revert

Author: gauravmanmode

src/optimagic/optimizers/nevergrad_optimizers.py

@@ -4,7 +4,6 @@
 
 import math
 from dataclasses import dataclass
-from enum import Enum
 from typing import TYPE_CHECKING, Any, Literal
 
 import numpy as np
@@ -1275,72 +1274,8 @@ def _solve_internal_problem(
         return res
 
 
-# TODO https://facebookresearch.github.io/nevergrad/optimizers_ref.html#nevergrad.families.EvolutionStrategy
-
-
-class Wizard(str, Enum):
-    """Available portfolio optimizers from Nevergrad."""
-
-    # REF https://openreview.net/pdf/bcf18ffaccd27991ddf707a37b164dbab4ec4771.pdf
-    NGOpt = "NGOpt"
-    NGOpt4 = "NGOpt4"
-    NGOpt8 = "NGOpt8"
-    NGOpt10 = "NGOpt10"
-    NGOpt12 = "NGOpt12"
-    NGOpt13 = "NGOpt13"
-    NGOpt14 = "NGOpt14"
-    NGOpt15 = "NGOpt15"
-    NGOpt16 = "NGOpt16"
-    NGOpt21 = "NGOpt21"
-    NGOpt36 = "NGOpt36"
-    NGOpt38 = "NGOpt38"
-    NGOpt39 = "NGOpt39"
-    NGOptRW = "NGOptRW"
-    NGOptF = "NGOptF"
-    NGOptF2 = "NGOptF2"
-    NGOptF3 = "NGOptF3"
-    NGOptF5 = "NGOptF5"
-
-    NgIoh2 = "NgIoh2"
-    NgIoh3 = "NgIoh3"
-    NgIoh4 = "NgIoh4"
-    NgIoh5 = "NgIoh5"
-    NgIoh6 = "NgIoh6"
-    NgIoh7 = "NgIoh7"
-    NgIoh11 = "NgIoh11"
-    NgIoh14 = "NgIoh14"
-    NgIoh13 = "NgIoh13"
-    NgIoh15 = "NgIoh15"
-    NgIoh12 = "NgIoh12"
-    NgIoh16 = "NgIoh16"
-    NgIoh17 = "NgIoh17"
-    NgIoh21 = "NgIoh21"
-    NgIoh20 = "NgIoh20"
-    NgIoh19 = "NgIoh19"
-    NgIoh18 = "NgIoh18"
-    NgIoh10 = "NgIoh10"
-    NgIoh9 = "NgIoh9"
-    NgIoh8 = "NgIoh8"
-    NgIoh12b = "NgIoh12b"
-    NgIoh13b = "NgIoh13b"
-    NgIoh14b = "NgIoh14b"
-    NgIoh15b = "NgIoh15b"
-
-    NgDS = "NgDS"
-    NgDS2 = "NgDS2"
-    NGDSRW = "NGDSRW"
-    NGO = "NGO"
-    NgIohRW2 = "NgIohRW2"
-    NgIohTuned = "NgIohTuned"
-
-    CSEC = "CSEC"
-    CSEC10 = "CSEC10"
-    CSEC11 = "CSEC11"
-    Wiz = "Wiz"
-
-
 @mark.minimizer(
-    name="nevergrad_wizard",
+    name="nevergrad_ngopt",
     solver_type=AggregationLevel.SCALAR,
     is_available=IS_NEVERGRAD_INSTALLED,
     is_global=True,
@@ -1355,7 +1290,7 @@ class Wizard(str, Enum):
     disable_history=False,
 )
 @dataclass(frozen=True)
-class NevergradWizard(Algorithm):
+class NevergradNGOpt(Algorithm):
     """Minimize a scalar function using a Meta Optimizer from Nevergrad.
 
     These are meta-optimizers that intelligently combine multiple different
@@ -1364,7 +1299,60 @@ class NevergradWizard(Algorithm):
 
     """
 
-    optimizer: Wizard = Wizard.NgIoh10  # rename algorithm_selection maybe
+    optimizer: Literal[
+        "NGOpt",
+        "NGOpt4",
+        "NGOpt8",
+        "NGOpt10",
+        "NGOpt12",
+        "NGOpt13",
+        "NGOpt14",
+        "NGOpt15",
+        "NGOpt16",
+        "NGOpt21",
+        "NGOpt36",
+        "NGOpt38",
+        "NGOpt39",
+        "NGOptRW",
+        "NGOptF",
+        "NGOptF2",
+        "NGOptF3",
+        "NGOptF5",
+        "NgIoh2",
+        "NgIoh3",
+        "NgIoh4",
+        "NgIoh5",
+        "NgIoh6",
+        "NgIoh7",
+        "NgIoh11",
+        "NgIoh14",
+        "NgIoh13",
+        "NgIoh15",
+        "NgIoh12",
+        "NgIoh16",
+        "NgIoh17",
+        "NgIoh21",
+        "NgIoh20",
+        "NgIoh19",
+        "NgIoh18",
+        "NgIoh10",
+        "NgIoh9",
+        "NgIoh8",
+        "NgIoh12b",
+        "NgIoh13b",
+        "NgIoh14b",
+        "NgIoh15b",
+        "NgDS",
+        "NgDS2",
+        "NGDSRW",
+        "NGO",
+        "NgIohRW2",
+        "NgIohTuned",
+        "CSEC",
+        "CSEC10",
+        "CSEC11",
+        "Wiz",
+    ] = "NGOpt"
     """The specific Nevergrad meta-optimizer to use.
 
     Each option is a portfolio of different algorithms.
@@ -1408,79 +1396,8 @@ def _solve_internal_problem(
         return res
 
 
-class Portfolio(str, Enum):
-    """Available portfolio optimizers in Nevergrad."""
-
-    Carola1 = "Carola1"
-    """
-    CAROLA1 - Cost-effective Asymptotic Randomized Optimization with Limited Access.
-
-    Method:
-
-    1. COBYLA (budget b/2).
-    2. CMA with Meta Model (budget b/2), starting from COBYLA’s best solution,
-    """
-    Carola2 = "Carola2"
-    """
-    CAROLA2 - see Carola1
-
-    Method
-
-    1. COBYLA (budget b/3) for fast approximation.
-    2. CMA with meta-model (budget b/3), starting from COBYLA’s best solution,
-        for robust local search.
-    3. SQP (budget b/3), starting from the best solution so far,
-        for fast refinement.
-    """
-    Carola3 = "Carola3"
-    """
-    CAROLA3 - CAROLA2 for the parallel case. see Carola2,
-
-    Method
-    1. Apply w copies of Carola2 in parallel, with budget b/w."""
-
-    MultiBFGSPlus = "MultiBFGSPlus"
-    LogMultiBFGSPlus = "LogMultiBFGSPlus"
-    SqrtMultiBFGSPlus = "SqrtMultiBFGSPlus"
-    MultiCobylaPlus = "MultiCobylaPlus"
-    MultiSQPPlus = "MultiSQPPlus"
-    BFGSCMAPlus = "BFGSCMAPlus"
-    LogBFGSCMAPlus = "LogBFGSCMAPlus"
-    SqrtBFGSCMAPlus = "SqrtBFGSCMAPlus"
-    SQPCMAPlus = "SQPCMAPlus"
-    LogSQPCMAPlus = "LogSQPCMAPlus"
-    SqrtSQPCMAPlus = "SqrtSQPCMAPlus"
-
-    MultiBFGS = "MultiBFGS"
-    LogMultiBFGS = "LogMultiBFGS"
-    SqrtMultiBFGS = "SqrtMultiBFGS"
-    MultiCobyla = "MultiCobyla"
-    ForceMultiCobyla = "ForceMultiCobyla"
-    MultiSQP = "MultiSQP"
-    BFGSCMA = "BFGSCMA"
-    LogBFGSCMA = "LogBFGSCMA"
-    SqrtBFGSCMA = "SqrtBFGSCMA"
-    SQPCMA = "SQPCMA"
-    LogSQPCMA = "LogSQPCMA"
-    SqrtSQPCMA = "SqrtSQPCMA"
-    FSQPCMA = "FSQPCMA"
-    F2SQPCMA = "F2SQPCMA"
-    F3SQPCMA = "F3SQPCMA"
-
-    MultiDiscrete = "MultiDiscrete"
-    CMandAS2 = "CMandAS2"
-    CMandAS3 = "CMandAS3"
-    MetaCMA = "MetaCMA"
-    CMA = "CMA"
-    PCEDA = "PCEDA"
-    MPCEDA = "MPCEDA"
-    MEDA = "MEDA"
-    NoisyBandit = "NoisyBandit"
-    Shiwa = "Shiwa"
-
-
 @mark.minimizer(
-    name="nevergrad_portfolio",
+    name="nevergrad_meta",
     solver_type=AggregationLevel.SCALAR,
     is_available=IS_NEVERGRAD_INSTALLED,
     is_global=True,
@@ -1495,7 +1412,7 @@ class Portfolio(str, Enum):
     disable_history=False,
 )
 @dataclass(frozen=True)
-class NevergradPortfolio(Algorithm):
+class NevergradMeta(Algorithm):
     """Minimize a scalar function using a Meta Optimizer from Nevergrad.
 
     This algorithm utilizes a combination of local and global optimizers to find
@@ -1504,7 +1421,45 @@ class NevergradPortfolio(Algorithm):
 
     """
 
-    optimizer: Portfolio = Portfolio.BFGSCMA
+    optimizer: Literal[
+        "MultiBFGSPlus",
+        "LogMultiBFGSPlus",
+        "SqrtMultiBFGSPlus",
+        "MultiCobylaPlus",
+        "MultiSQPPlus",
+        "BFGSCMAPlus",
+        "LogBFGSCMAPlus",
+        "SqrtBFGSCMAPlus",
+        "SQPCMAPlus",
+        "LogSQPCMAPlus",
+        "SqrtSQPCMAPlus",
+        "MultiBFGS",
+        "LogMultiBFGS",
+        "SqrtMultiBFGS",
+        "MultiCobyla",
+        "ForceMultiCobyla",
+        "MultiSQP",
+        "BFGSCMA",
+        "LogBFGSCMA",
+        "SqrtBFGSCMA",
+        "SQPCMA",
+        "LogSQPCMA",
+        "SqrtSQPCMA",
+        "FSQPCMA",
+        "F2SQPCMA",
+        "F3SQPCMA",
+        "MultiDiscrete",
+        "CMandAS2",
+        "CMandAS3",
+        "MetaCMA",
+        "CMA",
+        "PCEDA",
+        "MPCEDA",
+        "MEDA",
+        "NoisyBandit",
+        "Shiwa",
+        "Carola3",
+    ] = "Shiwa"
     """The specific Nevergrad meta-optimizer to use.
 
     Each option is a portfolio of different local and global algorithms.