code: def __args__(is_training):
      return [
          (
              [avg_pool2d, max_pool2d],
              {"padding": "SAME", "scope": "pool"},
          ),
          (
              [batch_norm],
              {
                  "decay": 0.9997,
                  "scale": True,
                  "epsilon": 0.001,
                  "is_training": is_training,
                  "fused": True,
                  "scope": "bn",
              },
          ),
          (
              [conv2d],
              {
                  "padding": "SAME",
                  "activation_fn": None,
                  "biases_initializer": None,
                  "scope": "conv",
              },
          ),
          ([dropout], {"is_training": is_training, "scope": "dropout"}),
          ([fc], {"activation_fn": None, "scope": "fc"}),
          (
              [sconv2d],
              {
                  "padding": "SAME",
                  "activation_fn": None,
                  "biases_initializer": None,
                  "scope": "sconv",
              },
          ),
      ]
  
imports: from __future__ import absolute_import
  from __future__ import division
  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 convbn
  from .layers import sconvbn
  from .ops import *
  from .utils import pad_info
  from .utils import set_args
  from .utils import var_scope
label_desc: Use image node_id 1 for calling a global function with example usage: __args__(is_training) and returns: list