code: def __init__(self, m):
      if args.conv:
          # architecture from https://www.tensorflow.org/get_started/mnist/pros
          self.F1 = m.add_parameters((5, 5, 1, 32))
          self.b1 = m.add_parameters((32,))
          self.F2 = m.add_parameters((5, 5, 32, 64))
          self.b2 = m.add_parameters((64,))
          input_size = 7 * 7 * 64
      else:
          input_size = 28 * 28
      self.W1 = m.add_parameters((HIDDEN_DIM, input_size))
      self.hbias = m.add_parameters((HIDDEN_DIM,))
      self.W2 = m.add_parameters((10, HIDDEN_DIM))
  
file_path: dynet/examples/mnist/mnist-autobatch.py
imports: import time
  import random
  import os
  import struct
  import argparse
  import numpy
  import dynet
label_desc: Use image node_id 1 to create a new MNISTClassify object from inherited base classes: object with example: obj = MNISTClassify(m)