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Support zipped vector files in init-model

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This commit is contained in:
Matthew Honnibal 2018-03-27 21:01:18 +00:00
parent 270fcfd925
commit db50ac524e
1 changed files with 12 additions and 2 deletions
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14
spacy/cli/init_model.py
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@ -10,6 +10,7 @@ from pathlib import Path
from preshed.counter import PreshCounter from preshed.counter import PreshCounter
import tarfile import tarfile
import gzip import gzip
import zipfile
from ._messages import Messages from ._messages import Messages
from ..vectors import Vectors from ..vectors import Vectors
@ -54,14 +55,19 @@ def init_model(lang, output_dir, freqs_loc=None, clusters_loc=None, vectors_loc=
def open_file(loc): def open_file(loc):
'''Handle .gz, .tar.gz or unzipped files''' '''Handle .gz, .tar.gz or unzipped files'''
loc = ensure_path(loc) loc = ensure_path(loc)
print("Open loc")
if tarfile.is_tarfile(str(loc)): if tarfile.is_tarfile(str(loc)):
return tarfile.open(str(loc), 'r:gz') return tarfile.open(str(loc), 'r:gz')
elif loc.parts[-1].endswith('gz'): elif loc.parts[-1].endswith('gz'):
return (line.decode('utf8') for line in gzip.open(str(loc), 'r')) return (line.decode('utf8') for line in gzip.open(str(loc), 'r'))
elif loc.parts[-1].endswith('zip'):
zip_file = zipfile.ZipFile(str(loc))
names = zip_file.namelist()
file_ = zip_file.open(names[0])
return (line.decode('utf8') for line in file_)
else: else:
return loc.open('r', encoding='utf8') return loc.open('r', encoding='utf8')
def create_model(lang, probs, oov_prob, clusters, vectors_data, vector_keys, prune_vectors): def create_model(lang, probs, oov_prob, clusters, vectors_data, vector_keys, prune_vectors):
print("Creating model...") print("Creating model...")
lang_class = get_lang_class(lang) lang_class = get_lang_class(lang)
@ -104,8 +110,12 @@ def read_vectors(vectors_loc):
vectors_data = numpy.zeros(shape=shape, dtype='f') vectors_data = numpy.zeros(shape=shape, dtype='f')
vectors_keys = [] vectors_keys = []
for i, line in enumerate(tqdm(f)): for i, line in enumerate(tqdm(f)):
pieces = line.split() line = line.rstrip()
pieces = line.rsplit(' ', vectors_data.shape[1]+1)
word = pieces.pop(0) word = pieces.pop(0)
if len(pieces) != vectors_data.shape[1]:
print(word, repr(line))
raise ValueError("Bad line in file")
vectors_data[i] = numpy.asarray(pieces, dtype='f') vectors_data[i] = numpy.asarray(pieces, dtype='f')
vectors_keys.append(word) vectors_keys.append(word)
return vectors_data, vectors_keys return vectors_data, vectors_keys