code: def test_perceiver_create_cross_attention(self):
      num_q_channels = 10
      num_heads = 5
      batch_size = 2
      dropout = 0.2
      layer = create_self_attention(
          num_channels=num_q_channels,
          num_heads=num_heads,
          dropout=dropout,
      )
      q_tensor = torch.rand(batch_size, num_q_channels, num_q_channels)
      out = layer(q_tensor)  # torch.Size([2, 10, 10])
      self.assertTrue(out.shape == torch.Size([2, 10, 10]))
  
imports: import unittest
  import torch
  from towhee.models.perceiver.create_self_attention import create_self_attention
label_desc: Use image node_id 1 for calling the PerceiverCreateCrossAttentionTest obj's underlying member method code with example usage: obj.test_perceiver_create_cross_attention() without return types