code: def get_conv_layer(
      spatial_dims: int,
      in_channels: int,
      out_channels: int,
      kernel_size: Sequence[int] | int = 3,
  ) -> nn.Module:
      padding = same_padding(kernel_size)
      mod: nn.Module = Convolution(
          spatial_dims,
          in_channels,
          out_channels,
          kernel_size=kernel_size,
          bias=False,
          conv_only=True,
          padding=padding,
      )
      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 Conv, Norm, Pool, same_padding
label_desc: Use image node_id 2 for calling a global function with example usage: get_conv_layer(spatial_dims, in_channels, out_channels, kernel_size) and returns: mod