在进行embedding时用到word2vec，出现参数问题

函数

def learn_embeddings(walks):
	'''
	Learn embeddings by optimizing the Skipgram objective using SGD.
	'''
	walks = [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)
	
	return

错误

TypeError: init() got an unexpected keyword argument ‘size’

对第二个参数size显示unexpected keyword argument

control+左键 查看了，word2vec的函数最新的size参数改成了:

class Word2Vec(utils.SaveLoad):
    def __init__(
            self, sentences=None, corpus_file=None, vector_size=100, alpha=0.025, window=5, min_count=5,
            max_vocab_size=None, sample=1e-3, seed=1, workers=3, min_alpha=0.0001,
            sg=0, hs=0, negative=5, ns_exponent=0.75, cbow_mean=1, hashfxn=hash, epochs=5, null_word=0,
            trim_rule=None, sorted_vocab=1, batch_words=MAX_WORDS_IN_BATCH, compute_loss=False, callbacks=(),
            comment=None, max_final_vocab=None, shrink_windows=True,
        ):

解决