class_docstr: A module which performs QKV attention and splits in a different order.
class_docstr_tok: ["A","module","which","performs","QKV","attention","and","splits","in","a","different","order","."]
code: def count_flops(model, _x, y):
      return count_flops_attn(model, _x, y)
  
imports: from abc import abstractmethod
  import math
  import numpy
  import torch
  import torch.nn
  import torch.nn.functional
  from ldm.modules.diffusionmodules.util import checkpoint, conv_nd, linear, avg_pool_nd, zero_module, normalization, timestep_embedding
  from ldm.modules.attention import SpatialTransformer
  from ldm.util import exists
label_desc: Use image node_id 3 for calling the QKVAttention obj's underlying member method code with example usage: obj.count_flops(model, _x, y) and returns: count_flops_attn