code: def create_mixer_cls(
      num_heads,
      qkv_bias,
      attn_drop,
      use_flash_attn,
      fused_bias_fc,
      bf16,
  ):
      mixer_cls = partial(
          MHA,
          num_heads=num_heads,
          bias=qkv_bias,
          dropout=attn_drop,
          fused_bias_fc=fused_bias_fc,
          use_flash_attn=use_flash_attn,
          bf16=bf16,
      )
      return mixer_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 1 for calling a global function with example usage: create_mixer_cls(num_heads, qkv_bias, attn_drop, use_flash_attn, fused_bias_fc, bf16) and returns: mixer_cls