code: def __init__(self):
      super(MNIST_Classifier, self).__init__()
      self.conv1 = nn.Conv2d(1, 10, kernel_size=5)
      self.conv2 = nn.Conv2d(10, 20, kernel_size=5)
      self.conv2_drop = nn.Dropout2d()
      self.fc1 = nn.Linear(320, 50)
      self.fc2 = nn.Linear(50, 10)
  
imports: import json
  import os
  import pickle
  from collections import Counter, OrderedDict
  import numpy
  import torch
  import torch.nn
  import torch.nn.functional
  from gensim.models import FastText
  from nltk.tokenize import sent_tokenize, word_tokenize
  from scipy.linalg import eig
  from skimage.filters import threshold_yen
label_desc: Use image node_id 1 to create a new MNIST_Classifier object from inherited base classes: nn with example: obj = MNIST_Classifier()