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36 lines
1.1 KiB
Python
36 lines
1.1 KiB
Python
from pydantic import StrictInt
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from thinc.api import Model, chain, list2array, Linear, zero_init, use_ops, with_array
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from thinc.api import LayerNorm, Maxout, Mish
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from ...util import registry
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from .._precomputable_affine import PrecomputableAffine
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from ..tb_framework import TransitionModel
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@registry.architectures.register("spacy.TransitionBasedParser.v1")
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def build_tb_parser_model(
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tok2vec: Model,
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nr_feature_tokens: StrictInt,
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hidden_width: StrictInt,
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maxout_pieces: StrictInt,
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use_upper=True,
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nO=None,
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):
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t2v_width = tok2vec.get_dim("nO") if tok2vec.has_dim("nO") else None
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tok2vec = chain(tok2vec, list2array(), Linear(hidden_width, t2v_width),)
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tok2vec.set_dim("nO", hidden_width)
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lower = PrecomputableAffine(
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nO=hidden_width if use_upper else nO,
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nF=nr_feature_tokens,
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nI=tok2vec.get_dim("nO"),
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nP=maxout_pieces,
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)
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if use_upper:
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with use_ops("numpy"):
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# Initialize weights at zero, as it's a classification layer.
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upper = Linear(nO=nO, init_W=zero_init)
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else:
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upper = None
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return TransitionModel(tok2vec, lower, upper)
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