From 64cf5116b7b582204cd85e05bb68fbc433eddc00 Mon Sep 17 00:00:00 2001 From: Ian Thompson Date: Thu, 13 Jul 2023 10:48:49 -0500 Subject: [PATCH] modified: spacy/language.py - corrected typo in docstring for :method:`Language.replace_listeners` - added noqa comment on unused local variable assignment in :method:`Language.from_config` as I wasn't sure if it should be unassigned modified: website/docs/api/language.mdx - corrected typo in `Language.replace_listeners` markdown --- spacy/language.py | 4 ++-- website/docs/api/language.mdx | 2 +- 2 files changed, 3 insertions(+), 3 deletions(-) diff --git a/spacy/language.py b/spacy/language.py index fd616483b..2c120c502 100644 --- a/spacy/language.py +++ b/spacy/language.py @@ -1825,7 +1825,7 @@ class Language: # Later we replace the component config with the raw config again. interpolated = filled.interpolate() if not filled.is_interpolated else filled pipeline = interpolated.get("components", {}) - sourced = util.get_sourced_components(interpolated) + sourced = util.get_sourced_components(interpolated) # noqa: F841 # If components are loaded from a source (existing models), we cache # them here so they're only loaded once source_nlps = {} @@ -1958,7 +1958,7 @@ class Language: useful when training a pipeline with components sourced from an existing pipeline: if multiple components (e.g. tagger, parser, NER) listen to the same tok2vec component, but some of them are frozen and not updated, - their performance may degrade significally as the tok2vec component is + their performance may degrade significantly as the tok2vec component is updated with new data. To prevent this, listeners can be replaced with a standalone tok2vec layer that is owned by the component and doesn't change if the component isn't updated. diff --git a/website/docs/api/language.mdx b/website/docs/api/language.mdx index de23156b9..068e8ea78 100644 --- a/website/docs/api/language.mdx +++ b/website/docs/api/language.mdx @@ -856,7 +856,7 @@ token-to-vector embedding component like [`Tok2Vec`](/api/tok2vec) or training a pipeline with components sourced from an existing pipeline: if multiple components (e.g. tagger, parser, NER) listen to the same token-to-vector component, but some of them are frozen and not updated, their -performance may degrade significally as the token-to-vector component is updated +performance may degrade significantly as the token-to-vector component is updated with new data. To prevent this, listeners can be replaced with a standalone token-to-vector layer that is owned by the component and doesn't change if the component isn't updated.