code: def _make_nconv(
      spatial_dims: int,
      nchan: int,
      depth: int,
      act: tuple[str, dict] | str,
      bias: bool = False,
  ):
      layers = []
      for _ in range(depth):
          layers.append(LUConv(spatial_dims, nchan, act, bias))
      return nn.Sequential(*layers)
  
imports: from __future__ import annotations
  import torch
  import torch.nn
  from monai.networks.blocks.convolutions import Convolution
  from monai.networks.layers.factories import Act, Conv, Dropout, Norm, split_args
  from monai.utils import deprecated_arg
label_desc: Use image node_id 2 for calling a global function with example usage: _make_nconv(spatial_dims, nchan, depth, act, bias) and returns: nn