code: def __post_init__(self):
      # The harmonic embedding layer converts input 3D coordinates
      # to a representation that is more suitable for
      # processing with a deep neural network.
      self.harmonic_embedding_xyz = HarmonicEmbedding(
          self.n_harmonic_functions_xyz, append_input=True
      )
      self.harmonic_embedding_dir = HarmonicEmbedding(
          self.n_harmonic_functions_dir, append_input=True
      )
      if not self.input_xyz and self.latent_dim <= 0:
          raise ValueError(
              "The latent dimension has to be > 0 if xyz is not input!"
          )
  
      embedding_dim_dir = self.harmonic_embedding_dir.get_output_dim()
  
      self.xyz_encoder = self._construct_xyz_encoder(
          input_dim=self.get_xyz_embedding_dim()
      )
  
      self.intermediate_linear = torch.nn.Linear(
          self.n_hidden_neurons_xyz, self.n_hidden_neurons_xyz
      )
      _xavier_init(self.intermediate_linear)
  
      self.density_layer = torch.nn.Linear(self.n_hidden_neurons_xyz, 1)
      _xavier_init(self.density_layer)
  
      # Zero the bias of the density layer to avoid
      # a completely transparent initialization.
      self.density_layer.bias.data[
          :
      ] = 0.0  # fixme: Sometimes this is not enough
  
      self.color_layer = torch.nn.Sequential(
          LinearWithRepeat(
              self.n_hidden_neurons_xyz + embedding_dim_dir,
              self.n_hidden_neurons_dir,
          ),
          torch.nn.ReLU(True),
          torch.nn.Linear(self.n_hidden_neurons_dir, self.color_dim),
          torch.nn.Sigmoid(),
      )
  
imports: import logging
  from typing import Optional, Tuple
  import torch
  from pytorch3d.common.linear_with_repeat import LinearWithRepeat
  from pytorch3d.implicitron.models.renderer.base import conical_frustum_to_gaussian, ImplicitronRayBundle
  from pytorch3d.implicitron.tools.config import expand_args_fields, registry
  from pytorch3d.renderer.cameras import CamerasBase
  from pytorch3d.renderer.implicit import HarmonicEmbedding
  from pytorch3d.renderer.implicit.utils import ray_bundle_to_ray_points
  from .base import ImplicitFunctionBase
  from .decoding_functions import _xavier_init, MLPWithInputSkips, TransformerWithInputSkips
  from .utils import create_embeddings_for_implicit_function
label_desc: Use image node_id 1 for calling the NeuralRadianceFieldBase obj's underlying member method code with example usage: obj.__post_init__() without return types