Mercurial > pylearn
comparison simple_autoassociator/graph.py @ 392:e2cb8d489908
More debugging
author | Joseph Turian <turian@gmail.com> |
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date | Tue, 08 Jul 2008 18:45:35 -0400 |
parents | ec8aadb6694d |
children |
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389:ec8aadb6694d | 392:e2cb8d489908 |
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15 y = sigmoid(dot(h, w2) + b2) | 15 y = sigmoid(dot(h, w2) + b2) |
16 | 16 |
17 loss_unsummed = binary_crossentropy(y, x) | 17 loss_unsummed = binary_crossentropy(y, x) |
18 loss = t.sum(loss_unsummed) | 18 loss = t.sum(loss_unsummed) |
19 | 19 |
20 (gw1, gb1, gw2, gb2) = t.grad(loss, [w1, b1, w2, b2]) | 20 (gw1, gb1, gw2, gb2, gy) = t.grad(loss, [w1, b1, w2, b2, y]) |
21 | 21 |
22 import theano.compile | 22 import theano.compile |
23 | 23 |
24 inputs = [x, w1, b1, w2, b2] | 24 inputs = [x, w1, b1, w2, b2] |
25 outputs = [y, h, loss, loss_unsummed, gw1, gb1, gw2, gb2] | 25 outputs = [y, h, loss, loss_unsummed, gw1, gb1, gw2, gb2, gy] |
26 trainfn = theano.compile.function(inputs, outputs) | 26 trainfn = theano.compile.function(inputs, outputs) |