INNER CODE UNIT · Python

observations

taishi-i/nagisa · nagisa/model.py:112

        observations   = [w_ws*h+b_ws for h in bilstm_outputs]
        return observations


    def forward(self, observations):

        def log_sum_exp(scores):
            npval = scores.npvalue()
            argmax_score = np.argmax(npval)
            max_score_expr = dy.pick(scores, argmax_score)
            max_score_expr_broadcast = dy.concatenate([max_score_expr] * self.dim_output)
            return max_score_expr + dy.log(dy.sum_elems(dy.transpose(dy.exp(scores - max_score_expr_broadcast))))

        init_alphas = [-1e10] * self.dim_output
        init_alphas[self.sp_s] = 0
        for_expr = dy.inputVector(init_alphas)
        for obs in observations:
            alphas_t = []

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