Mercurial > pylearn

annotate algorithms/tests/test_regressor.py @ 532:34ee3aff3e8f

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Improved embedding word preprocessing.
author Joseph Turian <turian@gmail.com>
date Tue, 18 Nov 2008 02:57:50 -0500
parents 8fcd0f3d9a17
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Olivier Breuleux <breuleuo@iro.umontreal.ca>
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1
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2
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3 import models
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4 import theano
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5 import numpy
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6 import time
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8
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9 def test_train(mode = theano.Mode('c|py', 'fast_run')):
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10
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11 reg = models.BinRegressor(regularize = False)
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12
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13 model = reg.make(lr = 0.01,
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14 input_size = 100,
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15 mode = mode,
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16 seed = 10)
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17
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18 # data = [[0, 1, 0, 0, 1, 1, 1, 0, 1, 0]*10]*10
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19 # targets = [[1]]*10
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20 #data = numpy.random.rand(10, 100)
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21
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22 R = numpy.random.RandomState(100)
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23 t1 = time.time()
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24 for i in xrange(1001):
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25 data = R.random_integers(0, 1, size = (10, 100))
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26 targets = data[:, 6].reshape((10, 1))
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27 cost = model.update(data, targets)
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28 if i % 100 == 0:
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29 print i, '\t', cost, '\t', 1*(targets.T == model.classify(data).T)
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30 t2 = time.time()
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31 return t2 - t1
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32
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33 if __name__ == '__main__':
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34 print 'optimized:'
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35 t1 = test_train(theano.Mode('c|py', 'fast_run'))
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36 print 'time:',t1
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37 print
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38
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39 print 'not optimized:'
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40 t2 = test_train(theano.Mode('c|py', 'fast_compile'))
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41 print 'time:',t2
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42
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