Force tagger to pass batch of docs into model in begin_training

spacy/pipeline/tagger.pyx

@@ -275,13 +275,18 @@ class Tagger(Pipe):
             err = Errors.E930.format(name="Tagger", obj=type(get_examples))
             raise ValueError(err)
         tags = set()
+        doc_sample = []
         for example in get_examples():
             for token in example.y:
                 tags.add(token.tag_)
+            if len(doc_sample) < 10:
+                doc_sample.append(example.x)
+        if not doc_sample:
+            doc_sample.append(Doc(self.vocab, words=["hello"]))
         for tag in sorted(tags):
             self.add_label(tag)
         self.set_output(len(self.labels))
-        self.model.initialize()
+        self.model.initialize(X=doc_sample)
         if sgd is None:
             sgd = self.create_optimizer()
         return sgd