code: def create_inputs(batch_size, world_size, iterations, dtype):
      return [
          [
              torch.randn(batch_size, 10).type(dtype)
              for _ in range(world_size)
          ]
          for _ in range(iterations)
      ]
  
imports: import logging
  import os
  import unittest
  import torch
  import torch.distributed
  import torch.multiprocessing
  import torch.optim
  from torch.nn.parallel import DistributedDataParallel
  from pytorch_metric_learning.losses import ContrastiveLoss, CrossBatchMemory
  from pytorch_metric_learning.miners import PairMarginMiner
  from pytorch_metric_learning.utils import distributed
  from ..None import TEST_DEVICE, TEST_DTYPES
label_desc: Use image node_id 6 for calling a global function with example usage: create_inputs(batch_size, world_size, iterations, dtype) and returns: unknown