code: def block(x, growth_rate=32, scope=None):
      x1 = batch_norm(x)
      x1 = relu(x1)
      x1 = conv(x1, 4 * growth_rate, 1, stride=1, scope="1")
      x1 = conv2d(
          x1, growth_rate, 3, stride=1, padding="SAME", scope="2/conv"
      )
      x = concat([x, x1], axis=3, name="out")
      return x
  
file_path: tensornets/tensornets/densenets.py
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 fc
  from .layers import max_pool2d
  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 8 for calling a global function with example usage: block(x, growth_rate, scope) and returns: x