code: def zf(
      x,
      is_training=False,
      classes=1000,
      stem=False,
      scope=None,
      reuse=None,
  ):
      x = pad(x, pad_info(7), name="pad1")
      x = conv(x, 96, 7, stride=2, padding="VALID", scope="conv1")
      x = srn(x, depth_radius=3, alpha=0.00005, beta=0.75, name="srn1")
      x = pad(x, pad_info(3, symmetry=False), name="pad2")
      x = max_pool2d(x, 3, stride=2, padding="VALID", scope="pool1")
  
      x = pad(x, pad_info(5), name="pad3")
      x = conv(x, 256, 5, stride=2, padding="VALID", scope="conv2")
      x = srn(x, depth_radius=3, alpha=0.00005, beta=0.75, name="srn2")
      x = pad(x, pad_info(3, symmetry=False), name="pad4")
      x = max_pool2d(x, 3, stride=2, padding="VALID", scope="pool2")
  
      x = conv(x, 384, 3, scope="conv3")
      x = conv(x, 384, 3, scope="conv4")
      x = conv(x, 256, 3, scope="conv5")
      if stem:
          return x
  
      x = reduce_mean(x, [1, 2], name="avgpool")
      x = fc(x, classes, scope="logits")
      x = softmax(x, name="probs")
      return x
  
file_path: tensornets/tensornets/zf.py
imports: from __future__ import absolute_import
  from __future__ import division
  import tensorflow
  from .layers import conv2d
  from .layers import fc
  from .layers import max_pool2d
  from .layers import convrelu
  from .ops import *
  from .utils import pad_info
  from .utils import set_args
  from .utils import var_scope
label_desc: Use image node_id 2 for calling a global function with example usage: zf(x, is_training, classes, stem, scope, reuse) and returns: x, x