Quickfix for logger of ConfiguredOptimizer (#1116)

nevergrad/optimization/callbacks.py

@@ -101,7 +101,7 @@ def __call__(self, optimizer: base.Optimizer, candidate: p.Parameter, loss: tp.F
         if hasattr(optimizer, "_configured_optimizer"):
             configopt = optimizer._configured_optimizer  # type: ignore
             if isinstance(configopt, base.ConfiguredOptimizer):
-                data.update({"#optimizer#" + x: y for x, y in configopt.config().items()})
+                data.update({"#optimizer#" + x: str(y) for x, y in configopt.config().items()})
         if isinstance(candidate._meta.get("sigma"), float):
             data["#meta-sigma"] = candidate._meta["sigma"]  # for TBPSA-like algorithms
         if candidate.generation > 1:

nevergrad/optimization/test_callbacks.py

@@ -55,6 +55,24 @@ def test_multiobjective_log_parameters(tmp_path: Path) -> None:
     assert len(logs) == 2
 
 
+def test_chaining_log_parameters(tmp_path: Path) -> None:
+    filepath = tmp_path / "logs.txt"
+    params = ng.p.Instrumentation(
+        None, 2.0, blublu="blublu", array=ng.p.Array(shape=(3, 2)), multiobjective=False
+    )
+    zmethods = ["CauchyLHSSearch", "DE", "CMA"]
+    ztmp1 = [ng.optimizers.registry[zmet] for zmet in zmethods]
+    optmodel = ng.families.Chaining(ztmp1, [50, 50])  #
+    optim = optmodel(parametrization=params, budget=100, num_workers=3)
+    logger = ng.callbacks.ParametersLogger(filepath)
+    optim.register_callback("tell", logger)
+    optim.minimize(_func, verbosity=2)
+    # read
+    logger = callbacks.ParametersLogger(filepath)
+    logs = logger.load_flattened()
+    assert len(logs) == 100
+
+
 def test_dump_callback(tmp_path: Path) -> None:
     filepath = tmp_path / "pickle.pkl"
     optimizer = optimizerlib.OnePlusOne(parametrization=2, budget=32)