code: def test_window_streaming_e2e_encoder_and_ctc_with_offline_attention():
      args = make_arg()
      model = th_asr.E2E(10, 5, args)
      asr = WindowStreamingE2E(model, args)
      in_data = np.random.randn(100, 10)
      for i in range(2):
          asr.accept_input(in_data)
      asr.decode_with_attention_offline()
  
imports: from __future__ import division
  import argparse
  import importlib
  import os
  import tempfile
  from test.utils_test import make_dummy_json
  import chainer
  import numpy
  import pytest
  import torch
  import espnet.nets.chainer_backend.e2e_asr
  import espnet.nets.pytorch_backend.e2e_asr
  from espnet.asr import asr_utils
  from espnet.nets.pytorch_backend.nets_utils import pad_list
  from espnet.nets.pytorch_backend.streaming.segment import SegmentStreamingE2E
  from espnet.nets.pytorch_backend.streaming.window import WindowStreamingE2E
  from espnet.utils.training.batchfy import make_batchset
label_desc: Use image node_id 5 for calling a global function with example usage: test_window_streaming_e2e_encoder_and_ctc_with_offline_attention() without return types