code: def test_attention(attention_params):
      attention_layer = AttentionLayer.from_params(
          attention_params.duplicate()
      ).eval()
  
      assert (
          attention_layer.self.num_attention_heads
          == attention_params["num_attention_heads"]
      )
      assert attention_layer.self.attention_head_size == int(
          attention_params["hidden_size"]
          / attention_params["num_attention_heads"]
      )
      assert (
          attention_layer.self.all_head_size
          == attention_params["num_attention_heads"]
          * attention_layer.self.attention_head_size
      )
      assert (
          attention_layer.self.query.in_features
          == attention_params["hidden_size"]
      )
      assert (
          attention_layer.self.key.in_features
          == attention_params["hidden_size"]
      )
      assert (
          attention_layer.self.value.in_features
          == attention_params["hidden_size"]
      )
      assert (
          attention_layer.self.dropout
          == attention_params["attention_dropout"]
      )
  
      assert (
          attention_layer.output.dense.in_features
          == attention_params["hidden_size"]
      )
      assert (
          attention_layer.output.dense.out_features
          == attention_params["hidden_size"]
      )
      assert (
          attention_layer.output.layer_norm.normalized_shape[0]
          == attention_params["hidden_size"]
      )
      assert (
          attention_layer.output.dropout.p
          == attention_params["hidden_dropout"]
      )
  
      attention_mask = torch.tensor([[0, 1, 0], [1, 1, 0]])
      attention_layer(
          torch.randn(2, 3, 6), attention_mask=attention_mask
      )
  
imports: import copy
  import torch
  import pytest
  from transformers.models.bert.configuration_bert import BertConfig
  from transformers.models.bert.modeling_bert import BertAttention, BertLayer
  from transformers.models.roberta.configuration_roberta import RobertaConfig
  from transformers.models.roberta.modeling_roberta import RobertaAttention, RobertaLayer
  from transformers.models.electra.configuration_electra import ElectraConfig
  from transformers.models.electra.modeling_electra import ElectraAttention, ElectraLayer
  from allennlp.common import Params, cached_transformers
  from allennlp.common.testing import run_distributed_test
  from allennlp.modules.transformer import AttentionLayer, TransformerLayer
label_desc: Use image node_id 3 for calling a global function with example usage: test_attention(attention_params) without return types