code: def get_conv_layer(
      spatial_dims: int,
      in_channels: int,
      out_channels: int,
      kernel_size: int = 3,
      stride: int = 1,
      bias: bool = False,
  ):
      return Convolution(
          spatial_dims,
          in_channels,
          out_channels,
          strides=stride,
          kernel_size=kernel_size,
          bias=bias,
          conv_only=True,
      )
  
file_path: MONAI/monai/networks/blocks/segresnet_block.py
imports: from __future__ import annotations
  import torch.nn
  from monai.networks.blocks.convolutions import Convolution
  from monai.networks.blocks.upsample import UpSample
  from monai.networks.layers.utils import get_act_layer, get_norm_layer
  from monai.utils import InterpolateMode, UpsampleMode
label_desc: Use image node_id 1 for calling a global function with example usage: get_conv_layer(spatial_dims, in_channels, out_channels, kernel_size, stride, bias) and returns: Convolution