code: def _transform_dense_weight(
      weight: tf.Tensor, log_step: tf.Tensor, quantized: bool = True
  ) -> tf.Tensor:
      """Transforms from latent to dense kernel or bias."""
      step = tf.exp(log_step)
      if not quantized:
          weight = tfc.round_st(weight / step)
      return weight * step
  
imports: import functools
  from typing import Callable, List, Tuple
  import tensorflow
  import tensorflow_compression
  from tensorflow_model_optimization.python.core.common.keras.compression import algorithm
label_desc: Use image node_id 2 for calling a global function with example usage: _transform_dense_weight(weight, log_step, quantized) and returns: unknown