code: def mod_mlp_to_swiglu(model: nn.Module, op=None) -> nn.Module:
      def _mlp_to_swiglu(block: TimmBlock):
          block.mlp = TimmSwiGLU(block.mlp, op=op)
          return block
  
      return replace_module(model, TimmBlock, _mlp_to_swiglu)
  
imports: import itertools
  from functools import partial, reduce
  from typing import Iterator
  import timm
  import torch
  import torch.nn
  from timm.models.layers import Mlp
  from timm.models.vision_transformer import Attention
  from timm.models.vision_transformer import Block
  from torch.utils import benchmark
  from utils import benchmark_main_helper
  import xformers.ops
label_desc: Use image node_id 3 for calling a global function with example usage: mod_mlp_to_swiglu(model, op) and returns: replace_module, block