code: def conv_nd(dims, *args, **kwargs):
      """
      Create a 1D, 2D, or 3D convolution module.
      """
      if dims == 1:
          return nn.Conv1d(*args, **kwargs)
      elif dims == 2:
          return nn.Conv2d(*args, **kwargs)
      elif dims == 3:
          return nn.Conv3d(*args, **kwargs)
      raise ValueError(f"unsupported dimensions: {dims}")
  
imports: import math
  import numpy
  import torch
  import torch.nn
  from apex.contrib.group_norm import GroupNorm
  from einops import repeat
  from torch._dynamo import disable
  from torch.cuda.amp import custom_bwd, custom_fwd
label_desc: Use image node_id 13 for calling a global function with example usage: conv_nd(dims) and returns: nn, nn, nn