code: def gen_inputs(
      self, input_dim, batch_size, num_frames, right_context_length
  ):
      input = torch.rand(batch_size, num_frames, input_dim).to(
          device=self.device, dtype=self.dtype
      )
      lengths = torch.randint(
          1, num_frames - right_context_length, (batch_size,)
      ).to(device=self.device, dtype=self.dtype)
      return input, lengths
  
file_path: audio/test/torchaudio_unittest/models/emformer/emformer_test_impl.py
imports: from abc import ABC, abstractmethod
  import torch
  from torchaudio.models import Emformer
  from torchaudio_unittest.common_utils import TestBaseMixin, torch_script
label_desc: Use image node_id 2 for calling the EmformerTestImpl obj's underlying member method code with example usage: obj.gen_inputs(input_dim, batch_size, num_frames, right_context_length) and returns: input,  lengths