rel_embedding_layers = []
rel_matrix_layers = []
for i in range(args.clayer):
rel_embedding_layers.append(
EmbeddingLayer(n_d=args.word_dim, vocab=rel_lis, fix_init_embs=False))
if args.model == 4:
for i in range(args.clayer):
rel_matrix_layers.append(
MatrixLayer(n_d=args.word_dim,
vocab=rel_lis,
rank=args.rank,
fix_init_embs=False))
word_embedding_layer.word_matching(word_lis)
print 'Construting input...'
train_input = []
dev_input = []
test_input = []
train_set = train_cors
test_set = test_cors
ratio = 0.80
train_size = len(train_set)
print 'Training set : ' + str(train_size)
test_size = len(test_set)
