code: def random_dataset(
      total_samples, hidden_dim, device, dtype=torch.half
  ):
      train_data = torch.randn(
          total_samples, hidden_dim, device=device, dtype=dtype
      )
      train_label = torch.empty(
          total_samples, dtype=torch.long, device=device
      ).random_(hidden_dim)
      train_dataset = torch.utils.data.TensorDataset(
          train_data, train_label
      )
      return train_dataset
  
imports: import os
  import json
  import argparse
  import torch
  from collections import OrderedDict
  from deepspeed.pipe import PipelineModule, LayerSpec
  from deepspeed.moe.layer import MoE
  from deepspeed.accelerator import get_accelerator
  import deepspeed.comm
label_desc: Use image node_id 1 for calling a global function with example usage: random_dataset(total_samples, hidden_dim, device, dtype) and returns: train_dataset