code: def get_aligned_activations(layer) -> np.ndarray:
      """Downloads 100k activations of the specified layer sampled from iterating over
      ImageNet. Activations of all layers where sampled at the same spatial positions for
      each image, allowing the calculation of correlations."""
      activation_paths = [
          PATH_TEMPLATE.format(
              sanitize(layer.model_name), sanitize(layer.name), page
          )
          for page in range(NUMBER_OF_PAGES)
      ]
      activations = np.vstack([load(path) for path in activation_paths])
      assert np.all(np.isfinite(activations))
      return activations
  
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 1 for calling a global function with example usage: get_aligned_activations(layer) and returns: activations