Update lexeme_norm checks

* Add util method for check
* Add new languages to list with lexeme norm tables
* Add check to all relevant components
* Add config details to warning message

Note that we're not actually inspecting the model config to see if
`NORM` is used as an attribute, so it may warn in cases where it's not
relevant.

spacy/errors.py

@@ -73,8 +73,13 @@ class Warnings:
             "degree. If this is intentional or the language you're using "
             "doesn't have a normalization table, please ignore this warning. "
             "If this is surprising, make sure you have the spacy-lookups-data "
-            "package installed. The languages with lexeme normalization tables "
-            "are currently: {langs}")
+            "package installed and load the table in your config. The "
+            "languages with lexeme normalization tables are currently: "
+            "{langs}\n\nLoad the table in your config with:\n\n"
+            "[initialize.lookups]\n"
+            "@misc = \"spacy.LookupsDataLoader.v1\"\n"
+            "lang = ${{nlp.lang}}\n"
+            "tables = [\"lexeme_norm\"]\n")
     W035 = ('Discarding subpattern "{pattern}" due to an unrecognized '
             "attribute or operator.")
 

spacy/pipeline/morphologizer.pyx

@@ -137,6 +137,7 @@ class Morphologizer(Tagger):
         DOCS: https://spacy.io/api/morphologizer#initialize
         """
         validate_get_examples(get_examples, "Morphologizer.initialize")
+        util.check_lexeme_norms(self.vocab, "morphologizer")
         if labels is not None:
             self.cfg["labels_morph"] = labels["morph"]
             self.cfg["labels_pos"] = labels["pos"]

spacy/pipeline/senter.pyx

@@ -138,6 +138,7 @@ class SentenceRecognizer(Tagger):
         DOCS: https://spacy.io/api/sentencerecognizer#initialize
         """
         validate_get_examples(get_examples, "SentenceRecognizer.initialize")
+        util.check_lexeme_norms(self.vocab, "senter")
         doc_sample = []
         label_sample = []
         assert self.labels, Errors.E924.format(name=self.name)

spacy/pipeline/tagger.pyx

@@ -249,6 +249,7 @@ class Tagger(TrainablePipe):
         DOCS: https://spacy.io/api/tagger#initialize
         """
         validate_get_examples(get_examples, "Tagger.initialize")
+        util.check_lexeme_norms(self.vocab, "tagger")
         if labels is not None:
             for tag in labels:
                 self.add_label(tag)

spacy/pipeline/transition_parser.pyx

@@ -493,10 +493,7 @@ cdef class Parser(TrainablePipe):
 
     def initialize(self, get_examples, nlp=None, labels=None):
         validate_get_examples(get_examples, "Parser.initialize")
-        lexeme_norms = self.vocab.lookups.get_table("lexeme_norm", {})
-        if len(lexeme_norms) == 0 and self.vocab.lang in util.LEXEME_NORM_LANGS:
-            langs = ", ".join(util.LEXEME_NORM_LANGS)
-            util.logger.debug(Warnings.W033.format(model="parser or NER", langs=langs))
+        util.check_lexeme_norms(self.vocab, "parser or NER")
         if labels is not None:
             actions = dict(labels)
         else:

spacy/util.py

@@ -59,7 +59,7 @@ if TYPE_CHECKING:
 
 OOV_RANK = numpy.iinfo(numpy.uint64).max
 DEFAULT_OOV_PROB = -20
-LEXEME_NORM_LANGS = ["da", "de", "el", "en", "id", "lb", "pt", "ru", "sr", "ta", "th"]
+LEXEME_NORM_LANGS = ["cs", "da", "de", "el", "en", "id", "lb", "mk", "pt", "ru", "sr", "ta", "th"]
 
 # Default order of sections in the config.cfg. Not all sections needs to exist,
 # and additional sections are added at the end, in alphabetical order.
@@ -70,7 +70,9 @@ CONFIG_SECTION_ORDER = ["paths", "variables", "system", "nlp", "components", "co
 
 logger = logging.getLogger("spacy")
 logger_stream_handler = logging.StreamHandler()
-logger_stream_handler.setFormatter(logging.Formatter("[%(asctime)s] [%(levelname)s] %(message)s"))
+logger_stream_handler.setFormatter(
+    logging.Formatter("[%(asctime)s] [%(levelname)s] %(message)s")
+)
 logger.addHandler(logger_stream_handler)
 
 
@@ -1454,10 +1456,13 @@ def is_cython_func(func: Callable) -> bool:
     if hasattr(func, attr):  # function or class instance
         return True
     # https://stackoverflow.com/a/55767059
-    if hasattr(func, "__qualname__") and hasattr(func, "__module__") \
-        and func.__module__ in sys.modules:  # method
-            cls_func = vars(sys.modules[func.__module__])[func.__qualname__.split(".")[0]]
-            return hasattr(cls_func, attr)
+    if (
+        hasattr(func, "__qualname__")
+        and hasattr(func, "__module__")
+        and func.__module__ in sys.modules
+    ):  # method
+        cls_func = vars(sys.modules[func.__module__])[func.__qualname__.split(".")[0]]
+        return hasattr(cls_func, attr)
     return False
 
 
@@ -1508,7 +1513,16 @@ def warn_if_jupyter_cupy():
     """
     if is_in_jupyter():
         from thinc.backends.cupy_ops import CupyOps
+
         if CupyOps.xp is not None:
             from thinc.backends import contextvars_eq_thread_ops
+
             if not contextvars_eq_thread_ops():
                 warnings.warn(Warnings.W111)
+
+
+def check_lexeme_norms(vocab, component_name):
+    lexeme_norms = vocab.lookups.get_table("lexeme_norm", {})
+    if len(lexeme_norms) == 0 and vocab.lang in LEXEME_NORM_LANGS:
+        langs = ", ".join(LEXEME_NORM_LANGS)
+        logger.debug(Warnings.W033.format(model=component_name, langs=langs))