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spec : add self speculative decoding, ngram and refactor (#1261)
* spec : add self speculative decoding and ngram-mod and refactor common : use common_ prefix for common library function llama : use LLAMA_TOKEN_NULL spec : add self speculative decoding (no draft model required) + refactor spec : add ngram-mod spec : various improvements ton ngram-map + docs spec : fix the check-rate logic of ngram-simple common : add common_speculative_is_compat() spec : simplify time measurement using common_time_meas refactor common_sampler_init refactor common_token_to_piece refactor and fix cur_p bug clean up * spec : remove check rate * spec: show warnings instead of abort --------- Co-authored-by: firecoperana <firecoperana> Co-authored-by: Sascha Rogmann <59577610+srogmann@users.noreply.github.com>
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@@ -272,8 +272,8 @@ struct tokenized_prompt {
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tokenized_prompt(llama_context * ctx, std::string pos, std::string neg) {
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const bool add_bos = llama_should_add_bos_token(llama_get_model(ctx));
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tokens_pos = ::llama_tokenize(ctx, pos, add_bos, true);
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tokens_neg = ::llama_tokenize(ctx, neg, add_bos, true);
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tokens_pos = ::common_tokenize(ctx, pos, add_bos, true);
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tokens_neg = ::common_tokenize(ctx, neg, add_bos, true);
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max_seq_len = std::max(tokens_pos.size(), tokens_neg.size());
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padding_seq(ctx, tokens_pos, max_seq_len);
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padding_seq(ctx, tokens_neg, max_seq_len);
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@@ -281,7 +281,7 @@ struct tokenized_prompt {
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void padding_seq(llama_context * ctx, std::vector<llama_token> & tokens, size_t len) {
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// TODO: customize padding token
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std::vector<llama_token> pad_tokens = ::llama_tokenize(ctx, " ", false);
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std::vector<llama_token> pad_tokens = ::common_tokenize(ctx, " ", false);
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llama_token pad_tok = pad_tokens.back();
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while (tokens.size() < len) {
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tokens.push_back(pad_tok);
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