From 2bbab641e9cf7a8f861c85c9ff18a6c51966431b Mon Sep 17 00:00:00 2001 From: Lj Miranda Date: Mon, 5 Sep 2022 11:28:30 +0800 Subject: [PATCH] Use Softmax v2 directly from thinc --- spacy/pipeline/spancat_exclusive.py | 17 ++++------------- 1 file changed, 4 insertions(+), 13 deletions(-) diff --git a/spacy/pipeline/spancat_exclusive.py b/spacy/pipeline/spancat_exclusive.py index befd5838f..9a52fc1d4 100644 --- a/spacy/pipeline/spancat_exclusive.py +++ b/spacy/pipeline/spancat_exclusive.py @@ -2,33 +2,24 @@ from dataclasses import dataclass from typing import Any, Callable, Dict, Iterable, List, Optional, Tuple, cast import numpy -from thinc.api import Config, Model, Ops, Optimizer, Softmax_v2 -from thinc.api import get_current_ops, set_dropout_rate -from thinc.types import Floats2d, Ints1d, Ints2d, Ragged +from thinc.api import Config, Model, Ops, Optimizer +from thinc.api import set_dropout_rate +from thinc.types import Floats2d, Ints2d, Ragged from ..compat import Protocol, runtime_checkable from ..errors import Errors from ..language import Language from ..tokens import Doc, Span, SpanGroup from ..training import Example, validate_examples -from ..util import registry from ..vocab import Vocab from .spancat import spancat_score, build_ngram_suggester from .trainable_pipe import TrainablePipe -@registry.layers("spacy.Softmax.v1") -def build_softmax(nO=None, nI=None) -> Model[Floats2d, Floats2d]: - """ - An output layer for softmax classification. - """ - return Softmax_v2(nI=nI, nO=nO) - - spancat_exclusive_default_config = """ [model] @architectures = "spacy.SpanCategorizer.v1" -scorer = {"@layers": "spacy.Softmax.v1"} +scorer = {"@layers": "Softmax.v2"} [model.reducer] @layers = spacy.mean_max_reducer.v1