Add temporary #type:ignore s

spacy/ml/models/tok2vec.py

@@ -186,6 +186,7 @@ def MultiHashEmbed(
         )
     return model
 
+
 def process_affix_config_group(
     label: str,
     start_len: Optional[int],
@@ -209,6 +210,7 @@ def process_affix_config_group(
         raise ValueError(Errors.E1045.format(label=label))
     return rows if rows is not None else []
 
+
 @registry.architectures("spacy.AffixMultiHashEmbed.v1")
 def AffixMultiHashEmbed(
     width: int,
@@ -237,7 +239,6 @@ def AffixMultiHashEmbed(
     TODO
     """
 
-
     if len(rows) != len(attrs):
         raise ValueError(f"Mismatched lengths: {len(rows)} vs {len(attrs)}")
 
@@ -272,7 +273,7 @@ def AffixMultiHashEmbed(
         )
     )
 
-    embeddings = [
+    embeddings = [  # type:ignore
         HashEmbed(width, row, column=i, seed=i + 7, dropout=0.0)
         for i, row in enumerate(rows)
     ]
@@ -306,8 +307,8 @@ def AffixMultiHashEmbed(
             )
         )
 
-    if include_static_vectors:
-        feature_extractor: Model[List[Doc], Ragged] = chain(
+    if include_static_vectors: 
+        feature_extractor: Model[List[Doc], Ragged] = chain( # type: ignore
             concatenate(*extractors),
             cast(Model[List[Ints2d], Ragged], list2ragged()),
             with_array(concatenate(*embeddings)),
@@ -321,7 +322,7 @@ def AffixMultiHashEmbed(
             ragged2list(),
         )
     else:
-        model = chain(
+        model = chain( # type: ignore
             concatenate(*extractors),
             cast(Model[List[Ints2d], Ragged], list2ragged()),
             with_array(concatenate(*embeddings)),