code: def compute_time_ids(self):
      # Adapted from pipeline.StableDiffusionXLPipeline._get_add_time_ids
      original_size = (self.config.resolution, self.config.resolution)
      target_size = (self.config.resolution, self.config.resolution)
      # crops_coords_top_left = (self.config.crops_coords_top_left_h, self.config.crops_coords_top_left_w)
      crops_coords_top_left = (0, 0)
      add_time_ids = list(
          original_size + crops_coords_top_left + target_size
      )
      add_time_ids = torch.tensor([add_time_ids])
      add_time_ids = add_time_ids.to(
          self.accelerator.device, dtype=self.weight_dtype
      )
      return add_time_ids
  
imports: import itertools
  import math
  import os
  import shutil
  import torch
  import torch.nn.functional
  from diffusers import StableDiffusionXLPipeline
  from diffusers.loaders import LoraLoaderMixin, text_encoder_lora_state_dict
  from diffusers.optimization import get_scheduler
  from huggingface_hub import create_repo, upload_folder
  from tqdm import tqdm
  from autotrain import logger
  from autotrain.trainers.dreambooth import utils
label_desc: Use image node_id 3 for calling the Trainer obj's underlying member method code with example usage: obj.compute_time_ids() and returns: add_time_ids