code: def test_freeze_embeddings_and_language_adapters(self):
      config = self.model_tester.prepare_config_and_inputs()[0]
      model = XmodForMaskedLM(config=config)
      num_trainable_params_before = sum(
          p.numel() for p in model.parameters() if p.requires_grad
      )
      model.freeze_embeddings_and_language_adapters()
      num_trainable_params_after = sum(
          p.numel() for p in model.parameters() if p.requires_grad
      )
      self.assertLess(
          num_trainable_params_after, num_trainable_params_before
      )
  
imports: import unittest
  from transformers import XLMRobertaTokenizer, is_torch_available
  from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
  from ...generation.test_utils import GenerationTesterMixin
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
  from ...test_pipeline_mixin import PipelineTesterMixin
label_desc: Use image node_id 18 for calling the XmodModelTest obj's underlying member method code with example usage: obj.test_freeze_embeddings_and_language_adapters() without return types