code: def forward(self, inputs):
      sent_ids, mask = inputs
      seq = self.embedding(sent_ids.long())
      seq = self.embed_dropout(seq)
  
      seq = torch.transpose(seq, 1, 2)  # from (N, L, C) -> (N, C, L)
  
      x = self.init_conv(seq, mask)
      prev_layers = []
  
      for layer in self.layers:
          x = layer(x, prev_layers, mask)
          prev_layers.append(x)
  
      x = self.linear_combine(torch.stack(prev_layers))
      x = self.global_pool(x, mask)
      x = self.output_dropout(x)
      x = self.linear_out(x)
      return x
  
file_path: nni/examples/nas/legacy/textnas/model.py
imports: import numpy
  import torch
  import torch.nn
  from nni.nas.pytorch import mutables
  from ops import ConvBN, LinearCombine, AvgPool, MaxPool, RNN, Attention, BatchNorm
  from utils import GlobalMaxPool, GlobalAvgPool
label_desc: Use image node_id 2 for calling the Model obj's underlying member method code with example usage: obj.forward(inputs) and returns: x