docstr: Forward missing attributes to the wrapped module.
docstr_tok: ["Forward","missing","attributes","to","the","wrapped","module","."]
code: def __getattr__(self, name: str):
      """Forward missing attributes to the wrapped module."""
      try:
          return super().__getattr__(name)  # defer to nn.Module's logic
      except AttributeError:
          return getattr(self.model, name)
  
imports: import argparse
  import logging
  import math
  import os
  import random
  from pathlib import Path
  import datasets
  import evaluate
  import torch
  import transformers
  from accelerate import Accelerator
  from accelerate.logging import get_logger
  from accelerate.utils import set_seed
  from datasets import DatasetDict, load_dataset
  from huggingface_hub import Repository, create_repo
  from torch import nn
  from torch.utils.data import DataLoader
  from tqdm import tqdm
  from transformers import AutoModel, AutoTokenizer, SchedulerType, default_data_collator, get_scheduler
  from transformers.utils import get_full_repo_name
  from peft import LoraConfig, TaskType, get_peft_model
label_desc: Use image node_id 4 for calling the AutoModelForSentenceEmbedding obj's underlying member method code with example usage: obj.__getattr__(name) and returns: super, getattr