code: def stemA(x):
      """Stem for Inception-v4,-ResNet-v2 (Fig. 3 in the v4 paper)"""
      x = conv(x, 32, 3, stride=2, padding="VALID", scope="block1a")
      x = conv(x, 32, 3, padding="VALID", scope="block2a")
      x = conv(x, 64, 3, scope="block2b")
  
      with tf.variable_scope("block3a"):
          x_1 = max_pool2d(
              x, 3, stride=2, padding="VALID", scope="pool"
          )
          x_2 = conv(x, 96, 3, stride=2, padding="VALID", scope="conv")
          x = concat([x_1, x_2], axis=3, name="concat")
  
      with tf.variable_scope("block4a"):
          x_1 = conv(x, 64, 1, scope="1a")
          x_1 = conv(x_1, 96, 3, padding="VALID", scope="1b")
          x_2 = conv(x, 64, 1, scope="2a")
          x_2 = conv(x_2, 64, (1, 7), scope="2b")
          x_2 = conv(x_2, 64, (7, 1), scope="2c")
          x_2 = conv(x_2, 96, 3, padding="VALID", scope="2d")
          x = concat([x_1, x_2], axis=3, name="concat")
  
      with tf.variable_scope("block5a"):
          x_1 = conv(x, 192, 3, stride=2, padding="VALID", scope="conv")
          x_2 = max_pool2d(
              x, 3, stride=2, padding="VALID", scope="pool"
          )
          x = concat([x_1, x_2], 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 10 for calling a global function with example usage: stemA(x) and returns: x