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speculative : add --draft-min CLI arg
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@ -609,7 +609,14 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
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[](common_params & params, int value) {
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params.n_draft = value;
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}
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).set_examples({LLAMA_EXAMPLE_SPECULATIVE, LLAMA_EXAMPLE_LOOKUP}));
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).set_examples({LLAMA_EXAMPLE_SPECULATIVE, LLAMA_EXAMPLE_LOOKUP, LLAMA_EXAMPLE_SERVER}));
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add_opt(common_arg(
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{"--draft-min"}, "N",
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string_format("minimum number of draft tokens to use for speculative decoding (default: %d)", params.n_draft_min),
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[](common_params & params, int value) {
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params.n_draft_min = value;
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}
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).set_examples({LLAMA_EXAMPLE_SPECULATIVE, LLAMA_EXAMPLE_LOOKUP, LLAMA_EXAMPLE_SERVER}));
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add_opt(common_arg(
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{"-ps", "--p-split"}, "N",
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string_format("speculative decoding split probability (default: %.1f)", (double)params.p_split),
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@ -1454,7 +1461,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
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fprintf(stderr, "warning: see main README.md for information on enabling GPU BLAS support\n");
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}
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}
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).set_examples({LLAMA_EXAMPLE_SPECULATIVE}));
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).set_examples({LLAMA_EXAMPLE_SPECULATIVE, LLAMA_EXAMPLE_SERVER}));
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add_opt(common_arg(
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{"-sm", "--split-mode"}, "{none,layer,row}",
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"how to split the model across multiple GPUs, one of:\n"
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@ -1599,7 +1606,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
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[](common_params & params, const std::string & value) {
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params.model_draft = value;
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}
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).set_examples({LLAMA_EXAMPLE_SPECULATIVE}));
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).set_examples({LLAMA_EXAMPLE_SPECULATIVE, LLAMA_EXAMPLE_SERVER}));
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add_opt(common_arg(
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{"-mu", "--model-url"}, "MODEL_URL",
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"model download url (default: unused)",
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@ -162,6 +162,7 @@ struct common_params {
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int32_t n_ubatch = 512; // physical batch size for prompt processing (must be >=32 to use BLAS)
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int32_t n_keep = 0; // number of tokens to keep from initial prompt
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int32_t n_draft = 5; // number of tokens to draft during speculative decoding
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int32_t n_draft_min = 0; // minimum number of draft tokens to use for speculative decoding
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int32_t n_chunks = -1; // max number of chunks to process (-1 = unlimited)
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int32_t n_parallel = 1; // number of parallel sequences to decode
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int32_t n_sequences = 1; // number of sequences to decode
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@ -13,9 +13,6 @@
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int main(int argc, char ** argv) {
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common_params params;
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// minimum size of the draft to use
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const int n_min = 5;
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if (!common_params_parse(argc, argv, params, LLAMA_EXAMPLE_SPECULATIVE)) {
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return 1;
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}
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@ -142,7 +139,7 @@ int main(int argc, char ** argv) {
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// evaluate the target model on [id_last, draft0, draft1, ..., draftN-1]
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{
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// do not waste time on small drafts
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if (draft.size() < n_min) {
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if (draft.size() < params.n_draft_min) {
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draft.clear();
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}
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