neuralSearch.py 文件源码

def sample(self, seed, maximumLength, T = 1):
        h = self.h0(seed).view(self.layers, 1, self.H)

        accumulator = ["START"]
        for _ in range(maximumLength):
            i = self.targetsOfSymbols([accumulator[-1]])[:,0]
            output, h = self(i,h)
            distribution = output.data.view(-1)/T
            distribution = F.log_softmax(distribution).data
            distribution = distribution.exp()

            c = torch.multinomial(distribution,1)[0]
            if self.lexicon[c] == "END": break

            accumulator.append(self.lexicon[c])

        return accumulator[1:]