How to fix RuntimeError "Expected object of scalar type Float but got scalar type Double for argument"?

Question

I'm trying to train a classifier via PyTorch. However, I am experiencing problems with training when I feed the model with training data. I get this error on y_pred = model(X_trainTensor):

RuntimeError: Expected object of scalar type Float but got scalar type Double for argument #4 'mat1'

Here are key parts of my code:

# Hyper-parameters  D_in = 47  # there are 47 parameters I investigate H = 33 D_out = 2  # output should be either 1 or 0 

# Format and load the data y = np.array( df['target'] ) X = np.array( df.drop(columns = ['target'], axis = 1) ) X_train, X_test, y_train, y_test = train_test_split(X, y, train_size = 0.8)  # split training/test data  X_trainTensor = torch.from_numpy(X_train) # convert to tensors y_trainTensor = torch.from_numpy(y_train) X_testTensor = torch.from_numpy(X_test) y_testTensor = torch.from_numpy(y_test) 

# Define the model model = torch.nn.Sequential(     torch.nn.Linear(D_in, H),     torch.nn.ReLU(),     torch.nn.Linear(H, D_out),     nn.LogSoftmax(dim = 1) ) 

# Define the loss function loss_fn = torch.nn.NLLLoss()  

for i in range(50):     y_pred = model(X_trainTensor)     loss = loss_fn(y_pred, y_trainTensor)     model.zero_grad()     loss.backward()     with torch.no_grad():                for param in model.parameters():             param -= learning_rate * param.grad 

Answer 1

Reference is from this github issue.

When the error is RuntimeError: Expected object of scalar type Float but got scalar type Double for argument #4 'mat1', you would need to use the .float() function since it says Expected object of scalar type Float.

Therefore, the solution is changing y_pred = model(X_trainTensor) to y_pred = model(X_trainTensor.float()).

Likewise, when you get another error for loss = loss_fn(y_pred, y_trainTensor), you need y_trainTensor.long() since the error message says Expected object of scalar type Long.

You could also do model.double(), as suggested by @Paddy .