code: def forward(self, x, adjs, weights):
      edges, ews = Get_edges(adjs)
      for i in range(self.steps):
          if i > 0:
              x = F.relu(x)
              x = F.dropout(x, p=self.dp, training=self.training)
          x = self._ops[i](
              x, edges[i], ews[i], weights[i]
          )  # call the gcn module
      return x
  
imports: import typing
  from .None import register_nas_space
  from .base import apply_fixed_architecture
  from .base import BaseSpace
  from ...model import BaseAutoModel
  from ....utils import get_logger
  from ..backend import *
  from ..utils import count_parameters, measure_latency
  import torch
  import torch.nn
  import torch.nn.functional
  from torch.nn import Module
  from .gasso_space import *
  from torch.autograd import Variable
  from collections import namedtuple
label_desc: Use image node_id 2 for calling the CellWS obj's underlying member method code with example usage: obj.forward(x, adjs, weights) and returns: x