code: def inception2(
      x,
      is_training=False,
      classes=1000,
      stem=False,
      scope=None,
      reuse=None,
  ):
      x = sconv2d(
          x, 64, 7, stride=2, depth_multiplier=8, scope="block1"
      )
      x = max_pool2d(x, 3, stride=2, scope="pool1")
  
      x = conv(x, 64, 1, scope="block2/1")
      x = conv(x, 192, 3, scope="block2/2")
      x = max_pool2d(x, 3, stride=2, scope="pool2")
  
      x = inceptionA(x, [64, [64, 64], [64, 96], 32], scope="block3a")
      x = inceptionA(x, [64, [64, 96], [64, 96], 64], scope="block3b")
  
      x = reductionA(
          x, [[128, 160], [64, 96, 96]], padding="SAME", scope="block3c"
      )
  
      x = inceptionA(
          x, [224, [64, 96], [96, 128], 128], scope="block4a"
      )
      x = inceptionA(
          x, [192, [96, 128], [96, 128], 128], scope="block4b"
      )
      x = inceptionA(
          x, [160, [128, 160], [128, 160], 96], scope="block4c"
      )
      x = inceptionA(
          x, [96, [128, 192], [160, 192], 96], scope="block4d"
      )
  
      x = reductionA(
          x,
          [[128, 192], [192, 256, 256]],
          padding="SAME",
          scope="block4e",
      )
  
      x = inceptionA(
          x, [352, [192, 320], [160, 224], 128], scope="block5a"
      )
      x = inceptionA(
          x,
          [352, [192, 320], [192, 224], 128],
          pool_fn=max_pool2d,
          scope="block5b",
      )
      if stem:
          return x
  
      x = reduce_mean(x, [1, 2], name="avgpool")
      x = dropout(x, keep_prob=0.8, scope="dropout")
      x = fc(x, classes, scope="logits")
      x = softmax(x, name="probs")
      return x
  
imports: from __future__ import absolute_import
  import tensorflow
  from .layers import avg_pool2d
  from .layers import batch_norm
  from .layers import conv2d
  from .layers import dropout
  from .layers import fc
  from .layers import max_pool2d
  from .layers import sconv2d
  from .layers import convrelu0
  from .layers import convbnrelu
  from .ops import *
  from .utils import pad_info
  from .utils import set_args
  from .utils import var_scope
label_desc: Use image node_id 3 for calling a global function with example usage: inception2(x, is_training, classes, stem, scope, reuse) and returns: x, x