fix None consistency

Author: Chillee

functorch/_src/decompositions.py

@@ -477,23 +477,23 @@ def native_layer_norm_backward(grad_out: Tensor, input: Tensor, normalized_shape
     if output_mask[0]:
         d_input = aten.mul(aten.div(rstd, N), inner)
     else:
-        d_input = aten.new_empty(input, (0,))
+        d_input = None
 
     if output_mask[1] and weight is not None:
         if len(outer_dim_indices) > 0:
             d_weight = aten.sum(aten.mul(grad_out, x_hat), outer_dim_indices, False)
         else:
             d_weight = aten.mul(grad_out, x_hat)
     else:
-        d_weight = aten.new_empty(input, (0,))
+        d_weight = None
 
     if output_mask[2] and bias is not None:
         if len(outer_dim_indices) > 0:
             d_bias = aten.sum(grad_out, outer_dim_indices, False)
         else:
             d_bias = grad_out
     else:
-        d_bias = aten.new_empty(input, (0,))
+        d_bias = None
     return (d_input, d_weight, d_bias)
 
 # @register_decomposition(aten.addmm)

test/test_ops.py

@@ -1313,7 +1313,7 @@ def get_names(inpt):
                 f.write(f'{op}\n')
 
     def test_decompositions_torchscriptable(self, device):
-        skip_list = []
+        skip_list = [torch.ops.aten.native_layer_norm_backward.default]
         for op, decomposition in decomposition_table.items():
             if op in skip_list:
                 continue