code: def _postprocess(
      self, F, preds: Tensor, offset: Tensor, scale: Tensor
  ) -> Tensor:
      offset = F.expand_dims(offset, axis=-1)
      scale = F.expand_dims(scale, axis=-1)
      preds = preds * (scale + self.normalizer_eps) + offset
      return preds
  
imports: from typing import List, Optional, Tuple
  from mxnet import init
  from mxnet.gluon import HybridBlock, nn
  from gluonts.core.component import validated
  from gluonts.mx import Tensor
  from gluonts.mx.block.feature import FeatureEmbedder
  from gluonts.mx.block.quantile_output import QuantileOutput
  from gluonts.mx.util import weighted_average
  from ._layers import PosFFN, SelfAttention
label_desc: Use image node_id 3 for calling the SelfAttentionNetwork obj's underlying member method code with example usage: obj._postprocess(F, preds, offset, scale) and returns: preds