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Use DEFAULT_EXCL_SPANCAT_MODEL

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I also renamed spancat_exclusive_default_config into
spancat_excl_default_config because black does some not pretty
formatting changes.
This commit is contained in:
Lj Miranda 2022-11-29 11:01:18 +08:00
parent d090ed404e
commit bd0562e609
1 changed files with 3 additions and 3 deletions
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6
spacy/pipeline/spancat_exclusive.py
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@ -13,7 +13,7 @@ from .spancat import spancat_score, Suggester
from .spancat import SpanCategorizer from .spancat import SpanCategorizer
spancat_exclusive_default_config = """ spancat_excl_default_config = """
[model] [model]
@architectures = "spacy.SpanCategorizer.v1" @architectures = "spacy.SpanCategorizer.v1"
scorer = {"@layers": "Softmax.v2"} scorer = {"@layers": "Softmax.v2"}
@ -39,7 +39,7 @@ maxout_pieces = 3
depth = 4 depth = 4
""" """
DEFAULT_SPANCAT_MODEL = Config().from_str(spancat_exclusive_default_config)["model"] DEFAULT_EXCL_SPANCAT_MODEL = Config().from_str(spancat_excl_default_config)["model"]
@Language.factory( @Language.factory(
@ -47,7 +47,7 @@ DEFAULT_SPANCAT_MODEL = Config().from_str(spancat_exclusive_default_config)["mod
assigns=["doc.spans"], assigns=["doc.spans"],
default_config={ default_config={
"spans_key": "sc", "spans_key": "sc",
"model": DEFAULT_SPANCAT_MODEL, "model": DEFAULT_EXCL_SPANCAT_MODEL,
"suggester": {"@misc": "spacy.ngram_suggester.v1", "sizes": [1, 2, 3]}, "suggester": {"@misc": "spacy.ngram_suggester.v1", "sizes": [1, 2, 3]},
"scorer": {"@scorers": "spacy.spancat_scorer.v1"}, "scorer": {"@scorers": "spacy.spancat_scorer.v1"},
}, },