code: def get_xformers_flash_attention_op(q, k, v):
      if not shared.cmd_opts.xformers_flash_attention:
          return None
  
      try:
          flash_attention_op = (
              xformers.ops.MemoryEfficientAttentionFlashAttentionOp
          )
          fw, bw = flash_attention_op
          if fw.supports(
              xformers.ops.fmha.Inputs(
                  query=q, key=k, value=v, attn_bias=None
              )
          ):
              return flash_attention_op
      except Exception as e:
          errors.display_once(e, "enabling flash attention")
  
      return None
  
imports: from __future__ import annotations
  import math
  import psutil
  import platform
  import torch
  from torch import einsum
  from ldm.util import default
  from einops import rearrange
  from modules import shared, errors, devices, sub_quadratic_attention
  from modules.hypernetworks import hypernetwork
  import ldm.modules.attention
  import ldm.modules.diffusionmodules.model
  import sgm.modules.attention
  import sgm.modules.diffusionmodules.model
label_desc: Use image node_id 16 for calling a global function with example usage: get_xformers_flash_attention_op(q, k, v) and returns: None, None, flash_attention_op