code: def draw(self, num_negatives):
      rand_nums = np.random.choice(self.high, size=num_negatives)
      rand_nums = torch.from_numpy(rand_nums).long().cuda()
      return rand_nums
  
imports: import logging
  import math
  import pprint
  from typing import List, Union
  import numpy
  import torch
  from classy_vision.generic.distributed_util import all_reduce_mean, gather_from_all, get_rank
  from classy_vision.generic.util import is_pos_int
  from classy_vision.losses import ClassyLoss, register_loss
  from torch import nn
  from vissl.config import AttrDict
label_desc: Use image node_id 2 for calling the NumpySampler obj's underlying member method code with example usage: obj.draw(num_negatives) and returns: rand_nums