code: def create_gaussian_diffusion(
      steps: int = 1000,
      learn_sigma: bool = False,
      sigma_small: bool = False,
      noise_schedule: str = "linear",
      use_kl: bool = False,
      predict_xstart: bool = False,
      rescale_timesteps: bool = False,
      rescale_learned_sigmas: bool = False,
      timestep_respacing: Union[List[int], str] = "",
  ) -> respace.SpacedDiffusion:
      """
      Adapted from `improved_diffusion.train_util.create_gaussian_diffusion`
      (https://github.com/openai/improved-diffusion)
      to replace the `space_timesteps` function.
      """
      betas = gd.get_named_beta_schedule(noise_schedule, steps)
      if use_kl:
          loss_type = gd.LossType.RESCALED_KL
      elif rescale_learned_sigmas:
          loss_type = gd.LossType.RESCALED_MSE
      else:
          loss_type = gd.LossType.MSE
      if not timestep_respacing:
          timestep_respacing = [steps]
      return respace.SpacedDiffusion(
          use_timesteps=space_timesteps(steps, timestep_respacing),
          betas=betas,
          model_mean_type=(
              gd.ModelMeanType.EPSILON
              if not predict_xstart
              else gd.ModelMeanType.START_X
          ),
          model_var_type=(
              (
                  gd.ModelVarType.FIXED_LARGE
                  if not sigma_small
                  else gd.ModelVarType.FIXED_SMALL
              )
              if not learn_sigma
              else gd.ModelVarType.LEARNED_RANGE
          ),
          loss_type=loss_type,
          rescale_timesteps=rescale_timesteps,
      )
  
imports: import copy
  import hashlib
  from pathlib import Path
  from typing import List, Set, Union
  import numpy
  import plotly.graph_objs
  import torch
  import torch.distributed
  import wandb
  from hydra.core.hydra_config import HydraConfig
  from hydra.utils import instantiate, to_absolute_path
  from improved_diffusion import dist_util
  from improved_diffusion import gaussian_diffusion
  from improved_diffusion import logger, respace, train_util
  from omegaconf import DictConfig, OmegaConf
label_desc: Use image node_id 6 for calling a global function with example usage: create_gaussian_diffusion(steps, learn_sigma, sigma_small, noise_schedule, use_kl, predict_xstart, rescale_timesteps, rescale_learned_sigmas, timestep_respacing) and returns: respace