code: def __len__(self):
      return self._length
  
imports: import argparse
  import itertools
  import math
  import os
  import random
  from pathlib import Path
  import intel_extension_for_pytorch
  import numpy
  import PIL
  import torch
  import torch.nn.functional
  import torch.utils.checkpoint
  from accelerate import Accelerator
  from accelerate.logging import get_logger
  from accelerate.utils import ProjectConfiguration, set_seed
  from huggingface_hub import create_repo, upload_folder
  from packaging import version
  from PIL import Image
  from torch.utils.data import Dataset
  from torchvision import transforms
  from tqdm.auto import tqdm
  from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
  from diffusers import AutoencoderKL, DDPMScheduler, PNDMScheduler, StableDiffusionPipeline, UNet2DConditionModel
  from diffusers.optimization import get_scheduler
  from diffusers.pipelines.stable_diffusion import StableDiffusionSafetyChecker
  from diffusers.utils import check_min_version
label_desc: Use image node_id 2 for calling the TextualInversionDataset obj's underlying member method code with example usage: obj.__len__() and returns: self