code: def hybrid_forward(self, F, x: Tensor) -> Tensor:
      val, gate = F.split(x, axis=self.axis, num_outputs=2)
      if self.nonlinear:
          val = F.tanh(val)
      gate = F.sigmoid(gate)
      return F.broadcast_mul(gate, val)
  
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 2 for calling the GatedLinearUnit obj's underlying member method code with example usage: obj.hybrid_forward(F, x) and returns: F