code: def _compute_attn_score(
      self,
      F,
      q: Tensor,
      k: Tensor,
      mask: Optional[Tensor],
  ) -> Tensor:
      score = F.batch_dot(lhs=q, rhs=k, transpose_b=True)
      score = self._apply_mask(F, score, mask)
      score = score / (math.sqrt(self.d_head) * self.temperature)
      score = F.softmax(score, axis=-1)
      score = self.dropout(score)
      return score
  
imports: import math
  from typing import List, Optional, Tuple
  from mxnet import init
  from mxnet.gluon import HybridBlock, nn, rnn
  from gluonts.core.component import validated
  from gluonts.mx import Tensor
label_desc: Use image node_id 6 for calling the SelfAttention obj's underlying member method code with example usage: obj._compute_attn_score(F, q, k, mask) and returns: score