code: def __init__(
      self,
      spatial_dims: int,
      in_channels: int,
      out_channels: int,
      dropout: tuple | str | float | None = None,
  ):
      super().__init__()
      self.conv = get_conv_layer(
          spatial_dims,
          in_channels,
          out_channels,
          kernel_size=1,
          stride=1,
          dropout=dropout,
          bias=True,
          act=None,
          norm=None,
          conv_only=False,
      )
  
imports: from __future__ import annotations
  from collections.abc import Sequence
  import numpy
  import torch
  import torch.nn
  from monai.networks.blocks.convolutions import Convolution
  from monai.networks.layers.factories import Act, Norm
  from monai.networks.layers.utils import get_act_layer, get_norm_layer
label_desc: Use image node_id 1 to create a new UnetOutBlock object from inherited base classes: nn with example: obj = UnetOutBlock(spatial_dims, in_channels, out_channels, dropout)