code: def get_fake_dataloader(lm_dataloader_len, args):
      fake_input = {"input": torch.zeros(args.batch_size)}
  
      class FakeDataset:
          def __getitem__(self, index):
              return fake_input
  
          def __len__(self):
              return lm_dataloader_len
  
      return FakeDataset()
  
imports: from collections import defaultdict
  import gc
  import logging
  import math
  import time
  import torch
  import torch.distributed
  from torch.distributed import rpc
  from torch.nn.parallel import DistributedDataParallel
  import utils
  from benchmarks.golden_configs.lm_wikitext2 import Pipe
  from fairscale.fair_dev.testing.testing import dist_init
  from fairscale.nn import Pipe
  from fairscale.nn.model_parallel import initialize_model_parallel
label_desc: Use image node_id 3 for calling a global function with example usage: get_fake_dataloader(lm_dataloader_len, args) and returns: FakeDataset, fake_input, lm_dataloader_len