class_docstr: A convolutional neural network for text classification which implemented by pytorch.
  
  We use different versions of this network to pretrain models for
  text classification.
code: def forward(self, _input):
      emb = self.emb_layer(_input)
      emb = self.drop(emb)
  
      output = self.encoder(emb)
  
      output = self.drop(output)
      pred = self.linear(output)
      pred = self.out(pred)
  
      return pred
  
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 3 for calling the TextCNNTorchModel obj's underlying member method code with example usage: obj.forward(_input) and returns: pred