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6 changes: 3 additions & 3 deletions requirements.txt
Original file line number Diff line number Diff line change
@@ -1,3 +1,3 @@
networkx==1.11
numpy==1.11.2
gensim==0.13.3
numpy>=1.16.2
networkx>=2.2
gensim>=3.4.0
4 changes: 2 additions & 2 deletions src/main.py
Original file line number Diff line number Diff line change
Expand Up @@ -83,9 +83,9 @@ def learn_embeddings(walks):
'''
Learn embeddings by optimizing the Skipgram objective using SGD.
'''
walks = [map(str, walk) for walk in walks]
walks = [list(map(str, walk)) for walk in walks]
model = Word2Vec(walks, size=args.dimensions, window=args.window_size, min_count=0, sg=1, workers=args.workers, iter=args.iter)
model.save_word2vec_format(args.output)
model.wv.save_word2vec_format(args.output)

return

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5 changes: 3 additions & 2 deletions src/node2vec.py
Original file line number Diff line number Diff line change
@@ -1,3 +1,4 @@
from __future__ import print_function
import numpy as np
import networkx as nx
import random
Expand Down Expand Up @@ -43,9 +44,9 @@ def simulate_walks(self, num_walks, walk_length):
G = self.G
walks = []
nodes = list(G.nodes())
print 'Walk iteration:'
print('Walk iteration:')
for walk_iter in range(num_walks):
print str(walk_iter+1), '/', str(num_walks)
print(str(walk_iter+1) + '/' + str(num_walks))
random.shuffle(nodes)
for node in nodes:
walks.append(self.node2vec_walk(walk_length=walk_length, start_node=node))
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