Mercurial > pylearn

annotate sandbox/simple_autoassociator/graph.py @ 395:70019965f888

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Basic, broken RBM implementation
author Joseph Turian <turian@gmail.com>
date Tue, 08 Jul 2008 20:14:21 -0400
parents 36baeb7125a4
children 8cc11ac97087
rev   line source
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1 """
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2 Theano graph for a simple autoassociator.
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3 @todo: Make nearly everything private.
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4 """
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5
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6 from pylearn.nnet_ops import sigmoid, binary_crossentropy
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7 from theano import tensor as t
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8 from theano.tensor import dot
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9 x = t.dvector()
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10 w1 = t.dmatrix()
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11 b1 = t.dvector()
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12 w2 = t.dmatrix()
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13 b2 = t.dvector()
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14 h = sigmoid(dot(x, w1) + b1)
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15 y = sigmoid(dot(h, w2) + b2)
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16
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17 loss_unsummed = binary_crossentropy(y, x)
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18 loss = t.sum(loss_unsummed)
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19
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20 (gw1, gb1, gw2, gb2, gy) = t.grad(loss, [w1, b1, w2, b2, y])
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21
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22 import theano.compile
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23
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24 inputs = [x, w1, b1, w2, b2]
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25 outputs = [y, h, loss, loss_unsummed, gw1, gb1, gw2, gb2, gy]
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26 trainfn = theano.compile.function(inputs, outputs)