code: def transpose_for_scores(self, x):
      new_x_shape = list(x.shape[:-1]) + [
          self.num_attention_heads,
          self.attention_head_size,
      ]
      x = x.reshape(new_x_shape)
      return x.transpose([0, 2, 1, 3])
  
imports: import copy
  import math
  import numpy
  import paddle
  import paddle.nn
  import paddle.nn.functional
  from medicalseg.cvlibs import manager
  from medicalseg.utils import load_pretrained_model
label_desc: Use image node_id 2 for calling the Attention obj's underlying member method code with example usage: obj.transpose_for_scores(x) and returns: x