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36 lines
1.9 KiB
Plaintext
36 lines
1.9 KiB
Plaintext
//- 💫 DOCS > USAGE > SPACY 101 > SERIALIZATION
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p
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| If you've been modifying the pipeline, vocabulary vectors and entities, or made
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| updates to the model, you'll eventually want
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| to #[strong save your progress] – for example, everything that's in your #[code nlp]
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| object. This means you'll have to translate its contents and structure
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| into a format that can be saved, like a file or a byte string. This
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| process is called serialization. spaCy comes with
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| #[strong built-in serialization methods] and supports the
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| #[+a("http://www.diveintopython3.net/serializing.html#dump") Pickle protocol].
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+aside("What's pickle?")
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| Pickle is Python's built-in object persistance system. It lets you
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| transfer arbitrary Python objects between processes. This is usually used
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| to load an object to and from disk, but it's also used for distributed
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| computing, e.g. with
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| #[+a("https://spark.apache.org/docs/0.9.0/python-programming-guide.html") PySpark]
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| or #[+a("http://dask.pydata.org/en/latest/") Dask]. When you unpickle an
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| object, you're agreeing to execute whatever code it contains. It's like
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| calling #[code eval()] on a string – so don't unpickle objects from
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| untrusted sources.
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p
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| All container classes and pipeline components, i.e.
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for cls in ["Doc", "Language", "Tokenizer", "Tagger", "DependencyParser", "EntityRecognizer", "Vocab", "StringStore"]
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| #[+api(cls.toLowerCase()) #[code=cls]],
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| have the following methods available:
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+table(["Method", "Returns", "Example"])
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- style = [1, 0, 1]
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+annotation-row(["to_bytes", "bytes", "nlp.to_bytes()"], style)
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+annotation-row(["from_bytes", "object", "nlp.from_bytes(bytes)"], style)
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+annotation-row(["to_disk", "-", "nlp.to_disk('/path')"], style)
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+annotation-row(["from_disk", "object", "nlp.from_disk('/path')"], style)
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