code: def __init__(
      self,
      spatial_dims: int,
      in_channels: int,
      out_channels: int,
      mode: str = "nearest",
      align_corners: bool | None = None,
  ):
      super().__init__()
      self.deconv = get_deconv_block(
          spatial_dims=spatial_dims,
          in_channels=in_channels,
          out_channels=out_channels,
      )
      self.mode = mode
      self.align_corners = align_corners
  
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 1 to create a new AdditiveUpSampleBlock object from inherited base classes: nn with example: obj = AdditiveUpSampleBlock(spatial_dims, in_channels, out_channels, mode, align_corners)