在运行代码的时候调用了zeros函数，按理说里面的dtype参数默认也应该是float啊，可是不知道为什么会报错，代码如下：
def _load_representation(self): ''' load user and item latent features generate by MF for every meta-graph ''' #if dt in ['yelp-200k', 'amazon-200k', 'amazon-50k', 'amazon-100k', 'amazon-10k', 'amazon-5k', 'cikm-yelp', 'yelp-50k', 'yelp-10k', 'yelp-5k', 'yelp-100k', 'douban']: fnum = self.N / 2 ufilename = self.data_dir + 'uids.txt' bfilename = self.data_dir + 'bids.txt' uids = [int(l.strip()) for l in open(ufilename, 'r').readlines()] uid2reps = {k:np.zeros(fnum, dtype=np.float64) for k in uids}
bids = [int(l.strip()) for l in open(bfilename, 'r').readlines()]
bid2reps = {k:np.zeros(fnum, dtype=np.float64) for k in bids}
ufiles, vfiles = self._generate_feature_files()
feature_dir = self.data_dir + 'mf_features/path_count/'
for find, filename in enumerate(ufiles):
ufs = np.loadtxt(feature_dir + filename, dtype=np.float64)
cur = find * self.F
for uf in ufs:
uid = int(uf[0])
f = uf[1:]
uid2reps[uid][cur:cur+self.F] = f
for find, filename in enumerate(vfiles):
bfs = np.loadtxt(feature_dir + filename, dtype=np.float64)
cur = find * self.F
for bf in bfs:
bid = int(bf[0])
f = bf[1:]
bid2reps[bid][cur:cur+self.F] = f
logging.info('load all representations, len(ufiles)=%s, len(vfiles)=%s, ufiles=%s, vfiles=%s', len(ufiles), len(vfiles), '|'.join(ufiles), '|'.join(vfiles))
return uid2reps, bid2reps
有问题的应该是里面这两句：
uids = [int(l.strip()) for l in open(ufilename, 'r').readlines()]
uid2reps = {k:np.zeros(fnum, dtype=np.float64) for k in uids}
最前面有导入numpy“import numpy as np”，求大神帮忙看看到底是哪里错了。。一直会提示“TypeError: 'float' object cannot be interpreted as an integer”。。
不知道你这个问题是否已经解决, 如果还没有解决的话: