Rooba
/
spaCy
mirror of https://github.com/explosion/spaCy.git
1
1
Fork 0
Code Issues Packages Projects Releases Wiki Activity
spaCy/website/api/cli.jade

595 lines
18 KiB
Plaintext
Raw Blame History

This file contains ambiguous Unicode characters

This file contains Unicode characters that might be confused with other characters. If you think that this is intentional, you can safely ignore this warning. Use the Escape button to reveal them.

//- 💫 DOCS > API > 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 spacy --help].
+h(3, "download") Download
p
| Download #[+a("/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("/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", "$").
spacy download [model] [--direct]
+table(["Argument", "Type", "Description"])
+row
+cell #[code model]
+cell positional
+cell Model name or shortcut (#[code en], #[code de], #[code vectors]).
+row
+cell #[code --direct], #[code -d]
+cell flag
+cell Force direct download of exact model version.
+row
+cell #[code --help], #[code -h]
+cell flag
+cell Show help message and available arguments.
+row("foot")
+cell creates
+cell directory, symlink
+cell
| The installed model package in your #[code site-packages]
| directory and a shortcut link as a symlink in #[code spacy/data].
+aside("Downloading best practices")
| The #[code download] command is mostly intended as a convenient,
| interactive wrapper – it performs compatibility checks and prints
| detailed messages in case things go wrong. It's #[strong not recommended]
| to use this command as part of an automated process. If you know which
| model your project needs, you should consider a
| #[+a("/usage/models#download-pip") direct download via pip], or
| uploading the model to a local PyPi installation and fetching it straight
| from there. This will also allow you to add it as a versioned package
| dependency to your project.
+h(3, "link") Link
p
| Create a #[+a("/usage/models#usage") shortcut link] for a model,
| either a Python package or a local directory. This will let you load
| models from any location using a custom name via
| #[+api("spacy#load") #[code spacy.load()]].
+infobox("Important note")
| In spaCy v1.x, you had to use the model data directory to set up a shortcut
| link for a local path. As of v2.0, spaCy expects all shortcut links to
| be #[strong loadable model packages]. If you want to load a data directory,
| call #[+api("spacy#load") #[code spacy.load()]] or
| #[+api("language#from_disk") #[code Language.from_disk()]] with the path,
| or use the #[+api("cli#package") #[code package]] command to create a
| model package.
+code(false, "bash", "$").
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.
+row("foot")
+cell creates
+cell symlink
+cell
| A shortcut link of the given name as a symlink in
| #[code spacy/data].
+h(3, "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").
spacy info [--markdown]
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.
+row("foot")
+cell prints
+cell #[code stdout]
+cell Information about your spaCy installation.
+h(3, "validate") Validate
+tag-new(2)
p
| Find all models installed in the current environment (both packages and
| shortcut links) and check whether they are compatible with the currently
| installed version of spaCy. Should be run after upgrading spaCy via
| #[code pip install -U spacy] to ensure that all installed models are
| can be used with the new version. The command is also useful to detect
| out-of-sync model links resulting from links created in different virtual
| environments. Prints a list of models, the installed versions, the latest
| compatible version (if out of date) and the commands for updating.
+code(false, "bash", "$").
spacy validate
+table(["Argument", "Type", "Description"])
+row("foot")
+cell prints
+cell #[code stdout]
+cell Details about the compatibility of your installed models.
+h(3, "convert") Convert
p
| Convert files into spaCy's #[+a("/api/annotation#json-input") JSON format]
| for use with the #[code train] command and other experiment management
| functions. The converter can be specified on the command line, or
| chosen based on the file extension of the input file.
+code(false, "bash", "$", false, false, true).
spacy convert [input_file] [output_dir] [--converter] [--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 converter], #[code -c]
+cell option
+cell #[+tag-new(2)] Name of converter to use (see below).
+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.
+row("foot")
+cell creates
+cell JSON
+cell Data in spaCy's #[+a("/api/annotation#json-input") JSON format].
p The following converters are available:
+table(["ID", "Description"])
+row
+cell #[code auto]
+cell Automatically pick converter based on file extension (default).
+row
+cell #[code conllu], #[code conll]
+cell Universal Dependencies #[code .conllu] or #[code .conll] format.
+row
+cell #[code ner]
+cell Tab-based named entity recognition format.
+row
+cell #[code iob]
+cell IOB named entity recognition format.
+h(3, "train") Train
p
| Train a model. Expects data in spaCy's
| #[+a("/api/annotation#json-input") JSON format]. On each epoch, a model
| will be saved out to the directory. Accuracy scores and model details
| will be added to a #[+a("/usage/training#models-generating") #[code meta.json]]
| to allow packaging the model using the
| #[+api("cli#package") #[code package]] command.
+code(false, "bash", "$", false, false, true).
spacy train [lang] [output_dir] [train_data] [dev_data] [--n-iter] [--n-sents] [--use-gpu] [--meta-path] [--vectors] [--no-tagger] [--no-parser] [--no-entities] [--gold-preproc]
+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 option
+cell Use GPU.
+row
+cell #[code --vectors], #[code -v]
+cell option
+cell Model to load vectors from.
+row
+cell #[code --meta-path], #[code -m]
+cell option
+cell
| #[+tag-new(2)] Optional path to model
| #[+a("/usage/training#models-generating") #[code meta.json]].
| All relevant properties like #[code lang], #[code pipeline] and
| #[code spacy_version] will be overwritten.
+row
+cell #[code --version], #[code -V]
+cell option
+cell
| Model version. Will be written out to the model's
| #[code meta.json] after training.
+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 --gold-preproc], #[code -G]
+cell flag
+cell Use gold preprocessing.
+row
+cell #[code --help], #[code -h]
+cell flag
+cell Show help message and available arguments.
+row("foot")
+cell creates
+cell model, pickle
+cell A spaCy model on each epoch, and a final #[code .pickle] file.
+h(4, "train-hyperparams") Environment variables for hyperparameters
+tag-new(2)
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
+table(["Name", "Description", "Default"])
+row
+cell #[code dropout_from]
+cell Initial dropout rate.
+cell #[code 0.2]
+row
+cell #[code dropout_to]
+cell Final dropout rate.
+cell #[code 0.2]
+row
+cell #[code dropout_decay]
+cell Rate of dropout change.
+cell #[code 0.0]
+row
+cell #[code batch_from]
+cell Initial batch size.
+cell #[code 1]
+row
+cell #[code batch_to]
+cell Final batch size.
+cell #[code 64]
+row
+cell #[code batch_compound]
+cell Rate of batch size acceleration.
+cell #[code 1.001]
+row
+cell #[code token_vector_width]
+cell Width of embedding tables and convolutional layers.
+cell #[code 128]
+row
+cell #[code embed_size]
+cell Number of rows in embedding tables.
+cell #[code 7500]
//- +row
//- +cell #[code parser_maxout_pieces]
//- +cell Number of pieces in the parser's and NER's first maxout layer.
//- +cell #[code 2]
//- +row
//- +cell #[code parser_hidden_depth]
//- +cell Number of hidden layers in the parser and NER.
//- +cell #[code 1]
+row
+cell #[code hidden_width]
+cell Size of the parser's and NER's hidden layers.
+cell #[code 128]
//- +row
//- +cell #[code history_feats]
//- +cell Number of previous action ID features for parser and NER.
//- +cell #[code 128]
//- +row
//- +cell #[code history_width]
//- +cell Number of embedding dimensions for each action ID.
//- +cell #[code 128]
+row
+cell #[code learn_rate]
+cell Learning rate.
+cell #[code 0.001]
+row
+cell #[code optimizer_B1]
+cell Momentum for the Adam solver.
+cell #[code 0.9]
+row
+cell #[code optimizer_B2]
+cell Adagrad-momentum for the Adam solver.
+cell #[code 0.999]
+row
+cell #[code optimizer_eps]
+cell Epsylon value for the Adam solver.
+cell #[code 1e-08]
+row
+cell #[code L2_penalty]
+cell L2 regularisation penalty.
+cell #[code 1e-06]
+row
+cell #[code grad_norm_clip]
+cell Gradient L2 norm constraint.
+cell #[code 1.0]
+h(3, "vocab") Vocab
+tag-new(2)
p
| Compile a vocabulary from a
| #[+a("/api/annotation#vocab-jsonl") lexicon JSONL] file and optional
| word vectors. Will save out a valid spaCy model that you can load via
| #[+api("spacy#load") #[code spacy.load]] or package using the
| #[+api("cli#package") #[code package]] command.
+code(false, "bash", "$").
spacy vocab [lang] [output_dir] [lexemes_loc] [vectors_loc]
+table(["Argument", "Type", "Description"])
+row
+cell #[code lang]
+cell positional
+cell
| Model language
| #[+a("https://en.wikipedia.org/wiki/List_of_ISO_639-1_codes") ISO code],
| e.g. #[code en].
+row
+cell #[code output_dir]
+cell positional
+cell Model output directory. Will be created if it doesn't exist.
+row
+cell #[code lexemes_loc]
+cell positional
+cell
| Location of lexical data in spaCy's
| #[+a("/api/annotation#vocab-jsonl") JSONL format].
+row
+cell #[code vectors_loc]
+cell positional
+cell Optional location of vectors data as numpy #[code .npz] file.
+row("foot")
+cell creates
+cell model
+cell A spaCy model containing the vocab and vectors.
+h(3, "evaluate") Evaluate
+tag-new(2)
p
| Evaluate a model's accuracy and speed on JSON-formatted annotated data.
| Will print the results and optionally export
| #[+a("/usage/visualizers") displaCy visualizations] of a sample set of
| parses to #[code .html] files. Visualizations for the dependency parse
| and NER will be exported as separate files if the respective component
| is present in the model's pipeline.
+code(false, "bash", "$", false, false, true).
spacy evaluate [model] [data_path] [--displacy-path] [--displacy-limit] [--gpu-id] [--gold-preproc]
+table(["Argument", "Type", "Description"])
+row
+cell #[code model]
+cell positional
+cell
| Model to evaluate. Can be a package or shortcut link name, or a
| path to a model data directory.
+row
+cell #[code data_path]
+cell positional
+cell Location of JSON-formatted evaluation data.
+row
+cell #[code --displacy-path], #[code -dp]
+cell option
+cell
| Directory to output rendered parses as HTML. If not set, no
| visualizations will be generated.
+row
+cell #[code --displacy-limit], #[code -dl]
+cell option
+cell
| Number of parses to generate per file. Defaults to #[code 25].
| Keep in mind that a significantly higher number might cause the
| #[code .html] files to render slowly.
+row
+cell #[code --gpu-id], #[code -g]
+cell option
+cell GPU to use, if any. Defaults to #[code -1] for CPU.
+row
+cell #[code --gold-preproc], #[code -G]
+cell flag
+cell Use gold preprocessing.
+row("foot")
+cell prints / creates
+cell #[code stdout], HTML
+cell Training results and optional displaCy visualizations.
+h(3, "package") Package
p
| Generate a #[+a("/usage/training#models-generating") model Python package]
| from an existing model data directory. All data files are copied over.
| If the path to a #[code meta.json] is supplied, or a #[code meta.json] is
| found in the input directory, this file is used. Otherwise, the data can
| be entered directly from the command line. After packaging, you can run
| #[code python setup.py sdist] from the newly created directory to turn
| your model into an installable archive file.
+code(false, "bash", "$", false, false, true).
spacy package [input_dir] [output_dir] [--meta-path] [--create-meta] [--force]
+aside-code("Example", "bash").
spacy package /input /output
cd /output/en_model-0.0.0
python setup.py sdist
pip install dist/en_model-0.0.0.tar.gz
+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-path], #[code -m]
+cell option
+cell #[+tag-new(2)] Path to #[code meta.json] file (optional).
+row
+cell #[code --create-meta], #[code -c]
+cell flag
+cell
| #[+tag-new(2)] Create a #[code meta.json] file on the command
| line, even if one already exists in the directory. If an
| existing file is found, its entries will be shown as the defaults
| in the command line prompt.
+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.
+row("foot")
+cell creates
+cell directory
+cell A Python package containing the spaCy model.
Reference in New Issue View Git Blame Copy Permalink