dict[Literal["random"], int] = {"random": 1000000},
         replacement: bool = True,
     ):
         super().__init__(

src/gradient_free_optimizers/optimizer_search/forest_optimization.py

@@ -59,7 +59,7 @@ def __init__(
         nth_process: int = None,
         warm_start_smbo=None,
         max_sample_size: int = 10000000,
-        sampling: dict = {"random": 1000000},
+        sampling: Dict[Literal["random"], int] = {"random": 1000000},
         replacement: bool = True,
         tree_regressor="extra_tree",
         tree_para={"n_estimators": 100},

src/gradient_free_optimizers/optimizer_search/lipschitz_optimizer.py

@@ -53,7 +53,7 @@ def __init__(
         nth_process: int = None,
         warm_start_smbo=None,
         max_sample_size: int = 10000000,
-        sampling: dict = {"random": 1000000},
+        sampling: Dict[Literal["random"], int] = {"random": 1000000},
         replacement: bool = True,
     ):
         super().__init__(

src/gradient_free_optimizers/optimizer_search/tree_structured_parzen_estimators.py

@@ -57,7 +57,7 @@ def __init__(
         nth_process: int = None,
         warm_start_smbo=None,
         max_sample_size: int = 10000000,
-        sampling: dict = {"random": 1000000},
+        sampling: Dict[Literal["random"], int] = {"random": 1000000},
         replacement: bool = True,
         gamma_tpe=0.2,
     ):