Пример #1
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 def sample_from_activation(self, vmap):
     mu = self.mean_from_activation(vmap)
     sigma2 = self.variance_from_activation(vmap)
     return samplers.gaussian(mu, sigma2)
Пример #2
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 def sample_from_activation(self, vmap):
     s = vmap[self] + samplers.gaussian(0, T.nnet.sigmoid(vmap[self])) # approximation: linear + gaussian noise
     return T.max(0, s) # rectify
Пример #3
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 def sample_from_activation(self, vmap):
     mu = self.mean_from_activation(vmap)
     return samplers.gaussian(mu)
Пример #4
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 def sample_from_activation(self, vmap):
     s = vmap[self] + samplers.gaussian(0, T.nnet.sigmoid(
         vmap[self]))  # approximation: linear + gaussian noise
     return T.max(0, s)  # rectify
Пример #5
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 def sample_from_activation(self, vmap):
     mu = self.mean_from_activation(vmap)
     return samplers.gaussian(mu)
Пример #6
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 def sample_from_activation(self, vmap):
     mu = self.mean_from_activation(vmap)
     sigma2 = self.variance_from_activation(vmap)
     return samplers.gaussian(mu, sigma2)
Пример #7
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 def sample_from_activation(self, vmap):
     a1 = vmap[self]
     a2 = vmap[self.precision_units]
     return samplers.gaussian(a1 / (-2 * a2), 1 / (-2 * a2))
Пример #8
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 def sample_from_activation(self, vmap):
     return samplers.gaussian(vmap[self])
Пример #9
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 def sample_from_activation(self, vmap):
     a1 = vmap[self]
     a2 = vmap[self.precision_units]
     return samplers.gaussian(a1 / (-2 * a2), 1 / (-2 * a2))
Пример #10
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 def sample_from_activation(self, vmap):
     return samplers.gaussian(vmap[self])