code: def test_calculate_plot_attention():
      idim, odim, ilens, olens = get_default_scope_inputs()
      train_args = get_default_train_args()
  
      model = E2E(idim, odim, train_args)
  
      batch = prepare_inputs(idim, odim, ilens, olens, is_cuda=False)
  
      assert model.calculate_all_attentions(*batch) == []
  
imports: import argparse
  import json
  import tempfile
  import numpy
  import pytest
  import torch
  from packaging.version import parse
  import espnet.lm.pytorch_backend.extlm
  import espnet.nets.pytorch_backend.lm.default
  from espnet.asr.pytorch_backend.asr_init import load_trained_model
  from espnet.nets.beam_search_transducer import BeamSearchTransducer
  from espnet.nets.pytorch_backend.e2e_asr_transducer import E2E
  from espnet.nets.pytorch_backend.nets_utils import pad_list
label_desc: Use image node_id 9 for calling a global function with example usage: test_calculate_plot_attention() without return types