运行时错误：预期标量类型 Float 但发现 Double（LSTM 分类器）

Question

I'm training my LSTM classifier.

epoch_num = 30

train_log = []
test_log = []
set_seed(111)
for epoch in range(1, epoch_num+1):

running_loss = 0    
train_loss = []
lstm_classifier.train()
for (inputs, labels) in tqdm(train_loader, desc='Training epoch ' + str(epoch), leave=False):        
    inputs, labels = inputs.to(device), labels.to(device)        
    optimizer.zero_grad()
    outputs = lstm_classifier(inputs)   
    loss = criterion(outputs, labels)
    loss.backward()                
    optimizer.step()        
    train_loss.append(loss.item())
train_log.append(np.mean(train_loss))

running_loss = 0
test_loss = []
lstm_classifier.eval()
with torch.no_grad():                
    for (inputs, labels) in tqdm(test_loader, desc='Test', leave=False):         
        inputs, labels = inputs.to(device), labels.to(device)        
        outputs = lstm_classifier(inputs)                       
        loss = criterion(outputs, labels)            
        test_loss.append(loss.item())
test_log.append(np.mean(test_loss))    
plt.plot(range(1, epoch+1), train_log, color='C0')
plt.plot(range(1, epoch+1), test_log, color='C1')
display.clear_output(wait=True)
display.display(plt.gcf())

error is:

RuntimeError Traceback (most recent call last) in ()

     23         print((labels.dtype))
     24         print(outputs[:,0].dtype)
---> 25         loss = criterion(outputs, labels)
     26         loss.backward()
     27         optimizer.step()

2 frames
/usr/local/lib/python3.7/dist-packages/torch/nn/functional.py in cross_entropy(input, target, weight, size_average, ignore_index, reduce, reduction)
   2822     if size_average is not None or reduce is not None:
   2823         reduction = _Reduction.legacy_get_string(size_average, reduce)
-> 2824     return torch._C._nn.cross_entropy_loss(input, target, weight, _Reduction.get_enum(reduction), ignore_index)
   2825 
   2826 

RuntimeError: expected scalar type Float but found Double

How to fix it?

Answer 1

RuntimeError: expected scalar type Float but found Double

The error at line loss = criterion(outputs, labels) is quite clear in that it requites your datatype to be float rather than double, but it doesn't explicitly say whether outputs or label is creating this.

My guess is its because of labels. Try converting it to float by doing labels.float()