Update unpacked pattern to use instead of due to conversion issue when input data types are mismatched

Author: gs-olive

core/lowering/passes/device_casting.cpp

@@ -23,18 +23,7 @@ void UnpackAndCastMaskedFill(std::shared_ptr<torch::jit::Graph>& graph) {
       %false: bool = prim::Constant[value=0]()
       %mask_cuda: Tensor = aten::to(%mask, %device, %dtype, %false, %false)
       %self_cuda: Tensor = aten::to(%self, %device, %dtype, %false, %false)
-
-      # Value is cast to type of original tensor and value defaults to float
-      %is_float: bool = aten::is_floating_point(%self)
-      %out: Tensor = prim::If(%is_float)
-        block0():
-          %no_cast: Tensor = aten::masked_fill(%self_cuda, %mask_cuda, %value)
-          -> (%no_cast)
-        block1():
-          %value_int: int = aten::Int(%value)
-          %casted_int: Tensor = aten::masked_fill(%self_cuda, %mask_cuda, %value_int)
-          -> (%casted_int)
-
+      %out: Tensor = aten::masked_fill_(%self_cuda, %mask_cuda, %value)
       return (%out))IR";
 
   torch::jit::SubgraphRewriter masked_fill_rewriter;