code: def __init__(self, vec, name, step=None):
      self.vec = vec
      self.name = name
      self.step = step
      self.shape = None
      self.vectors = 0
      self.cached_checksum = None
      self.sd_checkpoint = None
      self.sd_checkpoint_name = None
      self.optimizer_state_dict = None
      self.filename = None
      self.hash = None
      self.shorthash = None
  
imports: import os
  from collections import namedtuple
  from contextlib import closing
  import torch
  import tqdm
  import html
  import datetime
  import csv
  import safetensors.torch
  import numpy
  from PIL import Image, PngImagePlugin
  from torch.utils.tensorboard import SummaryWriter
  from modules import shared, devices, sd_hijack, sd_models, images, sd_samplers, sd_hijack_checkpoint, errors, hashes
  import modules.textual_inversion.dataset
  from modules.textual_inversion.learn_schedule import LearnRateScheduler
  from modules.textual_inversion.image_embedding import embedding_to_b64, embedding_from_b64, insert_image_data_embed, extract_image_data_embed, caption_image_overlay
  from modules.textual_inversion.logging import save_settings_to_file
label_desc: Use image node_id 1 to create a new Embedding object  with example: obj = Embedding(vec, name, step)