code: def save_encrypted_dataset(dataset_path, save_path, secret_key):
      dataset = load_from_disk(dataset_path, keep_in_memory=True)
      # This will save the encrypted dataset into disk
      torch.save(dataset, save_path, encryption_key=secret_key)
  
imports: from torch.utils.data import DataLoader
  import torch
  import torch.optim
  from contextlib import nullcontext
  import torch.nn.functional
  import os
  import torch.nn
  import time
  from bigdl.nano.pytorch.patching import patch_encryption
  from bigdl.nano.pytorch.encryption import EncryptedDataset
  import logging
  from bigdl.ppml.kms.ehsm.client import generate_primary_key, generate_data_key, get_data_key_plaintext
  from datasets.load import load_from_disk
  import argparse
  from transformers import BertTokenizer, BertModel, AdamW
label_desc: Use image node_id 3 for calling a global function with example usage: save_encrypted_dataset(dataset_path, save_path, secret_key) without return types