code: def test_multihead_attn_in_proj_weight_none(self, device, dtype):
      # Setting kdim == vdim == 2 means that vdim != embed_dim
      # will cause the logic to use per-input project weights, thereby
      # forcing self.in_proj_weight = None
      mha = torch.nn.MultiheadAttention(
          4, 4, vdim=2, kdim=2, dtype=dtype, device=device
      )
      query = torch.rand(4, 4, 4, dtype=dtype, device=device)
      key = torch.rand(4, 4, 2, dtype=dtype, device=device)
      mha(query, key, key)
  
imports: import contextlib
  import random
  import unittest
  import unittest.mock
  from torch.nn import MultiheadAttention
  from torch.testing._internal.common_device_type import instantiate_device_type_tests, dtypes, onlyCUDAAndPRIVATEUSE1
  from torch.testing._internal.common_nn import NNTestCase
  from torch.testing._internal.common_utils import run_tests, TEST_NUMPY, TEST_WITH_CROSSREF, parametrize, instantiate_parametrized_tests
  import torch.nn
  import torch
label_desc: Use image node_id 8 for calling the TestMultiheadAttentionNNDeviceType obj's underlying member method code with example usage: obj.test_multihead_attn_in_proj_weight_none(device, dtype) without return types