code: def retrieve_latents(
      encoder_output: torch.Tensor,
      generator: Optional[torch.Generator] = None,
      sample_mode: str = "sample",
  ):
      if (
          hasattr(encoder_output, "latent_dist")
          and sample_mode == "sample"
      ):
          return encoder_output.latent_dist.sample(generator)
      elif (
          hasattr(encoder_output, "latent_dist")
          and sample_mode == "argmax"
      ):
          return encoder_output.latent_dist.mode()
      elif hasattr(encoder_output, "latents"):
          return encoder_output.latents
      else:
          raise AttributeError(
              "Could not access latents of provided encoder_output"
          )
  
imports: import inspect
  import os
  from typing import Any, Callable, Dict, List, Optional, Tuple, Union
  import torch
  from PIL import Image
  from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer, CLIPVisionModelWithProjection
  from diffusers import DiffusionPipeline, StableDiffusionXLPipeline
  from diffusers.image_processor import PipelineImageInput, VaeImageProcessor
  from diffusers.loaders import FromSingleFileMixin, IPAdapterMixin, LoraLoaderMixin, TextualInversionLoaderMixin
  from diffusers.models import AutoencoderKL, ImageProjection, UNet2DConditionModel
  from diffusers.models.attention_processor import AttnProcessor2_0, FusedAttnProcessor2_0, LoRAAttnProcessor2_0, LoRAXFormersAttnProcessor, XFormersAttnProcessor
  from diffusers.pipelines.stable_diffusion_xl.pipeline_output import StableDiffusionXLPipelineOutput
  from diffusers.schedulers import KarrasDiffusionSchedulers
  from diffusers.utils import deprecate, is_accelerate_available, is_accelerate_version, is_invisible_watermark_available, logging, replace_example_docstring
  from diffusers.utils.torch_utils import randn_tensor
label_desc: Use image node_id 6 for calling a global function with example usage: retrieve_latents(encoder_output, generator, sample_mode) and returns: encoder_output, encoder_output, encoder_output