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spaCy/spacy/vocab.pyx
Matthew Honnibal 793430aa7a Get spaCy train command working with neural network 
* Integrate models into pipeline
* Add basic serialization (maybe incorrect)
* Fix pickle on vocab
2017-05-17 12:04:50 +02:00

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# coding: utf8
from __future__ import unicode_literals
import bz2
import ujson
import re
from libc.string cimport memset, memcpy
from libc.stdint cimport int32_t
from libc.math cimport sqrt
from cymem.cymem cimport Address
from .lexeme cimport EMPTY_LEXEME
from .lexeme cimport Lexeme
from .strings cimport hash_string
from .typedefs cimport attr_t
from .cfile cimport CFile
from .tokens.token cimport Token
from .attrs cimport PROB, LANG
from .structs cimport SerializedLexemeC
from .compat import copy_reg, pickle
from .lemmatizer import Lemmatizer
from .attrs import intify_attrs
from . import util
from . import attrs
from . import symbols
DEF MAX_VEC_SIZE = 100000
cdef float[MAX_VEC_SIZE] EMPTY_VEC
memset(EMPTY_VEC, 0, sizeof(EMPTY_VEC))
memset(&EMPTY_LEXEME, 0, sizeof(LexemeC))
EMPTY_LEXEME.vector = EMPTY_VEC
cdef class Vocab:
"""
A map container for a language's LexemeC structs.
"""
@classmethod
def load(cls, path, lex_attr_getters=None, lemmatizer=True,
tag_map=True, oov_prob=True, **deprecated_kwargs):
"""
Deprecated --- replace in spaCy 2
Load the vocabulary from a path.
Arguments:
path (Path):
The path to load from.
lex_attr_getters (dict):
A dictionary mapping attribute IDs to functions to compute them.
Defaults to None.
lemmatizer (object):
A lemmatizer. Defaults to None.
tag_map (dict):
A dictionary mapping fine-grained tags to coarse-grained parts-of-speech,
and optionally morphological attributes.
oov_prob (float):
The default probability for out-of-vocabulary words.
Returns:
Vocab: The newly constructed vocab object.
"""
path = util.ensure_path(path)
util.check_renamed_kwargs({'get_lex_attr': 'lex_attr_getters'}, deprecated_kwargs)
if 'vectors' in deprecated_kwargs:
raise AttributeError(
"vectors argument to Vocab.load() deprecated. "
"Install vectors after loading.")
if tag_map is True and (path / 'vocab' / 'tag_map.json').exists():
with (path / 'vocab' / 'tag_map.json').open('r', encoding='utf8') as file_:
tag_map = ujson.load(file_)
elif tag_map is True:
tag_map = None
if lex_attr_getters is not None \
and oov_prob is True \
and (path / 'vocab' / 'oov_prob').exists():
with (path / 'vocab' / 'oov_prob').open('r', encoding='utf8') as file_:
oov_prob = float(file_.read())
lex_attr_getters[PROB] = lambda text: oov_prob
if lemmatizer is True:
lemmatizer = Lemmatizer.load(path)
with (path / 'vocab' / 'strings.json').open('r', encoding='utf8') as file_:
strings_list = ujson.load(file_)
cdef Vocab self = cls(lex_attr_getters=lex_attr_getters, tag_map=tag_map,
lemmatizer=lemmatizer,
strings=strings_list)
self.load_lexemes(path / 'vocab' / 'lexemes.bin')
return self
def __init__(self, lex_attr_getters=None, tag_map=None, lemmatizer=None,
strings=tuple(), **deprecated_kwargs):
"""
Create the vocabulary.
lex_attr_getters (dict):
A dictionary mapping attribute IDs to functions to compute them.
Defaults to None.
lemmatizer (object):
A lemmatizer. Defaults to None.
tag_map (dict):
A dictionary mapping fine-grained tags to coarse-grained parts-of-speech,
and optionally morphological attributes.
oov_prob (float):
The default probability for out-of-vocabulary words.
Returns:
Vocab: The newly constructed vocab object.
"""
util.check_renamed_kwargs({'get_lex_attr': 'lex_attr_getters'}, deprecated_kwargs)
lex_attr_getters = lex_attr_getters if lex_attr_getters is not None else {}
tag_map = tag_map if tag_map is not None else {}
if lemmatizer in (None, True, False):
lemmatizer = Lemmatizer({}, {}, {})
self.mem = Pool()
self._by_hash = PreshMap()
self._by_orth = PreshMap()
self.strings = StringStore()
if strings:
for string in strings:
self.strings[string]
# Load strings in a special order, so that we have an onset number for
# the vocabulary. This way, when words are added in order, the orth ID
# is the frequency rank of the word, plus a certain offset. The structural
# strings are loaded first, because the vocab is open-class, and these
# symbols are closed class.
# TODO: Actually this has turned out to be a pain in the ass...
# It means the data is invalidated when we add a symbol :(
# Need to rethink this.
for name in symbols.NAMES + list(sorted(tag_map.keys())):
if name:
_ = self.strings[name]
self.lex_attr_getters = lex_attr_getters
self.morphology = Morphology(self.strings, tag_map, lemmatizer)
self.length = 1
property lang:
def __get__(self):
langfunc = None
if self.lex_attr_getters:
langfunc = self.lex_attr_getters.get(LANG, None)
return langfunc('_') if langfunc else ''
def __len__(self):
"""
The current number of lexemes stored.
"""
return self.length
def add_flag(self, flag_getter, int flag_id=-1):
"""
Set a new boolean flag to words in the vocabulary.
The flag_setter function will be called over the words currently in the
vocab, and then applied to new words as they occur. You'll then be able
to access the flag value on each token, using token.check_flag(flag_id).
See also:
Lexeme.set_flag, Lexeme.check_flag, Token.set_flag, Token.check_flag.
Arguments:
flag_getter:
A function f(unicode) -> bool, to get the flag value.
flag_id (int):
An integer between 1 and 63 (inclusive), specifying the bit at which the
flag will be stored. If -1, the lowest available bit will be
chosen.
Returns:
flag_id (int): The integer ID by which the flag value can be checked.
"""
if flag_id == -1:
for bit in range(1, 64):
if bit not in self.lex_attr_getters:
flag_id = bit
break
else:
raise ValueError(
"Cannot find empty bit for new lexical flag. All bits between "
"0 and 63 are occupied. You can replace one by specifying the "
"flag_id explicitly, e.g. nlp.vocab.add_flag(your_func, flag_id=IS_ALPHA")
elif flag_id >= 64 or flag_id < 1:
raise ValueError(
"Invalid value for flag_id: %d. Flag IDs must be between "
"1 and 63 (inclusive)" % flag_id)
for lex in self:
lex.set_flag(flag_id, flag_getter(lex.orth_))
self.lex_attr_getters[flag_id] = flag_getter
return flag_id
cdef const LexemeC* get(self, Pool mem, unicode string) except NULL:
"""
Get a pointer to a LexemeC from the lexicon, creating a new Lexeme
if necessary, using memory acquired from the given pool. If the pool
is the lexicon's own memory, the lexeme is saved in the lexicon.
"""
if string == u'':
return &EMPTY_LEXEME
cdef LexemeC* lex
cdef hash_t key = hash_string(string)
lex = <LexemeC*>self._by_hash.get(key)
cdef size_t addr
if lex != NULL:
if lex.orth != self.strings[string]:
raise LookupError.mismatched_strings(
lex.orth, self.strings[string], string)
return lex
else:
return self._new_lexeme(mem, string)
cdef const LexemeC* get_by_orth(self, Pool mem, attr_t orth) except NULL:
"""
Get a pointer to a LexemeC from the lexicon, creating a new Lexeme
if necessary, using memory acquired from the given pool. If the pool
is the lexicon's own memory, the lexeme is saved in the lexicon.
"""
if orth == 0:
return &EMPTY_LEXEME
cdef LexemeC* lex
lex = <LexemeC*>self._by_orth.get(orth)
if lex != NULL:
return lex
else:
return self._new_lexeme(mem, self.strings[orth])
cdef const LexemeC* _new_lexeme(self, Pool mem, unicode string) except NULL:
cdef hash_t key
if len(string) < 3 or self.length < 10000:
mem = self.mem
cdef bint is_oov = mem is not self.mem
lex = <LexemeC*>mem.alloc(sizeof(LexemeC), 1)
lex.orth = self.strings[string]
lex.length = len(string)
lex.id = self.length
lex.vector = <float*>mem.alloc(self.vectors_length, sizeof(float))
if self.lex_attr_getters is not None:
for attr, func in self.lex_attr_getters.items():
value = func(string)
if isinstance(value, unicode):
value = self.strings[value]
if attr == PROB:
lex.prob = value
elif value is not None:
Lexeme.set_struct_attr(lex, attr, value)
if is_oov:
lex.id = 0
else:
key = hash_string(string)
self._add_lex_to_vocab(key, lex)
assert lex != NULL, string
return lex
cdef int _add_lex_to_vocab(self, hash_t key, const LexemeC* lex) except -1:
self._by_hash.set(key, <void*>lex)
self._by_orth.set(lex.orth, <void*>lex)
self.length += 1
def __contains__(self, unicode string):
"""
Check whether the string has an entry in the vocabulary.
Arguments:
string (unicode): The ID string.
Returns:
bool Whether the string has an entry in the vocabulary.
"""
key = hash_string(string)
lex = self._by_hash.get(key)
return lex is not NULL
def __iter__(self):
"""
Iterate over the lexemes in the vocabulary.
Yields: Lexeme An entry in the vocabulary.
"""
cdef attr_t orth
cdef size_t addr
for orth, addr in self._by_orth.items():
yield Lexeme(self, orth)
def __getitem__(self, id_or_string):
"""
Retrieve a lexeme, given an int ID or a unicode string. If a previously
unseen unicode string is given, a new lexeme is created and stored.
Arguments:
id_or_string (int or unicode):
The integer ID of a word, or its unicode string.
If an int >= Lexicon.size, IndexError is raised. If id_or_string
is neither an int nor a unicode string, ValueError is raised.
Returns:
lexeme (Lexeme): The lexeme indicated by the given ID.
"""
cdef attr_t orth
if type(id_or_string) == unicode:
orth = self.strings[id_or_string]
else:
orth = id_or_string
return Lexeme(self, orth)
cdef const TokenC* make_fused_token(self, substrings) except NULL:
cdef int i
tokens = <TokenC*>self.mem.alloc(len(substrings) + 1, sizeof(TokenC))
for i, props in enumerate(substrings):
props = intify_attrs(props, strings_map=self.strings, _do_deprecated=True)
token = &tokens[i]
# Set the special tokens up to have arbitrary attributes
token.lex = <LexemeC*>self.get_by_orth(self.mem, props[attrs.ORTH])
if attrs.TAG in props:
self.morphology.assign_tag(token, props[attrs.TAG])
for attr_id, value in props.items():
Token.set_struct_attr(token, attr_id, value)
return tokens
def to_disk(self, path):
path = util.ensure_path(path)
if not path.exists():
path.mkdir()
strings_loc = path / 'strings.json'
with strings_loc.open('w', encoding='utf8') as file_:
self.strings.dump(file_)
self.dump(path / 'lexemes.bin')
def from_disk(self, path):
path = util.ensure_path(path)
with (path / 'vocab' / 'strings.json').open('r', encoding='utf8') as file_:
strings_list = ujson.load(file_)
for string in strings_list:
self.strings[string]
self.load_lexemes(path / 'lexemes.bin')
def lexemes_to_bytes(self, **exclude):
cdef hash_t key
cdef size_t addr
cdef LexemeC* lexeme = NULL
cdef SerializedLexemeC lex_data
cdef int size = 0
for key, addr in self._by_hash.items():
if addr == 0:
continue
size += sizeof(lex_data.data)
byte_string = b'\0' * size
byte_ptr = <unsigned char*>byte_string
cdef int j
cdef int i = 0
for key, addr in self._by_hash.items():
if addr == 0:
continue
lexeme = <LexemeC*>addr
lex_data = Lexeme.c_to_bytes(lexeme)
for j in range(sizeof(lex_data.data)):
byte_ptr[i] = lex_data.data[j]
i += 1
return byte_string
def lexemes_from_bytes(self, bytes bytes_data):
"""
Load the binary vocabulary data from the given string.
"""
cdef LexemeC* lexeme
cdef hash_t key
cdef unicode py_str
cdef int i = 0
cdef int j = 0
cdef SerializedLexemeC lex_data
chunk_size = sizeof(lex_data.data)
cdef unsigned char* bytes_ptr = bytes_data
for i in range(0, len(bytes_data), chunk_size):
lexeme = <LexemeC*>self.mem.alloc(1, sizeof(LexemeC))
for j in range(sizeof(lex_data.data)):
lex_data.data[j] = bytes_ptr[i+j]
Lexeme.c_from_bytes(lexeme, lex_data)
lexeme.vector = EMPTY_VEC
py_str = self.strings[lexeme.orth]
assert self.strings[py_str] == lexeme.orth, (py_str, lexeme.orth)
key = hash_string(py_str)
self._by_hash.set(key, lexeme)
self._by_orth.set(lexeme.orth, lexeme)
self.length += 1
# Deprecated --- delete these once stable
def dump_vectors(self, out_loc):
"""
Save the word vectors to a binary file.
Arguments:
loc (Path): The path to save to.
Returns:
None
#"""
cdef int32_t vec_len = self.vectors_length
cdef int32_t word_len
cdef bytes word_str
cdef char* chars
cdef Lexeme lexeme
cdef CFile out_file = CFile(out_loc, 'wb')
for lexeme in self:
word_str = lexeme.orth_.encode('utf8')
vec = lexeme.c.vector
word_len = len(word_str)
out_file.write_from(&word_len, 1, sizeof(word_len))
out_file.write_from(&vec_len, 1, sizeof(vec_len))
chars = <char*>word_str
out_file.write_from(chars, word_len, sizeof(char))
out_file.write_from(vec, vec_len, sizeof(float))
out_file.close()
def load_vectors(self, file_):
"""
Load vectors from a text-based file.
Arguments:
file_ (buffer): The file to read from. Entries should be separated by newlines,
and each entry should be whitespace delimited. The first value of the entry
should be the word string, and subsequent entries should be the values of the
vector.
Returns:
vec_len (int): The length of the vectors loaded.
"""
cdef LexemeC* lexeme
cdef attr_t orth
cdef int32_t vec_len = -1
cdef double norm = 0.0
whitespace_pattern = re.compile(r'\s', re.UNICODE)
for line_num, line in enumerate(file_):
pieces = line.split()
word_str = " " if whitespace_pattern.match(line) else pieces.pop(0)
if vec_len == -1:
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)
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]]
# Insert words into vocab to add vector.
self.get_by_orth(self.mem, string_id)
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 resize_vectors(self, int new_size):
"""
Set vectors_length to a new size, and allocate more memory for the Lexeme
vectors if necessary. The memory will be zeroed.
Arguments:
new_size (int): The new size of the vectors.
"""
cdef hash_t key
cdef size_t addr
if new_size > self.vectors_length:
for key, addr in self._by_hash.items():
lex = <LexemeC*>addr
lex.vector = <float*>self.mem.realloc(lex.vector,
new_size * sizeof(lex.vector[0]))
self.vectors_length = new_size
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))
def pickle_vocab(vocab):
sstore = vocab.strings
morph = vocab.morphology
length = vocab.length
data_dir = vocab.data_dir
lex_attr_getters = vocab.lex_attr_getters
lexemes_data = vocab.lexemes_to_bytes()
vectors_length = vocab.vectors_length
return (unpickle_vocab,
(sstore, morph, data_dir, lex_attr_getters,
lexemes_data, length, vectors_length))
def unpickle_vocab(sstore, morphology, data_dir,
lex_attr_getters, bytes lexemes_data, int length, int vectors_length):
cdef Vocab vocab = Vocab()
vocab.length = length
vocab.vectors_length = vectors_length
vocab.strings = sstore
vocab.morphology = morphology
vocab.data_dir = data_dir
vocab.lex_attr_getters = lex_attr_getters
vocab.lexemes_from_bytes(lexemes_data)
vocab.length = length
vocab.vectors_length = vectors_length
return vocab
copy_reg.pickle(Vocab, pickle_vocab, unpickle_vocab)
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))
#
#Deprecated --- delete these once stable
#
# def dump_vectors(self, out_loc):
# """
# Save the word vectors to a binary file.
#
# Arguments:
# loc (Path): The path to save to.
# Returns:
# None
# #"""
# cdef int32_t vec_len = self.vectors_length
# cdef int32_t word_len
# cdef bytes word_str
# cdef char* chars
#
# cdef Lexeme lexeme
# cdef CFile out_file = CFile(out_loc, 'wb')
# for lexeme in self:
# word_str = lexeme.orth_.encode('utf8')
# vec = lexeme.c.vector
# word_len = len(word_str)
#
# out_file.write_from(&word_len, 1, sizeof(word_len))
# out_file.write_from(&vec_len, 1, sizeof(vec_len))
#
# chars = <char*>word_str
# out_file.write_from(chars, word_len, sizeof(char))
# out_file.write_from(vec, vec_len, sizeof(float))
# out_file.close()
#
#
#
# def load_vectors(self, file_):
# """
# Load vectors from a text-based file.
#
# Arguments:
# file_ (buffer): The file to read from. Entries should be separated by newlines,
# and each entry should be whitespace delimited. The first value of the entry
# should be the word string, and subsequent entries should be the values of the
# vector.
#
# Returns:
# vec_len (int): The length of the vectors loaded.
# """
# cdef LexemeC* lexeme
# cdef attr_t orth
# cdef int32_t vec_len = -1
# cdef double norm = 0.0
#
# whitespace_pattern = re.compile(r'\s', re.UNICODE)
#
# for line_num, line in enumerate(file_):
# pieces = line.split()
# word_str = " " if whitespace_pattern.match(line) else pieces.pop(0)
# if vec_len == -1:
# 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)
# 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]]
# # Insert words into vocab to add vector.
# self.get_by_orth(self.mem, string_id)
# 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))
#
#
# def resize_vectors(self, int new_size):
# """
# Set vectors_length to a new size, and allocate more memory for the Lexeme
# vectors if necessary. The memory will be zeroed.
#
# Arguments:
# new_size (int): The new size of the vectors.
# """
# cdef hash_t key
# cdef size_t addr
# if new_size > self.vectors_length:
# for key, addr in self._by_hash.items():
# lex = <LexemeC*>addr
# lex.vector = <float*>self.mem.realloc(lex.vector,
# new_size * sizeof(lex.vector[0]))
# self.vectors_length = new_size
#
#
#
# def dump(self, loc=None):
# """
# Save the lexemes binary data to the given location, or
# return a byte-string with the data if loc is None.
#
# Arguments:
# loc (Path or None): The path to save to, or None.
# """
# if loc is None:
# return self.to_bytes()
# else:
# return self.to_disk(loc)
#
# def load_lexemes(self, loc):
# """
# Load the binary vocabulary data from the given location.
#
# Arguments:
# loc (Path): The path to load from.
#
# Returns:
# None
# """
# fp = CFile(loc, 'rb',
# on_open_error=lambda: IOError('LexemeCs file not found at %s' % loc))
# cdef LexemeC* lexeme = NULL
# cdef SerializedLexemeC lex_data
# cdef hash_t key
# cdef unicode py_str
# cdef attr_t orth = 0
# assert sizeof(orth) == sizeof(lexeme.orth)
# i = 0
# while True:
# try:
# fp.read_into(&orth, 1, sizeof(orth))
# except IOError:
# break
# lexeme = <LexemeC*>self.mem.alloc(sizeof(LexemeC), 1)
# # Copy data from the file into the lexeme
# fp.read_into(&lex_data.data, 1, sizeof(lex_data.data))
# Lexeme.c_from_bytes(lexeme, lex_data)
#
# lexeme.vector = EMPTY_VEC
# py_str = self.strings[lexeme.orth]
# key = hash_string(py_str)
# self._by_hash.set(key, lexeme)
# self._by_orth.set(lexeme.orth, lexeme)
# self.length += 1
# i += 1
# fp.close()
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