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: import argparse
  from collections import defaultdict
  from functools import reduce
  import gc
  import logging
  import math
  import operator
  import time
  from datasets.wikitext2_data import get_real_dataloaders
  from datasets.wikitext2_data import get_synthetic_dataloaders
  from models import transformer_lm
  import numpy
  import torch
  import torch.distributed
  import torch.multiprocessing
  from torch.nn.parallel import DistributedDataParallel
  from torch.optim import Adam
  from benchmarks.golden_configs.lm_wikitext2 import FSDP
  from fairscale.nn import auto_wrap, default_auto_wrap_policy, enable_wrap
  from fairscale.nn.data_parallel import FullyShardedDataParallel
label_desc: Use image node_id 9 for calling a global function with example usage: get_fake_dataloader(lm_dataloader_len, args) and returns: FakeDataset, fake_input, lm_dataloader_len