code: def push_activations(activations, from_layer, to_layer):
      """Push activations from one model to another using prerecorded correlations"""
      inverse_covariance_matrix = layer_inverse_covariance(from_layer)
      activations_decorrelated = np.dot(
          inverse_covariance_matrix, activations.T
      ).T
      covariance_matrix = layer_covariance(from_layer, to_layer)
      activation_recorrelated = np.dot(
          activations_decorrelated, covariance_matrix
      )
      return activation_recorrelated
  
file_path: lucid/lucid/modelzoo/aligned_activations.py
imports: from __future__ import absolute_import, division, print_function
  from lucid.misc.io.sanitizing import sanitize
  from lucid.misc.io import load
  import numpy
  from cachetools.func import lru_cache
label_desc: Use image node_id 4 for calling a global function with example usage: push_activations(activations, from_layer, to_layer) and returns: activation_recorrelated