#标签读取后由one-hot编码转化为数值
labels=torch.from_numpy(data['label'].todense())
labels=labels.nonzero()[:,1]
#GCN导入字符串列表labels转化为one-hot编码
classes=set(labels)
classes_dict={c:np.identity(len(classes))[i,:] for i,c in enumerate(classes)}
labels_onehot=np.array(list(map(classes_dict.get,labels)),dtype=np.int32)
#标签读取后由one-hot编码转化为数值
labels=torch.from_numpy(data['label'].todense())
labels=labels.nonzero()[:,1]
#GCN导入字符串列表labels转化为one-hot编码
classes=set(labels)
classes_dict={c:np.identity(len(classes))[i,:] for i,c in enumerate(classes)}
labels_onehot=np.array(list(map(classes_dict.get,labels)),dtype=np.int32)