code: def conv2d(w_in, w_out, k, *, stride=1, groups=1, bias=False):
      """Helper for building a conv2d layer."""
      assert (
          k % 2 == 1
      ), "Only odd size kernels supported to avoid padding issues."
      s, p, g, b = stride, (k - 1) // 2, groups, bias
      return nn.Conv2d(
          w_in, w_out, k, stride=s, padding=p, groups=g, bias=b
      )
  
imports: import numpy
  import torch
  import torch.nn
  from pycls.core.config import cfg
  from torch.nn import Module
label_desc: Use image node_id 1 for calling a global function with example usage: conv2d(w_in, w_out, k) and returns: nn