code: def head_reshape(self, x):
      K = self.n_head
      D = self.head_dim
      x = x.view(x.size()[:-1] + (K, D))  # B x (M+L) x K x D
      x = x.transpose(1, 2).contiguous()  # B x K x (M+L) x D
      x = x.view(-1, x.size(-2), x.size(-1))  # B_K x (M+L) x D
      return x
  
imports: import math
  import torch
  import torch.nn
  import torch.nn.functional
  from fairseq.modules.layer_norm import LayerNorm
  from .adaptive_span_attention import AdaptiveSpan
label_desc: Use image node_id 2 for calling the MultiHeadSeqAttention obj's underlying member method code with example usage: obj.head_reshape(x) and returns: x