spaCy/spacy/vectors.pyx
2017-08-19 22:07:00 +02:00

150 lines
4.4 KiB
Cython

from __future__ import unicode_literals
from libc.stdint cimport int32_t, uint64_t
import numpy
from collections import OrderedDict
import msgpack
import msgpack_numpy
msgpack_numpy.patch()
cimport numpy as np
from .typedefs cimport attr_t
from .strings cimport StringStore
from . import util
from .compat import basestring_
cdef class Vectors:
'''Store, save and load word vectors.'''
cdef public object data
cdef readonly StringStore strings
cdef public object key2row
cdef public object keys
cdef public int i
def __init__(self, strings, data_or_width):
self.strings = StringStore()
if isinstance(data_or_width, int):
self.data = data = numpy.zeros((len(strings), data_or_width),
dtype='f')
else:
data = data_or_width
self.i = 0
self.data = data
self.key2row = {}
self.keys = np.ndarray((self.data.shape[0],), dtype='uint64')
def __reduce__(self):
return (Vectors, (self.strings, self.data))
def __getitem__(self, key):
if isinstance(key, basestring):
key = self.strings[key]
i = self.key2row[key]
if i is None:
raise KeyError(key)
else:
return self.data[i]
def __setitem__(self, key, vector):
if isinstance(key, basestring):
key = self.strings.add(key)
i = self.key2row[key]
self.data[i] = vector
def __iter__(self):
yield from self.data
def __len__(self):
return self.i
def __contains__(self, key):
if isinstance(key, basestring_):
key = self.strings[key]
return key in self.key2row
def add(self, key, vector=None):
if isinstance(key, basestring_):
key = self.strings.add(key)
if key not in self.key2row:
i = self.i
if i >= self.keys.shape[0]:
self.keys.resize((self.keys.shape[0]*2,))
self.data.resize((self.data.shape[0]*2, self.data.shape[1]))
self.key2row[key] = self.i
self.keys[self.i] = key
self.i += 1
else:
i = self.key2row[key]
if vector is not None:
self.data[i] = vector
return i
def items(self):
for i, string in enumerate(self.strings):
yield string, self.data[i]
@property
def shape(self):
return self.data.shape
def most_similar(self, key):
raise NotImplementedError
def to_disk(self, path, **exclude):
serializers = OrderedDict((
('vectors', lambda p: numpy.save(p.open('wb'), self.data, allow_pickle=False)),
('keys', lambda p: numpy.save(p.open('wb'), self.keys, allow_pickle=False)),
))
return util.to_disk(path, serializers, exclude)
def from_disk(self, path, **exclude):
def load_keys(path):
if path.exists():
self.keys = numpy.load(path)
for i, key in enumerate(self.keys):
self.keys[i] = key
self.key2row[key] = i
def load_vectors(path):
if path.exists():
self.data = numpy.load(path)
serializers = OrderedDict((
('keys', load_keys),
('vectors', load_vectors),
))
util.from_disk(path, serializers, exclude)
return self
def to_bytes(self, **exclude):
def serialize_weights():
if hasattr(self.data, 'to_bytes'):
return self.data.to_bytes()
else:
return msgpack.dumps(self.data)
serializers = OrderedDict((
('keys', lambda: msgpack.dumps(self.keys)),
('vectors', serialize_weights)
))
return util.to_bytes(serializers, exclude)
def from_bytes(self, data, **exclude):
def deserialize_weights(b):
if hasattr(self.data, 'from_bytes'):
self.data.from_bytes()
else:
self.data = msgpack.loads(b)
def load_keys(keys):
self.keys.resize((len(keys),))
for i, key in enumerate(keys):
self.keys[i] = key
self.key2row[key] = i
deserializers = OrderedDict((
('keys', lambda b: load_keys(msgpack.loads(b))),
('vectors', deserialize_weights)
))
util.from_bytes(data, deserializers, exclude)
return self