Fill in missing morphologizer methods

spacy/_morphologizer.pyx

@@ -9,9 +9,9 @@ from .util import msgpack
 from .util import msgpack_numpy
 
 from thinc.api import chain
-from thinc.neural.util import to_categorical, copy_array
+from thinc.neural.util import to_categorical, copy_array, get_array_module
 from . import util
-from .pipe import Pipe
+from .pipeline import Pipe
 from ._ml import Tok2Vec, build_morphologizer_model
 from ._ml import link_vectors_to_models, zero_init, flatten
 from ._ml import create_default_optimizer
@@ -20,6 +20,7 @@ from .compat import json_dumps, basestring_
 from .tokens.doc cimport Doc
 from .vocab cimport Vocab
 from .morphology cimport Morphology
+from .morphology import parse_feature
 from .pipeline import Pipe
 
 
@@ -118,7 +119,7 @@ class Morphologizer(Pipe):
                     target[idx] = guesses[idx]
                 else:
                     for feature in features:
-                        column = feature_to_column(feature) # TODO
+                        _, column = parse_feature(feature)
                         target[idx, column] = 1
                 idx += 1
         target = self.model.ops.xp.array(target, dtype='f')
@@ -132,7 +133,10 @@ class Morphologizer(Pipe):
             yield
 
 def scores_to_guesses(scores, out_sizes):
-    raise NotImplementedError
-
-def feature_to_column(feature):
-    raise NotImplementedError
+    xp = get_array_module(scores)
+    guesses = xp.zeros((scores.shape[0], len(out_sizes)), dtype='i')
+    offset = 0
+    for i, size in enumerate(out_sizes):
+        guesses[:, i] = scores[:, offset : offset + size].argmax(axis=1)
+        offset += size
+    return guesses