class_docstr: Residual Network, see https://arxiv.org/abs/1512.03385
  Args:
      depth (int): ResNet depth, should be 34, 50.
      freeze_at (int): freeze the backbone at which stage
      norm_type (str): normalization type, 'bn'/'sync_bn'/'affine_channel'
      freeze_norm (bool): freeze normalization layers
      norm_decay (float): weight decay for normalization layer weights
      variant (str): ResNet variant, supports 'a', 'b', 'c', 'd' currently
      feature_maps (list): index of stages whose feature maps are returned
      dcn_v2_stages (list): index of stages who select deformable conv v2
      nonlocal_stages (list): index of stages who select nonlocal networks
class_docstr_tok: ["Residual","Network",",","see","https",":","\/\/arxiv.org\/abs\/1512.03385","Args",":","depth","(","int",")",":","ResNet","depth",",","should","be","34",",","50.","freeze_at","(","int",")",":","freeze","the","backbone","at","which","stage","norm_type","(","str",")",":","normalization","type",",","'bn'\/'sync_bn'\/'affine_channel'","freeze_norm","(","bool",")",":","freeze","normalization","layers","norm_decay","(","float",")",":","weight","decay","for","normalization","layer","weights","variant","(","str",")",":","ResNet","variant",",","supports","'","a","'",",","'","b","'",",","'","c","'",",","'d","'","currently","feature_maps","(","list",")",":","index","of","stages","whose","feature","maps","are","returned","dcn_v2_stages","(","list",")",":","index","of","stages","who","select","deformable","conv","v2","nonlocal_stages","(","list",")",":","index","of","stages","who","select","nonlocal","networks"]
code: def c1_stage(self, input):
      out_chan = self._c1_out_chan_num
  
      conv1_name = self.na.fix_c1_stage_name()
  
      if self.variant in ["c", "d"]:
          conv_def = [
              [out_chan // 2, 3, 2, "conv1_1"],
              [out_chan // 2, 3, 1, "conv1_2"],
              [out_chan, 3, 1, "conv1_3"],
          ]
      else:
          conv_def = [[out_chan, 7, 2, conv1_name]]
  
      for c, k, s, _name in conv_def:
          input = self._conv_norm(
              input=input,
              num_filters=c,
              filter_size=k,
              stride=s,
              act="relu",
              name=_name,
          )
  
      output = fluid.layers.pool2d(
          input=input,
          pool_size=3,
          pool_stride=2,
          pool_padding=1,
          pool_type="max",
      )
      return output
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import math
  from collections import OrderedDict
  from numbers import Integral
  from paddle import fluid
  from paddle.fluid.param_attr import ParamAttr
  from paddle.fluid.framework import Variable
  from paddle.fluid.regularizer import L2Decay
  from paddle.fluid.initializer import Constant
  from .nonlocal_helper import add_space_nonlocal
  from .name_adapter import NameAdapter
label_desc: Use image node_id 8 for calling the ResNet obj's underlying member method code with example usage: obj.c1_stage(input) and returns: output