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1
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2 import theano
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3 from theano import tensor, scalar
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4 import numpy
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5
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6 class XlogX(scalar.UnaryScalarOp):
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7 """
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8 Compute X * log(X), with special case 0 log(0) = 0.
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9 """
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10 @staticmethod
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11 def st_impl(x):
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12 if x == 0.0:
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13 return 0.0
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14 return x * numpy.log(x)
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15 def impl(self, x):
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16 return XlogX.st_impl(x)
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17 def grad(self, (x,), (gz,)):
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18 return [gz * (1 + scalar.log(x))]
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19 def c_code(self, node, name, (x,), (z,), sub):
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20 if node.inputs[0].type in [scalar.float32, scalar.float64]:
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21 return """%(z)s =
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22 %(x)s == 0.0
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23 ? 0.0
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24 : %(x)s * log(%(x)s);""" % locals()
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25 raise NotImplementedError('only floatingpoint is implemented')
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26 scalar_xlogx = XlogX(scalar.upgrade_to_float, name='scalar_xlogx')
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27 xlogx = tensor.Elemwise(scalar_xlogx, name='xlogx')
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28
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