Use max(uint64) for OOV lexeme rank

spacy/_ml.py

@@ -289,7 +289,7 @@ def link_vectors_to_models(vocab):
         if word.orth in vectors.key2row:
             word.rank = vectors.key2row[word.orth]
         else:
-            word.rank = 0
+            word.rank = util.OOV_RANK
     data = ops.asarray(vectors.data)
     # Set an entry here, so that vectors are accessed by StaticVectors
     # (unideal, I know)

spacy/cli/init_model.py

@@ -16,7 +16,7 @@
 
 from ..vectors import Vectors
 from ..errors import Errors, Warnings, user_warning
-from ..util import ensure_path, get_lang_class
+from ..util import ensure_path, get_lang_class, OOV_RANK
 
 try:
     import ftfy
@@ -148,7 +148,7 @@ def create_model(lang, lex_attrs, name=None):
     lang_class = get_lang_class(lang)
     nlp = lang_class()
     for lexeme in nlp.vocab:
-        lexeme.rank = 0
+        lexeme.rank = OOV_RANK
     lex_added = 0
     for attrs in lex_attrs:
         if "settings" in attrs:

spacy/lexeme.pxd

@@ -10,6 +10,7 @@ from numpy cimport ndarray
 
 
 cdef LexemeC EMPTY_LEXEME
+cdef attr_t OOV_RANK
 
 cdef class Lexeme:
     cdef LexemeC* c

spacy/lexeme.pyx

@@ -11,6 +11,7 @@ np.import_array()
 import numpy
 from thinc.neural.util import get_array_module
 
+from libc.stdint cimport UINT64_MAX
 from .typedefs cimport attr_t, flags_t
 from .attrs cimport IS_ALPHA, IS_ASCII, IS_DIGIT, IS_LOWER, IS_PUNCT, IS_SPACE
 from .attrs cimport IS_TITLE, IS_UPPER, LIKE_URL, LIKE_NUM, LIKE_EMAIL, IS_STOP
@@ -21,7 +22,9 @@ from .attrs import intify_attrs
 from .errors import Errors, Warnings, user_warning
 
 
+OOV_RANK = UINT64_MAX
 memset(&EMPTY_LEXEME, 0, sizeof(LexemeC))
+EMPTY_LEXEME.id = OOV_RANK
 
 
 cdef class Lexeme:

spacy/tests/vocab_vectors/test_lexeme.py

@@ -2,7 +2,9 @@
 from __future__ import unicode_literals
 
 import pytest
+import numpy
 from spacy.attrs import IS_ALPHA, IS_DIGIT
+from spacy.util import OOV_RANK
 
 
 @pytest.mark.parametrize("text1,prob1,text2,prob2", [("NOUN", -1, "opera", -2)])
@@ -69,3 +71,10 @@ def test_lexeme_bytes_roundtrip(en_vocab):
     assert one.orth == alpha.orth
     assert one.lower == alpha.lower
     assert one.lower_ == alpha.lower_
+
+
+def test_vocab_lexeme_oov_rank(en_vocab):
+    """Test that default rank is OOV_RANK."""
+    lex = en_vocab["word"]
+    assert OOV_RANK == numpy.iinfo(numpy.uint64).max
+    assert lex.rank == OOV_RANK

spacy/util.py

@@ -12,6 +12,7 @@
 import functools
 import itertools
 import numpy.random
+import numpy
 import srsly
 import catalogue
 import sys
@@ -34,6 +35,7 @@
 
 _data_path = Path(__file__).parent / "data"
 _PRINT_ENV = False
+OOV_RANK = numpy.iinfo(numpy.uint64).max
 
 
 class registry(object):

spacy/vocab.pyx

@@ -7,7 +7,7 @@ import srsly
 from collections import OrderedDict
 from thinc.neural.util import get_array_module
 
-from .lexeme cimport EMPTY_LEXEME
+from .lexeme cimport EMPTY_LEXEME, OOV_RANK
 from .lexeme cimport Lexeme
 from .typedefs cimport attr_t
 from .tokens.token cimport Token
@@ -165,9 +165,9 @@ cdef class Vocab:
         lex.orth = self.strings.add(string)
         lex.length = len(string)
         if self.vectors is not None:
-            lex.id = self.vectors.key2row.get(lex.orth, 0)
+            lex.id = self.vectors.key2row.get(lex.orth, OOV_RANK)
         else:
-            lex.id = 0
+            lex.id = OOV_RANK
         if self.lex_attr_getters is not None:
             for attr, func in self.lex_attr_getters.items():
                 value = func(string)