Dropping Trailing None's When Calculating Emitted ExecutionPlan Outputs

Summary:
Previously Support for outputting int/float was added in D53256808 for Seamless

This extends on this by dropping None Outputs (Which can be outputted by NanoGPT)

Differential Revision: D54328663

Author: Jack-Khuu

exir/emit/_emitter.py

@@ -1366,6 +1366,10 @@ def output(
         if isinstance(args_tuple, _AbstractValue):
             self.outputs.append(args_tuple.id)
         else:
+            # Drop all the None's present at the end of the list if there are any.
+            args_tuple = list(args_tuple)
+            while args_tuple and args_tuple[-1] is None:
+                args_tuple.pop()
             for arg in args_tuple:
                 if isinstance(arg, (int, float, bool)):
                     arg = self._emit_evalue(self._constant_to_evalue(arg, None))

exir/emit/test/test_emit.py

@@ -213,7 +213,7 @@ def forward(
     def test_constant_output(self):
         class M(torch.nn.Module):
             def forward(self, x):
-                return [((1, 3, 1.2), True, [x + x, x * x])]
+                return [((1, 3, 1.2), True, [x + x, x * x], None)]
 
         ep = torch.export.export(M(), (torch.ones(2, 3),))
         res = ep(torch.ones(2, 3))