class_docstr: A module which performs QKV attention. Matches legacy QKVAttention + input/ouput heads shaping
class_docstr_tok: ["A","module","which","performs","QKV","attention",".","Matches","legacy","QKVAttention","+","input\/ouput","heads","shaping"]
code: def count_flops(model, _x, y):
      return count_flops_attn(model, _x, y)
  
imports: import math
  from abc import abstractmethod
  import numpy
  import paddle
  import paddle.nn
  import paddle.nn.functional
  from .nn import avg_pool_nd
  from .nn import checkpoint
  from .nn import conv_nd
  from .nn import linear
  from .nn import normalization
  from .nn import SiLU
  from .nn import timestep_embedding
  from .nn import zero_module
label_desc: Use image node_id 3 for calling the QKVAttentionLegacy obj's underlying member method code with example usage: obj.count_flops(model, _x, y) and returns: count_flops_attn