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annotate algorithms/sgd.py @ 496:f13847478c6d

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A few more ideas, in comments
author Joseph Turian <turian@gmail.com>
date Tue, 28 Oct 2008 12:09:49 -0400
parents fbfd3932fd00
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2 from theano.compile import module
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3 from theano import tensor as T
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5 class StochasticGradientDescent(module.FancyModule):
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6 def __init__(self, params, gparams, lr=None):
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7 super(StochasticGradientDescent, self).__init__()
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9 self.lr = lr if lr is not None else module.Member(T.dscalar())
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10 self.params = params
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11 self.gparams = gparams
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13 self.updates = dict((p, p - self.lr * g) for p, g in zip(self.params, self.gparams))
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