code: def synthesize_data():
      img = torch.rand(gpc.config.BATCH_SIZE, 3, 32, 32)
      label = torch.randint(
          low=0, high=10, size=(gpc.config.BATCH_SIZE,)
      )
      return img, label
  
file_path: ColossalAI/examples/tutorial/auto_parallel/auto_parallel_with_resnet.py
imports: import torch
  from torchvision.models import resnet50
  from tqdm import tqdm
  import colossalai
  from colossalai.auto_parallel.tensor_shard.initialize import initialize_model
  from colossalai.device.device_mesh import DeviceMesh
  from colossalai.legacy.core import global_context
  from colossalai.logging import get_dist_logger
  from colossalai.nn.lr_scheduler import CosineAnnealingLR
label_desc: Use image node_id 1 for calling a global function with example usage: synthesize_data() and returns: img,  label