code: def create_mlp_cls(
      embed_dim, mlp_ratio, act_layer, fused_dense_gelu_dense, bf16
  ):
      inner_dim = int(embed_dim * mlp_ratio)
      if not fused_dense_gelu_dense:
          mlp_cls = partial(
              Mlp, hidden_features=inner_dim, activation=act_layer()
          )
      else:
          mlp_cls = partial(
              FusedDenseGeluDense, hidden_features=inner_dim, bf16=bf16
          )
      return mlp_cls
  
imports: import math
  from functools import partial
  from copy import deepcopy
  import torch
  import torch.nn
  import torch.nn.functional
  from torch.nn.init import trunc_normal_
  from timm.models.helpers import named_apply
  from timm.models.layers import PatchEmbed
  from src.models.modules.mha import MHA
  from src.models.modules.mlp import Mlp, FusedDenseGeluDense
  from src.models.modules.block import Block
label_desc: Use image node_id 2 for calling a global function with example usage: create_mlp_cls(embed_dim, mlp_ratio, act_layer, fused_dense_gelu_dense, bf16) and returns: mlp_cls