class_docstr: The High-Resolution Detail Branch
  
  Args:
      in_channels(int): The number of input channels.
      scb_channels(list|tuple): The channels of scb logits
      gf_index(list|tuple, optional): Which logit is selected as guidance flow from scb logits. Default: (0, 2, 4)
class_docstr_tok: ["The","High-Resolution","Detail","Branch","Args",":","in_channels","(","int",")",":","The","number","of","input","channels",".","scb_channels","(","list|tuple",")",":","The","channels","of","scb","logits","gf_index","(","list|tuple",",","optional",")",":","Which","logit","is","selected","as","guidance","flow","from","scb","logits",".","Default",":","(","0",",","2",",","4",")"]
code: def __init__(self, in_channels, scb_channels, gf_index=(0, 2, 4)):
      super().__init__()
      self.gf_index = gf_index
      self.gf_list = nn.LayerList(
          [nn.Conv2D(scb_channels[i], 1, 1) for i in gf_index]
      )
  
      channels = [64, 32, 16, 8]
      self.res_list = [
          resnet_vd.BasicBlock(
              in_channels, channels[0], stride=1, shortcut=False
          )
      ]
      self.res_list += [
          resnet_vd.BasicBlock(i, i, stride=1) for i in channels[1:-1]
      ]
      self.res_list = nn.LayerList(self.res_list)
  
      self.convs = nn.LayerList(
          [
              nn.Conv2D(channels[i], channels[i + 1], kernel_size=1)
              for i in range(len(channels) - 1)
          ]
      )
      self.gates = nn.LayerList(
          [GatedSpatailConv2d(i, i) for i in channels[1:]]
      )
  
      self.detail_conv = nn.Conv2D(channels[-1], 1, 1, bias_attr=False)
  
imports: from collections import defaultdict
  import time
  import paddle
  import paddle.nn
  import paddle.nn.functional
  import paddleseg
  from paddleseg.models import layers
  from paddleseg import utils
  from paddleseg.cvlibs import manager
  from ppmatting.models.losses import MRSD, GradientLoss
  from ppmatting.models.backbone import resnet_vd
label_desc: Use image node_id 1 to create a new HRDB object from inherited base classes: nn with example: obj = HRDB(in_channels, scb_channels, gf_index)