class_docstr: Test the process of importing the models from fairseq.
  
  Test methods in this test suite check the following things
  1. Models loaded with fairseq cane be imported.
  2. The same model can be recreated without fairseq.
class_docstr_tok: ["Test","the","process","of","importing","the","models","from","fairseq",".","Test","methods","in","this","test","suite","check","the","following","things","1",".","Models","loaded","with","fairseq","cane","be","imported",".","2",".","The","same","model","can","be","recreated","without","fairseq","."]
docstr: Fintuned wav2vec2 models from fairseq can be imported and yields the same results
docstr_tok: ["Fintuned","wav2vec2","models","from","fairseq","can","be","imported","and","yields","the","same","results"]
code: def test_import_finetuning_model(self, config, _):
      """Fintuned wav2vec2 models from fairseq can be imported and yields the same results"""
      num_out = 28
      batch_size, num_frames = 3, 1024
  
      original = self._get_model(config, num_out).eval()
      imported = import_fairseq_model(original).eval()
  
      # Without mask
      torch.manual_seed(0)
      x = torch.randn(batch_size, num_frames)
      ref = original(x, torch.zeros_like(x))["encoder_out"].transpose(
          0, 1
      )
      hyp, _ = imported(x)
      self.assertEqual(ref, hyp)
  
      # With mask
      lengths = torch.randint(
          low=0,
          high=num_frames,
          size=[
              batch_size,
          ],
      )
      mask = (
          torch.arange(num_frames).expand(batch_size, num_frames)
          >= lengths[:, None]
      )
      ref = original(x, mask)["encoder_out"].transpose(0, 1)
      hyp, output_lengths = imported(x, lengths)
      for i, l in enumerate(output_lengths):
          self.assertEqual(ref[i, :l, ...], hyp[i, :l, ...])
  
file_path: audio/test/torchaudio_unittest/models/wav2vec2/fairseq_integration_test.py
imports: import json
  import torch
  from parameterized import parameterized
  from torchaudio.models.wav2vec2 import hubert_base, hubert_large, hubert_xlarge, wav2vec2_base, wav2vec2_large, wav2vec2_large_lv60k, wav2vec2_xlsr_1b, wav2vec2_xlsr_2b, wav2vec2_xlsr_300m
  from torchaudio.models.wav2vec2.utils import import_fairseq_model
  from torchaudio_unittest.common_utils import get_asset_path, skipIfCudaSmallMemory, skipIfNoModule, TorchaudioTestCase
label_desc: Use image node_id 8 for calling the TestFairseqIntegration obj's underlying member method code with example usage: obj.test_import_finetuning_model(config, _) without return types