code: def __init__(self, m):
      self.pConv1 = m.add_parameters((5, 5, 1, 32))
      self.pB1 = m.add_parameters((32,))
      self.pConv2 = m.add_parameters((5, 5, 32, 64))
      self.pB2 = m.add_parameters((64,))
      self.pW1 = m.add_parameters((HIDDEN_DIM, 7 * 7 * 64))
      self.pB3 = m.add_parameters((HIDDEN_DIM,))
      self.pW2 = m.add_parameters((10, HIDDEN_DIM))
  
file_path: dynet/examples/mnist/basic-mnist-benchmarks/mnist_dynet_minibatch.py
imports: from __future__ import division
  import os
  import struct
  import argparse
  import random
  import time
  import numpy
  import dynet
label_desc: Use image node_id 1 to create a new mnist_network object from inherited base classes: object with example: obj = mnist_network(m)