docstr: Initialize an empty AttentionStore :param step_index: used to visualize only a specific step in the diffusion
  process
code: def __init__(self, attn_res):
      """
      Initialize an empty AttentionStore :param step_index: used to visualize only a specific step in the diffusion
      process
      """
      self.num_att_layers = -1
      self.cur_att_layer = 0
      self.step_store = self.get_empty_store()
      self.attention_store = {}
      self.curr_step_index = 0
      self.attn_res = attn_res
  
imports: import inspect
  import math
  from typing import Any, Callable, Dict, List, Optional, Tuple, Union
  import numpy
  import torch
  from torch.nn import functional
  from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
  from ...image_processor import VaeImageProcessor
  from ...loaders import LoraLoaderMixin, TextualInversionLoaderMixin
  from ...models import AutoencoderKL, UNet2DConditionModel
  from ...models.attention_processor import Attention
  from ...models.lora import adjust_lora_scale_text_encoder
  from ...schedulers import KarrasDiffusionSchedulers
  from ...utils import USE_PEFT_BACKEND, deprecate, logging, replace_example_docstring, scale_lora_layers, unscale_lora_layers
  from ...utils.torch_utils import randn_tensor
  from ..pipeline_utils import DiffusionPipeline
  from ..stable_diffusion import StableDiffusionPipelineOutput
  from ..stable_diffusion.safety_checker import StableDiffusionSafetyChecker
label_desc: Use image node_id 7 to create a new AttentionStore object  with example: obj = AttentionStore(attn_res)