code: def forward(self, x):
      if self._padding_mode != "zeros":
          x = F.pad(
              x,
              self._reversed_padding_repeated_twice,
              mode=self._padding_mode,
              data_format=self._data_format,
          )
  
      w = self.weight
      v = paddle.var(w, axis=[1, 2, 3], keepdim=True, unbiased=False)
      m = paddle.mean(w, axis=[1, 2, 3], keepdim=True)
      w = (w - m) / paddle.sqrt(v + 1e-5)
  
      out = F.conv._conv_nd(
          x,
          w,
          bias=self.bias,
          stride=self._stride,
          padding=self._updated_padding,
          padding_algorithm=self._padding_algorithm,
          dilation=self._dilation,
          groups=self._groups,
          data_format=self._data_format,
          channel_dim=self._channel_dim,
          op_type=self._op_type,
          use_cudnn=self._use_cudnn,
      )
      return out
  
file_path: PaddleSeg/contrib/MedicalSeg/medicalseg/models/backbones/resnet.py
imports: from os.path import join
  import paddle
  import paddle.nn
  import paddle.nn.functional
  from medicalseg.cvlibs import manager
label_desc: Use image node_id 1 for calling the StdConv2d obj's underlying member method code with example usage: obj.forward(x) and returns: out