code: def test_attention_from_pretrained(
      pretrained_name, relevant_top_level_module
  ):
      torch.manual_seed(1234)
      pretrained = cached_transformers.get(
          pretrained_name, False
      ).eval()
  
      if "distilbert" in pretrained_name:
          encoder = pretrained.transformer
      else:
          encoder = pretrained.encoder
      # Hacky way to get a bert layer.
      pretrained_module = list(encoder.layer.modules())[1].attention
  
      torch.manual_seed(1234)
      module = AttentionLayer.from_pretrained_module(
          pretrained_name,
          relevant_module=None
          if relevant_top_level_module is None
          else f"{relevant_top_level_module}.encoder.layer.0.attention",
      ).eval()
  
      batch_size = 2
      seq_length = 15
      hidden_size = module.self.query.in_features
  
      hidden_states = torch.randn(batch_size, seq_length, hidden_size)
      attention_mask = torch.randint(0, 2, (batch_size, seq_length))
      attention_mask_hf = attention_mask[:, None, None, :]
      attention_mask_hf = (1.0 - attention_mask_hf) * -10e5
  
      torch.manual_seed(1234)
      output = module(
          hidden_states, attention_mask=attention_mask.squeeze()
      ).hidden_states
  
      torch.manual_seed(1234)
      hf_output = pretrained_module(
          hidden_states, attention_mask=attention_mask_hf
      )[0]
  
      assert torch.allclose(output, hf_output, atol=1e-04)
  
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 6 for calling a global function with example usage: test_attention_from_pretrained(pretrained_name, relevant_top_level_module) without return types