code: def test_multihead_attention_dtype(self, device, dtype):
      embed_dim = 128
      num_heads = 8
      sl = 10
      bs = 8
      model = (
          nn.MultiheadAttention(embed_dim, num_heads)
          .to(device)
          .to(dtype)
      )
      q = torch.randn(sl, bs, embed_dim, device=device, dtype=dtype)
      k = torch.randn(sl, bs, embed_dim, device=device, dtype=dtype)
      v = torch.randn(sl, bs, embed_dim, device=device, dtype=dtype)
      out = model(q, k, v)
      self.assertEqual(q.size(), out[0].size())
      self.assertEqual(dtype, out[0].dtype)
  
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 3 for calling the TestMultiheadAttentionNNDeviceType obj's underlying member method code with example usage: obj.test_multihead_attention_dtype(device, dtype) without return types