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spaCy/website/docs/api/cli.jade
ines 3419ecbfdd Update docs on model shortcut links
2017-06-04 13:55:00 +02:00

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//- 💫 DOCS > USAGE > COMMAND LINE INTERFACE
include ../../_includes/_mixins
p
| As of v1.7.0, spaCy comes with new command line helpers to download and
| link models and show useful debugging information. For a list of available
| commands, type #[code python -m spacy]. To make the command even more
| convenient, we recommend
| #[+a("https://askubuntu.com/questions/17536/how-do-i-create-a-permanent-bash-alias/17537#17537") creating an alias]
| mapping #[code python -m spacy] to #[code spacy].
+aside("Why python -m?")
| The problem with a global entry point is that it's resolved by looking up
| entries in your #[code PATH] environment variable. This can give you
| unexpected results, like executing the wrong spaCy installation.
| #[code python -m] prevents fallbacks to system modules.
+infobox("⚠️ Deprecation note")
| As of spaCy 2.0, the #[code model] command to initialise a model data
| directory is deprecated. The command was only necessary because previous
| versions of spaCy expected a model directory to already be set up. This
| has since been changed, so you can use the #[+api("cli#train") #[code train]]
| command straight away.
+h(2, "download") Download
p
| Download #[+a("/docs/usage/models") models] for spaCy. The downloader finds the
| best-matching compatible version, uses pip to download the model as a
| package and automatically creates a
| #[+a("/docs/usage/models#usage") shortcut link] to load the model by name.
| Direct downloads don't perform any compatibility checks and require the
| model name to be specified with its version (e.g., #[code en_core_web_sm-1.2.0]).
+code(false, "bash").
python -m spacy download [model] [--direct]
+table(["Argument", "Type", "Description"])
+row
+cell #[code model]
+cell positional
+cell Model name or shortcut (#[code en], #[code de], #[code vectors]).
+row
+cell #[code --direct], #[code -d]
+cell flag
+cell Force direct download of exact model version.
+row
+cell #[code --help], #[code -h]
+cell flag
+cell Show help message and available arguments.
+aside("Downloading best practices")
| The #[code download] command is mostly intended as a convenient,
| interactive wrapper – it performs compatibility checks and prints
| detailed messages in case things go wrong. It's #[strong not recommended]
| to use this command as part of an automated process. If you know which
| model your project needs, you should consider a
| #[+a("/docs/usage/models#download-pip") direct download via pip], or
| uploading the model to a local PyPi installation and fetching it straight
| from there. This will also allow you to add it as a versioned package
| dependency to your project.
+h(2, "link") Link
p
| Create a #[+a("/docs/usage/models#usage") shortcut link] for a model,
| either a Python package or a local directory. This will let you load
| models from any location using a custom name via
| #[+api("spacy#load") #[code spacy.load()]].
+infobox("Important note")
| In spaCy v1.x, you had to use the model data directory to set up a shortcut
| link for a local path. As of v2.0, spaCy expects all shortcut links to
| be #[strong loadable model packages]. If you want to load a data directory,
| call #[+api("spacy#load") #[code spacy.load()]] or
| #[+api("language#from_disk") #[code Language.from_disk()]] with the path,
| or use the #[+api("cli#package") #[code package]] command to create a
| model package.
+code(false, "bash").
python -m spacy link [origin] [link_name] [--force]
+table(["Argument", "Type", "Description"])
+row
+cell #[code origin]
+cell positional
+cell Model name if package, or path to local directory.
+row
+cell #[code link_name]
+cell positional
+cell Name of the shortcut link to create.
+row
+cell #[code --force], #[code -f]
+cell flag
+cell Force overwriting of existing link.
+row
+cell #[code --help], #[code -h]
+cell flag
+cell Show help message and available arguments.
+h(2, "info") Info
p
| Print information about your spaCy installation, models and local setup,
| and generate #[+a("https://en.wikipedia.org/wiki/Markdown") Markdown]-formatted
| markup to copy-paste into #[+a(gh("spacy") + "/issues") GitHub issues].
+code(false, "bash").
python -m spacy info [--markdown]
python -m spacy info [model] [--markdown]
+table(["Argument", "Type", "Description"])
+row
+cell #[code model]
+cell positional
+cell A model, i.e. shortcut link, package name or path (optional).
+row
+cell #[code --markdown], #[code -md]
+cell flag
+cell Print information as Markdown.
+row
+cell #[code --help], #[code -h]
+cell flag
+cell Show help message and available arguments.
+h(2, "convert") Convert
p
| Convert files into spaCy's #[+a("/docs/api/annotation#json-input") JSON format]
| for use with the #[code train] command and other experiment management
| functions. The right converter is chosen based on the file extension of
| the input file. Currently only supports #[code .conllu].
+code(false, "bash").
python -m spacy convert [input_file] [output_dir] [--n-sents] [--morphology]
+table(["Argument", "Type", "Description"])
+row
+cell #[code input_file]
+cell positional
+cell Input file.
+row
+cell #[code output_dir]
+cell positional
+cell Output directory for converted JSON file.
+row
+cell #[code --n-sents], #[code -n]
+cell option
+cell Number of sentences per document.
+row
+cell #[code --morphology], #[code -m]
+cell option
+cell Enable appending morphology to tags.
+row
+cell #[code --help], #[code -h]
+cell flag
+cell Show help message and available arguments.
+h(2, "train") Train
p
| Train a model. Expects data in spaCy's
| #[+a("/docs/api/annotation#json-input") JSON format].
+code(false, "bash").
python -m spacy train [lang] [output_dir] [train_data] [dev_data] [--n-iter] [--n-sents] [--use-gpu] [--no-tagger] [--no-parser] [--no-entities]
+table(["Argument", "Type", "Description"])
+row
+cell #[code lang]
+cell positional
+cell Model language.
+row
+cell #[code output_dir]
+cell positional
+cell Directory to store model in.
+row
+cell #[code train_data]
+cell positional
+cell Location of JSON-formatted training data.
+row
+cell #[code dev_data]
+cell positional
+cell Location of JSON-formatted dev data (optional).
+row
+cell #[code --n-iter], #[code -n]
+cell option
+cell Number of iterations (default: #[code 20]).
+row
+cell #[code --n-sents], #[code -ns]
+cell option
+cell Number of sentences (default: #[code 0]).
+row
+cell #[code --use-gpu], #[code -G]
+cell flag
+cell Use GPU.
+row
+cell #[code --no-tagger], #[code -T]
+cell flag
+cell Don't train tagger.
+row
+cell #[code --no-parser], #[code -P]
+cell flag
+cell Don't train parser.
+row
+cell #[code --no-entities], #[code -N]
+cell flag
+cell Don't train NER.
+row
+cell #[code --help], #[code -h]
+cell flag
+cell Show help message and available arguments.
+h(3, "train-hyperparams") Environment variables for hyperparameters
p
| spaCy lets you set hyperparameters for training via environment variables.
| This is useful, because it keeps the command simple and allows you to
| #[+a("https://askubuntu.com/questions/17536/how-do-i-create-a-permanent-bash-alias/17537#17537") create an alias]
| for your custom #[code train] command while still being able to easily
| tweak the hyperparameters. For example:
+code(false, "bash").
parser_hidden_depth=2 parser_maxout_pieces=1 train-parser
+under-construction
+table(["Name", "Description", "Default"])
+row
+cell #[code dropout_from]
+cell
+cell #[code 0.2]
+row
+cell #[code dropout_to]
+cell
+cell #[code 0.2]
+row
+cell #[code dropout_decay]
+cell
+cell #[code 0.0]
+row
+cell #[code batch_from]
+cell
+cell #[code 1]
+row
+cell #[code batch_to]
+cell
+cell #[code 64]
+row
+cell #[code batch_compound]
+cell
+cell #[code 1.001]
+row
+cell #[code token_vector_width]
+cell
+cell #[code 128]
+row
+cell #[code embed_size]
+cell
+cell #[code 7500]
+row
+cell #[code parser_maxout_pieces]
+cell
+cell #[code 2]
+row
+cell #[code parser_hidden_depth]
+cell
+cell #[code 1]
+row
+cell #[code hidden_width]
+cell
+cell #[code 128]
+row
+cell #[code learn_rate]
+cell
+cell #[code 0.001]
+row
+cell #[code optimizer_B1]
+cell
+cell #[code 0.9]
+row
+cell #[code optimizer_B2]
+cell
+cell #[code 0.999]
+row
+cell #[code optimizer_eps]
+cell
+cell #[code 1e-08]
+row
+cell #[code L2_penalty]
+cell
+cell #[code 1e-06]
+row
+cell #[code grad_norm_clip]
+cell
+cell #[code 1.0]
+h(2, "package") Package
p
| Generate a #[+a("/docs/usage/saving-loading#generating") model Python package]
| from an existing model data directory. All data files are copied over.
| If the path to a meta.json is supplied, or a meta.json is found in the
| input directory, this file is used. Otherwise, the data can be entered
| directly from the command line. The required file templates are downloaded
| from #[+src(gh("spacy-dev-resources", "templates/model")) GitHub] to make
| sure you're always using the latest versions. This means you need to be
| connected to the internet to use this command.
+code(false, "bash").
python -m spacy package [input_dir] [output_dir] [--meta] [--force]
+table(["Argument", "Type", "Description"])
+row
+cell #[code input_dir]
+cell positional
+cell Path to directory containing model data.
+row
+cell #[code output_dir]
+cell positional
+cell Directory to create package folder in.
+row
+cell #[code meta]
+cell option
+cell Path to meta.json file (optional).
+row
+cell #[code --force], #[code -f]
+cell flag
+cell Force overwriting of existing folder in output directory.
+row
+cell #[code --help], #[code -h]
+cell flag
+cell Show help message and available arguments.
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