Remove assumption of component being a Pipe object or having a .cfg attribute.

spacy/cli/find_threshold.py

@@ -7,7 +7,6 @@ from typing import Optional, Tuple, Any, Dict, List
 import numpy
 import wasabi.tables
 
-from ..pipeline import TrainablePipe, Pipe
 from ..errors import Errors
 from ..training import Corpus
 from ._util import app, Arg, Opt, import_code, setup_gpu
@@ -111,14 +110,11 @@ def find_threshold(
         wasabi.msg.fail("Evaluation data not found", data_path, exits=1)
     nlp = util.load_model(model)
 
-    pipe: Optional[Pipe] = None
+    pipe: Optional[Any] = None
     try:
         pipe = nlp.get_pipe(pipe_name)
     except KeyError as err:
         wasabi.msg.fail(title=str(err), exits=1)
-
-    if not isinstance(pipe, TrainablePipe):
-        raise TypeError(Errors.E1044)
     if not hasattr(pipe, "scorer"):
         raise AttributeError(Errors.E1045)
 
@@ -170,10 +166,16 @@ def find_threshold(
                 threshold,
             ),
         )
-        nlp.get_pipe(pipe_name).cfg = set_nested_item(pipe.cfg, config_keys, threshold)
+        if hasattr(pipe, "cfg"):
+            setattr(
+                nlp.get_pipe(pipe_name),
+                "cfg",
+                set_nested_item(getattr(pipe, "cfg"), config_keys, threshold),
+            )
+
         scores[threshold] = nlp.evaluate(dev_dataset)[scores_key]
-        if not (
-            isinstance(scores[threshold], float) or isinstance(scores[threshold], int)
+        if not isinstance(scores[threshold], float) and not isinstance(
+            scores[threshold], int
         ):
             wasabi.msg.fail(
                 f"Returned score for key '{scores_key}' is not numeric. Threshold optimization only works for numeric "