code: def attention(self, client_module):
      qw = client_module.to_q.weight
      kw = client_module.to_k.weight
      vw = client_module.to_v.weight
  
      if qw.shape[1] == kw.shape[1]:
          qkvw = Parameter(
              torch.cat((qw, kw, vw), dim=0), requires_grad=False
          )
  
          return (
              qkvw,
              client_module.to_out[0].weight,
              client_module.to_out[0].bias,
              qw.shape[-1],
              client_module.heads,
          )
      else:
          # return None
          # kvw = Parameter(torch.cat((kw, vw), dim=0), requires_grad=False)
          return (
              qw,
              kw,
              vw,
              client_module.to_out[0].weight,
              client_module.to_out[0].bias,
              qw.shape[-1],
              client_module.heads,
          )
  
file_path: DeepSpeed/deepspeed/module_inject/containers/unet.py
imports: import torch
  from torch.nn.parameter import Parameter
  from ..policy import DSPolicy
  from ...model_implementations.diffusers.unet import DSUNet
label_desc: Use image node_id 5 for calling the UNetPolicy obj's underlying member method code with example usage: obj.attention(client_module) and returns: qkvw,  client_module,  client_module,  qw,  client_module, qw,  kw,  vw,  client_module,  client_module,  qw,  client_module