class_docstr: UNETR based on: "Hatamizadeh et al.,
  UNETR: Transformers for 3D Medical Image Segmentation <https://arxiv.org/abs/2103.10504>"
code: def forward(self, x_in):
      x, hidden_states_out = self.vit(x_in)
      enc1 = self.encoder1(x_in)
      x2 = hidden_states_out[3]
      enc2 = self.encoder2(self.proj_feat(x2))
      x3 = hidden_states_out[6]
      enc3 = self.encoder3(self.proj_feat(x3))
      x4 = hidden_states_out[9]
      enc4 = self.encoder4(self.proj_feat(x4))
      dec4 = self.proj_feat(x)
      dec3 = self.decoder5(dec4, enc4)
      dec2 = self.decoder4(dec3, enc3)
      dec1 = self.decoder3(dec2, enc2)
      out = self.decoder2(dec1, enc1)
      return self.out(out)
  
file_path: MONAI/monai/networks/nets/unetr.py
imports: from __future__ import annotations
  from collections.abc import Sequence
  import torch.nn
  from monai.networks.blocks.dynunet_block import UnetOutBlock
  from monai.networks.blocks.unetr_block import UnetrBasicBlock, UnetrPrUpBlock, UnetrUpBlock
  from monai.networks.nets.vit import ViT
  from monai.utils import deprecated_arg, ensure_tuple_rep
label_desc: Use image node_id 3 for calling the UNETR obj's underlying member method code with example usage: obj.forward(x_in) and returns: self