def test_fuse_duplicates_with_concat_output_accessor(self):
        """Fused_elementwise ops' that have the same input and elementwise ops
        and they have output accessors that write to the same concat output."""
        x = gen_input_tensor(shape=self.SHAPE, name="input_x")
        sigmoid1 = ops.elementwise(FuncEnum.SIGMOID)(x)
        sigmoid2 = ops.elementwise(FuncEnum.SIGMOID)(x)
        model_output = ops.concatenate()([sigmoid1, sigmoid2])
        model_output._attrs["is_output"] = True
        model_output._attrs["name"] = "output"

        x_pt = get_random_torch_tensor(self.SHAPE)
        sigmoid1_pt = torch.sigmoid(x_pt)
        sigmoid2_pt = torch.sigmoid(x_pt)
        y_pt = torch.concat([sigmoid1_pt, sigmoid2_pt])
        y_ait = torch.empty_like(y_pt)

        with compile_model(
            model_output,
            detect_target(),
            "/tmp",
            "fuse_duplicate_fused_elementwise_dups_with_accessors",
        ) as module:
            module.run_with_tensors({"input_x": x_pt}, {"output": y_ait})
            nsigmoid = self._count_fused_elementwise_ops(
                module.debug_sorted_graph, [FuncEnum.SIGMOID]
            )
            self.assertEqual(nsigmoid, 1)
            self.assertTrue(torch.allclose(y_pt, y_ait, atol=1e-2, rtol=1e-2))
Fused_elementwise ops' that have the same input and elementwise ops
        and they have output accessors that write to the same concat output.
tests/unittest/compiler/test_fuse_duplicate_fused_elementwise.py