code: def hybrid_forward(
      self,
      F,
      x: Tensor,
      c: Optional[Tensor] = None,
  ) -> Tensor:
      if self.add_skip:
          skip = self.skip_proj(x)
      else:
          skip = x
      if self.d_static > 0 and c is None:
          raise ValueError("static variable is expected.")
      if self.d_static == 0 and c is not None:
          raise ValueError("static variable is not accpeted.")
      if c is not None:
          x = F.concat(x, c, dim=-1)
      x = self.mlp(x)
      x = self.lnorm(F.broadcast_add(x, skip))
      return x
  
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 GatedResidualNetwork obj's underlying member method code with example usage: obj.hybrid_forward(F, x, c) and returns: x