Disregard special tag _SP in check for new tag map (#5641)

* Skip special tag  _SP in check for new tag map

In `Tagger.begin_training()` check for new tags aside from `_SP` in the
new tag map initialized from the provided gold tuples when determining
whether to reinitialize the morphology with the new tag map.

* Simplify _SP check

spacy/pipeline/pipes.pyx

@@ -528,10 +528,10 @@ class Tagger(Pipe):
                         new_tag_map[tag] = orig_tag_map[tag]
                     else:
                         new_tag_map[tag] = {POS: X}
-        if "_SP" in orig_tag_map:
-            new_tag_map["_SP"] = orig_tag_map["_SP"]
         cdef Vocab vocab = self.vocab
         if new_tag_map:
+            if "_SP" in orig_tag_map:
+                new_tag_map["_SP"] = orig_tag_map["_SP"]
             vocab.morphology = Morphology(vocab.strings, new_tag_map,
                                           vocab.morphology.lemmatizer,
                                           exc=vocab.morphology.exc)

spacy/tests/pipeline/test_tagger.py

@@ -3,6 +3,7 @@ from __future__ import unicode_literals
 
 import pytest
 from spacy.language import Language
+from spacy.symbols import POS, NOUN
 
 
 def test_label_types():
@@ -11,3 +12,16 @@ def test_label_types():
     nlp.get_pipe("tagger").add_label("A")
     with pytest.raises(ValueError):
         nlp.get_pipe("tagger").add_label(9)
+
+
+def test_tagger_begin_training_tag_map():
+    """Test that Tagger.begin_training() without gold tuples does not clobber
+    the tag map."""
+    nlp = Language()
+    tagger = nlp.create_pipe("tagger")
+    orig_tag_count = len(tagger.labels)
+    tagger.add_label("A", {"POS": "NOUN"})
+    nlp.add_pipe(tagger)
+    nlp.begin_training()
+    assert nlp.vocab.morphology.tag_map["A"] == {POS: NOUN}
+    assert orig_tag_count + 1 == len(nlp.get_pipe("tagger").labels)