code: def get_deconv_block(
      spatial_dims: int, in_channels: int, out_channels: int
  ) -> nn.Module:
      mod: nn.Module = Convolution(
          spatial_dims=spatial_dims,
          in_channels=in_channels,
          out_channels=out_channels,
          strides=2,
          act="RELU",
          norm="BATCH",
          bias=False,
          is_transposed=True,
          padding=1,
          output_padding=1,
      )
      return mod
  
imports: from __future__ import annotations
  from collections.abc import Sequence
  import torch
  from torch import nn
  from torch.nn import functional
  from monai.networks.blocks import Convolution
  from monai.networks.layers import same_padding
  from monai.networks.layers.factories import Conv, Norm, Pool
label_desc: Use image node_id 3 for calling a global function with example usage: get_deconv_block(spatial_dims, in_channels, out_channels) and returns: mod