code: def restore_params(network, path="models"):
      logging.info("Restore pre-trained parameters")
      maybe_download_and_extract(
          "squeezenet.npz",
          path,
          "https://github.com/tensorlayer/pretrained-models/raw/master/models/",
          expected_bytes=7405613,
      )  # ls -al
      params = load_npz(name=os.path.join(path, "squeezenet.npz"))
      assign_weights(params[: len(network.all_weights)], network)
      del params
  
file_path: TensorLayer/tensorlayer/models/squeezenetv1.py
imports: import os
  import tensorflow
  from tensorlayer import logging
  from tensorlayer.files import assign_weights, load_npz, maybe_download_and_extract
  from tensorlayer.layers import Concat, Conv2d, Dropout, GlobalMeanPool2d, Input, Lambda, MaxPool2d
  from tensorlayer.models import Model
label_desc: Use image node_id 2 for calling a global function with example usage: restore_params(network, path) without return types