fix parser tests to work with example (most still failing)

spacy/syntax/arc_eager.pyx

@@ -497,7 +497,7 @@ cdef class ArcEager(TransitionSystem):
     def has_gold(self, gold, start=0, end=None):
         raise NotImplementedError
 
-    def preprocess_gold(self, gold):
+    def preprocess_gold(self, example):
         raise NotImplementedError
 
     cdef Transition lookup_transition(self, object name_or_id) except *:

spacy/syntax/ner.pyx

@@ -94,7 +94,7 @@ cdef class BiluoPushDown(TransitionSystem):
     def has_gold(self, gold, start=0, end=None):
         raise NotImplementedError
 
-    def preprocess_gold(self, gold):
+    def preprocess_gold(self, example):
         raise NotImplementedError
 
     cdef Transition lookup_transition(self, object name) except *:

spacy/syntax/transition_system.pyx

@@ -97,7 +97,7 @@ cdef class TransitionSystem:
     def finalize_doc(self, doc):
         pass
 
-    def preprocess_gold(self, gold):
+    def preprocess_gold(self, example):
         raise NotImplementedError
 
     def is_gold_parse(self, StateClass state, example):

spacy/tests/parser/test_arc_eager_oracle.py

@@ -1,6 +1,7 @@
 import pytest
 from spacy.vocab import Vocab
 
+from spacy.gold import Example
 from spacy.pipeline.defaults import default_parser
 from spacy.pipeline import DependencyParser
 from spacy.tokens import Doc
@@ -11,9 +12,9 @@ from spacy.syntax.arc_eager import ArcEager
 
 def get_sequence_costs(M, words, heads, deps, transitions):
     doc = Doc(Vocab(), words=words)
-    gold = GoldParse(doc, heads=heads, deps=deps)
+    example = Example.from_dict(doc, {"heads": heads, "deps": deps})
     state = StateClass(doc)
-    M.preprocess_gold(gold)
+    M.preprocess_gold(example)
     cost_history = []
     for gold_action in transitions:
         state_costs = {}
@@ -149,6 +150,6 @@ def test_get_oracle_actions():
         elif head < i:
             parser.moves.add_action(3, dep)
     heads, deps = projectivize(heads, deps)
-    gold = GoldParse(doc, words=words, tags=tags, heads=heads, deps=deps)
+    example = Example.from_dict(doc, {"words": words, "tags": tags, "heads": heads, "deps": deps})
-    parser.moves.preprocess_gold(gold)
+    parser.moves.preprocess_gold(example)
-    parser.moves.get_oracle_sequence(doc, gold)
+    parser.moves.get_oracle_sequence(example)

spacy/tests/parser/test_ner.py

@@ -1,4 +1,6 @@
 import pytest
+from spacy.attrs import ENT_IOB
+
 from spacy import util
 from spacy.lang.en import English
 from spacy.pipeline.defaults import default_ner
@@ -8,7 +10,7 @@ from spacy.syntax.ner import BiluoPushDown
 from spacy.tokens import Doc
 
 from ..util import make_tempdir
-
+from ...gold import Example
 
 TRAIN_DATA = [
     ("Who is Shaka Khan?", {"entities": [(7, 17, "PERSON")]}),
@@ -48,41 +50,45 @@ def tsys(vocab, entity_types):
 
 
 def test_get_oracle_moves(tsys, doc, entity_annots):
-    gold = GoldParse(doc, entities=entity_annots)
+    example = Example.from_dict(doc, {"entities": entity_annots})
-    tsys.preprocess_gold(gold)
+    tsys.preprocess_gold(example)
-    act_classes = tsys.get_oracle_sequence(doc, gold)
+    act_classes = tsys.get_oracle_sequence(example)
     names = [tsys.get_class_name(act) for act in act_classes]
     assert names == ["U-PERSON", "O", "O", "B-GPE", "L-GPE", "O"]
 
 
 def test_get_oracle_moves_negative_entities(tsys, doc, entity_annots):
     entity_annots = [(s, e, "!" + label) for s, e, label in entity_annots]
-    gold = GoldParse(doc, entities=entity_annots)
+    example = Example.from_dict(doc, {"entities": entity_annots})
-    for i, tag in enumerate(gold.ner):
+    ex_dict = example.to_dict()
+
+    for i, tag in enumerate(ex_dict["doc_annotation"]["entities"]):
         if tag == "L-!GPE":
-            gold.ner[i] = "-"
+            ex_dict["doc_annotation"]["entities"][i] = "-"
-    tsys.preprocess_gold(gold)
+    example = Example.from_dict(doc, ex_dict)
-    act_classes = tsys.get_oracle_sequence(doc, gold)
+
+    tsys.preprocess_gold(example)
+    act_classes = tsys.get_oracle_sequence(example)
     names = [tsys.get_class_name(act) for act in act_classes]
     assert names
 
 
 def test_get_oracle_moves_negative_entities2(tsys, vocab):
     doc = Doc(vocab, words=["A", "B", "C", "D"])
-    gold = GoldParse(doc, entities=[])
+    entity_annots = ["B-!PERSON", "L-!PERSON", "B-!PERSON", "L-!PERSON"]
-    gold.ner = ["B-!PERSON", "L-!PERSON", "B-!PERSON", "L-!PERSON"]
+    example = Example.from_dict(doc, {"entities": entity_annots})
-    tsys.preprocess_gold(gold)
+    tsys.preprocess_gold(example)
-    act_classes = tsys.get_oracle_sequence(doc, gold)
+    act_classes = tsys.get_oracle_sequence(example)
     names = [tsys.get_class_name(act) for act in act_classes]
     assert names
 
 
 def test_get_oracle_moves_negative_O(tsys, vocab):
     doc = Doc(vocab, words=["A", "B", "C", "D"])
-    gold = GoldParse(doc, entities=[])
+    entity_annots = ["O", "!O", "O", "!O"]
-    gold.ner = ["O", "!O", "O", "!O"]
+    example = Example.from_dict(doc, {"entities": []})
-    tsys.preprocess_gold(gold)
+    tsys.preprocess_gold(example)
-    act_classes = tsys.get_oracle_sequence(doc, gold)
+    act_classes = tsys.get_oracle_sequence(example)
     names = [tsys.get_class_name(act) for act in act_classes]
     assert names
 
@@ -92,7 +98,7 @@ def test_oracle_moves_missing_B(en_vocab):
     biluo_tags = [None, None, "L-PRODUCT"]
 
     doc = Doc(en_vocab, words=words)
-    gold = GoldParse(doc, words=words, entities=biluo_tags)
+    example = Example.from_dict(doc, {"words": words, "entities": biluo_tags})
 
     moves = BiluoPushDown(en_vocab.strings)
     move_types = ("M", "B", "I", "L", "U", "O")
@@ -107,8 +113,8 @@ def test_oracle_moves_missing_B(en_vocab):
             moves.add_action(move_types.index("I"), label)
             moves.add_action(move_types.index("L"), label)
             moves.add_action(move_types.index("U"), label)
-    moves.preprocess_gold(gold)
+    moves.preprocess_gold(example)
-    moves.get_oracle_sequence(doc, gold)
+    moves.get_oracle_sequence(example)
 
 
 def test_oracle_moves_whitespace(en_vocab):
@@ -116,7 +122,7 @@ def test_oracle_moves_whitespace(en_vocab):
     biluo_tags = ["O", "O", "O", "B-ORG", None, "I-ORG", "L-ORG", "O", "O"]
 
     doc = Doc(en_vocab, words=words)
-    gold = GoldParse(doc, words=words, entities=biluo_tags)
+    example = Example.from_dict(doc, {"entities": biluo_tags})
 
     moves = BiluoPushDown(en_vocab.strings)
     move_types = ("M", "B", "I", "L", "U", "O")
@@ -128,8 +134,8 @@ def test_oracle_moves_whitespace(en_vocab):
         else:
             action, label = tag.split("-")
             moves.add_action(move_types.index(action), label)
-    moves.preprocess_gold(gold)
+    moves.preprocess_gold(example)
-    moves.get_oracle_sequence(doc, gold)
+    moves.get_oracle_sequence(example)
 
 
 def test_accept_blocked_token():

spacy/tests/parser/test_neural_parser.py

@@ -1,4 +1,6 @@
 import pytest
+
+from spacy.gold import Example
 from spacy.pipeline.defaults import default_parser, default_tok2vec
 from spacy.vocab import Vocab
 from spacy.syntax.arc_eager import ArcEager
@@ -71,7 +73,8 @@ def test_update_doc(parser, model, doc, gold):
         weights -= 0.001 * gradient
         return weights, gradient
 
-    parser.update((doc, gold), sgd=optimize)
+    example = Example.from_dict(doc, gold)
+    parser.update([example], sgd=optimize)
 
 
 @pytest.mark.xfail

spacy/tests/parser/test_nn_beam.py

@@ -42,11 +42,6 @@ def tokvecs(docs, vector_size):
     return output
 
 
-@pytest.fixture
-def golds(docs):
-    return [GoldParse(doc) for doc in docs]
-
-
 @pytest.fixture
 def batch_size(docs):
     return len(docs)
@@ -77,19 +72,24 @@ def scores(moves, batch_size, beam_width):
     ]
 
 
+# All tests below are skipped after removing Beam stuff during the Example/GoldParse refactor
+@pytest.mark.skip
 def test_create_beam(beam):
     pass
 
 
+@pytest.mark.skip
 def test_beam_advance(beam, scores):
     beam.advance(scores)
 
 
+@pytest.mark.skip
 def test_beam_advance_too_few_scores(beam, scores):
     with pytest.raises(IndexError):
         beam.advance(scores[:-1])
 
 
+@pytest.mark.skip
 def test_beam_parse():
     nlp = Language()
     config = {"learn_tokens": False, "min_action_freq": 30, "beam_width":  1, "beam_update_prob": 1.0}

spacy/tests/parser/test_preset_sbd.py

@@ -3,6 +3,7 @@ from thinc.api import Adam
 from spacy.attrs import NORM
 from spacy.vocab import Vocab
 
+from spacy.gold import Example
 from spacy.pipeline.defaults import default_parser
 from spacy.tokens import Doc
 from spacy.pipeline import DependencyParser
@@ -27,8 +28,8 @@ def parser(vocab):
     for i in range(10):
         losses = {}
         doc = Doc(vocab, words=["a", "b", "c", "d"])
-        gold = dict(heads=[1, 1, 3, 3], deps=["left", "ROOT", "left", "ROOT"])
+        example = Example.from_dict(doc, {"heads": [1, 1, 3, 3], "deps": ["left", "ROOT", "left", "ROOT"]})
-        parser.update((doc, gold), sgd=sgd, losses=losses)
+        parser.update([example], sgd=sgd, losses=losses)
     return parser