code: def test_torch_complex_constructor_with_tensor(self):
      tensors = [
          torch.rand(1),
          torch.randint(-5, 5, (1,)),
          torch.tensor([False]),
      ]
  
      def fn_tensor_float(real, img: float):
          return complex(real, img)
  
      def fn_tensor_int(real, img: int):
          return complex(real, img)
  
      def fn_tensor_bool(real, img: bool):
          return complex(real, img)
  
      def fn_float_tensor(real: float, img):
          return complex(real, img)
  
      def fn_int_tensor(real: int, img):
          return complex(real, img)
  
      def fn_bool_tensor(real: bool, img):
          return complex(real, img)
  
      for tensor in tensors:
          self.checkScript(fn_tensor_float, (tensor, 1.2))
          self.checkScript(fn_tensor_int, (tensor, 3))
          self.checkScript(fn_tensor_bool, (tensor, True))
  
          self.checkScript(fn_float_tensor, (1.2, tensor))
          self.checkScript(fn_int_tensor, (3, tensor))
          self.checkScript(fn_bool_tensor, (True, tensor))
  
      def fn_tensor_tensor(real, img):
          return complex(real, img) + complex(2)
  
      for x, y in product(tensors, tensors):
          self.checkScript(
              fn_tensor_tensor,
              (
                  x,
                  y,
              ),
          )
  
imports: import torch
  import os
  import sys
  from torch.testing._internal.jit_utils import JitTestCase, execWrapper
  from torch.testing._internal.common_utils import IS_MACOS
  from typing import List, Dict
  from itertools import product
  from textwrap import dedent
  import cmath
label_desc: Use image node_id 9 for calling the TestComplex obj's underlying member method code with example usage: obj.test_torch_complex_constructor_with_tensor() and returns: complex, complex, complex, complex, complex, complex, unknown