class_docstr: Original NeRF network.
class_docstr_tok: ["Original","NeRF","network","."]
docstr: Initialize the optimizers with a scheduler.
docstr_tok: ["Initialize","the","optimizers","with","a","scheduler","."]
code: def init_optimizer(
      self,
      learning_rate=0.0001,
      decay_steps=1000,
      decay_rate=0.98,
      staircase=True,
  ):
      """Initialize the optimizers with a scheduler."""
      learning_rate = tf.keras.optimizers.schedules.ExponentialDecay(
          learning_rate,
          decay_steps=decay_steps,
          decay_rate=decay_rate,
          staircase=staircase,
      )
      self.optimizer_network = tf.keras.optimizers.Adam(
          learning_rate=learning_rate
      )
  
file_path: graphics/tensorflow_graphics/projects/radiance_fields/nerf/model.py
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.utils
  import tensorflow_graphics.rendering.volumetric.ray_radiance
label_desc: Use image node_id 3 for calling the NeRF obj's underlying member method code with example usage: obj.init_optimizer(learning_rate, decay_steps, decay_rate, staircase) without return types