llama : add classifier-free guidance (#2135)
* Initial implementation * Remove debug print * Restore signature of llama_init_from_gpt_params * Free guidance context * Make freeing of guidance_ctx conditional * Make Classifier-Free Guidance a sampling function * Correct typo. CFG already means context-free grammar. * Record sampling time in llama_sample_classifier_free_guidance * Shift all values by the max value before applying logsoftmax * Fix styling based on review
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5 changed files with 188 additions and 5 deletions
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@ -236,6 +236,24 @@ bool gpt_params_parse(int argc, char ** argv, gpt_params & params) {
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break;
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}
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params.mirostat_tau = std::stof(argv[i]);
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} else if (arg == "--cfg-negative-prompt") {
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if (++i >= argc) {
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invalid_param = true;
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break;
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}
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params.cfg_negative_prompt = argv[i];
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} else if (arg == "--cfg-scale") {
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if (++i >= argc) {
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invalid_param = true;
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break;
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}
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params.cfg_scale = std::stof(argv[i]);
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} else if (arg == "--cfg-smooth-factor") {
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if (++i >= argc) {
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invalid_param = true;
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break;
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}
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params.cfg_smooth_factor = std::stof(argv[i]);
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} else if (arg == "-b" || arg == "--batch-size") {
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if (++i >= argc) {
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invalid_param = true;
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@ -469,6 +487,10 @@ void gpt_print_usage(int /*argc*/, char ** argv, const gpt_params & params) {
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fprintf(stderr, " modifies the likelihood of token appearing in the completion,\n");
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fprintf(stderr, " i.e. `--logit-bias 15043+1` to increase likelihood of token ' Hello',\n");
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fprintf(stderr, " or `--logit-bias 15043-1` to decrease likelihood of token ' Hello'\n");
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fprintf(stderr, " --cfg-negative-prompt PROMPT \n");
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fprintf(stderr, " negative prompt to use for guidance. (default: empty)\n");
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fprintf(stderr, " --cfg-scale N strength of guidance (default: %f, 1.0 = disable)\n", params.cfg_scale);
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fprintf(stderr, " --cfg-smooth-factor N smooth factor between old and new logits (default: %f, 1.0 = no smoothing)\n", params.cfg_smooth_factor);
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fprintf(stderr, " -c N, --ctx-size N size of the prompt context (default: %d)\n", params.n_ctx);
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fprintf(stderr, " --ignore-eos ignore end of stream token and continue generating (implies --logit-bias 2-inf)\n");
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fprintf(stderr, " --no-penalize-nl do not penalize newline token\n");
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@ -535,7 +557,7 @@ std::vector<llama_token> llama_tokenize(struct llama_context * ctx, const std::s
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return res;
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}
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std::tuple<struct llama_model *, struct llama_context *> llama_init_from_gpt_params(const gpt_params & params) {
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struct llama_context_params llama_context_params_from_gpt_params(const gpt_params & params) {
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auto lparams = llama_context_default_params();
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lparams.n_ctx = params.n_ctx;
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@ -551,6 +573,12 @@ std::tuple<struct llama_model *, struct llama_context *> llama_init_from_gpt_par
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lparams.logits_all = params.perplexity;
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lparams.embedding = params.embedding;
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return lparams;
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}
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std::tuple<struct llama_model *, struct llama_context *> llama_init_from_gpt_params(const gpt_params & params) {
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auto lparams = llama_context_params_from_gpt_params(params);
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llama_model * model = llama_load_model_from_file(params.model.c_str(), lparams);
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if (model == NULL) {
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fprintf(stderr, "%s: error: failed to load model '%s'\n", __func__, params.model.c_str());
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