class_docstr: Network for generating voxels from latent codes.
class_docstr_tok: ["Network","for","generating","voxels","from","latent","codes","."]
code: def __init__(
      self,
      num_latent_codes=4371,
      latent_code_dim=256,
      fc_channels=512,
      fc_activation="relu",
      conv_size=4,
      norm3d="batchnorm",
      bce_gamma=0.8,
      proj_weight=0.01,
      mirror_weight=1.0,
  ):
      self.num_latent_codes = num_latent_codes
      self.latent_code_dim = latent_code_dim
      self.fc_channels = fc_channels
      self.fc_activation = fc_activation
      self.conv_size = conv_size
      self.norm3d = norm3d
      self.model = None
      self.model_backup = None
      self.latent_code_vars = None
      self.network_vars = None
      self.global_step = None
      self.latest_epoch = None
  
      self.optimizer_network = None
      self.optimizer_latent = None
  
      self.checkpoint = None
      self.manager = None
      self.summary_writer = None
  
      self.bce_gamma = bce_gamma
      self.proj_weight = proj_weight
      self.mirror_weight = mirror_weight
  
      self.mask_voxels = voxel_functions.get_mask_voxels()
  
file_path: graphics/tensorflow_graphics/projects/radiance_fields/sharf/geometry_net/model.py
imports: from absl import logging
  import tensorflow
  import tensorflow_graphics.projects.radiance_fields.sharf.geometry_net.layers
  import tensorflow_graphics.projects.radiance_fields.sharf.voxel_functions
label_desc: Use image node_id 1 to create a new GeometryNetwork object  with example: obj = GeometryNetwork(num_latent_codes, latent_code_dim, fc_channels, fc_activation, conv_size, norm3d, bce_gamma, proj_weight, mirror_weight)