Add section on disabling pipeline components

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ines 2017-05-25 00:10:06 +02:00
parent 9efa662345
commit 419d265ff0

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@ -315,3 +315,43 @@ p
| For more information and a detailed guide on how to package your model, | For more information and a detailed guide on how to package your model,
| see the documentation on | see the documentation on
| #[+a("/docs/usage/saving-loading#models") saving and loading models]. | #[+a("/docs/usage/saving-loading#models") saving and loading models].
+h(2, "disabling") Disabling pipeline components
p
| If you don't need a particular component of the pipeline for
| example, the tagger or the parser, you can disable loading it. This can
| sometimes make a big difference and improve loading speed. Disabled
| component names can be provided to #[code spacy.load], #[code from_disk]
| or the #[code nlp] object itself as a list:
+code.
nlp = spacy.load('en', disable['parser', 'tagger'])
nlp = English().from_disk('/model', disable=['vectorizer', 'ner'])
doc = nlp(u"I don't want parsed", disable=['parser'])
p
| Note that you can't write directly to #[code nlp.pipeline], as this list
| holds the #[em actual components], not the IDs. However, if you know the
| order of the components, you can still slice the list:
+code.
nlp = spacy.load('en')
nlp.pipeline = nlp.pipeline[:2] # only use the first two components
+infobox("Important note: disabling pipeline components")
.o-block
| Since spaCy v2.0 comes with better support for customising the
| processing pipeline components, the #[code parser], #[code tagger]
| and #[code entity] keyword arguments have been replaced with
| #[code disable], which takes a list of
| #[+a("/docs/usage/language-processing-pipeline") pipeline component names].
| This lets you disable both default and custom components when loading
| a model, or initialising a Language class via
| #[+api("language-from_disk") #[code from_disk]].
+code-new.
nlp = spacy.load('en', disable=['parser'])
doc = nlp(u"I don't want parsed", disable=['parser'])
+code-old.
nlp = spacy.load('en', parser=False)
doc = nlp(u"I don't want parsed", parse=False)