code: def generate(self):
      data = torch.rand(self.batch_size, 3, 224, 224)
      label = torch.randint(low=0, high=10, size=(self.batch_size,))
      return data, label
  
file_path: ColossalAI/examples/tutorial/hybrid_parallel/train.py
imports: import os
  import torch
  from titans.model.vit.vit import _create_vit_model
  from tqdm import tqdm
  import colossalai
  from colossalai.legacy.context import ParallelMode
  from colossalai.legacy.core import global_context
  from colossalai.legacy.nn import CrossEntropyLoss
  from colossalai.legacy.pipeline.pipelinable import PipelinableContext
  from colossalai.logging import get_dist_logger
  from colossalai.nn.lr_scheduler import CosineAnnealingWarmupLR
  from colossalai.utils import is_using_pp
label_desc: Use image node_id 2 for calling the DummyDataloader obj's underlying member method code with example usage: obj.generate() and returns: data,  label