code: def forward(self, input):
      input = input.unsqueeze(0)
      input = input.unsqueeze(-2).expand(
          *input.shape[: -(len(input.shape) - 2)],
          self.out_features,
          self.in_features,
      )
      res = self.manifold.normdist2plane(
          input,
          self.bias,
          self.weight,
          signed=True,
          norm=self.weight_norm,
      )
      return res
  
imports: import logging
  import math
  import os
  import numpy
  import torch
  import torch.nn
  import torch.nn.functional
  from pythae.data.preprocessors import DataProcessor
  from pythae.models import AutoModel, PoincareVAE, PoincareVAEConfig
  from pythae.models.base.base_utils import ModelOutput
  from pythae.models.nn import BaseDecoder, BaseEncoder
  from pythae.models.pvae.pvae_utils import PoincareBall
  from pythae.trainers import BaseTrainer, BaseTrainerConfig
label_desc: Use image node_id 2 for calling the GeodesicLayer obj's underlying member method code with example usage: obj.forward(input) and returns: res