class_docstr: Shape and appearance conditioned network for radiance fields.
class_docstr_tok: ["Shape","and","appearance","conditioned","network","for","radiance","fields","."]
docstr: Load checkpoints.
docstr_tok: ["Load","checkpoints","."]
code: def load_checkpoint(self, checkpoint=None):
      """Load checkpoints."""
      if checkpoint is None:
          latest_checkpoint = self.manager.latest_checkpoint
      else:
          latest_checkpoint = checkpoint
      if latest_checkpoint is not None:
          logging.info("Checkpoint %s restored", latest_checkpoint)
          _ = self.checkpoint.restore(
              latest_checkpoint
          ).expect_partial()
          for a, b in zip(
              self.model_backup.variables, self.model.variables
          ):
              a.assign(b)
      else:
          logging.warning("No checkpoint was restored.")
  
imports: from absl import logging
  import numpy
  import tensorflow
  import tensorflow_graphics.geometry.representation.ray
  import tensorflow_graphics.math.feature_representation
  import tensorflow_graphics.projects.radiance_fields.nerf.layers
  import tensorflow_graphics.projects.radiance_fields.sharf.voxel_functions
  import tensorflow_graphics.projects.radiance_fields.utils
  import tensorflow_graphics.rendering.volumetric.ray_radiance
label_desc: Use image node_id 5 for calling the AppearanceNetwork obj's underlying member method code with example usage: obj.load_checkpoint(checkpoint) without return types