old_contents: import numpy as np
  import theano
  import theano.tensor as T
new_contents: import numpy as np
  import theano
  import theano.tensor as T
  
  
  class NeuralNetwork(object):
  
      def __init__(self, layers, miniBatchSize):
  		self.miniBatchSize = miniBatchSize
  		#Initialize layers.
  		self.layers = layers
  		self.numLayers = len(self.layers)
  		self.firstLayer = self.layers[0]
  		self.lastLayer = self.layers[-1]
  		#Populate self.learningParams with a complete list of weights and biases from all layers.
  		self.learningParams = []
  		for layer in self.layers:
  			for param in layer.learningParams:
  				self.learningParams.append(param)
  		#Connect each layer's input to the previous layer's output.
  		for i in xrange(1, self.numLayers):
  			nextLayer = layers[i]
  			previousLayer = layers[i-1]
  			nextLayer.input = previousLayer.output
subject: Add first code for NeuralNetwork class.