class_docstr: Swin Transformer block based on: "Liu et al.,
  Swin Transformer: Hierarchical Vision Transformer using Shifted Windows
  <https://arxiv.org/abs/2103.14030>"
  https://github.com/microsoft/Swin-Transformer
code: def forward_part2(self, x):
      return self.drop_path(self.mlp(self.norm2(x)))
  
imports: from __future__ import annotations
  import itertools
  from collections.abc import Sequence
  import numpy
  import torch
  import torch.nn
  import torch.nn.functional
  import torch.utils.checkpoint
  from torch.nn import LayerNorm
  from typing_extensions import Final
  from monai.networks.blocks import MLPBlock
  from monai.networks.blocks import PatchEmbed, UnetOutBlock, UnetrBasicBlock, UnetrUpBlock
  from monai.networks.layers import DropPath, trunc_normal_
  from monai.utils import ensure_tuple_rep, look_up_option, optional_import
  from monai.utils.deprecate_utils import deprecated_arg
label_desc: Use image node_id 3 for calling the SwinTransformerBlock obj's underlying member method code with example usage: obj.forward_part2(x) and returns: self