code: def __init__(self, ckpt_path, layer, max_chunk=1600000):
      (
          model,
          cfg,
          task,
      ) = fairseq.checkpoint_utils.load_model_ensemble_and_task(
          [ckpt_path]
      )
      self.model = model[0].eval().cuda()
      self.task = task
      self.layer = layer  # assume this is 1-based like HuBERT
      self.max_chunk = max_chunk
      logger.info(f"TASK CONFIG:\n{self.task.cfg}")
      logger.info(f" max_chunk = {self.max_chunk}")
      logger.info(f" model:\n{self.model}")
  
file_path: fairseq/examples/hubert/simple_kmeans/dump_w2v2_feature.py
imports: import logging
  import os
  import sys
  import fairseq
  import soundfile
  import torch
  import torch.nn.functional
  from feature_utils import get_path_iterator, dump_feature
label_desc: Use image node_id 1 to create a new Wav2Vec2FeatureReader object from inherited base classes: object with example: obj = Wav2Vec2FeatureReader(ckpt_path, layer, max_chunk)