code: def forward(
      self, x: list[torch.Tensor], image_size: list[int]
  ) -> torch.Tensor:
      f = x[0]
      self.grid = self.grid.to(device=f.device)
      theta = self.fc(f.reshape(f.shape[0], -1))
      if self.save_theta:
          self.theta = theta.detach()
      out: torch.Tensor = self.affine_transform(theta) - self.grid
      return out
  
imports: from __future__ import annotations
  import torch
  from torch import nn
  from torch.nn import functional
  from monai.networks.blocks.regunet_block import RegistrationDownSampleBlock, RegistrationExtractionBlock, RegistrationResidualConvBlock, get_conv_block, get_deconv_block
  from monai.networks.utils import meshgrid_ij
label_desc: Use image node_id 4 for calling the AffineHead obj's underlying member method code with example usage: obj.forward(x, image_size) and returns: out