code: def forward(self, x):
      x = x.unsqueeze(1)  # (batch, Ci, len, d)
      x = [F.relu(conv(x)).squeeze(3) for conv in self.convs1]
      x = [F.max_pool1d(i, i.size(2)).squeeze(2) for i in x]
      x = torch.cat(x, 1)
      return x
  
file_path: textflint/textflint/input/model/test_model/textcnn_torch_model.py
imports: import torch
  from torch import nn
  from torch.nn import functional
  from .glove_embedding import GloveEmbedding
  from textflint.common.utils.load import load_cached_state_dict
  from textflint.common import device
label_desc: Use image node_id 2 for calling the CNNTextLayer obj's underlying member method code with example usage: obj.forward(x) and returns: x