35 lines
1.1 KiB
Python
35 lines
1.1 KiB
Python
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from typing import Optional, List
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from thinc.types import Floats2d
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from thinc.api import Model
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from spacy.util import registry
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from spacy.tokens import Doc
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def EntityLinker_v1(
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tok2vec: Model, nO: Optional[int] = None
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) -> Model[List[Doc], Floats2d]:
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chain = registry.get("layers", "chain.v1")
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clone = registry.get("layers", "clone.v1")
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with Model.define_operators({">>": chain, "**": clone}):
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token_width = tok2vec.maybe_get_dim("nO")
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Linear = registry.get("layers", "Linear.v1")
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output_layer = Linear(nO=nO, nI=token_width)
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list2ragged = registry.get("layers", "list2ragged.v1")
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reduce_mean = registry.get("layers", "reduce_mean.v1")
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residual = registry.get("layers", "residual.v1")
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Maxout = registry.get("layers", "Maxout.v1")
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model = (
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tok2vec
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>> list2ragged()
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>> reduce_mean()
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>> residual(Maxout(nO=token_width, nI=token_width, nP=2, dropout=0.0)) # type: ignore[arg-type]
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>> output_layer
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)
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model.set_ref("output_layer", output_layer)
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model.set_ref("tok2vec", tok2vec)
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return model
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