code: def test_reparametrize_some_weights(self, functional_call):
      module = MockModule()
      weight = torch.tensor([[2.0]])
      bias = torch.tensor([5.0])
      buffer = torch.tensor([3.0])
      extra = torch.tensor([1.0])
  
      parameters = {"l1.weight": weight}
      x = torch.randn(1, 1)
      out = functional_call(module, parameters, x)
      self.assertEqual(out, x * weight + module.l1.bias + module.buffer)
  
      parameters = {"l1.weight": weight, "extra": extra}
      x = torch.randn(1, 1)
      out = functional_call(module, parameters, x)
      self.assertEqual(out, x * weight + module.l1.bias + module.buffer)
  
imports: import contextlib
  import os
  import re
  import subprocess
  import sys
  import unittest
  import torch
  import torch.nn.utils.stateless
  from torch.testing._internal.common_cuda import TEST_MULTIGPU
  from torch.testing._internal.common_utils import run_tests, TestCase, parametrize, instantiate_parametrized_tests, subtest
label_desc: Use image node_id 12 for calling the TestStatelessFunctionalAPI obj's underlying member method code with example usage: obj.test_reparametrize_some_weights(functional_call) without return types