import torch
from torch import nn
from torch.autograd import Variable
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
xy = pd.read_csv("all.csv",names=['pm2.5','pm10,s02','no2','co','o3','tem','hig_tem','low_tem','rain','qiya','shidu','zuixiaoshidu','fengsu_10min','fengsu','rizuidafengsu','rizhao'])
x_data = xy.iloc[6:-1,:-1].values
y_data = xy.iloc[:6,:-1].values


x_data = Variable(torch.from_numpy(x_data))
y_data = Variable(torch.from_numpy(y_data))
.....

I want to run an RNN but  i can’t solve the data problem . Then i got an error:
RuntimeError: can't convert a given np.ndarray to a tensor - it has an invalid type. The only supported types are: double, float, int64, int32, and uint8.

how can i make it available?