code: def state_dict(self):
      return {
          CURRICULUM_LEARNING_BATCH: self.batch,
          CURRICULUM_LEARNING_CONSUMED_SAMPLES: self.consumed_samples,
          CURRICULUM_LEARNING_STEP: self.curriculum_step,
          CURRICULUM_LEARNING_CURRENT_DIFFICULTIES: self.current_difficulties,
          CURRICULUM_LEARNING_DATA_CLUSTER_PATHS: self.data_cluster_paths,
          CURRICULUM_LEARNING_DATA_CLUSTER_CURRENT_POSITION: self.data_cluster_current_position,
          CURRICULUM_LEARNING_NP_RNG_STATE: np.random.get_state(),
      }
  
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 13 for calling the DeepSpeedDataSampler obj's underlying member method code with example usage: obj.state_dict() and returns: dict