Add error for non-string labels (#4690)

Add error when attempting to add non-string labels to `Tagger` or
`TextCategorizer`.

spacy/errors.py

@@ -529,6 +529,7 @@ class Errors(object):
     E185 = ("Received invalid attribute in component attribute declaration: "
             "{obj}.{attr}\nAttribute '{attr}' does not exist on {obj}.")
     E186 = ("'{tok_a}' and '{tok_b}' are different texts.")
+    E187 = ("Only unicode strings are supported as labels.")
 
 
 @add_codes

spacy/pipeline/pipes.pyx

@@ -13,6 +13,7 @@ from thinc.misc import LayerNorm
 from thinc.neural.util import to_categorical
 from thinc.neural.util import get_array_module
 
+from ..compat import basestring_
 from ..tokens.doc cimport Doc
 from ..syntax.nn_parser cimport Parser
 from ..syntax.ner cimport BiluoPushDown
@@ -547,6 +548,8 @@ class Tagger(Pipe):
         return build_tagger_model(n_tags, **cfg)
 
     def add_label(self, label, values=None):
+        if not isinstance(label, basestring_):
+            raise ValueError(Errors.E187)
         if label in self.labels:
             return 0
         if self.model not in (True, False, None):
@@ -1016,6 +1019,8 @@ class TextCategorizer(Pipe):
         return float(mean_square_error), d_scores
 
     def add_label(self, label):
+        if not isinstance(label, basestring_):
+            raise ValueError(Errors.E187)
         if label in self.labels:
             return 0
         if self.model not in (None, True, False):

spacy/tests/pipeline/test_tagger.py

@@ -0,0 +1,14 @@
+# coding: utf8
+from __future__ import unicode_literals
+
+import pytest
+from spacy.language import Language
+from spacy.pipeline import Tagger
+
+
+def test_label_types():
+    nlp = Language()
+    nlp.add_pipe(nlp.create_pipe("tagger"))
+    nlp.get_pipe("tagger").add_label("A")
+    with pytest.raises(ValueError):
+        nlp.get_pipe("tagger").add_label(9)

spacy/tests/pipeline/test_textcat.py

@@ -62,3 +62,11 @@ def test_textcat_learns_multilabel():
                     assert score < 0.5
                 else:
                     assert score > 0.5
+
+
+def test_label_types():
+    nlp = Language()
+    nlp.add_pipe(nlp.create_pipe("textcat"))
+    nlp.get_pipe("textcat").add_label("answer")
+    with pytest.raises(ValueError):
+        nlp.get_pipe("textcat").add_label(9)