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62 lines
2.6 KiB
Plaintext
62 lines
2.6 KiB
Plaintext
//- 💫 DOCS > USAGE > PROCESSING PIPELINES > ATTRIBUTE HOOKS
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p
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| Hooks let you customize some of the behaviours of the #[code Doc],
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| #[code Span] or #[code Token] objects by adding a component to the
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| pipeline. For instance, to customize the
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| #[+api("doc#similarity") #[code Doc.similarity]] method, you can add a
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| component that sets a custom function to
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| #[code doc.user_hooks['similarity']]. The built-in #[code Doc.similarity]
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| method will check the #[code user_hooks] dict, and delegate to your
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| function if you've set one. Similar results can be achieved by setting
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| functions to #[code Doc.user_span_hooks] and #[code Doc.user_token_hooks].
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+code("Polymorphic similarity example").
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span.similarity(doc)
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token.similarity(span)
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doc1.similarity(doc2)
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p
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| By default, this just averages the vectors for each document, and
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| computes their cosine. Obviously, spaCy should make it easy for you to
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| install your own similarity model. This introduces a tricky design
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| challenge. The current solution is to add three more dicts to the
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| #[code Doc] object:
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+aside("Implementation note")
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| The hooks live on the #[code Doc] object because the #[code Span] and
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| #[code Token] objects are created lazily, and don't own any data. They
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| just proxy to their parent #[code Doc]. This turns out to be convenient
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| here — we only have to worry about installing hooks in one place.
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+table(["Name", "Description"])
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+row
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+cell #[code user_hooks]
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+cell Customise behaviour of #[code doc.vector], #[code doc.has_vector], #[code doc.vector_norm] or #[code doc.sents]
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+row
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+cell #[code user_token_hooks]
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+cell Customise behaviour of #[code token.similarity], #[code token.vector], #[code token.has_vector], #[code token.vector_norm] or #[code token.conjuncts]
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+row
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+cell #[code user_span_hooks]
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+cell Customise behaviour of #[code span.similarity], #[code span.vector], #[code span.has_vector], #[code span.vector_norm] or #[code span.root]
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p
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| To sum up, here's an example of hooking in custom #[code .similarity()]
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| methods:
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+code("Add custom similarity hooks").
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class SimilarityModel(object):
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def __init__(self, model):
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self._model = model
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def __call__(self, doc):
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doc.user_hooks['similarity'] = self.similarity
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doc.user_span_hooks['similarity'] = self.similarity
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doc.user_token_hooks['similarity'] = self.similarity
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def similarity(self, obj1, obj2):
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y = self._model([obj1.vector, obj2.vector])
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return float(y[0])
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