code: def resnet50(
      x,
      is_training=False,
      classes=1000,
      stem=False,
      scope=None,
      reuse=None,
  ):
      def stack_fn(x):
          x = _stack(x, _block1, 64, 3, stride1=1, scope="conv2")
          x = _stack(x, _block1, 128, 4, scope="conv3")
          x = _stack(x, _block1, 256, 6, scope="conv4")
          x = _stack(x, _block1, 512, 3, scope="conv5")
          return x
  
      return resnet(
          x, False, stack_fn, is_training, classes, stem, scope, reuse
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  import tensorflow
  from .layers import batch_norm
  from .layers import conv2d
  from .layers import fc
  from .layers import max_pool2d
  from .layers import sconv2d
  from .layers import convbn
  from .layers import gconvbn
  from .ops import *
  from .utils import pad_info
  from .utils import set_args
  from .utils import var_scope
label_desc: Use image node_id 3 for calling a global function with example usage: resnet50(x, is_training, classes, stem, scope, reuse) and returns: resnet, x