Renaming gold & annotation_setter (#6042)

* version bump to 3.0.0a16

* rename "gold" folder to "training"

* rename 'annotation_setter' to 'set_extra_annotations'

* formatting

extra/example_data/textcat_example_data/textcatjsonl_to_trainjson.py

@@ -1,7 +1,7 @@
 from pathlib import Path
 import plac
 import spacy
-from spacy.gold import docs_to_json
+from spacy.training import docs_to_json
 import srsly
 import sys
 

setup.py

@@ -23,7 +23,7 @@ Options.docstrings = True
 
 PACKAGES = find_packages()
 MOD_NAMES = [
-    "spacy.gold.example",
+    "spacy.training.example",
     "spacy.parts_of_speech",
     "spacy.strings",
     "spacy.lexeme",
@@ -48,7 +48,7 @@ MOD_NAMES = [
     "spacy.pipeline._parser_internals.stateclass",
     "spacy.pipeline._parser_internals.transition_system",
     "spacy.tokenizer",
-    "spacy.gold.gold_io",
+    "spacy.training.gold_io",
     "spacy.tokens.doc",
     "spacy.tokens.span",
     "spacy.tokens.token",

spacy/about.py

@@ -1,6 +1,6 @@
 # fmt: off
 __title__ = "spacy-nightly"
-__version__ = "3.0.0a15"
+__version__ = "3.0.0a16"
 __release__ = True
 __download_url__ = "https://github.com/explosion/spacy-models/releases/download"
 __compatibility__ = "https://raw.githubusercontent.com/explosion/spacy-models/master/compatibility.json"

spacy/cli/convert.py

@@ -7,9 +7,9 @@ import re
 import sys
 
 from ._util import app, Arg, Opt
-from ..gold import docs_to_json
+from ..training import docs_to_json
 from ..tokens import DocBin
-from ..gold.converters import iob2docs, conll_ner2docs, json2docs, conllu2docs
+from ..training.converters import iob2docs, conll_ner2docs, json2docs, conllu2docs
 
 
 # Converters are matched by file extension except for ner/iob, which are

spacy/cli/debug_data.py

@@ -8,7 +8,7 @@ import typer
 
 from ._util import app, Arg, Opt, show_validation_error, parse_config_overrides
 from ._util import import_code, debug_cli, get_sourced_components
-from ..gold import Corpus, Example
+from ..training import Corpus, Example
 from ..pipeline._parser_internals import nonproj
 from ..language import Language
 from .. import util

spacy/cli/evaluate.py

@@ -5,7 +5,7 @@ import re
 import srsly
 from thinc.api import require_gpu, fix_random_seed
 
-from ..gold import Corpus
+from ..training import Corpus
 from ..tokens import Doc
 from ._util import app, Arg, Opt
 from ..scorer import Scorer

spacy/cli/train.py

@@ -16,7 +16,7 @@ from ._util import app, Arg, Opt, parse_config_overrides, show_validation_error
 from ._util import import_code, get_sourced_components
 from ..language import Language
 from .. import util
-from ..gold.example import Example
+from ..training.example import Example
 from ..errors import Errors
 
 

spacy/errors.py

@@ -66,7 +66,7 @@ class Warnings:
             "in problems with the vocab further on in the pipeline.")
     W030 = ("Some entities could not be aligned in the text \"{text}\" with "
             "entities \"{entities}\". Use "
-            "`spacy.gold.biluo_tags_from_offsets(nlp.make_doc(text), entities)`"
+            "`spacy.training.biluo_tags_from_offsets(nlp.make_doc(text), entities)`"
             " to check the alignment. Misaligned entities ('-') will be "
             "ignored during training.")
     W033 = ("Training a new {model} using a model with no lexeme normalization "

spacy/language.py

@@ -17,7 +17,7 @@ from timeit import default_timer as timer
 from .tokens.underscore import Underscore
 from .vocab import Vocab, create_vocab
 from .pipe_analysis import validate_attrs, analyze_pipes, print_pipe_analysis
-from .gold import Example, validate_examples
+from .training import Example, validate_examples
 from .scorer import Scorer
 from .util import create_default_optimizer, registry, SimpleFrozenList
 from .util import SimpleFrozenDict, combine_score_weights, CONFIG_SECTION_ORDER

spacy/pipeline/_parser_internals/arc_eager.pyx

@@ -8,7 +8,7 @@ from ...typedefs cimport hash_t, attr_t
 from ...strings cimport hash_string
 from ...structs cimport TokenC
 from ...tokens.doc cimport Doc, set_children_from_heads
-from ...gold.example cimport Example
+from ...training.example cimport Example
 from ...errors import Errors
 from .stateclass cimport StateClass
 from ._state cimport StateC

spacy/pipeline/_parser_internals/ner.pyx

@@ -5,7 +5,7 @@ from cymem.cymem cimport Pool
 from ...typedefs cimport weight_t, attr_t
 from ...lexeme cimport Lexeme
 from ...attrs cimport IS_SPACE
-from ...gold.example cimport Example
+from ...training.example cimport Example
 from ...errors import Errors
 from .stateclass cimport StateClass
 from ._state cimport StateC

spacy/pipeline/_parser_internals/transition_system.pxd

@@ -3,7 +3,7 @@ from cymem.cymem cimport Pool
 from ...typedefs cimport attr_t, weight_t
 from ...structs cimport TokenC
 from ...strings cimport StringStore
-from ...gold.example cimport Example
+from ...training.example cimport Example
 from .stateclass cimport StateClass
 from ._state cimport StateC
 

spacy/pipeline/attributeruler.py

@@ -4,7 +4,7 @@ from pathlib import Path
 
 from .pipe import Pipe
 from ..errors import Errors
-from ..gold import validate_examples
+from ..training import validate_examples
 from ..language import Language
 from ..matcher import Matcher
 from ..scorer import Scorer

spacy/pipeline/dep_parser.pyx

@@ -9,7 +9,7 @@ from .functions import merge_subtokens
 from ..language import Language
 from ._parser_internals import nonproj
 from ..scorer import Scorer
-from ..gold import validate_examples
+from ..training import validate_examples
 
 
 default_model_config = """

spacy/pipeline/entity_linker.py

@@ -12,7 +12,7 @@ from ..tokens import Doc
 from .pipe import Pipe, deserialize_config
 from ..language import Language
 from ..vocab import Vocab
-from ..gold import Example, validate_examples
+from ..training import Example, validate_examples
 from ..errors import Errors, Warnings
 from ..util import SimpleFrozenList
 from .. import util

spacy/pipeline/entityruler.py

@@ -9,7 +9,7 @@ from ..util import ensure_path, to_disk, from_disk, SimpleFrozenList
 from ..tokens import Doc, Span
 from ..matcher import Matcher, PhraseMatcher
 from ..scorer import Scorer
-from ..gold import validate_examples
+from ..training import validate_examples
 
 
 DEFAULT_ENT_ID_SEP = "||"

spacy/pipeline/lemmatizer.py

@@ -8,7 +8,7 @@ from ..lookups import Lookups, load_lookups
 from ..scorer import Scorer
 from ..tokens import Doc, Token
 from ..vocab import Vocab
-from ..gold import validate_examples
+from ..training import validate_examples
 from .. import util
 
 

spacy/pipeline/morphologizer.pyx

@@ -16,7 +16,7 @@ from .pipe import deserialize_config
 from .tagger import Tagger
 from .. import util
 from ..scorer import Scorer
-from ..gold import validate_examples
+from ..training import validate_examples
 
 
 default_model_config = """

spacy/pipeline/multitask.pyx

@@ -8,7 +8,7 @@ from ..tokens.doc cimport Doc
 
 from .pipe import Pipe
 from .tagger import Tagger
-from ..gold import validate_examples
+from ..training import validate_examples
 from ..language import Language
 from ._parser_internals import nonproj
 from ..attrs import POS, ID

spacy/pipeline/ner.pyx

@@ -7,7 +7,7 @@ from ._parser_internals.ner cimport BiluoPushDown
 
 from ..language import Language
 from ..scorer import Scorer
-from ..gold import validate_examples
+from ..training import validate_examples
 
 
 default_model_config = """

spacy/pipeline/pipe.pyx

@@ -4,7 +4,7 @@ from thinc.api import set_dropout_rate, Model
 
 from ..tokens.doc cimport Doc
 
-from ..gold import validate_examples
+from ..training import validate_examples
 from ..errors import Errors
 from .. import util
 

spacy/pipeline/sentencizer.pyx

@@ -7,7 +7,7 @@ from ..tokens.doc cimport Doc
 from .pipe import Pipe
 from ..language import Language
 from ..scorer import Scorer
-from ..gold import validate_examples
+from ..training import validate_examples
 from .. import util
 
 

spacy/pipeline/senter.pyx

@@ -11,7 +11,7 @@ from .tagger import Tagger
 from ..language import Language
 from ..errors import Errors
 from ..scorer import Scorer
-from ..gold import validate_examples
+from ..training import validate_examples
 from .. import util
 
 

spacy/pipeline/simple_ner.py

@@ -6,8 +6,8 @@ from thinc.util import to_numpy
 from itertools import islice
 
 from ..errors import Errors
-from ..gold import Example, spans_from_biluo_tags, iob_to_biluo, biluo_to_iob
-from ..gold import validate_examples
+from ..training import Example, spans_from_biluo_tags, iob_to_biluo, biluo_to_iob
+from ..training import validate_examples
 from ..tokens import Doc
 from ..language import Language
 from ..vocab import Vocab

spacy/pipeline/tagger.pyx

@@ -17,7 +17,7 @@ from ..attrs import POS, ID
 from ..parts_of_speech import X
 from ..errors import Errors, TempErrors, Warnings
 from ..scorer import Scorer
-from ..gold import validate_examples
+from ..training import validate_examples
 from .. import util
 
 

spacy/pipeline/textcat.py

@@ -6,7 +6,7 @@ import numpy
 
 from .pipe import Pipe
 from ..language import Language
-from ..gold import Example, validate_examples
+from ..training import Example, validate_examples
 from ..errors import Errors
 from ..scorer import Scorer
 from .. import util

spacy/pipeline/tok2vec.py

@@ -3,7 +3,7 @@ from thinc.api import Model, set_dropout_rate, Optimizer, Config
 from itertools import islice
 
 from .pipe import Pipe
-from ..gold import Example, validate_examples
+from ..training import Example, validate_examples
 from ..tokens import Doc
 from ..vocab import Vocab
 from ..language import Language

spacy/pipeline/transition_parser.pyx

@@ -21,7 +21,7 @@ from ..ml.parser_model cimport WeightsC, ActivationsC, SizesC, cpu_log_loss
 from ..ml.parser_model cimport get_c_weights, get_c_sizes
 from ..tokens.doc cimport Doc
 
-from ..gold import validate_examples
+from ..training import validate_examples
 from ..errors import Errors, Warnings
 from .. import util
 

spacy/schemas.py

@@ -12,7 +12,7 @@ from .attrs import NAMES
 if TYPE_CHECKING:
     # This lets us add type hints for mypy etc. without causing circular imports
     from .language import Language  # noqa: F401
-    from .gold import Example  # noqa: F401
+    from .training import Example  # noqa: F401
 
 
 ItemT = TypeVar("ItemT")

spacy/scorer.py

@@ -1,7 +1,7 @@
 from typing import Optional, Iterable, Dict, Any, Callable, TYPE_CHECKING
 import numpy as np
 
-from .gold import Example
+from .training import Example
 from .tokens import Token, Doc, Span
 from .errors import Errors
 from .util import get_lang_class, SimpleFrozenList

spacy/tests/doc/test_add_entities.py

@@ -1,4 +1,4 @@
-from spacy.gold import Example
+from spacy.training import Example
 from spacy.pipeline import EntityRecognizer
 from spacy.tokens import Span, Doc
 from spacy import registry

spacy/tests/parser/test_add_label.py

@@ -3,7 +3,7 @@ from thinc.api import Adam, fix_random_seed
 from spacy import registry
 from spacy.attrs import NORM
 from spacy.vocab import Vocab
-from spacy.gold import Example
+from spacy.training import Example
 from spacy.tokens import Doc
 from spacy.pipeline import DependencyParser, EntityRecognizer
 from spacy.pipeline.ner import DEFAULT_NER_MODEL

spacy/tests/parser/test_arc_eager_oracle.py

@@ -1,7 +1,7 @@
 import pytest
 from spacy.vocab import Vocab
 from spacy import registry
-from spacy.gold import Example
+from spacy.training import Example
 from spacy.pipeline import DependencyParser
 from spacy.tokens import Doc
 from spacy.pipeline._parser_internals.nonproj import projectivize

spacy/tests/parser/test_ner.py

@@ -4,7 +4,7 @@ from spacy.lang.en import English
 from spacy.language import Language
 from spacy.lookups import Lookups
 from spacy.pipeline._parser_internals.ner import BiluoPushDown
-from spacy.gold import Example
+from spacy.training import Example
 from spacy.tokens import Doc
 from spacy.vocab import Vocab
 import logging

spacy/tests/parser/test_neural_parser.py

@@ -1,7 +1,7 @@
 import pytest
 
 from spacy import registry
-from spacy.gold import Example
+from spacy.training import Example
 from spacy.vocab import Vocab
 from spacy.pipeline._parser_internals.arc_eager import ArcEager
 from spacy.pipeline.transition_parser import Parser

spacy/tests/parser/test_parse.py

@@ -3,7 +3,7 @@ import pytest
 from spacy.lang.en import English
 from ..util import get_doc, apply_transition_sequence, make_tempdir
 from ... import util
-from ...gold import Example
+from ...training import Example
 
 TRAIN_DATA = [
     (

spacy/tests/parser/test_preset_sbd.py

@@ -3,7 +3,7 @@ from thinc.api import Adam
 from spacy.attrs import NORM
 from spacy.vocab import Vocab
 from spacy import registry
-from spacy.gold import Example
+from spacy.training import Example
 from spacy.pipeline.dep_parser import DEFAULT_PARSER_MODEL
 from spacy.tokens import Doc
 from spacy.pipeline import DependencyParser

spacy/tests/pipeline/test_attributeruler.py

@@ -1,6 +1,6 @@
 import pytest
 import numpy
-from spacy.gold import Example
+from spacy.training import Example
 from spacy.lang.en import English
 from spacy.pipeline import AttributeRuler
 from spacy import util, registry

spacy/tests/pipeline/test_entity_linker.py

@@ -4,7 +4,7 @@ import pytest
 from spacy.kb import KnowledgeBase, get_candidates, Candidate
 
 from spacy import util, registry
-from spacy.gold import Example
+from spacy.training import Example
 from spacy.lang.en import English
 from spacy.tests.util import make_tempdir
 from spacy.tokens import Span

spacy/tests/pipeline/test_morphologizer.py

@@ -1,7 +1,7 @@
 import pytest
 
 from spacy import util
-from spacy.gold import Example
+from spacy.training import Example
 from spacy.lang.en import English
 from spacy.language import Language
 from spacy.tests.util import make_tempdir

spacy/tests/pipeline/test_senter.py

@@ -1,7 +1,7 @@
 import pytest
 
 from spacy import util
-from spacy.gold import Example
+from spacy.training import Example
 from spacy.lang.en import English
 from spacy.language import Language
 from spacy.tests.util import make_tempdir

spacy/tests/pipeline/test_simple_ner.py

@@ -1,6 +1,6 @@
 import pytest
 from spacy.lang.en import English
-from spacy.gold import Example
+from spacy.training import Example
 from spacy import util
 from ..util import make_tempdir
 

spacy/tests/pipeline/test_tagger.py

@@ -1,6 +1,6 @@
 import pytest
 from spacy import util
-from spacy.gold import Example
+from spacy.training import Example
 from spacy.lang.en import English
 from spacy.language import Language
 

spacy/tests/pipeline/test_textcat.py

@@ -10,7 +10,7 @@ from spacy.tokens import Doc
 from spacy.pipeline.tok2vec import DEFAULT_TOK2VEC_MODEL
 
 from ..util import make_tempdir
-from ...gold import Example
+from ...training import Example
 
 
 TRAIN_DATA = [

spacy/tests/regression/test_issue1-1000.py

@@ -1,7 +1,7 @@
 import pytest
 import random
 from spacy import util
-from spacy.gold import Example
+from spacy.training import Example
 from spacy.matcher import Matcher
 from spacy.attrs import IS_PUNCT, ORTH, LOWER
 from spacy.vocab import Vocab

spacy/tests/regression/test_issue1501-2000.py

@@ -3,7 +3,7 @@ import gc
 import numpy
 import copy
 
-from spacy.gold import Example
+from spacy.training import Example
 from spacy.lang.en import English
 from spacy.lang.en.stop_words import STOP_WORDS
 from spacy.lang.lex_attrs import is_stop

spacy/tests/regression/test_issue2001-2500.py

@@ -3,7 +3,7 @@ import numpy
 from spacy.tokens import Doc
 from spacy.matcher import Matcher
 from spacy.displacy import render
-from spacy.gold import iob_to_biluo
+from spacy.training import iob_to_biluo
 from spacy.lang.it import Italian
 from spacy.lang.en import English
 

spacy/tests/regression/test_issue2501-3000.py

@@ -1,6 +1,6 @@
 import pytest
 from spacy import displacy
-from spacy.gold import Example
+from spacy.training import Example
 from spacy.lang.en import English
 from spacy.lang.ja import Japanese
 from spacy.lang.xx import MultiLanguage

spacy/tests/regression/test_issue3501-4000.py

@@ -9,7 +9,7 @@ from spacy.tokens import Doc, Token
 from spacy.matcher import Matcher, PhraseMatcher
 from spacy.errors import MatchPatternError
 from spacy.util import minibatch
-from spacy.gold import Example
+from spacy.training import Example
 from spacy.lang.hi import Hindi
 from spacy.lang.es import Spanish
 from spacy.lang.en import English

spacy/tests/regression/test_issue4001-4500.py

@@ -2,8 +2,8 @@ import pytest
 from spacy.pipeline import Pipe
 from spacy.matcher import PhraseMatcher, Matcher
 from spacy.tokens import Doc, Span, DocBin
-from spacy.gold import Example, Corpus
-from spacy.gold.converters import json2docs
+from spacy.training import Example, Corpus
+from spacy.training.converters import json2docs
 from spacy.vocab import Vocab
 from spacy.lang.en import English
 from spacy.util import minibatch, ensure_path, load_model

spacy/tests/regression/test_issue4501-5000.py

@@ -1,9 +1,7 @@
 import pytest
-from mock import Mock
-from spacy.matcher import DependencyMatcher
 from spacy.tokens import Doc, Span, DocBin
-from spacy.gold import Example
-from spacy.gold.converters.conllu2docs import conllu2docs
+from spacy.training import Example
+from spacy.training.converters.conllu2docs import conllu2docs
 from spacy.lang.en import English
 from spacy.kb import KnowledgeBase
 from spacy.vocab import Vocab
@@ -12,7 +10,7 @@ from spacy.util import ensure_path, load_model_from_path
 import numpy
 import pickle
 
-from ..util import get_doc, make_tempdir
+from ..util import make_tempdir
 
 
 def test_issue4528(en_vocab):

spacy/tests/test_cli.py

@@ -1,8 +1,8 @@
 import pytest
 from click import NoSuchOption
 
-from spacy.gold import docs_to_json, biluo_tags_from_offsets
-from spacy.gold.converters import iob2docs, conll_ner2docs, conllu2docs
+from spacy.training import docs_to_json, biluo_tags_from_offsets
+from spacy.training.converters import iob2docs, conll_ner2docs, conllu2docs
 from spacy.lang.en import English
 from spacy.schemas import ProjectConfigSchema, RecommendationSchema, validate
 from spacy.cli.pretrain import make_docs

spacy/tests/test_language.py

@@ -3,7 +3,7 @@ import pytest
 from spacy.language import Language
 from spacy.tokens import Doc, Span
 from spacy.vocab import Vocab
-from spacy.gold import Example
+from spacy.training import Example
 from spacy.lang.en import English
 from spacy.util import registry
 

spacy/tests/test_new_example.py

@@ -1,5 +1,5 @@
 import pytest
-from spacy.gold.example import Example
+from spacy.training.example import Example
 from spacy.tokens import Doc
 from spacy.vocab import Vocab
 

spacy/tests/test_scorer.py

@@ -1,8 +1,8 @@
 from numpy.testing import assert_almost_equal, assert_array_almost_equal
 import pytest
 from pytest import approx
-from spacy.gold import Example
-from spacy.gold.iob_utils import biluo_tags_from_offsets
+from spacy.training import Example
+from spacy.training.iob_utils import biluo_tags_from_offsets
 from spacy.scorer import Scorer, ROCAUCScore
 from spacy.scorer import _roc_auc_score, _roc_curve
 from .util import get_doc

spacy/tests/test_tok2vec.py

@@ -6,7 +6,7 @@ from spacy.ml.models.tok2vec import MishWindowEncoder, MaxoutWindowEncoder
 from spacy.pipeline.tok2vec import Tok2Vec, Tok2VecListener
 from spacy.vocab import Vocab
 from spacy.tokens import Doc
-from spacy.gold import Example
+from spacy.training import Example
 from spacy import util
 from spacy.lang.en import English
 from .util import get_batch

spacy/tests/test_training.py

@@ -1,9 +1,10 @@
 import numpy
-from spacy.gold import biluo_tags_from_offsets, offsets_from_biluo_tags, Alignment
-from spacy.gold import spans_from_biluo_tags, iob_to_biluo
-from spacy.gold import Corpus, docs_to_json
-from spacy.gold.example import Example
-from spacy.gold.converters import json2docs
+from spacy.training import biluo_tags_from_offsets, offsets_from_biluo_tags, Alignment
+from spacy.training import spans_from_biluo_tags, iob_to_biluo
+from spacy.training import Corpus, docs_to_json
+from spacy.training.example import Example
+from spacy.training.converters import json2docs
+from spacy.training.augment import make_orth_variants_example
 from spacy.lang.en import English
 from spacy.tokens import Doc, DocBin
 from spacy.util import get_words_and_spaces, minibatch
@@ -12,7 +13,6 @@ import pytest
 import srsly
 
 from .util import make_tempdir
-from ..gold.augment import make_orth_variants_example
 
 
 @pytest.fixture

spacy/tests/test_util.py

@@ -5,7 +5,7 @@ from .util import get_random_doc
 from spacy import util
 from spacy.util import dot_to_object, SimpleFrozenList
 from thinc.api import Config, Optimizer
-from spacy.gold.batchers import minibatch_by_words
+from spacy.training.batchers import minibatch_by_words
 from ..lang.en import English
 from ..lang.nl import Dutch
 from ..language import DEFAULT_CONFIG_PATH

spacy/tokenizer.pyx

@@ -24,7 +24,7 @@ from .util import registry
 from .attrs import intify_attrs
 from .symbols import ORTH
 from .scorer import Scorer
-from .gold import validate_examples
+from .training import validate_examples
 
 
 cdef class Tokenizer:

spacy/training/converters/conll_ner2docs.py

@@ -1,7 +1,7 @@
 from wasabi import Printer
 
 from .. import tags_to_entities
-from ...gold import iob_to_biluo
+from ...training import iob_to_biluo
 from ...lang.xx import MultiLanguage
 from ...tokens import Doc, Span
 from ...util import load_model

spacy/training/converters/conllu2docs.py

@@ -1,7 +1,7 @@
 import re
 
 from .conll_ner2docs import n_sents_info
-from ...gold import iob_to_biluo, spans_from_biluo_tags
+from ...training import iob_to_biluo, spans_from_biluo_tags
 from ...tokens import Doc, Token, Span
 from ...vocab import Vocab
 from wasabi import Printer

spacy/training/converters/iob2docs.py

@@ -1,7 +1,7 @@
 from wasabi import Printer
 
 from .conll_ner2docs import n_sents_info
-from ...gold import iob_to_biluo, tags_to_entities
+from ...training import iob_to_biluo, tags_to_entities
 from ...tokens import Doc, Span
 from ...util import minibatch
 

website/README.md

@@ -289,11 +289,11 @@ always be the **last element** in the row.
 > | Column 1 | Column 2 ~~List[Doc]~~ |
 > ```
 
-| Name                | Description                                                                                                                                                             |
-| ------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
-| `vocab`             | The shared vocabulary. ~~Vocab~~                                                                                                                                        |
-| `model`             | The Thinc [`Model`](https://thinc.ai/docs/api-model) wrapping the transformer. ~~Model[List[Doc], FullTransformerBatch]~~                                               |
-| `annotation_setter` | Function that takes a batch of `Doc` objects and transformer outputs can set additional annotations on the `Doc`. ~~Callable[[List[Doc], FullTransformerBatch], None]~~ |
+| Name                    | Description                                                                                                                                                                 |
+| ----------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| `vocab`                 | The shared vocabulary. ~~Vocab~~                                                                                                                                            |
+| `model`                 | The Thinc [`Model`](https://thinc.ai/docs/api-model) wrapping the transformer. ~~Model[List[Doc], FullTransformerBatch]~~                                                   |
+| `set_extra_annotations` | Function that takes a batch of `Doc` objects and transformer outputs and can set additional annotations on the `Doc`. ~~Callable[[List[Doc], FullTransformerBatch], None]~~ |
 
 ### List {#list}
 

website/docs/api/cli.md

@@ -357,12 +357,12 @@ File       /path/to/spacy/ml/models/tok2vec.py (line 207)
 ℹ [training.logger]
 Registry   @loggers
 Name       spacy.ConsoleLogger.v1
-Module     spacy.gold.loggers
+Module     spacy.training.loggers
 File       /path/to/spacy/gold/loggers.py (line 8)
 ℹ [training.batcher]
 Registry   @batchers
 Name       spacy.batch_by_words.v1
-Module     spacy.gold.batchers
+Module     spacy.training.batchers
 File       /path/to/spacy/gold/batchers.py (line 49)
 ℹ [training.batcher.size]
 Registry   @schedules
@@ -372,7 +372,7 @@ File       /Users/ines/Repos/explosion/thinc/thinc/schedules.py (line 43)
 ℹ [training.dev_corpus]
 Registry   @readers
 Name       spacy.Corpus.v1
-Module     spacy.gold.corpus
+Module     spacy.training.corpus
 File       /path/to/spacy/gold/corpus.py (line 18)
 ℹ [training.optimizer]
 Registry   @optimizers
@@ -387,7 +387,7 @@ File       /Users/ines/Repos/explosion/thinc/thinc/schedules.py (line 91)
 ℹ [training.train_corpus]
 Registry   @readers
 Name       spacy.Corpus.v1
-Module     spacy.gold.corpus
+Module     spacy.training.corpus
 File       /path/to/spacy/gold/corpus.py (line 18)
 ```
 

website/docs/api/corpus.md

@@ -58,7 +58,7 @@ train/test skew.
 > #### Example
 >
 > ```python
-> from spacy.gold import Corpus
+> from spacy.training import Corpus
 >
 > # With a single file
 > corpus = Corpus("./data/train.spacy")
@@ -82,7 +82,7 @@ Yield examples from the data.
 > #### Example
 >
 > ```python
-> from spacy.gold import Corpus
+> from spacy.training import Corpus
 > import spacy
 >
 > corpus = Corpus("./train.spacy")

website/docs/api/data-formats.md

@@ -175,7 +175,7 @@ run [`spacy pretrain`](/api/cli#pretrain).
 >
 > ```python
 > from spacy.tokens import DocBin
-> from spacy.gold import Corpus
+> from spacy.training import Corpus
 >
 > doc_bin = DocBin(docs=docs)
 > doc_bin.to_disk("./data.spacy")

website/docs/api/example.md

@@ -22,7 +22,7 @@ both documents.
 >
 > ```python
 > from spacy.tokens import Doc
-> from spacy.gold import Example
+> from spacy.training import Example
 >
 > words = ["hello", "world", "!"]
 > spaces = [True, False, False]
@@ -48,7 +48,7 @@ see the [training format documentation](/api/data-formats#dict-input).
 >
 > ```python
 > from spacy.tokens import Doc
-> from spacy.gold import Example
+> from spacy.training import Example
 >
 > predicted = Doc(vocab, words=["Apply", "some", "sunscreen"])
 > token_ref = ["Apply", "some", "sun", "screen"]
@@ -301,7 +301,7 @@ tokenizations add up to the same string. For example, you'll be able to align
 > #### Example
 >
 > ```python
-> from spacy.gold import Alignment
+> from spacy.training import Alignment
 >
 > bert_tokens = ["obama", "'", "s", "podcast"]
 > spacy_tokens = ["obama", "'s", "podcast"]

website/docs/api/top-level.md

@@ -538,7 +538,7 @@ sequences in the batch.
 
 ## Training data and alignment {#gold source="spacy/gold"}
 
-### gold.biluo_tags_from_offsets {#biluo_tags_from_offsets tag="function"}
+### training.biluo_tags_from_offsets {#biluo_tags_from_offsets tag="function"}
 
 Encode labelled spans into per-token tags, using the
 [BILUO scheme](/usage/linguistic-features#accessing-ner) (Begin, In, Last, Unit,
@@ -554,7 +554,7 @@ single-token entity.
 > #### Example
 >
 > ```python
-> from spacy.gold import biluo_tags_from_offsets
+> from spacy.training import biluo_tags_from_offsets
 >
 > doc = nlp("I like London.")
 > entities = [(7, 13, "LOC")]
@@ -568,7 +568,7 @@ single-token entity.
 | `entities`  | A sequence of `(start, end, label)` triples. `start` and `end` should be character-offset integers denoting the slice into the original string. ~~List[Tuple[int, int, Union[str, int]]]~~ |
 | **RETURNS** | A list of strings, describing the [BILUO](/usage/linguistic-features#accessing-ner) tags. ~~List[str]~~                                                                                    |
 
-### gold.offsets_from_biluo_tags {#offsets_from_biluo_tags tag="function"}
+### training.offsets_from_biluo_tags {#offsets_from_biluo_tags tag="function"}
 
 Encode per-token tags following the
 [BILUO scheme](/usage/linguistic-features#accessing-ner) into entity offsets.
@@ -576,7 +576,7 @@ Encode per-token tags following the
 > #### Example
 >
 > ```python
-> from spacy.gold import offsets_from_biluo_tags
+> from spacy.training import offsets_from_biluo_tags
 >
 > doc = nlp("I like London.")
 > tags = ["O", "O", "U-LOC", "O"]
@@ -590,7 +590,7 @@ Encode per-token tags following the
 | `entities`  | A sequence of [BILUO](/usage/linguistic-features#accessing-ner) tags with each tag describing one token. Each tag string will be of the form of either `""`, `"O"` or `"{action}-{label}"`, where action is one of `"B"`, `"I"`, `"L"`, `"U"`. ~~List[str]~~ |
 | **RETURNS** | A sequence of `(start, end, label)` triples. `start` and `end` will be character-offset integers denoting the slice into the original string. ~~List[Tuple[int, int, str]]~~                                                                                 |
 
-### gold.spans_from_biluo_tags {#spans_from_biluo_tags tag="function" new="2.1"}
+### training.spans_from_biluo_tags {#spans_from_biluo_tags tag="function" new="2.1"}
 
 Encode per-token tags following the
 [BILUO scheme](/usage/linguistic-features#accessing-ner) into
@@ -600,7 +600,7 @@ token-based tags, e.g. to overwrite the `doc.ents`.
 > #### Example
 >
 > ```python
-> from spacy.gold import spans_from_biluo_tags
+> from spacy.training import spans_from_biluo_tags
 >
 > doc = nlp("I like London.")
 > tags = ["O", "O", "U-LOC", "O"]

website/docs/api/transformer.md

@@ -61,11 +61,11 @@ on the transformer architectures and their arguments and hyperparameters.
 > nlp.add_pipe("transformer", config=DEFAULT_CONFIG)
 > ```
 
-| Setting             | Description                                                                                                                                                                                                                                                                                                           |
-| ------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
-| `max_batch_items`   | Maximum size of a padded batch. Defaults to `4096`. ~~int~~                                                                                                                                                                                                                                                           |
-| `annotation_setter` | Function that takes a batch of `Doc` objects and transformer outputs to set additional annotations on the `Doc`. The `Doc._.transformer_data` attribute is set prior to calling the callback. Defaults to `null_annotation_setter` (no additional annotations). ~~Callable[[List[Doc], FullTransformerBatch], None]~~ |
-| `model`             | The Thinc [`Model`](https://thinc.ai/docs/api-model) wrapping the transformer. Defaults to [TransformerModel](/api/architectures#TransformerModel). ~~Model[List[Doc], FullTransformerBatch]~~                                                                                                                        |
+| Setting                 | Description                                                                                                                                                                                                                                                                                                           |
+| ----------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| `max_batch_items`       | Maximum size of a padded batch. Defaults to `4096`. ~~int~~                                                                                                                                                                                                                                                           |
+| `set_extra_annotations` | Function that takes a batch of `Doc` objects and transformer outputs to set additional annotations on the `Doc`. The `Doc._.transformer_data` attribute is set prior to calling the callback. Defaults to `null_annotation_setter` (no additional annotations). ~~Callable[[List[Doc], FullTransformerBatch], None]~~ |
+| `model`                 | The Thinc [`Model`](https://thinc.ai/docs/api-model) wrapping the transformer. Defaults to [TransformerModel](/api/architectures#TransformerModel). ~~Model[List[Doc], FullTransformerBatch]~~                                                                                                                        |
 
 ```python
 https://github.com/explosion/spacy-transformers/blob/master/spacy_transformers/pipeline_component.py
@@ -102,14 +102,14 @@ attribute. You can also provide a callback to set additional annotations. In
 your application, you would normally use a shortcut for this and instantiate the
 component using its string name and [`nlp.add_pipe`](/api/language#create_pipe).
 
-| Name                | Description                                                                                                                                                                                                                                                                             |
-| ------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
-| `vocab`             | The shared vocabulary. ~~Vocab~~                                                                                                                                                                                                                                                        |
-| `model`             | The Thinc [`Model`](https://thinc.ai/docs/api-model) wrapping the transformer. Usually you will want to use the [TransformerModel](/api/architectures#TransformerModel) layer for this. ~~Model[List[Doc], FullTransformerBatch]~~                                                      |
-| `annotation_setter` | Function that takes a batch of `Doc` objects and transformer outputs and stores the annotations on the `Doc`. The `Doc._.trf_data` attribute is set prior to calling the callback. By default, no additional annotations are set. ~~Callable[[List[Doc], FullTransformerBatch], None]~~ |
-| _keyword-only_      |                                                                                                                                                                                                                                                                                         |
-| `name`              | String name of the component instance. Used to add entries to the `losses` during training. ~~str~~                                                                                                                                                                                     |
-| `max_batch_items`   | Maximum size of a padded batch. Defaults to `128*32`. ~~int~~                                                                                                                                                                                                                           |
+| Name                    | Description                                                                                                                                                                                                                                                                             |
+| ----------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| `vocab`                 | The shared vocabulary. ~~Vocab~~                                                                                                                                                                                                                                                        |
+| `model`                 | The Thinc [`Model`](https://thinc.ai/docs/api-model) wrapping the transformer. Usually you will want to use the [TransformerModel](/api/architectures#TransformerModel) layer for this. ~~Model[List[Doc], FullTransformerBatch]~~                                                      |
+| `set_extra_annotations` | Function that takes a batch of `Doc` objects and transformer outputs and stores the annotations on the `Doc`. The `Doc._.trf_data` attribute is set prior to calling the callback. By default, no additional annotations are set. ~~Callable[[List[Doc], FullTransformerBatch], None]~~ |
+| _keyword-only_          |                                                                                                                                                                                                                                                                                         |
+| `name`                  | String name of the component instance. Used to add entries to the `losses` during training. ~~str~~                                                                                                                                                                                     |
+| `max_batch_items`       | Maximum size of a padded batch. Defaults to `128*32`. ~~int~~                                                                                                                                                                                                                           |
 
 ## Transformer.\_\_call\_\_ {#call tag="method"}
 
@@ -205,7 +205,7 @@ modifying them.
 
 Assign the extracted features to the Doc objects. By default, the
 [`TransformerData`](/api/transformer#transformerdata) object is written to the
-[`Doc._.trf_data`](#custom-attributes) attribute. Your annotation_setter
+[`Doc._.trf_data`](#custom-attributes) attribute. Your `set_extra_annotations`
 callback is then called, if provided.
 
 > #### Example

website/docs/usage/embeddings-transformers.md

@@ -253,10 +253,10 @@ for doc in nlp.pipe(["some text", "some other text"]):
 
 You can also customize how the [`Transformer`](/api/transformer) component sets
 annotations onto the [`Doc`](/api/doc), by specifying a custom
-`annotation_setter`. This callback will be called with the raw input and output
-data for the whole batch, along with the batch of `Doc` objects, allowing you to
-implement whatever you need. The annotation setter is called with a batch of
-[`Doc`](/api/doc) objects and a
+`set_extra_annotations` function. This callback will be called with the raw
+input and output data for the whole batch, along with the batch of `Doc`
+objects, allowing you to implement whatever you need. The annotation setter is
+called with a batch of [`Doc`](/api/doc) objects and a
 [`FullTransformerBatch`](/api/transformer#fulltransformerbatch) containing the
 transformers data for the batch.
 
@@ -267,7 +267,7 @@ def custom_annotation_setter(docs, trf_data):
         doc._.custom_attr = data
 
 nlp = spacy.load("en_core_trf_lg")
-nlp.get_pipe("transformer").annotation_setter = custom_annotation_setter
+nlp.get_pipe("transformer").set_extra_annotations = custom_annotation_setter
 doc = nlp("This is a text")
 assert isinstance(doc._.custom_attr, TransformerData)
 print(doc._.custom_attr.tensors)
@@ -314,7 +314,7 @@ component:
 >         get_spans=get_doc_spans,
 >         tokenizer_config={"use_fast": True},
 >     ),
->     annotation_setter=null_annotation_setter,
+>     set_extra_annotations=null_annotation_setter,
 >     max_batch_items=4096,
 > )
 > ```
@@ -333,7 +333,7 @@ tokenizer_config = {"use_fast": true}
 [components.transformer.model.get_spans]
 @span_getters = "spacy-transformers.doc_spans.v1"
 
-[components.transformer.annotation_setter]
+[components.transformer.set_extra_annotations]
 @annotation_setters = "spacy-transformers.null_annotation_setter.v1"
 
 ```

website/docs/usage/linguistic-features.md

@@ -1366,7 +1366,7 @@ token.
 
 ```python
 ### {executable="true"}
-from spacy.gold import Alignment
+from spacy.training import Alignment
 
 other_tokens = ["i", "listened", "to", "obama", "'", "s", "podcasts", "."]
 spacy_tokens = ["i", "listened", "to", "obama", "'s", "podcasts", "."]

website/docs/usage/processing-pipelines.md

@@ -1500,7 +1500,7 @@ add those entities to the `doc.ents`, you can wrap it in a custom pipeline
 component function and pass it the token texts from the `Doc` object received by
 the component.
 
-The [`gold.spans_from_biluo_tags`](/api/top-level#spans_from_biluo_tags) is very
+The [`training.spans_from_biluo_tags`](/api/top-level#spans_from_biluo_tags) is very
 helpful here, because it takes a `Doc` object and token-based BILUO tags and
 returns a sequence of `Span` objects in the `Doc` with added labels. So all your
 wrapper has to do is compute the entity spans and overwrite the `doc.ents`.
@@ -1515,7 +1515,7 @@ wrapper has to do is compute the entity spans and overwrite the `doc.ents`.
 ```python
 ### {highlight="1,8-9"}
 import your_custom_entity_recognizer
-from spacy.gold import offsets_from_biluo_tags
+from spacy.training import offsets_from_biluo_tags
 from spacy.language import Language
 
 @Language.component("custom_ner_wrapper")

website/docs/usage/training.md

@@ -735,7 +735,7 @@ as **config settings** – in this case, `source`.
 ### functions.py {highlight="7-8"}
 from typing import Callable, Iterator, List
 import spacy
-from spacy.gold import Example
+from spacy.training import Example
 from spacy.language import Language
 import random
 
@@ -783,7 +783,7 @@ annotations are the same.
 ### functions.py
 from typing import Callable, Iterable, Iterator, List
 import spacy
-from spacy.gold import Example
+from spacy.training import Example
 
 @spacy.registry.batchers("filtering_batch.v1")
 def filter_batch(size: int) -> Callable[[Iterable[Example]], Iterator[List[Example]]]: