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Simplify CLI implementation for subcommands. Remove model command.

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This commit is contained in:
Matthew Honnibal 2017-05-22 04:46:45 -05:00
parent 33e2222839
commit 80e19a2399
1 changed files with 19 additions and 42 deletions
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61
spacy/__main__.py
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@ -69,29 +69,6 @@ def package(input_dir, output_dir, meta=None, force=False):
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(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(
input_file=("input file", "positional", None, str),
output_dir=("output directory for converted file", "positional", None, str),
@ -105,19 +82,6 @@ def convert(input_file, output_dir, n_sents=10, morphology=False):
"""
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)
@plac.annotations(
lang=("model language", "positional", None, str),
@ -131,13 +95,12 @@ def model(lang, model_dir, freqs_data, clusters_data=None, vectors_data=None):
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,
def train(lang, output_dir, train_data, dev_data=None, n_iter=15,
nsents=0, use_gpu=False,
no_tagger=False, no_parser=False, no_entities=False):
"""
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)
@ -146,7 +109,21 @@ def train(self, lang, output_dir, train_data, dev_data=None, n_iter=15,
if __name__ == '__main__':
import plac
import sys
if sys.argv[1] == 'train':
plac.call(train)
if sys.argv[1] == 'convert':
plac.call(convert)
commands = {
'train': train,
'convert': convert,
'download': download,
'link': link,
'info': info,
'package': package,
}
if len(sys.argv) == 1:
print("Available commands: %s" % ', '.join(sorted(commands)))
sys.exit(1)
command = sys.argv.pop(1)
sys.argv[0] = 'spacy %s' % command
if command in commands:
plac.call(commands[command])
else:
print("Unknown command: %s. Available: %s" % (command, ', '.join(commands)))
sys.exit(1)