@ptrblck Thanks for that suggestion! The new prediction block is running into this error - I found this solve for it but am confused because the data being used has already been converted into a numpy array
name = userInput['Name'].cat.codes.values

inputColumns = np.stack([name, etc...], 1)

and then converted over to tensors.
inputColumns = torch.tensor(inputColumns, dtype=torch.int64)

Is there something wrong in this process that would cause this error? The same process worked for the
model.train() function.
['POL_STATUS', 'P1_POLICY_REFUSED', 'FLOODING', 'Zipcode', 'Combined FIPS', 'State', 'Name']

---------------------------------------------------------------------------

TypeError                                 Traceback (most recent call last)

<ipython-input-62-4fec13edb637> in <module>()
      1 preds = []
      2 with torch.no_grad():
----> 3   newY_val = model(inputCatColumns, inputNumColumns)
      4   preds.append(newY_val > 0.) # if y_val are logits
      5   loss = loss_function(newY_val, test_outputs)

1 frames

<ipython-input-35-5bbeaf977447> in forward(self, x_categorical, x_numerical)
     28         print(x_categorical)
     29         for i,e in enumerate(self.all_embeddings):
---> 30           print(x_categorical[:,i])
     31           embeddings.append(e(x_categorical[:,i]))
     32 

TypeError: list indices must be integers or slices, not tuple