Function common_sampler_sample

smallthinker/common/sampling.cpp:338–382

}

llama_token common_sampler_sample(struct common_sampler * gsmpl, struct llama_context * ctx, int idx, bool grammar_first) {
    gsmpl->set_logits(ctx, idx);

    auto & grmr  = gsmpl->grmr;
    auto & chain = gsmpl->chain;
    auto & cur_p = gsmpl->cur_p; // initialized by set_logits

    if (grammar_first) {
        llama_sampler_apply(grmr, &cur_p);
    }

    llama_sampler_apply(chain, &cur_p);

    GGML_ASSERT(cur_p.selected != -1 && "no selected token during sampling - check your sampling configuration");

    const llama_token id = cur_p.data[cur_p.selected].id;

    if (grammar_first) {
        return id;
    }

    // check if it the sampled token fits the grammar
    {
        llama_token_data       single_token_data       = { id, 1.0f, 0.0f };
        llama_token_data_array single_token_data_array = { &single_token_data, 1, -1, false };

        llama_sampler_apply(grmr, &single_token_data_array);

        const bool is_valid = single_token_data_array.data[0].logit != -INFINITY;
        if (is_valid) {
            return id;
        }
    }

    // resampling:
    // if the token is not valid, sample again, but first apply the grammar sampler and then the sampling chain
    gsmpl->set_logits(ctx, idx);

    llama_sampler_apply(grmr,  &cur_p);
    llama_sampler_apply(chain, &cur_p);

    GGML_ASSERT(cur_p.selected != -1 && "no selected token during re-sampling - check your sampling configuration");

    return cur_p.data[cur_p.selected].id;
}

std::vector<llama_token> common_sampler_sample_and_accept_n(struct common_sampler * gsmpl, struct llama_context * ctx, const std::vector<int> & idxs, const llama_tokens & draft, bool grammar_first) {
    GGML_ASSERT(idxs.size() == draft.size() + 1 && "idxs.size() must be draft.size() + 1");