def rare_words():
c = config.default_config
vocab = load_vocabulary(corpuspath(c.embedding.corpus))
min_count = c.embedding.min_count
rare_words = sorted([word for (word, count) in vocab.items() if count < min_count])
frequent_words = sorted([word for (word, count) in vocab.items() if count >= min_count])
print("Total number of words:", len(vocab))
print("Number of words with embedding:", len(frequent_words))
print("Number of words without embeddings:", len(rare_words))
return rare_words, frequent_words
def create_embedding(embeddingconfig):
makedirs('data/embeddings', exist_ok=True)
corpuspath = config.corpuspath(embeddingconfig.corpus)
embeddingpath = config.embeddingpath(embeddingconfig)
if path.isfile(embeddingpath):
return
create_word_embedding( infile=corpuspath \
, outfile=embeddingpath \
, size=embeddingconfig.dimension \
, estimator=embeddingconfig.estimator \
, negative=embeddingconfig.negative \
, downsample=embeddingconfig.downsampling \
, min_count=embeddingconfig.min_count )
def create_grams(gramconfig):
makedirs('data/grams', exist_ok=True)
corpuspath = config.corpuspath(gramconfig.corpus)
grampath = config.grampath(gramconfig)
if path.isfile(grampath):
return
uncompressed_grampath = str(Path(grampath).parent / Path(grampath).stem)
with gzip.open(corpuspath, mode='rt') as inf:
with open(uncompressed_grampath, mode='wt') as outf: # may overwrite
for line in inf:
c = gramconfig
for gram, skip in iter_grams(line, c.gram_size, c.skipwords, c.skippos, c.filter_skips):
completegram = ' '.join(chain(gram[ : c.skippos], skip, gram[c.skippos : ]))
print(completegram, file=outf)
subprocess.run(['/usr/bin/shuf', '-o', uncompressed_grampath, uncompressed_grampath])
compress(uncompressed_grampath)