mirror of
https://github.com/explosion/spaCy.git
synced 2024-12-24 17:06:29 +03:00
Refactor CLI
This commit is contained in:
Matthew Honnibal
parent
cc569a348d
commit
7811d97339
|
|
@ -13,122 +13,112 @@ from spacy.cli import model as cli_model
|
|||
from spacy.cli import convert as cli_convert
|
||||
|
||||
|
||||
class CLI(object):
|
||||
@plac.annotations(
|
||||
model=("model to download (shortcut or model name)", "positional", None, str),
|
||||
direct=("force direct download. Needs model name with version and won't "
|
||||
"perform compatibility check", "flag", "d", bool)
|
||||
)
|
||||
def download(model, direct=False):
|
||||
"""
|
||||
Command-line interface for spaCy
|
||||
Download compatible model from default download path using pip. Model
|
||||
can be shortcut, model name or, if --direct flag is set, full model name
|
||||
with version.
|
||||
"""
|
||||
commands = ('download', 'link', 'info', 'package', 'train', 'model', 'convert')
|
||||
|
||||
@plac.annotations(
|
||||
model=("model to download (shortcut or model name)", "positional", None, str),
|
||||
direct=("force direct download. Needs model name with version and won't "
|
||||
"perform compatibility check", "flag", "d", bool)
|
||||
)
|
||||
def download(self, model, direct=False):
|
||||
"""
|
||||
Download compatible model from default download path using pip. Model
|
||||
can be shortcut, model name or, if --direct flag is set, full model name
|
||||
with version.
|
||||
"""
|
||||
cli_download(model, direct)
|
||||
cli_download(model, direct)
|
||||
|
||||
|
||||
@plac.annotations(
|
||||
origin=("package name or local path to model", "positional", None, str),
|
||||
link_name=("name of shortuct link to create", "positional", None, str),
|
||||
force=("force overwriting of existing link", "flag", "f", bool)
|
||||
)
|
||||
def link(self, origin, link_name, force=False):
|
||||
"""
|
||||
Create a symlink for models within the spacy/data directory. Accepts
|
||||
either the name of a pip package, or the local path to the model data
|
||||
directory. Linking models allows loading them via spacy.load(link_name).
|
||||
"""
|
||||
cli_link(origin, link_name, force)
|
||||
@plac.annotations(
|
||||
origin=("package name or local path to model", "positional", None, str),
|
||||
link_name=("name of shortuct link to create", "positional", None, str),
|
||||
force=("force overwriting of existing link", "flag", "f", bool)
|
||||
)
|
||||
def link(origin, link_name, force=False):
|
||||
"""
|
||||
Create a symlink for models within the spacy/data directory. Accepts
|
||||
either the name of a pip package, or the local path to the model data
|
||||
directory. Linking models allows loading them via spacy.load(link_name).
|
||||
"""
|
||||
cli_link(origin, link_name, force)
|
||||
|
||||
|
||||
@plac.annotations(
|
||||
model=("optional: shortcut link of model", "positional", None, str),
|
||||
markdown=("generate Markdown for GitHub issues", "flag", "md", str)
|
||||
)
|
||||
def info(self, model=None, markdown=False):
|
||||
"""
|
||||
Print info about spaCy installation. If a model shortcut link is
|
||||
speficied as an argument, print model information. Flag --markdown
|
||||
prints details in Markdown for easy copy-pasting to GitHub issues.
|
||||
"""
|
||||
cli_info(model, markdown)
|
||||
@plac.annotations(
|
||||
model=("optional: shortcut link of model", "positional", None, str),
|
||||
markdown=("generate Markdown for GitHub issues", "flag", "md", str)
|
||||
)
|
||||
def info(model=None, markdown=False):
|
||||
"""
|
||||
Print info about spaCy installation. If a model shortcut link is
|
||||
speficied as an argument, print model information. Flag --markdown
|
||||
prints details in Markdown for easy copy-pasting to GitHub issues.
|
||||
"""
|
||||
cli_info(model, markdown)
|
||||
|
||||
|
||||
@plac.annotations(
|
||||
input_dir=("directory with model data", "positional", None, str),
|
||||
output_dir=("output parent directory", "positional", None, str),
|
||||
meta=("path to meta.json", "option", "m", str),
|
||||
force=("force overwriting of existing folder in output directory", "flag", "f", bool)
|
||||
)
|
||||
def package(self, input_dir, output_dir, meta=None, force=False):
|
||||
"""
|
||||
Generate Python package for model data, including meta and required
|
||||
installation files. A new directory will be created in the specified
|
||||
output directory, and model data will be copied over.
|
||||
"""
|
||||
cli_package(input_dir, output_dir, meta, force)
|
||||
@plac.annotations(
|
||||
input_dir=("directory with model data", "positional", None, str),
|
||||
output_dir=("output parent directory", "positional", None, str),
|
||||
meta=("path to meta.json", "option", "m", str),
|
||||
force=("force overwriting of existing folder in output directory", "flag", "f", bool)
|
||||
)
|
||||
def package(input_dir, output_dir, meta=None, force=False):
|
||||
"""
|
||||
Generate Python package for model data, including meta and required
|
||||
installation files. A new directory will be created in the specified
|
||||
output directory, and model data will be copied over.
|
||||
"""
|
||||
cli_package(input_dir, output_dir, meta, force)
|
||||
|
||||
|
||||
@plac.annotations(
|
||||
lang=("model language", "positional", None, str),
|
||||
output_dir=("output directory to store model in", "positional", None, str),
|
||||
train_data=("location of JSON-formatted training data", "positional", None, str),
|
||||
dev_data=("location of JSON-formatted development data (optional)", "positional", None, str),
|
||||
n_iter=("number of iterations", "option", "n", int),
|
||||
nsents=("number of sentences", "option", None, int),
|
||||
parser_L1=("L1 regularization penalty for parser", "option", "L", float),
|
||||
use_gpu=("Use GPU", "flag", "g", bool),
|
||||
no_tagger=("Don't train tagger", "flag", "T", bool),
|
||||
no_parser=("Don't train parser", "flag", "P", bool),
|
||||
no_entities=("Don't train NER", "flag", "N", bool)
|
||||
)
|
||||
def train(self, lang, output_dir, train_data, dev_data=None, n_iter=15,
|
||||
nsents=0, parser_L1=0.0, use_gpu=False,
|
||||
no_tagger=False, no_parser=False, no_entities=False):
|
||||
"""
|
||||
Train a model. Expects data in spaCy's JSON format.
|
||||
"""
|
||||
nsents = nsents or None
|
||||
cli_train(lang, output_dir, train_data, dev_data, n_iter, nsents,
|
||||
use_gpu, no_tagger, no_parser, no_entities, parser_L1)
|
||||
@plac.annotations(
|
||||
lang=("model language", "positional", None, str),
|
||||
output_dir=("output directory to store model in", "positional", None, str),
|
||||
train_data=("location of JSON-formatted training data", "positional", None, str),
|
||||
dev_data=("location of JSON-formatted development data (optional)", "positional", None, str),
|
||||
n_iter=("number of iterations", "option", "n", int),
|
||||
nsents=("number of sentences", "option", None, int),
|
||||
parser_L1=("L1 regularization penalty for parser", "option", "L", float),
|
||||
use_gpu=("Use GPU", "flag", "g", bool),
|
||||
no_tagger=("Don't train tagger", "flag", "T", bool),
|
||||
no_parser=("Don't train parser", "flag", "P", bool),
|
||||
no_entities=("Don't train NER", "flag", "N", bool)
|
||||
)
|
||||
def train(lang, output_dir, train_data, dev_data=None, n_iter=15,
|
||||
nsents=0, parser_L1=0.0, use_gpu=False,
|
||||
no_tagger=False, no_parser=False, no_entities=False):
|
||||
"""
|
||||
Train a model. Expects data in spaCy's JSON format.
|
||||
"""
|
||||
nsents = nsents or None
|
||||
cli_train(lang, output_dir, train_data, dev_data, n_iter, nsents,
|
||||
use_gpu, no_tagger, no_parser, no_entities, parser_L1)
|
||||
|
||||
@plac.annotations(
|
||||
lang=("model language", "positional", None, str),
|
||||
model_dir=("output directory to store model in", "positional", None, str),
|
||||
freqs_data=("tab-separated frequencies file", "positional", None, str),
|
||||
clusters_data=("Brown clusters file", "positional", None, str),
|
||||
vectors_data=("word vectors file", "positional", None, str)
|
||||
)
|
||||
def model(self, lang, model_dir, freqs_data, clusters_data=None, vectors_data=None):
|
||||
"""
|
||||
Initialize a new model and its data directory.
|
||||
"""
|
||||
cli_model(lang, model_dir, freqs_data, clusters_data, vectors_data)
|
||||
@plac.annotations(
|
||||
input_file=("input file", "positional", None, str),
|
||||
output_dir=("output directory for converted file", "positional", None, str),
|
||||
n_sents=("Number of sentences per doc", "option", "n", float),
|
||||
morphology=("Enable appending morphology to tags", "flag", "m", bool)
|
||||
)
|
||||
def convert(input_file, output_dir, n_sents=10, morphology=False):
|
||||
"""
|
||||
Convert files into JSON format for use with train command and other
|
||||
experiment management functions.
|
||||
"""
|
||||
cli_convert(input_file, output_dir, n_sents, morphology)
|
||||
|
||||
@plac.annotations(
|
||||
input_file=("input file", "positional", None, str),
|
||||
output_dir=("output directory for converted file", "positional", None, str),
|
||||
n_sents=("Number of sentences per doc", "option", "n", float),
|
||||
morphology=("Enable appending morphology to tags", "flag", "m", bool)
|
||||
)
|
||||
def convert(self, input_file, output_dir, n_sents=10, morphology=False):
|
||||
"""
|
||||
Convert files into JSON format for use with train command and other
|
||||
experiment management functions.
|
||||
"""
|
||||
cli_convert(input_file, output_dir, n_sents, morphology)
|
||||
@plac.annotations(
|
||||
lang=("model language", "positional", None, str),
|
||||
model_dir=("output directory to store model in", "positional", None, str),
|
||||
freqs_data=("tab-separated frequencies file", "positional", None, str),
|
||||
clusters_data=("Brown clusters file", "positional", None, str),
|
||||
vectors_data=("word vectors file", "positional", None, str)
|
||||
)
|
||||
def model(lang, model_dir, freqs_data, clusters_data=None, vectors_data=None):
|
||||
"""
|
||||
Initialize a new model and its data directory.
|
||||
"""
|
||||
cli_model(lang, model_dir, freqs_data, clusters_data, vectors_data)
|
||||
|
||||
|
||||
def __missing__(self, name):
|
||||
print("\n Command %r does not exist."
|
||||
"\n Use the --help flag for a list of available commands.\n" % name)
|
||||
|
||||
@plac.annotations(
|
||||
lang=("model language", "positional", None, str),
|
||||
output_dir=("output directory to store model in", "positional", None, str),
|
||||
|
|
@ -147,6 +137,7 @@ def train(self, lang, output_dir, train_data, dev_data=None, n_iter=15,
|
|||
"""
|
||||
Train a model. Expects data in spaCy's JSON format.
|
||||
"""
|
||||
print(train_data, dev_data)
|
||||
nsents = nsents or None
|
||||
cli_train(lang, output_dir, train_data, dev_data, n_iter, nsents,
|
||||
use_gpu, no_tagger, no_parser, no_entities)
|
||||
|
|
@ -157,3 +148,5 @@ if __name__ == '__main__':
|
|||
import sys
|
||||
if sys.argv[1] == 'train':
|
||||
plac.call(train)
|
||||
if sys.argv[1] == 'convert':
|
||||
plac.call(convert)
|
||||
|
|
|
|||
Loading…
Reference in New Issue
Block a user