code: def inceptionB(x, f, scale=1.0, scope=None):
      conv1 = conv(x, f[0], 1, scope="1x1")
  
      conv2 = conv(x, f[1][0], 1, scope="7x7/r")
      conv2 = conv(conv2, f[1][1], (1, 7), scope="7x7/1")
      conv2 = conv(conv2, f[1][2], (7, 1), scope="7x7/2")
  
      conv3 = conv(x, f[2][0], 1, scope="d7x7/r")
      conv3 = conv(conv3, f[2][0], (7, 1), scope="d7x7/1")
      conv3 = conv(conv3, f[2][1], (1, 7), scope="d7x7/2")
      conv3 = conv(conv3, f[2][1], (7, 1), scope="d7x7/3")
      conv3 = conv(conv3, f[1][2], (1, 7), scope="d7x7/4")
  
      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 16 for calling a global function with example usage: inceptionB(x, f, scale, scope) and returns: x