Unsupervised Deep Learning in Python: Master Data Science and Machine Learning with Modern Neural Networks written in Python and Theano (Machine Learning in Python) by LazyProgrammer

Author:LazyProgrammer
Language: eng
Format: epub
Published: 2016-06-29T22:00:00+00:00

X_in = T.matrix('X_%s' % self.id)

X_hat = self.forward_output(X_in)

# attach it to the object so it can be used later

# must be sigmoidal because the output is also a sigmoid

H = T.nnet.sigmoid(X_in.dot(self.W) + self.bh)

self.hidden_op = theano.function(

inputs=[X_in],

outputs=H,

)

# cost = ((X_in - X_hat) * (X_in - X_hat)).sum() / N

cost = -(X_in * T.log(X_hat) + (1 - X_in) * T.log(1 - X_hat)).sum() / N

cost_op = theano.function(

inputs=[X_in],

outputs=cost,

)

updates = [

(p, p + mu*dp - learning_rate*T.grad(cost, p)) for p, dp in zip(self.params, self.dparams)

] + [

(dp, mu*dp - learning_rate*T.grad(cost, p)) for p, dp in zip(self.params, self.dparams)

]

train_op = theano.function(

inputs=[X_in],

updates=updates,

)

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