code: def l2_loss_distrib(
      prediction, target, global_batch_size, weights=1.0
  ):
      """L2 loss implementation that forces same prediction and target shapes."""
      assert (
          prediction.shape == target.shape
      ), "Shape dims should be the same."
      return tf.reduce_sum(weights * tf.square(target - prediction)) * (
          1.0 / global_batch_size
      )
  
file_path: graphics/tensorflow_graphics/projects/radiance_fields/utils.py
imports: import math
  import tensorflow
  from tensorflow_graphics.geometry.transformation import rotation_matrix_3d
  from tensorflow_graphics.util import shape
label_desc: Use image node_id 8 for calling a global function with example usage: l2_loss_distrib(prediction, target, global_batch_size, weights) and returns: unknown