Integrate initialize settings

spacy/language.py

@@ -1217,9 +1217,10 @@ class Language:
                 name="tokenizer",
             )
             self.tokenizer.initialize(get_examples, nlp=self, **tok_settings)
+        proc_settings = settings.get("components", {})
         for name, proc in self.pipeline:
             if hasattr(proc, "initialize"):
-                p_settings = settings.get(name, {})
+                p_settings = proc_settings.get(name, {})
                 p_settings = validate_init_settings(
                     proc.initialize, p_settings, section="components", name=name
                 )

spacy/training/initialize.py

@@ -55,9 +55,7 @@ def init_nlp(config: Config, *, use_gpu: int = -1, silent: bool = True) -> Langu
             msg.info(f"Resuming training for: {resume_components}")
             nlp.resume_training(sgd=optimizer)
     with nlp.select_pipes(disable=[*frozen_components, *resume_components]):
-        nlp.initialize(
-            lambda: train_corpus(nlp), sgd=optimizer, settings=I["components"]
-        )
+        nlp.initialize(lambda: train_corpus(nlp), sgd=optimizer, settings=I)
         msg.good("Initialized pipeline components")
     # Verify the config after calling 'initialize' to ensure labels
     # are properly initialized