spaCy/spacy/deprecated.py

83 lines
2.8 KiB
Python

from sputnik.dir_package import DirPackage
from sputnik.package_list import (PackageNotFoundException,
CompatiblePackageNotFoundException)
import sputnik
from . import about
def get_package(data_dir):
if not isinstance(data_dir, six.string_types):
raise RuntimeError('data_dir must be a string')
return DirPackage(data_dir)
def get_package_by_name(name=None, via=None):
if name is None:
return
lang = get_lang_class(name)
try:
return sputnik.package(about.__title__, about.__version__,
name, data_path=via)
except PackageNotFoundException as e:
raise RuntimeError("Model '%s' not installed. Please run 'python -m "
"%s.download' to install latest compatible "
"model." % (name, lang.__module__))
except CompatiblePackageNotFoundException as e:
raise RuntimeError("Installed model is not compatible with spaCy "
"version. Please run 'python -m %s.download "
"--force' to install latest compatible model." %
(lang.__module__))
def read_lang_data(package):
tokenization = package.load_json(('tokenizer', 'specials.json'))
with package.open(('tokenizer', 'prefix.txt'), default=None) as file_:
prefix = read_prefix(file_) if file_ is not None else None
with package.open(('tokenizer', 'suffix.txt'), default=None) as file_:
suffix = read_suffix(file_) if file_ is not None else None
with package.open(('tokenizer', 'infix.txt'), default=None) as file_:
infix = read_infix(file_) if file_ is not None else None
return tokenization, prefix, suffix, infix
def align_tokens(ref, indices): # Deprecated, surely?
start = 0
queue = list(indices)
for token in ref:
end = start + len(token)
emit = []
while queue and queue[0][1] <= end:
emit.append(queue.pop(0))
yield token, emit
start = end
assert not queue
def detokenize(token_rules, words): # Deprecated?
"""To align with treebanks, return a list of "chunks", where a chunk is a
sequence of tokens that are separated by whitespace in actual strings. Each
chunk should be a tuple of token indices, e.g.
>>> detokenize(["ca<SEP>n't", '<SEP>!'], ["I", "ca", "n't", "!"])
[(0,), (1, 2, 3)]
"""
string = ' '.join(words)
for subtoks in token_rules:
# Algorithmically this is dumb, but writing a little list-based match
# machine? Ain't nobody got time for that.
string = string.replace(subtoks.replace('<SEP>', ' '), subtoks)
positions = []
i = 0
for chunk in string.split():
subtoks = chunk.split('<SEP>')
positions.append(tuple(range(i, i+len(subtoks))))
i += len(subtoks)
return positions