mirror of
https://github.com/explosion/spaCy.git
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115 lines
3.4 KiB
Python
115 lines
3.4 KiB
Python
import os
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from os import path
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import codecs
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import ujson
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import re
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DATA_DIR = path.join(path.dirname(__file__), '..', 'data')
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def utf8open(loc, mode='r'):
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return codecs.open(loc, mode, 'utf8')
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def read_lang_data(name):
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data_dir = path.join(DATA_DIR, name)
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tokenization = read_tokenization(data_dir)
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prefix = read_prefix(data_dir)
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suffix = read_suffix(data_dir)
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infix = read_infix(data_dir)
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lex_loc = path.join(data_dir, 'lexemes.json')
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if path.exists(lex_loc):
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with open(lex_loc) as file_:
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lexemes = ujson.load(file_)
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else:
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lexemes = {}
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return tokenization, prefix, suffix, infix, lexemes
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def read_prefix(data_dir):
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with utf8open(path.join(data_dir, 'prefix')) as file_:
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entries = file_.read().split('\n')
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expression = '|'.join(['^' + re.escape(piece) for piece in entries if piece.strip()])
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return expression
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def read_suffix(data_dir):
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with utf8open(path.join(data_dir, 'suffix')) as file_:
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entries = file_.read().split('\n')
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expression = '|'.join([re.escape(piece) + '$' for piece in entries if piece.strip()])
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return expression
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def read_infix(data_dir):
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with utf8open(path.join(data_dir, 'infix')) as file_:
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entries = file_.read().split('\n')
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expression = '|'.join([piece for piece in entries if piece.strip()])
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return expression
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def read_tokenization(lang):
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loc = path.join(DATA_DIR, lang, 'tokenization')
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entries = []
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seen = set()
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with utf8open(loc) as file_:
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for line in file_:
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line = line.strip()
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if line.startswith('#'):
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continue
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if not line:
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continue
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pieces = line.split()
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chunk = pieces.pop(0)
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assert chunk not in seen, chunk
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seen.add(chunk)
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entries.append((chunk, list(pieces)))
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if chunk[0].isalpha() and chunk[0].islower():
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chunk = chunk[0].title() + chunk[1:]
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pieces[0] = pieces[0][0].title() + pieces[0][1:]
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seen.add(chunk)
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entries.append((chunk, pieces))
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return entries
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def read_detoken_rules(lang):
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loc = path.join(DATA_DIR, lang, 'detokenize')
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entries = []
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with utf8open(loc) as file_:
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for line in file_:
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entries.append(line.strip())
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return entries
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def align_tokens(ref, indices):
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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):
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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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