code: def inception1(
      x,
      is_training=False,
      classes=1000,
      stem=False,
      scope=None,
      reuse=None,
  ):
      x = pad(x, pad_info(7), name="pad")
      x = conv0(x, 64, 7, stride=2, padding="VALID", scope="block1")
      x = max_pool2d(x, 3, stride=2, scope="pool1")
      x = lrn(x, depth_radius=2, alpha=0.00002, beta=0.75, name="lrn1")
  
      x = conv0(x, 64, 1, scope="block2/3x3/r")
      x = conv0(x, 192, 3, scope="block2/3x3/1")
      x = lrn(x, depth_radius=2, alpha=0.00002, beta=0.75, name="lrn2")
      x = max_pool2d(x, 3, stride=2, scope="pool2")
  
      x = inception(x, [64, [96, 128], [16, 32], 32], scope="block3a")
      x = inception(x, [128, [128, 192], [32, 96], 64], scope="block3b")
  
      x = max_pool2d(x, 3, stride=2, scope="pool3")
  
      x = inception(x, [192, [96, 208], [16, 48], 64], scope="block4a")
      x = inception(x, [160, [112, 224], [24, 64], 64], scope="block4b")
      x = inception(x, [128, [128, 256], [24, 64], 64], scope="block4c")
      x = inception(x, [112, [144, 288], [32, 64], 64], scope="block4d")
      x = inception(
          x, [256, [160, 320], [32, 128], 128], scope="block4e"
      )
  
      x = max_pool2d(x, 3, stride=2, scope="pool4")
  
      x = inception(
          x, [256, [160, 320], [32, 128], 128], scope="block5a"
      )
      x = inception(
          x, [384, [192, 384], [48, 128], 128], 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 2 for calling a global function with example usage: inception1(x, is_training, classes, stem, scope, reuse) and returns: x, x