code: def conv2d(ni:int, nf:int, ks:int=3, stride:int=1, padding:int=None, bias=False, init:LayerFunc=nn.init.kaiming_normal_) -> nn.Conv2d:
      "Create and initialize `nn.Conv2d` layer. `padding` defaults to `ks//2`."
      if padding is None: padding = ks//2
      return init_default(nn.Conv2d(ni, nf, kernel_size=ks, stride=stride, padding=padding, bias=bias), initf conv2d(ni:int, nf:int, ks:int=3, stride:int=1, padding:int=None, bias=False, init:LayerFunc=nn.init.kaiming_normal_) -> nn.Conv2d:
      "Create and initialize `nn.Conv2d` layer. `padding` defaults to `ks//2`."
      if padding is None: padding = ks//2
      return init_default(nn.Conv2d(ni, nf, kernel_size=ks, stride=stride, padding=padding, bias=bias), init)
docs: Create and initialize `nn.Conv2d` layer. `padding` defaults to `ks//2`.