code: def move_to_cuda(batch, device):
      return {k: v.to(device) for k, v in batch.items()}
  
imports: import argparse
  import os
  from functools import partial
  from typing import Dict
  import torch
  import torch.distributed
  from datasets import load_dataset
  from huggingface_hub import snapshot_download
  from model.modeling_openmoe import OpenMoeForCausalLM, set_openmoe_args
  from model.openmoe_policy import OpenMoeForCausalLMPolicy
  from torch.utils.data import Dataset
  from tqdm import tqdm
  from transformers import T5Tokenizer
  from transformers.models.llama import LlamaConfig
  import colossalai
  from colossalai.booster import Booster
  from colossalai.booster.plugin.moe_hybrid_parallel_plugin import MoeHybridParallelPlugin
  from colossalai.cluster import DistCoordinator
  from colossalai.moe.layers import apply_load_balance
  from colossalai.moe.manager import MOE_MANAGER
  from colossalai.moe.utils import skip_init
  from colossalai.nn.optimizer import HybridAdam
  from colossalai.utils import get_current_device
label_desc: Use image node_id 1 for calling a global function with example usage: move_to_cuda(batch, device) and returns: unknown