Introduce C-style API (#370)
* Major refactoring - introduce C-style API * Clean up * Add <cassert> * Add <iterator> * Add <algorithm> .... * Fix timing reporting and accumulation * Measure eval time only for single-token calls * Change llama_tokenize return meaningpull/380/head
Georgi Gerganov
1 year ago
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GitHub
parent
da0e9fe90c
commit
f5a77a629b
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#ifndef LLAMA_H
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#define LLAMA_H
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#include <stddef.h>
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#include <stdint.h>
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#include <stdbool.h>
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#ifdef LLAMA_SHARED
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# ifdef _WIN32
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# ifdef LLAMA_BUILD
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# define LLAMA_API __declspec(dllexport)
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# else
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# define LLAMA_API __declspec(dllimport)
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# endif
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# else
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# define LLAMA_API __attribute__ ((visibility ("default")))
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# endif
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#else
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# define LLAMA_API
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#endif
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#define LLAMA_FILE_VERSION 1
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#define LLAMA_FILE_MAGIC 0x67676d66 // 'ggmf' in hex
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#define LLAMA_FILE_MAGIC_UNVERSIONED 0x67676d6c // pre-versioned files
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#ifdef __cplusplus
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extern "C" {
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#endif
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//
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// C interface
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//
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// TODO: show sample usage
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//
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struct llama_context;
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typedef int llama_token;
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typedef struct llama_token_data {
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llama_token id; // token id
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float p; // probability of the token
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float plog; // log probability of the token
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} llama_token_data;
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struct llama_context_params {
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int n_ctx; // text context
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int n_parts; // -1 for default
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int seed; // RNG seed, 0 for random
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bool f16_kv; // use fp16 for KV cache
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bool logits_all; // the llama_eval() call computes all logits, not just the last one
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bool vocab_only; // only load the vocabulary, no weights
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};
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LLAMA_API struct llama_context_params llama_context_default_params();
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// Various functions for loading a ggml llama model.
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// Allocate (almost) all memory needed for the model.
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// Return NULL on failure
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LLAMA_API struct llama_context * llama_init_from_file(
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const char * path_model,
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struct llama_context_params params);
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// Frees all allocated memory
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LLAMA_API void llama_free(struct llama_context * ctx);
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// TODO: not great API - very likely to change
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// Returns 0 on success
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LLAMA_API int llama_model_quantize(
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const char * fname_inp,
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const char * fname_out,
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int itype,
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int qk);
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// Run the llama inference to obtain the logits and probabilities for the next token.
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// tokens + n_tokens is the provided batch of new tokens to process
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// n_past is the number of tokens to use from previous eval calls
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// Returns 0 on success
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LLAMA_API int llama_eval(
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struct llama_context * ctx,
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const llama_token * tokens,
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int n_tokens,
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int n_past,
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int n_threads);
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// Convert the provided text into tokens.
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// The tokens pointer must be large enough to hold the resulting tokens.
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// Returns the number of tokens on success, no more than n_max_tokens
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// Returns a negative number on failure - the number of tokens that would have been returned
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// TODO: not sure if correct
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LLAMA_API int llama_tokenize(
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struct llama_context * ctx,
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const char * text,
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llama_token * tokens,
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int n_max_tokens,
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bool add_bos);
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LLAMA_API int llama_n_vocab(struct llama_context * ctx);
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LLAMA_API int llama_n_ctx (struct llama_context * ctx);
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// Token logits obtained from the last call to llama_eval()
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// The logits for the last token are stored in the last row
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// Can be mutated in order to change the probabilities of the next token
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// Rows: n_tokens
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// Cols: n_vocab
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LLAMA_API float * llama_get_logits(struct llama_context * ctx);
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// Token Id -> String. Uses the vocabulary in the provided context
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LLAMA_API const char * llama_token_to_str(struct llama_context * ctx, llama_token token);
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// Special tokens
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LLAMA_API llama_token llama_token_bos();
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LLAMA_API llama_token llama_token_eos();
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// TODO: improve the last_n_tokens interface ?
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LLAMA_API llama_token llama_sample_top_p_top_k(
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llama_context * ctx,
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const llama_token * last_n_tokens_data,
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int last_n_tokens_size,
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int top_k,
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double top_p,
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double temp,
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double repeat_penalty);
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// Performance information
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LLAMA_API void llama_print_timings(struct llama_context * ctx);
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LLAMA_API void llama_reset_timings(struct llama_context * ctx);
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// Print system information
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LLAMA_API const char * llama_print_system_info(void);
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#ifdef __cplusplus
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}
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#endif
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#endif
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Binary file not shown.
@ -1,4 +1,4 @@
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set(TEST_TARGET test-tokenizer-0)
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add_executable(${TEST_TARGET} ${TEST_TARGET}.cpp)
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target_link_libraries(${TEST_TARGET} PRIVATE utils)
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target_link_libraries(${TEST_TARGET} PRIVATE llama ggml utils)
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add_test(NAME ${TEST_TARGET} COMMAND $<TARGET_FILE:${TEST_TARGET}> ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab.bin)
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