docstr: n, c, h, w = x.size()
  h //= self.stride
  w //= self.stride
  device = x.get_device() if x.is_cuda else torch.device('cpu')
  # noinspection PyUnresolvedReferences
  padding = torch.zeros(n, c, h, w, device=device, requires_grad=False)
  return padding
docstr_tok: ["n",",","c",",","h",",","w","=","x.size","(",")","h","\/\/=","self.stride","w","\/\/=","self.stride","device","=","x.get_device","(",")","if","x.is_cuda","else","torch.device","(","'cpu","'",")","#","noinspection","PyUnresolvedReferences","padding","=","torch.zeros","(","n",",","c",",","h",",","w",",","device=device",",","requires_grad=False",")","return","padding"]
code: def forward(self, x):
      """n, c, h, w = x.size()
      h //= self.stride
      w //= self.stride
      device = x.get_device() if x.is_cuda else torch.device('cpu')
      # noinspection PyUnresolvedReferences
      padding = torch.zeros(n, c, h, w, device=device, requires_grad=False)
      return padding"""
      return x * 0
  
imports: from collections import OrderedDict
  from nni.retiarii.serializer import basic_unit
  import torch
  import nni.retiarii.nn.pytorch
  from putils import get_same_padding, build_activation
label_desc: Use image node_id 2 for calling the ZeroLayer obj's underlying member method code with example usage: obj.forward(x) and returns: unknown