from pydantic import StrictInt
from thinc.api import Model, chain, list2array, Linear, zero_init, use_ops

from ...util import registry
from .._layers import PrecomputableAffine
from ...syntax._parser_model import ParserModel


@registry.architectures.register("spacy.TransitionBasedParser.v1")
def build_tb_parser_model(
    tok2vec: Model,
    nr_feature_tokens: StrictInt,
    hidden_width: StrictInt,
    maxout_pieces: StrictInt,
    nO=None,
):
    token_vector_width = tok2vec.get_dim("nO")
    tok2vec = chain(tok2vec, list2array())
    tok2vec.set_dim("nO", token_vector_width)

    lower = PrecomputableAffine(
        nO=hidden_width,
        nF=nr_feature_tokens,
        nI=tok2vec.get_dim("nO"),
        nP=maxout_pieces,
    )
    lower.set_dim("nP", maxout_pieces)
    with use_ops("numpy"):
        # Initialize weights at zero, as it's a classification layer.
        upper = Linear(nO=nO, init_W=zero_init)
    model = ParserModel(tok2vec, lower, upper)
    return model