code: def __init__(
      self,
      inplanes,
      planes,
      stride=1,
      abn=InPlaceABNSync,
      dilation=1,
      downsample=None,
      fist_dilation=1,
      multi_grid=1,
  ):
      super(Bottleneck, self).__init__()
      self.conv1 = nn.Conv2d(
          inplanes, planes, kernel_size=1, bias=False
      )
      self.bn1 = abn(planes)
      self.conv2 = nn.Conv2d(
          planes,
          planes,
          kernel_size=3,
          stride=stride,
          padding=dilation * multi_grid,
          dilation=dilation * multi_grid,
          bias=False,
      )
      self.bn2 = abn(planes)
      self.conv3 = nn.Conv2d(
          planes, planes * 4, kernel_size=1, bias=False
      )
      self.bn3 = abn(planes * 4)
      self.relu = nn.ReLU(inplace=False)
      self.relu_inplace = nn.ReLU(inplace=True)
      self.downsample = downsample
      self.dilation = dilation
      self.stride = stride
  
file_path: insightface/parsing/dml_csr/networks/modules/util.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import torch.nn
  from inplace_abn import InPlaceABNSync
label_desc: Use image node_id 1 to create a new Bottleneck object from inherited base classes: nn with example: obj = Bottleneck(inplanes, planes, stride, abn, dilation, downsample, fist_dilation, multi_grid)