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- # View more python tutorials on my Youtube and Youku channel!!!
- # Youtube video tutorial: https://www.youtube.com/channel/UCdyjiB5H8Pu7aDTNVXTTpcg
- # Youku video tutorial: http://i.youku.com/pythontutorial
- # 5 - theano.function
- """
- Please note, this code is only for python 3+. If you are using python 2+, please modify the code accordingly.
- """
- from __future__ import print_function
- import numpy as np
- import theano
- import theano.tensor as T
- # activation function example
- x = T.dmatrix('x')
- s = 1 / (1 + T.exp(-x)) # logistic or soft step
- logistic = theano.function([x], s)
- print(logistic([[0, 1],[-1, -2]]))
- # multiply outputs for a function
- a, b = T.dmatrices('a', 'b')
- diff = a - b
- abs_diff = abs(diff)
- diff_squared = diff ** 2
- f = theano.function([a, b], [diff, abs_diff, diff_squared])
- print( f(np.ones((2, 2)), np.arange(4).reshape((2, 2))) )
- # default value and name for a function
- x, y, w = T.dscalars('x', 'y', 'w')
- z = (x+y)*w
- f = theano.function([x,
- theano.In(y, value=1),
- theano.In(w, value=2, name='weights')],
- z)
- print(f(23, 2, weights=4))
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