code: def __init__(self, attnstore, place_in_unet):
      super().__init__()
      self.attnstore = attnstore
      self.place_in_unet = place_in_unet
  
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 .None import StableDiffusionPipelineOutput
  from .safety_checker import StableDiffusionSafetyChecker
label_desc: Use image node_id 1 to create a new AttendExciteAttnProcessor object  with example: obj = AttendExciteAttnProcessor(attnstore, place_in_unet)