code: def sample_from_clusters(self):
      num_clusters = len(self.data_clusters)
      weight_sum = sum(self.data_cluster_sizes)
      weights = [x / weight_sum for x in self.data_cluster_sizes]
      samples = self.np_rng.choice(
          num_clusters, self.global_batch_size, replace=True, p=weights
      )
      samples = np.bincount(samples, minlength=num_clusters)
      return samples
  
imports: import torch
  import os
  import numpy
  import deepspeed.comm
  from deepspeed.utils import logger
  from deepspeed.accelerator import get_accelerator
  from ..constants import *
  from ..curriculum_scheduler import CurriculumScheduler
  from .indexed_dataset import MMapIndexedDataset
  from .utils import create_mmap_dataset_builder, close_mmap_dataset_builder, find_fit_int_dtype
label_desc: Use image node_id 8 for calling the DeepSpeedDataSampler obj's underlying member method code with example usage: obj.sample_from_clusters() and returns: samples