mirror of https://github.com/explosion/spaCy.git
610 lines
23 KiB
Cython
610 lines
23 KiB
Cython
from __future__ import unicode_literals
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from libc.stdio cimport fopen, fclose, fread, fwrite, FILE
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from libc.string cimport memset
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from libc.stdint cimport int32_t
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from libc.stdint cimport uint64_t
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from libc.math cimport sqrt
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import bz2
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from os import path
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import io
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import math
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import ujson as json
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import tempfile
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from .lexeme cimport EMPTY_LEXEME
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from .lexeme cimport Lexeme
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from .strings cimport hash_string
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from .orth cimport word_shape
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from .typedefs cimport attr_t
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from .cfile cimport CFile
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from .lemmatizer import Lemmatizer
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from . import attrs
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from . import symbols
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from cymem.cymem cimport Address
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from .serialize.packer cimport Packer
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from .attrs cimport PROB, LANG
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from . import deprecated
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from . import util
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try:
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import copy_reg
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except ImportError:
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import copyreg as copy_reg
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DEF MAX_VEC_SIZE = 100000
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cdef float[MAX_VEC_SIZE] EMPTY_VEC
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memset(EMPTY_VEC, 0, sizeof(EMPTY_VEC))
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memset(&EMPTY_LEXEME, 0, sizeof(LexemeC))
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EMPTY_LEXEME.vector = EMPTY_VEC
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cdef class Vocab:
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'''A map container for a language's LexemeC structs.
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'''
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@classmethod
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def load(cls, path, lex_attr_getters=None, lemmatizer=True,
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tag_map=True, serializer_freqs=True, oov_prob=True, **deprecated_kwargs):
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"""
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Load the vocabulary from a path.
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Arguments:
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path (Path):
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The path to load from.
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lex_attr_getters (dict):
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A dictionary mapping attribute IDs to functions to compute them.
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Defaults to None.
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lemmatizer (object):
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A lemmatizer. Defaults to None.
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tag_map (dict):
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A dictionary mapping fine-grained tags to coarse-grained parts-of-speech,
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and optionally morphological attributes.
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oov_prob (float):
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The default probability for out-of-vocabulary words.
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Returns:
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Vocab: The newly constructed vocab object.
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"""
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util.check_renamed_kwargs({'get_lex_attr': 'lex_attr_getters'}, deprecated_kwargs)
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if 'vectors' in deprecated_kwargs:
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raise AttributeError(
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"vectors argument to Vocab.load() deprecated. "
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"Install vectors after loading.")
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if tag_map is True and (path / 'vocab' / 'tag_map.json').exists():
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with (path / 'vocab' / 'tag_map.json').open('r', encoding='utf8') as file_:
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tag_map = json.load(file_)
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if lex_attr_getters is not None \
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and oov_prob is True \
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and (path / 'vocab' / 'oov_prob').exists():
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with (path / 'vocab' / 'oov_prob').open('r', encoding='utf8') as file_:
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oov_prob = float(file_.read())
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lex_attr_getters[PROB] = lambda text: oov_prob
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if lemmatizer is True:
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lemmatizer = Lemmatizer.load(path)
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if serializer_freqs is True and (path / 'vocab' / 'serializer.json').exists():
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with (path / 'vocab' / 'serializer.json').open('r', encoding='utf8') as file_:
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serializer_freqs = json.load(file_)
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cdef Vocab self = cls(lex_attr_getters=lex_attr_getters, tag_map=tag_map,
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lemmatizer=lemmatizer, serializer_freqs=serializer_freqs)
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with (path / 'vocab' / 'strings.json').open('r', encoding='utf8') as file_:
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self.strings.load(file_)
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self.load_lexemes(path / 'vocab' / 'lexemes.bin')
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return self
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def __init__(self, lex_attr_getters=None, tag_map=None, lemmatizer=None,
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serializer_freqs=None, **deprecated_kwargs):
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'''Create the vocabulary.
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lex_attr_getters (dict):
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A dictionary mapping attribute IDs to functions to compute them.
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Defaults to None.
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lemmatizer (object):
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A lemmatizer. Defaults to None.
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tag_map (dict):
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A dictionary mapping fine-grained tags to coarse-grained parts-of-speech,
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and optionally morphological attributes.
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oov_prob (float):
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The default probability for out-of-vocabulary words.
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Returns:
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Vocab: The newly constructed vocab object.
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'''
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util.check_renamed_kwargs({'get_lex_attr': 'lex_attr_getters'}, deprecated_kwargs)
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lex_attr_getters = lex_attr_getters if lex_attr_getters is not None else {}
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tag_map = tag_map if tag_map is not None else {}
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if lemmatizer in (None, True, False):
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lemmatizer = Lemmatizer({}, {}, {})
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serializer_freqs = serializer_freqs if serializer_freqs is not None else {}
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self.mem = Pool()
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self._by_hash = PreshMap()
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self._by_orth = PreshMap()
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self.strings = StringStore()
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# Load strings in a special order, so that we have an onset number for
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# the vocabulary. This way, when words are added in order, the orth ID
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# is the frequency rank of the word, plus a certain offset. The structural
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# strings are loaded first, because the vocab is open-class, and these
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# symbols are closed class.
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# TODO: Actually this has turned out to be a pain in the ass...
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# It means the data is invalidated when we add a symbol :(
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# Need to rethink this.
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for name in symbols.NAMES + list(sorted(tag_map.keys())):
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if name:
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_ = self.strings[name]
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self.lex_attr_getters = lex_attr_getters
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self.morphology = Morphology(self.strings, tag_map, lemmatizer)
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self.serializer_freqs = serializer_freqs
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self.length = 1
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self._serializer = None
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property serializer:
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# Having the serializer live here is super messy :(
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def __get__(self):
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if self._serializer is None:
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self._serializer = Packer(self, self.serializer_freqs)
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return self._serializer
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property lang:
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def __get__(self):
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langfunc = None
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if self.lex_attr_getters:
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langfunc = self.lex_attr_getters.get(LANG, None)
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return langfunc('_') if langfunc else ''
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def __len__(self):
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"""The current number of lexemes stored."""
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return self.length
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def resize_vectors(self, int new_size):
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'''
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Set vectors_length to a new size, and allocate more memory for the Lexeme
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vectors if necessary. The memory will be zeroed.
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Arguments:
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new_size (int): The new size of the vectors.
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'''
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cdef hash_t key
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cdef size_t addr
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if new_size > self.vectors_length:
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for key, addr in self._by_hash.items():
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lex = <LexemeC*>addr
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lex.vector = <float*>self.mem.realloc(lex.vector,
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new_size * sizeof(lex.vector[0]))
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self.vectors_length = new_size
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def add_flag(self, flag_getter, int flag_id=-1):
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'''Set a new boolean flag to words in the vocabulary.
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The flag_setter function will be called over the words currently in the
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vocab, and then applied to new words as they occur. You'll then be able
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to access the flag value on each token, using token.check_flag(flag_id).
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See also:
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Lexeme.set_flag, Lexeme.check_flag, Token.set_flag, Token.check_flag.
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Arguments:
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flag_getter:
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A function f(unicode) -> bool, to get the flag value.
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flag_id (int):
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An integer between 1 and 63 (inclusive), specifying the bit at which the
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flag will be stored. If -1, the lowest available bit will be
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chosen.
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Returns:
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flag_id (int): The integer ID by which the flag value can be checked.
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'''
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if flag_id == -1:
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for bit in range(1, 64):
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if bit not in self.lex_attr_getters:
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flag_id = bit
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break
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else:
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raise ValueError(
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"Cannot find empty bit for new lexical flag. All bits between "
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"0 and 63 are occupied. You can replace one by specifying the "
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"flag_id explicitly, e.g. nlp.vocab.add_flag(your_func, flag_id=IS_ALPHA")
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elif flag_id >= 64 or flag_id < 1:
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raise ValueError(
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"Invalid value for flag_id: %d. Flag IDs must be between "
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"1 and 63 (inclusive)" % flag_id)
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for lex in self:
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lex.set_flag(flag_id, flag_getter(lex.orth_))
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self.lex_attr_getters[flag_id] = flag_getter
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return flag_id
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cdef const LexemeC* get(self, Pool mem, unicode string) except NULL:
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'''Get a pointer to a LexemeC from the lexicon, creating a new Lexeme
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if necessary, using memory acquired from the given pool. If the pool
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is the lexicon's own memory, the lexeme is saved in the lexicon.'''
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if string == u'':
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return &EMPTY_LEXEME
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cdef LexemeC* lex
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cdef hash_t key = hash_string(string)
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lex = <LexemeC*>self._by_hash.get(key)
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cdef size_t addr
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if lex != NULL:
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if lex.orth != self.strings[string]:
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raise LookupError.mismatched_strings(
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lex.orth, self.strings[string], self.strings[lex.orth], string)
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return lex
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else:
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return self._new_lexeme(mem, string)
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cdef const LexemeC* get_by_orth(self, Pool mem, attr_t orth) except NULL:
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'''Get a pointer to a LexemeC from the lexicon, creating a new Lexeme
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if necessary, using memory acquired from the given pool. If the pool
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is the lexicon's own memory, the lexeme is saved in the lexicon.'''
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if orth == 0:
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return &EMPTY_LEXEME
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cdef LexemeC* lex
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lex = <LexemeC*>self._by_orth.get(orth)
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if lex != NULL:
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return lex
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else:
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return self._new_lexeme(mem, self.strings[orth])
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cdef const LexemeC* _new_lexeme(self, Pool mem, unicode string) except NULL:
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cdef hash_t key
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cdef bint is_oov = mem is not self.mem
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if len(string) < 3:
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mem = self.mem
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lex = <LexemeC*>mem.alloc(sizeof(LexemeC), 1)
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lex.orth = self.strings[string]
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lex.length = len(string)
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lex.id = self.length
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lex.vector = <float*>mem.alloc(self.vectors_length, sizeof(float))
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if self.lex_attr_getters is not None:
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for attr, func in self.lex_attr_getters.items():
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value = func(string)
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if isinstance(value, unicode):
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value = self.strings[value]
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if attr == PROB:
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lex.prob = value
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elif value is not None:
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Lexeme.set_struct_attr(lex, attr, value)
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if is_oov:
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lex.id = 0
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else:
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key = hash_string(string)
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self._add_lex_to_vocab(key, lex)
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assert lex != NULL, string
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return lex
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cdef int _add_lex_to_vocab(self, hash_t key, const LexemeC* lex) except -1:
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self._by_hash.set(key, <void*>lex)
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self._by_orth.set(lex.orth, <void*>lex)
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self.length += 1
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def __contains__(self, unicode string):
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'''Check whether the string has an entry in the vocabulary.
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Arguments:
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string (unicode): The ID string.
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Returns:
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bool Whether the string has an entry in the vocabulary.
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'''
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key = hash_string(string)
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lex = self._by_hash.get(key)
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return True if lex is not NULL else False
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def __iter__(self):
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'''Iterate over the lexemes in the vocabulary.
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Yields: Lexeme An entry in the vocabulary.
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'''
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cdef attr_t orth
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cdef size_t addr
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for orth, addr in self._by_orth.items():
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yield Lexeme(self, orth)
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def __getitem__(self, id_or_string):
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'''Retrieve a lexeme, given an int ID or a unicode string. If a previously
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unseen unicode string is given, a new lexeme is created and stored.
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Arguments:
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id_or_string (int or unicode):
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The integer ID of a word, or its unicode string.
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If an int >= Lexicon.size, IndexError is raised. If id_or_string
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is neither an int nor a unicode string, ValueError is raised.
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Returns:
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lexeme (Lexeme): The lexeme indicated by the given ID.
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'''
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cdef attr_t orth
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if type(id_or_string) == unicode:
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orth = self.strings[id_or_string]
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else:
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orth = id_or_string
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return Lexeme(self, orth)
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cdef const TokenC* make_fused_token(self, substrings) except NULL:
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cdef int i
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tokens = <TokenC*>self.mem.alloc(len(substrings) + 1, sizeof(TokenC))
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for i, props in enumerate(substrings):
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token = &tokens[i]
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# Set the special tokens up to have morphology and lemmas if
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# specified, otherwise use the part-of-speech tag (if specified)
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token.lex = <LexemeC*>self.get(self.mem, props['F'])
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if 'pos' in props:
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self.morphology.assign_tag(token, props['pos'])
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if 'L' in props:
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tokens[i].lemma = self.strings[props['L']]
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for feature, value in props.get('morph', {}).items():
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self.morphology.assign_feature(&token.morph, feature, value)
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return tokens
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def dump(self, loc):
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"""Save the lexemes binary data to the given location.
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Arguments:
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loc (Path): The path to save to.
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"""
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if hasattr(loc, 'as_posix'):
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loc = loc.as_posix()
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cdef bytes bytes_loc = loc.encode('utf8') if type(loc) == unicode else loc
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cdef CFile fp = CFile(bytes_loc, 'wb')
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cdef size_t st
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cdef size_t addr
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cdef hash_t key
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for key, addr in self._by_hash.items():
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lexeme = <LexemeC*>addr
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fp.write_from(&lexeme.orth, sizeof(lexeme.orth), 1)
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fp.write_from(&lexeme.flags, sizeof(lexeme.flags), 1)
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fp.write_from(&lexeme.id, sizeof(lexeme.id), 1)
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fp.write_from(&lexeme.length, sizeof(lexeme.length), 1)
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fp.write_from(&lexeme.orth, sizeof(lexeme.orth), 1)
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fp.write_from(&lexeme.lower, sizeof(lexeme.lower), 1)
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fp.write_from(&lexeme.norm, sizeof(lexeme.norm), 1)
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fp.write_from(&lexeme.shape, sizeof(lexeme.shape), 1)
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fp.write_from(&lexeme.prefix, sizeof(lexeme.prefix), 1)
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fp.write_from(&lexeme.suffix, sizeof(lexeme.suffix), 1)
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fp.write_from(&lexeme.cluster, sizeof(lexeme.cluster), 1)
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fp.write_from(&lexeme.prob, sizeof(lexeme.prob), 1)
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fp.write_from(&lexeme.sentiment, sizeof(lexeme.sentiment), 1)
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fp.write_from(&lexeme.l2_norm, sizeof(lexeme.l2_norm), 1)
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fp.write_from(&lexeme.lang, sizeof(lexeme.lang), 1)
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fp.close()
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def load_lexemes(self, loc):
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'''Load the binary vocabulary data from the given location.
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Arguments:
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loc (Path): The path to load from.
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Returns:
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None
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'''
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fp = CFile(loc, 'rb',
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on_open_error=lambda: IOError('LexemeCs file not found at %s' % loc))
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cdef LexemeC* lexeme
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cdef hash_t key
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cdef unicode py_str
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cdef attr_t orth
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assert sizeof(orth) == sizeof(lexeme.orth)
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i = 0
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while True:
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try:
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fp.read_into(&orth, 1, sizeof(orth))
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except IOError:
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break
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lexeme = <LexemeC*>self.mem.alloc(sizeof(LexemeC), 1)
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# Copy data from the file into the lexeme
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fp.read_into(&lexeme.flags, 1, sizeof(lexeme.flags))
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fp.read_into(&lexeme.id, 1, sizeof(lexeme.id))
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fp.read_into(&lexeme.length, 1, sizeof(lexeme.length))
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fp.read_into(&lexeme.orth, 1, sizeof(lexeme.orth))
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fp.read_into(&lexeme.lower, 1, sizeof(lexeme.lower))
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fp.read_into(&lexeme.norm, 1, sizeof(lexeme.norm))
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fp.read_into(&lexeme.shape, 1, sizeof(lexeme.shape))
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fp.read_into(&lexeme.prefix, 1, sizeof(lexeme.prefix))
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fp.read_into(&lexeme.suffix, 1, sizeof(lexeme.suffix))
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fp.read_into(&lexeme.cluster, 1, sizeof(lexeme.cluster))
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fp.read_into(&lexeme.prob, 1, sizeof(lexeme.prob))
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fp.read_into(&lexeme.sentiment, 1, sizeof(lexeme.sentiment))
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fp.read_into(&lexeme.l2_norm, 1, sizeof(lexeme.l2_norm))
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fp.read_into(&lexeme.lang, 1, sizeof(lexeme.lang))
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lexeme.vector = EMPTY_VEC
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py_str = self.strings[lexeme.orth]
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key = hash_string(py_str)
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self._by_hash.set(key, lexeme)
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self._by_orth.set(lexeme.orth, lexeme)
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self.length += 1
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i += 1
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fp.close()
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def dump_vectors(self, out_loc):
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'''Save the word vectors to a binary file.
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Arguments:
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loc (Path): The path to save to.
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Returns:
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None
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'''
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cdef int32_t vec_len = self.vectors_length
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cdef int32_t word_len
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cdef bytes word_str
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cdef char* chars
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cdef Lexeme lexeme
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cdef CFile out_file = CFile(out_loc, 'wb')
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for lexeme in self:
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word_str = lexeme.orth_.encode('utf8')
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vec = lexeme.c.vector
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word_len = len(word_str)
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out_file.write_from(&word_len, 1, sizeof(word_len))
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out_file.write_from(&vec_len, 1, sizeof(vec_len))
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chars = <char*>word_str
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out_file.write_from(chars, word_len, sizeof(char))
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out_file.write_from(vec, vec_len, sizeof(float))
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out_file.close()
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def load_vectors(self, file_):
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"""Load vectors from a text-based file.
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Arguments:
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file_ (buffer): The file to read from. Entries should be separated by newlines,
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and each entry should be whitespace delimited. The first value of the entry
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should be the word string, and subsequent entries should be the values of the
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vector.
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Returns:
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vec_len (int): The length of the vectors loaded.
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"""
|
|
cdef LexemeC* lexeme
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|
cdef attr_t orth
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|
cdef int32_t vec_len = -1
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|
cdef double norm = 0.0
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|
for line_num, line in enumerate(file_):
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|
pieces = line.split()
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|
word_str = pieces.pop(0)
|
|
if vec_len == -1:
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|
vec_len = len(pieces)
|
|
elif vec_len != len(pieces):
|
|
raise VectorReadError.mismatched_sizes(file_, line_num,
|
|
vec_len, len(pieces))
|
|
orth = self.strings[word_str]
|
|
lexeme = <LexemeC*><void*>self.get_by_orth(self.mem, orth)
|
|
lexeme.vector = <float*>self.mem.alloc(vec_len, sizeof(float))
|
|
for i, val_str in enumerate(pieces):
|
|
lexeme.vector[i] = float(val_str)
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|
norm = 0.0
|
|
for i in range(vec_len):
|
|
norm += lexeme.vector[i] * lexeme.vector[i]
|
|
lexeme.l2_norm = sqrt(norm)
|
|
self.vectors_length = vec_len
|
|
return vec_len
|
|
|
|
def load_vectors_from_bin_loc(self, loc):
|
|
"""Load vectors from the location of a binary file.
|
|
|
|
Arguments:
|
|
loc (unicode): The path of the binary file to load from.
|
|
|
|
Returns:
|
|
vec_len (int): The length of the vectors loaded.
|
|
"""
|
|
cdef CFile file_ = CFile(loc, b'rb')
|
|
cdef int32_t word_len
|
|
cdef int32_t vec_len = 0
|
|
cdef int32_t prev_vec_len = 0
|
|
cdef float* vec
|
|
cdef Address mem
|
|
cdef attr_t string_id
|
|
cdef bytes py_word
|
|
cdef vector[float*] vectors
|
|
cdef int line_num = 0
|
|
cdef Pool tmp_mem = Pool()
|
|
while True:
|
|
try:
|
|
file_.read_into(&word_len, sizeof(word_len), 1)
|
|
except IOError:
|
|
break
|
|
file_.read_into(&vec_len, sizeof(vec_len), 1)
|
|
if prev_vec_len != 0 and vec_len != prev_vec_len:
|
|
raise VectorReadError.mismatched_sizes(loc, line_num,
|
|
vec_len, prev_vec_len)
|
|
if 0 >= vec_len >= MAX_VEC_SIZE:
|
|
raise VectorReadError.bad_size(loc, vec_len)
|
|
|
|
chars = <char*>file_.alloc_read(tmp_mem, word_len, sizeof(char))
|
|
vec = <float*>file_.alloc_read(self.mem, vec_len, sizeof(float))
|
|
|
|
string_id = self.strings[chars[:word_len]]
|
|
while string_id >= vectors.size():
|
|
vectors.push_back(EMPTY_VEC)
|
|
assert vec != NULL
|
|
vectors[string_id] = vec
|
|
line_num += 1
|
|
cdef LexemeC* lex
|
|
cdef size_t lex_addr
|
|
cdef double norm = 0.0
|
|
cdef int i
|
|
for orth, lex_addr in self._by_orth.items():
|
|
lex = <LexemeC*>lex_addr
|
|
if lex.lower < vectors.size():
|
|
lex.vector = vectors[lex.lower]
|
|
norm = 0.0
|
|
for i in range(vec_len):
|
|
norm += lex.vector[i] * lex.vector[i]
|
|
lex.l2_norm = sqrt(norm)
|
|
else:
|
|
lex.vector = EMPTY_VEC
|
|
self.vectors_length = vec_len
|
|
return vec_len
|
|
|
|
|
|
def write_binary_vectors(in_loc, out_loc):
|
|
cdef CFile out_file = CFile(out_loc, 'wb')
|
|
cdef Address mem
|
|
cdef int32_t word_len
|
|
cdef int32_t vec_len
|
|
cdef char* chars
|
|
with bz2.BZ2File(in_loc, 'r') as file_:
|
|
for line in file_:
|
|
pieces = line.split()
|
|
word = pieces.pop(0)
|
|
mem = Address(len(pieces), sizeof(float))
|
|
vec = <float*>mem.ptr
|
|
for i, val_str in enumerate(pieces):
|
|
vec[i] = float(val_str)
|
|
|
|
word_len = len(word)
|
|
vec_len = len(pieces)
|
|
|
|
out_file.write_from(&word_len, 1, sizeof(word_len))
|
|
out_file.write_from(&vec_len, 1, sizeof(vec_len))
|
|
|
|
chars = <char*>word
|
|
out_file.write_from(chars, len(word), sizeof(char))
|
|
out_file.write_from(vec, vec_len, sizeof(float))
|
|
|
|
|
|
class LookupError(Exception):
|
|
@classmethod
|
|
def mismatched_strings(cls, id_, id_string, original_string):
|
|
return cls(
|
|
"Error fetching a Lexeme from the Vocab. When looking up a string, "
|
|
"the lexeme returned had an orth ID that did not match the query string. "
|
|
"This means that the cached lexeme structs are mismatched to the "
|
|
"string encoding table. The mismatched:\n"
|
|
"Query string: {query}\n"
|
|
"Orth cached: {orth_str}\n"
|
|
"ID of orth: {orth_id}".format(
|
|
query=repr(original_string), orth_str=repr(id_string), orth_id=id_)
|
|
)
|
|
|
|
|
|
class VectorReadError(Exception):
|
|
@classmethod
|
|
def mismatched_sizes(cls, loc, line_num, prev_size, curr_size):
|
|
return cls(
|
|
"Error reading word vectors from %s on line %d.\n"
|
|
"All vectors must be the same size.\n"
|
|
"Prev size: %d\n"
|
|
"Curr size: %d" % (loc, line_num, prev_size, curr_size))
|
|
|
|
@classmethod
|
|
def bad_size(cls, loc, size):
|
|
return cls(
|
|
"Error reading word vectors from %s.\n"
|
|
"Vector size: %d\n"
|
|
"Max size: %d\n"
|
|
"Min size: 1\n" % (loc, size, MAX_VEC_SIZE))
|