Hello,

I am new to pytorch and I am trying to predict diabetes classification.

```
import torch.optim as optim
import torch
import numpy as np
from torch.autograd import Variable
from torch.utils.data import Dataset, DataLoader
model = DeepNet(8)
#8 input features, and 3 outputs
optimizer = optim.SGD(model.parameters(), lr=0.0001)
loss_fn = nn.CrossEntropyLoss()
#batch size of 200 is indicated in the parameters of the dataloader.
loss_list = []
for epoch in range(100): # loop over the dataset for 100 epochs
avg_loss = 0
for index, data in enumerate(train_loader, 0):
inputs, labels = data
inputs, labels = Variable(inputs), Variable(labels)
optimizer.zero_grad()
outputs = model(inputs)
print(inputs.size(), labels.size(), outputs.size())
loss = loss_fn(outputs, labels.long())
avg_loss += loss.data.numpy().ravel()[0]
loss.backward()
optimizer.step()
loss_list.append(avg_loss/inputs.shape[0])
plt.plot(loss_list)
print("The loss value at 100th epoch:", loss_list[99])
```

However, I am having an error: multi-target not supported at c:\a\w\1\s\tmp_conda_3.6_091443\conda\conda-bld\pytorch_1544087948354\work\aten\src\thnn\generic/ClassNLLCriterion.c:21."

Here are the sizes of the inputs, labels, and outputs, respectively:

torch.Size([200, 8]) torch.Size([200, 1]) torch.Size([200, 3])

Any help is greatly appreciated! Thank you very much!