code: def _compute_qkv(self, F, x: Tensor) -> Tuple[Tensor, Tensor, Tensor]:
      cx = F.slice_axis(
          x, axis=1, begin=-self.prediction_length, end=None
      )
      q = self.q_proj(cx)
      k = self.k_proj(x)
      q = self._split_head(F, q)
      k = self._split_head(F, k)
      v = self.v_proj(x)
      if self.share_values:
          v = F.broadcast_like(v.expand_dims(axis=1), k)
      else:
          v = self._split_head(F, v)
      return q, k, v
  
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 4 for calling the SelfAttention obj's underlying member method code with example usage: obj._compute_qkv(F, x) and returns: q,  k,  v