import tensorflow as tf

      A dictionary of the initial values of the
      cluster centroids, cluster indices, original weights,
      the pretrained flag for marking the first training
      epoch, and weight name.
    """
    result = {}
    weights = getattr(layer.layer, name)
    if self.preserve_sparsity and not tf.reduce_any(weights == 0):
      self.preserve_sparsity = False
      logging.warning(
          'Input layer does not contain zero weights, so apply CQAT instead.')
    centroids_mask = None
    centroids, lookup = get_unique(weights)
    num_centroids = tf.size(centroids)
