class_docstr: Given a model and a flashlight dataset, pre-compute and store embeddings
  
  Args:
      input_root, str :
          Path to the flashlight dataset
      output_root, str :
          Desired output directory. Will be created if non-existent
      split, str :
          Dataset split
code: def copy_labels(self):
      self.require_output_path()
  
      labels = list(
          filter(
              lambda x: self.extension not in x,
              glob.glob(self.get_input_path("*")),
          )
      )
      for fname in tqdm.tqdm(labels):
          copy(fname, self.output_path)
  
imports: import argparse
  import glob
  import os
  from shutil import copy
  import h5py
  import numpy
  import soundfile
  import torch
  import tqdm
  import fairseq
  from torch import nn
label_desc: Use image node_id 8 for calling the EmbeddingDatasetWriter obj's underlying member method code with example usage: obj.copy_labels() without return types