code: def inceptionC(x, f, scale=1.0, scope=None):
      conv1 = conv(x, f[0], 1, scope="1x1")
  
      conv2 = conv(x, f[1][0], 1, scope="3x3/r")
      conv2_1 = conv(conv2, f[1][1], (1, 3), scope="3x3/1")
      conv2_2 = conv(conv2, f[1][2], (3, 1), scope="3x3/2")
      conv2 = concat([conv2_1, conv2_2], axis=3, name="3x3/c")
  
      conv3 = conv(x, f[2][0], 1, scope="d3x3/r")
      if len(f[2]) < 3:
          conv3 = conv(conv3, f[2][1], (3, 3), scope="d3x3/1")
      else:
          conv3 = conv(conv3, f[2][1], (3, 1), scope="d3x3/11")
          conv3 = conv(conv3, f[2][2], (1, 3), scope="d3x3/12")
      conv3_1 = conv(conv3, f[2][-1], (1, 3), scope="d3x3/21")
      conv3_2 = conv(conv3, f[2][-1], (3, 1), scope="d3x3/22")
      conv3 = concat([conv3_1, conv3_2], axis=3, name="d3x3/c")
  
      pool = avg_pool2d(x, 3)
      pool = conv(pool, f[3], 1, scope="proj")
  
      x = concat([conv1, conv2, conv3, pool], axis=3, name="concat")
      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 18 for calling a global function with example usage: inceptionC(x, f, scale, scope) and returns: x