Ejemplo n.º 1
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 def sample_from_activation(self, vmap):
     p0 = self.probabilities_from_activation(vmap)
     s0 = samplers.multinomial(p0)
     s = s0[:, :, :-1] # chop off the last state (zero state)
     return s
Ejemplo n.º 2
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 def sample_from_activation(self, vmap):
     p0 = self.probabilities_from_activation(vmap)
     s0 = samplers.multinomial(p0)
     s = s0[:, :, :-1]  # chop off the last state (zero state)
     return s
Ejemplo n.º 3
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 def sample_from_activation(self, vmap):
     p = self.probabilities_from_activation(vmap)
     return samplers.multinomial(p)
Ejemplo n.º 4
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 def sample_from_activation(self, vmap):
     p = self.probabilities_from_activation(vmap)
     return samplers.multinomial(p)
Ejemplo n.º 5
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 def sample_from_activation(self, vmap):
     p0 = activation_functions.softmax_with_zero(vmap[self])
     s0 = samplers.multinomial(p0)
     s = s0[:, :, :-1]  # chop off the last state (zero state)
     return s
Ejemplo n.º 6
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 def sample_from_activation(self, vmap):
     p = activation_functions.softmax(vmap[self])
     return samplers.multinomial(p)
Ejemplo n.º 7
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 def sample_from_activation(self, vmap):
     p0 = activation_functions.softmax_with_zero(vmap[self])
     s0 = samplers.multinomial(p0)
     s = s0[:, :, :-1]  # chop off the last state (zero state)
     return s
Ejemplo n.º 8
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 def sample_from_activation(self, vmap):
     p = activation_functions.softmax(vmap[self])
     return samplers.multinomial(p)