code: def fire_block(n, n_filter, max_pool=False, name="fire_block"):
      n = Conv2d(
          n_filter,
          (1, 1),
          (1, 1),
          tf.nn.relu,
          "SAME",
          name=name + ".squeeze1x1",
      )(n)
      n1 = Conv2d(
          n_filter * 4,
          (1, 1),
          (1, 1),
          tf.nn.relu,
          "SAME",
          name=name + ".expand1x1",
      )(n)
      n2 = Conv2d(
          n_filter * 4,
          (3, 3),
          (1, 1),
          tf.nn.relu,
          "SAME",
          name=name + ".expand3x3",
      )(n)
      n = Concat(-1, name=name + ".concat")([n1, n2])
      if max_pool:
          n = MaxPool2d((3, 3), (2, 2), "VALID", name=name + ".max")(n)
      return n
  
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 1 for calling a global function with example usage: fire_block(n, n_filter, max_pool, name) and returns: n