code: def load_checkpoint_(self):
      (
          model,
          _,
          task,
      ) = fairseq.checkpoint_utils.load_model_ensemble_and_task(
          [self.checkpoint_path]
      )
      self.model = model[0].eval()
      self.model = self.model.to(self.device)
      for parameter in self.model.parameters():
          parameter.requires_grad_(False)
  
      self.should_normalize = task.cfg.normalize
  
file_path: textlesslib/textless/data/hubert_feature_reader.py
imports: import torch
  import fairseq
  import torch.nn.functional
label_desc: Use image node_id 2 for calling the HubertFeatureReader obj's underlying member method code with example usage: obj.load_checkpoint_() without return types