code: def test_ffn_prune_for_adaprune_in_roberta(self, device: str):
      _, model = get_toy_model(
          device=device,
          architecture="roberta_base",
      )
      sample = mk_sample("en", device, batch_size=1)
      for layer in model.encoder.sentence_encoder.layers:
          fc1_original_size = layer.fc1.out_features
          remove_index = layer._get_fc_rank(remove_num=2)
          layer._prune_fc_layer(remove_index=remove_index)
          self.assertEqual(
              layer.fc1.out_features, fc1_original_size - 2
          )
  
      task_loss, _ = model.forward(**sample["net_input"])
  
imports: import functools
  import unittest
  from typing import Any, Dict, Sequence
  import fairseq
  import fairseq.options
  import fairseq.tasks
  import torch
  from tests.utils import dummy_dictionary
label_desc: Use image node_id 11 for calling the RobertaTest obj's underlying member method code with example usage: obj.test_ffn_prune_for_adaprune_in_roberta(device) without return types