code: def __init__(self, depth=50, width=26, scales=4, variant="b"):
      super(Res2NetC5, self).__init__()
      feat_in, feat_out = [1024, 2048]
      self.res5 = Blocks(
          feat_in,
          feat_out,
          count=3,
          stage_num=5,
          width=width,
          scales=scales,
          variant=variant,
      )
      self.feat_out = feat_out
  
imports: from numbers import Integral
  import paddle
  import paddle.nn
  import paddle.nn.functional
  from ppdet.core.workspace import register, serializable
  from ..shape_spec import ShapeSpec
  from .resnet import ConvNormLayer
label_desc: Use image node_id 1 to create a new Res2NetC5 object from inherited base classes: nn with example: obj = Res2NetC5(depth, width, scales, variant)