hi guys i wanna write a function  test_model(model, criterion):
It should  print  the  loss  and the test set  accuracy , and should  return  y_true  and  y_pred  as NumPy arrays.
so i tried the following :
def test_model(model_ft, test_dataloaders,criterion,device):
# set model to evaluate model
model_ft.eval()
# Iterate over data.
for inputs, labels in dataloaders[phase]:
    inputs = inputs.to(device)
    labels = labels.to(device)

and now my question how do i get y_pred and y_true and the rest things?
We are in the framework of transfer learning in pytorch so the function i wanna write is the same as the train_model see(https://pytorch.org/tutorials/beginner/transfer_learning_tutorial.html 3) but somewhat edited for the prediction purpose. I also thought of concatenate the y_pred and y_true after each batch but i really cant put this into reality could you plz help me out ? Thanks