class_docstr: A convolutional neural network for text classification.
  
  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.out(output)
      return pred
  
imports: import json
  import os
  import torch
  from torch import nn
  from torch.nn import functional
  import textattack
  from textattack.model_args import TEXTATTACK_MODELS
  from textattack.models.helpers import GloveEmbeddingLayer
  from textattack.models.helpers.utils import load_cached_state_dict
  from textattack.shared import utils
label_desc: Use image node_id 5 for calling the WordCNNForClassification obj's underlying member method code with example usage: obj.forward(_input) and returns: pred