code: def reshape_heads_to_batch_dim(self, tensor):
      batch_size, seq_len, dim = tensor.shape
      head_size = self.heads
      tensor = tensor.reshape(
          [batch_size, seq_len, head_size, dim // head_size]
      )
      tensor = tensor.transpose([0, 2, 1, 3]).reshape(
          [batch_size * head_size, seq_len, dim // head_size]
      )
      return tensor
  
imports: import math
  from inspect import isfunction
  import numpy
  import paddle
  import paddle.nn
  import paddle.nn.functional
label_desc: Use image node_id 2 for calling the CrossAttention obj's underlying member method code with example usage: obj.reshape_heads_to_batch_dim(tensor) and returns: tensor