code: def test_tensor_ctr(self):
      test_device = get_test_device()
      inp = torch.tensor([[1, 2, 3, 4, 5]], device=test_device)
      inp_lazy = torch.tensor([[1, 2, 3, 4, 5]], device="lazy")
  
      def foo(x):
          # Calling a view op to ensure that functionalization wrapping occurs.
          return x.view(-1)
  
      out_ref = foo(inp)
      out = foo(inp_lazy)
      torch.testing.assert_close(out_ref.cpu(), out.cpu())
  
imports: from typing import Sequence
  import torch
  import functools
  from torch.testing._internal.common_utils import run_tests, TestCase
  from torch.testing._internal.jit_utils import JitTestCase
  from torch.testing._internal.common_methods_invocations import op_db
  from torch.testing._internal.common_device_type import ops, instantiate_device_type_tests
  import torch._lazy
  import torch._lazy.config
  import torch._lazy.metrics
  import torch._lazy.ir_cache
  import torch._lazy.ts_backend
  import itertools
  import yaml
  import os
  import pathlib
  from unittest import skip
label_desc: Use image node_id 3 for calling the TestLazyTensor obj's underlying member method code with example usage: obj.test_tensor_ctr() and returns: x