mirror of https://github.com/explosion/spaCy.git
111 lines
3.8 KiB
Python
111 lines
3.8 KiB
Python
from pathlib import Path
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from . import about
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from . import util
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from .download import download
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try:
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basestring
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except NameError:
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basestring = str
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def read_lang_data(package):
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tokenization = package.load_json(('tokenizer', 'specials.json'))
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with package.open(('tokenizer', 'prefix.txt'), default=None) as file_:
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prefix = read_prefix(file_) if file_ is not None else None
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with package.open(('tokenizer', 'suffix.txt'), default=None) as file_:
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suffix = read_suffix(file_) if file_ is not None else None
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with package.open(('tokenizer', 'infix.txt'), default=None) as file_:
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infix = read_infix(file_) if file_ is not None else None
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return tokenization, prefix, suffix, infix
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def align_tokens(ref, indices): # Deprecated, surely?
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start = 0
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queue = list(indices)
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for token in ref:
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end = start + len(token)
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emit = []
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while queue and queue[0][1] <= end:
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emit.append(queue.pop(0))
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yield token, emit
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start = end
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assert not queue
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def detokenize(token_rules, words): # Deprecated?
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"""To align with treebanks, return a list of "chunks", where a chunk is a
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sequence of tokens that are separated by whitespace in actual strings. Each
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chunk should be a tuple of token indices, e.g.
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>>> detokenize(["ca<SEP>n't", '<SEP>!'], ["I", "ca", "n't", "!"])
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[(0,), (1, 2, 3)]
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"""
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string = ' '.join(words)
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for subtoks in token_rules:
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# Algorithmically this is dumb, but writing a little list-based match
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# machine? Ain't nobody got time for that.
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string = string.replace(subtoks.replace('<SEP>', ' '), subtoks)
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positions = []
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i = 0
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for chunk in string.split():
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subtoks = chunk.split('<SEP>')
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positions.append(tuple(range(i, i+len(subtoks))))
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i += len(subtoks)
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return positions
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def fix_glove_vectors_loading(overrides):
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"""Special-case hack for loading the GloVe vectors, to support deprecated
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<1.0 stuff. Phase this out once the data is fixed."""
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if 'data_dir' in overrides and 'path' not in overrides:
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raise ValueError("The argument 'data_dir' has been renamed to 'path'")
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if overrides.get('path') is False:
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return overrides
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if overrides.get('path') in (None, True):
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data_path = util.get_data_path()
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else:
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path = overrides['path']
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if isinstance(path, basestring):
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path = Path(path)
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data_path = path.parent
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vec_path = None
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if 'add_vectors' not in overrides:
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if 'vectors' in overrides:
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vec_path = util.match_best_version(overrides['vectors'], None, data_path)
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if vec_path is None:
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return overrides
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else:
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vec_path = util.match_best_version('en_glove_cc_300_1m_vectors', None, data_path)
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if vec_path is not None:
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vec_path = vec_path / 'vocab' / 'vec.bin'
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if vec_path is not None:
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overrides['add_vectors'] = lambda vocab: vocab.load_vectors_from_bin_loc(vec_path)
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return overrides
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class ModelDownload():
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"""Replace download modules within en and de with deprecation warning and
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download default language model (using shortcut). Use classmethods to allow
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importing ModelDownload as download and calling download.en() etc."""
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@classmethod
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def load(self, lang):
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util.print_msg(
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"The spacy.{l}.download command is now deprecated. Please use "
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"spacy.download [model name or shortcut] instead. For more "
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"info and available models, see the documentation: {d}. "
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"Downloading default '{l}' model now...".format(d=about.__docs__, l=lang),
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title="Warning: deprecated command")
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download(lang)
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@classmethod
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def en(cls, *args, **kwargs):
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cls.load('en')
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@classmethod
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def de(cls, *args, **kwargs):
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cls.load('de')
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