The Parser is now a Pipe (2) (#5844)

* moving syntax folder to _parser_internals

* moving nn_parser and transition_system

* move nn_parser and transition_system out of internals folder

* moving nn_parser code into transition_system file

* rename transition_system to transition_parser

* moving parser_model and _state to ml

* move _state back to internals

* The Parser now inherits from Pipe!

* small code fixes

* removing unnecessary imports

* remove link_vectors_to_models

* transition_system to internals folder

* little bit more cleanup

* newlines

bin/ud/ud_train.py

@@ -16,7 +16,7 @@ from bin.ud import conll17_ud_eval
 from spacy.tokens import Token, Doc
 from spacy.gold import Example
 from spacy.util import compounding, minibatch, minibatch_by_words
-from spacy.syntax.nonproj import projectivize
+from spacy.pipeline._parser_internals.nonproj import projectivize
 from spacy.matcher import Matcher
 from spacy import displacy
 from collections import defaultdict

examples/training/conllu.py

@@ -13,7 +13,7 @@ import spacy
 import spacy.util
 from spacy.tokens import Token, Doc
 from spacy.gold import Example
-from spacy.syntax.nonproj import projectivize
+from spacy.pipeline._parser_internals.nonproj import projectivize
 from collections import defaultdict
 from spacy.matcher import Matcher
 

setup.py

@@ -31,6 +31,7 @@ MOD_NAMES = [
     "spacy.vocab",
     "spacy.attrs",
     "spacy.kb",
+    "spacy.ml.parser_model",
     "spacy.morphology",
     "spacy.pipeline.dep_parser",
     "spacy.pipeline.morphologizer",
@@ -40,14 +41,14 @@ MOD_NAMES = [
     "spacy.pipeline.sentencizer",
     "spacy.pipeline.senter",
     "spacy.pipeline.tagger",
-    "spacy.syntax.stateclass",
-    "spacy.syntax._state",
+    "spacy.pipeline.transition_parser",
+    "spacy.pipeline._parser_internals.arc_eager",
+    "spacy.pipeline._parser_internals.ner",
+    "spacy.pipeline._parser_internals.nonproj",
+    "spacy.pipeline._parser_internals._state",
+    "spacy.pipeline._parser_internals.stateclass",
+    "spacy.pipeline._parser_internals.transition_system",
     "spacy.tokenizer",
-    "spacy.syntax.nn_parser",
-    "spacy.syntax._parser_model",
-    "spacy.syntax.nonproj",
-    "spacy.syntax.transition_system",
-    "spacy.syntax.arc_eager",
     "spacy.gold.gold_io",
     "spacy.tokens.doc",
     "spacy.tokens.span",
@@ -57,7 +58,6 @@ MOD_NAMES = [
     "spacy.matcher.matcher",
     "spacy.matcher.phrasematcher",
     "spacy.matcher.dependencymatcher",
-    "spacy.syntax.ner",
     "spacy.symbols",
     "spacy.vectors",
 ]

spacy/cli/debug_data.py

@@ -10,7 +10,7 @@ from thinc.api import Config
 from ._util import app, Arg, Opt, show_validation_error, parse_config_overrides
 from ._util import import_code, debug_cli
 from ..gold import Corpus, Example
-from ..syntax import nonproj
+from ..pipeline._parser_internals import nonproj
 from ..language import Language
 from .. import util
 

spacy/gold/example.pyx

@@ -10,7 +10,7 @@ from .align import Alignment
 from .iob_utils import biluo_to_iob, biluo_tags_from_offsets, biluo_tags_from_doc
 from .iob_utils import spans_from_biluo_tags
 from ..errors import Errors, Warnings
-from ..syntax import nonproj
+from ..pipeline._parser_internals import nonproj
 
 
 cpdef Doc annotations2doc(vocab, tok_annot, doc_annot):

spacy/ml/parser_model.pxd

@@ -1,8 +1,6 @@
 from libc.string cimport memset, memcpy
-from libc.stdlib cimport calloc, free, realloc
-from ..typedefs cimport weight_t, class_t, hash_t
-
-from ._state cimport StateC
+from ..typedefs cimport weight_t, hash_t
+from ..pipeline._parser_internals._state cimport StateC
 
 
 cdef struct SizesC:

spacy/ml/parser_model.pyx

@@ -1,29 +1,18 @@
 # cython: infer_types=True, cdivision=True, boundscheck=False
-cimport cython.parallel
 cimport numpy as np
 from libc.math cimport exp
-from libcpp.vector cimport vector
 from libc.string cimport memset, memcpy
 from libc.stdlib cimport calloc, free, realloc
-from cymem.cymem cimport Pool
-from thinc.extra.search cimport Beam
 from thinc.backends.linalg cimport Vec, VecVec
 cimport blis.cy
 
 import numpy
 import numpy.random
-from thinc.api import Linear, Model, CupyOps, NumpyOps, use_ops, noop
+from thinc.api import Model, CupyOps, NumpyOps
 
-from ..typedefs cimport weight_t, class_t, hash_t
-from ..tokens.doc cimport Doc
-from .stateclass cimport StateClass
-from .transition_system cimport Transition
-
-from ..compat import copy_array
-from ..errors import Errors, TempErrors
-from ..util import create_default_optimizer
 from .. import util
-from . import nonproj
+from ..typedefs cimport weight_t, class_t, hash_t
+from ..pipeline._parser_internals.stateclass cimport StateClass
 
 
 cdef WeightsC get_c_weights(model) except *:

spacy/ml/tb_framework.py

@@ -1,5 +1,5 @@
 from thinc.api import Model, noop, use_ops, Linear
-from ..syntax._parser_model import ParserStepModel
+from .parser_model import ParserStepModel
 
 
 def TransitionModel(tok2vec, lower, upper, dropout=0.2, unseen_classes=set()):

spacy/pipeline/_parser_internals/_state.pxd

@@ -1,15 +1,14 @@
-from libc.string cimport memcpy, memset, memmove
-from libc.stdlib cimport malloc, calloc, free
+from libc.string cimport memcpy, memset
+from libc.stdlib cimport calloc, free
 from libc.stdint cimport uint32_t, uint64_t
 from cpython.exc cimport PyErr_CheckSignals, PyErr_SetFromErrno
 from murmurhash.mrmr cimport hash64
 
-from ..vocab cimport EMPTY_LEXEME
-from ..structs cimport TokenC, SpanC
-from ..lexeme cimport Lexeme
-from ..symbols cimport punct
-from ..attrs cimport IS_SPACE
-from ..typedefs cimport attr_t
+from ...vocab cimport EMPTY_LEXEME
+from ...structs cimport TokenC, SpanC
+from ...lexeme cimport Lexeme
+from ...attrs cimport IS_SPACE
+from ...typedefs cimport attr_t
 
 
 cdef inline bint is_space_token(const TokenC* token) nogil:

spacy/pipeline/_parser_internals/arc_eager.pxd

@@ -1,8 +1,6 @@
-from cymem.cymem cimport Pool
-
 from .stateclass cimport StateClass
-from ..typedefs cimport weight_t, attr_t
-from .transition_system cimport TransitionSystem, Transition
+from ...typedefs cimport weight_t, attr_t
+from .transition_system cimport Transition, TransitionSystem
 
 
 cdef class ArcEager(TransitionSystem):

spacy/pipeline/_parser_internals/arc_eager.pyx

@@ -1,24 +1,17 @@
 # cython: profile=True, cdivision=True, infer_types=True
-from cpython.ref cimport Py_INCREF
 from cymem.cymem cimport Pool, Address
 from libc.stdint cimport int32_t
 
 from collections import defaultdict, Counter
-import json
 
-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 ...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 ...errors import Errors
 from .stateclass cimport StateClass
 from ._state cimport StateC
-from .transition_system cimport move_cost_func_t, label_cost_func_t
-from ..gold.example cimport Example
-
-from ..errors import Errors
-from .nonproj import is_nonproj_tree
-from . import nonproj
-
 
 # Calculate cost as gold/not gold. We don't use scalar value anyway.
 cdef int BINARY_COSTS = 1

spacy/pipeline/_parser_internals/ner.pxd

@@ -1,6 +1,4 @@
 from .transition_system cimport TransitionSystem
-from .transition_system cimport Transition
-from ..typedefs cimport attr_t
 
 
 cdef class BiluoPushDown(TransitionSystem):

spacy/pipeline/_parser_internals/ner.pyx

@@ -2,17 +2,14 @@ from collections import Counter
 from libc.stdint cimport int32_t
 from cymem.cymem cimport Pool
 
-from ..typedefs cimport weight_t
+from ...typedefs cimport weight_t, attr_t
+from ...lexeme cimport Lexeme
+from ...attrs cimport IS_SPACE
+from ...gold.example cimport Example
+from ...errors import Errors
 from .stateclass cimport StateClass
 from ._state cimport StateC
-from .transition_system cimport Transition
-from .transition_system cimport do_func_t
-from ..lexeme cimport Lexeme
-from ..attrs cimport IS_SPACE
-from ..gold.iob_utils import biluo_tags_from_offsets
-from ..gold.example cimport Example
-
-from ..errors import Errors
+from .transition_system cimport Transition, do_func_t
 
 
 cdef enum:

spacy/pipeline/_parser_internals/nonproj.pyx

@@ -5,9 +5,9 @@ scheme.
 """
 from copy import copy
 
-from ..tokens.doc cimport Doc, set_children_from_heads
+from ...tokens.doc cimport Doc, set_children_from_heads
 
-from ..errors import Errors
+from ...errors import Errors
 
 
 DELIMITER = '||'

spacy/pipeline/_parser_internals/stateclass.pxd

@@ -1,12 +1,8 @@
-from libc.string cimport memcpy, memset
-
 from cymem.cymem cimport Pool
-cimport cython
 
-from ..structs cimport TokenC, SpanC
-from ..typedefs cimport attr_t
+from ...structs cimport TokenC, SpanC
+from ...typedefs cimport attr_t
 
-from ..vocab cimport EMPTY_LEXEME
 from ._state cimport StateC
 
 

spacy/pipeline/_parser_internals/stateclass.pyx

@@ -1,7 +1,7 @@
 # cython: infer_types=True
 import numpy
 
-from ..tokens.doc cimport Doc
+from ...tokens.doc cimport Doc
 
 
 cdef class StateClass:

spacy/pipeline/_parser_internals/transition_system.pxd

@@ -1,11 +1,11 @@
 from cymem.cymem cimport Pool
 
-from ..typedefs cimport attr_t, weight_t
-from ..structs cimport TokenC
-from ..strings cimport StringStore
+from ...typedefs cimport attr_t, weight_t
+from ...structs cimport TokenC
+from ...strings cimport StringStore
+from ...gold.example cimport Example
 from .stateclass cimport StateClass
 from ._state cimport StateC
-from ..gold.example cimport Example
 
 
 cdef struct Transition:

spacy/pipeline/_parser_internals/transition_system.pyx

@@ -1,19 +1,17 @@
 # cython: infer_types=True
 from __future__ import print_function
-from cpython.ref cimport Py_INCREF
 from cymem.cymem cimport Pool
 
 from collections import Counter
 import srsly
 
-from ..typedefs cimport weight_t
-from ..tokens.doc cimport Doc
-from ..structs cimport TokenC
+from ...typedefs cimport weight_t, attr_t
+from ...tokens.doc cimport Doc
+from ...structs cimport TokenC
 from .stateclass cimport StateClass
-from ..typedefs cimport attr_t
 
-from ..errors import Errors
-from .. import util
+from ...errors import Errors
+from ... import util
 
 
 cdef weight_t MIN_SCORE = -90000

spacy/pipeline/dep_parser.pyx

@@ -1,13 +1,13 @@
 # cython: infer_types=True, profile=True, binding=True
 from typing import Optional, Iterable
-from thinc.api import CosineDistance, to_categorical, get_array_module, Model, Config
+from thinc.api import Model, Config
 
-from ..syntax.nn_parser cimport Parser
-from ..syntax.arc_eager cimport ArcEager
+from .transition_parser cimport Parser
+from ._parser_internals.arc_eager cimport ArcEager
 
 from .functions import merge_subtokens
 from ..language import Language
-from ..syntax import nonproj
+from ._parser_internals import nonproj
 from ..scorer import Scorer
 
 

spacy/pipeline/entity_linker.py

@@ -222,9 +222,9 @@ class EntityLinker(Pipe):
         set_dropout_rate(self.model, drop)
         if not sentence_docs:
             warnings.warn(Warnings.W093.format(name="Entity Linker"))
-            return 0.0
+            return losses
         sentence_encodings, bp_context = self.model.begin_update(sentence_docs)
-        loss, d_scores = self.get_similarity_loss(
+        loss, d_scores = self.get_loss(
             sentence_encodings=sentence_encodings, examples=examples
         )
         bp_context(d_scores)
@@ -235,7 +235,7 @@ class EntityLinker(Pipe):
             self.set_annotations(docs, predictions)
         return losses
 
-    def get_similarity_loss(self, examples: Iterable[Example], sentence_encodings):
+    def get_loss(self, examples: Iterable[Example], sentence_encodings):
         entity_encodings = []
         for eg in examples:
             kb_ids = eg.get_aligned("ENT_KB_ID", as_string=True)
@@ -247,7 +247,7 @@ class EntityLinker(Pipe):
         entity_encodings = self.model.ops.asarray(entity_encodings, dtype="float32")
         if sentence_encodings.shape != entity_encodings.shape:
             err = Errors.E147.format(
-                method="get_similarity_loss", msg="gold entities do not match up"
+                method="get_loss", msg="gold entities do not match up"
             )
             raise RuntimeError(err)
         gradients = self.distance.get_grad(sentence_encodings, entity_encodings)
@@ -337,13 +337,13 @@ class EntityLinker(Pipe):
                                     final_kb_ids.append(candidates[0].entity_)
                                 else:
                                     random.shuffle(candidates)
-                                    # this will set all prior probabilities to 0 if they should be excluded from the model
+                                    # set all prior probabilities to 0 if incl_prior=False
                                     prior_probs = xp.asarray(
                                         [c.prior_prob for c in candidates]
                                     )
                                     if not self.cfg.get("incl_prior"):
                                         prior_probs = xp.asarray(
-                                            [0.0 for c in candidates]
+                                            [0.0 for _ in candidates]
                                         )
                                     scores = prior_probs
                                     # add in similarity from the context

spacy/pipeline/multitask.pyx

@@ -1,7 +1,7 @@
 # cython: infer_types=True, profile=True, binding=True
 from typing import Optional
 import numpy
-from thinc.api import CosineDistance, to_categorical, to_categorical, Model, Config
+from thinc.api import CosineDistance, to_categorical, Model, Config
 from thinc.api import set_dropout_rate
 
 from ..tokens.doc cimport Doc
@@ -9,7 +9,7 @@ from ..tokens.doc cimport Doc
 from .pipe import Pipe
 from .tagger import Tagger
 from ..language import Language
-from ..syntax import nonproj
+from ._parser_internals import nonproj
 from ..attrs import POS, ID
 from ..errors import Errors
 
@@ -219,3 +219,6 @@ class ClozeMultitask(Pipe):
 
         if losses is not None:
             losses[self.name] += loss
+
+    def add_label(self, label):
+        raise NotImplementedError

spacy/pipeline/ner.pyx

@@ -1,9 +1,9 @@
 # cython: infer_types=True, profile=True, binding=True
 from typing import Optional, Iterable
-from thinc.api import CosineDistance, to_categorical, get_array_module, Model, Config
+from thinc.api import Model, Config
 
-from ..syntax.nn_parser cimport Parser
-from ..syntax.ner cimport BiluoPushDown
+from .transition_parser cimport Parser
+from ._parser_internals.ner cimport BiluoPushDown
 
 from ..language import Language
 from ..scorer import Scorer

spacy/pipeline/pipe.pxd

@@ -0,0 +1,2 @@
+cdef class Pipe:
+    cdef public str name

spacy/pipeline/pipe.pyx

@@ -8,7 +8,7 @@ from ..errors import Errors
 from .. import util
 
 
-class Pipe:
+cdef class Pipe:
     """This class is a base class and not instantiated directly. Trainable
     pipeline components like the EntityRecognizer or TextCategorizer inherit
     from it and it defines the interface that components should follow to
@@ -17,8 +17,6 @@ class Pipe:
     DOCS: https://spacy.io/api/pipe
     """
 
-    name = None
-
     def __init__(self, vocab, model, name, **cfg):
         """Initialize a pipeline component.
 

spacy/pipeline/sentencizer.pyx

@@ -203,3 +203,9 @@ class Sentencizer(Pipe):
         cfg = srsly.read_json(path)
         self.punct_chars = set(cfg.get("punct_chars", self.default_punct_chars))
         return self
+
+    def get_loss(self, examples, scores):
+        raise NotImplementedError
+
+    def add_label(self, label):
+        raise NotImplementedError

spacy/pipeline/senter.pyx

@@ -109,7 +109,7 @@ class SentenceRecognizer(Tagger):
         for eg in examples:
             eg_truth = []
             for x in eg.get_aligned("sent_start"):
-                if x == None:
+                if x is None:
                     eg_truth.append(None)
                 elif x == 1:
                     eg_truth.append(labels[1])

spacy/pipeline/simple_ner.py

@@ -131,8 +131,6 @@ class SimpleNER(Pipe):
         return losses
 
     def get_loss(self, examples: List[Example], scores) -> Tuple[List[Floats2d], float]:
-        loss = 0
-        d_scores = []
         truths = []
         for eg in examples:
             tags = eg.get_aligned("TAG", as_string=True)
@@ -159,7 +157,6 @@ class SimpleNER(Pipe):
         if not hasattr(get_examples, "__call__"):
             gold_tuples = get_examples
             get_examples = lambda: gold_tuples
-        labels = _get_labels(get_examples())
         for label in _get_labels(get_examples()):
             self.add_label(label)
         labels = self.labels

spacy/pipeline/textcat.py

@@ -238,8 +238,11 @@ class TextCategorizer(Pipe):
 
         DOCS: https://spacy.io/api/textcategorizer#rehearse
         """
+
+        if losses is not None:
+            losses.setdefault(self.name, 0.0)
         if self._rehearsal_model is None:
-            return
+            return losses
         try:
             docs = [eg.predicted for eg in examples]
         except AttributeError:
@@ -250,7 +253,7 @@ class TextCategorizer(Pipe):
             raise TypeError(err)
         if not any(len(doc) for doc in docs):
             # Handle cases where there are no tokens in any docs.
-            return
+            return losses
         set_dropout_rate(self.model, drop)
         scores, bp_scores = self.model.begin_update(docs)
         target = self._rehearsal_model(examples)
@@ -259,7 +262,6 @@ class TextCategorizer(Pipe):
         if sgd is not None:
             self.model.finish_update(sgd)
         if losses is not None:
-            losses.setdefault(self.name, 0.0)
             losses[self.name] += (gradient ** 2).sum()
         return losses
 

spacy/pipeline/tok2vec.py

@@ -199,6 +199,9 @@ class Tok2Vec(Pipe):
         docs = [Doc(self.vocab, words=["hello"])]
         self.model.initialize(X=docs)
 
+    def add_label(self, label):
+        raise NotImplementedError
+
 
 class Tok2VecListener(Model):
     """A layer that gets fed its answers from an upstream connection,

spacy/pipeline/transition_parser.pxd

@@ -1,16 +1,15 @@
-from .stateclass cimport StateClass
-from .arc_eager cimport TransitionSystem
+from cymem.cymem cimport Pool
+
 from ..vocab cimport Vocab
-from ..tokens.doc cimport Doc
-from ..structs cimport TokenC
-from ._state cimport StateC
-from ._parser_model cimport WeightsC, ActivationsC, SizesC
+from .pipe cimport Pipe
+from ._parser_internals.transition_system cimport Transition, TransitionSystem
+from ._parser_internals._state cimport StateC
+from ..ml.parser_model cimport WeightsC, ActivationsC, SizesC
 
 
-cdef class Parser:
+cdef class Parser(Pipe):
     cdef readonly Vocab vocab
     cdef public object model
-    cdef public str name
     cdef public object _rehearsal_model
     cdef readonly TransitionSystem moves
     cdef readonly object cfg

spacy/pipeline/transition_parser.pyx

@@ -1,42 +1,32 @@
 # cython: infer_types=True, cdivision=True, boundscheck=False
-cimport cython.parallel
+from __future__ import print_function
+from cymem.cymem cimport Pool
 cimport numpy as np
 from itertools import islice
-from cpython.ref cimport PyObject, Py_XDECREF
-from cpython.exc cimport PyErr_CheckSignals, PyErr_SetFromErrno
-from libc.math cimport exp
 from libcpp.vector cimport vector
-from libc.string cimport memset, memcpy
+from libc.string cimport memset
 from libc.stdlib cimport calloc, free
-from cymem.cymem cimport Pool
-from thinc.backends.linalg cimport Vec, VecVec
 
-from thinc.api import chain, clone, Linear, list2array, NumpyOps, CupyOps, use_ops
-from thinc.api import get_array_module, zero_init, set_dropout_rate
-from itertools import islice
 import srsly
+
+from ._parser_internals.stateclass cimport StateClass
+from ..ml.parser_model cimport alloc_activations, free_activations
+from ..ml.parser_model cimport predict_states, arg_max_if_valid
+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 ..errors import Errors, Warnings
+from .. import util
+from ..util import create_default_optimizer
+
+from thinc.api import set_dropout_rate
 import numpy.random
 import numpy
 import warnings
 
-from ..tokens.doc cimport Doc
-from ..typedefs cimport weight_t, class_t, hash_t
-from ._parser_model cimport alloc_activations, free_activations
-from ._parser_model cimport predict_states, arg_max_if_valid
-from ._parser_model cimport WeightsC, ActivationsC, SizesC, cpu_log_loss
-from ._parser_model cimport get_c_weights, get_c_sizes
-from .stateclass cimport StateClass
-from ._state cimport StateC
-from .transition_system cimport Transition
 
-from ..util import create_default_optimizer, registry
-from ..compat import copy_array
-from ..errors import Errors, Warnings
-from .. import util
-from . import nonproj
-
-
-cdef class Parser:
+cdef class Parser(Pipe):
     """
     Base class of the DependencyParser and EntityRecognizer.
     """
@@ -107,7 +97,7 @@ cdef class Parser:
 
     @property
     def tok2vec(self):
-        '''Return the embedding and convolutional layer of the model.'''
+        """Return the embedding and convolutional layer of the model."""
         return self.model.get_ref("tok2vec")
 
     @property
@@ -138,13 +128,13 @@ cdef class Parser:
         raise NotImplementedError
 
     def init_multitask_objectives(self, get_examples, pipeline, **cfg):
-        '''Setup models for secondary objectives, to benefit from multi-task
+        """Setup models for secondary objectives, to benefit from multi-task
         learning. This method is intended to be overridden by subclasses.
 
         For instance, the dependency parser can benefit from sharing
         an input representation with a label prediction model. These auxiliary
         models are discarded after training.
-        '''
+        """
         pass
 
     def use_params(self, params):

spacy/tests/parser/test_arc_eager_oracle.py

@@ -4,8 +4,8 @@ from spacy import registry
 from spacy.gold import Example
 from spacy.pipeline import DependencyParser
 from spacy.tokens import Doc
-from spacy.syntax.nonproj import projectivize
-from spacy.syntax.arc_eager import ArcEager
+from spacy.pipeline._parser_internals.nonproj import projectivize
+from spacy.pipeline._parser_internals.arc_eager import ArcEager
 from spacy.pipeline.dep_parser import DEFAULT_PARSER_MODEL
 
 

spacy/tests/parser/test_ner.py

@@ -5,7 +5,7 @@ from spacy.lang.en import English
 
 from spacy.language import Language
 from spacy.lookups import Lookups
-from spacy.syntax.ner import BiluoPushDown
+from spacy.pipeline._parser_internals.ner import BiluoPushDown
 from spacy.gold import Example
 from spacy.tokens import Doc
 from spacy.vocab import Vocab

spacy/tests/parser/test_neural_parser.py

@@ -3,8 +3,8 @@ import pytest
 from spacy import registry
 from spacy.gold import Example
 from spacy.vocab import Vocab
-from spacy.syntax.arc_eager import ArcEager
-from spacy.syntax.nn_parser import Parser
+from spacy.pipeline._parser_internals.arc_eager import ArcEager
+from spacy.pipeline.transition_parser import Parser
 from spacy.tokens.doc import Doc
 from thinc.api import Model
 from spacy.pipeline.tok2vec import DEFAULT_TOK2VEC_MODEL

spacy/tests/parser/test_nonproj.py

@@ -1,7 +1,7 @@
 import pytest
-from spacy.syntax.nonproj import ancestors, contains_cycle, is_nonproj_arc
-from spacy.syntax.nonproj import is_nonproj_tree
-from spacy.syntax import nonproj
+from spacy.pipeline._parser_internals.nonproj import ancestors, contains_cycle, is_nonproj_arc
+from spacy.pipeline._parser_internals.nonproj import is_nonproj_tree
+from spacy.pipeline._parser_internals import nonproj
 
 from ..util import get_doc