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82 lines
3.9 KiB
Plaintext
82 lines
3.9 KiB
Plaintext
//- 💫 DOCS > USAGE > MODELS > PRODUCTION USE
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p
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| If your application depends on one or more models,
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| you'll usually want to integrate them into your continuous integration
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| workflow and build process. While spaCy provides a range of useful helpers
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| for downloading, linking and loading models, the underlying functionality
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| is entirely based on native Python packages. This allows your application
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| to handle a model like any other package dependency.
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+infobox("Training models for production")
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| For an example of an automated model training and build process, see
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| #[+a("/usage/training#example-training-spacy") this example] of how
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| we're training and packaging our models for spaCy.
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+h(3, "models-download") Downloading and requiring model dependencies
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p
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| spaCy's built-in #[+api("cli#download") #[code download]] command
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| is mostly intended as a convenient, interactive wrapper. It performs
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| compatibility checks and prints detailed error messages and warnings.
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| However, if you're downloading models as part of an automated build
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| process, this only adds an unnecessary layer of complexity. If you know
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| which models your application needs, you should be specifying them directly.
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p
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| Because all models are valid Python packages, you can add them to your
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| application's #[code requirements.txt]. If you're running your own
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| internal PyPi installation, you can simply upload the models there. pip's
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| #[+a("https://pip.pypa.io/en/latest/reference/pip_install/#requirements-file-format") requirements file format]
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| supports both package names to download via a PyPi server, as well as direct
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| URLs.
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+code("requirements.txt", "text").
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spacy>=2.0.0,<3.0.0
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-e #{gh("spacy-models")}/releases/download/en_core_web_sm-2.0.0/en_core_web_sm-2.0.0.tar.gz#en_core_web_sm
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p
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| Specifying #[code #egg=] with the package name tells pip
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| which package to expect from the download URL. This way, the
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| package won't be re-downloaded and overwritten if it's already
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| installed - just like when you're downloading a package from PyPi.
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p
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| All models are versioned and specify their spaCy dependency. This ensures
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| cross-compatibility and lets you specify exact version requirements for
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| each model. If you've trained your own model, you can use the
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| #[+api("cli#package") #[code package]] command to generate the required
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| meta data and turn it into a loadable package.
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+h(3, "models-loading") Loading and testing models
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p
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| Downloading models directly via pip won't call spaCy's link
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| #[+api("cli#link") #[code link]] command, which creates
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| symlinks for model shortcuts. This means that you'll have to run this
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| command separately, or use the native #[code import] syntax to load the
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| models:
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+code.
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import en_core_web_sm
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nlp = en_core_web_sm.load()
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p
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| In general, this approach is recommended for larger code bases, as it's
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| more "native", and doesn't depend on symlinks or rely on spaCy's loader
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| to resolve string names to model packages. If a model can't be
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| imported, Python will raise an #[code ImportError] immediately. And if a
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| model is imported but not used, any linter will catch that.
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p
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| Similarly, it'll give you more flexibility when writing tests that
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| require loading models. For example, instead of writing your own
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| #[code try] and #[code except] logic around spaCy's loader, you can use
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| #[+a("http://pytest.readthedocs.io/en/latest/") pytest]'s
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| #[+a("https://docs.pytest.org/en/latest/builtin.html#_pytest.outcomes.importorskip") #[code importorskip()]]
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| method to only run a test if a specific model or model version is
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| installed. Each model package exposes a #[code __version__] attribute
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| which you can also use to perform your own version compatibility checks
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| before loading a model.
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