INNER CODE UNIT · Python

init_alphas

taishi-i/nagisa · nagisa/model.py:125

        init_alphas = [-1e10] * self.dim_output
        init_alphas[self.sp_s] = 0
        for_expr = dy.inputVector(init_alphas)
        for obs in observations:
            alphas_t = []
            for next_tag in range(self.dim_output):
                obs_broadcast = dy.concatenate([dy.pick(obs, next_tag)] * self.dim_output)
                next_tag_expr = for_expr + self.trans[next_tag] + obs_broadcast
                alphas_t.append(log_sum_exp(next_tag_expr))
            for_expr = dy.concatenate(alphas_t)
        terminal_expr = for_expr + self.trans[self.sp_e]
        alpha = log_sum_exp(terminal_expr)
        return alpha


    def score_sentence(self, observations, tags):
        if not len(observations) == len(tags):
            raise AssertionError("len(observations) != len(tags)")

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