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 load_from_disk(self, model_path):
      self.load_state_dict(load_cached_state_dict(model_path))
      self.to(device)
      self.eval()
  
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 TextCNNTorchModel obj's underlying member method code with example usage: obj.load_from_disk(model_path) without return types