code: def _init_thresh(
      self, inner_channels, serial=False, smooth=False, bias=False
  ):
      in_channels = inner_channels
      if serial:
          in_channels += 1
      self.thresh = nn.Sequential(
          nn.Conv2d(
              in_channels, inner_channels // 4, 3, padding=1, bias=bias
          ),
          BatchNorm2d(inner_channels // 4),
          nn.ReLU(inplace=True),
          self._init_upsample(
              inner_channels // 4,
              inner_channels // 4,
              smooth=smooth,
              bias=bias,
          ),
          BatchNorm2d(inner_channels // 4),
          nn.ReLU(inplace=True),
          self._init_upsample(
              inner_channels // 4, 1, smooth=smooth, bias=bias
          ),
          nn.Sigmoid(),
      )
      return self.thresh
  
file_path: EasyOCR/easyocr/DBNet/decoders/seg_detector_asf.py
imports: from collections import OrderedDict
  import pdb
  import torch
  import torch.nn
  from .feature_attention import ScaleFeatureSelection
label_desc: Use image node_id 3 for calling the SegSpatialScaleDetector obj's underlying member method code with example usage: obj._init_thresh(inner_channels, serial, smooth, bias) and returns: self