Expected scalar type Long but found Float

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#1

Aakash, please help withis error am getting, I am completely new to machine learning
expected scalar type Long but found Float

I changed it to long , it then said expected float got long
what do I do or what am I doing wrong

It's Intro Time
#2

I am not Aakash though but make sure both of your inputs are of the same type, especially if you are using Cross Entropy of any kind. That is in
F.binary_cross_entropy(x, y)
if your x is float y must be float.

1 Like
#3

Hi Godwin, can you please share the code for the cell which is causing this issue?

#4

Hi,
As mentioned in assignment 2, our pytorch dataset is of type float32. Now we defined class:
class InsuranceModel(nn.Module):

def __init__(self):

    super().__init__()

    self.linear = nn.Linear(input_size, output_size)            # fill this (hint: use input_size & output_size defined above)

    

def forward(self, xb):

    xb = xb.reshape(-1, input_size)                         # fill this

    out = self.linear(xb)

    return out



def training_step(self, batch):

    inputs, targets = batch 

    # Generate predictions

    out = self(inputs)          

    # Calcuate loss

    loss = F.cross_entropy(out, targets)                          # fill this

    return loss



def validation_step(self, batch):

    inputs, targets = batch

    # Generate predictions

    out = self(inputs)

    # Calculate loss

    loss = F.cross_entropy(out, targets)                             # fill this    

    return {'val_loss': loss.detach()}

    

def validation_epoch_end(self, outputs):

    batch_losses = [x['val_loss'] for x in outputs]

    epoch_loss = torch.stack(batch_losses).mean()   # Combine losses

    return {'val_loss': epoch_loss.item()}



def epoch_end(self, epoch, result, num_epochs):

    # Print result every 20th epoch

    if (epoch+1) % 20 == 0 or epoch == num_epochs-1:

        print("Epoch [{}], val_loss: {:.4f}".format(epoch+1, result['val_loss']))

Then we created a model object:
model = InsuranceModel()

Now we defined:
def evaluate(model, val_loader):

outputs = [model.validation_step(batch) for batch in val_loader]

return model.validation_epoch_end(outputs)

Here, If i try to do below:
result = evaluate(model, val_loader)
print(result)

We get error: expected scalar type Long but found Float

#5

Hi,
I got the issue. Our output_size is incorrect. Instead of 1, it was 7 for me. But now, After fixing that, I am facing another error in exact same line.

“1D target tensor expected, multi-target not supported”