title: How to find the output of convolutional_mlp of Theano tutorial based on python
body: <p>I have 10000 images fed to CNN in Theano tutorial described <a href="https://github.com/lisa-lab/DeepLearningTutorials" rel="nofollow">here</a>.</p>
  
  <p>In the classification step, I want to classify those images into 40 classes. So, the number of units in the last layer would be 40. I want to get the predicted value from there. Layer3 calls 'LogisticRegression' function that is available in this package. I think CNN goes to   'LogisticRegression' function to evaluate the predicted values. How can I access to these value?<br>
  The info related to layers are:</p>
  
  <pre><code> layer1 = LeNetConvPoolLayer(
      rng,
      input=layer0.output,
      image_shape=(batch_size, nkerns[0], 12, 12),
      filter_shape=(nkerns[1], nkerns[0], 5, 5),
      poolsize=(2, 2)
  )
  
  # the HiddenLayer being fully-connected, it operates on 2D matrices of
  # shape (batch_size, num_pixels) (i.e matrix of rasterized images).
  # This will generate a matrix of shape (batch_size, nkerns[1] * 4 * 4),
  # or (500, 50 * 4 * 4) = (500, 800) with the default values.
  layer2_input = layer1.output.flatten(2)
  
  # construct a fully-connected sigmoidal layer
  layer2 = HiddenLayer(
      rng,
      input=layer2_input,
      n_in=nkerns[1] * 4 * 4,
      n_out=500,
      activation=T.tanh
  )
  
  # classify the values of the fully-connected sigmoidal layer
  layer3 = LogisticRegression(input=layer2.output, n_in=500, n_out=40)
  </code></pre>
  
  <p>I think, if we could get output from 'layer3', it would be great. I want this value, because I want to count how many samples in each class have been predicted accurately.
  Is there any body to help</p>