class_docstr: Residual network block used SegResNet based on `3D MRI brain tumor segmentation using autoencoder regularization
  <https://arxiv.org/pdf/1810.11654.pdf>`_.
class_docstr_tok: ["Residual","network","block","used","SegResNet","based","on","`","3D","MRI","brain","tumor","segmentation","using","autoencoder","regularization","<","https",":","\/\/arxiv.org\/pdf\/1810.11654.pdf",">","`","_","."]
code: def forward(self, x):
      identity = x
      x = self.conv2(
          self.act2(self.norm2(self.conv1(self.act1(self.norm1(x)))))
      )
      x += identity
      return x
  
imports: from __future__ import annotations
  from collections.abc import Callable
  from typing import Union
  import numpy
  import torch
  import torch.nn
  from monai.networks.blocks.upsample import UpSample
  from monai.networks.layers.factories import Act, Conv, Norm, split_args
  from monai.networks.layers.utils import get_act_layer, get_norm_layer
  from monai.utils import UpsampleMode, has_option
label_desc: Use image node_id 2 for calling the SegResBlock obj's underlying member method code with example usage: obj.forward(x) and returns: x