diff --git a/spacy/tokens/_serialize.py b/spacy/tokens/_serialize.py
index 762854f76..873d85835 100644
--- a/spacy/tokens/_serialize.py
+++ b/spacy/tokens/_serialize.py
@@ -13,12 +13,9 @@ from ..errors import Errors
 from ..util import SimpleFrozenList, ensure_path
 from ..vocab import Vocab
 from ._dict_proxies import SpanGroups
+from .doc import DOCBIN_ALL_ATTRS as ALL_ATTRS
 from .doc import Doc
 
-# fmt: off
-ALL_ATTRS = ("ORTH", "NORM", "TAG", "HEAD", "DEP", "ENT_IOB", "ENT_TYPE", "ENT_KB_ID", "ENT_ID", "LEMMA", "MORPH", "POS", "SENT_START")
-# fmt: on
-
 
 class DocBin:
     """Pack Doc objects for binary serialization.
diff --git a/spacy/tokens/doc.pyx b/spacy/tokens/doc.pyx
index c5a2721a3..206253949 100644
--- a/spacy/tokens/doc.pyx
+++ b/spacy/tokens/doc.pyx
@@ -52,12 +52,18 @@ from ..errors import Errors, Warnings
 from ..morphology import Morphology
 from ..util import get_words_and_spaces
 from ._retokenize import Retokenizer
-from ._serialize import ALL_ATTRS as DOCBIN_ALL_ATTRS
 from .underscore import Underscore, get_ext_args
 
 DEF PADDING = 5
 
 
+# We store the docbin attrs here rather than in _serialize to avoid
+# import cycles.
+
+# fmt: off
+DOCBIN_ALL_ATTRS = ("ORTH", "NORM", "TAG", "HEAD", "DEP", "ENT_IOB", "ENT_TYPE", "ENT_KB_ID", "ENT_ID", "LEMMA", "MORPH", "POS", "SENT_START")
+# fmt: on
+
 cdef int bounds_check(int i, int length, int padding) except -1:
     if (i + padding) < 0:
         raise IndexError(Errors.E026.format(i=i, length=length))
diff --git a/spacy/training/callbacks.py b/spacy/training/callbacks.py
index 053227a11..21c3d56a1 100644
--- a/spacy/training/callbacks.py
+++ b/spacy/training/callbacks.py
@@ -1,15 +1,17 @@
-from typing import Callable, Optional
+from typing import TYPE_CHECKING, Callable, Optional
 
 from ..errors import Errors
-from ..language import Language
 from ..util import load_model, logger, registry
 
+if TYPE_CHECKING:
+    from ..language import Language
+
 
 @registry.callbacks("spacy.copy_from_base_model.v1")
 def create_copy_from_base_model(
     tokenizer: Optional[str] = None,
     vocab: Optional[str] = None,
-) -> Callable[[Language], Language]:
+) -> Callable[["Language"], "Language"]:
     def copy_from_base_model(nlp):
         if tokenizer:
             logger.info("Copying tokenizer from: %s", tokenizer)