mirror of https://github.com/explosion/spaCy.git
Merge branch 'master' of https://github.com/explosion/spaCy
This commit is contained in:
commit
b797dca977
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@ -97,3 +97,6 @@ Desktop.ini
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# Other
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*.tgz
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# Pycharm project files
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*.idea
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@ -29,7 +29,7 @@ def main(vectors_loc, lang=None):
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nr_row, nr_dim = header.split()
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nlp.vocab.reset_vectors(width=int(nr_dim))
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for line in file_:
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line = line.decode('utf8')
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line = line.rstrip().decode('utf8')
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pieces = line.rsplit(' ', nr_dim)
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word = pieces[0]
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vector = numpy.asarray([float(v) for v in pieces[1:]], dtype='f')
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@ -459,6 +459,8 @@ _exc = {
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"disorganised": "disorganized",
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"distil": "distill",
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"distils": "distills",
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"doin": "doing",
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"doin'": "doing",
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"dramatisation": "dramatization",
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"dramatisations": "dramatizations",
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"dramatise": "dramatize",
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@ -687,6 +689,8 @@ _exc = {
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"globalises": "globalizes",
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"globalising": "globalizing",
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"glueing ": "gluing ",
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"goin": "going",
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"goin'":"going",
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"goitre": "goiter",
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"goitres": "goiters",
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"gonorrhoea": "gonorrhea",
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@ -733,6 +737,8 @@ _exc = {
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"harmonised": "harmonized",
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"harmonises": "harmonizes",
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"harmonising": "harmonizing",
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"havin": "having",
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"havin'": "having",
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"homoeopath": "homeopath",
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"homoeopathic": "homeopathic",
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"homoeopaths": "homeopaths",
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@ -924,6 +930,8 @@ _exc = {
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"localised": "localized",
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"localises": "localizes",
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"localising": "localizing",
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"lovin": "loving",
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"lovin'": "loving",
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"louvre": "louver",
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"louvred": "louvered",
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"louvres": "louvers ",
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@ -387,6 +387,21 @@ for exc_data in [
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{ORTH: "O'clock", LEMMA: "o'clock", NORM: "o'clock"},
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{ORTH: "lovin'", LEMMA: "love", NORM: "loving"},
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{ORTH: "Lovin'", LEMMA: "love", NORM: "loving"},
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{ORTH: "lovin", LEMMA: "love", NORM: "loving"},
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{ORTH: "Lovin", LEMMA: "love", NORM: "loving"},
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{ORTH: "havin'", LEMMA: "have", NORM: "having"},
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{ORTH: "Havin'", LEMMA: "have", NORM: "having"},
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{ORTH: "havin", LEMMA: "have", NORM: "having"},
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{ORTH: "Havin", LEMMA: "have", NORM: "having"},
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{ORTH: "doin'", LEMMA: "do", NORM: "doing"},
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{ORTH: "Doin'", LEMMA: "do", NORM: "doing"},
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{ORTH: "doin", LEMMA: "do", NORM: "doing"},
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{ORTH: "Doin", LEMMA: "do", NORM: "doing"},
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{ORTH: "goin'", LEMMA: "go", NORM: "going"},
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{ORTH: "Goin'", LEMMA: "go", NORM: "going"},
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{ORTH: "goin", LEMMA: "go", NORM: "going"},
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{ORTH: "Goin", LEMMA: "go", NORM: "going"},
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{ORTH: "Mt.", LEMMA: "Mount", NORM: "Mount"},
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{ORTH: "Ak.", LEMMA: "Alaska", NORM: "Alaska"},
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@ -21,8 +21,25 @@ class JapaneseTokenizer(object):
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words = [x.surface for x in self.tokenizer.tokenize(text)]
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return Doc(self.vocab, words=words, spaces=[False]*len(words))
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# add dummy methods for to_bytes, from_bytes, to_disk and from_disk to
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# allow serialization (see #1557)
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def to_bytes(self, **exclude):
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return b''
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def from_bytes(self, bytes_data, **exclude):
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return self
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def to_disk(self, path, **exclude):
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return None
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def from_disk(self, path, **exclude):
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return self
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class JapaneseDefaults(Language.Defaults):
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lex_attr_getters = dict(Language.Defaults.lex_attr_getters)
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lex_attr_getters[LANG] = lambda text: 'ja'
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@classmethod
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def create_tokenizer(cls, nlp=None):
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return JapaneseTokenizer(cls, nlp)
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@ -257,7 +257,7 @@ p
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+row
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+cell #[code dev_data]
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+cell positional
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+cell Location of JSON-formatted dev data (optional).
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+cell Location of JSON-formatted development data for evaluation.
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+row
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+cell #[code --n-iter], #[code -n]
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@ -562,7 +562,7 @@ p
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+cell #[code orth_]
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+cell unicode
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+cell
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| Verbatim text content (identical to #[code Span.text]). Existst
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| Verbatim text content (identical to #[code Span.text]). Exists
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| mostly for consistency with the other attributes.
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+row
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