code: def test_relmha_adapter_init(self, n_head, proj_dim):
      torch.random.manual_seed(0)
      x = torch.randn(2, 32, 50)
      lengths = torch.randint(1, x.size(1), size=(x.size(0),))
      lengths[torch.randint(0, x.size(0), size=(1,))[0]] = x.size(1)
  
      adapter = adapter_modules.RelPositionMultiHeadAttentionAdapter(
          n_head=n_head, n_feat=50, dropout_rate=0.0, proj_dim=proj_dim
      )
      relpos_enc = adapter_modules.RelPositionalEncodingAdapter(
          d_model=50
      )
  
      pad_mask, att_mask = get_mask(lengths)
      relpos_enc.extend_pe(lengths.max(), device="cpu")
  
      with torch.no_grad():
          assert adapter.linear_out.weight.sum() == 0
          if (
              hasattr(adapter.linear_out, "bias")
              and adapter.linear_out.bias is not None
          ):
              assert adapter.linear_out.bias.sum() == 0
  
          _, pos_emb = relpos_enc(x)
          out = adapter(x, x, x, att_mask, pos_emb)
          assert out.sum().abs() <= 1e-8
          assert out.shape == x.shape
  
imports: import pytest
  import torch
  from nemo.collections.asr.parts.submodules import adapters
  from nemo.core.classes.mixins import adapter_mixin_strategies
  from nemo.utils import config_utils
label_desc: Use image node_id 6 for calling the TestASRAdapterModules obj's underlying member method code with example usage: obj.test_relmha_adapter_init(n_head, proj_dim) without return types