class_docstr: ResBlock employs skip connection and two convolution blocks and is used
  in 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.norm1(x)
      x = self.act(x)
      x = self.conv1(x)
  
      x = self.norm2(x)
      x = self.act(x)
      x = self.conv2(x)
  
      x += identity
  
      return x
  
file_path: MONAI/monai/networks/blocks/segresnet_block.py
imports: from __future__ import annotations
  import torch.nn
  from monai.networks.blocks.convolutions import Convolution
  from monai.networks.blocks.upsample import UpSample
  from monai.networks.layers.utils import get_act_layer, get_norm_layer
  from monai.utils import InterpolateMode, UpsampleMode
label_desc: Use image node_id 2 for calling the ResBlock obj's underlying member method code with example usage: obj.forward(x) and returns: x