spaCy/spacy/deprecated.py

160 lines
5.6 KiB
Python

# coding: utf8
from __future__ import unicode_literals
from pathlib import Path
from . import about
from . import util
from .cli import download
from .cli import link
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
def match_best_version(target_name, target_version, path):
path = util.ensure_path(path)
if path is None or not path.exists():
return None
matches = []
for data_name in path.iterdir():
name, version = split_data_name(data_name.parts[-1])
if name == target_name:
matches.append((tuple(float(v) for v in version.split('.')), data_name))
if matches:
return Path(max(matches)[1])
else:
return None
def split_data_name(name):
return name.split('-', 1) if '-' in name else (name, '')
def fix_glove_vectors_loading(overrides):
"""
Special-case hack for loading the GloVe vectors, to support deprecated
<1.0 stuff. Phase this out once the data is fixed.
"""
if 'data_dir' in overrides and 'path' not in overrides:
raise ValueError("The argument 'data_dir' has been renamed to 'path'")
if overrides.get('path') is False:
return overrides
if overrides.get('path') in (None, True):
data_path = util.get_data_path()
else:
path = util.ensure_path(overrides['path'])
data_path = path.parent
vec_path = None
if 'add_vectors' not in overrides:
if 'vectors' in overrides:
vec_path = match_best_version(overrides['vectors'], None, data_path)
if vec_path is None:
return overrides
else:
vec_path = match_best_version('en_glove_cc_300_1m_vectors', None, data_path)
if vec_path is not None:
vec_path = vec_path / 'vocab' / 'vec.bin'
if vec_path is not None:
overrides['add_vectors'] = lambda vocab: vocab.load_vectors_from_bin_loc(vec_path)
return overrides
def resolve_model_name(name):
"""
If spaCy is loaded with 'de', check if symlink already exists. If
not, user may have upgraded from older version and have old models installed.
Check if old model directory exists and if so, return that instead and create
shortcut link. If English model is found and no shortcut exists, raise error
and tell user to install new model.
"""
if name == 'en' or name == 'de':
versions = ['1.0.0', '1.1.0']
data_path = Path(util.get_data_path())
model_path = data_path / name
v_model_paths = [data_path / Path(name + '-' + v) for v in versions]
if not model_path.exists(): # no shortcut found
for v_path in v_model_paths:
if v_path.exists(): # versioned model directory found
if name == 'de':
link(v_path, name)
return name
else:
raise ValueError(
"Found English model at {p}. This model is not "
"compatible with the current version. See "
"https://spacy.io/docs/usage/models to download the "
"new model.".format(p=v_path))
return name
class ModelDownload():
"""
Replace download modules within en and de with deprecation warning and
download default language model (using shortcut). Use classmethods to allow
importing ModelDownload as download and calling download.en() etc.
"""
@classmethod
def load(self, lang):
util.print_msg(
"The spacy.{l}.download command is now deprecated. Please use "
"python -m spacy download [model name or shortcut] instead. For more "
"info and available models, see the documentation: {d}. "
"Downloading default '{l}' model now...".format(d=about.__docs_models__, l=lang),
title="Warning: deprecated command")
download(lang)
@classmethod
def en(cls, *args, **kwargs):
cls.load('en')
@classmethod
def de(cls, *args, **kwargs):
cls.load('de')