code: def __init__(
      self,
      in_features,
      out_features,
      manifold,
      over_param=False,
      weight_norm=False,
  ):
      super(GeodesicLayer, self).__init__(
          in_features, out_features, manifold, over_param, weight_norm
      )
  
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 1 to create a new GeodesicLayer object from inherited base classes: RiemannianLayer with example: obj = GeodesicLayer(in_features, out_features, manifold, over_param, weight_norm)