code: def __args_rcnn__(is_training):
      return [
          ([conv2d], {"activation_fn": None, "scope": "conv"}),
          ([dropout], {"is_training": is_training}),
          ([fc], {"activation_fn": None, "scope": "fc"}),
      ]
  
imports: from __future__ import absolute_import
  from __future__ import division
  import tensorflow
  from .layers import batch_norm
  from .layers import bias_add
  from .layers import conv2d
  from .layers import darkconv
  from .layers import dropout
  from .layers import flatten
  from .layers import fc
  from .layers import max_pool2d
  from .ops import *
  from .utils import remove_head
  from .utils import set_args
  from .utils import var_scope
  from .references.yolos import get_v2_boxes
  from .references.yolos import opts
  from .references.yolos import v2_inputs
  from .references.yolos import v2_loss
  from .references.rcnns import get_boxes
  from .references.rcnns import roi_pool2d
  from .references.rcnns import rp_net
label_desc: Use image node_id 2 for calling a global function with example usage: __args_rcnn__(is_training) and returns: list