spacy nightly (3.0.0rc) load without vocab how to add word2vec vectorspace?

Question

In spacy 2 I use this to add a vocab to an empty spacy model with vectorspace (spacy init) :

nlp3=spacy.load('nl_core_news_sm') #standard model without vectors
spacy.load("spacyinitnlmodelwithvectorspace",vocab=nlp3.vocab)

In spacy nightly version 3.0.0rc the vocab parameter is not in spacy.load anymore. Has anyone a suggesstion how I can add vocab to a spacy model?

Answer 1

this works, from Export vectors from fastText to spaCy add's vecfile to spacy model. only tested on small dataset

from future import unicode_literals

import numpy import spacy

def spacy_load_vec(spacy_model,vec_file,spacy_vec_model,print_words=False): """ spacy model zonder vectoren + vecfile wordt spacy model met vectorspace Export vectors from fastText to spaCy

Parameters
----------
spacy_model : TYPE
    spacy model zonder vectorspace.
vec_file : TYPE
    vecfile met fasttext of w2v getrainde vectoren.
spacy_vec_model : TYPE
    spacy model met vectorspace.
print_words : TYPE, optional
    woorden printen True/false. The default is False.

Returns
-------
None.

"""
nlp = spacy.load(spacy_model)
with open(vec_file, 'rb') as file_:
    header = file_.readline()
    nr_row, nr_dim = header.split()
    nlp.vocab.reset_vectors(width=int(nr_dim))
    count = 0
    for line in file_:
        count += 1
        line = line.rstrip().decode('utf8')
        pieces = line.rsplit(' ', int(nr_dim))
        word = pieces[0]
        if print_words:
            print("{} - {}".format(count, word)) 
        vector = numpy.asarray([float(v) for v in pieces[1:]], dtype='f')
        nlp.vocab.set_vector(word, vector)  # add the vectors to the vocab
nlp.to_disk(spacy_vec_model)