运行时报错。
这是我的代码：
import numpy as np
import matplotlib.pyplot as plt
import torch
import torch.nn as nn
import torch.optim as optim
from torch.autograd import Variable
x_train = np.array([[3.3],[4.4],[5.5],[6.71],[6.93],[4.168],[9.779],[6.182],[7.59],[2.167],[7.042],[10.791],[5.313],[7.997],[3.1]], dtype=np.float32)
y_train = np.array([[1.23],[3.24],[2.3],[2.14],[2.93],[3.168],[1.779],[2.182],[2.59],[3.167],[1.042],[3.791],[3.313],[2.997],[1.1]], dtype=np.float32)
x_train = torch.from_numpy(x_train)
y_train = torch.from_numpy(y_train)
class LinearRegression(nn.Module):
def __init__(self):
super(LinearRegression,self).__init__()
self.linear = nn.Linear(1,1)
def forward(self,x):
out = self.linear(x)
return out
if torch.cuda.is_available():
model = LinearRegression().cuda()
else:
model = LinearRegression()
criterion = nn.MSELoss()
optimizer = optim.SGD(model.parameters(),lr = 1e-3)
num_epoch = 100
for epcoh in range(num_epoch):
if torch.cuda.is_available():
inputs = Variable(x_train).cuda()
outputs = Variable(y_train).cuda()
else:
inputs = Variable(x_train)
outputs = Variable(y_train)
out = model(inputs)
target = y_train
loss = criterion(out,target)
optimizer.zero_grad()
loss.backward()
optimizer.step()
if (epcoh+1)%20 == 0:
print('Epoch[{}/{}],loss:{:.6f}'
.format((epcoh+1,num_epoch,loss.data[0])))
model.eval()
predict = model(Variable(x_train))
predict = predict.data.numpy()
plt.plot(x_train.numpy(),y_train(),'ro',label = 'Original data')
plt.plot(x_train.numpy(),predict,label = 'Fitting Line')
plt.show()
错误截图：
各位大佬们，这个错误是怎么回事啊，是cpu的问题吗？以下是cpu的信息截图：
torch.cuda.current_device(): 0
torch.cuda.device(0):
torch.cuda.device_count(): 1
torch.cuda.get_device_name(0): GeForce MX250
torch.cuda.is_available(): True
