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TransitionBasedParser.v1 to legacy (#8586)
* TransitionBasedParser.v1 to legacy * register sublayers * bump spacy-legacy to 3.0.7
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# Our libraries
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spacy-legacy>=3.0.6,<3.1.0
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spacy-legacy>=3.0.7,<3.1.0
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cymem>=2.0.2,<2.1.0
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preshed>=3.0.2,<3.1.0
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thinc>=8.0.7,<8.1.0
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@ -40,7 +40,7 @@ setup_requires =
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thinc>=8.0.7,<8.1.0
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install_requires =
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# Our libraries
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spacy-legacy>=3.0.6,<3.1.0
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spacy-legacy>=3.0.7,<3.1.0
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murmurhash>=0.28.0,<1.1.0
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cymem>=2.0.2,<2.1.0
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preshed>=3.0.2,<3.1.0
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@ -1,6 +1,9 @@
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from thinc.api import Model, normal_init
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from ..util import registry
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@registry.layers("spacy.PrecomputableAffine.v1")
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def PrecomputableAffine(nO, nI, nF, nP, dropout=0.1):
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model = Model(
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"precomputable_affine",
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@ -10,48 +10,7 @@ from ..tb_framework import TransitionModel
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from ...tokens import Doc
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@registry.architectures("spacy.TransitionBasedParser.v1")
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def transition_parser_v1(
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tok2vec: Model[List[Doc], List[Floats2d]],
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state_type: Literal["parser", "ner"],
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extra_state_tokens: bool,
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hidden_width: int,
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maxout_pieces: int,
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use_upper: bool = True,
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nO: Optional[int] = None,
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) -> Model:
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return build_tb_parser_model(
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tok2vec,
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state_type,
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extra_state_tokens,
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hidden_width,
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maxout_pieces,
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use_upper,
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nO,
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)
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@registry.architectures("spacy.TransitionBasedParser.v2")
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def transition_parser_v2(
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tok2vec: Model[List[Doc], List[Floats2d]],
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state_type: Literal["parser", "ner"],
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extra_state_tokens: bool,
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hidden_width: int,
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maxout_pieces: int,
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use_upper: bool,
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nO: Optional[int] = None,
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) -> Model:
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return build_tb_parser_model(
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tok2vec,
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state_type,
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extra_state_tokens,
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hidden_width,
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maxout_pieces,
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use_upper,
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nO,
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)
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def build_tb_parser_model(
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tok2vec: Model[List[Doc], List[Floats2d]],
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state_type: Literal["parser", "ner"],
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@ -1,7 +1,9 @@
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from thinc.api import Model, noop
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from .parser_model import ParserStepModel
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from ..util import registry
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@registry.layers("spacy.TransitionModel.v1")
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def TransitionModel(
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tok2vec, lower, upper, resize_output, dropout=0.2, unseen_classes=set()
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):
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@ -553,6 +553,13 @@ consists of either two or three subnetworks:
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| `nO` | The number of actions the model will predict between. Usually inferred from data at the beginning of training, or loaded from disk. ~~int~~ |
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| **CREATES** | The model using the architecture. ~~Model[List[Docs], List[List[Floats2d]]]~~ |
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<Accordion title="spacy.TransitionBasedParser.v1 definition" spaced>
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[TransitionBasedParser.v1](/api/legacy#TransitionBasedParser_v1) had the exact same signature,
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but the `use_upper` argument was `True` by default.
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</Accordion>
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## Tagging architectures {#tagger source="spacy/ml/models/tagger.py"}
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### spacy.Tagger.v1 {#Tagger}
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@ -103,6 +103,11 @@ and residual connections.
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| `depth` | The number of convolutional layers. Recommended value is `4`. ~~int~~ |
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| **CREATES** | The model using the architecture. ~~Model[Floats2d, Floats2d]~~ |
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### spacy.TransitionBasedParser.v1 {#TransitionBasedParser_v1}
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Identical to [`spacy.TransitionBasedParser.v2`](/api/architectures#TransitionBasedParser)
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except the `use_upper` was set to `True` by default.
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### spacy.TextCatEnsemble.v1 {#TextCatEnsemble_v1}
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The `spacy.TextCatEnsemble.v1` architecture built an internal `tok2vec` and
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