code: def hybrid_forward(self, F, inputs, **kwargs):
          # pylint: disable=unused-argument
          r
          current_input = inputs
          for layer in self.hnet:
              projected_input = layer(current_input)
              linear_transform = current_input
              nonlinear_transform, transform_gate = projected_input.split(num_outputs=2, axis=-1)
              nonlinear_transform = self._activation(nonlinear_transform)
              transform_gate = transform_gate.sigmoid()
              current_input = (1 - transform_gate) * linear_transform + \
                              transform_gate * nonlinear_transform
          return current_input
docs: r"""
          Forward computation for highway layer
  
          Parameters
          ----------
          inputs: NDArray
              The input tensor is of shape `(..., input_size)`.
  
          Returns
          ----------
          outputs: NDArray
              The output tensor is of the same shape with input tensor `(..., input_size)`.