code: def test_encoder_forward_ilens(whisper_encoder):
      input_tensor = torch.randn(
          4, 3200, device=next(whisper_encoder.parameters()).device
      )
      input_lens = torch.tensor(
          [500, 1000, 1600, 3200],
          device=next(whisper_encoder.parameters()).device,
      )
      xs_pad, olens, _ = whisper_encoder(input_tensor, input_lens)
  
      assert xs_pad.size() == torch.Size([4, 10, 384])
      assert torch.equal(olens.cpu(), torch.tensor([2, 3, 5, 10]))
  
file_path: espnet/test/espnet2/asr/encoder/test_whisper_encoder.py
imports: import sys
  import pytest
  import torch
  from packaging.version import parse
  from espnet2.asr.encoder.whisper_encoder import OpenAIWhisperEncoder
label_desc: Use image node_id 5 for calling a global function with example usage: test_encoder_forward_ilens(whisper_encoder) without return types