fix loading normalizers from checkpoint with OTF

src/fairchem/core/modules/normalization/_load_utils.py

@@ -85,16 +85,19 @@ def _load_from_config(
     """
     modules = _load_check_duplicates(config, name)
     for target in config:
-        if target == "fit" and not config["fit"].get("fitted", False):
-            # remove values for output targets that have already been read from files
-            targets = [
-                target for target in config["fit"]["targets"] if target not in modules
-            ]
-            fit_kwargs.update(
-                {k: v for k, v in config["fit"].items() if k != "targets"}
-            )
-            modules.update(fit_fun(targets=targets, dataset=dataset, **fit_kwargs))
-            config["fit"]["fitted"] = True
+        if target == "fit":
+            if not config["fit"].get("fitted", False):
+                # remove values for output targets that have already been read from files
+                targets = [
+                    target
+                    for target in config["fit"]["targets"]
+                    if target not in modules
+                ]
+                fit_kwargs.update(
+                    {k: v for k, v in config["fit"].items() if k != "targets"}
+                )
+                modules.update(fit_fun(targets=targets, dataset=dataset, **fit_kwargs))
+                config["fit"]["fitted"] = True
         # if a single file for all outputs is not provided,
         # then check if a single file is provided for a specific output
         elif target != "file":

src/fairchem/core/modules/normalization/normalizer.py

@@ -269,14 +269,17 @@ def load_normalizers_from_config(
 ) -> dict[str, Normalizer]:
     """Create a dictionary with element references from a config."""
     # edit the config slightly to extract override args
-    if "fit" in config:
-        override_values = {
-            target: vals
-            for target, vals in config["fit"]["targets"].items()
-            if isinstance(vals, dict)
-        }
-        config["fit"]["override_values"] = override_values
-        config["fit"]["targets"] = list(config["fit"]["targets"].keys())
+    if "fit" in config:  # noqa
+        if "override_values" not in config["fit"] and isinstance(
+            config["fit"]["targets"], dict
+        ):
+            override_values = {
+                target: vals
+                for target, vals in config["fit"]["targets"].items()
+                if isinstance(vals, dict)
+            }
+            config["fit"]["override_values"] = override_values
+            config["fit"]["targets"] = list(config["fit"]["targets"].keys())
 
     return _load_from_config(
         config,