Move replacement logic to Language.from_config

spacy/language.py

@@ -1629,6 +1629,7 @@ class Language:
         # Later we replace the component config with the raw config again.
         interpolated = filled.interpolate() if not filled.is_interpolated else filled
         pipeline = interpolated.get("components", {})
+        sourced = util.get_sourced_components(interpolated)
         # If components are loaded from a source (existing models), we cache
         # them here so they're only loaded once
         source_nlps = {}
@@ -1671,6 +1672,17 @@ class Language:
                 raise ValueError(
                     Errors.E942.format(name="pipeline_creation", value=type(nlp))
                 )
+        # Detect components with listeners that are not frozen consistently
+        for name, proc in nlp.pipeline:
+            if getattr(proc, "listening_components", None):  # e.g. tok2vec/transformer
+                for listener in proc.listening_components:
+                    # If it's a component sourced from another pipeline, we check if
+                    # the tok2vec listeners should be replaced with standalone tok2vec
+                    # models (e.g. so component can be frozen without its performance
+                    # degrading when other components/tok2vec are updated)
+                    paths = sourced.get(listener, {}).get("replace_listeners", [])
+                    if paths:
+                        nlp.replace_listeners(name, listener, paths)
         return nlp
 
     def replace_listeners(
@@ -1744,6 +1756,7 @@ class Language:
             # Go over the listener layers and replace them
             for listener in pipe_listeners:
                 util.replace_model_node(pipe.model, listener, tok2vec.model.copy())
+                tok2vec.remove_listener(listener, pipe_name)
 
     def to_disk(
         self, path: Union[str, Path], *, exclude: Iterable[str] = SimpleFrozenList()

spacy/training/initialize.py

@@ -14,7 +14,8 @@ from ..vectors import Vectors
 from ..errors import Errors, Warnings
 from ..schemas import ConfigSchemaTraining
 from ..util import registry, load_model_from_config, resolve_dot_names, logger
-from ..util import load_model, ensure_path, OOV_RANK, DEFAULT_OOV_PROB
+from ..util import load_model, ensure_path, get_sourced_components
+from ..util import OOV_RANK, DEFAULT_OOV_PROB
 
 if TYPE_CHECKING:
     from ..language import Language  # noqa: F401
@@ -70,14 +71,7 @@ def init_nlp(config: Config, *, use_gpu: int = -1) -> "Language":
     for name, proc in nlp.pipeline:
         if getattr(proc, "listening_components", None):  # e.g. tok2vec/transformer
             for listener in proc.listening_components:
-                # If it's a component sourced from another pipeline, we check if
+                if listener in frozen_components and name not in frozen_components:
-                # the tok2vec listeners should be replaced with standalone tok2vec
-                # models (e.g. so component can be frozen without its performance
-                # degrading when other components/tok2vec are updated)
-                paths = sourced.get(listener, {}).get("replace_listeners", [])
-                if paths:
-                    nlp.replace_listeners(name, listener, paths)
-                elif listener in frozen_components and name not in frozen_components:
                     logger.warning(Warnings.W087.format(name=name, listener=listener))
                 # We always check this regardless, in case user freezes tok2vec
                 if listener not in frozen_components and name in frozen_components:
@@ -181,20 +175,6 @@ def init_tok2vec(
     return False
 
 
-def get_sourced_components(
-    config: Union[Dict[str, Any], Config]
-) -> Dict[str, Dict[str, Any]]:
-    """RETURNS (List[str]): All sourced components in the original config,
-    e.g. {"source": "en_core_web_sm"}. If the config contains a key
-    "factory", we assume it refers to a component factory.
-    """
-    return {
-        name: cfg
-        for name, cfg in config.get("components", {}).items()
-        if "factory" not in cfg and "source" in cfg
-    }
-
-
 def convert_vectors(
     nlp: "Language",
     vectors_loc: Optional[Path],

spacy/util.py

@@ -434,6 +434,20 @@ def load_model_from_config(
     return nlp
 
 
+def get_sourced_components(
+    config: Union[Dict[str, Any], Config]
+) -> Dict[str, Dict[str, Any]]:
+    """RETURNS (List[str]): All sourced components in the original config,
+    e.g. {"source": "en_core_web_sm"}. If the config contains a key
+    "factory", we assume it refers to a component factory.
+    """
+    return {
+        name: cfg
+        for name, cfg in config.get("components", {}).items()
+        if "factory" not in cfg and "source" in cfg
+    }
+
+
 def resolve_dot_names(config: Config, dot_names: List[Optional[str]]) -> Tuple[Any]:
     """Resolve one or more "dot notation" names, e.g. corpora.train.
     The paths could point anywhere into the config, so we don't know which
@@ -1480,5 +1494,6 @@ def _pipe(docs, proc, name, default_error_handler, kwargs):
 def raise_error(proc_name, proc, docs, e):
     raise e
 
+
 def ignore_error(proc_name, proc, docs, e):
     pass